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PREDICTS Project: Global Analysis Reveals Massive Biodiversity Losses

By Claire Asher, on 21 May 2015

The changing climate is only one of a myriad of pressures faced by global biodiversity – we are also changing habitats and altering land-use on an unprecedented scale. The first global analysis published from the PREDICTS project reveals the striking global effect of land-use change on local biodiversity patterns, and highlights the importance of future climate-mitigation strategies in shaping the future of biodiversity and the vital ecosystem services it provides.

Human activities are causing widespread change to and degradation of habitats, which has been linked to serious biodiversity declines globally. Land-use change comes in many forms, from deforestation and agriculture to urban development and road-building, and previous work by the PREDICTS project has shown how different types of land-use influence different types of species differently. We are interested in biodiversity loss at a global scale, and many metrics aim to quantify this, but viewing global patterns can obscure local-scale changes that are likely to be more important for the resilience of ecosystem services. Ecosystem services include clean air and water, food, medicine and nutrient cycling, among others, and are vital both for biodiversity and for human survival and well-being. The PREDICTS project considers local-scale changes to biodiversity in response to land-use change, to produce a powerful model that can be used to project the impact of future land-use and climate change. In their latest paper, published in Nature last month, the PREDICTS team reveal their most comprehensive analysis to date, showing massive reductions in local biodiversity since 1500, and projecting further widespread losses under several future climate and land-use scenarios. There is still hope, however, and strategies to mitigate greenhouse gas emissions without major land-use change could offer the opportunity for global biodiversity to recover.

Understanding the Past and Present

The PREDICTS team have assembled a database of over 1,130,000 records of species abundance and nearly 330,000 records of species richness across more than 11,000 sites worldwide. The database includes results from 284 scientific publications, and represents over 25,000 species. Using this incredible resource, the team compared species richness and abundance between sites with different land-use types and produced a statistical model to quantify local biodiversity responses to land-use change. This enabled them to infer changes in species assemblages since the year 1500.They found that species richness and total abundance were both strongly influenced by land-use type and intensity, with reductions in biodiversity outside of primary vegetation and the worst losses seen in intensively used areas. Local biodiversity was also negatively impacted by human population density and accessibility (measured by the distance to the nearest main road). In the worst-affected habitats, changing land-use away from primary vegetation reduced species richness and abundance by an average of about 40%, and globally, land-use change was responsible for an average reduction in species richness and abundance of around 9%. The value of secondary vegetation (forest recovering from past damage) for biodiversity depended strongly on how mature the habitat was, with species diversity increasing over time, and mature secondary vegetation most closely resembling primary habitats. Restoration projects do, therefore, have the power to return biodiversity to damaged habitats, but (unsurprisingly!) it will take time.

Previous estimates have suggested that local losses of species richness and diversity greater than 20% are likely to substantially impair ecosystem services contributed to by biodiversity and reduce overall ecosystem function. Some scientists believe biodiversity loses at this scale may push populations towards ‘tipping points’ where ecosystem function declines lead to further species loss. Thus, in the worst-affected habitats considered by the PREDICTS team, which experienced on average a 31% loss of local species richness, ecosystem function is likely to be substantially impaired.

Changes in species richness and abundance may underestimate the real impact of land-use change because the measure fails to capture the composition of a community. The team therefore compared the species composition between sites and found that communities tended to be similar under similar land-use. Communities living in primary and secondary vegetation were most alike, while more disturbed habitats such as plantation forest, pasture and cropland tended to support a different cluster of more human-tolerant species. Human-dominated landscapes lost far more natural local diversity than more pristine sites where natural vegetation remains.

Reconstructing past biodiversity loss indicated that the greatest reductions in species richness occurred in (unsurprisingly) the 19th and 20th centuries, and that by 2005 local species richness worldwide had reduced by 13.6% due to land-use change and related anthropogenic pressures. How will this trend continue into the future?

Projecting the Future

The PREDICTS team then went on to combine their analysis of current species’ responses to land-use change with four climate scenarios produced by the Intergovernmental Panel on Climate Change, to project future changes in biodiversity under different socioeconomic scenarios of land-use change. Projecting as far as 2095, the PREDICTS model projects rapid biodiversity losses under a ‘business-as-usual’ land-use scenario, with species richness projected to drop a further 3.5%. These loses are not likely to be uniformly distributed, however, with the largest loses predicted to occur in economically poor but highly biodiverse regions, such as Southeast Asia and Sub-Saharan Africa. Buisness-as-usual results in rapid human population growth and agricultural expansion, and most closely matches recent trends, and yields the most severe losses in biodiversity of any scenario considered by the PREDICTS team. Continuing on as we have been does not bode well for biodiversity or the vital ecosystem services it provides us.

