MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Lingzhao Fang, Peter Sørensen, Goutam Sahana, Frank Panitz, Guosheng Su, Shengli Zhang, Ying Yu, Bingjie Li, Li Ma, George Liu, Mogens Sandø Lund, Bo Thomsen

ABSTRACT

MicroRNAs (miRNA) are key modulators of gene expression and so act as putative fine-tuners of complex phenotypes. Here, we hypothesized that causal variants of complex traits are enriched in miRNAs and miRNA-target networks. First, we conducted a genome-wide association study (GWAS) for seven functional and milk production traits using imputed sequence variants (13~15 million) and >10,000 animals from three dairy cattle breeds, i.e., Holstein (HOL), Nordic red cattle (RDC) and Jersey (JER). Second, we analyzed for enrichments of association signals in miRNAs and their miRNA-target networks. Our results demonstrated that genomic regions harboring miRNA genes were significantly (P < 0.05) enriched with GWAS signals for milk production traits and mastitis, and that enrichments within miRNA-target gene networks were significantly higher than in random gene-sets for the majority of traits. Furthermore, most between-trait and across-breed correlations of enrichments with miRNA-target networks were significantly greater than with random gene-sets, suggesting pleiotropic effects of miRNAs. Intriguingly, genes that were differentially expressed in response to mammary gland infections were significantly enriched in the miRNA-target networks associated with mastitis. All these findings were consistent across three breeds. Collectively, our observations demonstrate the importance of miRNAs and their targets for the expression of complex traits. More... »

PAGES

9345

References to SciGraph publications

  • 2017-12. MicroRNA expression profiling of porcine mammary epithelial cells after challenge with Escherichia coli in vitro in BMC GENOMICS
  • 2012-09. Landscape of transcription in human cells in NATURE
  • 2017-12. MicroRNA roles in signalling during lactation: an insight from differential expression, time course and pathway analyses of deep sequence data in SCIENTIFIC REPORTS
  • 2008-12. Gene expression profiling of liver from dairy cows treated intra-mammary with lipopolysaccharide in BMC GENOMICS
  • 2012-12. Expression profiles of microRNAs from lactating and non-lactating bovine mammary glands and identification of miRNA related to lactation in BMC GENOMICS
  • 2015-12. Differential expression of microRNAs in porcine parvovirus infected porcine cell line in VIROLOGY JOURNAL
  • 2017-12. Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster in SCIENTIFIC REPORTS
  • 2017-12. Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection in GENETICS SELECTION EVOLUTION
  • 2013-05. MicroRNAs and Atherosclerosis in CURRENT ATHEROSCLEROSIS REPORTS
  • 2016-12. Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants in BMC GENETICS
  • 2014-12. Transcriptome microRNA profiling of bovine mammary epithelial cells challenged with Escherichia coli or Staphylococcus aureusbacteria reveals pathogen directed microRNA expression profiles in BMC GENOMICS
  • 2017-12. Detection and comparison of microRNAs in the caprine mammary gland tissues of colostrum and common milk stages in BMC GENETICS
  • 2016-12. Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits in BMC GENOMICS
  • 2014-12. Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle in BMC GENOMICS
  • 2017-12. Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds in BMC GENOMICS
  • 2005-02. Genome-wide association studies for common diseases and complex traits in NATURE REVIEWS GENETICS
  • 2015-12. MicroRNA expression profiles of bovine milk exosomes in response to Staphylococcus aureus infection in BMC GENOMICS
  • 2016-12. Increased prediction accuracy using a genomic feature model including prior information on quantitative trait locus regions in purebred Danish Duroc pigs in BMC GENETICS
  • 2014-08. Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle in NATURE GENETICS
  • 2015-12. Impact of QTL properties on the accuracy of multi-breed genomic prediction in GENETICS SELECTION EVOLUTION
  • 2011-08. Gene set analysis of SNP data: benefits, challenges, and future directions in EUROPEAN JOURNAL OF HUMAN GENETICS
  • 2010-11. Complex traits: Using genetic architecture to improve predictions in NATURE REVIEWS GENETICS
  • 2013-12. The advantages and limitations of trait analysis with GWAS: a review in PLANT METHODS
  • 2010-04. Variance component model to account for sample structure in genome-wide association studies in NATURE GENETICS
  • 2014-04. Discovering the complexity of the metazoan transcriptome in GENOME BIOLOGY
  • 2012-06. Improved linear mixed models for genome-wide association studies in NATURE METHODS
  • 2017-12. Integrating Sequence-based GWAS and RNA-Seq Provides Novel Insights into the Genetic Basis of Mastitis and Milk Production in Dairy Cattle in SCIENTIFIC REPORTS
  • 2015-11. Partitioning heritability by functional annotation using genome-wide association summary statistics in NATURE GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-018-27729-y

    DOI

    http://dx.doi.org/10.1038/s41598-018-27729-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1104585098

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/29921979


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of Maryland, College Park", 
              "id": "https://www.grid.ac/institutes/grid.164295.d", 
              "name": [
                "Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark", 
                "Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China", 
                "Department of Animal and Avian Sciences, University of Maryland, 20742 MD, College Park, USA", 
                "Animal Genomics and Improvement Laboratory, ARS USDA, 207052350 MD, Beltsville, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fang", 
            "givenName": "Lingzhao", 
            "id": "sg:person.013742572403.89", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013742572403.89"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Aarhus University", 
              "id": "https://www.grid.ac/institutes/grid.7048.b", 
              "name": [
                "Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark"
              ], 
              "type": "Organization"
            }, 
            "familyName": "S\u00f8rensen", 
            "givenName": "Peter", 
            "id": "sg:person.01252337106.35", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01252337106.35"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Aarhus University", 
              "id": "https://www.grid.ac/institutes/grid.7048.b", 
              "name": [
                "Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sahana", 
            "givenName": "Goutam", 
            "id": "sg:person.0727046246.31", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0727046246.31"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Aarhus University", 
              "id": "https://www.grid.ac/institutes/grid.7048.b", 
              "name": [
                "Section for Molecular Genetics and Systems Biology, Department of Molecular Biology and Genetics, Aarhus University, 8000, Aarhus C, Denmark"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Panitz", 
            "givenName": "Frank", 
            "id": "sg:person.01077435434.19", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01077435434.19"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Aarhus University", 
              "id": "https://www.grid.ac/institutes/grid.7048.b", 
              "name": [
                "Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Su", 
            "givenName": "Guosheng", 
            "id": "sg:person.01262045357.16", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01262045357.16"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "China Agricultural University", 
              "id": "https://www.grid.ac/institutes/grid.22935.3f", 
              "name": [
                "Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zhang", 
            "givenName": "Shengli", 
            "id": "sg:person.01156267530.51", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01156267530.51"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "China Agricultural University", 
              "id": "https://www.grid.ac/institutes/grid.22935.3f", 
              "name": [
                "Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yu", 
            "givenName": "Ying", 
            "id": "sg:person.01132513030.39", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01132513030.39"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Aarhus University", 
              "id": "https://www.grid.ac/institutes/grid.7048.b", 
              "name": [
                "Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Li", 
            "givenName": "Bingjie", 
            "id": "sg:person.014634125653.07", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014634125653.07"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Maryland, College Park", 
