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research [2015/04/07 17:57]
ivan
research [2016/08/31 21:54]
shamil
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 Some of our findings include the demonstrated association between mutation rate and replication timing; elevated mutation rate in functional regions due to maintenance of hypermutable sites by natural selection; and a unique spectrum of clustered mutations suggesting a specific mechanism generating clustered mutations. For somatic cancer mutations, we demonstrated that the relationship between chromatin accessibility and modification and mutation rate is highly cell-type specific. We also showed that the somatic mutation rate is decreased in regulatory regions marked by accessible chromatin, and linked this observation to the action of nucleotide excision repair. Some of our findings include the demonstrated association between mutation rate and replication timing; elevated mutation rate in functional regions due to maintenance of hypermutable sites by natural selection; and a unique spectrum of clustered mutations suggesting a specific mechanism generating clustered mutations. For somatic cancer mutations, we demonstrated that the relationship between chromatin accessibility and modification and mutation rate is highly cell-type specific. We also showed that the somatic mutation rate is decreased in regulatory regions marked by accessible chromatin, and linked this observation to the action of nucleotide excision repair.
  
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 <WRAP leftalign>//​**Functional effect of allelic variants**//</​WRAP>​ <WRAP leftalign>//​**Functional effect of allelic variants**//</​WRAP>​
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 In non-coding regions of the genome, the effects of regulatory variants can also be analyzed using a combination of functional and comparative genomics data. Here, we are interested in using Whole Genome Sequencing to identify regulatory variants of larger effects in humans and animals. In non-coding regions of the genome, the effects of regulatory variants can also be analyzed using a combination of functional and comparative genomics data. Here, we are interested in using Whole Genome Sequencing to identify regulatory variants of larger effects in humans and animals.
  
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 <WRAP rightalign>//​**Population genetics**//</​WRAP>​ <WRAP rightalign>//​**Population genetics**//</​WRAP>​
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 Our recent results include the demonstration that deleterious alleles are younger than neutral alleles at the same population frequency. We studied the effect of population bottlenecks and expansions on the burden of deleterious mutations under arbitrary dominance coefficient. We are currently interested in the inference of complex natural selection in the form of balancing selection, genetic dominance, epistasis, and pleiotropy from population sequencing data. Our recent results include the demonstration that deleterious alleles are younger than neutral alleles at the same population frequency. We studied the effect of population bottlenecks and expansions on the burden of deleterious mutations under arbitrary dominance coefficient. We are currently interested in the inference of complex natural selection in the form of balancing selection, genetic dominance, epistasis, and pleiotropy from population sequencing data.
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-**Evolution,​ maintenance and allelic architecture of complex traits**\\ +<WRAP clear></​WRAP>​ 
 +<WRAP leftalign>//​**Evolution,​ maintenance and allelic architecture of complex traits**//</​WRAP>​
 {{:​heritability.png?​nolink&​400 |}} {{:​heritability.png?​nolink&​400 |}}
 Despite widespread interest in the genetics of complex traits (including common human diseases), basic principles of complex trait genetics are still poorly understood. We attack the problem from three directions. First, we develop theoretical models of evolution and maintenance of complex trait variation under various allelic architectures. Second, we are involved in a large zebrafish screen aiming at identification of key parameters of allelic architecture of complex traits. Third, we work on statistical methods for the analysis of available genomic data in phenotyped human populations. This includes methods for predicting complex phenotypes from genotypes. Despite widespread interest in the genetics of complex traits (including common human diseases), basic principles of complex trait genetics are still poorly understood. We attack the problem from three directions. First, we develop theoretical models of evolution and maintenance of complex trait variation under various allelic architectures. Second, we are involved in a large zebrafish screen aiming at identification of key parameters of allelic architecture of complex traits. Third, we work on statistical methods for the analysis of available genomic data in phenotyped human populations. This includes methods for predicting complex phenotypes from genotypes.
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-**Computational and statistical methods for sequencing studies**\\ +<WRAP clear></​WRAP>​ 
 +<WRAP rightalign>//​**Computational and statistical methods for sequencing studies**//</​WRAP>​
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 We develop computational and statistical methods for sequencing studies. VT-test is designed to detect combined association of rare variants with a complex phenotype. SNPTrack has been developed for gene mapping in model organisms. We continue developing new methods including methods that benefit from pedigree collection and functional genomic data. We actively participate in collaborative projects devoted to sequencing of populations with common diseases. We develop computational and statistical methods for sequencing studies. VT-test is designed to detect combined association of rare variants with a complex phenotype. SNPTrack has been developed for gene mapping in model organisms. We continue developing new methods including methods that benefit from pedigree collection and functional genomic data. We actively participate in collaborative projects devoted to sequencing of populations with common diseases.
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 +<WRAP leftalign>//​**[[Brigham Genomic Medicine (BGM)]]**//</​WRAP>​
  
-**Personal Genomics Consultation Service (PGCS)**\\ ​ 
 {{:​pgcs.png?​nolink&​400 |}} {{:​pgcs.png?​nolink&​400 |}}
-The lab is intertwined with the computational component of Personal Genome Consultation Service. This service aims at discovering genes underlying previously uncharacterized human Mendelian diseases of rare diseases with unknown genetic etiology. We use genomic data of individual pedigrees to identify mutations potentially causing the phenotypes. +The lab is intertwined with the computational component of Brigham Genomic Medicine (BGM) program. This service aims at discovering genes underlying previously uncharacterized human Mendelian diseases of rare diseases with unknown genetic etiology. We use genomic data of individual pedigrees to identify mutations potentially causing the phenotypes.