Genomic Connections – iBOL Europe

Genomic Connection #7 – Bringing data to life: Biodiversity genomics applications

Kasia Fantoni — Fri, 12 Dec 2025 09:23:00 +0000

In the seventh – and last! – episode of Genomic Connections, Kasia and Christian talk with Brent Emerson and José Melo-Ferreira about the many applications of genomic data and how their work brings genomic data into action to solve real-world problems.

Brent leads the Research Group on Ecology and Evolution on Islands, an initiative within the Institute of Natural Products and Agrobiology and the Spanish National Research Council in Tenerife (IPNA CSIC). His team uses genetic and genomic tools to understand what structures diversity. The community led by Brent focuses on the use of DNA barcodes to characterise species assemblages at scale and the genetic connectivity among species across different ecosystems.
José is the Leader of the Genomics of Evolutionary Change research group at CIBIO-BIOPOLIS, based at CIBIO-InBIO, the Research Centre on Biodiversity and Genetic Resources of Portugal, where he is also an Assistant Professor at the University of Porto. His team uses genomic tools to understand fundamental evolutionary processes in different species. José is particularly interested in using genomics to support the conservation and management of biodiversity and to understand the impact of anthropogenic change on species’ adaptive potential.

We already talked about Biodiversity Genomics Applications in this blog post.

You can listen to Genomic Connections on Spotify and PocketCast. The RSS Feed is available here.

The episode’s full Transcript (AI-generated) is available below the credits.

Credits

“Genomic Connections” is a podcast about the science, stories, and people behind biodiversity genomics produced by ⁠⁠ERGA⁠⁠⁠⁠ and ⁠⁠⁠⁠iBOL Europe⁠⁠⁠⁠ within the ⁠⁠⁠Biodiversity Genomics Europe (BGE) project⁠⁠⁠.

“Genomic Connections” is written and produced by Christian de Guttry, Kasia Fantoni, Luísa Marins, and Chiara Bortoluzzi.

Graphic design by Luísa Marins.

BGE is a Horizon Europe project funded by the European Commission, the Swiss Confederation and the United Kingdom.

The episode is licensed under a CC-BY 4.0 license.

You can listen to Genomic Connections on Spotify and PocketCast.

Episode #7 Transcript

Hi Kasia, how are you today? Hi Chris, very nice, thank you. So today is a bit special, I think, because it’s the last episode of Genomic Connections, at least of this season. Are you sad about it? Yes, of course.

I got very close to our speakers and to our episodes, so yes, I’m a bit nostalgic already. Yeah, we got to know many different people from our communities. What do you want to talk about today? We went through all of the specifics and technical stuff that happens in biodiversity genomics, but then how do people really use these tools and these methods and this data in real life? So I would say we should talk about applications of biodiversity genomics.

Yeah, I definitely agree. I think this is a bit of a black box for many of us, but honestly how society uses the information that we provide is a central point also for the discipline in the future. Especially nowadays where biodiversity genomics is getting more and more used by NGOs, by governments, or also by the managers of a natural park.

So, let’s start our discussion. Who would you pick in your community? I would call Brent Emerson, who is the work package leader of barcode application within BG, who leads the research group on ecology and evolution on islands, an initiative within the Institute of Natural Products and Agrobiology and the Spanish National Research Council based in Tenerife. His research uses genetic and genomic tools to understand what structures diversity and especially focusses on the use of DNA barcodes to characterise species assemblages.

And you? I go for José Melo Ferreira, the leader of the Genomics of Evolutionary Change research group at CBO Biopolis, based at CBO in Bio, the research centre on biodiversity and genetic resources of Portugal. He is also an assistant professor at the University of Porto. His team uses genomics tools to understand fundamental evolutionary processes.

And José is particularly interested in using genomics for the conservation and management of biodiversity and to understand the impact of anthropogenic change on the adaptive potential of species. He is also the leader of BG genome application work package. Brent, José, welcome.

OK, welcome, everybody. Let’s try to warm up in one sentence each. So what’s the single most useful thing your data deliver? Eyeball clearly with barcodes and erga with reference genomes and genomic data.

OK, I guess the most useful thing we deliver is taxonomic data that’s in a universal format that can be accessed anywhere, anytime in the world. So taxonomy is a very specialised skill to identify material, especially in sick material. It’s a very complicated process.

So we can actually make all the taxonomic information available without the difficulty of being a taxonomist. So really, it’s like making the most of the limited taxonomic resources we have. And so the DNA sequence associated with the species is a universal language, if you like, or a piece of information that even if you’re not, it doesn’t matter what language you might speak.

As soon as you access a sequence with the name associated with it, you can use it. Yeah, that’s brilliant. And you, José, from the erga side? Yeah, well, when we have access to complete information about the genomes of a given species, we have access to its history, its evolutionary history.

And so everything is very useful for conservation and management, like estimates of genetic diversity, population connectivity in breeding. But I can mention in the single sentence you requested, the thing that fascinates me, and it’s also very important for conservation management, which is to have access to adaptive genetic variation, meaning that we can, analysing the genomes of individuals of a certain species, we can identify local adaptations, so understand what are the genes or the portions of the genome that are important for local adaptation of a certain population. And sometimes that’s not very evident only by looking at morphology.

And so we can have this access to history that gives us the makeup of a biological species. Yeah, thank you so much. So the entire picture.

So basically, eyeball and erga, you can have the entire picture of a species with morphology, taxonomy, and then reference genomes. Let’s say that eyeball, you’re the neighbourhood watching who’s here now, while erga, you’re the forensic lab and understanding how it’s doing and why. Can you give us an example where that partnership shifted an actual decision on the ground? So I think that’s a great image of what the power of eyeball perspective with barcodes and erga perspective with genomics, where with barcodes, you can identify what exists in a certain place.

And then with the genomes, we can understand why it’s there, when it went there, and all the history that is involved in the establishment of the species in a certain place. And so these two dimensions are very complementary and actually work together to deliver very meaningful information. There are plenty of examples that certainly Brent will mention a few also later, but I can mention, for example, the cases of invasive mosquitoes that are vectors of important diseases that affect humans, like dengue virus or the West Nile virus, and barcode-based approaches like, for example, using eDNA, which is the possibility of analysing the DNA that is present in a certain, for example, water sample.

We can identify the presence of a certain mosquito, for example. We can identify changes in the ranges of this species. And then with genomics, we can understand why this, for example, range changes is occurring.

If there is any genetic basis, for example, the Asian tiger mosquito is now invading north in Europe. And genomics can understand exactly why, if it’s being, if it’s adapting to these northernmost regions in terms of overwintering strategies. Also, an important thing that genomics can do is identify the basis of resistance to insecticides, for example, some types of insecticides.

And this has been used actually already for monitoring these variants that confer insecticide resistance and that locally can be used to change the strategy for the control, for example, change the type of insecticide, knowing that there is a certain resistance to a certain product that has been developing in a certain population. So that’s a simple example where these two perspectives of barcoding and genomics can work together for actual management decisions on the ground. Yeah, I could probably add another practical example here.

So like DNA barcoding, use it to distinguish different species. And that can be a really useful tool when we have legal harvesting of materials, for example, wood. Now, this tree can be harvested, that tree can’t.

OK, we can easily follow up and understand whether it’s been harvested, belongs to the right or the wrong species. But sometimes species are so closely related that becomes a very difficult or impossible task with standard DNA barcoding. So, for example, with rosewood trees in Madagascar.

Now, with a whole genome of any of the rosewood species, we can then use genome skimming to identify those species that we can’t distinguish with a standard barcode. Now, it might sound like you’re smashing a walnut with a sledgehammer using whole genome skim data, but it’s actually not. It turns out to be probably more cost effective and quicker than many other approaches.

And when we’re dealing with little bits of wood that have been processed, you know, it has to be a DNA based approach. So, I mean, so this is kind of this coming together of the two approaches, barcoding and genomics, is something that we’re trying to catalyse now in the Biodiversity Genomics Europe project. And so these examples, hopefully they will be really one of many examples in five years time rather than highlights right now.

You were talking about monitoring and monitoring at scale can feel like counting the raindrops when it’s raining. So could you name one policy or management decision that only happened because barcodes turned an unclear, shady picture into something decision ready? Yeah, sure. I could probably give you a real world example.

It’s not where a policy decision has been effected yet. It’s where it’s in process, if you like. So here in the Canary Islands, you know, we have a very rich fauna of invertebrates in terms of endemic species.

And so the other ones that we value, the natives and the endemics, and the introduced species are the ones we’re more worried about. Now, we have a great database that lists all species and their status as introduced or native, and that helps us with management strategy. Now, with our barcoding work here, we’re finding that many of the species that have been believed to be natives are actually introduced.

So we have to shift them from this bucket of species we’re interested in protecting to this bucket, which is species we should be watching for. So that’s been a fairly straightforward exercise. Get a specimen here, sequence it, and then look to see what’s similar to that sequence globally.

And if you find that that same sequence or something very similar is also found in Germany, in Poland and the UK, it’s very clear that it’s been here a very little amount of time and is a human introduced. So that reshapes the management landscape here for invertebrates. And on the erga side, conservation in practise.

When did our reference genome, together with population genomic data, move a species from we’re concerned to this is the plan? Which metric actually defined the genetic diversity in breeding adaptive variants? Yeah, fortunately, I think that we’re at a stage in the development of the field of genomics where this example starts accumulating and that’s I think it’s an excellent sign for the strategies for conservation. There’s, for example, the example of the kakapo, which is a flightless parrot in New Zealand, that is actually the world’s only flightless parrot and the heaviest parrot that exists. And this species is critically endangered so the total population living is a couple hundred individuals.

And actually with chromosome level reference genome plus resequencing data, meaning adding genomic data at the population level, it has been used for strategies to restore and recover this population. For example, using metrics like runs of homozygosity, which is a metric of inbreeding of if the population is very little, has very little genetic diversity, then this metric gives us an idea of this little diversity. And this can anchor translocation strategies and things like that, making pair recommendations.

It can be used to analyse, for example, immune gene diversity, which is really important to understand the potential for the populations to persist. I could talk about the example of the California condor, but I want actually to touch on an example that is here from the Iberian Peninsula, which is the Iberian lynx. And so the Iberian lynx was on the brink of extinction early this century and there was a major and important recovery programme for the recovery and conservation of the Iberian lynx.

And so this started early in the century and essentially accompanied all the development of genomics and I think it’s an excellent example of how the progress that the technological analytical capacities that we’ve been developing in genomics has been uptaken by this programme along the way. And now towards the existence of first the draft and our high quality reference genome. And this has been used, I can give several examples first to understand the evolutionary history of the, of the, of the species, and importantly the demographic history meaning in the past what was the effective population size the sizes of the populations that were able to maintain diversity to create to understand the baselines of this natural diversity for for conservation, but then also to understand and quantify genomic erosion, erosion we call it when when diversity is being lost, and this leads also in very small populations to the accumulation of variants of mutations that are deleterious meaning bad that cause problems.

And so to quantify this, this fitness implications of this genomic erosion, and then in also to, to, to guide the captive breeding programme to select individuals that are more diverse that are more suitable to be reintroduced in nature to guide the translocations and introductions and, and also to to, there has been also a change in a way that these populations can be then monitored by shifting from the use of a small amount of markers in the genome to do this monitoring to larger sets of markers that are much more informative about the provenance diversity of the individuals. So I think this is a, an example that where the progress of genomics and now with reference genomes with the greatest power to to do this inferences that has really helped the to bring this species back and from a critically endangered situation to a vulnerable situation which is an important progress, but this, this can also be used so these situations where we have this is a problem, and this is how we solve it. Often this is the problem is really critical is something that is disappearing and we want to, to, to restore it and conserve it.

But this can also be using situations where, where we can identify. This is not a problem yet but this will be a problem for example if we identify situations of adaptations that will be impacted or are being impacted by climate change. We can predict the trajectories of these, these populations take into account this adaptive variation.

And so actually be preemptive, meaning, before we have a problem, we already know that we may have a problem and we can target measures to devise target measures to solve it in the future. Okay, let’s try now to make a budget test. So if a random authority hands you 100k, 100,000 euro.

Eyeball, do you spend it more on barcoding sites and for Erga on fever but deeper genomes plus population genomic data. These are just two ideas but you can give us your shopping list. I’ll start, I’ll spend it on neither of those two things I would, I would use it.

So what we lack I mean more data. We need to understand the data we have before we get to more data and what we find is a bottleneck is understanding the sequences you obtain and what species they belong to. So I would I would definitely invest that money in forging taxonomic collaborations so that we can have better curated reference libraries for the Canary Islands.

I would use it to to apply techniques that have been developed within the biodiversity genomics Europe project to obtain sequence data from museum material so we can use, we can basically take advantage of the taxonomic history that we have, and the hard work that many taxonomics have invested. And we can, we can make that universal and so I’d be wanting to obtain material well identified from the Canary Islands from different collections across Europe and obtaining barcode reference sequences and that way we can clearly identify what we have and where it is right now, maybe 30 or 40% of our sample material we can identify taxonomically there’s a vast amount that needs. We need to know what that species belongs to so that’s that’s pretty much where I spend that money, and it would be a wise investment for sure.

What about you, Joseph. Well, it really depends on what already exists. For example, if, if we identify a problem that we need to solve for for a certain species.

Sometimes genomics is incremental so there are several studies that produce genomic data, sometimes a reference genome already exists and so this changes the strategy that I would follow. If nothing exists at all. I would definitely start by generating a high quality reference genome to have a baseline for the follow up genomic analysis that that we can we can do.

And this is actually the strategy that we’re doing in the biodiversity genomics Europe project, where we have case studies for applications where we, the different types of projects that are involved there, where we generate population level sequencing data to anchor analysis on a reference genome, so that the inferences that that we can we can make are more complete and then this can be crafted to the different objectives of each problem. If it’s a problem of low effective population size and understanding of connectivity. If it’s a problem where understanding adaptation can be can be important.

If we want to use all genomes to, for example, monitor genetic diversity through time. It really depends on the on the specifics, but I would definitely in terms of strategy for genomics use generate the first high quality reference genome, and then population level data of all genomes to to to tackle in depth is is this problem or and find the best solution and management and conservation strategies, depending on the objective of the of the study. What if we talked about bioeconomy.

So, for Ergem, one way that genomes and genomic data make industries smarter, you can think of resilience, breeding, innovation, we already talked a bit about some of those. Yeah, for for genomics there are also numerous examples from, I think the one obvious is livestock breeding right where genomic profiling can help select animals that had better disease resistance faster growth depending on the production that that is being done. But I think one one very interesting example is for fish stock management.

And that’s actually covered also by a case study in the biodiversity genomics your project. And so, the, the fisheries is an important activity in the world and sustainable fishery is is important to to develop and genomics and can really help to understand because sometimes neutral genetic variation or genetic variation that can be identified with with a few markers show very little structure in the end of this fish populations, but with genomics and and anchored on reference genomes shallow structure can be identified sometimes related with with some adaptive variants that exists in some in some regions, and this has actually been used to develop a snapshot so essays that can be used to to monitor the origin of the of the fish that are fish and understand in this way, manage the, the, the way that that fish are being harvested.

