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SUMMARY:New probabilistic methods for inference of natural selection on re
 gulatory sequences in the human genome - Adam Siepel\, Cornell University
DTSTART:20130219T140000Z
DTEND:20130219T150000Z
UID:TALK43013@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:For decades\, it has been hypothesized that gene regulation ha
 s played a central role in human evolution\, yet much remains unknown abou
 t the genome-wide impact of regulatory mutations.  Here we use complete ge
 nome sequence data to demonstrate that natural selection has exerted a pro
 found influence on human regulatory sequences since our divergence from ch
 impanzees 4-6 million years ago.  Our analysis is based on a new probabili
 stic method for characterizing the influence of natural selection on colle
 ctions of short regulatory elements scattered across the genome.  Our meth
 od\, called Inference of Natural Selection from Interspersed Genomically c
 oHerent elemenTs (INSIGHT)\, uses a generative probabilistic model to cont
 rast patterns of genetic variation in humans and nonhuman primates in the 
 elements of interest with those in nearby "neutral" sites.  Using a Bayesi
 an approach\, we are able to pool weak information from many short element
 s in a manner that accounts for variation across the genome in patterns of
  neutral genetic variation.  The model is efficiently fitted to genome-wid
 e data by an approximate expectation maximization algorithm.  Using simula
 tions\, we show that INSIGHT can accurately estimate the evolutionary para
 meters of interest even in complex evolutionary scenarios.  We apply it to
  real genomic data and find that binding sites have experienced somewhat w
 eaker selection than protein-coding genes\, on average\, but that the bind
 ing sites of several transcription factors show clear evidence of adaptati
 on.  We project that regulatory elements may make larger cumulative contri
 butions than protein-coding genes to both adaptive substitutions and delet
 erious polymorphisms\, which has important implications for human evolutio
 n and disease.
LOCATION:Auditorium\, Microsoft Research Ltd\, 21 Station Road\, Cambridge
 \, CB1 2FB
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