              "id": "https://www.grid.ac/institutes/grid.164295.d", 
              "name": [
                "Department of Animal and Avian Sciences, University of Maryland, 20742 MD, College Park, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ma", 
            "givenName": "Li", 
            "id": "sg:person.01142110673.77", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01142110673.77"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Animal Genomics and Improvement Laboratory, ARS USDA, 207052350 MD, Beltsville, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Liu", 
            "givenName": "George", 
            "id": "sg:person.012167476737.92", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012167476737.92"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Aarhus University", 
              "id": "https://www.grid.ac/institutes/grid.7048.b", 
              "name": [
                "Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lund", 
            "givenName": "Mogens Sand\u00f8", 
            "id": "sg:person.0740177106.57", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740177106.57"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Aarhus University", 
              "id": "https://www.grid.ac/institutes/grid.7048.b", 
              "name": [
                "Section for Molecular Genetics and Systems Biology, Department of Molecular Biology and Genetics, Aarhus University, 8000, Aarhus C, Denmark"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Thomsen", 
            "givenName": "Bo", 
            "id": "sg:person.01351114304.02", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01351114304.02"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.3389/fgene.2013.00280", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000078193"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12711-015-0124-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000768333", 
              "https://doi.org/10.1186/s12711-015-0124-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12711-015-0124-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000768333", 
              "https://doi.org/10.1186/s12711-015-0124-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-015-2044-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001889789", 
              "https://doi.org/10.1186/s12864-015-2044-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1089/omi.2011.0118", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003008024"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature11233", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003047559", 
              "https://doi.org/10.1038/nature11233"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb4172", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003234479", 
              "https://doi.org/10.1186/gb4172"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-15-181", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003903825", 
              "https://doi.org/10.1186/1471-2164-15-181"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1172/jci62876", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004072706"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.224202", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005941767"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.136127.111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007044518"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkv1221", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007957046"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12863-015-0322-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011423702", 
              "https://doi.org/10.1186/s12863-015-0322-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.genet.35.102401.090633", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011541917"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3390/ijms16034997", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012212847"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btu704", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012313285"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12863-016-0363-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013136050", 
              "https://doi.org/10.1186/s12863-016-0363-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.548", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016055940", 
              "https://doi.org/10.1038/ng.548"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.548", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016055940", 
              "https://doi.org/10.1038/ng.548"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkt1181", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016904256"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3168/jds.2015-10705", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019152554"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2004.12.035", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020132624"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-13-731", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020812194", 
              "https://doi.org/10.1186/1471-2164-13-731"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3390/ijms150813494", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021964495"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1746-4811-9-29", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022629361", 
              "https://doi.org/10.1186/1746-4811-9-29"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-016-2443-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022649278", 
              "https://doi.org/10.1186/s12864-016-2443-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg1521", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022754728", 
              "https://doi.org/10.1038/nrg1521"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg1521", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022754728", 
              "https://doi.org/10.1038/nrg1521"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1152/physiolgenomics.00084.2011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023133360"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1155/2014/970607", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026264262"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.3034", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028025360", 
              "https://doi.org/10.1038/ng.3034"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/cvr/cvn156", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029456753"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.10.2.220", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029509736"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0092-8674(04)00045-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031254572"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2009.05.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031607969"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.3404", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033620431", 
              "https://doi.org/10.1038/ng.3404"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1161/circresaha.112.266502", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036427985"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1161/circresaha.112.266502", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036427985"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/g3.111.001198", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037455212"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/g3.111.001198", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037455212"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.110.116855", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039215498"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.110.116855", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039215498"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gks901", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039258013"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11883-013-0322-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039442148", 
              "https://doi.org/10.1007/s11883-013-0322-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-9-443", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039692856", 
              "https://doi.org/10.1186/1471-2164-9-443"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1242/jcs.055210", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040054930"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-15-728", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040718046", 
              "https://doi.org/10.1186/1471-2164-15-728"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2888", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041430780", 
              "https://doi.org/10.1038/nrg2888"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2888", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041430780", 