Projected net change in local richness from 1500 to 2095. Source: http://www.nature.com/nature/journal/v520/n7545/abs/nature14324.html.

Projected net change in local richness from 1500 to 2095. Source: http://www.nature.com/nature/journal/v520/n7545/abs/nature14324.html.

Perhaps surprisingly, the second-worst scenario for biodiversity is in fact the scenario with the least climate change (IMAGE2.6). This is because this scenario achieved reduced emmisions and climatic change by rapidly converting the world’s forests (primary vegetation) to crops and biofuel. In contrast, the IPCC scenario MiniCAM 4.5, which mitigates climate change through the use of carbon markets, crop improvements and diet shifts, however, is projected to increase average species richness. Not all our possible solutions to curb greenhouse gas emissions and reduce climate change will necessarily spell good news for biodiversity.

It isn’t all bad news, though. The right strategies can promote biodiversity globally, even producing increases in species richness by 2095 of up to 2%, and the PREDICTS team say widespread biodiversity loss is not inevitable. Concerted efforts and the right socioeconomic choices can make long-term global sustainability of biodiversity an achievable goal.

Original Article:

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This research was made possible by funding from the Natural Environment Research Councik (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC).

Finding Shared Genes Between Species

By Claire Asher, on 7 May 2015

a guest blog by Natasha Glover, written for the 2015 Write About Research Competition.

Did you know we share approximately 98% of our genes with chimpanzees? Chimps are commonly referred to as our evolutionary “cousins.” This makes sense to anyone who’s seen Planet of The Apes – chimps and humans share many of the same physical characteristics. But did you also know that we share approximately 92% of our genes with mice? About 80% of our genes with dogs? Half with a fruit fly? Even plants and humans (who couldn’t be morphologically more different than night at day), have about 20% of genes in common.

These shared genes are evidence of evolution from a common ancestor and the relatedness of all life on Earth. The shared genes are called homologous genes, or genes which share a common ancestry either between or within species. They can be further classified into two main categories: orthologs, which are pairs of genes that started diverging through speciation, and paralogs, which are pairs of genes that started diverging through gene duplication. Finding and studying homologous genes is important, because the same gene in two different species (orthologs) are more likely to have the same cellular function than two duplicated genes (paralogs).

This brings us to the concept of model organisms, which are representative species studied by many scientists from which the knowledge learned from them can be transferred to other, closely related species. For example, this is why researchers experiment on mice instead of humans to test new drugs. Orthologs between mice and humans allow for observing basic human biological processes in mice, and then transferring the knowledge to humans. Orthologs are also applicable to agricultural research. Imagine if a scientist finds an interesting gene in the model plant Arabidopsis thaliana, perhaps a gene controlling an important agronomical trait like seed size, flowering time, or tolerance to drought. It would be useful to find the ortholog of this gene in another economically important crop such as rice, wheat or soybean in order to exploit the trait of interest.

Homologous genes correspond to shared attributes between species. We can identify the shared traits just by looking at them. But how can we identify orthologs and paralogs at the molecular level, that is, how do we identify these genes by analyzing their sequence? It’s important to keep in mind that the concepts of homology are purely from an evolutionary perspective. Thus, we can deduce orthologous and paralogous relationships between pairs of genes using a phylogenetic tree (See Box 1).

SharedGenes_fig1Box 1. This tree represents the relationship between 5 gene sequences. Each node of the tree either represents a speciation (S1 and S2) or duplication event (star). Thus to know the relation between pairs of genes, you just have to trace them back to their shared node (closest common ancestral copy). In this example, the blue genes between dog and human are orthologous to each other (because they trace back to a speciation event). The red dog and red human genes are also orthologous to each other. However, all the blue genes are paralogous to all the red genes because they trace back to a duplication node. All of these red and blue genes are orthologous to the black (frog) gene, an example of a many:1 relationship.

Evolutionary scenarios and relationships become complicated when dealing with many lineage-specific gene duplications and losses. In plants especially, homologous relationships are hard to infer because of their highly complex genomes compared to animals. Plant genomes tend to be much larger and much more duplicated than animal genomes, making ortholog inference in plants very challenging.

Several algorithms and tools are available to predict homologous relationships between genomes. OMA (Orthologous Matrix) is one of them. It’s a method and database for the inference of orthologs and paralogs among completely sequenced genomes. Launched by Dessimoz and colleagues in 2004, OMA has steadily increased the number of species in the database to 1706, including both prokaryotes and eukaryotes. With its many genomes and accurate orthology prediction, OMA is a great starting point for evolutionary biology and genomics analyses. Recently OMA has undergone its 17th browser release to include a website facelift, gene function prediction, and more support for plant genomes. For plants in particular, there is now over 450 million years of evolution represented with the orthology prediction between the species Selaginella moellendorffii (representing early vascular plants) and Physcomitrella patens (representing the non-vascular plants).

