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      Comparative genomics of Steinernema reveals deeply conserved gene regulatory networks.

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          Abstract

          Parasitism is a major ecological niche for a variety of nematodes. Multiple nematode lineages have specialized as pathogens, including deadly parasites of insects that are used in biological control. We have sequenced and analyzed the draft genomes and transcriptomes of the entomopathogenic nematode Steinernema carpocapsae and four congeners (S. scapterisci, S. monticolum, S. feltiae, and S. glaseri).

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          Evolution of genes and genomes on the Drosophila phylogeny.

          Andrew G Clark, Michael B Eisen, Douglas R Smith … (2007)
          Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.
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            Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project.

            Mark Gerstein, Zhi John Lu, Eric Van Nostrand … (2010)
            We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.
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              Inconsistency of phylogenetic estimates from concatenated data under coalescence.

              Laura Kubatko, James H. Degnan (2007)
              Although multiple gene sequences are becoming increasingly available for molecular phylogenetic inference, the analysis of such data has largely relied on inference methods designed for single genes. One of the common approaches to analyzing data from multiple genes is concatenation of the individual gene data to form a single supergene to which traditional phylogenetic inference procedures - e.g., maximum parsimony (MP) or maximum likelihood (ML) - are applied. Recent empirical studies have demonstrated that concatenation of sequences from multiple genes prior to phylogenetic analysis often results in inference of a single, well-supported phylogeny. Theoretical work, however, has shown that the coalescent can produce substantial variation in single-gene histories. Using simulation, we combine these ideas to examine the performance of the concatenation approach under conditions in which the coalescent produces a high level of discord among individual gene trees and show that it leads to statistically inconsistent estimation in this setting. Furthermore, use of the bootstrap to measure support for the inferred phylogeny can result in moderate to strong support for an incorrect tree under these conditions. These results highlight the importance of incorporating variation in gene histories into multilocus phylogenetics.
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                Author and article information

                Journal
                Journal ID (iso-abbrev): Genome Biol.
                Title: Genome biology
                Publisher: Springer Science and Business Media LLC
                ISSN (Electronic): 1474-760X
                ISSN (Print): 1474-7596
                Publication date (Electronic): Sep 21 2015
                Volume: 16
                Affiliations
                [1 ] Department of Nematology, University of California, Riverside, CA, 92521, USA. adler.dillman@ucr.edu.
                [2 ] Department of Developmental and Cell Biology, University of California, Irvine, CA, 92697, USA. mmacchie@uci.edu.
                [3 ] Department of Biology and Evolutionary Ecology Laboratories, Brigham Young University, Provo, UT, 84602, USA. finli6@gmail.com.
                [4 ] Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA. arogers@caltech.edu.
                [5 ] Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA. bawilli@caltech.edu.
                [6 ] Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA. igor.antoshechkin@caltech.edu.
                [7 ] Department of Entomology, University of Arizona, Tucson, AZ, 85721, USA. mingmail@email.arizona.edu.
                [8 ] Division of Biology and Biomedical Sciences, Washington University, St Louis, MO, 63110, USA. gzane01@gmail.com.
                [9 ] Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, 53706, USA. Luxiaojun@tsinghua.edu.cn.
                [10 ] Department of Entomology and Nematology, University of California, Davis, CA, 95616, USA. eelewis@ucdavis.edu.
                [11 ] Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, 53706, USA. hgblair@bact.wisc.edu.
                [12 ] Department of Entomology, University of Arizona, Tucson, AZ, 85721, USA. spstock@email.arizona.edu.
                [13 ] Department of Biology and Evolutionary Ecology Laboratories, Brigham Young University, Provo, UT, 84602, USA. byron_adams@byu.edu.
                [14 ] Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA. pws@caltech.edu.
                [15 ] Howard Hughes Medical Institute, Pasadena, CA, 91125, USA. pws@caltech.edu.
                [16 ] Department of Developmental and Cell Biology, University of California, Irvine, CA, 92697, USA. ali.mortazavi@uci.edu.
                Article
                Publisher Item ID: 10.1186/s13059-015-0746-6
                DOI: 10.1186/s13059-015-0746-6
                PMC ID: 4578762
                PubMed ID: 26392177
                SO-VID: 6919c4f0-a87a-4abf-8701-37aed0fc0de9
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