(Transcribed by TurboScribe.ai. Go Unlimited to remove this message.)

and devise this continuous monitoring and management strategies to control and ensure the sustainability of this important economic activity. And for the AIVOL side, so Brent, can you tell us one way that barcodes clean up supply chains like traceability, fraud or miscandling? Yeah, sure. I mean, there’s a lot of examples.

I think we’re going to go back to what one of the first ones that ever came out. This was before it was even called barcoding, and this was a study that came out in 1994. It was based on the fact that we knew, or the world knew, that there’s a lot of illegal harvesting of whales for commercial purposes, particularly in Japan.

So this group from New Zealand, at least one of the authors was from New Zealand, they took small laboratory equipment with them into Japan, set up little PCR labs in hotel rooms, went around restaurants, harvested what was allegedly legally harvested minke whale meat, and then PCR amplified it and sequenced it and referenced that against known species sequences. And they found it just was a Pandora’s box. There was minke whales that were harvested outside of harvestable areas.

There’s also humpback whales and thin whales. And even some of the meat was porpoise and dolphin. And I think, but I’m not 100% sure, some of the meat was not even terrestrial, was not even marine mammal, was terrestrial mammal.

And so this really demonstrates how with new sequences to regulate the supply chain, to detect fraud, and to detect illegal harvesting. And so fraud in terms of selling something that isn’t what it says on the label, and illegal harvesting, things that just shouldn’t be on the plate anyway. And so this is now quite widely applied, and DNA sequences used by various authorities in the United States and in Europe, particularly for this reason.

So it’s super powerful and easily applicable. Right. So one day when we will buy a tuna can, we will be 100% sure that it’s only tuna inside.

Thank you very much for your answer. But now let’s talk a bit about data, about files. So what’s your messiest data headache? Like mixed samples, shaky vouchers, biassed references? And the workaround you use so the application does what it says on the tin? So Brent, you can start.

Okay. Messiest data headache is just real data and the concept of what a species is. So we have a, you know, when we have a lot of anonymous sequence data, or allegedly belongs to one species, we find it’s very divergent with regard to its barcode sequences.

You know, the inevitable question is, was this one species or two? And that becomes quite important for policy and decision making. Particularly if it’s more, if it’s, we have multiple species, but it’s been classically labelled as one. Well, we need to, I mean, that needs to be described.

It doesn’t exist unless it has a taxonomic name in administrative and policymaking circles. Making those decisions is not straightforward. And so this is an area that, where I think there needs to be more work in terms of fully integrating species concepts into the interpretation of barcode sequence data and allowing for the nuances of speciation, that it is not a black and white process.

It’s a, there is not a single number of mutations beyond which you can say, oh, now we have two species. So being as a headache is also super exciting and a lot of fun to work with. And it’s again, an area where genomics comes in and helps.

So quite often we’re applying genomic tools. We have these two divergent, or in some cases, nine divergent lineages that are labelled as one species and we find them in sympatry. So we can then use genomic data to ask the question, are they behaving as biological species in sympatry? It’s an instant answer with genomic data.

It’s an instant answer. So there’s a lot of scope there. And this is another area where these two fields in taxonomy can really come together and be super helpful, I think, especially given that the logistics of generating the kind of data we’re talking about is becoming more and more achievable or less problematic.

Yes. So in our day-to-day work in genomics, we often find all sorts of difficult samples or difficult data. Yet, I think that sometimes what makes that sample or data set difficult is often an opportunity to extract information that was previously inaccessible for researchers or to derive extra amounts of information that can enrich the knowledge that can be derived from them.

And I can give a couple of examples. One are museum samples, meaning that these are biological specimens deposited in natural history museums, sometimes for over a century, very often. And the DNA that can be extracted from these samples is degraded and is present in low amounts naturally.

And so this makes genomic analysis challenging, but possible. And this possibility really opens a new window of opportunity to sort of unlock the vault and making use of these remarkable natural history collections. And it also reduces the impact of new sampling.

So if we have all these collections deposited in museums, we can reuse it using cutting-edge genomic techniques to analyse them. Of course, if we have really short pieces of DNA and with low amounts, that requires some care in terms of laboratory work to extract correctly and produce the libraries that are required and to sequence. And then in the analysis, we also need to apply some crafted approaches to take into account, for example, mutations that may arise that are not really original, that are physical damages given the time that has passed since the collection.

Since we have very little DNA, often we need to pull individuals from the same populations to increase the amount of diversity that we can analyse and analyse it at the population level. So this strategy allows us to really analyse and apply this cutting-edge, high-throughput genomics to understand things without new sampling, just simply going to the museums. And that’s, I think, a fascinating field.

And then I can give a second example, which are samples with mixed DNAs from several species. And this can be, for example, non-invasive samples, scats that have DNA from the host, but also from the preys, for example, hosts, cobiants, parasites. And when we extract the full DNA that is present in a certain sample and then sequence everything, part will be from the host.

And often, if we’re interested in studying the host, we just get rid of all the rest of the DNA sequences that are there. But these actually have all this information about, I don’t know, the diet of individuals, about plants that a pollinator visits, about parasites that exist in certain hosts. And so this sort of mixed and difficult samples actually present an opportunity to provide a more integrative view on the biology of species.

What advancement has the highest chance to change your field trajectory? And I would start with Joseph. I think that one foreseeable advance that we have on the field is to move from this strategy that we’ve been talking about, so generating a single reference genome and then additional re-sequencing data from individuals from that population to a pan-genome approach. So, meaning that we can generate high-quality genomes from every single individual that we analyse in a certain population.

Because the approach that we have right now, we essentially can identify a variation that is present in the common part of the genome that is common to all individuals we analyse. And this is the majority of the genome, if we’re talking about a single species, and has been very, very informative for all the things that we’ve been discussing. But we’re leaving this perhaps tinier piece of the genome where there is variation among individuals and that we currently cannot analyse with this strategy of reference genome and then re-sequencing data.

And so having access to that, we can, for example, analyse genes that are present in some individuals and not in others. The expansion of gene families, for example, in the immune system, in which sometimes the number of copies of genes is important for the ability of individuals to resist to diseases. Structural variations or changes in the way the genome is organised that can be important also for local adaptation.

And so I think this is an advance that is foreseeable, that we’re moving in that direction. And I think that will change also the way our inference power in the field, because we will have access to much more information, much more information than we have now. But I think at this stage, I can also see an advance that will change also the application power, which is a sort of a consolidation stage where we have all the technological ability to generate reference genomes and whole genome data.

We have all the analytical pipelines developed. And so in terms of fundamental science, we are able to do all sorts of analysis. And now I think our work and our job as a genomicist and scientist is also to make this more and more accessible to non-specialists so that they can use this routinely in their activities.

Managers that can then influence policy decisions. This already occurs, but making this analysis of genomes from the lab to the analytical part accessible for non-specialists, I think that that will change and increase a lot the way these techniques can be really applied in the field. Yeah, that’s very, very promising.

And Brent? I think it’s a kind of similar response to Jose, that the developments that are letting us overcome historical barriers to working at scale, like the pan-genome approach is now kind of tangible, and that’s super exciting. And I think in the barcoding world, just as an example, when I was doing my PhD, which was a long time ago, just to get one sequence was such a painful process. It involved weeks of work and radioactivity.

Then you put your X-ray in the freezer and you pull it out a week later and you open it up and there’s nothing there. You cry and you go back again. But now just generating like a thousand sequences just doesn’t seem like that big a deal.

It’s so achievable and now becoming more affordable. So the idea of research groups that were previously excluded from this kind of research because of cost limitations, that’s becoming less and less. So the idea of having in your lab everything you need, all the resources, including the sequencer, the sequencing unit to generate barcode data at scale, is every year it’s becoming more affordable for more labs.

And so in the Biodiversity Genomics Europe Research Project, there’s been a lot of focus on training for these newly available technologies for implementation. We need more of that. And so barcoding, its most basic application is monitoring an inventory.

And some of the most exciting places to do that are the places that have been sort of left out or have been left out because of cost restrictions. So I think one of the biggest advances and there’s groups working on reducing the cost further for the peripheries that are needed, the equipment that’s needed. So as that continues, it has the strongest chance of us having globally generated data from some of the most exciting parts of the world.

So yeah, I think that’s the strongest advance is this overcoming of scale issues. Yeah, that also democratise, let’s say, access to technologies. And yeah, it’s so beautiful.

So I foresee the next discussion coming at higher level. How many individuals do you need to create a reference PanGenome to make it so? That’s a good question. Do you need 10 or 100? All of them.

So let’s proceed with our last question. I would like to start with Brent again. So if you have 24 hours, a backpack and your kit, all of things that you are necessary for you, for your job, where do you go and what do you sample? Your dream? Okay, first of all, I need more than 48 hours because I live in the Canary Islands.

It takes a long time to get anywhere from here. I think there’s two places I go. The first would be to revisit the Trans-Mexican Volcanic Belt.

I had a PhD student working there. She did some sort of preliminary work on arthropods and it just turned out to be super interesting. So to be able to go back there and sort of scale up more sites, a broader section of the vertebrate community, not just sampling on top of the Sky Islands but in the lowlands below, just have a really detailed understanding of what’s driving diversification there because we saw some really cool signatures and it’d just be great to follow up on that.

So that would be a pretty exciting thing to do. The second thing I’d do is if I had a rucksack and a full kit, I would travel around the museums of Europe trying to get collaborations for sequencing relevant material for the former of the Canary Islands. It sounds like a bit of a boring, pretty boring to do the first one but it’s equally as exciting as far as I’m concerned.

Both are exciting, yeah. Joseph? Yeah, I would probably also need more than 48 hours but so one thing that has always fascinated me is biodiversity in general, meaning the diversity of species of animals and plants and all types of species that exist and it strikes me how little we still know about this diversity. And so if I could do whatever I wanted with infinite money and perhaps a little bit more of time, I will definitely, and also provided that all the ethical and legal aspects of sampling are covered and agreed with the local authorities and communities, I would definitely go to a biodiversity-rich locality in the world like in Africa or in South America, do a bioblitz and then sequence everything.

As a second one, I share this brand’s desire to go around the museums in the world because this has been a really fascinating aspect of my research. It is really, really amazing the level of diversity, of biodiversity that we can find in the drawers in natural history museums, things that are not shown to the public. It’s really resources that are amazing and that need to be used to increase the knowledge that we have about biodiversity.

Sounds like a good plan for 48 hours, we stick to that. And that was the last question, Brent and Josette, thank you so much for joining us. And thank you to all our listeners, this was the last episode of Genomic Connections, we hope you enjoyed it and thank you.

This podcast is brought together by Biodiversity Genomics Europe, a project funded by the European Union, the Swiss Confederation and the United Kingdom.

Genomic Connection #6 – The code of life: the world of bioinformatics

Kasia Fantoni — Wed, 29 Oct 2025 14:14:15 +0000

In the sixth episode of Genomic Connections, Kasia and Christian talk with Rutger Vos and Diego de Panis about their experiences in bioinformatics and the central role this discipline plays in transforming vast amounts of data into biological insights.

Rutger is a computational evolutionary biologist and the head of the Data Competence Center at the Naturalis Biodiversity Center (Leiden, the Netherlands). Diego is a biologist based at the Leibniz Institute for Zoo and Wildlife Research (Berlin, Germany) with 10+ years of data-driven research experience assembling sequences and connecting genes with phenotypes and biological processes. We already talked about Bioinformatics in this blog post.

This episode comes in a different format than usual: it was screenplayed and produced as a video interview, rather than as a podcast. You can watch the video here, and listen to the audio-only version here.

Podcast episode:

You can listen to Genomic Connections on Spotify and PocketCast. The RSS Feed is available here.

The episode’s full Transcript (AI-generated) is available below the credits.

Credits

“Genomic Connections” is written and produced by Christian de Guttry, Kasia Fantoni, Luísa Marins and Chiara Bortoluzzi.

Graphic design by Luísa Marins.

BGE is a Horizon Europe project funded by the European Commission, the Swiss Confederation and the United Kingdom.

The episode is licensed under a CC-BY 4.0 license.

You can listen to Genomic Connections on Spotify and PocketCast.

Episode #6 Transcript

Hi Kasia, good morning. How are you today? (0:03) Hi Chris, good morning. Wonderful.

(0:06) Here it’s a bit rainy actually in the Netherlands, so it could be better. (0:09) What about you? (0:10) Switzerland is still sunny, I guess for two, three days more. (0:15) I wanted to ask you something.

(0:17) Today I forgot what we wanted to talk about. (0:21) You mentioned last week, but then I… (0:24) Are you talking about the Genomic Connections episode? (0:28) Exactly. (0:28) It’s about bioinformatics.

(0:31) Oh, bioinformatics. Such a difficult concept. (0:35) And how do you think you can explain this to our public? (0:38) Well, you need champions to really go through this together.

(0:45) Talking about champions, do you think you have a champion in the iBull community that can explain to us? (0:53) Well, sure. We have Rutger Voss from Naturalis Biodiversity Centre. (0:59) I think he’s pretty strong.

(1:03) Our champion, I see him like the King Arthur of Urga. (1:07) It’s Diego de Panis from IZW in Berlin. (1:12) I prefer to not pronounce the entire name of the institutions because it’s quite long and tedious to understand.

(1:19) Wonderful. (1:21) Well, I think we can get started, but I’m not sure whether the audio format would be enough for this very special episode. (1:31) All right.

We went to writing blogs, to making podcasts, and now you’re not happy with the podcast anymore. (1:37) Let’s try, you know, we can try to make a video. (1:41) Wow.

Sounds great. Let’s get started. (1:44) Okay, let’s get started.

(1:47) Name, team and affiliation. (1:50) Diego de Panis, team Urga. The affiliation is Leibniz Institute of Wildlife Research.

(2:01) Rutger Voss, team iBull. I work at Naturalis Biodiversity Centre in Leiden, the Netherlands. (2:09) How would you briefly describe what you do? (2:12) I coordinate the sequencing and assembly committee of ERGA.

(2:16) I struggle with DNA barcoding data and try to get good stuff out of it. (2:21)

Years in bioinformatics. (2:25) Not many.

I am a biologist, so I’m just improvising bioinformatics. (2:32) Bioinformatics exists since the dawn of time. In the Bible, Adam and Eve named the species, and that’s the first step in bioinformatics.

(2:41) It’s an ancient science, the first one. (2:45) Bioinformatics, more biology or more computer science? (2:52) I think it’s a weird mixture of the two, but I would guess this more biology. (3:01) I’m going to have to agree.

Yeah, at least what we do is more biology. (3:06) There are fields in bioinformatics that are very algorithm orientated, but we’re mostly just struggling with the mess that is biology, genetics, and the naming of species. (3:18) It’s all just very messy, and we’re doing a lot of bookkeeping to keep that clean.

(3:23) Coffee, mate or tea while coding? (3:27) Mate all the way. (3:30) Definitely coffee always. (3:33) One thing that Eyeball does better than Erga? (3:37) Do we? (3:41) I think it’s a better branding.

