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

Jieming Chen, Joel Rozowsky, Timur R. Galeev, Arif Harmanci, Robert Kitchen, Jason Bedford, Alexej Abyzov, Yong Kong, Lynne Regan and Mark Gerstein ()
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Jieming Chen: Program in Computational Biology and Bioinformatics, Yale University
Joel Rozowsky: Program in Computational Biology and Bioinformatics, Yale University
Timur R. Galeev: Program in Computational Biology and Bioinformatics, Yale University
Arif Harmanci: Program in Computational Biology and Bioinformatics, Yale University
Robert Kitchen: Program in Computational Biology and Bioinformatics, Yale University
Jason Bedford: Program in Computational Biology and Bioinformatics, Yale University
Alexej Abyzov: Program in Computational Biology and Bioinformatics, Yale University
Yong Kong: Yale University
Lynne Regan: Program in Computational Biology and Bioinformatics, Yale University
Mark Gerstein: Program in Computational Biology and Bioinformatics, Yale University

Nature Communications, 2016, vol. 7, issue 1, 1-13

Abstract: 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).

Date: 2016
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DOI: 10.1038/ncomms11101

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