The burst of larger, more complex sequenced genomes in the past decade provides a unique challenge in terms of orthology prediction. OMA tackles this problem, and provides a valuable resource to the scientific community. So, want to find out how many genes humans have in common with yeast? Try OMA.

References

  • Altenhoff AM, Dessimoz C. Inferring Orthology and Paralogy. In: Anisimova M, editor. Evolutionary Genomics. Totowa, NJ: Humana Press; 2012. pp. 259–279. Available: http://discovery.ucl.ac.uk/1395519/
  • Altenhoff AM, Škunca N, Glover N, Train C-M, Sueki A, Piližota I, et al. The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements. Nucleic Acids Res. 2014; gku1158. doi:10.1093/nar/gku1158

NatashaGloverNatasha Glover received her Bachelor of Science and PhD from the Department of Crop and Soil Environmental Science at Virginia Tech in the U.S. Her PhD was focused on plant genomics and biotechnology. She received a Marie Curie International Incoming Fellowship for her first postdoc and worked in Clermont-Ferrand, France at the Institut Nationale de la Recherche Agronomique for 3 years. There, she concentrated on computational biology, with a focus on synteny and duplication in the wheat genome. Natasha is a currently a postdoc based at Bayer CropScience in Ghent, Belgium as part of the Marie Curie PLANT FELLOWS program. Her co-advisor is Dr. Christophe Dessimoz in the department of Genetics, Evolution, and Environment at UCL.

Competitive Generosity Drives Charitable Donations

By Claire Asher, on 17 April 2015

Unconditional generosity is a characteristic of humans on which we pride ourselves, and billions of dollars is donated to hundreds of thousands of charitable organisations every year. But look at it from an evolutionary perspective, and this trait seems difficult to explain. In some situations, giving may have evolved to advertise positive characteristics of the giver in the aim of attracting a mate. Recent research from GEE suggests this may explain the charitable behaviour of men donating to female fundraisers online. Data from over 2500 fundraising campaigns showed that men donate £10 more on average if previous male donors have been particularly generous.

Helping others at random, with no promise of reciprocity in the future, should not be favoured by natural selection as it will tend to disadvantage the altruist. Yet we see people doing just that every day. One theory that may explain selfless, unconditional generosity in humans (and other animals) is the ‘competitive helping’ hypothesis, which suggests generosity may sometimes be used to advertise positive characteristics to potential mates. The hypothesis suggests that people will compete to be the most generous, particularly when they are in the presence of attractive potential mates. If generosity is costly, and competition for mates is tough, then competitive generosity could be favoured by natural selection as a mechanism to honestly communicate quality. Only the best quality males could afford to be so generous, making them more attractive to on looking females.

To test this hypothesis, GEE researcher Dr Nichola Raihani and Professor Sarah Smith from the University of Bristol reviewed 2561 online fundraising pages, and selected 668 that had public donations and an image of the fundraiser. They then calculated the average donation running up to a large donation of £50 or more. They compared these donations with those made after the large donation, according to the gender of the donors and the gender and attractiveness of the fundraiser. They found men tended to give larger amounts after other men had made large donations. Men were also more generous when the fundraiser was an attractive female, giving four times more to female fundraisers following a large donation from another male. Attractive female fundraisers received £28 more during these bidding wars than less attractive females and males!

Interestingly, while this pattern is clear in donations by men, the same is not true for women donating money online. This suggests that male charitable behaviour represents a competitive helping display, favoured by sexual selection as an honest signal of male quality.

It’s fascinating that evolutionary biology can offer insights into human behaviour even in the modern world. People are really generous and their reasons for giving to charity are generally not self-serving but it doesn’t preclude their motives from having evolved to benefit them in some way. Take eating for example, our primary drive is to dispel the feeling of hunger, which is pleasurable, but the evolutionary purpose is to make sure we don’t starve and die. Generous behaviours can be seen in a similar way – the motivation for performing them doesn’t have to be the same as the evolutionary function.” – Dr Nichola Raihani

Original Article:

() Current Biology

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This research was made possible by funding from the Economic and Social Research Council (ESRC) and the Royal Society.

Annoucing the Winners of the Write About Research Competition

By Claire Asher, on 10 April 2015

Thanks to everyone who entered our Write About Research competition. We received some great entries from GEE students and postdocs, covering a broad range of topics from conservation to genetics. The entries will be posted here over the coming months, so watch this space!

The Winners are…

Drum roll please …

WINNER: David Curnick – “Can Large MPAs Protect Tuna and Sharks?”