They’re older, right? They’re much older. (3:49) Eyeball has a huge community of people who collect specimens in the field. (3:54) I think there’s many, many people behind it who just collect the specimen and want to have it barcoded.

(4:01) And Erga is probably just by necessity, because genome sequencing is a bigger endeavour, is more focused on fewer institutes. (4:09) So as a community, Eyeball is bigger. (4:12) One thing Erga does better than Eyeball? (4:17) Everything.

(4:20) I think that since ERGA is much smaller, or the high quality reference genomes community and the VP is much smaller, it can achieve things more rapidly, like throughout the community and that, and vertical integration of protocols and workflows, I think. (4:41) I think Erga has better integrated infrastructure. (4:47) At least from where we are now, it looks to me, and I’m not sure if the perception is accurate, that there’s more tooling already in place where Eyeball is developing more right now.

(5:01) Are there any misconceptions people have about your project? (5:08) Misconceptions? The challenge is to make people understand what’s this about, right? (5:15) I don’t know if many people understand what is important of having reference genomes or high quality genomes for the eukaryotic biodiversity. (5:26) I think a misconception with DNA barcoding is that it is more precise than it really is. (5:33) And probably a lot of people think that it is a kind of a yes or no answer.

(5:39) And you can absolutely identify every species with a single barcode. (5:44) And nature is more complicated than that. (5:47) What, you can’t? You cannot identify everything? (5:50) I’m afraid not, Diego.

No, I’m sorry. (5:54) Favourite tool or software for data analysis? (5:58) I’ll say I really like Minimap and also I really like HiFiASM. (6:01) This is a tool for mapping reads to genomes and also for reference or for mapping reads or for generating genome assemblies.

(6:09) I think they are super solid software, pretty well written, super fast. (6:15) It’s hard to answer. I can name some tools that I work with a lot that are probably not my favourites.

(6:22) We’re trying to do more with Galaxy. (6:24) So I’m learning more about how Galaxy works and it is a very useful tool. (6:29) I think I’m probably most excited to start up this tool called Mesquite, which is a kind of a graphical tool to explore sequence data and phylogenetic trees.

(6:41) But that’s more also nostalgia because I did my first postdoc with the Madison twins, who are the developers of Mesquite. (6:51) And I also wrote some modules for it. (6:53) So every time when I start it up, I see the credits and then I get kind of nostalgic for my time in Canada where I contributed to that.

(7:04) Which is tougher, collecting specimens for DNA or assembling chromosomes on a computer? (7:12) Collecting a species for DNA, that’s much, much difficult. (7:16) Yeah, collecting the species is difficult, especially when for the barcoding, we try to do it obviously at scale, right? (7:25) In the barcoding activities, we try to capture more species, but shallower. (7:31) And so that is very decentralised and done by a lot of volunteers.

(7:35) And they have to then also, first of all, grab the right species, identify it correctly and record in a consistent way what they’ve done. (7:47) And when people input data, we make mistakes, right? (7:52) So then obviously there’s going to be mistakes in what’s collected and that’s very difficult to correct afterwards. (8:00) Any friendly nickname to each other’s team or projects? (8:04) What? (8:07) I just call them the genome people.

(8:11) And who will achieve the mission first? Millions of barcodes or genomes of all you species? (8:18) I would guess the barcode guys. I mean, it’s so easy to get a barcode right. It’s just a tiny piece of DNA.

(8:27) We’re already there. We have millions of barcodes. It’s mission accomplished.

(8:32) Describe yourself in one word. (8:36) Biologist. (8:38) Rutger.

(8:39) Nerd. (8:41) And describe your counterpart in one word. (8:45) He’s a bioinformatician, I’ll say.

So bioinformatician, proper bioinformatician. (8:51) I thought you were a proper bioinformatician. I’m just faking it.

(8:54) I’m not. (8:55) So we are both, I think, by training biologists. (9:01) And so when I say I’m a bioinformatician, I feel a little bit like a faker.

(9:09) Maybe you feel that way too, but that’s not very flattering. (9:13) Maybe say generalist. You can be both a biologist and have the technical expertise.

So let’s say generalist. (9:20) Why? Okay. (9:23) The biggest myth people believe about bioinformatics.

(9:27) I’ll say that it’s a thing that is super straightforward and effortless. (9:34) That you can just do a few lines of code and then you’re going to get everything out of it. (9:42) Yeah, that’s exactly right.

(9:43) The struggle is much more with just the messiness of the tools and the messiness in the data. (9:53) And just struggling to stitch everything together. (9:56) Also in such a way that we actually know what we did afterwards and why we did it and come to reasonable information.

(10:04) So it’s much messier than people perceive it to be, I think. (10:09) If you could sequence any species next, which one and why? (10:16) Really good question. (10:19) I think I would sequence something from the Southern Hemisphere, like a crone eagle.

(10:26) I’m very excited about where ancient DNA sequencing is going. (10:30) So the thing that just as kind of a passion popped up in my head is that, of course, we have the human genome. (10:38) We have the Neanderthal genome.

We have the Denisovan genome. (10:42) I’m holding out whether it’s going to be possible to sequence a Homo erectus. (10:47) I’m not sure if we’ll ever find good fossils for that, but that would be amazing.

(10:52) Okay. And to finish, say goodbye and wish something to the other for the end of BGE. (11:00) Bye bye.

Thank you very much. I wish him a lot of luck, success. (11:08) Thank you very much.

Bye bye. I wish you many coherent assemblies.

Genomic Connection #5 – Communicating the Science Behind Biodiversity Genomics

Kasia Fantoni — Wed, 17 Sep 2025 11:24:20 +0000

In the fifth episode of Genomic Connections, Kasia Fantoni and Christian De Guttry are joined by Ela Sari, Science Communications Advisor at ⁠Naturalis Biodiversity Center ⁠(the Netherlands) and Luísa Marins, ERGA Scientific Communication and Dissemination Coordinator based at the ⁠Leibniz Institute for Zoo and Wildlife Research⁠ (Germany). They talk about science communication and the importance of disseminating information about biodiversity genomics to a variety of audiences.

You can listen to Genomic Connections on Spotify and PocketCast. The RSS Feed is available here.

The episode’s full Transcript (AI-generated) is available below the credits.

Credits

“Genomic Connections” is written and produced by Christian de Guttry, Kasia Fantoni, Luísa Marins and Chiara Bortoluzzi.

Graphic design by Luísa Marins.

BGE is a Horizon Europe project funded by the European Commission, the Swiss Confederation and the United Kingdom.

The episode is licensed under a CC-BY 4.0 license.

You can listen to Genomic Connections on Spotify and PocketCast.

Episode #5 Transcript

My morning started with a 10-message chain from my plumber. He wrote, ETA ASAP, but VC is DOA unless DIY. So basically, I needed a translator just to know when I could use the bathroom.

Gee, this really sounds like a typical research email with acronyms everywhere. No clear subject line, and the sender, of course, is sure that it will be clearly understood by the recipient. Exactly.

When even my toilet speaks jargon, you know it, it’s time for a serious chat about communication. Which is perfect, because today we dive into how clear words, inside and outside the lab, can save projects time and also household plumbing. We will ask, how do you turn DNA barcodes and high-speed scaffolds into sentences that humans, and not just machines, can follow? And especially, why do good updates, tidy slides, and the right acronym at the right moment, keep giant projects, like Biodiversity Genomic Europe, running smoothly? I am Kasia Fantoni, iBOL Europe Community Manager.

And I am Cristian de Gutry, ERGA Project Manager, and you are listening to Genomic Connection, the podcast about biodiversity genomics. Today, decoded in plain language. So today we are joined by Ela Sari and Luisa Marins.

Ela has a multidisciplinary background with studies in both architecture and science communication from Delft University of Technology. She is very passionate about connecting people and engaging in creative work, and combines her interest in science, technology, and nature as a science communicator at the Naturalis Biodiversity Centre. Luisa studied biology since she has always been fascinated by biodiversity.

But also, she also had a strong interest in the communication field and how to tell stories. So right now, she is based in Berlin and works at the Leibniz Institute for Zoo and Wildlife Research, supporting communication and outreach actions for the European Reference Genome Atlas. Naturalis is the Dutch National Research Institute for Biodiversity, working with one of the largest natural history collections in the world.

Their researchers work on describing, monitoring, and understanding biodiversity. The Leibniz Institute for Zoo and Wildlife Research, also known as Leibniz IZW, has the goal of understanding the adaptability of wildlife in the context of global changes. And to contribute to the enhancement of the survival of viable wildlife populations.

For this purpose, they investigate the diversity of life histories, the mechanics of evolutionary adaptations, and their limits. How did you end up communicating? Yeah, thanks for having me here. Well, for me, it’s quite an interesting story because I’ve always been very creative, and I wanted to make the world a better place.

So I also love technology. And that’s why I chose to study architecture at Delft University of Technology. But slowly, yeah, it sounds a bit weird, but I started that I didn’t want to put an Ela Sari building on this world.

I wanted to make impact. I wanted to connect with people. So that’s why I eventually decided to combine my master’s in architecture, also with science communication at Delft University of Technology.

And then I did my internship at Naturalist Biodiversity Centre. And I’ve always been in love with nature, with biodiversity. So it was perfect.

And the rest is history, you could say. Yeah, Luisa here. So I have a bit of a different journey because I studied biology and I worked with genomics of animal species in my bachelor’s and master’s.

But in my whole life, I always had a strong interest in communication and telling stories and also visual communication, the more visual part and arts and things like that. And at some point, I even thought about studying architecture. And then during my master’s, I had the opportunity to get more involved with the European Reference Genome Atlas because they needed support in this more outwards facing role of communication.

And I was there and I got more involved in this. And so I really think science communication is a way that brings together my interests very well. So cool.

So two different paths. But in the end, communicating well in any job is vital, right? So but for you, it is your day to day mission. So in one sentence, why does communication matter so much? Yeah, I think in one sentence is because no one can do basically anything alone.

And the only way to get help and to get anything done is with other people. And so you need to communicate your ideas, to connect, to improve the ideas and make them real. Yeah, for me, it will be that communication is actually the bridge that connects knowledge to action, you could say.

If there’s no communication, there is no engagement, no education, no decision making, no change. So communication is key. Yeah, Tata and Rieko, both of you.

I think you already anticipated it a little bit in your responses. But why is scientific communication so important? Yeah, you could say that scientific communication is crucial because it makes really complex research accessible. So as I just said, it makes it applicable.

It makes it into action. So when you make sure that everyone understands and can engage with it, you can actually apply these scientific discoveries to make improvements, to tackle the biodiversity crisis, to really make an impact. And also in today’s world where misinformation and fake news is so prominently in our daily lives, it’s also, I think, really important to build trust in science.

So then clear and credible scientific communication becomes even more vital, you could say. Yeah, also important to keep in mind that a big part of this research is actually funded by society. And then it’s a big responsibility that the people who are funding this have some idea, at least, of what’s happening.

So it’s the only way they can really value it and have an interest and care about what scientists are doing. So just to add this. Yeah, this is very true.

Especially try to communicate to society what is DNA barcode and the reference to human genomes. To me, it looks kind of difficult. So what is your most effective strategy for turning hard science words into plain talk non-scientists can follow? Yeah, I think there are many little things you can do.

But yeah, always trying to link these abstract concepts into more concrete things or things that relate to everyday life. Yeah, keeping things, breaking them, long process into smaller steps that one can follow. It’s very common that people reuse metaphors.

So comparing the genome to a book and the DNA, the words written in it. Or, for example, in the case of ergo, the process of genome assembly can use the metaphor of a puzzle. Very difficult puzzle, but still some sort of puzzle.

And yeah, things like avoiding technical words or if you really need to use one of these words, give a brief explanation or refer to something that they can make sense of. Yeah, and thank you, Luisa, because it was actually also exactly how I would answer this question. I think using metaphors, analogies and storytelling is very important in our job.

And like you said, for example, here at Naturalis, we always try to communicate that DNA barcode is like a barcode on a product in a supermarket, for example. So every item has its unique barcode. It can help the cashier to identify stuff quickly.

And in the same way, every species has its unique DNA barcode, helping scientists identify them accurately. So it’s always really nice to use those kind of examples. And since I don’t have this background in biology, it also really helps me to understand such difficult and complex stuff.

Yeah. And how important for both of you is the visual part of the communication in this context? Because now you’re talking mostly about written parts, but how important is the visualisation? Yeah, I think the visual part is important also to attract people’s attention. So apart from explaining things, it’s always easier if you have an image to help you make sense.

But also we use colour and other visual elements to simply bring the people to want to learn about that. So it’s very important to make things attractive. Otherwise, you can put a lot of effort into writing something that sounds really nice.

But if no one cares to click on it or stop by your activity because it’s not visually appealing, that’s a pity. Yeah, that’s a really important part. So, for example, one example that we do for BGE is in the past that we made this visual story about hamsters and we called it Hamster Time.

And we saw that it really worked and it really got some nice engagement. So indeed, it’s really important to make it not only appealing, but also fun to the public. Yeah, talking about the public.

So you’re both very involved in the Biodiversity Genomics Europe project, BGE. And when you have to communicate about the results or about the project itself, you are reaching a very diverse audience that includes, yes, scientific community, lab researchers, but also policymakers and the general public. So how do you make sure that you tail, let’s say, the message for each different target audience? Yeah, so we always have to think about the audiences and their drivers.

And every target group has its different drivers. For example, the driver of a policymaker is way more focused on impact. And for example, the drivers for a citizen scientist are maybe more involved with being part of this, solving this bigger issue of the biodiversity crisis.

So every message is custom made. And a good example of this is the table on our BGE website. When you go to our BGE website, the first thing you see is this table for different target groups, the genomics community, policymakers, scientists and public media.

So that can also be really nice to directly navigate to the right information. Yeah, I think also, as you mentioned, just always really thinking carefully about who you are talking to, whatever, if you’re planning for an event or writing a text. And just to add one thing that I sometimes do and can be useful is to really try to think about your audience in a very concrete way.

You can imagine a person that represents that audience and think, how old are they? What are their interests? What are their, what they do in their free time maybe? And what would really drive them to read or pay attention to what you’re trying to communicate? So you can give them a name. You can give them a job title and use this very concrete way of imagining who you were talking to. And this might help you come up with ideas for what you want to communicate.

Yes. And of course, the best situation is that you’re actually able to meet those target groups. So that’s also really nice that along the way in the BGE project, we’re starting to see more people, get more engaged.

So that’s also really helpful. Yeah, clearly. Given that you mentioned hamster time, so click and likes don’t tell the full story, right? I know that there are good indicators of success, but they’re not everything.

How do you decide that a newsletter, a tweet or a webinar really worked? It’s just reactions and interactions. Most of all, if people reply, if they, as a result of the newsletter, they actually come back to you asking for more information or if a given webinar starts such a nice discussion that leads to some scientific collaboration. So it’s this active role of the audience that they need to reply.

