April 2nd, Melissa Wilson Sayres: Sex-biased evolution and disease

WilsonSayres

Melissa Wilson Sayres is an evolutionary and computational biologist broadly interested in questions of genome evolution, mutation rate variation, and the consequences on species biology. She analyzes large-scale datasets to study questions relating to sex-specific mutational processes, including, how sex chromosomes arise and evolve, and how and why mutation rates differ between the sexes. She also develops models and analyzes experimental data to understand the genomic effects of natural selection, background selection, and convergent evolution.

Wilson Sayres received her B.S. in Medical Mathematics from Creighton University in Omaha, Nebraska, her Ph.D. in Integrative Biology: Bioinformatics & Genomics from The Pennsylvania State University, and currently works as a Miller postdoctoral fellow at the University of California, Berkeley.

Title: Sex-biased evolution and disease

Sex-biased processes occur on a variety of levels, from the differentiation of our sex chromosomes, to population dynamics, to the way that diseases affect each sex. The inundation of genomic and transcriptomic sequences provide the opportunity to apply computational and statistical approaches to understand sex-biased processes. The human sex chromosomes, X and Y, were once an indistinguishable pair of autosomes, but over the past 180 million years have become quite different. The Y has lost 90% of the ancestral gene content, but still retains relics of its ancestral partnership with the X. The Y chromosome, inherited through the genetic paternal line, and being nearly devoid of homologous recombination, also experiences evolutionary processes differently that regions that recombine. As such, studying patterns of genome-wide diversity can provide a unique insight into the history of sex-biased demography and selection acting on the Y chromosome. In addition to sex-biased genomics, many diseases, such as the autoimmune disease, Rheumatoid Arthritis (RA), act in a sex-biased manner. RA affects three times as many women as men, and its onset and severity are affected by a complex interaction between genotype and environment. Particularly, pregnancy often has an ameliorating effect on RA disease activity. I will discuss our computational approaches to: 1) understand the degradation of the Y, and how this process has affected the X chromosome; 2) illuminate the history of sex-biased demography and selection acting on the Y chromosome; and, 3) evaluate gene expression variation across clinical RA patients in the natural human model system of pregnancy.

Seminar details

Wednesday April 2nd, 2014
1:00 PM Lunch (sign up below)
1:15 PM Seminar
Location: Clark Center S360
If you would like to speak with Melissa, contact Pleuni Pennings (pleuni@stanford.edu)

March 19th, Eyal Elyashiv: Building a population genetic map of the effects of linked selection, with application to Drosophila melanogaster

About Eyal

Eyal Elyashiv, Columbia University

Eyal Elyashiv, Columbia University

Eyal is PhD candidate at the Hebrew University of Jerusalem and a visiting student at Columbia University, working under the supervision of Prof. Guy Sella.

Talk: Building a population genetic map of the effects of linked selection, with application to Drosophila melanogaster

Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of such “linked selection” on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and gaining insight into the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a site is polymorphic given local annotations and substitution patterns. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a population genetic map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from ~190 lines in Drosophila melanogaster and show that it reliably predicts diversity levels at the 1Mb scale, as well as helps interpret finer diversity patterns around substitutions in proteins and UTRs. The method outperforms existing ones and allows one to distinguish the contribution of sweeps from other modes of linked selection and to obtain robust estimates of sweep parameters, in particular providing strong evidence for sweeps in UTRs. More generally, our findings indicate that linked selection has had a pronounced effect in reducing diversity levels and increasing their variance in D. melanogaster, and suggest that other modes of selection (e.g. partial and soft sweeps) contribute substantially to these effects. Our approach presents the advantages of being flexible in the species to which it can be applied, the modes of selection that it can consider and in its ability to readily incorporate ever-improving functional annotations and genetic maps.

Seminar details

Wednesday March 19th, 2014
1:00 PM Lunch (sign up below)
1:15 PM Seminar
Location: Clark Center S360
If you would like to speak with Eyal, contact Jonathan Pritchard (pritch@stanford.edu)

March 12th, Claudia Bank: Shifting fitness landscapes in response to altered environments

About Claudia:

Claudia Bank

Claudia Bank

Claudia Bank is a postdoc in Jeffrey Jensen’s lab at the École Polytéchnique Fédérale de Lausanne in Switzerland, and currently spending a semester at UC Berkeley as a Simons- Berkeley fellow in the program “Evolutionary Biology and the Theory of Computing”. Following a Master’s degree in Mathematics from Germany, she obtained her PhD in Population Genetics under the supervision of Joachim Hermisson in Vienna, Austria.

Claudia’s research is focused on the study of evolution – and in particular, the population genetics of adaptation and speciation – at the interface between theoretical and empirical biology. The approaches she uses involve theoretical modeling, computational methods, and statistical data analysis.

Talk: Shifting fitness landscapes in response to altered environments

One of the most controversial questions in evolutionary biology is the role of adaptation in molecular evolution. After decades of debate between selectionists and neutralists, new high-throughput methods are beginning to illuminate the full distribution of fitness effects of new mutations. Here, we shed light on the adaptive potential in Saccharomyces cerevisiae by presenting systematic high-throughput fitness measurements for 560 point mutations in a region of Hsp90 under six environmental conditions. Under elevated salinity, we observe numerous beneficial mutations, all of which are observed to be associated with high costs of adaptation. We thus demonstrate that an essential protein can harbor adaptive potential upon an environmental challenge, and report a remarkable fit of the data to Fisher’s geometric model. In addition, we compare the differences in the DFEs resulting from mutations covering 1, 2 and 3 nucleotide steps from the wild type – showing that multiple-step mutations harbor more potential for adaptation in challenging environments, but also tend to be more deleterious in the standard environment. We utilize a Bayesian MCMC modeling framework to evaluate the statistical significance of the results – showing a remarkable accuracy of the experimental approach that allows us, e.g., to identify a deleterious synonymous mutation under standard conditions.

Seminar details

Wednesday March 12th, 2014
1:00 PM Lunch (sign up below)
1:15 PM Seminar
Location: Clark Center S360
If you would like to speak with Claudia, contact Pleuni Pennings (pleuni@stanford.edu)