This application responds to NHGRI's call for Medical Sequencing Discovery Projects that will use next-generation sequencing technology to tackle high-impact challenges in medical genetics. We propose to build on our successes in the study of blood lipid levels and other complex traits in a Sardinian population cohort by generating draft whole genome sequences for 1,000 individuals using whole genome shotgun approaches, as pioneered by the 1,000 Genomes Project. The proposed experimental plan poses many logistical, computational and statistical challenges, which we are uniquely poised to address - as evidenced by our track record in the organization and phenotyping of the population cohort from a highly inter-related town-dwelling subgroup of the founder Sardinian population, and in the development and deployment of tools for the analysis of cutting edge human genetics data. The proposed plan will allow us to evaluate the contribution of common (frequency >5.0%) and rare (frequency 0.5 - 5.0%) single nucleotide polymorphisms, short insertions and deletions, large copy number polymorphisms and other structural variants to blood levels of low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c) and triglycerides (TG), all of which are key risk factors for cardiovascular disease. The isolated Sardinian population is ideal for this type of study for several reasons, and in particular because: (i) the bottleneck that occurred after colonization of the island attenuated natural selection against deleterious alleles, increasing the odds that deleterious alleles will reach modest frequencies (0.5 - 5.0%) and will be detected in the present study;(ii) our ascertainment of many relatives of the individuals to be sequenced enables us and our collaborators to investigate the effects of any rare alleles we identify by genotyping the relatives of sequenced individuals;(iii) sharing of long haplotype stretches surrounding rare variants will facilitate imputation based analyses of shotgun sequence data, which improve the accuracy of individual genotype calls and thus increase power. The proposed research will help advance NIH's mission by furthering our understanding of the genetic factors contributing to blood lipid levels and coronary heart disease. In addition, these studies will result in experimental strategies and analysis tools that will be readily deployable by many laboratories to study the genomes of hundreds to thousands of individuals and further our understanding of the genetics and biology of many different traits and conditions.

Public Health Relevance

In the past several years, genome-wide association studies have furthered our understanding of the molecular basis blood lipid levels, which are key risk factors for the development of cardiovascular disease. The success of these studies resulted, in large part, from their ability to explore the genome in a comprehensive manner, systematically assessing the impact of common variation on the trait of interest. Here we propose to deploy high-throughput sequencing technologies to extend these systematic whole genome assessments to include rarer variants as well. To maximize our chances of success, we focus our study on an isolated founder population in Sardinia, which is ideal for the study of rare genetic variants. Our results should expand the understanding of the genetics of blood lipid levels and also result in strategies that can be widely deployed to study many human traits. In this way, the proposed research plan addresses several objectives of the Grand Opportunity call;it describes groundbreaking, innovative, high impact research that has the potential to accelerate human genetics research for a wide range of complex phenotypes.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
High Impact Research and Research Infrastructure Programs (RC2)
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Special Emphasis Panel (ZHG1-HGR-P (O1))
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Wang, Lu
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University of Michigan Ann Arbor
Biostatistics & Other Math Sci
Schools of Public Health
Ann Arbor
United States
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