Evolutionary constraint facilitates interpretation of genetic variation in resequenced human genomes
David L. Goode1, Gregory M. Cooper2, Jeremy Schmutz3,4, Mark Dickson3, Eidelyn Gonzales3, Ming Tsai3,4, Kalpana Karra5, Eugene Davydov6, Serafim Batzoglou6, Richard M. Myers3,4 and Arend Sidow1,5,7
+Author Affiliations
1 Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA;
2 Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA;
3 Stanford Human Genome Center, Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA;
4 HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA;
5 Department of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA;
6 Department of Computer Science, Stanford University, Stanford, California 94305-5428, USA
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 (<1%) to high frequency (>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.
Footnotes
↵7 Corresponding author.
E-mail arend@stanford.edu; fax (630) 725-4905.
[Supplemental material is available online at http://www.genome.org. All sequences can be retrieved from the NCBI Trace Archive (http://www.ncbi.nlm.nih.gov/Traces/trace.cgi) using the search string CENTER_NAME = “SHGC” and SPECIES_CODE = “HOMO SAPIENS”.]
Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.102210.109.
Received October 20, 2009.
Accepted January 8, 2010.
Copyright © 2010 by Cold Spring Harbor Laboratory Press
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