So this is to me, when I know that it really happened, the communication and it was successful, if at least someone gets back to us and takes something out of this, that’s always very nice to see. Yeah, for me, it’s exactly the same. So we always like to measure success and not just by quantity, but also by engagement quality.

So it includes how many people take action, shared information with others or engaged in deeper conversations. That’s the real impact. So that’s also something I can see very clearly happening with the Erga Eyeball Connection series.

So that’s really nice to see that you worked on. And it’s really easy to understand. So also for me, without my background in biology, it’s really informative and it’s also a fun way.

And a more personal example is that last year I got the opportunity to make a BGE video for the Tour de Femmes, the cycling race, and it started in Rotterdam. And the organisation, they invited us to talk about the marine invasive species in the city sport and how BGE is working on this important issue. And those videos are great because I got a lot of responses from family and friends who are also part of this general public, you could say.

So then you see that those videos are really working and really effective. Yeah. That also worked with my mom, who is one of our followers on Spotify with the podcast.

It’s nice. Yeah, but it’s nice, right? You see it happening. Yes.

So, Ella, you talked about this experience of going to the port of Rotterdam. And I think you and Luisa as well, you had the chance of going a bit to the field or to the lab or just to experience, let’s say, biodiversity genomics from A to Z when it comes to environments, like working environments. So what was the most adventurous moment that you experienced since you are involved in BGE? I thought I would tell you a story about my master’s because I worked with a species of two-toed sloth from the Amazon.

And I had the really, really wonderful opportunity to travel to the Amazon during this project. And, yeah, after I had been working for a while with this data, so just genomic data for this species, and I was already very in love with this species, but I had never seen it. So only the DNA sequences.

And then going there, I had this moment where – this is a very cool city in Manaus. It’s in the middle of the Amazon. And, yeah, it was a very special trip for me.

And because it’s in the middle of the jungle, these things happen that we got – I was staying at the lab of a professor, and she said, yeah, someone found a sloth and it needs to be rescued from the middle of the city and brought back to the forest. You want to follow them? And I said, yes, please. And it was exactly the species that I was studying.

So I had this encounter with the sloth. I could see it very close, and I saw it as they released it back. So we drove to a park that was connected already in the forest, and I saw it being released and then climbing up the tree.

And it was extremely cute, and I was so happy. And it reminded me of these things are real and how easy it can be to be so alienated when you’re working on the computer all the time from the reality of what you’re doing, right? The goal is to help the individual animals that exist in the world still, fortunately. And seeing that one was really – I don’t know if it’s an adventurous moment, but it was a beautiful moment for me.

I think it’s the perfect example of an Indiana Jones moment. And now that I hear you speaking in such an enthusiastic way, I always – yeah, it’s a bit sad that I never studied biology, actually. So my story is definitely not as cool.

My Indiana Jones moment, yeah, it’s not really Indiana Jones, but what I love is that I was able to be the host on stage for the BarcodingNL event at Naturalis. It was this really nice event for Dutch amateur expert collectors, and it’s a crucial group of people. Without them, it’s not possible, the work we can do.

So engaging with this audience, asking questions, getting a lot of questions, it’s really nice to get in touch with one of the target groups. That’s actually what we just discussed. So for me, that was a really special moment.

Cool. And now, before we wrap up, like a personal twist, if you could have any historical or fictional character as an intern working with you at IZW or Naturalis for a week, who would be it and why? Yeah, for me, it’s the British documentary maker, Louis Theroux. I’m not sure if you know this guy, but his curiosity, his often awkward conversations with people from all walks of life, I think it will bring an entirely fresh perspective to science communication because Louis has this incredible ability to dig deep into complex and uncomfortable subjects.

So it’s not really uncomfortable what we are doing, but I think it’s really nice to have someone right next to me asking those really, really important questions, someone who doesn’t know anything about this subject. So I think it will be very helpful and inspiring to meet up with such a person. For me, I don’t know if I can pick one person.

Basically, someone very, very, very creative. So even from a completely different field, an artist, someone that can bring new ideas and look at BGE and come up with new ways that we can communicate it. But also just science communicators that I really like and I’ve been following for years, like Zee Frank, Emily Grassley, some names that maybe you don’t know, but there are some really cool people doing interesting science communication and it would be nice to have their insights.

Thank you very much to both of you. It was a pleasure to communicate with you and see you soon. Thank you so much.

Thank you.

Genomic Connection #4 – From base pairs to briefcases: inside the DSI deal-making

Kasia Fantoni — Tue, 15 Jul 2025 09:58:47 +0000

In the fourth episode of Genomic Connections, Kasia Fantoni and Christian De Guttry are joined by Amber Hartman Scholz, microbiologist and Head of the Science Policy & Internationalisation Department at the Leibniz Institute DSMZ in Braunschweig, Germany. They dive into the topic of Digital Sequence Information, or DSI, and the ongoing global discussions on how to ensure equitable access to and fair sharing of benefits arising from the use of genetic information from biodiversity.

You can listen to Genomic Connections on Spotify and PocketCast. The RSS Feed is available here.

The episode’s full Transcript (AI-generated) is available below the credits.

If you want to learn more about the CBD – United Nations Convention on Biological Diversity, we wrote about it in this blog post.

Credits

“Genomic Connections” is written and produced by Christian de Guttry, Kasia Fantoni, Luisa Marins and Chiara Bortoluzzi.

Graphic design by Luisa Marins.

BGE is a Horizon Europe project funded by the European Commission, the Swiss Confederation and the United Kingdom.

The episode is licensed under a CC-BY 4.0 license.

You can listen to Genomic Connections on Spotify and PocketCast.

Episode #4 Transcript

(0:05) My phone made a great playlist last night. (0:08) Every song was called Track 01 by unknown artists. Can you imagine? (0:12) I love the music, but I could not like the band.

(0:15) Yeah, that is digital sequence information in a nutshell. (0:19) Great DNA data, yet no credit or benefit for the country that provided it. (0:25) It’s a bit like dancing at a concert where the musicians are hiding.

(0:29) Yeah, exactly. (0:31) So the current DSI talks are like the manager saying enjoy the music,(0:36) but buy a t-shirt so the artist gets something back. (0:40) Today we will ask how can science keep the playlist open (0:44) while making sure that the right people share the rewards.

(0:49) So grab your headphones because this episode is about keeping the music playing (0:54) while giving proper credit to the people behind every note. (0:58) I am Kasia Fantoni, iBOL Europe Community Manager. (1:02) And I am Christian Beguttri, ERGA Project Manager.

(1:05) And you are listening to Genomic Connections, podcast about biodiversity genomics. (1:11) So today we are joined by Dr. Amber Hartmann-Scholz, (1:17) a macrobiologist and head of the Science and Policy and Internalization Department (1:22) at the Leibniz Institute DSMZ in Braunschweig, Germany. (1:28) She leads projects on international science policy (1:31) and especially on access and benefits sharing and digital sequence information.

(1:36) She led the DSMZ implementation to become a registered collection (1:40) under the EU Nagoya Protocol regulation (1:43) and co-founded both the DSI Scientific Network and German Nagoya Protocol Hub. (1:48) The Science, Policy and Internationalization Department (1:52) at the Leibniz Institute DSMZ in Braunschweig, Germany, (1:56) coordinates the Institute’s strategic engagement (1:58) in science policy and international collaborations. (2:02) It supports global biodiversity initiatives (2:05) and represents DSMZ in international frameworks, (2:08) including those related to access and benefits sharing under the Nagoya Protocol.

(2:14) To set the scene, how does someone move from pipettes and lab coats (2:20) into the high stakes world of international treaty talks? (2:23) And what drew you personally to the ethical and legal side of genomics? (2:28) It’s a great question. (2:29) I think the best place to start is the words that my undergraduate advisor gave me, (2:36) which is that opportunity favors the prepared mind. (2:39) And so in some ways, the transition from the bench to policy is a coincidence.

(2:45) But in some ways I was prepared and I knew that I wanted to go there. (2:49) And so I really went into graduate school and did my PhD (2:54) because I wanted to ask questions. (2:58) I wanted to understand the life sciences at a deeper level.

(3:04) But at the same time, I knew that I didn’t want to stay in laboratory based sciences. (3:11) And I had heard in my undergraduate about this field called science policy. (3:17) And so the entire time that I’m doing my PhD, (3:19) I know that I want to go into the field of science policy.

(3:22) And I’m kind of constantly looking around thinking, how am I going to get there? (3:27) And the coincidence is that funded by the Gordon and Betty Moore Foundation, (3:33) there was an inaugural program of the California Council on Science and Technologies (3:39) science policy fellowships that was advertised in the summer that I was writing my PhD thesis. (3:47) So this is the summer of 2009. (3:49) I mean, before then, there were other options.

(3:52) So most people would apply for, at least in the United States, where I was born and raised.(3:59) The American Association for the Advancement of Science at the national level (4:03) has also a number of science policy fellowships that are offered. (4:06) And so my backup plan had always been, OK, I’ll apply for a AAAS fellowship.

(4:11) But because that one happened. (4:12) And at the time, again, another coincidence is that I started my PhD at Johns Hopkins University, (4:17) which is in Baltimore. But my PhD advisor, Jonathan Eisen, (4:21) took a job at the University of California at Davis in my fourth year.

(4:25) So I was sort of a visiting student living in Northern California. (4:29) And then I had to go back and forth once a year to Baltimore. (4:33) And so I’m sitting there in my now husband’s apartment writing my thesis.

(4:39) And then I see this email pop through and I was like, oh, look, I don’t even have to like move.(4:43) I can just stay here in Davis and drive to Sacramento, which is a 20 minute commute. (4:47) And I have to get this fellowship.

And I did get it. (4:51) I mean, it was quite competitive. But then once you kind of get your foot in the door, (4:54) then you have your first policy experience.

(4:56) And then I was looking for a job actually in D.C. at that at that point. (5:03) Indeed, to leave Northern California for family reasons. (5:08) And then my program officer that I had had during my PhD, a woman named Mary Maxson, (5:15) had a job in the Obama administration at the White House Office of Science and Technology Policy.

(5:19) And it turns out that she was being promoted to a different position in OSTP, which meant that her job was free. (5:25) So when I reached out to her for a networking conversation just to sort of hear, you know, the D.C. scene, (5:32) her job became open and she handed my resume over to the PCAST co-chairs, (5:38) which is the President’s Council of Advisors on Science and Technology. (5:41) And then.

To make a much longer story short, I ultimately landed there. (5:47) So it really much is like I was looking for it. (5:50) But also sometimes you kind of get lucky and, you know, you’re in the right place at the right time with the right set of skills.

(5:57) And and the same thing again here. At the DSMZ. (6:02) So, again, for family and for private reasons, we left D.C. (6:07) after we started a family and I landed in Braunschweig, Germany, which is my home, (6:12) my husband’s hometown, which is, you know, quite different than Northern California or Washington, D.C. (6:20) And I kind of looked around at different biology institutes and I’m trained as a microbiologist.

(6:25) And I was like, oh, yeah, the the DSMZ is here, the German Collection for Microorganisms and Cell Cultures. (6:31) Oh, look, they have a relatively new director, a guy named Jorg Overmann that I knew from my Ph.D. (6:35) because I had studied in Woods Hole, Massachusetts and taken a microbial diversity class there. (6:40) And I met and worked with him for several weeks during the summer.

(6:43) And I was thinking, oh, wow, huh, maybe he could help me find something in the region.(6:50) And so I came in to have coffee with him. (6:52) And then it turns out that he was looking for a deputy, for somebody to sort of help with with the broader strategic issues that the Institute was facing.

(7:01) And so he kind of created a job at that time point. (7:05) And then the Institute was also facing the challenges of implementation with the Nagoya Protocol, (7:11)because we receive microbial deposits from around 90 different countries around the world and send out 40,000 things a year around the world. (7:22) And so we really have to worry about the international regimes that govern biodiversity, even though our stuff is invisible, it’s still biodiversity.

(7:31) And so basically, I start my job in 2014. (7:34) And that’s when the Nagoya Protocol, which is the foremost sort of instrument that regulates access to biodiversity and the requirements to share benefits. (7:44) And he just sort of says, like, Amber, there’s this new Nagoya Protocol.

(7:47) It’s going to create a lot of problems for the collection, for our research. (7:51) Could you like work on that? (7:53) And at the time, it was I had no idea that it would turn into, you know, what’s now become a 12 person department focused on many different aspects of this international policy complex. (8:07) In the broader sense, benefit sharing, but also the buzzwords, digital sequence information and indicators and the global biodiversity framework and a number of other topics that we can get into.

(8:17) So you can kind of see like there were a lot of coincidences where I never could have seen it coming. (8:23) And, you know, most people probably won’t have the luck to just have jobs created for them here or there. (8:27) And I definitely didn’t plan it that way, but it kind of just ended up that way a little bit.

(8:34) Well, that’s very much of an incredible sequence of coincidence. (8:39) Indeed, it’s really fascinating how you got where we are. (8:44) So with the next question, for anyone who keeps hearing DSI, what does it exactly mean? (8:52) What is digital sequence information and why it has become such a diplomatic hot potato? (8:59) Yeah, that’s a great question.

I think the funniest thing when talking to different scientific communities is that they hear the word digital sequence information. (9:07) And it kind of sounds like something that they sort of know or might have heard about, but it doesn’t actually ring a bell. (9:14) Right.

So if somebody says to you genetic data or nucleotide sequences or, you know, RNA, DNA, you’re like pretty sure that you know what they’re talking about. (9:23) Digital sequence information is like sounds like this funky like cousin of genetic data. (9:29) And I think that’s probably a fair characteristic.

The reason that it sounds like that is because it’s an invented policy term that was coined in 2016 at Cancun at COP 13. (9:42) So the basic way to understand this, and I’m going to kind of give you a little bit of a cartoon version of what happened. (9:50) Parties had agreed in 2010 to the Nagoya Protocol, as we just mentioned.

And in 2016, the Nagoya Protocol has now taken force. (10:01) But some of the underlying tensions or unresolved issues that didn’t get solved in the Nagoya Protocol kind of come bubbling up.(10:14) And one of those issues that had been discussed, but for which there was never enough political will, time or attention was the topic of, well, what about genetic data? (10:25) Is that in or not in the Nagoya Protocol? And it was always kind of this gray area where parties didn’t specifically say that it was or wasn’t in the Nagoya Protocol.

(10:33) And so COP 16, led by an African group, but then supported by BRULAC, which is the Latin American group. (10:42) This topic of digital sequence information, again, so the policymakers just kind of like create this word like on the spot there in Cancun and they say, this is what we’re going to call this. (10:52) And the basic policy rhetoric behind that is scientists have access to this huge genetic databases.

(11:05) They can use those databases that are open to the public and they can use the tools of synthetic biology, like CRISPR-Cas9 is kind of like just coming online. (11:16) But there’s definitely the topic of synthetic biology already at that. And negotiators know about that because that’s also another parallel negotiation track under the Convention on Biological Diversity.

It relates to the Cartagena Protocol. (11:28) So negotiators are kind of like piecing together, OK, well, we didn’t really resolve the issue about genetic data in the Nagoya Protocol. (11:33) And now they have these cool biotech tools in synthetic biology.

