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.

A functional IL-6 receptor (IL6R) variant is a risk factor for persistent atopic dermatitis

Abstract: Background Atopic dermatitis (AD) is a common inflammatory skin disease. Previous studies have revealed shared genetic determinants among different inflammatory disorders, suggesting that markers associated with immune-related traits might also play a role in AD. Objective We sought to identify novel genetic risk factors for AD. Methods We examined the results of all genome-wide association studies from a public repository and selected 318 genetic markers that were significantly associated with any inflammatory trait. These markers were considered candidates and tested for association with AD in a 3-step approach including 7 study populations with 7130 patients with AD and 9253 control subjects. Results A functional amino acid change in the IL-6 receptor (IL-6R Asp358Ala; rs2228145) was significantly associated with AD (odds ratio [OR], 1.15; P = 5 × 10 −9 ). Interestingly, investigation of 2 independent population-based birth cohorts showed that IL-6R 358Ala specifically predisposes to the persistent form of AD (OR persistent AD = 1.22, P = .0008; OR transient AD = 1.04, P = .54). This variant determines the balance between the classical membrane-bound versus soluble IL-6R signaling pathways. Carriers of 358Ala had increased serum levels of soluble IL-6R ( P = 4 × 10 −14 ), with homozygote carriers showing a 2-fold increase. Moreover, we demonstrate that soluble IL-6R levels were higher in patients with AD than in control subjects (46.0 vs 37.8 ng/mL, P = .001). Additional AD risk variants were identified in RAD50 , RUNX3 , and ERBB3 . Conclusion Our study supports the importance of genetic variants influencing inflammation in the etiology of AD. Moreover, we identified a functional genetic variant in IL6R influencing disease prognosis and specifically predisposing to persistent AD.

Association between quantitative traits underlying asthma and the HLA-DRB1 locus in a family-based population sample.

Abstract: The region of human chromosome 6 containing the MHC has been identified as influencing asthma and atopy (allergy) by several genome-wide searches. The MHC contains many genes with potential effects on innate and specific immunity. As a first step in dissecting MHC influences on asthma and its underlying quantitative phenotypes, we have examined the HLA-DRB1 locus in a population sample consisting of 1004 individuals from 230 families from the rural Australian town of Busselton. The locus was strongly associated with the (loge) total serum IgE concentration, accounting for 4.0% of the σ2 (variance) in that trait (multi-allelic test, P=0.00001). The locus also influenced specific IgE titres to common allergens (multi-allelic tests, 2.8% σ2 for the house dust mite allergen Der p I, P=0.0013; 3.0% of σ2 for Der p II, P=0.0007; and 2.1% of σ2 for the cat allergen Fel d I, P=0.014). No associations were found to the categorical phenotype of asthma, or to the quantitative traits of peripheral blood eosinophil counts and bronchial hyper-responsiveness. Transmission disequilibrium tests excluded genetic admixture as a cause of false-positive findings. The results indicate that HLA-DRB1 alleles modulate the total serum IgE concentration and IgE responses to allergens, but do not account for the previous observations of linkage of asthma to the MHC.

Single nucleotide polymorphism and linkage disequilibrium within the TCR α/δ locus

Abstract: Much attention is being given to the identification of common disease genes through whole-genome linkage disequilibrium (LD) screens with single nucleotide polymorphisms (SNPs). Simulation studies have suggested that useful LD is unlikely to extend beyond 3 kb, and that > 500,000 SNPs may be needed for comprehensive coverage of the genome. The TCR alpha/delta locus on chromosome 14q contains many V, J and D segments that combine with constant domains to produce either an alpha or a delta chain of the T cell receptor. Multiple SNPs have been recognized within the V segments, and it has been suggested that variation within the locus may modify the course of autoimmune and allergic diseases. We have examined LD within an 850 kb section of the TCR alpha/delta locus on chromosome 14q by typing 24 V gene segment SNPs and two microsatellites. One hundred and fifty-nine nuclear and extended families were genotyped in order to derive haplotypes, and the pair-wise LD between SNPs was investigated in 600 haplotypes from unrelated individuals (the parents). The mean extent of useful LD was much greater than suggested by simulations: significant LD was relatively common at 250 kb and was detectable beyond 500 kb. The mean extent of LD was twice as far between alleles of low frequency than between common alleles. The distribution of LD was highly irregular and concentrated in three distinct islands. The results differ from those obtained by simulation, and if they are typical of other genomic regions, suggest that the minimum number of markers necessary for comprehensive LD mapping may be reduced by at least an order of magnitude.

Nogo Receptor 1 (RTN4R) as a candidate gene for schizophrenia: analysis using human and mouse genetic approaches.

Abstract: Background NOGO Receptor 1 (RTN4R) regulates axonal growth, as well as axon regeneration after injury. The gene maps to the 22q11.2 schizophrenia susceptibility locus and is thus a strong functional and positional candidate gene.

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

Abstract: 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.

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.