Gonçalo R. Abecasis

Bio: Gonçalo R. Abecasis is an academic researcher from University of Michigan. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 179, co-authored 595 publications receiving 230323 citations. Previous affiliations of Gonçalo R. Abecasis include Johns Hopkins University School of Medicine & Wellcome Trust Centre for Human Genetics.

Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits

Abstract: Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.

Genome-wide association study of plasma polyunsaturated fatty acids in the InCHIANTI Study.

Abstract: Polyunsaturated fatty acids (PUFA) have a role in many physiological processes, including energy production, modulation of inflammation, and maintenance of cell membrane integrity. High plasma PUFA concentrations have been shown to have beneficial effects on cardiovascular disease and mortality. To identify genetic contributors of plasma PUFA concentrations, we conducted a genome-wide association study of plasma levels of six omega-3 and omega-6 fatty acids in 1,075 participants in the InCHIANTI study on aging. The strongest evidence for association was observed in a region of chromosome 11 that encodes three fatty acid desaturases (FADS1, FADS2, FADS3). The SNP with the most significant association was rs174537 near FADS1 in the analysis of arachidonic acid (AA; p=5.95610 246 ). Minor allele homozygotes had lower AA compared to the major allele homozygotes and rs174537 accounted for 18.6% of the additive variance in AA concentrations. This SNP was also associated with levels of eicosadienoic acid (EDA; p=6.78610 29 ) and eicosapentanoic acid (EPA; p=1.07610 214 ). Participants carrying the allele associated with higher AA, EDA, and EPA also had higher lowdensity lipoprotein (LDL-C) and total cholesterol levels. Outside the FADS gene cluster, the strongest region of association mapped to chromosome 6 in the region encoding an elongase of very long fatty acids 2 (ELOVL2). In this region, association was observed with EPA (rs953413; p=1.1610 26 ). The effects of rs174537 were confirmed in an independent sample of 1,076 subjects participating in the GOLDN study. The ELOVL2 SNP was associated with docosapentanoic and DHA but not with EPA in GOLDN. These findings show that polymorphisms of genes encoding enzymes in the metabolism of PUFA contribute to plasma concentrations of fatty acids.

Common variants in the GDF5-UQCC region are associated with variation in human height

Abstract: Identifying genetic variants that influence human height will advance our understanding of skeletal growth and development. Several rare genetic variants have been convincingly and reproducibly associated with height in mendelian syndromes, and common variants in the transcription factor gene HMGA2 are associated with variation in height in the general population. Here we report genome-wide association analyses, using genotyped and imputed markers, of 6,669 individuals from Finland and Sardinia, and follow-up analyses in an additional 28,801 individuals. We show that common variants in the osteoarthritis-associated locus GDF5-UQCC contribute to variation in height with an estimated additive effect of 0.44 cm (overall P < 10(-15)). Our results indicate that there may be a link between the genetic basis of height and osteoarthritis, potentially mediated through alterations in bone growth and development.

Strong Association of the Y402H Variant in Complement Factor H at 1q32 with Susceptibility to Age-Related Macular Degeneration

Abstract: Using a large sample of cases and controls from a single center, we show that a T→C substitution in exon 9 (Y402H) of the complement factor H gene is strongly associated with susceptibility to age-related macular degeneration, the most common cause of blindness in the elderly. Frequency of the C allele was 0.61 in cases, versus 0.34 in age-matched controls ( P −24 ). Genotype frequencies also differ markedly between cases and controls (χ 2 =112.68 [2 degrees of freedom]; P −24 ). A multiplicative model fits the data well, and we estimate the population frequency of the high-risk C allele to be 0.39 (95% confidence interval 0.36–0.42) and the genotype relative risk to be 2.44 (95% confidence interval 2.08–2.83) for TC heterozygotes and 5.93 (95% confidence interval 4.33–8.02) for CC homozygotes.

Gene polymorphism in Netherton and common atopic disease.

Abstract: Atopic dermatitis (AD) and asthma are characterized by IgE-mediated atopic (allergic) responses to common proteins (allergens), many of which are proteinases. Loci influencing atopy have been localized to a number of chromosomal regions1, including the chromosome 5q31 cytokine cluster2,3,4. Netherton disease is a rare recessive skin disorder in which atopy is a universal accompaniment5. The gene underlying Netherton disease (SPINK5)6 encodes a 15-domain serine proteinase inhibitor (LEKTI) which is expressed in epithelial and mucosal surfaces and in the thymus6,7. We have identified six coding polymorphisms in SPINK5 (Table 1) and found that a Glu420→Lys variant shows significant association with atopy and AD in two independent panels of families. Our results implicate a previously unrecognized pathway for the development of common allergic illnesses.

Fast and accurate short read alignment with Burrows–Wheeler transform

Abstract: Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ~10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: [email protected]

Fast gapped-read alignment with Bowtie 2

Abstract: As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

Abstract: Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

Initial sequencing and analysis of the human genome.

Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

Abstract: Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.