And so the rhetoric or the hypothesis, depending on your discipline, is made. (11:47) Those scientists can use those tools and that open data and they can have a loophole and not need to come back to collect physical samples from mega biodiverse countries and bypass the rules and regulations of the freshly negotiated Nagoya Protocol. (12:06) And so digital sequence information is kind of this term that refers to this intersection of science and policy in which we have policy observations being made about advancements in science and the international policy community needing to catch up.

(12:24) In some ways, they should have seen this coming. I mean, it was clear in even in the early 2000s, the genomics revolution was about to happen. (12:31) But policy always is slower than science.

Sometimes that’s good. Sometimes that’s bad. And in this particular case, it meant that the global north and the global south kind of like sat there in 2016.

(12:44) And again, in Egypt in 2018, the COP14, and they kind of like roll their collective eyes and they’re like, OK, here we go again, another conflict to resolve in the broader topic of benefit sharing. (12:57) How do we ensure that the benefits that come from genetic data are shared back with the countries that provide access to the biodiversity that then gives rise to that open public data? (13:12) And then that’s the next, you know, how many years is that? Like, that’s the next six years of negotiations from 2018 to 2024 is kind of trying to crack that tough nut. (13:25) I like what you just said that science can slow down policies and from scientists, sometimes we hear the opposite, right, that policies are slowing down science.

(13:36) And in one sentence, what is the most common misconception you encounter when people hear that DSI might be regulated because the scientists are scared about regulation and are scared about policies coming so hard within their field? (13:54) That is historically unregulated still today, mostly. (13:58) I only get one sentence, right? I would say on digital sequence information, we got a good deal. (14:06) And we being the academic community, the generators of this public good and what I mean by we got a good deal.

(14:17) I think that the parties to the Convention on Biological Diversity and I hope other UN conventions like biodiversity beyond national jurisdictions, which governs now the high seas and the WHO’s pandemic preparedness agreement, which is the pathogen access and benefit sharing rules and the plan treaty. (14:38) Anyhow, there’s other negotiations that continue to happen.(14:40) But first and foremost, that the parties to the Convention on Biological Diversity, they got it right, which is that publicly available genetic data can generate both non-commercial and commercial benefits and that those users that create those benefits should be treated accordingly.

(15:09) And the argument that we made coming from the sort of non-commercial or the academic sector was to say, yes, we absolutely do need to share genetic data in public databases because of several reasons. (15:24) Number one, taxpayers pay for our research. If we kept this public, that would sort of be dishonest and intransparent.

Number two, the very biological nature of this data is that if I show you ACGT, ACGT, you don’t know anything about what those letters mean until you compare it to ACGT, ACTT. (15:42) And then you know, OK, there’s one letter difference. Let’s see if this organism does one thing a little bit differently.

Of course, that’s over millions and billions of letters. But the point is, we can only understand our data by comparing it in context, in context with what organisms do, what they look like, what actions, what functions they have, and in comparison with this like code of life. (16:03) And so if we didn’t put them in public databases and continue to build and grow that data set, it would be impossible for us to do the things that we need to do with it.

And those things that we do are also really important for society, like respond to pandemics, like protect species that are about to go extend, like measure the diversity of an ecosystem, like develop a new crop that’s resistance to climate change. (16:28) And so we sort of said, look, yes, this is open. And yes, there’s a lot of benefits that come from it.

And those benefits go back to the public good. And they can only be shared in a multilateral basis, meaning everybody puts into the system and everybody takes out and we capture those sort of what we call in the policy speak, these non-monetary benefits. (16:46) On the other side, those companies that might be making a profit by developing diagnostic tests or vaccines, those companies that might be making the next cancer drug, those companies that might be making a new biomediation remediation reagent or soil fertilizer, and they will make a profit from it.

(17:04) Those are the ones that now under the new COP 16 decision from October 2024 will need to pay a portion of their revenue or of their profits and share that with the Cali fund, with a new global biodiversity fund. (17:20) And I think that makes sense. It protects open access and even protects commercial users of DSI because it doesn’t create many of the things that we were very scared about in those six years of negotiations, those three rounds of COPs, where you would close down the databases.

(17:40) You wouldn’t let certain kinds of data talk to others. You wouldn’t allow for a deeper interconnectivity and integration of data. And that would have been way, way bad, not only for us, but also for commercial users or for researchers at large.

So by and large, we got a good deal. And I’m proud of the decisions that the parties of the world took on behalf of the international scientific community. (18:06) Thanks, Amber.

And back to the international policies. So there are many countries that actually would like, would advocate for a global regulated system to share benefits rather than country specific bilateral agreements. And what is the strongest argument in your view for the multilateral approach? (18:31) Yeah, I’m going to kind of emphasize some of that in our previous conversation, our previous discussion, our previous question.

I think the hardest part in looking at the history of the Convention on Biological Diversity, the third objective, which is the fair and equitable sharing of benefits from biodiversity, the text of the convention, the evolution of the bond guidelines in 2002, (18:58) then in 2010, the Nagoya Protocol, and then the 2022 or 2024, the COP 15 and COP 16 decisions on digital sequence information is this age old tension between practicality of a legal approach and the principle of the approach. (19:23) And so for me, the Nagoya Protocol, which says, and the convention itself, countries have sovereign rights over their biodiversity. Biodiversity within the border of a country is not the common heritage of mankind or of humankind.

It is in a country’s sovereign rights. It can be regulated and controlled in the same way that natural gas or diamonds or gold deposits can be controlled by a country. (19:49) That makes sense.

That’s fair. That’s equitable. And that’s fixing the wrongs of hundreds of years.

And then there’s things in these same policy documents, like in the CBD, where it talks about facilitating access and using biotechnology, sharing equitably in cooperation at eye level. (20:14) I mean, that’s not the text of the convention there, that last part, but in general, these sort of like wanting to bring people together and exactly how you implement things, those objectives. And the Nagoya Protocol kind of does its best.

It sort of says like every country can choose to regulate access. They don’t have to. And if you do, you’re supposed to do it like this.

(20:38) But it creates a huge amount of uncertainty for practitioners when those things are not held at a high level of accountability. And because the Nagoya Protocol has basically zero enforcement provisions, it has no teeth in it like other conventions, for example, CITES, that sort of says, okay, your borders are shut down and you can’t do anything unless you answer these emails. (21:00) Nothing happens.

So then there’s sort of no motivation for those actors that don’t sort of follow the rules. But for scientists, they are trying to follow the rules and they have no path forward towards compliance. And so this is what I mean, the practical aspects of benefit sharing is that we have to recognize that, like, life food moves fast, research moves fast.

(21:24) It needs answers within a couple of weeks, ideally, month or two at most. But it cannot really wait for a year to be able to move an international collaboration forward. And what happens is that collaboration partner gets dropped and another guy gets picked.

And that’s bad for that country. It’s bad for those scientists. And it’s bad for fairness and equity.

(21:42) So what I would love to see, you know, maybe by the time I retire, is for new options for countries to emerge that should they choose to and the exercise of their sovereign rights, that they would look for new opportunities that align with the new multilateral mechanism for digital sequence information. (22:05) And to say, hey, let me try this out for, let’s say, for some organisms. Let’s create standardized rules or just like notification systems instead of a permitting system or standardized agreements that a couple of countries choose to use together that will help to facilitate access, that will get us back to the original 1992 text and that will align us with where we’ve landed now in 2025.

(22:31) I mean, I don’t expect that the most sacred or the most important or endemic plants, let’s say, are necessarily going to find a brand new multilateral mechanism for the physical biological material. But I could imagine that for certain organisms, you know, for example, like for the microbes that are found in humans that are found in every human around the world, or for those things that get exchanged by the winds of the planet, right, where lots of seeds and dust are constantly moving around. (23:01) That we could say for certain kinds of things, let’s try new approaches to create a multilateral mechanism for genetic resources, for samples, and test out new options that give us more options than just the strict procedures of the Nagoya Protocol.

(23:18) And in fact, the Nagoya Protocol has these options built into it. It’s just they haven’t been taken advantage of yet. So Article 10 is the global multilateral beneficiary mechanism.

Article 8 is a number of facilitated access procedures for biodiversity, for food security and for public health. (23:36) And parties can choose in the exercise of their sovereign rights to explore those options and to test out new things, either individually or collectively with neighbor countries or in a region. And I very much look forward to pioneering or departing with others to put some of those into place.

(23:54) Yeah, it sounds like the multilateral approach will keep at bay bureaucracy and this slow machine that sometimes gets into play. And I guess that many of scientists are scared about it. But yeah, as you said.

(24:05) Yeah. And can I add on there, Christian? I mean, we shouldn’t forget these UN agreements under the CBD and under other UN fora, they are themselves multilateral agreements. It’s all parties coming together in consensus.

(24:20) The place that bilateral creeps in is this important recognition of countries sovereign rights that you can choose to run your country how you want to. But at the same time, like fundamentally, there’s this tension between multilateral and bilateral. There’s this sort of recognition that we want to do it all together.

We want to do it the same way. And then we want to have just our way too. (24:42) And that is going to be there no matter what.

Right. I mean, look at the United States right now. It is in and of itself the definition of bilateralism.

So these aren’t going to be solved overnight. But I am optimistic. (24:54) I hope before you get to retirement.

(24:56) Yeah, maybe. (24:59) If only I was 10 years old and I’d be much more optimistic. (25:02) Okay, you mentioned benefit sharing.

So we are not only talking about cash, right? Clearly not about cash. And can you give us just one real world example of a non-monetary benefit that done right can make the difference for society or for local communities or for countries themselves? (25:34) I only want one. I mean, there’s so many and a lot of them are very dear to my heart.

I mean, I would say I have a favorite pink and gray sweater that I wear. Sorry, it’s not sweater scarf that I wear in the winter. (25:54) That was given to me by an Indonesian PhD student.

We have like a birthday circle here at the Institute where everybody takes turns giving each other the gift. And so this young woman was here, you know, visiting from Indonesia, doing her PhD.(26:06) And ironically, this isn’t specifically a benefit sharing outcome.

So this young woman ended up doing her PhD research, which I would say training somebody to become a doctor, to become a PhD trained scientist is a perfect example of a non-monetary benefit sharing. (26:31) However, the bad news in this particular example is that we were unable in the course of her PhD in those first years to get the necessary ABS permits from her home country. So she ended up doing her work on Colombian samples.

(26:48) And, you know, this is a sort of tradeoff, like that’s the non-monetary benefit, which is the training of the scientists, you know, here in Germany with our infrastructure, with our facilities and with the collaborative, you know, community of many international scientists working here. (27:06) The downside is that, unfortunately, she couldn’t study her own native material. And so I’m always really captivated because she was a lovely woman.

And like I said, the scarf reminds me almost daily in the winter of that kind of gift that she gave. And also of this sort of, you know, give and take that we have still in this system. (27:32) Thank you.

It’s very personal and very touching somehow. (27:39) So you talked a bit about, you already mentioned the CALI and the new measures to make basically company paying for the data they access. (27:52) And indeed, sometimes there is some joke made around about the future sequence police.

Basically, the options that were drafted at the last COP meeting in CALI may feel a bit as a police of the formal authority to scientists. So what does exactly CALI proposes? (28:14) Yeah, so CALI, just to be clear, is a city in Colombia and it was the host city of COP 16. (28:21) And the agreement at CALI on digital sequence information has a number of components.

(28:29) And included in the decision on digital sequence information are rules, proposed new rules, for databases that have genetic data in them, that have digital sequence information in them, to implement these rules in order to be compliant with the new CBD decision. (28:55) And this is where this sort of like database police question has come up. (29:01) And one thing that we were most concerned about during COP, as everything was being negotiated, was to what extent databases would need to police what sequences were uploaded into databases and whether or not they would need to be doing legal compliance checks, basically a brand new checkpoint under the Nagoya protocol.

(29:26) And the good news is that that did not come to fruition. That language that was proposed was edited and modified to what it now currently is, which is that databases should request the submitters of data, and I don’t have the exact language in front of me, that they are allowed to share this data publicly. (29:46) And that’s much different than saying a database needs to check every single piece of data that comes into the database to make sure that it is legally compliant with all possible national, international laws.

Genomic Connection #3 – DNA Metadata and FAIR Play

Kasia Fantoni — Thu, 19 Jun 2025 09:55:11 +0000

In the third episode of Genomic Connections, Christian and Kasia chat with Joana Pauperio, Biodiversity Project Manager at the European Nucleotide Archive, in the European Bioinformatics Institute (EMBL-EBI). They discuss the concept of “metadata,” why it is crucial to ensure high-quality research, and some best practices scientists should follow to ensure the data they produce is FAIR—Findable, Accessible, Interoperable, and Reusable.

You can listen to Genomic Connections on Spotify and PocketCast. The RSS Feed is available here.

The episode’s full Transcript (AI-generated) is available below the credits.

Credits

“Genomic Connections” is written and produced by Christian de Guttry, Kasia Fantoni, Luisa Marins and Chiara Bortoluzzi.

Graphic design by Luisa Marins.

BGE is a Horizon Europe project funded by the European Commission, the Swiss Confederation and the United Kingdom.

The episode is licensed under a CC-BY 4.0 license.

You can listen to Genomic Connections on Spotify and PocketCast.

