+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: not found

      The genomic basis of adaptive evolution in threespine sticklebacks

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          Marine stickleback fish have colonized and adapted to innumerable streams and lakes formed since the last ice age, providing an exceptional opportunity to characterize genomic mechanisms underlying repeated ecological adaptation in nature. Here we develop a high quality reference genome assembly for threespine sticklebacks. By sequencing the genomes of 20 additional individuals from a global set of marine and freshwater populations, we identify a genome-wide set of loci that are consistently associated with marine-freshwater divergence. Our results suggest that reuse of globally-shared standing genetic variation, including chromosomal inversions, plays an important role in repeated evolution of distinct marine and freshwater sticklebacks, and in the maintenance of divergent ecotypes during early stages of reproductive isolation. Both coding and regulatory changes occur in the set of loci underlying marine-freshwater evolution, with regulatory changes likely predominating in this classic example of repeated adaptive evolution in nature.

          Related collections

          Most cited references 56

          • Record: found
          • Abstract: found
          • Article: not found

          Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes.

          We have conducted a comprehensive search for conserved elements in vertebrate genomes, using genome-wide multiple alignments of five vertebrate species (human, mouse, rat, chicken, and Fugu rubripes). Parallel searches have been performed with multiple alignments of four insect species (three species of Drosophila and Anopheles gambiae), two species of Caenorhabditis, and seven species of Saccharomyces. Conserved elements were identified with a computer program called phastCons, which is based on a two-state phylogenetic hidden Markov model (phylo-HMM). PhastCons works by fitting a phylo-HMM to the data by maximum likelihood, subject to constraints designed to calibrate the model across species groups, and then predicting conserved elements based on this model. The predicted elements cover roughly 3%-8% of the human genome (depending on the details of the calibration procedure) and substantially higher fractions of the more compact Drosophila melanogaster (37%-53%), Caenorhabditis elegans (18%-37%), and Saccharaomyces cerevisiae (47%-68%) genomes. From yeasts to vertebrates, in order of increasing genome size and general biological complexity, increasing fractions of conserved bases are found to lie outside of the exons of known protein-coding genes. In all groups, the most highly conserved elements (HCEs), by log-odds score, are hundreds or thousands of bases long. These elements share certain properties with ultraconserved elements, but they tend to be longer and less perfectly conserved, and they overlap genes of somewhat different functional categories. In vertebrates, HCEs are associated with the 3' UTRs of regulatory genes, stable gene deserts, and megabase-sized regions rich in moderately conserved noncoding sequences. Noncoding HCEs also show strong statistical evidence of an enrichment for RNA secondary structure.
            • Record: found
            • Abstract: found
            • Article: not found

            Genome duplication in the teleost fish Tetraodon nigroviridis reveals the early vertebrate proto-karyotype.

            Tetraodon nigroviridis is a freshwater puffer fish with the smallest known vertebrate genome. Here, we report a draft genome sequence with long-range linkage and substantial anchoring to the 21 Tetraodon chromosomes. Genome analysis provides a greatly improved fish gene catalogue, including identifying key genes previously thought to be absent in fish. Comparison with other vertebrates and a urochordate indicates that fish proteins have diverged markedly faster than their mammalian homologues. Comparison with the human genome suggests approximately 900 previously unannotated human genes. Analysis of the Tetraodon and human genomes shows that whole-genome duplication occurred in the teleost fish lineage, subsequent to its divergence from mammals. The analysis also makes it possible to infer the basic structure of the ancestral bony vertebrate genome, which was composed of 12 chromosomes, and to reconstruct much of the evolutionary history of ancient and recent chromosome rearrangements leading to the modern human karyotype.
              • Record: found
              • Abstract: found
              • Article: not found

              Evo-devo and an expanding evolutionary synthesis: a genetic theory of morphological evolution.

              Biologists have long sought to understand which genes and what kinds of changes in their sequences are responsible for the evolution of morphological diversity. Here, I outline eight principles derived from molecular and evolutionary developmental biology and review recent studies of species divergence that have led to a genetic theory of morphological evolution, which states that (1) form evolves largely by altering the expression of functionally conserved proteins, and (2) such changes largely occur through mutations in the cis-regulatory sequences of pleiotropic developmental regulatory loci and of the target genes within the vast networks they control.

                Author and article information

                26 March 2012
                4 April 2012
                5 October 2012
                : 484
                : 7392
                : 55-61
                [1 ]Department of Developmental Biology, Beckman Center B300, Stanford University School of Medicine, Stanford CA 94305, USA
                [2 ]Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge MA 02142, USA
                [3 ]Science for Life Laboratory Uppsala, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala 751 23, Sweden
                [4 ]Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
                [5 ]European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
                [6 ]HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL 35806, USA
                [7 ]Department of Molecular Genetics, Benaroya Research Institute at Virginia Mason, 1201 Ninth Avenue, Seattle WA 98101, USA
                [8 ]Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
                Author notes

                Max Planck Institute for Evolutionary Biology, August-Thienemann-Str. 2, Plön 24306, Germany


                Bioinformatics Core, Zuckerman Research Center, New York, NY 10065


                Department of Molecular & Cell Biology, 142 LSA #3200, University of California, Berkeley, CA 94720, USA


                these authors contributed equally to this work


                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

                Funded by: National Human Genome Research Institute : NHGRI
                Award ID: P50 HG002568-09S1 || HG
                Funded by: National Human Genome Research Institute : NHGRI
                Award ID: P50 HG002568-09 || HG
                Funded by: Howard Hughes Medical Institute :
                Award ID: || HHMI_



                Comment on this article