Computational and EvolutionaryMolecular Biology

Yun S. Song

UC Berkeley, CS Grad Visit DayMarch 17, 2008

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Introduction Short-read resequencing Coalescent Theory DE

Biosystems & Computational Biology

CS faculty members:

Ruzena BajcsyBrian A. BarskyJerome A. FeldmanMichael I. Jordan (coordinator)Richard KarpJitendra MalikElchanan Mossel

Christos PapadimitriouLior PachterSatish RaoStuart J. RussellYun S. SongBernd SturmfelsKatherine Yelick

In what follows, I will give a brief overview of my group’sresearch interests.

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Introduction Short-read resequencing Coalescent Theory DE

Biosystems & Computational Biology

CS faculty members:

Ruzena BajcsyBrian A. BarskyJerome A. FeldmanMichael I. Jordan (coordinator)Richard KarpJitendra MalikElchanan Mossel

Christos PapadimitriouLior PachterSatish RaoStuart J. RussellYun S. SongBernd SturmfelsKatherine Yelick

In what follows, I will give a brief overview of my group’sresearch interests.

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Introduction Short-read resequencing Coalescent Theory DE

Computational BiologyThe use of computational and mathematical techniques toaddress questions arising from biology.Examples: Forensic DNA analysis, Sequence alignment,Genome-wide disease gene mapping, Phylogenetics

Mathematical Population GeneticsThe study of the evolutionary forces (such as populationhistory, natural selection, and recombination) that produceand maintain genetic variation within species.Tightly linked to many branches of mathematics.

Tools usedAlgorithmsGraph theoryCombinatoricsStochastic processes

Dynamical systemsMachine learningSignal processingReconfigurable computing

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Introduction Short-read resequencing Coalescent Theory DE

High-throughput short-read resequencing

Genomic sequencing technology entered a revolutionaryphase in 2007.High-throughput short-read sequencing technology candeliver fast and cost-effective generation of immenseamounts of sequence data.For instance, we can now sequence a Drosophila genomein a few days and a human genome in a few weeks usingthe Solexa/Illumina platform.

The main and immediate challengeThe assembly and analyses of short-read resequencing data.

We want to develop efficient algorithms and computationalinfrastructure to meet that challenge, addressing the sheervolume and nature of short-read data.

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Introduction Short-read resequencing Coalescent Theory DE

Short-read sequencing

hundreds of millions of them)

Randomly fragmentgenomic DNA

Sequence short−reads

Assemble

(tens of millions to

In the Solexa/Illumina platform, each short-read is between30 to 45 base-pairs long.

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Introduction Short-read resequencing Coalescent Theory DE

Our approach1 Simultaneously map hundreds of short-reads onto a

reference genome using FPGA.

Calculates diagonal score

a = score_diagb = score_leftc = score_up

Outputs minimum score

Calculates minimum score

Reset lastlast one pulsebefore this PE startscomputing on valid data.

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2 Use graph-theory-based algorithms to assemble the shortreads into a complete genome, while detecting geneticvariation and correcting for sequencing errors.

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Introduction Short-read resequencing Coalescent Theory DE

1000 human genomes

The National Human Genome Research Institute (NHGRI)recently announced an international collaboration toresequence 1000 human genomes from around the world.(http://www.1000genomes.org/)

1000 Drosophila genomesMy group is closely involved in a project that proposes toresequence 1000 Drosophila genomes.

A well-studied model organism.About 20 times shorter than the human genome.Drosophila genome is less repetitive.Can perform direct functional analysis.

Further Computational ChallengeHow are we going to analyze 1000 genomes?

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Introduction Short-read resequencing Coalescent Theory DE

1000 human genomes

The National Human Genome Research Institute (NHGRI)recently announced an international collaboration toresequence 1000 human genomes from around the world.(http://www.1000genomes.org/)

1000 Drosophila genomesMy group is closely involved in a project that proposes toresequence 1000 Drosophila genomes.

A well-studied model organism.About 20 times shorter than the human genome.Drosophila genome is less repetitive.Can perform direct functional analysis.

Further Computational ChallengeHow are we going to analyze 1000 genomes?

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Introduction Short-read resequencing Coalescent Theory DE

Coalescent Theory (CS294-26/STAT260)Random rooted graph with directed, weighted, markededges.Related to random partitions, size-biased permutations,and other combinatorial structures.

Some questions that can be addressed using the coalescentHow many ancestors at time t back in time?Who is related to whom?Time to the common ancestor.The age of a mutation.Population history.Targets and dynamics of natural selection.Speciation.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

The coalescent with recombinationA retrospective stochastic genealogical process with collisionsand branchings of lineages.

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Introduction Short-read resequencing Coalescent Theory DE

Computational biology is an active area of research at UC Berkeley.

Designated Emphasis in Computational and Genomic BiologyAbout 30 faculty members spanning 7 Departments:

BioengineeringBiostatisticsChemistryEECSIntegrative BiologyMathematicsStatistics

(http://computationalbiology.berkeley.edu/)

Faculty members in CS affiliated with the DEMichael I. Jordan, Richard M. Karp, Lior Pachter, Yun S. Song,Bernd Sturmfels

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