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      Genetic characterization of Tibetan pigs adapted to high altitude under natural selection based on a large whole-genome dataset

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          Abstract

          The Qinghai-Tibet Plateau is a valuable genetic resource pool, and the high-altitude adaptation of Tibetan pigs is a classic example of the adaptive evolution of domestic animals. Here, we report the presence of Darwinian positive selection signatures in Tibetan pigs (TBPs) using 348 genome-wide datasets (127 whole-genome sequence datasets (WGSs) and 221 whole-genome single-nucleotide polymorphism (SNP) chip datasets). We characterized a high-confidence list of genetic signatures related response to high-altitude adaptation in Tibetan pigs, including 4,598 candidate SNPs and 131 candidate genes. Functional annotation and enrichment analysis revealed that 131 candidate genes are related to multiple systems and organs in Tibetan pigs. Notably, eight of the top ten novel genes, RALB, NBEA, LIFR, CLEC17A, PRIM2, CDH7, GK5 and FAM83B, were highlighted and associated with improved adaptive heart functions in Tibetan pigs high-altitude adaptation. Moreover, genome-wide association analysis revealed that 29 SNPs were involved in 13 candidate genes associated with at least one adaptive trait. In particular, among the top ten candidate genes, CLEC17A is related to a reduction in hemoglobin (HGB) in Tibetan pigs. Overall, our study provides a robust SNP/gene list involving genetic adaptation for Tibetan pig high-altitude adaptation, and it will be a valuable resource for future Tibetan pig studies.

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          Most cited references48

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          KEGG: kyoto encyclopedia of genes and genomes.

          M Kanehisa (2000)
          KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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            KEGG as a reference resource for gene and protein annotation

            KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an integrated database resource for biological interpretation of genome sequences and other high-throughput data. Molecular functions of genes and proteins are associated with ortholog groups and stored in the KEGG Orthology (KO) database. The KEGG pathway maps, BRITE hierarchies and KEGG modules are developed as networks of KO nodes, representing high-level functions of the cell and the organism. Currently, more than 4000 complete genomes are annotated with KOs in the KEGG GENES database, which can be used as a reference data set for KO assignment and subsequent reconstruction of KEGG pathways and other molecular networks. As an annotation resource, the following improvements have been made. First, each KO record is re-examined and associated with protein sequence data used in experiments of functional characterization. Second, the GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes. Third, new automatic annotation servers, BlastKOALA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from the GENES database. As a resource for translational bioinformatics, various data sets are created for antimicrobial resistance and drug interaction networks.
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              The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease

              Summary Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.
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                Author and article information

                Contributors
                zhaosg@gsau.edu.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                24 July 2024
                24 July 2024
                2024
                : 14
                : 17062
                Affiliations
                [1 ]College of Animal Science and Technology, Gansu Agricultural University, ( https://ror.org/05ym42410) Lanzhou, China
                [2 ]Academy of Agriculture and Animal Husbandry Sciences, Institute of Animal Husbandry and Veterinary Medicine, Lhasa, China
                [3 ]GRID grid.419010.d, ISNI 0000 0004 1792 7072, State Key Laboratory of Genetic Resources and Evolution, Chinese Academy of Sciences, , Kunming Institute of Zoology, ; Kunming, China
                [4 ]College of Grassland Science, Gansu Agricultural University, ( https://ror.org/05ym42410) Lanzhou, China
                [5 ]The Animal Husbandry Station in Changdu, Changdu, China
                [6 ]The Beast Prevention Station in Gongbujiangda County, Linzhi, China
                [7 ]The Animal Husbandry Station in Tibet Autonomous Region, Lhasa, China
                Article
                65559
                10.1038/s41598-024-65559-3
                11269713
                39048584
                690541aa-60df-4382-b065-6d29f5b6e55e
                © The Author(s) 2024

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 27 January 2024
                : 20 June 2024
                Funding
                Funded by: The study was supported by the National Natural Science Foundation of China
                Award ID: 32060730
                Award Recipient :
                Funded by: Agricultural science and technology project of Gansu Province
                Award ID: GNKJ-2023-27
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                tibetan pigs,high-altitude adaptation,wgs,snp,natural selection,population genetics,animal breeding,genetic markers,bioinformatics,genomic analysis

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