RUNNERS UP: Charlie Outhwaite – “The Challenge of Monitoring Biodiversity” and
Natasha Glover – “Finding Shared Genes Between Species”

Winners each receive a £50 gift voucher.

Male Promiscuity Boosts Role of Chance in Sex Chromosome Evolution

By Claire Asher, on 19 March 2015

Humans, like all mammals and birds, determine sex with chromosomes. Whether a fertilised egg develops into a male or female depends on what chromosomes it carries Scientists have long recognised that genes evolve a little differently on the sex chromosomes, and recent research in GEE suggests this may be due to differing patterns of inheritance that favour the influence of chance on gene sequence change. Furthermore, promiscuity in males has a large influence on the magnitude of this effect, with chance playing an even greater role in sex-chromosome evolution in highly promiscuous species. Using genetic sequence data in combination with physical and behavioural measurements of promiscuity in birds, Dr Alison Wright and Professor Judith Mank report strong evidence for the role of neutral forces in sex chromosome evolution.

In birds and mammals, along with some invertebrates and reptiles, sex is determined by the chromosomes you carry – the sex chromosomes, as they are aptly named. If you are a male mammal, you carry one X and one Y chromosome; a female mammal carries two X chromosomes. Similarly, if you are a male bird, you carry two Z chromosomes; a female carries one Z and one W. Whether it’s the XY system, the ZW system or even the UV system used by some species of algae, the result is more or less the same. Sex is determined by the presence or absence of particular chromosomes. This isn’t always the case – some species determine sex using temperature during development, other species determine sex based on social conditions, while others do away with fixed sexes altogether and are either hermaphrodite or possess the ability to switch sex. However, one of the most common, and certainly the best studied, systems among living organisms is to determine sex with chromosomes.

Unlike autosomal chromosomes (all our chromosomes that are not sex chromosomes), sex chromosomes are not inherited and expressed equally across the sexes. The Y and W chromosomes only ever appear in one sex, for example. This has some interesting consequences for evolution. For example, scientists have found that the ‘major sex chromosomes’ (X and Z chromosomes) tend to evolve faster than the autosomes. Known as the Faster-X (or Faster-Z) effect, this phenomenon is now well documented in a range of different species, and scientists have suggested a number of possible explanations for why this might be the case. Faster evolution on the major sex chromosomes might be caused by more effective natural selection favouring beneficial mutations (adaptive hypothesis) or due to less effective natural selection failing to remove harmful mutations (neutral hypothesis).

Why would natural selection act differently on sex chromosomes than autosomal ones? In a paper published in Molecular Ecology this month, Dr Alison Wright explains that the differences between chromosomes arise because of differences in the pattern of inheritance, which ultimately influences the number of chromosomes that are passed on to the next generation, called the effective population size. An individual who never reproduces is an evolutionary dead end, and as their genes are not passed on, and they are not counted in the effective population size. Individuals that do mate contribute sex chromosomes unevenly, and this can have a significant impact on the course of sex-chromosome evolution.

When two individuals mate, they each pass one of each pair of chromosomes to the offspring. Each chromosome has an equal likelihood of being carried by the offspring, and the effective population size (ie chance of being passed on) of all autosomal chromosomes is the same. But for the sex chromosomes, things are a bit more complicated. Each time a pair of individuals mate, between them they bring three major sex chromosomes and one minor chromosome to the table. This translates to major sex chromosomes having an effective population size three times larger than the minor sex chromosomes. And both sex chromosomes have a smaller effective population size than the autosomes.

But that’s only if everybody is monogamous. As soon as promiscuity is involved, things get even more complicated. If males are promiscuous (and they often are, in the animal kingdom), then this means some males in the population are likely to be very successful, while others fail to reproduce at all. In other words, the variance in male mating success is much higher. Promiscuity reduces the effective population size of the minor chromosomes even further.

promiscuitysexchromosomes

Why does effective population size matter? Well, the effective population size determines the relative influence of chance on gene sequence evolution. Although we generally think of evolution progressing as natural selection favours beneficial mutations and purges deleterious ones, chance also has a big role to play. Chance, known in this context as genetic drift, has a bigger impact on small populations, and rare mutations. This is because when a particular mutation is rare, it only takes a little bit of bad luck for it to be lost forever. Just think of the times you’ve walked home in the rain only to hear the characteristic crunch of the end of a snail’s life – here your foot is the agent of genetic drift. The death of that snail had little or nothing to do with the genes it carried, but your foot has altered the course of evolution, slightly. The effective population size of autosomal genes reflects the population size of the organisms they are found in, but for the sex chromosomes, their effective population size is even smaller, making them more prone to genetic drift.

