There is much interest in characterizing the variation in a human individual, because this may elucidate what contributes significantly to a person's phenotype, thereby enabling personalized genomics. We focus here on the variants in a person's ‘exome,’ which is the set of exons in a genome, because the exome is believed to harbor much of the functional variation. We provide an analysis of the ∼12,500 variants that affect the protein coding portion of an individual's genome. We identified ∼10,400 nonsynonymous single nucleotide polymorphisms (nsSNPs) in this individual, of which ∼15–20% are rare in the human population. We predict ∼1,500 nsSNPs affect protein function and these tend be heterozygous, rare, or novel. Of the ∼700 coding indels, approximately half tend to have lengths that are a multiple of three, which causes insertions/deletions of amino acids in the corresponding protein, rather than introducing frameshifts. Coding indels also occur frequently at the termini of genes, so even if an indel causes a frameshift, an alternative start or stop site in the gene can still be used to make a functional protein. In summary, we reduced the set of ∼12,500 nonsilent coding variants by ∼8-fold to a set of variants that are most likely to have major effects on their proteins' functions. This is our first glimpse of an individual's exome and a snapshot of the current state of personalized genomics. The majority of coding variants in this individual are common and appear to be functionally neutral. Our results also indicate that some variants can be used to improve the current NCBI human reference genome. As more genomes are sequenced, many rare variants and non-SNP variants will be discovered. We present an approach to analyze the coding variation in humans by proposing multiple bioinformatic methods to hone in on possible functional variation.
Characterizing the functional variation in an individual is an important step towards the era of personalized medicine. Protein-coding exons are thought to be especially enriched in functional variation. In 2007, we published the genome sequence of J. Craig Venter. Here we analyze the genetic variation of J. Craig Venter's exome, focusing on variation in the coding portion of genes, which is thought to contribute significantly to a person's physical make-up. We survey ∼12,500 nonsilent coding variants and, by applying multiple bioinformatic approaches, we reduce the number of potential phenotypic variants by ∼8-fold. Our analysis provides a snapshot of the current state of personalized genomics. We find that <1% of variants are linked to any known phenotypes; this demonstrates the dearth of scientific knowledge for phenotype-genotype associations. However, ∼80% of an individual's nonsynonymous variants are commonly found in the human population and, because phenotypic associations to common variants will be elucidated via genome-wide association studies over the next few years, the capability to interpret personalized genomes will expand and evolve. As sequencing of individual genomes becomes more prevalent, the bioinformatic approaches we present in this study can be used as a paradigm to pursue the study of protein-coding variants for the genomes of many individuals.