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      The genomic substrate for adaptive radiation in African cichlid fish

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          Cichlid fishes are famous for large, diverse and replicated adaptive radiations in the Great Lakes of East Africa. To understand the molecular mechanisms underlying cichlid phenotypic diversity, we sequenced the genomes and transcriptomes of five lineages of African cichlids: the Nile tilapia ( Oreochromis niloticus), an ancestral lineage with low diversity; and four members of the East African lineage: Neolamprologus brichardi/pulcher (older radiation, Lake Tanganyika), Metriaclima zebra (recent radiation, Lake Malawi), Pundamilia nyererei (very recent radiation, Lake Victoria), and Astatotilapia burtoni (riverine species around Lake Tanganyika). We found an excess of gene duplications in the East African lineage compared to tilapia and other teleosts, an abundance of non-coding element divergence, accelerated coding sequence evolution, expression divergence associated with transposable element insertions, and regulation by novel microRNAs. In addition, we analysed sequence data from sixty individuals representing six closely related species from Lake Victoria, and show genome-wide diversifying selection on coding and regulatory variants, some of which were recruited from ancient polymorphisms. We conclude that a number of molecular mechanisms shaped East African cichlid genomes, and that amassing of standing variation during periods of relaxed purifying selection may have been important in facilitating subsequent evolutionary diversification.

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          Most cited references 46

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          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.
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            The evolutionary fate and consequences of duplicate genes.

            Gene duplication has generally been viewed as a necessary source of material for the origin of evolutionary novelties, but it is unclear how often gene duplicates arise and how frequently they evolve new functions. Observations from the genomic databases for several eukaryotic species suggest that duplicate genes arise at a very high rate, on average 0.01 per gene per million years. Most duplicated genes experience a brief period of relaxed selection early in their history, with a moderate fraction of them evolving in an effectively neutral manner during this period. However, the vast majority of gene duplicates are silenced within a few million years, with the few survivors subsequently experiencing strong purifying selection. Although duplicate genes may only rarely evolve new functions, the stochastic silencing of such genes may play a significant role in the passive origin of new species.
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              The genomic basis of adaptive evolution in threespine sticklebacks

              Summary 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.

                Author and article information

                26 February 2015
                03 September 2014
                18 September 2014
                18 March 2015
                : 513
                : 7518
                : 375-381
                [1 ]Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
                [2 ]MRC Functional Genomics Unit, University of Oxford, Oxford OX1 3QX, UK.
                [3 ]Department of Fish Ecology and Evolution, Eawag Swiss Federal Institute of Aquatic Science and Technology, Center for Ecology, Evolution & Biogeochemistry, CH-6047 Kastanienbaum, Switzerland.
                [4 ]Division of Aquatic Ecology, Institute of Ecology & Evolution, University of Bern, CH-3012 Bern, Switzerland.
                [5 ]Gurdon Institute, Cambridge CB2 1QN, UK.
                [6 ]Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK.
                [7 ]Department of Biology, University of Konstanz, D-78457 Konstanz, Germany.
                [8 ]European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
                [9 ]Institute of Molecular and Cell Biology, A*STAR, 138673 Singapore.
                [10 ]Department of Biology, Reed College, Portland, Oregon 97202, USA.
                [11 ]Biology Department, Stanford University, Stanford, California 94305-5020, USA.
                [12 ]Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, USA.
                [13 ]Benaroya Research Institute at Virginia Mason, Seattle, Washington 98101, USA.
                [14 ]Institut Génétique et Développement, CNRS/University of Rennes, 35043 Rennes, France.
                [15 ]CIRAD, Campus International de Baillarguet, TA B-110/A, 34398 Montpellier cedex 5, France.
                [16 ]School of Biology, Georgia Institute of Technology, Atlanta, Georgia 30332-0230, USA.
                [17 ]Department of Biology, University of Maryland, College Park, Maryland 20742, USA.
                [18 ]Animal Genetics, Institute of Animal Science, ARO, The Volcani Center, Bet-Dagan, 50250 Israel.
                [19 ]Zoological Institute, University of Basel, CH-4051 Basel, Switzerland.
                [20 ]Department of Integrative Biology, Center for Computational Biology and Bioinformatics; The University of Texas at Austin, Austin, Texas 78712, USA.
                [21 ]Department of Biological Sciences, Tokyo Institute of Technology, Tokyo, 226-8501 Yokohama, Japan.
                [22 ]Systématique, Adaptation, Evolution, National Museum of Natural History, 75005 Paris, France.
                [23 ]Institute of Aquaculture, University of Stirling, Stirling FK9 4LA, UK.
                [24 ]Carnegie Institution of Washington, Department of Embryology, 3520 San Martin Drive Baltimore, Maryland 21218, USA.
                [25 ]National Cheng Kung University, Tainan City, 704 Taiwan.
                [26 ]Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 751 23 Uppsala, Sweden.
                [27 ]Vertebrate and Health Genomics, The Genome Analysis Centre, Norwich NR18 7UH, UK.
                Author notes
                Correspondence and requests for materials should be addressed to F.D.P. ( Federica.di-palma@ ), K.L.-T. ( Kersli@ ), J.T.S. ( todd.streelman@ ), and O.S. ( ole.seehausen@ ).
                ©2014 Macmillan Publishers Limited. All rights reserved

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