              "https://doi.org/10.1038/nrg2888"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.2037", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045203738", 
              "https://doi.org/10.1038/nmeth.2037"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.celrep.2013.10.041", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045254319"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3168/jds.2012-5748", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045637231"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ejhg.2011.57", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050964013", 
              "https://doi.org/10.1038/ejhg.2011.57"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkn851", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051949960"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12985-015-0359-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053146387", 
              "https://doi.org/10.1186/s12985-015-0359-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/s0016672399004255", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1054058162"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/s1461145710001446", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1054933654"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.116.187161", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067739600"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.116.187161", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067739600"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.116.187161", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067739600"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.116.189498", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067739644"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.116.189498", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067739644"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.116.189498", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067739644"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2527/jas.2015-9838", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1070890498"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5713/ajas.15.0605", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1073082997"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep44605", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084132489", 
              "https://doi.org/10.1038/srep44605"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep45560", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084133296", 
              "https://doi.org/10.1038/srep45560"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1098/rsob.170019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084603555"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12863-017-0498-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084956300", 
              "https://doi.org/10.1186/s12863-017-0498-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12863-017-0498-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084956300", 
              "https://doi.org/10.1186/s12863-017-0498-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/005165", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085114316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/005165", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085114316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/005165", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085114316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12711-017-0319-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085378698", 
              "https://doi.org/10.1186/s12711-017-0319-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12711-017-0319-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085378698", 
              "https://doi.org/10.1186/s12711-017-0319-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0177182", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085438141"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41598-017-02281-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085546295", 
              "https://doi.org/10.1038/s41598-017-02281-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.117.200642", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085619653"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.117.200642", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085619653"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.117.200642", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085619653"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2017.06.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090371979"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3390/ijms18071560", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090742512"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-017-4004-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091143786", 
              "https://doi.org/10.1186/s12864-017-4004-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-017-4004-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091143786", 
              "https://doi.org/10.1186/s12864-017-4004-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/wdev.289", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091290046"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/s0022029917000437", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091312432"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-017-4070-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091329690", 
              "https://doi.org/10.1186/s12864-017-4070-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-017-4070-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091329690", 
              "https://doi.org/10.1186/s12864-017-4070-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3920/978-90-8686-550-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1109737727"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2018-12", 
        "datePublishedReg": "2018-12-01", 
        "description": "MicroRNAs (miRNA) are key modulators of gene expression and so act as putative fine-tuners of complex phenotypes. Here, we hypothesized that causal variants of complex traits are enriched in miRNAs and miRNA-target networks. First, we conducted a genome-wide association study (GWAS) for seven functional and milk production traits using imputed sequence variants (13~15\u2009million) and >10,000 animals from three dairy cattle breeds, i.e., Holstein (HOL), Nordic red cattle (RDC) and Jersey (JER). Second, we analyzed for enrichments of association signals in miRNAs and their miRNA-target networks. Our results demonstrated that genomic regions harboring miRNA genes were significantly (P\u2009<\u20090.05) enriched with GWAS signals for milk production traits and mastitis, and that enrichments within miRNA-target gene networks were significantly higher than in random gene-sets for the majority of traits. Furthermore, most between-trait and across-breed correlations of enrichments with miRNA-target networks were significantly greater than with random gene-sets, suggesting pleiotropic effects of miRNAs. Intriguingly, genes that were differentially expressed in response to mammary gland infections were significantly enriched in the miRNA-target networks associated with mastitis. All these findings were consistent across three breeds. Collectively, our observations demonstrate the importance of miRNAs and their targets for the expression of complex traits.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1038/s41598-018-27729-y", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1045337", 
            "issn": [
              "2045-2322"
            ], 
            "name": "Scientific Reports", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "8"
          }
        ], 
        "name": "MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle", 
        "pagination": "9345", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "e66597c2d711606d55f2838bac5469a48fb8b57e79cb6c83faeb4f61b87f649d"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "29921979"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101563288"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/s41598-018-27729-y"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1104585098"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/s41598-018-27729-y", 
          "https://app.dimensions.ai/details/publication/pub.1104585098"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T13:32", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8659_00000604.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://www.nature.com/articles/s41598-018-27729-y"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-27729-y'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-27729-y'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-27729-y'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-27729-y'


     

    This table displays all metadata directly associated to this object as RDF triples.