Dr Alison Wright, Professor Judith Mank and colleagues from GEE sequenced expressed genes in six species of birds, spanning 90 million years of evolution, to investigate the rate of evolutionary change in genes on different chromosomes. They compared sequence data from monogamous species like the Swan Goose (Anser cygnoides) and the Guinea Fowl (Numida meleagris) with promiscuous species like the Mallard duck (Anas platyrhynchos), wild Turkey (Meleagris gallopavo), and Peafowl (Pavo cristatus) to investigate how gene sequences and gene expression patterns vary both within and between species. They then matched data on the rate of evolution with characteristics of species that are associated with promiscuity, such as testes weight and sperm number. Their results indicate that natural selection is less effective on the Z chromosome in general, and this becomes even more pronounced in promiscuous species. The authors therefore conclude that Faster-Z evolution in birds is not adaptive, but is driven by neutral processes.

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Differences in gene sequences within and between species can tell us a lot about the rate of evolution for different lineages. This is because the genetic code has some redundancy in it – DNA is split up into three-letter words or codons, and there are many cases where different codons translate into the same amino acid. So, it is possible to have genetic sequence change that is essentially invisible to natural selection – it doesn’t alter the resulting protein sequence and so has no influence on the organism. Changes in gene sequence that swap between these ‘synonymous’ codons can therefore give us a rough baseline of neutral change. Non-synonymous differences (the ones that do have an effect on the organism), between individuals or between species, represent the rate of evolution. More non-synonymous changes suggests either positive selection, where evolution favours those changes because they are beneficial, or genetic drift, where selection is weaker and cannot remove slightly harmful mutations from the population. The authors found that genes on the Z chromosome show a faster rate of non-synonymous change than autosomal genes. Further, the ratio was significantly correlated with measures of promiscuity, with more promiscuous species having more non-synonymous changes.

Although this could be a mark of positive natural selection, the authors found no difference in the number of genes undergoing positive selection between sex- and autosomal-chromosomes, suggesting the Faster-Z effect is driven by genetic drift rather than positive selection. In fact, differences within species indicate that natural selection is less effective at removing mildly deleterious mutations from the Z chromosome than the autosomes. Combined with other analyses on gene expression, these results show strong support for the neutral explanation for Faster-Z evolution in birds.

Interesting, promiscuity increases the effective population size of X chromosomes, and that may explain why previous studies have found evidence that Faster-X chromosome may well be due to positive selection. These differences suggest that Z chromosomes may be less important in adaptation than X chromosomes.

Original Article:

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This research was made possible by funding from the Natural Environment Research Council (NERC) and the European Research Council (ERC).

Sloths Move Slow, Evolve Fast

By Claire Asher, on 11 March 2015

Sloth003Sloths might be notorious for their leisurely pace of life, but research published last year shows they are no slow coaches when it comes to evolution.

Sloths, as we know and love them, are small, slow-moving creatures found in the trees of tropical rainforests. But modern sloths are pretty odd compared to their extinct relatives. Sloths (Folivora) are represented today by just six species in two families; the Megalonychidae (two-toed sloths) and the Bradypodidae (three-toed sloths). But 20,000 years ago there were perhaps as many as 50 species of sloth spread across the globe, and most were relatively large, ground-dwelling animals quite unlike modern sloths. While most modern sloths weigh in at a modest 6kg, extinct species such as Megatherium americanum and Eremotherium eomigrans could weigh up to 5 tonnes!

[Read More at Curious Meerkat]

Write About Research – A GEE Research Blog Competition

By Claire Asher, on 3 March 2015

The GEE Research blog communicates UCL science with a wider, non-specialist audience, by providing short summaries of recent research in the department of UCL Genetics, Evolution and Environment. This provides an opportunity to engage with a broad audience, including other academics, students, members of the public, and even businesses and policy-makers. It is a great way to increase the reach and impact of your research. Now we’re offering the opportunity to contribute your own writing to the GEE blog – this is your chance to explain your research to the world, to improve your science communication skills, and maybe even win yourself some cash!

Public communication of science is a key skill for any scientist, and is increasingly being appreciated by academics and research councils as an important part of science education and training. It is a totally different medium from traditional academic papers; it offers the freedom to tell a story, but also presents challenges – you must communicate in a way that anybody can understand. Compared to academic journals, popular writing has the potential to reach a far broader range of readers and can have many benefits for your research – for example leading to new collaborations and inviting comment and feedback from readers who would never otherwise come into contact with your work.

If you are interested in writing a guest post for the GEE Research blog, now is your chance! Enter our “Write About Research” contest and not only will your blog post be published online, but you’ll also be in with a chance to win £50!

