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A uniform survey of allele-specific binding and expression over 1000-Genomes-Project individuals

Author

Listed:
  • Jieming Chen

    (Program in Computational Biology and Bioinformatics, Yale University
    Integrated Graduate Program in Physical and Engineering Biology, Yale University)

  • Joel Rozowsky

    (Program in Computational Biology and Bioinformatics, Yale University
    Yale University)

  • Timur R. Galeev

    (Program in Computational Biology and Bioinformatics, Yale University
    Yale University)

  • Arif Harmanci

    (Program in Computational Biology and Bioinformatics, Yale University
    Yale University)

  • Robert Kitchen

    (Program in Computational Biology and Bioinformatics, Yale University
    Yale University)

  • Jason Bedford

    (Program in Computational Biology and Bioinformatics, Yale University)

  • Alexej Abyzov

    (Program in Computational Biology and Bioinformatics, Yale University
    Yale University
    Present address: Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota 55905, USA)

  • Yong Kong

    (Yale University
    Keck Biotechnology Resource Laboratory, Yale University)

  • Lynne Regan

    (Program in Computational Biology and Bioinformatics, Yale University
    Integrated Graduate Program in Physical and Engineering Biology, Yale University
    Yale University)

  • Mark Gerstein

    (Program in Computational Biology and Bioinformatics, Yale University
    Integrated Graduate Program in Physical and Engineering Biology, Yale University
    Yale University
    Yale University)

Abstract

Large-scale sequencing in the 1000 Genomes Project has revealed multitudes of single nucleotide variants (SNVs). Here, we provide insights into the functional effect of these variants using allele-specific behaviour. This can be assessed for an individual by mapping ChIP-seq and RNA-seq reads to a personal genome, and then measuring ‘allelic imbalances’ between the numbers of reads mapped to the paternal and maternal chromosomes. We annotate variants associated with allele-specific binding and expression in 382 individuals by uniformly processing 1,263 functional genomics data sets, developing approaches to reduce the heterogeneity between data sets due to overdispersion and mapping bias. Since many allelic variants are rare, aggregation across multiple individuals is necessary to identify broadly applicable ‘allelic elements’. We also found SNVs for which we can anticipate allelic imbalance from the disruption of a binding motif. Our results serve as an allele-specific annotation for the 1000 Genomes variant catalogue and are distributed as an online resource (alleledb.gersteinlab.org).

Suggested Citation

  • Jieming Chen & Joel Rozowsky & Timur R. Galeev & Arif Harmanci & Robert Kitchen & Jason Bedford & Alexej Abyzov & Yong Kong & Lynne Regan & Mark Gerstein, 2016. "A uniform survey of allele-specific binding and expression over 1000-Genomes-Project individuals," Nature Communications, Nature, vol. 7(1), pages 1-13, September.
  • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms11101
    DOI: 10.1038/ncomms11101
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