    395 TRIPLES      21 PREDICATES      99 URIs      21 LITERALS      9 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/s41598-018-27729-y schema:about anzsrc-for:06
    2 anzsrc-for:0604
    3 schema:author N70586a2ee4d844239680874c8531ccc3
    4 schema:citation sg:pub.10.1007/s11883-013-0322-z
    5 sg:pub.10.1038/ejhg.2011.57
    6 sg:pub.10.1038/nature11233
    7 sg:pub.10.1038/ng.3034
    8 sg:pub.10.1038/ng.3404
    9 sg:pub.10.1038/ng.548
    10 sg:pub.10.1038/nmeth.2037
    11 sg:pub.10.1038/nrg1521
    12 sg:pub.10.1038/nrg2888
    13 sg:pub.10.1038/s41598-017-02281-3
    14 sg:pub.10.1038/srep44605
    15 sg:pub.10.1038/srep45560
    16 sg:pub.10.1186/1471-2164-13-731
    17 sg:pub.10.1186/1471-2164-15-181
    18 sg:pub.10.1186/1471-2164-15-728
    19 sg:pub.10.1186/1471-2164-9-443
    20 sg:pub.10.1186/1746-4811-9-29
    21 sg:pub.10.1186/gb4172
    22 sg:pub.10.1186/s12711-015-0124-6
    23 sg:pub.10.1186/s12711-017-0319-0
    24 sg:pub.10.1186/s12863-015-0322-9
    25 sg:pub.10.1186/s12863-016-0363-8
    26 sg:pub.10.1186/s12863-017-0498-2
    27 sg:pub.10.1186/s12864-015-2044-9
    28 sg:pub.10.1186/s12864-016-2443-6
    29 sg:pub.10.1186/s12864-017-4004-z
    30 sg:pub.10.1186/s12864-017-4070-2
    31 sg:pub.10.1186/s12985-015-0359-4
    32 https://doi.org/10.1002/wdev.289
    33 https://doi.org/10.1016/j.ajhg.2009.05.011
    34 https://doi.org/10.1016/j.ajhg.2017.06.005
    35 https://doi.org/10.1016/j.cell.2004.12.035
    36 https://doi.org/10.1016/j.celrep.2013.10.041
    37 https://doi.org/10.1016/s0092-8674(04)00045-5
    38 https://doi.org/10.1017/s0016672399004255
    39 https://doi.org/10.1017/s0022029917000437
    40 https://doi.org/10.1017/s1461145710001446
    41 https://doi.org/10.1089/omi.2011.0118
    42 https://doi.org/10.1093/bioinformatics/btu704
    43 https://doi.org/10.1093/cvr/cvn156
    44 https://doi.org/10.1093/nar/gkn851
    45 https://doi.org/10.1093/nar/gks901
    46 https://doi.org/10.1093/nar/gkt1181
    47 https://doi.org/10.1093/nar/gkv1221
    48 https://doi.org/10.1098/rsob.170019
    49 https://doi.org/10.1101/005165
    50 https://doi.org/10.1101/gr.10.2.220
    51 https://doi.org/10.1101/gr.136127.111
    52 https://doi.org/10.1101/gr.224202
    53 https://doi.org/10.1146/annurev.genet.35.102401.090633
    54 https://doi.org/10.1152/physiolgenomics.00084.2011
    55 https://doi.org/10.1155/2014/970607
    56 https://doi.org/10.1161/circresaha.112.266502
    57 https://doi.org/10.1172/jci62876
    58 https://doi.org/10.1242/jcs.055210
    59 https://doi.org/10.1371/journal.pone.0177182
    60 https://doi.org/10.1534/g3.111.001198
    61 https://doi.org/10.1534/genetics.110.116855
    62 https://doi.org/10.1534/genetics.116.187161
    63 https://doi.org/10.1534/genetics.116.189498
    64 https://doi.org/10.1534/genetics.117.200642
    65 https://doi.org/10.2527/jas.2015-9838
    66 https://doi.org/10.3168/jds.2012-5748
    67 https://doi.org/10.3168/jds.2015-10705
    68 https://doi.org/10.3389/fgene.2013.00280
    69 https://doi.org/10.3390/ijms150813494
    70 https://doi.org/10.3390/ijms16034997
    71 https://doi.org/10.3390/ijms18071560
    72 https://doi.org/10.3920/978-90-8686-550-5
    73 https://doi.org/10.5713/ajas.15.0605
    74 schema:datePublished 2018-12
    75 schema:datePublishedReg 2018-12-01
    76 schema:description MicroRNAs (miRNA) are key modulators of gene expression and so act as putative fine-tuners of complex phenotypes. Here, we hypothesized that causal variants of complex traits are enriched in miRNAs and miRNA-target networks. First, we conducted a genome-wide association study (GWAS) for seven functional and milk production traits using imputed sequence variants (13~15 million) and >10,000 animals from three dairy cattle breeds, i.e., Holstein (HOL), Nordic red cattle (RDC) and Jersey (JER). Second, we analyzed for enrichments of association signals in miRNAs and their miRNA-target networks. Our results demonstrated that genomic regions harboring miRNA genes were significantly (P < 0.05) enriched with GWAS signals for milk production traits and mastitis, and that enrichments within miRNA-target gene networks were significantly higher than in random gene-sets for the majority of traits. Furthermore, most between-trait and across-breed correlations of enrichments with miRNA-target networks were significantly greater than with random gene-sets, suggesting pleiotropic effects of miRNAs. Intriguingly, genes that were differentially expressed in response to mammary gland infections were significantly enriched in the miRNA-target networks associated with mastitis. All these findings were consistent across three breeds. Collectively, our observations demonstrate the importance of miRNAs and their targets for the expression of complex traits.
