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      Selection at a genomic region of major effect is responsible for evolution of complex life histories in anadromous steelhead

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          Abstract

          Background

          Disparity in the timing of biological events occurs across a variety of systems, yet the understanding of genetic basis underlying diverse phenologies remains limited. Variation in maturation timing occurs in steelhead trout, which has been associated with greb1L, an oestrogen target gene. Previous techniques that identified this gene only accounted for about 0.5–2.0% of the genome and solely investigated coastal populations, leaving uncertainty on the genetic basis of this trait and its prevalence across a larger geographic scale.

          Results

          We used a three-tiered approach to interrogate the genomic basis of complex phenology in anadromous steelhead. First, fine scale mapping with 5.3 million SNPs from resequencing data covering 68% of the genome confirmed a 309-kb region consisting of four genes on chromosome 28, including greb1L, to be the genomic region of major effect for maturation timing. Second, broad-scale characterization of candidate greb1L genotypes across 59 populations revealed unexpected patterns in maturation phenology for inland fish migrating long distances relative to those in coastal streams. Finally, genotypes from 890 PIT-tag tracked steelhead determined associations with early versus late arrival to spawning grounds that were previously unknown.

          Conclusions

          This study clarifies the genetic bases for disparity in phenology observed in steelhead, determining an unanticipated trait association with premature versus mature arrival to spawning grounds and identifying multiple candidate genes potentially contributing to this variation from a single genomic region of major effect. This illustrates how dense genome mapping and detailed phenotypic characterization can clarify genotype to phenotype associations across geographic ranges of species.

          Electronic supplementary material

          The online version of this article (10.1186/s12862-018-1255-5) contains supplementary material, which is available to authorized users.

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          Most cited references35

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          Impact of climate change on marine pelagic phenology and trophic mismatch.

          Phenology, the study of annually recurring life cycle events such as the timing of migrations and flowering, can provide particularly sensitive indicators of climate change. Changes in phenology may be important to ecosystem function because the level of response to climate change may vary across functional groups and multiple trophic levels. The decoupling of phenological relationships will have important ramifications for trophic interactions, altering food-web structures and leading to eventual ecosystem-level changes. Temperate marine environments may be particularly vulnerable to these changes because the recruitment success of higher trophic levels is highly dependent on synchronization with pulsed planktonic production. Using long-term data of 66 plankton taxa during the period from 1958 to 2002, we investigated whether climate warming signals are emergent across all trophic levels and functional groups within an ecological community. Here we show that not only is the marine pelagic community responding to climate changes, but also that the level of response differs throughout the community and the seasonal cycle, leading to a mismatch between trophic levels and functional groups.
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            A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data

            (2013)
            Motivation: Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. Results: We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. Availability: http://samtools.sourceforge.net. Contact: hengli@broadinstitute.org.
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              SAMBLASTER: fast duplicate marking and structural variant read extraction

              Motivation: Illumina DNA sequencing is now the predominant source of raw genomic data, and data volumes are growing rapidly. Bioinformatic analysis pipelines are having trouble keeping pace. A common bottleneck in such pipelines is the requirement to read, write, sort and compress large BAM files multiple times. Results: We present SAMBLASTER, a tool that reduces the number of times such costly operations are performed. SAMBLASTER is designed to mark duplicates in read-sorted SAM files as a piped post-pass on DNA aligner output before it is compressed to BAM. In addition, it can simultaneously output into separate files the discordant read-pairs and/or split-read mappings used for structural variant calling. As an alignment post-pass, its own runtime overhead is negligible, while dramatically reducing overall pipeline complexity and runtime. As a stand-alone duplicate marking tool, it performs significantly better than PICARD or SAMBAMBA in terms of both speed and memory usage, while achieving nearly identical results. Availability and implementation: SAMBLASTER is open-source C++ code and freely available for download from https://github.com/GregoryFaust/samblaster. Contact: imh4y@virginia.edu
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                Author and article information

                Contributors
                mics@critfc.org
                hesj@critfc.org
                jzendt@ykfp.org
                nars@critfc.org
                Journal
                BMC Evol Biol
                BMC Evol. Biol
                BMC Evolutionary Biology
                BioMed Central (London )
                1471-2148
                15 September 2018
                15 September 2018
                2018
                : 18
                : 140
                Affiliations
                [1 ]ISNI 0000 0000 9899 6002, GRID grid.448477.c, Columbia River Inter-Tribal Fish Commission, ; 3059F National Fish Hatchery Road, Hagerman, ID 83332 USA
                [2 ]ISNI 0000 0000 9899 6002, GRID grid.448477.c, Columbia River Inter-Tribal Fish Commission, ; Portland, OR 97232 USA
                [3 ]Yakama Nation Fisheries Program, Toppenish, WA 98948 USA
                Author information
                http://orcid.org/0000-0002-3842-0946
                Article
                1255
                10.1186/s12862-018-1255-5
                6139179
                30219030
                4068ffd3-2868-43b1-908e-75c8f455ea1d
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 21 April 2018
                : 24 August 2018
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Evolutionary Biology
                oncorhynchus,adaptation,genome evolution,pooled sequencing,sexual maturation,greb1l,migration

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