Guidelines

Your blog should be written in a way such that an ‘educated non-specialist’ audience can understand and follow it. You can therefore assume a GCSE-level science background and jargon should be explained the first time you use it. Blogs should begin with a short opening paragraph that sets the scene – basically the abstract of the blog post – summarising the key points of the article and leading the reader into the post. The rest of the post should provide background, a summary of the focus paper(s) and should end with a broad conclusion, setting the research into the larger context, and highlighting it’s relevance and importance. Take a look at other GEE blog posts for an idea of what we’re looking for.

Choosing a Topic

  • Your blog post must cover your overall area of research
  • Entries should focus on one or two key papers
  • You could therefore write about one of your own publications or a recent publication in your area of research. Alternatively, you could write a general background to your research area, focussing on a few key (but not necessarily recent) papers in that field.
  • Just be sure not to scoop yourself – please don’t write about your own research that has not yet been published, or assessed work (e.g. MSc project) that has not yet been assessed.
  • If you are unsure whether your idea fits the criteria, feel free to contact c.asher@ucl.ac.uk with any queries

Eligibility

You must be an MSc, MRes or PhD Student, or a PostDoc undertaking a research project (or having completed a research project in the last 12 months) in the UCL Department of Genetics, Evolution and Environment.

How to Enter

  • One entry per person
  • Entries must be between 600 and 1200 words
  • All entries must include a reference list including any published papers that you refer to directly. In-text referencing is not necessary. The reference list does not count towards the word count.
  • Send your entry, along with a 150-word biography to c.asher@ucl.ac.uk
  • Please also recommend at least one photo to include with the post (either your own image or one from Wikimedia commons).
  • Entries must be received by 5pm 31st March 2015

Prizes and Publication

  • We will be posting all blog entries on the GEE Research blog over the next year (between April 10th 2015 and April 9th 2016).
  • Additionally, there will be a £50 gift voucher for each of the three best entries, as judged by Dr Claire Asher
  • Entries will be judged by Dr Claire Asher, and winners announced on 10th April 2015
  • Winners will be announced in a specific post on the GEE Research blog, and will bear no relation to the order in which each blog post is subsequently posted on the site.

If you have any questions or queries about the contest, please feel free to contact c.asher@ucl.ac.uk.

Good Luck!

Was Fermentation Key to Yeast Diversification?

By Claire Asher, on 17 February 2015

From bread to beer, yeast has shaped our diets and our recreation for centuries. Recent research in GEE shows how humans have shaped the evolution of this important microorganism. As well as revealing the evolutionary origins of modern fission yeast, the new study published in Nature Genetics this month shows how techniques developed for detecting genetic causes of disease in humans can be usefully applied to better understand the ecology, biochemistry and evolution of commercially and scientifically important microorganisms like yeast.

Fission yeast, Schizosaccharomyces pombe, is one of the principal ‘model’ species that cell biologists use to try and understand the inner workings of cells. Most famously, Paul Nurse used this yeast to discover the genes that control cell division. The laboratory strain was first isolated from French wine in 1924, and has been used ever since by an increasingly large community of fission yeast researchers. However, serendipitous collection of new strains has continued slowly since that time, and many of these are associated with human fermentation processes – different strains have been isolated from Sicilian vineyards, from the Brazilian sugarcane spirit Cachaça and from the fermented tea Kombucha. Despite it’s enormous scientific importance, little is known about the ecology and evolution of fission yeast.

Research published this month by Professor Jürg Bähler, Dr Daniel Jeffares and colleagues from UCL’s department of Genetics, Evolution and Environment, along with researchers from 10 other institutions across five countries, reveals an intimate link between historic dispersal and diversification in yeast and our love of fermented food and drinks. The project sequenced the genomes of 161 strains of fission yeast, isolated in 20 countries over the last 100 years, enabling the researchers to reconstruct the evolutionary history of S. pombe, as well as investigating genetic and phenotypic variation within and between strains.

Beer, Wine and Colonialism

Bähler and Jeffares were able to date the diversification and dispersal of S. pombe to around 2,300 years ago, coinciding with the early distribution of fermented drinks such as beer and wine. Strains from the Americas were most similar to each other, and dated to around 1600 years ago, most likely carried across the Atlantic in fermented products by European colonists. This is reminiscent of findings for the common bread and beer yeast species, Saccharomyces cerevisae, whose global dispersal is thought to date to around 10,000 years ago, coinciding with Neolithic population expansions. This research therefore reveals the intimate link between human use of yeast for fermentation and it’s evolutionary diversification, and highlights the power of humans to shape the lives of the organisms with which they interact.