    77 schema:genre research_article
    78 schema:inLanguage en
    79 schema:isAccessibleForFree true
    80 schema:isPartOf N07010587ee284e5bb22575e410150c6e
    81 Nba4fb9cf49fc48b19546e6d4a710bd9b
    82 sg:journal.1045337
    83 schema:name MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle
    84 schema:pagination 9345
    85 schema:productId N04affbbdfbb742fda3bb6769a32c6543
    86 N370ae362273a4ccaacd3dcfe58f9d0af
    87 N854ebc352c964d0b9ee630521362230e
    88 Na63e609348ee479ba408b8abeeeea4dc
    89 Ne577eb098dfb47fc81eb2af387ce0630
    90 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104585098
    91 https://doi.org/10.1038/s41598-018-27729-y
    92 schema:sdDatePublished 2019-04-10T13:32
    93 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    94 schema:sdPublisher N9247ea3366164e04b79e2de53452e77c
    95 schema:url https://www.nature.com/articles/s41598-018-27729-y
    96 sgo:license sg:explorer/license/
    97 sgo:sdDataset articles
    98 rdf:type schema:ScholarlyArticle
    99 N04affbbdfbb742fda3bb6769a32c6543 schema:name nlm_unique_id
    100 schema:value 101563288
    101 rdf:type schema:PropertyValue
    102 N07010587ee284e5bb22575e410150c6e schema:issueNumber 1
    103 rdf:type schema:PublicationIssue
    104 N370ae362273a4ccaacd3dcfe58f9d0af schema:name pubmed_id
    105 schema:value 29921979
    106 rdf:type schema:PropertyValue
    107 N3fd322763b004f2a807b50807d63d172 rdf:first sg:person.0740177106.57
    108 rdf:rest Nc2b64db0b9a7443593e1eabb0307f844
    109 N4f4e5b8c47244dbe993098869123f722 rdf:first sg:person.0727046246.31
    110 rdf:rest Nb81810c48f484c3187662ab51f5c1272
    111 N70586a2ee4d844239680874c8531ccc3 rdf:first sg:person.013742572403.89
    112 rdf:rest Nbd0d7925d8fe4eb38c76ed69d793607b
    113 N854ebc352c964d0b9ee630521362230e schema:name readcube_id
    114 schema:value e66597c2d711606d55f2838bac5469a48fb8b57e79cb6c83faeb4f61b87f649d
    115 rdf:type schema:PropertyValue
    116 N9247ea3366164e04b79e2de53452e77c schema:name Springer Nature - SN SciGraph project
    117 rdf:type schema:Organization
    118 Na63e609348ee479ba408b8abeeeea4dc schema:name dimensions_id
    119 schema:value pub.1104585098
    120 rdf:type schema:PropertyValue
    121 Nb49501512b4a4d6aa42917808bbb896a rdf:first sg:person.01142110673.77
    122 rdf:rest Nf94afc1b3d4e45cf9993a84e08160e8e
    123 Nb7533a6aff764f87990cccd11c55a793 rdf:first sg:person.01262045357.16
    124 rdf:rest Nd9ab623b15444073b626bd21b7476695
    125 Nb81810c48f484c3187662ab51f5c1272 rdf:first sg:person.01077435434.19
    126 rdf:rest Nb7533a6aff764f87990cccd11c55a793
    127 Nba4fb9cf49fc48b19546e6d4a710bd9b schema:volumeNumber 8
    128 rdf:type schema:PublicationVolume
    129 Nbd0d7925d8fe4eb38c76ed69d793607b rdf:first sg:person.01252337106.35
    130 rdf:rest N4f4e5b8c47244dbe993098869123f722
    131 Nbf3692e487fb463e9783f2acad0f19fc rdf:first sg:person.01132513030.39
    132 rdf:rest Nfa07421162c34735aa03af95366922ef
    133 Nc2b64db0b9a7443593e1eabb0307f844 rdf:first sg:person.01351114304.02
    134 rdf:rest rdf:nil
    135 Nd2a948c56db7479cb3ee844da410eb27 schema:name Animal Genomics and Improvement Laboratory, ARS USDA, 207052350 MD, Beltsville, USA
    136 rdf:type schema:Organization
    137 Nd9ab623b15444073b626bd21b7476695 rdf:first sg:person.01156267530.51
    138 rdf:rest Nbf3692e487fb463e9783f2acad0f19fc
    139 Ne577eb098dfb47fc81eb2af387ce0630 schema:name doi
    140 schema:value 10.1038/s41598-018-27729-y
    141 rdf:type schema:PropertyValue
    142 Nf94afc1b3d4e45cf9993a84e08160e8e rdf:first sg:person.012167476737.92
    143 rdf:rest N3fd322763b004f2a807b50807d63d172
    144 Nfa07421162c34735aa03af95366922ef rdf:first sg:person.014634125653.07
    145 rdf:rest Nb49501512b4a4d6aa42917808bbb896a
    146 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    147 schema:name Biological Sciences
    148 rdf:type schema:DefinedTerm
    149 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    150 schema:name Genetics
    151 rdf:type schema:DefinedTerm
    152 sg:journal.1045337 schema:issn 2045-2322
    153 schema:name Scientific Reports
    154 rdf:type schema:Periodical
    155 sg:person.01077435434.19 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
    156 schema:familyName Panitz
