Gavin C. Conant

Bio: Gavin C. Conant is an academic researcher from North Carolina State University. The author has contributed to research in topics: Genome & Gene duplication. The author has an hindex of 30, co-authored 95 publications receiving 6453 citations. Previous affiliations of Gavin C. Conant include University College Dublin & University of New Mexico.

The genome of the mesopolyploid crop species Brassica rapa

Abstract: We report the annotation and analysis of the draft genome sequence of Brassica rapa accession Chiifu-401-42, a Chinese cabbage. We modeled 41,174 protein coding genes in the B. rapa genome, which has undergone genome triplication. We used Arabidopsis thaliana as an outgroup for investigating the consequences of genome triplication, such as structural and functional evolution. The extent of gene loss (fractionation) among triplicated genome segments varies, with one of the three copies consistently retaining a disproportionately large fraction of the genes expected to have been present in its ancestor. Variation in the number of members of gene families present in the genome may contribute to the remarkable morphological plasticity of Brassica species. The B. rapa genome sequence provides an important resource for studying the evolution of polyploid genomes and underpins the genetic improvement of Brassica oil and vegetable crops.

Turning a hobby into a job: how duplicated genes find new functions.

Abstract: Gene duplication provides raw material for functional innovation. Recent advances have shed light on two fundamental questions regarding gene duplication: which genes tend to undergo duplication? And how does natural selection subsequently act on them? Genomic data suggest that different gene classes tend to be retained after single-gene and whole-genome duplications. We also know that functional differences between duplicate genes can originate in several different ways, including mutations that directly impart new functions, subdivision of ancestral functions and selection for changes in gene dosage. Interestingly, in many cases the 'new' function of one copy is a secondary property that was always present, but that has been co-opted to a primary role after the duplication.

The butterfly plant arms-race escalated by gene and genome duplications.

Abstract: Coevolutionary interactions are thought to have spurred the evolution of key innovations and driven the diversification of much of life on Earth. However, the genetic and evolutionary basis of the innovations that facilitate such interactions remains poorly understood. We examined the coevolutionary interactions between plants (Brassicales) and butterflies (Pieridae), and uncovered evidence for an escalating evolutionary arms-race. Although gradual changes in trait complexity appear to have been facilitated by allelic turnover, key innovations are associated with gene and genome duplications. Furthermore, we show that the origins of both chemical defenses and of molecular counter adaptations were associated with shifts in diversification rates during the arms-race. These findings provide an important connection between the origins of biodiversity, coevolution, and the role of gene and genome duplications as a substrate for novel traits.

GenomeVx: simple web-based creation of editable circular chromosome maps

Abstract: We describe GenomeVx, a web-based tool for making editable, publication-quality, maps of mitochondrial and chloroplast genomes and of large plasmids. These maps show the location of genes and chromosomal features as well as a position scale. The program takes as input either raw feature positions or GenBank records. In the latter case, features are automatically extracted and colored, an example of which is given. Output is in the Adobe Portable Document Format (PDF) and can be edited by programs such as Adobe Illustrator. Availability: GenomeVx is available at http://wolfe.gen.tcd.ie/ GenomeVx

Asymmetric Sequence Divergence of Duplicate Genes

Abstract: Much like humans, gene duplicates may be created equal, but they do not stay that way for long. For four completely sequenced genomes we show that 20%-30% of duplicate gene pairs show asymmetric evolution in the amino acid sequence of their protein products. That is, one of the duplicates evolves much faster than the other. The greater this asymmetry, the greater the ratio Ka/Ks of amino acid substitutions (Ka) to silent substitutions (Ks) in a gene pair. This indicates that most asymmetric divergence may be caused by relaxed selective constraints on one of the duplicates. However, we also find some candidate duplicates where positive (directional) selection of beneficial mutations (Ka/Ks > 1) may play a role in asymmetric divergence. Our analysis rests on a codon-based model of molecular evolution that allows a test for asymmetric divergence in Ka. The method is also more sensitive in detecting positive selection (Ka/Ks > 1) than models relying only on pairwise gene comparisons.

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.

Network biology: understanding the cell's functional organization

Abstract: A key aim of postgenomic biomedical research is to systematically catalogue all molecules and their interactions within a living cell. There is a clear need to understand how these molecules and the interactions between them determine the function of this enormously complex machinery, both in isolation and when surrounded by other cells. Rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize our view of biology and disease pathologies in the twenty-first century.

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STRING v9.1: protein-protein interaction networks, with increased coverage and integration

Abstract: Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.