Search bioRxivSearch

Biology subjects

Shamil Sunyaev

Publications and source records attributed to Shamil Sunyaev.

5 recordsLinked to original sources

Negative selection in humans and fruit flies involves synergistic epistasis

Negative selection against deleterious alleles produced by mutation is the most common form of natural selection, which strongly influences within-population variation and interspecific divergence. However, some fundamental properties of negative selection remain obscure. In particular, it is still not known whether deleterious alleles affect fitness independently, so that cumulative fitness loss depends exponentially on the number of deleterious alleles, or synergistically, so that each additional deleterious allele results in a larger decrease in relative fitness. Negative selection with synergistic epistasis must produce negative linkage disequilibrium between deleterious alleles, and therefore, underdispersed distribution of the number of deleterious alleles in the genome. Indeed, we detected underdispersion of the number of rare loss-of-function (LoF) alleles in eight independent datasets from modern human and Drosophila melanogaster populations. Thus, ongoing selection against deleterious alleles is characterized by synergistic epistasis, which can explain how human and fly populations persist despite very high genomic deleterious mutation rates.

Evolutionary Biology

Shared effect modeling reveals that a fraction of autoimmune disease associations are consistent with eQTLs in three immune cell types

The majority of autoimmune disease risk effects identified by genome-wide association studies (GWAS) localize to open chromatin with gene regulatory activity. GWAS loci are also enriched for expression quantitative trait loci (eQTLs), suggesting that most disease risk variants exert their pathological effects by altering gene expression1,2. However, because causal variants are difficult to identify and cis-eQTLs occur frequently, it remains challenging to translate this bulk observation into specific instances of a disease risk variant driving changes to gene regulation. Here, we use a novel joint likelihood framework with higher resolution than previous methods to identify loci where disease risk and an eQTL are driven by a single, shared genetic effect as opposed to distinct effects in close proximity. We find that approximately 25% of autoimmune disease loci harbor an eQTL driven by the same genetic ...

Genetics

Quantifying the unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects

Introduction Introduction Results Discussion 1. Preliminaries 2.1 Performance Guarantees 2. The UnseenEst Algorithm 3. Datasets 4. Validation experiments 5. Related works 6.1 Faithful samples 6.2 Chebyshev construction 6.3 Proof of Proposition... 6. Proofs of the... References References Recent efforts aggregating the genomes and exomes of tens of thousands of individuals have provided unprecedented insights into the landscape of rare human genetic variation1,2 and generated critical resources for clinical and population genetics. The recently announced U.S. Precision Med ...

Genetics

Leveraging distant relatedness to quantify human mutation and gene conversion rates

The rate at which human genomes mutate is a central biological parameter that has many implications for our ability to understand demographic and evolutionary phenomena. We present a method for inferring mutation and gene conversion rates using the number of sequence differences observed in identical-by-descent (IBD) segments together with a reconstructed model of recent population size history. This approach is robust to, and can quantify, the presence of substantial genotyping error, as validated in coalescent simulations. We applied the method to 498 trio-phased Dutch individuals from the Genome of the Netherlands (GoNL) project, sequenced at an average depth of 13x. We infer a point mutation rate of 1.66 {+/-} 0.04 x 10-8 per base per generation, and a rate of 1.26 {+/-} 0.06 x 10-9 for < 20 bp indels. Our estimated average genome-wide mutation rate is higher than most pedigree-based estimates reported thus far, but lower than estimates obtained using substitution rates across primates. By quantifying how estimates vary as a function of allele frequency, we infer the probability that a site is involved in non-crossover gene conversion as 5.99 {+/-} 0.69 x 10-6, consistent with recent reports. We find that recombination does not have observable mutagenic effects after gene conversion is accounted for, and that local gene conversion rates reflect recombination rates. We detect a strong enrichment for recent deleterious variation among mismatching variants found within IBD regions, and observe summary statistics of local IBD sharing to closely match previously proposed metrics of background selection, but find no significant effects of selection on our estimates of mutation rate. We detect no evidence for strong variation of mutation rates in a number of genomic annotations obtained from several recent studies.

Genetics

No evidence that natural selection has been less effective at removing deleterious mutations in Europeans than in West Africans

Non-African populations have experienced major bottlenecks in the time since their split from West Africans, which has led to the hypothesis that natural selection to remove weakly deleterious mutations may have been less effective in non-Africans. To directly test this hypothesis, we measure the per-genome accumulation of deleterious mutations across diverse humans. We fail to detect any significant differences, but find that archaic Denisovans accumulated non-synonymous mutations at a higher rate than modern humans, consistent with the longer separation time of modern and archaic humans. We also revisit the empirical patterns that have been interpreted as evidence for less effective removal of deleterious mutations in non-Africans than in West Africans, and show they are not driven by differences in selection after population separation, but by neutral evolution.

Evolutionary Biology