    157 schema:givenName Frank
    158 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01077435434.19
    159 rdf:type schema:Person
    160 sg:person.01132513030.39 schema:affiliation https://www.grid.ac/institutes/grid.22935.3f
    161 schema:familyName Yu
    162 schema:givenName Ying
    163 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01132513030.39
    164 rdf:type schema:Person
    165 sg:person.01142110673.77 schema:affiliation https://www.grid.ac/institutes/grid.164295.d
    166 schema:familyName Ma
    167 schema:givenName Li
    168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01142110673.77
    169 rdf:type schema:Person
    170 sg:person.01156267530.51 schema:affiliation https://www.grid.ac/institutes/grid.22935.3f
    171 schema:familyName Zhang
    172 schema:givenName Shengli
    173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01156267530.51
    174 rdf:type schema:Person
    175 sg:person.012167476737.92 schema:affiliation Nd2a948c56db7479cb3ee844da410eb27
    176 schema:familyName Liu
    177 schema:givenName George
    178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012167476737.92
    179 rdf:type schema:Person
    180 sg:person.01252337106.35 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
    181 schema:familyName Sørensen
    182 schema:givenName Peter
    183 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01252337106.35
    184 rdf:type schema:Person
    185 sg:person.01262045357.16 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
    186 schema:familyName Su
    187 schema:givenName Guosheng
    188 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01262045357.16
    189 rdf:type schema:Person
    190 sg:person.01351114304.02 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
    191 schema:familyName Thomsen
    192 schema:givenName Bo
    193 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01351114304.02
    194 rdf:type schema:Person
    195 sg:person.013742572403.89 schema:affiliation https://www.grid.ac/institutes/grid.164295.d
    196 schema:familyName Fang
    197 schema:givenName Lingzhao
    198 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013742572403.89
    199 rdf:type schema:Person
    200 sg:person.014634125653.07 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
    201 schema:familyName Li
    202 schema:givenName Bingjie
    203 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014634125653.07
    204 rdf:type schema:Person
    205 sg:person.0727046246.31 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
    206 schema:familyName Sahana
    207 schema:givenName Goutam
    208 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0727046246.31
    209 rdf:type schema:Person
    210 sg:person.0740177106.57 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
    211 schema:familyName Lund
    212 schema:givenName Mogens Sandø
    213 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740177106.57
    214 rdf:type schema:Person
    215 sg:pub.10.1007/s11883-013-0322-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1039442148
    216 https://doi.org/10.1007/s11883-013-0322-z
    217 rdf:type schema:CreativeWork
    218 sg:pub.10.1038/ejhg.2011.57 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050964013
    219 https://doi.org/10.1038/ejhg.2011.57
    220 rdf:type schema:CreativeWork
    221 sg:pub.10.1038/nature11233 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003047559
    222 https://doi.org/10.1038/nature11233
    223 rdf:type schema:CreativeWork
    224 sg:pub.10.1038/ng.3034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028025360
    225 https://doi.org/10.1038/ng.3034
    226 rdf:type schema:CreativeWork
    227 sg:pub.10.1038/ng.3404 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033620431
    228 https://doi.org/10.1038/ng.3404
    229 rdf:type schema:CreativeWork
    230 sg:pub.10.1038/ng.548 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016055940
    231 https://doi.org/10.1038/ng.548
    232 rdf:type schema:CreativeWork
    233 sg:pub.10.1038/nmeth.2037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045203738
    234 https://doi.org/10.1038/nmeth.2037
    235 rdf:type schema:CreativeWork
    236 sg:pub.10.1038/nrg1521 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022754728
    237 https://doi.org/10.1038/nrg1521
    238 rdf:type schema:CreativeWork
    239 sg:pub.10.1038/nrg2888 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041430780
    240 https://doi.org/10.1038/nrg2888
