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Evolutionary constraint facilitates interpretation of genetic variation in resequenced human genomes

Authors :
Arend Sidow
Eidelyn Gonzales
Jeremy Schmutz
Serafim Batzoglou
Eugene Davydov
Richard M. Myers
Ming Tsai
Gregory M. Cooper
Mark Dickson
David L Goode
Kalpana Karra
Source :
Genome Research. 20:301-310
Publication Year :
2010
Publisher :
Cold Spring Harbor Laboratory, 2010.

Abstract

Here, we demonstrate how comparative sequence analysis facilitates genome-wide base-pair-level interpretation of individual genetic variation and address two questions of importance for human personal genomics: first, whether an individual's functional variation comes mostly from noncoding or coding polymorphisms; and, second, whether population-specific or globally-present polymorphisms contribute more to functional variation in any given individual. Neither has been definitively answered by analyses of existing variation data because of a focus on coding polymorphisms, ascertainment biases in favor of common variation, and a lack of base-pair-level resolution for identifying functional variants. We resequenced 575 amplicons within 432 individuals at genomic sites enriched for evolutionary constraint and also analyzed variation within three published human genomes. We find that single-site measures of evolutionary constraint derived from mammalian multiple sequence alignments are strongly predictive of reductions in modern-day genetic diversity across a range of annotation categories and across the allele frequency spectrum from rare (10% minor allele frequency). Furthermore, we show that putatively functional variation in an individual genome is dominated by polymorphisms that do not change protein sequence and that originate from our shared ancestral population and commonly segregate in human populations. These observations show that common, noncoding alleles contribute substantially to human phenotypes and that constraint-based analyses will be of value to identify phenotypically relevant variants in individual genomes.

Details

ISSN :
10889051
Volume :
20
Database :
OpenAIRE
Journal :
Genome Research
Accession number :
edsair.doi.dedup.....a049e9ea1e2dead2e4a3ad78eef0e410
Full Text :
https://doi.org/10.1101/gr.102210.109