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 populationspecific 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.[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 SPE-CIES_CODE = ''HOMO SAPIENS' '.] As the sequencing of human genomes becomes routine, a growing challenge is how to assess the functional consequences of the genetic variation carried by a given individual. Of the >3 million variants present in any given human genome (Levy et al. 2007;Bentley et al. 2008;Wang et al. 2008;Kim et al. 2009;Mardis et al. 2009;McKernan et al. 2009), only a small fraction are expected to be phenotypically relevant (Kimura 1983;Ng et al. 2008;Mardis et al. 2009); among those that are, there is a great range in the degree to which they contribute to phenotype . Therefore, to fully leverage the benefits of genome-wide variation data, methods for detecting and evaluating functional variants across the entire genome are required, as is an improved understanding of the nature of functional human genetic variation.One strategy for identifying potentially important genetic variants is to focus on polymorphisms that fall into regions that have well-defined molecular functions, such as protein-coding exons. Several methods exist to estimate the impact of nonsynonymous changes on protein function, using data on the physicochem...