Dr. Michael Balke head of Coleoptera Section at the Zoological State Collection Munich (Germany) and expert on taxonomy, phylogenetics, systematics and biogeography of water beetles of East-Asia
Dr. Paschalia Kapli researcher at the Department of Genetics, Evolution and Environment of the University College London (UK) and expert on phylogenetics, evolution and species delimitation
She is also involved in the development team of the software PTP for species delimitation (https://sco.h-its.org/exelixis/web/software/PTP/index.html)
Species delimitation aims to determine the boundaries and numbers of species from empirical data. During the last decade, sequence-based species delimitation has been the most popular approach, and is routinely used in systematic studies. The broad application of molecular species delimitation has been crucial in accelerating the pace of species identification and in quickly assessing the biodiversity of poorly studied groups and areas. Several algorithms and implementations exist for this purpose, and they can broadly be classified into multi-locus methods, implementing the multi-species coalescent model, and the single-locus methods focusing on the DNA-barcoding concept. The former is the most realistic approach and is appropriate for studies performing taxonomic revisions or studies examining the details of the diversification process. In large-scale biodiversity assessments (e.g., meta-barcoding studies) the samples may have high genetic divergence, and their number can range from hundreds to thousands, and, thus, employing multi-locus methods is practically impossible. Single-locus methods have served as an excellent tool in such instances, provided they only require a single barcoding marker that is particularly easy to amplify. The majority of the methods are computationally cheap, scaling well on large datasets, and provide us with a fast shortcut to identify overlooked biodiversity or systematic problems. The single-locus methods are further classified as either tree-based or distance-based, depending on whether groups are delimited using sequence distances or a phylogeny. Although each approach relies on simplified assumptions with respect to the complexity of species diversification. several empirical and simulation studies suggest they provide accurate delimitations and as such they constitute a powerful approach to biodiversity assessment studies. In this presentation we will review the assumptions and algorithms of methods from both single-locus approaches [tree-based: GMYC/(m)PTP and distance-based: ABGD] and we will try to identify factors that need to be accounted for, especially when drawing systematic and taxonomic conclusions.
Wednesday 17th (morning)
Dr. Guy Baele researcher at Evolutionary and Computational Virology Section of Rega Institute at KU Leuven (Belgium) and expert on Statistical and Computational Phylogenetics and virus evolution
He is also involved in the development team of the software Beast (http://beast.community/)
Phylogeneticists are typically interested in obtaining time-stamped rooted phylogenetic trees. The assumption of a strict molecular clock throughout the tree was originally required to infer divergence dates, but subsequent development of relaxed clock models has allowed for the removal of such an assumption. Different relaxations of the molecular clock have been developed to accommodate a multitude of evolutionary scenarios. These models allow to estimate divergence times in two distinct scenarios: isochronous data sets, where some type of calibration needs to be provided, and heterochronous data sets, where the differences between sequences sampled at different times can be used to calibrate the molecular clock. Populations for which such studies are possible are known as measurably evolving populations and are characterized by sufficiently long or numerous sampled sequences and a fast mutation rate relative to the available range of sequence sampling times. While RNA viral evolution is the most well-known example of using such an approach, the definition of a measurably evolving population also applies to ancient DNA, and allows us to estimate divergence times without paleontological calibrations.
Wednesday 17th (afternoon)
Dr. Lluis-Quintana Murci. Scientific Director of Pasteur Institute, CNRS, Paris and expert on evolutionary genetics of human populations
Different environmental, demographic and selective forces, together with cultural and social characteristics of human lifestyle, shape the patterns of variability of the human genome at the population level. I will review our most recent data on these different aspects, by focusing on specific examples of demography, lifestyle and natural selection. In particular, because infectious diseases have always been a major cause of human mortality, natural selection is expected to act strongly on host defence genes. This is particularly expected for innate immunity genes, as they represent the first line of host defence against pathogens. I will present different cases of how some of these genes and the pathways they trigger have been targeted by natural selection, in its different forms and intensities. I will also illustrate how these findings are helping to delineate genes that are important for host defence, with respect to those exhibiting higher immunological redundancy, and to increase our understanding of how past selection has had an impact on disease susceptibility in modern populations. Finally, I will present data showing that population adaptation can be facilitated by the acquisition, via admixture, of advantageous alleles from locally “adapted” populations. These events involve, for example, archaic introgression from Neanderthals, who introduced variants affecting immune responses to viral challenges into European genomes, or post-admixture selection among African Bantu-speaking populations, who acquired adaptive alleles related to immune responses or food metabolism from local populations of rainforest hunter-gatherers or pastoralists. This presentation will provide a glimpse into how population and functional genomic approaches increase our understanding of whether and how populations can adapt to environmental changes over different time scales.