    241 rdf:type schema:CreativeWork
    242 sg:pub.10.1038/s41598-017-02281-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085546295
    243 https://doi.org/10.1038/s41598-017-02281-3
    244 rdf:type schema:CreativeWork
    245 sg:pub.10.1038/srep44605 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084132489
    246 https://doi.org/10.1038/srep44605
    247 rdf:type schema:CreativeWork
    248 sg:pub.10.1038/srep45560 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084133296
    249 https://doi.org/10.1038/srep45560
    250 rdf:type schema:CreativeWork
    251 sg:pub.10.1186/1471-2164-13-731 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020812194
    252 https://doi.org/10.1186/1471-2164-13-731
    253 rdf:type schema:CreativeWork
    254 sg:pub.10.1186/1471-2164-15-181 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003903825
    255 https://doi.org/10.1186/1471-2164-15-181
    256 rdf:type schema:CreativeWork
    257 sg:pub.10.1186/1471-2164-15-728 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040718046
    258 https://doi.org/10.1186/1471-2164-15-728
    259 rdf:type schema:CreativeWork
    260 sg:pub.10.1186/1471-2164-9-443 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039692856
    261 https://doi.org/10.1186/1471-2164-9-443
    262 rdf:type schema:CreativeWork
    263 sg:pub.10.1186/1746-4811-9-29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022629361
    264 https://doi.org/10.1186/1746-4811-9-29
    265 rdf:type schema:CreativeWork
    266 sg:pub.10.1186/gb4172 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003234479
    267 https://doi.org/10.1186/gb4172
    268 rdf:type schema:CreativeWork
    269 sg:pub.10.1186/s12711-015-0124-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000768333
    270 https://doi.org/10.1186/s12711-015-0124-6
    271 rdf:type schema:CreativeWork
    272 sg:pub.10.1186/s12711-017-0319-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085378698
    273 https://doi.org/10.1186/s12711-017-0319-0
    274 rdf:type schema:CreativeWork
    275 sg:pub.10.1186/s12863-015-0322-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011423702
    276 https://doi.org/10.1186/s12863-015-0322-9
    277 rdf:type schema:CreativeWork
    278 sg:pub.10.1186/s12863-016-0363-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013136050
    279 https://doi.org/10.1186/s12863-016-0363-8
    280 rdf:type schema:CreativeWork
    281 sg:pub.10.1186/s12863-017-0498-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084956300
    282 https://doi.org/10.1186/s12863-017-0498-2
    283 rdf:type schema:CreativeWork
    284 sg:pub.10.1186/s12864-015-2044-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001889789
    285 https://doi.org/10.1186/s12864-015-2044-9
    286 rdf:type schema:CreativeWork
    287 sg:pub.10.1186/s12864-016-2443-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022649278
    288 https://doi.org/10.1186/s12864-016-2443-6
    289 rdf:type schema:CreativeWork
    290 sg:pub.10.1186/s12864-017-4004-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1091143786
    291 https://doi.org/10.1186/s12864-017-4004-z
    292 rdf:type schema:CreativeWork
    293 sg:pub.10.1186/s12864-017-4070-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091329690
    294 https://doi.org/10.1186/s12864-017-4070-2
    295 rdf:type schema:CreativeWork
    296 sg:pub.10.1186/s12985-015-0359-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053146387
    297 https://doi.org/10.1186/s12985-015-0359-4
    298 rdf:type schema:CreativeWork
    299 https://doi.org/10.1002/wdev.289 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091290046
    300 rdf:type schema:CreativeWork
    301 https://doi.org/10.1016/j.ajhg.2009.05.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031607969
    302 rdf:type schema:CreativeWork
    303 https://doi.org/10.1016/j.ajhg.2017.06.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090371979
    304 rdf:type schema:CreativeWork
    305 https://doi.org/10.1016/j.cell.2004.12.035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020132624
    306 rdf:type schema:CreativeWork
    307 https://doi.org/10.1016/j.celrep.2013.10.041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045254319
    308 rdf:type schema:CreativeWork
    309 https://doi.org/10.1016/s0092-8674(04)00045-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031254572
    310 rdf:type schema:CreativeWork
    311 https://doi.org/10.1017/s0016672399004255 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054058162
