John G. Gibbons

Bio: John G. Gibbons is an academic researcher from University of Massachusetts Amherst. The author has contributed to research in topics: Genome & Aspergillus fumigatus. The author has an hindex of 22, co-authored 40 publications receiving 4259 citations. Previous affiliations of John G. Gibbons include Harvard University & Clark University.

Genome-Wide Association Analysis Identifies Loci for Type 2 Diabetes and Triglyceride Levels

Abstract: New strategies for prevention and treatment of type 2 diabetes (T2D) require improved insight into disease etiology. We analyzed 386,731 common single-nucleotide polymorphisms (SNPs) in 1464 patients with T2D and 1467 matched controls, each characterized for measures of glucose metabolism, lipids, obesity, and blood pressure. With collaborators (FUSION and WTCCC/UKT2D), we identified and confirmed three loci associated with T2D-in a noncoding region near CDKN2A and CDKN2B, in an intron of IGF2BP2, and an intron of CDKAL1-and replicated associations near HHEX and in SLC30A8 found by a recent whole-genome association study. We identified and confirmed association of a SNP in an intron of glucokinase regulatory protein (GCKR) with serum triglycerides. The discovery of associated variants in unsuspected genes and outside coding regions illustrates the ability of genome-wide association studies to provide potentially important clues to the pathogenesis of common diseases.

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 October 2009–30 November 2009

Abstract: This article documents the addition of 411 microsatellite marker loci and 15 pairs of Single Nucleotide Polymorphism (SNP) sequencing primers to the Molecular Ecology Resources Database. Loci were developed for the following species: Acanthopagrus schlegeli, Anopheles lesteri, Aspergillus clavatus, Aspergillus flavus, Aspergillus fumigatus, Aspergillus oryzae, Aspergillus terreus, Branchiostoma japonicum, Branchiostoma belcheri, Colias behrii, Coryphopterus personatus, Cynogolssus semilaevis, Cynoglossus semilaevis, Dendrobium officinale, Dendrobium officinale, Dysoxylum malabaricum, Metrioptera roeselii, Myrmeciza exsul, Ochotona thibetana, Neosartorya fischeri, Nothofagus pumilio, Onychodactylus fischeri, Phoenicopterus roseus, Salvia officinalis L., Scylla paramamosain, Silene latifo, Sula sula, and Vulpes vulpes. These loci were cross-tested on the following species: Aspergillus giganteus, Colias pelidne, Colias interior, Colias meadii, Colias eurytheme, Coryphopterus lipernes, Coryphopterus glaucofrenum, Coryphopterus eidolon, Gnatholepis thompsoni, Elacatinus evelynae, Dendrobium loddigesii Dendrobium devonianum, Dysoxylum binectariferum, Nothofagus antarctica, Nothofagus dombeyii, Nothofagus nervosa, Nothofagus obliqua, Sula nebouxii, and Sula variegata. This article also documents the addition of 39 sequencing primer pairs and 15 allele specific primers or probes for Paralithodes camtschaticus.

Concerted copy number variation balances ribosomal DNA dosage in human and mouse genomes

Abstract: Tandemly repeated ribosomal DNA (rDNA) arrays are among the most evolutionary dynamic loci of eukaryotic genomes. The loci code for essential cellular components, yet exhibit extensive copy number (CN) variation within and between species. CN might be partly determined by the requirement of dosage balance between the 5S and 45S rDNA arrays. The arrays are nonhomologous, physically unlinked in mammals, and encode functionally interdependent RNA components of the ribosome. Here we show that the 5S and 45S rDNA arrays exhibit concerted CN variation (cCNV). Despite 5S and 45S rDNA elements residing on different chromosomes and lacking sequence similarity, cCNV between these loci is strong, evolutionarily conserved in humans and mice, and manifested across individual genotypes in natural populations and pedigrees. Finally, we observe that bisphenol A induces rapid and parallel modulation of 5S and 45S rDNA CN. Our observations reveal a novel mode of genome variation, indicate that natural selection contributed to the evolution and conservation of cCNV, and support the hypothesis that 5S CN is partly determined by the requirement of dosage balance with the 45S rDNA array. We suggest that human disease variation might be traced to disrupted rDNA dosage balance in the genome.

Benchmarking Next-Generation Transcriptome Sequencing for Functional and Evolutionary Genomics

Abstract: Next-generation sequencing has opened the door to genomic analysis of nonmodel organisms. Technologies generating long-sequence reads (200-400 bp) are increasingly used in evolutionary studies of nonmodel organisms, but the short-sequence reads (30-50 bp) that can be produced at lower cost are thought to be of limited utility for de novo sequencing applications. Here, we tested this assumption by short-read sequencing the transcriptomes of the tropical disease vectors Aedes aegypti and Anopheles gambiae, for which complete genome sequences are available. Comparison of our results to the reference genomes allowed us to accurately evaluate the quantity, quality, and functional and evolutionary information content of our "test" data. We produced more than 0.7 billion nucleotides of sequenced data per species that assembled into more than 21,000 test contigs larger than 100 bp per species and covered approximately 27% of the Aedes reference transcriptome. Remarkably, the substitution error rate in the test contigs was approximately 0.25% per site, with very few indels or assembly errors. Test contigs of both species were enriched for genes involved in energy production and protein synthesis and underrepresented in genes involved in transcription and differentiation. Ortholog prediction using the test contigs was accurate across hundreds of millions of years of evolution. Our results demonstrate the considerable utility of short-read transcriptome sequencing for genomic studies of nonmodel organisms and suggest an approach for assessing the information content of next-generation data for evolutionary studies.

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.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

Abstract: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

Biological, clinical and population relevance of 95 loci for blood lipids

Abstract: Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.