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      Population Genomics of Parallel Adaptation in Threespine Stickleback using Sequenced RAD Tags

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          Abstract

          Next-generation sequencing technology provides novel opportunities for gathering genome-scale sequence data in natural populations, laying the empirical foundation for the evolving field of population genomics. Here we conducted a genome scan of nucleotide diversity and differentiation in natural populations of threespine stickleback ( Gasterosteus aculeatus). We used Illumina-sequenced RAD tags to identify and type over 45,000 single nucleotide polymorphisms (SNPs) in each of 100 individuals from two oceanic and three freshwater populations. Overall estimates of genetic diversity and differentiation among populations confirm the biogeographic hypothesis that large panmictic oceanic populations have repeatedly given rise to phenotypically divergent freshwater populations. Genomic regions exhibiting signatures of both balancing and divergent selection were remarkably consistent across multiple, independently derived populations, indicating that replicate parallel phenotypic evolution in stickleback may be occurring through extensive, parallel genetic evolution at a genome-wide scale. Some of these genomic regions co-localize with previously identified QTL for stickleback phenotypic variation identified using laboratory mapping crosses. In addition, we have identified several novel regions showing parallel differentiation across independent populations. Annotation of these regions revealed numerous genes that are candidates for stickleback phenotypic evolution and will form the basis of future genetic analyses in this and other organisms. This study represents the first high-density SNP–based genome scan of genetic diversity and differentiation for populations of threespine stickleback in the wild. These data illustrate the complementary nature of laboratory crosses and population genomic scans by confirming the adaptive significance of previously identified genomic regions, elucidating the particular evolutionary and demographic history of such regions in natural populations, and identifying new genomic regions and candidate genes of evolutionary significance.

          Author Summary

          Oceanic threespine stickleback have invaded and adapted to freshwater habitats countless times across the northern hemisphere. These freshwater populations have often evolved in similar ways from the ancestral marine stock from which they independently derived. With the exception of a few identified genes, the genetic basis of this remarkable parallel adaptation is unclear. Here we show that the parallel phenotypic evolution is matched by parallel patterns of nucleotide diversity and population differentiation across the genome. We used a novel high-throughput sequence-based genotyping approach to produce the first high density genome-wide scans of threespine stickleback populations and identified several genomic regions indicative of both divergent and balancing selection. Some of these regions have been associated previously with traits important for freshwater adaptation, but others were previously unidentified. Within these genomic regions we identified candidate genes, laying the foundation for further genetic and functional study of key pathways. This research illustrates the complementary nature of laboratory mapping, functional genetics, and population genomics.

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          Most cited references117

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          The impact of next-generation sequencing technology on genetics.

          If one accepts that the fundamental pursuit of genetics is to determine the genotypes that explain phenotypes, the meteoric increase of DNA sequence information applied toward that pursuit has nowhere to go but up. The recent introduction of instruments capable of producing millions of DNA sequence reads in a single run is rapidly changing the landscape of genetics, providing the ability to answer questions with heretofore unimaginable speed. These technologies will provide an inexpensive, genome-wide sequence readout as an endpoint to applications ranging from chromatin immunoprecipitation, mutation mapping and polymorphism discovery to noncoding RNA discovery. Here I survey next-generation sequencing technologies and consider how they can provide a more complete picture of how the genome shapes the organism.
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            Widespread parallel evolution in sticklebacks by repeated fixation of Ectodysplasin alleles.

            Major phenotypic changes evolve in parallel in nature by molecular mechanisms that are largely unknown. Here, we use positional cloning methods to identify the major chromosome locus controlling armor plate patterning in wild threespine sticklebacks. Mapping, sequencing, and transgenic studies show that the Ectodysplasin (EDA) signaling pathway plays a key role in evolutionary change in natural populations and that parallel evolution of stickleback low-plated phenotypes at most freshwater locations around the world has occurred by repeated selection of Eda alleles derived from an ancestral low-plated haplotype that first appeared more than two million years ago. Members of this clade of low-plated alleles are present at low frequencies in marine fish, which suggests that standing genetic variation can provide a molecular basis for rapid, parallel evolution of dramatic phenotypic change in nature.
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              Genomic scans for selective sweeps using SNP data.

              Detecting selective sweeps from genomic SNP data is complicated by the intricate ascertainment schemes used to discover SNPs, and by the confounding influence of the underlying complex demographics and varying mutation and recombination rates. Current methods for detecting selective sweeps have little or no robustness to the demographic assumptions and varying recombination rates, and provide no method for correcting for ascertainment biases. Here, we present several new tests aimed at detecting selective sweeps from genomic SNP data. Using extensive simulations, we show that a new parametric test, based on composite likelihood, has a high power to detect selective sweeps and is surprisingly robust to assumptions regarding recombination rates and demography (i.e., has low Type I error). Our new test also provides estimates of the location of the selective sweep(s) and the magnitude of the selection coefficient. To illustrate the method, we apply our approach to data from the Seattle SNP project and to Chromosome 2 data from the HapMap project. In Chromosome 2, the most extreme signal is found in the lactase gene, which previously has been shown to be undergoing positive selection. Evidence for selective sweeps is also found in many other regions, including genes known to be associated with disease risk such as DPP10 and COL4A3.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                February 2010
                February 2010
                26 February 2010
                : 6
                : 2
                : e1000862
                Affiliations
                [1 ]Center for Ecology and Evolutionary Biology, University of Oregon, Eugene, Oregon, United States of America
                [2 ]Institute of Molecular Biology, University of Oregon, Eugene, Oregon, United States of America
                [3 ]Genomics Core Facility, University of Oregon, Eugene, Oregon, United States of America
                University of California Davis, United States of America
                Author notes

                Conceived and designed the experiments: PAH SB EAJ WAC. Performed the experiments: PAH SB PDE. Analyzed the data: PAH SB NS WAC. Contributed reagents/materials/analysis tools: PAH SB PDE EAJ WAC. Wrote the paper: PAH SB WAC.

                Article
                09-PLGE-RA-1835R3
                10.1371/journal.pgen.1000862
                2829049
                20195501
                2f6ea3c0-45cc-42cb-a28b-a542bca74cb4
                Hohenlohe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 20 October 2009
                : 28 January 2010
                Page count
                Pages: 23
                Categories
                Research Article
                Computational Biology/Genomics
                Ecology/Marine and Freshwater Ecology
                Evolutionary Biology/Developmental Evolution
                Evolutionary Biology/Genomics

                Genetics
                Genetics

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