Episode #3 Transcript

Hey, Kasia, yesterday, I spent an hour at the airport watching identical black suitcases spin around the belt, and one traveler had to tape a giant pink flamingo to his handle. He arrived, he collected his bag immediately, and I continued playing like a joulet. Ah, I feel you well. Kasia: But this is an excellent metaphor, actually, in genomics, rich sample metadata is that Flamingo tag, a DNA sequence carrying specimen information, permit, code and preservation method leaves the belt all at once, and it’s highly traceable. A sequence without those details exists in scientific Limbo only and is set for lost property.
Imagine a groundbreaking biodiversity study making the headlines only for scientists to realize that the DNA records lack specimen information without those ties, the datasets fails every fair test. Future researchers cannot replicate the work or build on it, and months of field effort drift into the same scientific limbo, indeed, and for these reasons, today, we will explore how standardized metadata and fare principles turn raw reeds into fully ticketed passengers bags that can travel the world of research. Our guest works daily to attach those Flamingo tags before the flight takes off. I am Kasia Fantoni. I’m a Europe Community Manager, and I am Christian de Guttry, erga project manager, and you’re listening to genomic connections, a podcast about biodiversity and genomics. Let’s get started.
For this episode, we are joined by Joana Pauperio. Joana is a biodiversity project manager at the European nucleotide archive in the European Bioinformatics Institute. Joana works on biodiversity data coordination, and she especially works with the community, understanding their needs and supporting data structuring and submission to sequencing archives. She’s also involved in a number of projects and initiatives working toward fair biodiversity, genomics data and infrastructure linking Joanna is also the CO lead of the elixir biodiversity community,
the European nucleotide archive, also known as ena, is an open platform for the management, sharing, integration and dissemination of sequence data. Ena holds a globally comprehensive sequence record and is the European node of the International nucleotide sequence database. Collaboration together with the NCBI in the US and ddbj in Japan. Ena is managed and operated by the European Bioinformatics institutes, EMBL EBI.
Let’s get started in biodiversity research, we also hear about metadata. What exactly does it mean? Metadata? So metadata, I guess we can describe it formally as a set of data that describes and provides context to other data.
So this is probably not a very easy concept, because we’re saying data a lot. So as an example, if we look into specimen or sample metadata, when you use a specimen to collect information, could be some morphological information, could be some biological traits, the metadata would be the information that gives context on the sample, so what species it is, what it was collected, when that helps then interpret the data. So I guess that that’s a more easy to understand definition of metadata. Yeah,
okay, and give us the 32nd page. Why should anyone care about good metadata for barcodes or reference genomes?
Yeah, well, if, I guess, if we’re building reference information, right, if we’re producing barcodes and reference genomes, I guess the whole idea of this would be that this data that we’re producing is then used as reference in other studies in the future,
and so that we can actually use it. And for this to be useful, we need to have context, and that’s what all good metadata is about.
So with our barcodes and our reference genomes, we need to include information of what species they belong to. Otherwise it’s it’s not very relevant where we collected it, when add some biological information of the organism, and that will help us contextualize and the data.
Data and help in interpret, interpret the data. And the more relevant metadata we add, the more correct our interpretations will be, and the more useful this will be towards the future.
Yeah, if DNA is the book of life, metadata is kind of a sticky note left on the cover with three details must always be on that sticky note, so you can trust a data set.
I like your sticky notes imaging. That’s very nice. Okay, so I think
the three most important basic things are taxonomic identification. In this case, I mean, if we have a barcode or reference genome, we need to know the species it’s referring to, or at least something to put it in the tree of life.
Location of origin, where it came from, could be as simple as the country where it came from. The more information, the better date of collection, when it was collected, so you can put it on a temporal scale, I would say these three are the most important ones.
Yeah, it sounds like also metadata are kind of the, let’s say, legacy for the future researchers that would like to reuse the data from public repositories. Yes, and nowadays, we hear all time that scientific data and metadata should follow the fair principles, meaning they should be findable, Accessible, Interoperable and reusable. Could you explain what this mean in practice and how this principle have improved your worked? Your work. Okay, so this, this is kind of a long one, I guess, because there is a lot of things so,
so maybe let’s, let’s break it down a bit. So the the F and fair is all about findability. So if we want the data to be findable, we need to have it again, have this rich metadata that we have been talking about before,
and we need this metadata to be indexed, to be searchable, so that people can find them when the data is stored. And also very important is that we should use persistent identifiers, so IDs that we attached to the data
or metadata, and that allows people to find it more easily. So you know, if you use that ID, you will always find it
accessibility.
It’s all about having a communication protocols that are standardized, having data open, allowing for authentication when things are needed, and making sure that the metadata is accessible again. It also connects with the findability. Interoperability is more about communication. So communication between databases, communication within machines. So we need to make sure that the metadata as it is put in is readable and understandable by both people and machines. So we need to use languages that are standardized. We need to use languages that are broadly applicable, and we need to have these links between things. And then the last one, the reusability is, is a little bit of all that we talked about until now. So we need to have rich metadata. Again, we need to have things open, and we also need to track provenance of the data. That’s also very important thing about reusability, and again, the standardization and the meeting the standards that are built by the community. How does this help my work? Or how does this influence my work? I think
the work that I do, which is mostly interacting with the community and making sure that we can help them make their data available, being guided by these principles, help us in this communication. It helps us also understand what we need to do to make things better for the community and how we can help them actually make them Data Fair. So I think these are guiding principles that we should follow.
Thanks a lot, Joanna and talking about communities and serving communities. So,
within BGE, we have two communities, and one is the barcoding DNA barcoding one which relies on like and DNA barcoding relies on short reads while reference genomes run on gigabytes. So how do you manage single.
Metadata model that serves both communities. So the communities are different, but they are they overlap quite a bit, and there are, though, there are metadata that is specific to some of the methods and to some of the pipelines that are used in both communities. A lot of it is
of overlaps. So
if we look, for example, at sample metadata, they all all of these analysis rely on specimens or in organisms or in samples, and the differences actually, in this case, will be more from where the sample originates, and not so much the type of analysis that we’re going to do with it, in this case in terms of short reads or long reads,
because, for example, if a specimen comes from, it’s freshly collected. We have much more information that is available on them because we’re collecting it now. If it comes from a museum, then the information that we have there may be a little bit limited, because it was collected in the past. And sometimes we have to adjust the way that the metadata is collected so that people are aware that in some cases we have more information available. In other cases, we have less information available, and that’s the kind of exercise that we have been done doing in this project. So trying to understand, trying to map what metadata can be collected, and trying to adjust it to their specific needs. So I guess that’s what you could call a single metadata model that has some specificities for the different communities, but, but that there, these are maps so we can
come from one to the other one, I guess.
Yeah, it makes sense. You repeated the word collected, collected several times. When you talk about collection, I think about people going on the field, especially in these two communities. And when you go to the field, sometimes you have a piece of paper and a pencil to collect the metadata. That has to be extremely precise. So I think that common mistake always happen.
Could you describe a true metadata nightmare that you experience something that happened to you or that you witness in the past, and are there any guidelines to avoid such errors? If we’re calling it a nightmare, that’s quite strong.
I guess thinking,
I guess the worst, or one of the worst things that can happen is that you, I don’t know, swap IDs between specimens when you have the data. I think that’s the worst case, and that has repercussions, because if the data is submitted, then you will have to cancel some of it, or you’re going to have to update it. Sometimes it’s difficult to track back where the error was, so that causes difficult errors to
solve.
And I think I mean, the way to solve these type of errors is always be very careful in tracking the data and try to be very precise, as you said, in terms of the data collection and also all through the processes for lab analysis and data
analysis, and I would say there are a lot of other smaller and calmer errors with for example, sample coordinates, dates, some of them can be easily identified. Some are very difficult to understand that it’s actually an error. It needs to be the researcher that actually spots it and often also what we see aren’t exactly errors, but it’s more like difficulties in providing information in the needed format so that is better to interpret. For example, when referencing to a specimen, people usually, and if specimen is kept in a museum,
people usually provide the ID, but sometimes the Id only is not enough. Within an institution, we have some guidelines on how to provide that, but if people don’t follow those guidelines, then it becomes difficult to do these linking and for the metadata to actually be useful. So I think there’s different levels of errors and different ways of getting around them and having a good metadata collected. A question on top of this that I’m curious about your opinion. So do you think that some of those mistakes that we as researchers made are made because we don’t give
to metadata the importance that they need
still today in our community, is this increasing
the value of the metadata, the perception of the value of the metadata, or we still have a lot of work to do.
Uh,
okay, so I think the mistakes don’t necessarily come from the lack of importance. I think some mistakes are are some mistakes are just bad mistakes, some, some may come from the lack of knowledge of I mean, you, you may know that metadata is important, important, but you may not necessarily know how to deal with it and how to provide it. So one thing is to collect it, the other thing is to put it out there for the public. So I think there’s still a lot of training needed in this sense, and a lot of communication towards the researchers. I do think there is an increasing awareness of how important metadata is, not only for your own study, because I think that the researchers are usually aware, but also for the future that you don’t. You don’t need to just make your data available, but you need that context too. So I think that’s increasing, but there’s still work that needs to be done there.
So talking about the future and metadata that will get to the future,
imagine that in 50 years, somebody will reuse that assets that you worked on. What do you hope that future scientists will be able to do because of the metadata that was rock solid?
So if my metadata is rock solid, that would be great, and if I’m able to link it appropriately so metadata with data and different data sets by using the persistent identifiers, then I would expect first that future sciences will be able to find and access it. I think that’s the first thing they would need to find it.
Then, I guess because they are able to understand its context, because it’s very good metadata,
they could do a lot of things. I mean, they could be analyze it with innovative methods, still with AI, like very advanced things. They could make predictions, analyze trends. I guess everything is out in the open to be done.
Yeah, yeah, I agree, but today, many labs are still afraid of data entry. Days. Have you discovered one practical trick or tools that turns metadata capture from an adic into an habit like wizards or electronic field notebook or something like this.
So I don’t think that there are magic tools that make metadata collection like completely hassle free. So it is, it is something that requires work. Could be made simpler, could be made more difficult, depending on the way we do things, I would say planning ahead is my first advice. So understanding what we need to be to collect or to capture, where we will share this information, what are the standards that we need to use to be able to share this information? That’s the first step. And then, I mean, there’s, there’s a lot of tools that can help you, there’s some apps that help you capture data from the field that they already validate information to standards. There are brokering systems so so tools or groups of entities, groups of people, that help people actually validate this metadata and then make this public. So there are a few things that exist and that can be used, but I don’t see yet a likely magic tool or a single thing that can be used for it.
Oh, that’s a pity. Okay, but then
going back to the two communities, erga and Ivo Europe,
can you share one good practice that barcodes could learn from Genome builders about metadata and vice versa? Well, I think this one is a bit difficult, because I think both communities have been evolving together and improving their metadata
practices together,
maybe thinking on things that so things that were crossed over between the communities. I think the barcoding community also always had a sense of the importance of the specimen information and vouchering to link with the barcodes. I think that was something that passed on into the genome builders that this is always very important.
In terms of referencing, and then maybe in terms of the genome community, they started early understanding that they needed help with their metadata and setting up brokering systems. So this is tools that help people validate the information after it is collected and before it is shared. And I think these this is a good example, also that the barcoding community may follow. So I would say probably these two things can be used as example, but they are the communities are working together and evolving together in this aspect.
Fantastic
and now a personal twist. Let’s say, if you could tag one fictional character as the metadata manager for the day, who would be and why everybody’s allowed.
Okay, my first thought was Spock from Star Trek.
So he’s very rational, very thorough. He has a lot of analytical skills. He’s very committed. I mean, he needs to do that. He does that. So I think he would be a good metadata manager.
Then I started thinking a little bit on fairies, because they could do some magic in some of the processes to make them easier. Those would be my Yeah, my suggestions. Okay. Thank you very much today,
this podcast is brought together by biodiversity, genomics Europe, Project founded by the European Union, the Swiss Confederation and the United Kingdom.

Genomic Connection #2 – Tech for Biodiversity: The role of DNA sequencing

Kasia Fantoni — Wed, 14 May 2025 13:48:41 +0000

In the second episode of Genomic Connections, Kasia and Christian are joined by Claudio Ciofi, Professor at the University of Florence (⁠UNIFI⁠) and founder of the Florence High-Throughput Sequencing Facility.

They ask Claudio about the many ways DNA information is empowering biodiversity research and improving conservation outcomes, the top methods and technologies for obtaining high-quality genomic data, his first-hand experiences working in the field to collect samples from fascinating species such as Komodo dragons and Galápagos tortoises, and, finally, his vision for the future of the rapidly evolving field of biodiversity genomics.

You can listen to Genomic Connections on Spotify and PocketCast. The RSS Feed is available here.

The episode’s full Transcript (AI-generated) is available below the credits.

Credits

“Genomic Connections” is written and produced by Christian de Guttry, Kasia Fantoni, Luisa Marins and Chiara Bortoluzzi.

Graphic design by Luisa Marins.

BGE is a Horizon Europe project funded by the European Commission, the Swiss Confederation and the United Kingdom.

The episode is licensed under a CC-BY 4.0 license.

You can listen to Genomic Connections on Spotify and PocketCast.

Episode #2 Transcript

0:01: A friend of mine convinced me to buy a DNA test kit, you know, , one of those where you spit and send the sample to the company.

0:11: Oh wow, so you’re going to learn the secrets of your ancestry at last, right?

0:16: Yeah, I’m tempted, but then I started wondering what’s actually going to happen with my sample once I mail it off and who is going to do the sequencing and keep the data.

0:29: Yeah, that’s a great point, but you know that sequencing isn’t just about ancestry kits.

0:33: In biodiversity genomics, we rely on professional sequencing centres where samples are processed and managed similar to a high-tech lab in a movie.

0:42: Yeah, exactly.

0:44: And that’s what we are exploring today.

0:46: Why these centres are so important, how they handle thousands of samples at a time, and what makes them special in our field.

0:53: So in other words, we’ll get the insight scoop on how a sequencing centre works.

0:59: I am Christian De Gutri, URA project manager, and I am Kasha Antoni, AO Europe Community Manager, and this is Genomic Connections, the podcast about biodiversity genomics.

1:14: For this episode we are joined by Claudio Shofi, professor of ecology and molecular ecology at the University of Florence in Italy.

1:23: Claudio has had a truly international career, including operating his PhD in the United Kingdom and two postdoctoral appointments in the United States.

1:33: Still today he keeps intense international collaborations.

1:36: Indeed, Claudio co-founded the European Reference Genome Atlas ERA.

1:41: And he is also part of the coordination committee of the Biodiversity Genomics Europe project.

1:47: Both of them are particularly dear to our podcast.

1:51: Also, Claudio holds special collaboration with Indonesia on reptile conservation biology and genetics.

1:59: At the University of Florence, Claudio set up a molecular genetics lab focused on wildlife conservation, and he also founded the Florence High Throughput sequencing Facility.

2:10: The university itself is one of Italy’s largest and most active public research institution.

2:16: It takes part in a lot of important research projects, both nationally and internationally, and it offers more than 140 degree programmes across all the main disciplines, making it especially appealing to students from abroad.

2:31: But after this huge advertisement, most importantly, who would not enjoy a visit to Tuscany?

2:37: But OK, let’s get started with the, with our questions.

2:45: Claudio, why it is so important to use DNA in biodiversity research, be it barcoding or reference genomes.

2:56: Well, Christian, this is, , that is a, , a perspective that I generally bring up to my, , students in, , conservation genetics and also molecular ecology classes.

3:09: , in fact, there are a number of, , , questions that cannot be answered or resolved or are very difficult to resolve, , using, , standard ecological, , methodology.

3:22: , for instance, how do you assess the level of biodiversity of an area or, , how do you assess the presence or, or the absence, , of a species, , being that species a rare one or an invasive species that, , say just arrived in a region.

3:40: You might want to go and use, , a classical ecological techniques in which you, you go and try to , capture a species in the field or you can go for noninvasive sampling, , so, , go into the field and collect, , , part of, of an animals had had been left in the territory.

4:07: And use these, , these non-invasive biological samples like for instance, a, a bunch of hair or a faecal samples, and classical non-invasive sample samples, and you extract DNA from these samples and From this DNA you can basically characterise a sequence of DNA, a barcoding sequence, OK, which is which is species specific, which tells you which species that samples belong to.

4:38: And this is a very, say very important aspect of, of barcoding.

4:45: So to identify a Particular species in a in a territory without seeing the animals at all and that’s that’s important again for species that are very cryptic or elusive or or invasive species that have only just one individual that just arrived in a particular area of interest.

5:04: With the same methodology which is, which is called generally meta barcoding and the world basically.

5:11: Is kind of self explanatory.

