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      A genome-wide scan for candidate lethal variants in Thoroughbred horses

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          Abstract

          Domestic animal populations are often characterised by high rates of inbreeding and low effective population sizes due to selective breeding practices. These practices can result in otherwise rare recessive deleterious alleles drifting to high frequencies, resulting in reduced fertility rates. This study aimed to identify potential recessive lethal haplotypes in the Thoroughbred horse breed, a closed population that has been selectively bred for racing performance. In this study, we identified a haplotype in the LY49B gene that shows strong evidence of being homozygous lethal, despite having high frequencies of heterozygotes in Thoroughbreds and other domestic horse breeds. Variant analysis of whole-genome sequence data identified two SNPs in the 3′UTR of the LY49B gene that may result in loss of function. Analysis of transcriptomic data from equine embryonic tissue revealed that LY49B is expressed in the trophoblast during placentation stage of development. These findings suggest that LY49B may have an essential, but as yet unknown function in the implantation stage of equine development. Further investigation of this region may allow for the development of a genetic test to improve fertility rates in horse populations. Identification of other lethal variants could assist in improving natural levels of fertility in horse populations.

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          The genetics of inbreeding depression.

          Inbreeding depression - the reduced survival and fertility of offspring of related individuals - occurs in wild animal and plant populations as well as in humans, indicating that genetic variation in fitness traits exists in natural populations. Inbreeding depression is important in the evolution of outcrossing mating systems and, because intercrossing inbred strains improves yield (heterosis), which is important in crop breeding, the genetic basis of these effects has been debated since the early twentieth century. Classical genetic studies and modern molecular evolutionary approaches now suggest that inbreeding depression and heterosis are predominantly caused by the presence of recessive deleterious mutations in populations.
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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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              A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep.

              Texel sheep are renowned for their exceptional meatiness. To identify the genes underlying this economically important feature, we performed a whole-genome scan in a Romanov x Texel F2 population. We mapped a quantitative trait locus with a major effect on muscle mass to chromosome 2 and subsequently fine-mapped it to a chromosome interval encompassing the myostatin (GDF8) gene. We herein demonstrate that the GDF8 allele of Texel sheep is characterized by a G to A transition in the 3' UTR that creates a target site for mir1 and mir206, microRNAs (miRNAs) that are highly expressed in skeletal muscle. This causes translational inhibition of the myostatin gene and hence contributes to the muscular hypertrophy of Texel sheep. Analysis of SNP databases for humans and mice demonstrates that mutations creating or destroying putative miRNA target sites are abundant and might be important effectors of phenotypic variation.
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                Author and article information

                Contributors
                evelyn.todd@sydney.edu.au
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                4 August 2020
                4 August 2020
                2020
                : 10
                : 13153
                Affiliations
                [1 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, School of Life and Environmental Sciences, , The University of Sydney, ; Sydney, Australia
                [2 ]Racing Australia Equine Genetics Research Centre, Sydney, Australia
                [3 ]ISNI 0000 0000 8578 2742, GRID grid.6341.0, Department of Animal Breeding and Genetics, , Swedish University of Agricultural Sciences, ; Uppsala, Sweden
                [4 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, Livestock Genetics, Department of Biosystems, , KU Leuven, ; Leuven, Belgium
                [5 ]ISNI 0000 0004 0607 975X, GRID grid.19477.3c, Department of Companion Animal Clinical Sciences, Faculty of Veterinary Medicine, , Norwegian University of Life Sciences, ; Oslo, Norway
                Article
                68946
                10.1038/s41598-020-68946-8
                7403398
                32753654
                3a8f7e68-7ef2-464d-b2fd-76860c7c7eb4
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 13 May 2020
                : 26 June 2020
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                © The Author(s) 2020

                Uncategorized
                computational biology and bioinformatics,genetics
                Uncategorized
                computational biology and bioinformatics, genetics

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