Technion
 
         Computer Science Colloquium
 
Time+Place : Tuesday 27/12/2011 14:30 room 337-8 Taub  Bld.
 
Speaker    : Ilan Gronau
 
Affiliation: Postdoc at the Siepel lab, Department of Biology
             Statistics and Computational Biology, Cornell University
 
Host       : Shlomo Moran
 
Title      : Using Individual Human Genomes to Illuminate the Mysteries
             of Early Human History
 
Abstract   :
 
In the decade since the publication of the first draft of the human genome
sequence, there has been a growing effort to sequence more human
individuals. These data provide a rich source of information about human
evolution, however, this potential has not yet been realized. We recently
developed a modeling framework based on coalescent theory, which allows
inference of key demographic parameters of ancient human population history
from a small number of individual genome sequences. We implemented a
Bayesian inference algorithm for infering ancestral population sizes,
divergence times, and migration rates from a set of sequence alignments at
many neutrally evolving loci along the genome. Our algorithm, called G-PhoCS
(Generalized Phylogenetic Coalescent Sampler), draws its inference from the
patterns of variation in the genealogies at many neutrally evolving loci.
Essentially, it exploits the fact that even small numbers of present-day
genomes represent many ancestral genomes, which have been shuffled and
assorted by the process of recombination.
Because the sequences provide only very weak information about the genealogy
at each locus, the method integrates over candidate genealogies using Markov
chain Monte Carlo (MCMC) sampling. The implementation of G-Phocs was
designed to be efficient enough to facilitate analysis of genome-wide
sequence data from multiple individuals.
 
We used G-PhoCS to examine the published genome sequences of six individuals
from six different population groups from East-Asia, Europe, Western and
Southern Africa. One of these individuals is a member of the
Khoisan-speaking hunter-gatherer population of Southern Africa, known
collectively as the San. The San exhibit one of the highest known levels of
genetic divergence from other human populations, and are therefore highly
informative about ancient human demography. Applying G-PhoCS to these
sequences, we were able to provide highly confident estimates of divergence
times and ancestral population sizes, taking into account various scenarios
of gene flow between populations. Our main focus was on the time of
divergence of the San population from other populations, as well as the
divergence of Eurasian populations from African populations (also referred
to as the "out-of-Africa" date).
 
In this talk, I will present our Bayesian inference algorithm, G-PhoCS,
highlighting the main modeling challenges tackled in its design and
implementation. I will also describe the pipeline we developed for preparing
the sequence data for analysis, making sure to account for various potential
sources of bias. I will summarize the demographic estimates we obtained in
our data analysis, and compare them to previously published estimates based
on genetic data. To conclude, I will mention some projects we are currently
working on in the Siepel lab, involving analysis of a recently published set
of 54 individual human genomes from a wide array of populations.
 
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See:  <http://www.nature.com/ng/journal/v43/n10/full/ng.937.html>
Gronau I, Hubisz MJ, Gulko B, Danko CG, Siepel A.   Bayesian inference
of ancient human demography from individual genome sequences.  Nature
Genetics 43 1031-1034.   2011
 
G-PhoCS web site:  <http://compgen.bscb.cornell.edu/GPhoCS/>
 
Short Bio:
 
Ilan Gronau has been a postdoctoral fellow at the Siepel lab in Cornell
since 2009. He completed his Ph.D. in CS at the Technion under supervision
of Prof. Shlomo Moran. Ilan studies mathematical and algorithmic aspects of
evolution, and currently focuses his research on developing computational
methods for analysis of fully sequenced individual genomes.
 
Refreshments served from 14:15 on,
 	Lecture starts at 14:30
 
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