5:13: You can use environmental samples and so samples like of water or of soil you extract the DNA from these samples and then in this DNA you have all the genomic components of the of all the species that have been.

5:32: They have been or are living in that, in that area and that left a tiny particles of their body in the in, in, in the terrain or or in the water, OK?

5:45: And so we extracted NA from, from these from these environmental samples and you can then with the with novel, , 2nd and 3rd generation.

5:59: , sequencing techniques, , you can have an idea of how many species are in that area because, , you can identify the, these, , , species specific, , barcode, , DNA, , that belongs to the species that, , that live in the particular territory.

6:23: So with, with barcoding and meta barcoding, you can identify species and, and describe biodiversity in area, , most of the time much quicker than you can do with classical ecological techniques.

6:37: I mean, the methodologies are, , they complement each other.

6:41: It’s not that the, the one is, is better than the other.

6:45: But, , molecular genetic techniques basically have proven to be very useful to say improve the knowledge of the biodiversity of a certain territory, something that now is required by by the European Community, for instance, to the to the local authorities, particularly in Italy with genomics on the other hand, you go.

7:07: And assess in first say the the evolutionary history of the species, how a particular taxa say have colonised the territory and how it disperse in the territory.

7:18: So describing movements of individual is important, say to .

7:23: Assess for instance connection among populations and say see for instance whether ecological barrier exists and this is important for assessing whether restored, for instance, ecological corridors actually function, OK, in the restoration in restoration ecology.

7:44: Describing movements of individuals is very important.

7:47: Again, you can, you can do that by using classical ecological techniques like, , for instance, GPS tracking, OK, or capture marker capture in which you capture the animal, you mark the animals, and then you again, you try to recapture the animal to see where it go, where it went.

8:06: , but, , that has some limitation about, I mean, the, , the effort that you had to, , make to, , to trap the animals and, , see whether you are, you are trapping and you are, , , collecting, , you basically, you’re marking the right ones that make, that, that do move, , from one population to, to the other.

8:29: With genetic, with, , with the, with the genetic and particular genomic, , , genomic studies, you can have, you can have information on the average number of individuals that per generation they move from one population to the other.

8:46: Again, and this is quite important to assess both, both the success of ecological restoration programme.

8:57: But and also to identify in this case, , how distinct and how isolated populations are OK, , this is important as we all know that maintaining a high level of genetic diversity in the population is crucial to assess whether this population is viable and then determine whether.

9:22: , this population, , is, , is prone to extinction or not.

9:27: high, high level of genetic variability bring with itself, a good chance for the population of survival, a low genetic variability can basically lead to physiological, morphological, , , defects, you know, and, and then, , increase the risk of extinction.

9:48: So.

9:49: Maintenance of genetic diversity is important also to see as we know to respond to climate and therefore habitat changes and assess whether say dear mutations exist that may imperil again the survival of the species.

10:10: To make things a bit more tangible, , you know, people often want to know, , about real life, real world impact.

10:21: , do you have any success or intriguing story for both barcoding and genome that you can share?

10:29: I’ve been working and I’m working on, , on, on tropical species.

10:33: Yeah, I’ve been working on, , on giant Galapagos tortoises and, and, , and I.

10:38: Keep working on Komodo dragons in, in southeastern Indonesia and for both species which are of conservation concerns, one thing that genomic has served in particular.

10:56: Was the again the identification of of conservation of management units for conservation, OK, something that that both barcoding, so the characterization of, of single DNA sequences and a more comprehensive view of the genome have .

11:23: Have helped us to do in on in the Galapagos tortoise, for instance, , you know, the Galapagos tortoises are found on different volcanoes in Galapagos Island and there is.

11:37: A centre in Santa Cruz in the island of Santa Cruz where these animals are bred in captivity and these tortoises, some of these these tortoises come from from parents which origin was unknown comparing basically the the genomic signature of each young tortoise with the genomic signature of white population.

12:07: , the centre can basically, , choose, , which population is the most similar from a genetic point of view and therefore can basically translocate or reintroduce the particular individual to the population of origin and these assessment, the assessment of the different.

12:24: In among the national population has improved with genomics from single locals to multi-locals to genome wide say comparison of national population in a similar way we are working in in in Indonesia.

12:42: There is, , within the, the range of Komodo Dragon, , which is in, in the archipelago of Komodo National Park and the Island of Flores in the southeast, southeast Indonesia is about 500 kilometres east of Bali, , north, say, , a bit north of, , of Darwin in Australia.

13:03: , in this, , in this archipelago, , you basically have 6, different island population in one, in one island, , these species went extinct in the early 80s and because of because of pushing of its main prey, the Timor deer.

13:27: , since the establishment, basically of of Komodo National Park, the deer has been reintroduced, and the, , Indonesian government, , wanted to know whether these the predators, the Komodo dragons could be reintroduced as well in this island.

13:42: And again, knowing the genomic structure of the, , the, the, the extant populations, , it was very important to determine.

13:55: If we had to, we were to choose individuals from the from the national population which individual we had to choose to create a new population for introduction so that the genetic variability of this population is high enough to have a a high chance of survival in the generation to come and for these having a.

14:17: A comprehensive view of, of the genomics of natural population is very important for in this case, reintroduction purpose and in the case of Galapagos Island for demographic reinforcement, let’s say, purposes.

14:35: These are fantastic stories, Claudio.

14:37: So basically, if I understood correctly with barcoding, you go there, you identify the species, and then with the reference genomes or whole genome sequencing, you then can study on how to better protect them and in the meantime, studying their history.

14:54: And that’s fantastic.

14:56: So you mentioned that now genomics improved a lot, these practises, and we know that genomics is closely linked also in its definition to the technology.

15:07: We hear much about the new tech like Oxford Nanoor, Pack Bao and high C sequencing.

15:14: So while all of them are excellent tools to enhance biodiversity genomics, what’s the one that made you go, wow, Oxford Apo, , And specific bioscience, , technologies are complementary techniques.

15:31: Oxford Nanopole provide long, , very long stretches of information on very long stretches of DNA, , and, , see bioscience techniques provide information of long stretches of DNA a bit shorter than oxo nanopore but with a slightly higher quality, OK.

15:52: Then you have these methods on the, the high C metals which are metals basically to capture to understand chromosome conformation and and then characterise they say the number of interaction between genes that may be separated by many nucleotides in the, in the linear genome.

16:13: And, and this again a method that complement the long long re technologies to describe chromosome level genome.

16:24: , among these techniques, the first that we used and we, , have been very excited with, , was indeed the second one.

16:34: So the one, provided by, , by, , Pacific Bioscience.

16:39: I don’t want to make any advertising advertising here.

16:42: I’m just saying that.

16:44: Generally labs that are relatively young laboratories, OK, they and they they have no they have some limits budget wise they generally are forced to choose one techniques or the other at first they can they can’t afford to buy all platforms that are on the market so we focused on.

17:07: On the pack Bao, , mainly, , because of high quality of the, , sequences that this technique, , provide, we started from Sanger sequencing in our lab, , which provide very high quality of DNA sequences then we moved to the .

17:28: To the short rate sequencing which is basically the the lumina or sequencing by synthesis techniques, OK, which again has a very high quality of provide very high quality of DNA sequencing but characterising short rates of DNA.

17:46: And pack Bao basically gave us the opportunity to look at DNA with the same amount of accuracy or or or very similar to the amount of accuracy that you can that you can get with the lumina sequencing so with the with the sequencing by synthesis technique.

18:08: With all of this, it means like that there are samples which are stored, , preserved somewhere, and indeed we know that biobanking is essential to keep the samples fresh.

18:21: If the future scientists were to discover one of your stored samples 50 years from now, what do you hope or wish they could learn or do with it?

18:32: We, we do take advantage now, no, of the, of the reconstruction of genetic structure.

18:37: of extinct population using museum samples or biological remains.

18:43: , this has been done again same example with Galapagos tortoises where bones of, of dead tortoises have been found on islands where these species, .

18:58: , went extinct and from these bones, , DNA was extracted and, and, and with that we were able to basically to reconstruct the degenerative structure of an extinct populations.

19:10: And again, this is important for reintroduction, reintroduction purposes.

19:15: , so I, , something that, , the samples that we have now say in the, in the ultra freezer.

19:24: , again, can be used basically for similar purposes.

19:30: So to compare the genetic structure of current populations to the genetic genomic structure of the population will, which will have survived in 50 years from now.

19:43: The difference is in 50 years they will be able.

19:46: , for sure they will be able to to to make a much better prediction on population viability and survival potential that we are able to do now based on, on, on the, on this comparison.

19:59: So comparing the genetic structure of ancient population.

20:05: A population that 50 years ago with the genetic structure of current populations, one can make prediction knowing the difference in this genetic structure, , and genomic components make prediction on the viability and the, the, the chance of surviving on this population with The tools both genetic and bioinformatic tools that we will have a disposal in 50 years from now, I think that this prediction on population variability which will be much, much better and much, much improved respect to to to the present.

20:49: Thank you, Claudio, and let’s hope that the technology will give us other views of the DNA compared to what we have today in 15 years.

20:58: Maybe only one click or one picture would reveal the species’ DNA.

21:02: Who knows how things will go in the future.

21:06: , so now what regarding your lab, could you give us a sneak peek at what’s the next big thing in the horizon that you can’t wait to tackle?

21:16: Perhaps the possibility of analysing genomes with the same speed and ease with which we now analyse single or multi-locus part of the genomes.

21:34: , analyse genomes for say hundreds of individuals, , , , again with, , with the same, .

21:45: Economic and logistical and equipment possibility that, that we are using now to, to analyse to, to do multi-local assays or reduce representation or using reduced representation techniques.

22:00: , particularly for say subtleties of the genomes that make a small population surviving, , heart condition without say going extinct.

22:12: OK.

22:12: Now, , we can do this with pos with economic and, , facility, , possibilities, possibilities that we have, we, we, we can do this.

22:24: With tens of a few hundreds of individuals, but the, the, the, the vision here is to, is to enlarge this to, to make it easy to, to, to, to characterise the part of the genomes for hundreds of individuals much easier than we can do now basically.

22:44: And, , from the lab, I would move to the field and I ask you, what happened?

22:52: What’s the most unexpected experience you’ve ever had while sampling like some sort of Indiana Jones moment?

23:01: Well, I can’t say with cargos tortoise because they’re quite a timid animals.

23:06: , I will have to think, , something about Komodo dragons.

23:11: , and, , The, the, the, the, these, these animals are generally very shy and wary of human beings, OK.

23:21: Although tourists now that goes to to specific part of Komodo National Park, they are used to see these animals resting on the ground or basking, , , and they see not, not to be bothered by, by, by humans.

23:39: , they are.

23:40: Basically just used to the presence of humans, but these are just a very tiny proportion of the number of individuals that one can find in Komodo National Park.

23:49: And I remember in a, in a, in a, in one of the smallest islands on the southern very southern part of the part that overlook basically the south, OK, , Timor and then Antarctica basically, , , in these islands, these, these Komo dragons have never seen a human being.

24:10: , so we, we expected these animals to be very, , very difficult to find, very difficult to capture, , very difficult to see.

24:20: And while we were walking, , I remember on a trail that we were, , the, the, the, that, that we that we did, , , cut, , , across the, across the, across the tropical forest, we at a certain point, all of a sudden and basically we notice a, a, a relatively large dragon aiming for us running down the hill.

24:47: , aiming, , against us, and I basically stopped, , wondering what what is this guy doing, .

24:57: Don’t you see that we are humans, , we are not something to eat.

25:01: Probably he, he or she confused us, , for deer, , because the size basically of a Timor deer is the same size of a, , of a, of a person which is seen, , which, which is, , , seen from uphill, .

25:22: And, and in fact, after basically when, when this animal arrived approximately 3 or 4 metres from us, suddenly stopped, , gazed at us, looked at us for a couple of seconds, turned around and then run away.

25:37: So that was the, , , one of the one of the occasion in which we were basically actually attacked by these by these species.

25:49: But, , , this piece is basically these animals didn’t realise what we were.

25:56: We were the what the he or she was basically confusing us as a prey that we were in a play but actually human being in that in that case are kind of.

26:07: , top predator as they are.

26:11: Well, fantastic.

26:12: That’s a fight or flight situation that you experience.

26:18: OK, let’s move on to the, to the last question.

26:20: So before we wrap up, if you could have any historical or fictional or contemporary character as your intern in your lab in your sequencing centre for a week, who would be it and why?

26:36: It, I, I don’t think it will be someone technical, say someone that knows about techniques, let’s say in the lab but some more some someone that could inspire, say.

26:51: Our, our conservation work in general, I would think of, , , say scientist or conservationist who has inspired me during my, , academic career as well.

27:06: , Gerard Darrell is one of these.

27:08: , Gerard Darry was a, you know, a British naturalist, , writer, a conservationist, and Was the one basically who envisaged the first zoos that’s not just a showcase for the public, let’s say, but it was aimed to captive breeding and reintroduction of endangered species into the wild and that inspired me quite a lot so .

27:34: , conservation biology and conservation genetics were in their infancies in the late 70s, in the, in the, in between the late 70s and the late 80s.

27:49: And Darl was one character which basically inspired my, my, my career, basically my studies.

27:59: Also, , Michael, Michael Sule, , , he is, , he was an American biology.

28:08: He, he died a few years ago actually, but he’s mainly known for his work promoting the idea of conservation biology.

28:15: , he was the co-founder of the first, , and the first president also the Society for Conservation Biology.

28:22: So, , , scientists basically that.

28:26: Won’t help us in the lab actually but will mainly help us to have a vision basically for the future for conservation of, of, of endangered species in general.

28:37: Thank you, Claudio.

28:41: This podcast is brought together by Biodiversity Genomics Europe, a project funded by the European Union, the Swiss Confederation, and the United Kingdom.

Genomic Connection #1 – Introducing Genomic Connections: A podcast about Biodiversity Genomics – Frozen Futures

Kasia Fantoni — Thu, 17 Apr 2025 12:05:34 +0000

Within the Biodiversity Genomics Europe (BGE) project, we’ve been collaborating with ERGA (the European Reference Genome Atlas) on “Connections,” a series of blog posts dedicated to Biodiversity Genomics that are published monthly since January 2025.

Now, “Connections” has also turned into a podcast, “Genomic Connections,” further expanding ways to reach our audience. We will release an episode of “Genomic Connections” per month, starting in April 2025, and here you can listen to the show’s trailer. Each episode will explore a different step of the genomic workflow, always highlighting the many connections between the two communities and the advantages of joining forces for better outcomes for biodiversity. For each “Genomic Connection” episode, the podcast hosts Christian de Guttry (ERGA Project Manager) and Kasia Fantoni (iBOL Europe Community Manager) interview experts who help boost genomic science and infrastructure in Europe: the challenges they face, the innovations they develop, and the impact of their work.

You can listen to Genomic Connections on Spotify and PocketCast.

For the first episode of Genomic Connections, “Frozen Futures – The role of Biobanking in Biodiversity Genomics,” Kasia and Christian are joined by Jonas Astrin and Camilla Di Nizo from the Leibniz Institute for the Analysis of Biodiversity Change (LIB) to talk about the essential role of Biobanking.

