Analysis and interpretation of DNA Sequence Data in Association Studies

Summary

Principal Investigator: Jonathan Pritchard
Affiliation: University of Chicago
Country: USA
Abstract: It is becoming feasible to generate massive quantities of DNA sequence data for disease association studies. This presents both challenges and opportunities for human genetics. Perhaps most importantly, with large scale resequencing data, it will be possible to start identifying genes at which rare variants contribute to disease susceptibility. Here we propose to create a number of the analytical tools that will be needed for analyzing and interpreting the forthcoming data. Our first two Aims focus on using some of the first genome-wide resequencing data to better annotate noncoding sites that are likely to be functional. Our third Aim develops statistical methods for analyzing data that emerge from disease association studies to identify genes with rare variants that contribute to disease. The statistical methods will use the annotation approaches that we will develop in the first two Aims to prioritize variants according to the likelihood that they might have biological function. Using, in part, our improved functional annotation of potentially functional sites, we will also develop new statistical methods to identify genes that contribute to disease phenotypes through the action of many rare variants.
Funding Period: ----------------2008 - ---------------2011-
more information: NIH RePORT

Top Publications

  1. pmc The deleterious mutation load is insensitive to recent population history
    Yuval B Simons
    1 Department of Ecology, Evolution and Behavior, Hebrew University of Jerusalem, Jerusalem, Israel 2
    Nat Genet 46:220-4. 2014
  2. pmc Identification of genetic variants that affect histone modifications in human cells
    Graham McVicker
    Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
    Science 342:747-9. 2013
  3. pmc Inference of population splits and mixtures from genome-wide allele frequency data
    Joseph K Pickrell
    Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
    PLoS Genet 8:e1002967. 2012
  4. pmc Dissecting the regulatory architecture of gene expression QTLs
    Daniel J Gaffney
    Department of Human Genetics, University of Chicago, 920 E58th Street, Chicago, IL 60637, USA
    Genome Biol 13:R7. 2012
  5. doi Comment on "Widespread RNA and DNA sequence differences in the human transcriptome"
    Joseph K Pickrell
    Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
    Science 335:1302; author reply 1302. 2012
  6. pmc Exon-specific QTLs skew the inferred distribution of expression QTLs detected using gene expression array data
    Jean Baptiste Veyrieras
    Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
    PLoS ONE 7:e30629. 2012
  7. pmc DNase I sensitivity QTLs are a major determinant of human expression variation
    Jacob F Degner
    Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA
    Nature 482:390-4. 2012
  8. pmc Efficient counting of k-mers in DNA sequences using a bloom filter
    Páll Melsted
    Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
    BMC Bioinformatics 12:333. 2011
  9. pmc False positive peaks in ChIP-seq and other sequencing-based functional assays caused by unannotated high copy number regions
    Joseph K Pickrell
    Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
    Bioinformatics 27:2144-6. 2011
  10. pmc A genome-wide study of DNA methylation patterns and gene expression levels in multiple human and chimpanzee tissues
    Athma A Pai
    Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
    PLoS Genet 7:e1001316. 2011