From Genotype to Phenotype

Fission Yeast, Schizosaccharomyces pombe

The researchers also used genome-wide association techniques to investigate the relationship between genotype and phenotype in the different strains. They began by carefully measuring 74 different traits in representatives of each strain. Some traits were simple, such as cell size and shape, but the researchers also measured environment-genotype interactions, for example by investigating growth rates and population sizes with different nutrient availabilities, drug treatments and other environment variables. In total, they identified 223 different phenotypes, most of which were heritable to some extent. Further, relatively few of the phenotypes were strongly linked to a particular population or region, making yeast ideal for genome-wide association studies (GWAS), unlike Saccharomyces cerevisae, for which it has not been possible to use GWAS successfully.

GWAS was developed to identify genes that are linked to specific diseases in humans, however this study highlights how the technique can usefully be applied to understanding evolution and genotype-phenotype relationships in other organisms. Tightly controlled experimental conditions that can be achieved with microorganisms in the laboratory make GWAS possible and informative for organisms such as yeast. The researchers found 89 traits that were significantly associated with at least one gene; the strongest association explained about a quarter of variation between individuals.

Hallmarks of Selection

Looking at variation in genomic sequence between strains also allowed the researchers to investigate which parts of the genome have undergone more evolutionary change than others, and which regions are likely to be particularly important for function. Genes and genomic regions that are crucial to survival (such as those involved in basic cellular function, for example), tend to change relatively little over evolutionary time, because most mutations in their sequence would be severely detrimental to survival. A process known as purifying selection tends to keep these genetic sequences the same over long stretches of evolutionary time. Less crucial genetic sequences have more freedom to change without having serious consequences; they are not subject to strong purifying selection and tend to show more variation between individuals and populations.

The authors found that genetic variation between strains was lowest for protein-coding gene sequences (those that produce protein products such as hormones and enzymes), which is to be expected. However, they found variation was also low in non-coding regions near genes. These regions are thought to be important in gene regulation, echoing an increasing appreciation that the evolution of the regulation of gene expression may be as important, if not more so, than the evolution of the gene sequences themselves.

This ground-breaking research from GEE reveals fascinating insights into the ecology and evolution of fission yeast, a microorganism that directly or indirectly influences our lives on a daily basis. It highlights how important humans have been in shaping the genomes of commercially and scientifically important organisms, whilst also expanding our knowledge of genes, genomes and phenotypes more generally. Applying techniques such as this to a wider range of organisms has the potential to vastly increase our understanding of the genomic dynamics of evolutionary change.

Original Article:

() Nature Genetics

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This research was made possible by funding from the Wellcome Trust, the European Research Council (ERC), the (BBSRC), the UK Medical Research Council (MRC), Cancer Research UK, the Czech Science Foundation and Charles University.

Planning for the Future – Resilience to Extreme Weather

By Claire Asher, on 15 January 2015

As climate change progresses, extreme weather events are set to increase in frequency, costing billions and causing immeasurable harm to lives and livelihoods. GEE’s Professor Georgina Mace contributed to the recent Royal Society report on “Resilience to Extreme Weather”, which predicts the future impacts of increasing extreme weather events, and evaluates potential strategies for improving our ability to survive, even thrive, despite them.

Extreme weather events, such as floods, droughts and hurricanes, are predicted to increase in frequency and severity as the climate warms, and there is some evidence this is happening already. These extreme events come at a considerable cost both to people’s lives, health and wellbeing, and the economy. Between 1980 and 2004, extreme weather is estimated to have cost around US$1.5 trillion, and costs are rising. A recent report by the Royal Society reviews the future risks of extreme weather and the measures we can take to improve our resilience.

The global insured and uninsured economic losses from the two biggest categories of weather-related extreme events. Royal Society (2014)

The global insured and uninsured economic losses from the two biggest categories of weather-related extreme events. Royal Society (2014)

Disaster risk is a combination of the likelihood of a particular disaster occurring and the impact on people and infrastructure. However, the impact will be influenced not only by the severity of the disaster, but by the vulnerability of the population and its infrastructure, a characteristic we have the potential to change. Thus, while it may be possible to reduce the frequency of disasters by reducing carbon emissions and slowing climate change, another key priority is to improve our own resilience against these events. Rather than just surviving extreme weather, we must adapt and transform.

The risks posed by climate change may be underestimated if exposure and vulnerability to extreme weather are not taken into account. Mapped climate and population projections for the next century show that the number of people exposed to floods, droughts and heatwaves will both increase and become more concentrated.

Exposure risk to floods and droughts in 2090. Royal Society (2014)

Exposure risk to floods and droughts in 2090. Royal Society (2014)

In their recent report, the Royal Society compared different approaches to increasing resilience to coastal flooding, river flooding, heatwaves and droughts. Overall, they found that a portfolio of defence options, including both physical and social techniques and those that utilise both traditional engineering solutions and more ecosystem based approaches. Broadly, approaches can be categorised as engineering, ecosystem-based, or hybrids of the two. Resilience strategies that incorporate natural ecosystems and processes tend to be more affordable and deliver wider societal benefits as well as simply reducing the immediate impact of the disaster.