The episode’s full Transcript (AI-generated) is available below the credits.

Credits

The episode is licensed under a CC-BY 4.0 license.

“Genomic Connections” is written and produced by Christian de Guttry, Kasia Fantoni, Luisa Marins and Chiara Bortoluzzi.

Graphic design by Luisa Marins. Postproduction by Kasia Fantoni.

Biodiversity Genomics Europe is a Horizon Europe project funded by the European Commission, the Swiss Confederation and the United Kingdom.

Episode #1, “Frozen Futures” Transcript

Kasia:

Oh, Chris, I had a bit of a rough return home because my fridge broke. Luckily, most of the stuff inside didn’t spoil, but I had to throw some tiramisu leftovers in the trash.

Christian:

Oh, yes, that sounds like a rocky welcome home. And while it’s horrible that you had to throw out your tiramisu, it’s good that most of your food didn’t spoil,

Kasia:

yes, indeed, it mainly was food that wouldn’t risk much deterioration,

Christian:

Good for you; differently from your food, the samples Biogenomic Europe work with are very sensitive to outside temperatures, and would have suffered way worse than your tiramisù.

Kasia:

Indeed, we need to store them very safely and as soon as possible, to make sure that they preserve their genomic information. And that’s where biobanking comes in. In today’s episode, we will talk about bio banking with Jonas Astrin and Camila Di Nizo.

I am Kasia Fantoni iBOL Europe Community Manager,

Christian:

I’m Christian de Guttry, ERGA project manager, and you’re listening to Genomic Connections, a podcast about Biodiversity Genomics.

Kasia:

For this episode, we are joined by Jonas Astrin and Camila Di. Both of them are from the Leibniz Institute of the analysis of biodiversity change in short, LIB. Jonas Astrin is the head of the section and curator of the biobank of LIB and he is also responsible for the strategic development of the biobank. He is also active in various biobanking networks such as the global genome biodiversity network and the International Society for biological and environmental resources. Jonas is also engaged in biospecimen research. Camilla di Nizo oversees the cell culture lab at lib and there she manages daily Sample Acquisition. Her work includes developing protocols for obtaining cryopreserving cells from non model species and conducting karyotype analysis where needed.

Christian:
LIB was created by joining forces between the zoological research Museum in Koenig in Bonn and the Museum of Nature of Hamburg. So this organization is dedicated to studying how biodiversity changes over time, supporting conservation effort and sharing knowledge with the public. The Lib biobank stores many kind of samples, including DNA from animals tissues, living cells, small organisms and even environmental samples in liquid nitrogen at minus 190 degrees Celsius, and personally, I find it wonderful to know that these samples and the associated data are available for researchers

worldwide.

Kasia:

Fantastic. Let’s get started. So bio banking can sound like a fancy cold storage system in your own words, what is so exciting about it and why it is so critical for Biodiversity Genomics?

Jonas:
Well, hello, thanks for the question. And yeah, why is it exciting? If you are a nerd, it definitely is exciting because science is exciting to nerds. If you’re not a nerd, then you should tune out, probably, but being a nerd as we are, bio banking is great because it enables science. You can do some proper scientific research, at least at the molecular level, without having biobanks. Biobanks make research repeatable in a way, because they archive the samples that have been used, you can prove the research wrong using those samples. You can repeat the research, and as long as we have the material, the collection, that can be accessed over and over again. Bio banks are just one component, because you also have morphological collections, as we call them, where the whole animals are usually stored, or, yeah, parts of the organisms at least, that can help identify them. So yeah, apart from repeating or making science repeatable, biobanks also make it possible to expand on previous research, so you can use specimens that have been amply described or analyzed and the results published on them, and use them in another context. And this just grows the knowledge net and makes knowledge or makes the samples more meaningful every time they are reused. Also you can completely or base completely new studies on the material so it’s more sustainable. You don’t have to go out and recollect every single time and just use the material that has been already collected and. And use that in new studies.

Christian:

That’s wonderful. So basically, for what I understood, biobank, biobanks are a legacy for the future of research, and we mentioned before that within the biobank, you can also store DNA at those super low temperatures, and we often talk about DNA as the book of life. So if your bio bank were a library, how would you describe your cataloging system and the rail collections you are most proud of?

Jonas:

Okay, so that’s yeah, two parts of the question. Our catalog that we have is not too different, different, actually, from a library catalog, although, strictly speaking, we would rather be an archive than a library, because a library has copies of the same media that exists several times, and everything that we have are unique objects, so more of an archive of life, and yeah, the catalog is a database that’s maybe not too exciting to look at if you’re not a nerd in another area and in the data area, but it enables a lot of data sharing. This database is structured by common data standards, and we deal out the data to both our own portal at the lib website, and to the ggbm the that is the global biodiversity biobanking network. That’s an aggregated aggregator site where lots of different biobanks from throughout the world show their data and make it accessible. Yeah, the second part of the questions, a question about our holdings. So we have, in general, generally speaking, we have mostly animals. We have also quite a few environmental samples, like sediment samples or filtered water samples. But from those animals, it’s mostly vertebrates and arthropods, insects, spiders, crabs, etc. In terms of material, it’s either tissue or cells or DNA and yeah, regionally, they come a lot of them, our samples, come from Central Europe and particularly Germany, mostly probably based on the fact that we have been working in the German bucker life project for over a decade, and has accumulated lots of samples regionally. And it makes sense to structure collections regionally. But we also, through other projects, have lots of samples, for example, from the Caucasus area. We have quite a few samples from Africa, few from Latin America and basically worldwide, where we collaborate with lots of different partners. The most exciting sample, I had to think a bit about it, but I think I would say maybe a wooly mammoth. We got a hair sample from a wooly mammoth that was came from the permafrost and Todd, and we were able to extract DNA from it and did a DNA barcode on the mammoth. So if you see a hairy elephant walking around and want to snatch a hair and DNA barcode it to make sure it is a wooly mammoth, you can compare it against our data.

Camilla:

Yeah, can I compliment a little bit and talk about some other special samples that we We are also proud of? So we had sales from the Soho dove, which is unfortunately already extinct in the wild, as well as other critically endangered species such as the European eel or the yellow crested cacao or the Madagascar spider tortoise. And some of these species are still poorly known, despite their threat in its status, which we believe that’s very important to have this in our collections.

Kasia:

Thanks so much both. It seems like you need a lot of technological advancement and technology and technology, generally speaking, to preserve all these very precious samples. And we know that technological advancement is running pretty fast. So is there any recent innovation on storage methodologies that made you think like, this is the game changing methodology or technology for bio banking?

Camilla:

Well, I think what we consider an innovation in our bio bank is the recent creation of our cell culture bank. Although it’s not a it’s a an old technique. We only recent people are realizing the importance of archiving sales due to the range of possibilities that sales provide. It because cells can carry identical copies of the genetic information, giving high quality material for genomic studies, which is particularly reported nowadays, doing due to the increase number of these projects. And additionally, because cells can provide chromosome information, we have observed a recent increase in interest in cytogenetic studies, which is also old, but now people, it’s becoming more popular because it’s complementing these genomic projects.

Christian:

I have the impression that the permafrost was our planet biobank for a long time, but now we are little by little, losing it. Unfortunately, I have a question about iBOL Europe and ERGA. So both rely on high quality samples, and we know that the cold chain is quite important for high quality sample, but these two communities, they do different kind of research. And how do you tailor if you tailor biobanking practices to meet the needs of these two communities?

Jonas:

So generally speaking, I would say that to be properly set up as a biobank will make will enable you to cater to all kinds of different communities, including the bar coding and the genome sequencing community. And there’s nothing special we need to do now to adapt to these projects. But you need a proper database. You need good temperature monitoring, ideally redundant temperature monitoring in your collections, you need good service instruments, and my take is that you would also need liquid nitrogen to to make sure that you have the best possible preservation, particularly for samples that go to the genome stream, and definitely for the cells that Camilla mentioned, and yeah, you also need to be in a network, and you need to be able to show your data through through portals like GGBN. For us, the situation is pretty good. We were lucky that we had been approved a new building that we’re moving into this year, and we have a big new cryo facility with lots of shiny, huge liquid nitrogen tanks that even our DNA goes into minus 190 degrees storage. So we could make sure that everything is really perfectly stored, and that helps for bringing samples in so we have cryo cards that move around and cryo pots that we can use to solve the samples, all at liquid nitrogen temperatures, and that helps with the cold chain that Camilla is now going to comment on, yeah.

Camilla:

Now what I wanted to comment is that having these standardized procedures for collecting, transporting, storing samples, applies to all genomic projects. So we we try to encourage, whenever possible, to have step frozen tissues or trying cell culture, because it’s two approaches, yeah, the high quality DNA for any Genome Project, either iBOL (Europe) or ERGA.

Kasia:

I think that when talking about bio banking, so we talk about storage, but also logistics, I think they play an important role. So we have different specimens coming from different region of Europe, at least to LIB so and what is the biggest challenge that you face when shipping or receiving samples, especially when we talk about remote out of permafrost or international locations?

Camilla:

Yeah, I think regarding the transport of flash frozen samples or frozen cells is very challenging, because not everybody has access to dry ice or a dry shipper with liquid nitrogen, especially if we are talking about collecting remote and bringing to the to the bio bank, to the lab and additionally specialized couriers are normally very expensive and subject to specific regulations, which makes more difficult, I would say, thinking about the cells. So transporting tissues to grow from the field, to grow the cells in the lead requires a specific type of medium with antibiotics to prevent contamination. And this can be an obstacle because it has to be kept at constant temperature, four degrees, not less than that. And also, in my case, what. Is a little bit challenging is that the time limit to process this, these samples, to grow the cells, so I have to process as soon as possible to increase the chance of having cells. So finally, it’s important to mention that we need all the pyramids, and this sometimes could be quite challenging, especially depending on the country

Christian:

To keep pace with time, we could discuss, we should discuss about artificial intelligence and machine learning that basically are two similar concepts. Do you think that this kind of technology, I mean, all of the genomic lab in the world are now thinking on how to apply these technologies to their own research. And do you think that this technology play your role in how you organize or monitor the specimen, or in any other aspects within your facility?

Camilla:

Yes, I we believe that artificial artificial intelligence would help us to ensure accurate sample tracking and prevent misleading for example. Also, we think that in the future, we will benefit from AI to the text, sample contamination, degradation, cell viability. So

the so far, we don’t foresee that much need, actually, because lots of stuff is done manually and needs eye control. So it’s also a risk to apply AI to an unlimited extent. So for bio banking, we’re a bit old school on that.

Kasia:

So do you know, like, there is a lot of thing going on, I guess, in your lab, but is, is, can you give us a glimpse of the road ahead that you have, for instance, if you have any be important milestone or project you want or hope to tackle at your biobank?

Jonas:

Yes, so an important challenge for the future of biobanking in general is to work towards the harmonization of biobanks and to grow the network, particularly biodiversity, because we have some catching up to do, but also generally, I mean biobanking is most widespread in the human biobanking area with which we interact as well, and it’s important to interact with those biobanks, because technologically, they’re usually more advanced, and best practices are usually done together with those biobanks, as we do in isper But yeah, I mean in biodiversity, we have lots of small communities storing frozen samples in their own Way, and in part, they need their own way, because they are also particularly collected and need to be preserved in a particular way. But still, there are some chances to better standardize how we’re doing this, how we’re collecting information on them, how we’re sharing that information, and how we are talking about options to strengthen the bio banking community, so we have all these little tribes of bio banks and molecular collections that we need to bring closer together, get them to talk more, interact more, use synergies and build better joint projects, and GGBN can be a key player to do that and harmonize and streamline the processes. And, yeah, this is about protocols. This is about data. This is about graph writing and also science policy, I guess.

Camilla:

Yeah, regarding the cell, the plan is to archive the largest number of species, especially those that are considered more difficult to obtain the cells. In the case of vertebrates, for example, amphibians, the group that suffers more now in that we are living this climate crisis, reptiles and fishes are also difficult to get cells, so the goal is to develop protocols to have more of these in our collection. And one of our wishes is to Coronavirus their cells from invertebrates, particularly arthropods, to cover this group with the largest number of species, we have already started some tests, which has proven very difficult, but I’m positive that this could be our next big step.

Christian:

That’s super interesting. Actually, bio banking is a an evolving field of research, we can say, given that we are talking talking about the future. So imagine a future scientist stumbling on one of your stored viads 50 years from now. So in 2075 What do you hope they will be able to discover or be able to do with that sample?

Camilla:

Yeah, I mean, my first thought would would be that that person doesn’t stumble, that he or she would, in a very organized, very neat way, go to the dgbm portal, look worldwide for where they can find which sample and have the appropriate metadata with it. And then they would see, oh, okay, I can go to LIB biobank and they will have this and that cell culture or DNA, or whatever I’m looking for. But no one knows. So maybe it is going to be a stumbling because politically, it’s not very clear where we’re going. And for that option, we’re also trying to to gear up and quite a few samples, DNA samples that we have, we have been sealing in metal capsules and keeping as a backup storage at room temperature, without water, without oxygen, in inert gasses, to really help people stumble on post apocalyptic biobank samples. I don’t think we have the wooly mammoth there, but lots of red listed species, protected species that may, by then, not be around anymore. But yes, what should people be able to do with that sample? So they should be able to reconstruct research that has been done, and they should be able to open up a window in time for species, for populations, and this is what collections are for, to understand how these species and populations have changed over time, why maybe they got extinct, or why maybe that population has flourished. What was it genetically maybe that made that possible? And infer from this material, useful information, valuable information, both for society and for basic knowledge and yeah, understand biodiversity better and protect better biodiversity better. Camilla, did you want to add anything about?

Camilla:

Yeah, In the cell perspective, I think people would be able to perform comparative studies or virology or disease that we have now and would maybe have in the future, or use the sales or eco toxicological studies in different organisms, comparing human environmental impact now and in the future, or use the cell to recover biodiversity.

Kasia:

Why not talking about stumbling still, I would like to come up with the last question, which is a bit more on the funny side, and I would like to ask both of you if you could preserve a sample from any mythological or extinct creatures. Which one would you pick and why?

Camilla:

I think this is the most difficult question.

The first thing that I thought was a unicorn, because my daughter loves unicorns. But now, giving a second thought, maybe the dodo, this big bird that was extinct from Mauritius Island, because I think it’s very sad that we had the chance to co exist with this animal and ended up driving it to extinction,

Jonas:

I guess for me to just name something, I could name a few things that I would love to have at the biobank. But what I thought of first thing the top of my head was Europe, to read a sea scorpion, those up to several meter long, swimming Scorpion related giants and the seas. And would be really cool to understand their their metabolism, their Yeah, evolution better by having DNA from them, at least. Maybe even better if we do invertebrates, one of cells and maybe grow a little at some point.

Kasia:

Wonderful. Thank you so much. Camila and Jonas for joining us. This podcast is brought together by Biodiversity Genomics. Europe project founded by the European Union, the Swiss Confederation and the United Kingdom.

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