Scientific Experts

Detail Information

Publications17

  1. pmc The deleterious mutation load is insensitive to recent population history
    Yuval B Simons
    1 Department of Ecology, Evolution and Behavior, Hebrew University of Jerusalem, Jerusalem, Israel 2
    Nat Genet 46:220-4. 2014
    ..However, for those diseases that have a direct impact on fitness, strongly deleterious rare mutations probably do have an important role, and recent growth will have increased their impact. ..
  2. pmc Identification of genetic variants that affect histone modifications in human cells
    Graham McVicker
    Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
    Science 342:747-9. 2013
    ..Furthermore, variants that affect chromatin at distal regulatory sites frequently also direct changes in chromatin and gene expression at associated promoters. ..
  3. pmc Inference of population splits and mixtures from genome-wide allele frequency data
    Joseph K Pickrell
    Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
    PLoS Genet 8:e1002967. 2012
    ..Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com...
  4. pmc Dissecting the regulatory architecture of gene expression QTLs
    Daniel J Gaffney
    Department of Human Genetics, University of Chicago, 920 E58th Street, Chicago, IL 60637, USA
    Genome Biol 13:R7. 2012
    ..Using the HapMap lymphoblastoid cell lines, we combine 1000 Genomes genotypes and an extensive catalogue of human functional elements to investigate the biological mechanisms that eQTLs perturb...
  5. doi Comment on "Widespread RNA and DNA sequence differences in the human transcriptome"
    Joseph K Pickrell
    Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
    Science 335:1302; author reply 1302. 2012
    ..We found that at least 88% of these sequence mismatches can likely be explained by technical artifacts such as errors in mapping sequencing reads to a reference genome, sequencing errors, and genetic variation...
  6. pmc Exon-specific QTLs skew the inferred distribution of expression QTLs detected using gene expression array data
    Jean Baptiste Veyrieras
    Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
    PLoS ONE 7:e30629. 2012
    ..Nonetheless, we do observe an overall enrichment of eQTLs in exons versus introns in all three data sets, consistent with an important role for exonic sequences in gene regulation...
  7. pmc DNase I sensitivity QTLs are a major determinant of human expression variation
    Jacob F Degner
    Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA
    Nature 482:390-4. 2012
    ..Our observations indicate that dsQTLs are highly abundant in the human genome and are likely to be important contributors to phenotypic variation...
  8. pmc Efficient counting of k-mers in DNA sequences using a bloom filter
    Páll Melsted
    Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
    BMC Bioinformatics 12:333. 2011
    ..These singleton k-mers are uninformative for many algorithms without some kind of error correction...
  9. pmc False positive peaks in ChIP-seq and other sequencing-based functional assays caused by unannotated high copy number regions
    Joseph K Pickrell
    Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
    Bioinformatics 27:2144-6. 2011
    ..Here, we consider whether false positive peak calls can be caused by particular type of error in the reference genome: multicopy sequences which have been incorrectly assembled and collapsed into a single copy...
  10. pmc A genome-wide study of DNA methylation patterns and gene expression levels in multiple human and chimpanzee tissues
    Athma A Pai
    Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
    PLoS Genet 7:e1001316. 2011
    ..In particular, we estimate that, in the tissues we studied, inter-species differences in promoter methylation might underlie as much as 12%-18% of differences in gene expression levels between humans and chimpanzees...
  11. pmc DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines
    Jordana T Bell
    Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
    Genome Biol 12:R10. 2011
    ..Here we measured methylation levels at 22,290 CpG dinucleotides in lymphoblastoid cell lines from 77 HapMap Yoruba individuals, for which genome-wide gene expression and genotype data were also available...
  12. pmc Noisy splicing drives mRNA isoform diversity in human cells
    Joseph K Pickrell
    Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America
    PLoS Genet 6:e1001236. 2010
    ..7% and show that introns in highly expressed genes are spliced more accurately, likely due to their shorter length. These results implicate noisy splicing as an important property of genome evolution...
  13. doi Adaptation - not by sweeps alone
    Jonathan K Pritchard
    Department of Human Genetics, Howard Hughes Medical Institute, University of Chicago, Illinois 60615, USA
    Nat Rev Genet 11:665-7. 2010
    ..Jonathan Pritchard and Anna Di Rienzo argue that many adaptive events in natural populations may occur by polygenic adaptation, which would largely go undetected by conventional methods for detecting selection...
  14. pmc Understanding mechanisms underlying human gene expression variation with RNA sequencing
    Joseph K Pickrell
    Department of Human Genetics, The University of Chicago, Chicago 60637, USA
    Nature 464:768-72. 2010
    ..Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing and allele-specific expression across individuals...
  15. pmc The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation
    Jonathan K Pritchard
    Department of Human Genetics, The University of Chicago, Room 507, 929 E 58th St, Chicago, IL 60637, USA
    Curr Biol 20:R208-15. 2010
    ..We close by discussing some of the likely opportunities for progress in the field...
  16. pmc Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data
    Jacob F Degner
    Department of Human Genetics, University of Chicago, 920 E 58th St, CLSC 507, Chicago, IL 60637, USA
    Bioinformatics 25:3207-12. 2009
    ..Here, we investigate the impact of SNP variation on the reliability of read-mapping in the context of detecting allele-specific expression (ASE)...
  17. pmc Characterizing natural variation using next-generation sequencing technologies
    Yoav Gilad
    Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
    Trends Genet 25:463-71. 2009
    ..A better understanding of the sources of error and bias in sequencing data is essential, especially in the context of studies of variation at dynamic quantitative traits...