| Time | Speaker | Title | Resources | |
|---|---|---|---|---|
| 09:30 to 09:40 | Rajesh Gopakumar (ICTS-TIFR, India) | Welcome remarks | ||
| 09:40 to 11:10 | Kavita Jain (JNCASR, India) | Introduction to Stochastic Modeling in Evolution (Lecture 1) | ||
| 11:30 to 13:00 | Deepa Agashe (NCBS, Bengaluru, India) | Introduction to Genetics Variation | ||
| 14:00 to 15:00 | Samay Pande (IISc, India) | Bacterial predator mediated enrichment of antibiotic resistance in complex microbial communities | ||
| 16:30 to 18:00 | - | Posters |
| Time | Speaker | Title | Resources | |
|---|---|---|---|---|
| 11:30 to 13:00 | Kavita Jain (JNCASR, India) | Introduction to Stochastic Modeling in Evolution (Lecture 3) | ||
| 14:00 to 15:00 | - | Posters | ||
| 16:30 to 18:00 | Susanna Manrubia (Centro Nacional de Biotecnología CNB-CSIC, Spain) | Topological Structure of Genotype Spaces and the Dynamics of Molecular Evolution (Lecture 2) | ||
| 18:30 to 20:00 | David Nelson (Harvard University, USA) | Introduction to Spatial Population Genetics (Lecture 1) |
| Time | Speaker | Title | Resources | |
|---|---|---|---|---|
| 09:30 to 11:00 | Michael Lynch (University of Arizona, USA) |
The Population-Genetic Environment (Lecture 1) Evolution is a population-genetic process governed by the joint forces of mutation, recombination, and random genetic drift, all of which vary by more than four orders of magnitude across the Tree of Life. As these three features define the population-genetic playing field upon which evolution operates, such quantitative knowledge is an essential resource for understanding the limits to all adaptive and nonadaptive evolutionary pathways. More |
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| 11:30 to 12:30 | Saskya van Nouhuys (IISc, India) |
Spatio-temporal dynamics of interacting species across a fragmented and changing landscape Species in a community, even those that interact closely, experience their shared landscape differently because they have different dispersal abilities and availability of their limiting resources vary. Using long-term survey and population genetic markers I show the impact of habitat fragmentation and environmental change on a butterfly, two of its parasitoids, and a hyperparasitoid in Åland, Finland. Climate change has led to increased spatial synchrony of butterfly population dynamics, resulting in large-scale destabilizing population fluctuation. High trophic level species such as parasitoids are disproportionally affected by environmental change because they depend on their unstable host as a resources. The vulnerability of many parasitoid species is amplified because of their sex determination mechanism, which leads to male sterility with inbreeding when populations become small. In this system genetic structures of the parasitoid populations show that while one dispersive species has so far managed to ride out the storm, it’s own parasitoid species, a hyperparasitoid, may not. |
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| 14:00 to 15:00 | Deepa Agashe (NCBS, India) |
Evolutionary impacts of biased mutation spectra Biased mutation spectra are pervasive, with widely varying direction and magnitude of mutational biases that influence genome evolution and adaptation. Why are unbiased spectra rare, and how do such diverse biases evolve? We show that changing the mutation spectrum allows populations to sample previously under-sampled mutational space. The resulting shift in the distribution of fitness effects is advantageous: the beneficial mutation supply and beneficial pleiotropy increase, and deleterious load reduces. More broadly, adaptive walk simulations indicate that the evolution of a mutational bias in an unbiased ancestor is selectively neutral; but reversing the direction of a long-term bias is always selectively favoured. Indeed, spectrum changes in the bacterial phylogeny occur frequently, typically involving reversals of ancestral bias. Thus, shifts in mutation spectra evolve under selection, and can directly alter outcomes of adaptive evolution by facilitating access to beneficial mutations. |
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| 16:30 to 18:00 | - | Posters | ||
| 18:30 to 20:00 | Nancy Chen (University of Rochester, USA) | Relatedness and Inbreeding |
| Time | Speaker | Title | Resources | |
|---|---|---|---|---|
| 09:30 to 11:00 | Michael Lynch (University of Arizona, USA) |
Evolution as a Population-Genetic Process (Lecture 2) Critical to understanding the evolutionary potential and limitations of phylogenetic lineages is information on the distribution of fitness and phenotypic effects of new mutations. Based on bioenergetic considerations alone, few mutations can have absolutely zero effects, and multiple lines of evidence indicate that the vast majority of mutations are deleterious, with most being very mildly so and the mode being near zero. More |
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| 11:30 to 12:30 | Nishad Matange (IISER - Pune, India) |
The Evolutionary Logic of Antimicrobial Resistance The evolution of antimicrobial resistance (AMR) is akin to natural selection. Bacterial populations challenged with antibiotics rapidly evolve drug resistance due to the fixation of resistance-conferring mutations. In recent years, genome sequencing has revealed that mutations in bacteria that are selected by antibiotics can have a variety of different mechanisms by which they confer resistance. Further, different mutations that confer resistance show strong genetic interactions, i.e. epistasis, which produces a variety of interesting effects at the cellular and population levels. My group has been trying to understand what the evolutionary logic of mutation fixation is in bacteria challenged with antibiotics. In this talk, I will describe some of our efforts in trying to relate mutation, mechanism, environment and selection using laboratory evolution of drug resistance in E. coli to ultimately understand why certain sequences and combinations of mutations are successful during the evolution of AMR. |
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| 14:00 to 15:00 | Chaitanya Gokhale (Max Planck Institute for Evolutionary Biology, Germany) | From games to genes... and back | ||
| 16:30 to 18:00 | Guillaume Martin (Universidad de Montpellier II, France) | Mutation, Selection and Evolutionary Rescue in Simple Phenotype-fitness Landscapes (Lecture 2) |
| Time | Speaker | Title | Resources | |
|---|---|---|---|---|
| 09:30 to 11:00 | Michael Lynch (University of Arizona, USA) |
Evolution of Cellular Complexity (Lecture 3) To minimize energetic costs and mutational vulnerability, all other things being equal, natural selection is expected to always favor simplicity over complexity. Yet, many aspects of cell biology are demonstrably over-designed, particularly in eukaryotes, and most notably in multicellular species. More |
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| 11:00 to 11:30 | Organisers | Closing Remarks |