Ecosystem-based approaches can take a variety of different forms, but often involve maintaining or improving natural ecosystems. For example … Large, intact tropical forests are important in climate regulation, flood and erosion management and … Forests can also act as a physical defence, and help to sustain livelihoods and provide resources for post-disaster recovery. Ecosystem-based approaches often require a lot of land and can take a long time to become established and effective, however in the long-term they tend to be more affordable and offer a wider range of benefits than engineering approaches. For this reason, they are often called ‘no regret’ options. Evidence for the effectiveness of different resilience strategies is highly varied. Engineered approaches are often well-established, with decades of strong research to back them up. In contrast, ecosystem approaches have been developed more recently and there is less evidence available on their effects. The Royal Society report indicates that for coastal flooding and drought, some of the most affordable and effective solutions are ecosystem-based, such as mangrove maintenance as a coastal defence and agroforestry to mitigate the effects of drought and maintain soil quality. In many situations, hybrid solutions may offer the best mixture of affordability and effectiveness.

It is crucial for governments to develop and implement resilience strategies and start building resilience now. This will be most effective if resilience measures are coordinated internationally, resources shared and where possible, cooperative measures implemented. By directing funds towards resilience-building, governments can reduce the need for costly disaster responses later. Governments can reduce the economic and human costs of extreme weather by focussing on minimising the consequences of infrastructure failure, rather than trying to avoid failure entirely. Prioritising essential infrastructure and focussing on minimising the harmful effects of extreme weather are likely to be the most effective approaches in preparing for future increases in extreme weather events.

Original Article:

() Resilience to
extreme weather

Forecasting Extinction

By Claire Asher, on 5 January 2015

Classifying a species as either extinct or extant is important if we are to quantify and monitor current rates of biodiversity loss, but it is rare that a biologist is handy to actually observe an extinction event. Finding the last member of a species is difficult, if not impossible, so extinction classifications are usually estimates based on the last recorded sightings of a species. Estimates always come with some inaccuracy, however, and recent research by GEE academics Dr Ben Collen and Professor Tim Blackburn aimed to investigate how accurate our best estimates of extinction really are.

Using data from experimental populations of the single-celled protist Loxocephalus, as well as wild populations of seven species of mammal, bird and amphibian, the authors tested six alternative estimation techniques to calculation the actual date of extinction. In particular, they were interested in whether the accuracy of these estimates is influenced by the rate of population decline, the search effort put in to find remaining individuals and the total number of sightings of the species. The dataset included very rapid declines (40% a year in the Common Mist frog) and much slower ones (16% per year in the Corncrake), and different sampling regimes.

Their results showed that the speed of decline was a crucial factor affecting the accuracy of extinction estimates – for experimental laboratory populations, estimates were most accurate for rapid population declines, however slow population declines in wild populations tended to produce more accurate results. The sampling regime was also important, with larger inaccuracies occurring when sampling effort decreased over time. This is probably a common situation for many species – close monitoring is common for species of high conservation priority, but interest may decrease as the species becomes closer and closer to extinction. The total number of sightings was also an important factor – a larger number of sightings overall tended to produce more accurate estimates.

Finally, the estimation technique also influenced accuracy, but only in interaction with the other variables mentioned above. Some methods fared best for rapid population declines, others for slower ones. Many of the methods fare poorly when sampling effort changes over time, particularly if it decreases, although they were relatively robust to sporadic, opportunistic sampling regimes. Overall, optimal linear estimation, a statistical method which makes fewer assumptions about the exact pattern of sightings, produced the most accurate results in cases where more than 10 sightings were recorded in total.

This study highlights the challenges faced by ecologists trying to determine whether a species has gone extinct or not. Sightings of rare species are often opportunistic, and only rarely are they part of a systematic, long-term monitoring program. Thus, methods that produce accurate results in the face of changing or sporadic search efforts are of key importance to conservationists. If the history of a species’ population declines and of the sampling effort are known, then statistical estimates can be selected which provide the best estimates for the particular situation. However, this information is rarely available and so using techniques that can provide accurate estimates for a range of different historical scenarios are likely to be of most use in predicting extinction status. Ultimately, it is extremely useful for conservationists to know whether a species is extinct or not, but estimates will always be subject to error except in rare cases (such as the passenger pigeon, for example) where the extinction event is observed first hand. There will always be cases of species turning up years after they were declared extinct, and no estimate will ever be perfect, but understanding the sources of error and the best methods to use to minimise it can be of great benefit in reducing the frequency with which that happens.

Original Article:

() Conservation Biology

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This research was made possible by funding from the Natural Environment Research Council (NERC).