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Nat Commun. 2016 Apr 18;7:11101. doi: 10.1038/ncomms11101.

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

Author information

1
Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA.
2
Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut 06520, USA.
3
Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA.
4
Department of Computer Science, Yale University, New Haven, Connecticut, 06520, USA.
5
Keck Biotechnology Resource Laboratory, Yale University, New Haven, Connecticut 06511, USA.

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).

PMID:
27089393
PMCID:
PMC4837449
DOI:
10.1038/ncomms11101
[Indexed for MEDLINE]
Free PMC Article

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