Data for Genetic Analysis Workshop 18: human whole genome sequence, blood pressure, and simulated phenotypes in extended pedigrees

BMC Proceedings

Proceedings

Goncalo Abecasis¹  Tom W Blackwell¹  Christian Fuchsberger¹  Goo Jun¹  Joanne E Curran²  John Blangero²  Juan M Peralta²  Thomas D Dyer²  Satish Kumar²  Ravindranath Duggirala²  Marcio A Almeida²  Laura Almasy²  Jack W Kent²  Sobha Puppala²  Donna Lehman³  Sharon Fowler³  Andrew R Wood⁴ 

[1] Department of Biostatistics, Center for Statistical Genetics, University of Michigan, 48109, Ann Arbor, Michigan, USA;Department of Genetics, Texas Biomedical Research Institute, 78227, San Antonio, Texas, USA;Division of Clinical Epidemiology, Department of Medicine, University of San Antonio Health Science Center at San Antonio, 78229, San Antonio, Texas, USA;Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK;

关键词: Systolic Blood Pressure;    Diastolic Blood Pressure;    Whole Genome Sequencing;    Genetic Analysis Workshop;    Impute Genotype;   

DOI  :  10.1186/1753-6561-8-S1-S2

来源: Springer

【 摘 要 】

Genetic Analysis Workshop 18 (GAW18) focused on identification of genes and functional variants that influence complex phenotypes in human sequence data. Data for the workshop were donated by the T2D-GENES Consortium and included whole genome sequences for odd-numbered autosomes in 464 key individuals selected from 20 Mexican American families, a dense set of single-nucleotide polymorphisms in 959 individuals in these families, and longitudinal data on systolic and diastolic blood pressure measured at 1-4 examinations over a period of 20 years. Simulated phenotypes were generated based on the real sequence data and pedigree structures. In the design of the simulation model, gene expression measures from the San Antonio Family Heart Study (not distributed as part of the GAW18 data) were used to identify genes whose mRNA levels were correlated with blood pressure. Observed variants within these genes were designated as functional in the GAW18 simulation if they were nonsynonymous and predicted to have deleterious effects on protein function or if they were noncoding and associated with mRNA levels. Two simulated longitudinal phenotypes were modeled to have the same trait distributions as the real systolic and diastolic blood pressure data, with effects of age, sex, and medication use, including a genotype-medication interaction. For each phenotype, more than 1000 sequence variants in more than 200 genes present on the odd-numbered autosomes individually explained less than 0.01-2.78% of phenotypic variance. Cumulatively, variants in the most influential gene explained 7.79% of trait variance. An additional simulated phenotype, Q1, was designed to be correlated among family members but to not be associated with any sequence variants. Two hundred replicates of the phenotypes were simulated, with each including data for 849 individuals.

【 授权许可】

CC BY   
© Almasy et al.; licensee BioMed Central Ltd. 2014