A group of scientists, based primarily at Stanford University School of Medicine, have introduced ethnicity-specific reference genome sequences in a study to be published in the open-access journal PLoS Genetics on September 15th. Their utility was demonstrated in analyzing the genomes of a four-person family and following the flow of genes, in particular those associated with disease risk, from one generation to the next.
The researchers augmented the widely-used human reference genome, the result of the Human Genome Project. This reference genome lacks the most common variants at 1.6 million genomic positions, 4,000 of which affect disease risk. For the current study, using published genetic data from hundreds of unrelated people, the scientists developed three ethnicity-specific synthetic reference genomes, each containing the most common variants for that group. Comparing an individual's genome to one that is ethnically matched and contains the most common variants aides the detection of rare disease risk variants and reduces the number of errors in determining each person's exact genome sequence, the researchers found.
Using the genomes of the family, the research team was able to estimate the average mutation rate in the human population and more finely pinpoint the mixing of chromosomes, a process that maximizes genetic diversity across generations. The characterization of flow of genetic information enabled the identification of sequencing errors and, specifically, genetic risk factors associated with predisposition to blood clot formation and response to blood-thinning medications. Furthermore, a sequence-based methodology for Human Leukocyte Antigen (HLA) typing was presented. HLA types are the sets of variable immune system genes that determine pathogen recognition and are associated with several disease traits including autoimmune diseases and psoriasis, of which all four family members — parents, daughter and son — are at high risk.
The authors suggest that, as the cost for whole-genome sequencing lowers, the need to interpret these data grows. "The ethnicity-specific, family-based approaches to interpretation of individual genetic profiles are emblematic of the next generation of genetic risk assessment using whole-genome sequencing," the authors conclude.
FINANCIAL DISCLOSURE: FED was supported by NIH/NHLBI training grant T32 HL094274-01A2 and the Stanford University School of Medicine Dean's Postdoctoral Fellowship. MTW was supported by NIH National Research Service Award fellowship F32 HL097462. JKB, OEC, and CDB were supported by NHGRI grant U01HG005715. CFT, JMH, KS, LG, MW-C, MW, and RBA were supported by grants from the NIH/NIGMS U01 GM61374. KEO was supported by NIH/NHGRI 5 P50 HG003389-05. AJB was supported by the Lucile Packard Foundation for Children's Health, Hewlett Packard Foundation, and NIH/NIGMS R01 GM079719. JTD and KJK were supported by NIH/NLM T15 LM007033. EAA was supported by NIH/NHLBI KO8 HL083914, NIH New Investigator DP2 Award OD004613, and a grant from the Breetwor Family Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
COMPETING INTERESTS: JVT and AWZ are founders, consultants, and equity holders in Clinical Future; GMC has advisory roles in and research sponsorships from several companies involved in genome sequencing technology and personal genomics (see http://arep.med.harvard.edu/gmc/tech.html); MS is on the scientific advisory board of DNA Nexus and holds stock in Personalis; RBA has received consultancy fees from Novartis and 23andMe and holds stock in Personalis; AJB is a scientific advisory board member and founder for NuMedii and Genstruct, a scientific advisory board member for Johnson and Johnson, has received consultancy fees from Lilly, NuMedii, Johnson and Johnson, Genstruct, Tercica, and Prevendia and honoraria from Lilly and Siemens, and holds stock in NuMedii, Genstruct, and Personalis. EAA holds stock in Personalis.
CITATION: Dewey FE, Chen R, Cordero SP, Ormond KE, Caleshu C, et al. (2011) Phased Whole-Genome Genetic Risk in a Family Quartet Using a Major Allele Reference Sequence. PLoS Genet 7(9): e1002280. doi:10.1371/journal.pgen.1002280
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