@article {1387, title = {Evolution and functional impact of rare coding variation from deep sequencing of human exomes.}, journal = {Science}, volume = {337}, year = {2012}, month = {2012 Jul 06}, pages = {64-9}, abstract = {

As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111{\texttimes} in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86\% with a minor allele frequency less than 0.5\%), previously unknown (82\%), and population-specific (82\%). On average, 2.3\% of the 13,595 SNVs each person carried were predicted to affect protein function of ~313 genes per genome, and ~95.7\% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.

}, keywords = {African Americans, Disease, European Continental Ancestry Group, Evolution, Molecular, Exome, Female, Gene Frequency, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, High-Throughput Nucleotide Sequencing, Humans, Male, Polymorphism, Single Nucleotide, Population Growth, Selection, Genetic}, issn = {1095-9203}, doi = {10.1126/science.1219240}, author = {Tennessen, Jacob A and Bigham, Abigail W and O{\textquoteright}Connor, Timothy D and Fu, Wenqing and Kenny, Eimear E and Gravel, Simon and McGee, Sean and Do, Ron and Liu, Xiaoming and Jun, Goo and Kang, Hyun Min and Jordan, Daniel and Leal, Suzanne M and Gabriel, Stacey and Rieder, Mark J and Abecasis, Goncalo and Altshuler, David and Nickerson, Deborah A and Boerwinkle, Eric and Sunyaev, Shamil and Bustamante, Carlos D and Bamshad, Michael J and Akey, Joshua M} } @article {6283, title = {Whole-genome sequence-based analysis of high-density lipoprotein cholesterol.}, journal = {Nat Genet}, volume = {45}, year = {2013}, month = {2013 Aug}, pages = {899-901}, abstract = {

We describe initial steps for interrogating whole-genome sequence data to characterize the genetic architecture of a complex trait, levels of high-density lipoprotein cholesterol (HDL-C). We report whole-genome sequencing and analysis of 962 individuals from the Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) studies. From this analysis, we estimate that common variation contributes more to heritability of HDL-C levels than rare variation, and screening for mendelian variants for dyslipidemia identified individuals with extreme HDL-C levels. Whole-genome sequencing analyses highlight the value of regulatory and non-protein-coding regions of the genome in addition to protein-coding regions.

}, keywords = {Cholesterol, HDL, Computational Biology, Databases, Genetic, Genetic Variation, Genome, Human, Genome-Wide Association Study, Genomics, Heterozygote, Humans, Open Reading Frames}, issn = {1546-1718}, doi = {10.1038/ng.2671}, author = {Morrison, Alanna C and Voorman, Arend and Johnson, Andrew D and Liu, Xiaoming and Yu, Jin and Li, Alexander and Muzny, Donna and Yu, Fuli and Rice, Kenneth and Zhu, Chengsong and Bis, Joshua and Heiss, Gerardo and O{\textquoteright}Donnell, Christopher J and Psaty, Bruce M and Cupples, L Adrienne and Gibbs, Richard and Boerwinkle, Eric} } @article {6547, title = {Sequencing of 2 subclinical atherosclerosis candidate regions in 3669 individuals: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {359-64}, abstract = {

BACKGROUND: Atherosclerosis, the precursor to coronary heart disease and stroke, is characterized by an accumulation of fatty cells in the arterial intimal-medial layers. Common carotid intima media thickness (cIMT) and plaque are subclinical atherosclerosis measures that predict cardiovascular disease events. Previously, genome-wide association studies demonstrated evidence for association with cIMT (SLC17A4) and plaque (PIK3CG).

METHODS AND RESULTS: We sequenced 120 kb around SLC17A4 (6p22.2) and 251 kb around PIK3CG (7q22.3) among 3669 European ancestry participants from the Atherosclerosis Risk in Communities (ARIC) study, Cardiovascular Health Study (CHS), and Framingham Heart Study (FHS) in Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Primary analyses focused on 438 common variants (minor allele frequency >=1\%), which were independently meta-analyzed. A 3{\textquoteright} untranslated region CCDC71L variant (rs2286149), upstream from PIK3CG, was the most significant finding in cIMT (P=0.00033) and plaque (P=0.0004) analyses. A SLC17A4 intronic variant was also associated with cIMT (P=0.008). Both were in low linkage disequilibrium with the genome-wide association study single nucleotide polymorphisms. Gene-based tests including T1 count and sequence kernel association test for rare variants (minor allele frequency <1\%) did not yield statistically significant associations. However, we observed nominal associations for rare variants in CCDC71L and SLC17A3 with cIMT and of the entire 7q22 region with plaque (P=0.05).

CONCLUSIONS: Common and rare variants in PIK3CG and SLC17A4 regions demonstrated modest association with subclinical atherosclerosis traits. Although not conclusive, these findings may help to understand the genetic architecture of regions previously implicated by genome-wide association studies and identify variants within these regions for further investigation in larger samples.

}, keywords = {Aged, Aged, 80 and over, Aging, Atherosclerosis, Class Ib Phosphatidylinositol 3-Kinase, Cohort Studies, European Continental Ancestry Group, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Sodium-Phosphate Cotransporter Proteins, Type I}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000116}, author = {Bis, Joshua C and White, Charles C and Franceschini, Nora and Brody, Jennifer and Zhang, Xiaoling and Muzny, Donna and Santibanez, Jireh and Gibbs, Richard and Liu, Xiaoming and Lin, Honghuang and Boerwinkle, Eric and Psaty, Bruce M and North, Kari E and Cupples, L Adrienne and O{\textquoteright}Donnell, Christopher J} } @article {6578, title = {Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {335-43}, abstract = {

BACKGROUND: Genome-wide association studies have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study aims to follow up genome-wide association study signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular-related traits.

METHODS AND RESULTS: The study included 4231 participants from 3 CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with >=1 of 14 phenotypes. A total of 52 736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency >=1\%), we performed unweighted regression analyses to obtain P values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied 2 approaches: collapsed aggregate statistics and joint analysis of variants using the sequence kernel association test.

CONCLUSIONS: We sequenced 77 genomic loci in participants from 3 cohorts. We established a set of filters to identify high-quality variants and implemented statistical and bioinformatics strategies to analyze the sequence data and identify potentially functional variants within genome-wide association study loci.

}, keywords = {Adult, Aged, Aged, 80 and over, Aging, Cohort Studies, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Research Design, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000350}, author = {Lin, Honghuang and Wang, Min and Brody, Jennifer A and Bis, Joshua C and Dupuis, Jos{\'e}e and Lumley, Thomas and McKnight, Barbara and Rice, Kenneth M and Sitlani, Colleen M and Reid, Jeffrey G and Bressler, Jan and Liu, Xiaoming and Davis, Brian C and Johnson, Andrew D and O{\textquoteright}Donnell, Christopher J and Kovar, Christie L and Dinh, Huyen and Wu, Yuanqing and Newsham, Irene and Chen, Han and Broka, Andi and DeStefano, Anita L and Gupta, Mayetri and Lunetta, Kathryn L and Liu, Ching-Ti and White, Charles C and Xing, Chuanhua and Zhou, Yanhua and Benjamin, Emelia J and Schnabel, Renate B and Heckbert, Susan R and Psaty, Bruce M and Muzny, Donna M and Cupples, L Adrienne and Morrison, Alanna C and Boerwinkle, Eric} }