    312 rdf:type schema:CreativeWork
    313 https://doi.org/10.1017/s0022029917000437 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091312432
    314 rdf:type schema:CreativeWork
    315 https://doi.org/10.1017/s1461145710001446 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054933654
    316 rdf:type schema:CreativeWork
    317 https://doi.org/10.1089/omi.2011.0118 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003008024
    318 rdf:type schema:CreativeWork
    319 https://doi.org/10.1093/bioinformatics/btu704 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012313285
    320 rdf:type schema:CreativeWork
    321 https://doi.org/10.1093/cvr/cvn156 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029456753
    322 rdf:type schema:CreativeWork
    323 https://doi.org/10.1093/nar/gkn851 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051949960
    324 rdf:type schema:CreativeWork
    325 https://doi.org/10.1093/nar/gks901 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039258013
    326 rdf:type schema:CreativeWork
    327 https://doi.org/10.1093/nar/gkt1181 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016904256
    328 rdf:type schema:CreativeWork
    329 https://doi.org/10.1093/nar/gkv1221 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007957046
    330 rdf:type schema:CreativeWork
    331 https://doi.org/10.1098/rsob.170019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084603555
    332 rdf:type schema:CreativeWork
    333 https://doi.org/10.1101/005165 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085114316
    334 rdf:type schema:CreativeWork
    335 https://doi.org/10.1101/gr.10.2.220 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029509736
    336 rdf:type schema:CreativeWork
    337 https://doi.org/10.1101/gr.136127.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007044518
    338 rdf:type schema:CreativeWork
    339 https://doi.org/10.1101/gr.224202 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005941767
    340 rdf:type schema:CreativeWork
    341 https://doi.org/10.1146/annurev.genet.35.102401.090633 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011541917
    342 rdf:type schema:CreativeWork
    343 https://doi.org/10.1152/physiolgenomics.00084.2011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023133360
    344 rdf:type schema:CreativeWork
    345 https://doi.org/10.1155/2014/970607 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026264262
    346 rdf:type schema:CreativeWork
    347 https://doi.org/10.1161/circresaha.112.266502 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036427985
    348 rdf:type schema:CreativeWork
    349 https://doi.org/10.1172/jci62876 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004072706
    350 rdf:type schema:CreativeWork
    351 https://doi.org/10.1242/jcs.055210 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040054930
    352 rdf:type schema:CreativeWork
    353 https://doi.org/10.1371/journal.pone.0177182 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085438141
    354 rdf:type schema:CreativeWork
    355 https://doi.org/10.1534/g3.111.001198 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037455212
    356 rdf:type schema:CreativeWork
    357 https://doi.org/10.1534/genetics.110.116855 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039215498
    358 rdf:type schema:CreativeWork
    359 https://doi.org/10.1534/genetics.116.187161 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067739600
    360 rdf:type schema:CreativeWork
    361 https://doi.org/10.1534/genetics.116.189498 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067739644
    362 rdf:type schema:CreativeWork
    363 https://doi.org/10.1534/genetics.117.200642 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085619653
    364 rdf:type schema:CreativeWork
    365 https://doi.org/10.2527/jas.2015-9838 schema:sameAs https://app.dimensions.ai/details/publication/pub.1070890498
    366 rdf:type schema:CreativeWork
    367 https://doi.org/10.3168/jds.2012-5748 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045637231
    368 rdf:type schema:CreativeWork
    369 https://doi.org/10.3168/jds.2015-10705 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019152554
    370 rdf:type schema:CreativeWork
    371 https://doi.org/10.3389/fgene.2013.00280 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000078193
    372 rdf:type schema:CreativeWork
    373 https://doi.org/10.3390/ijms150813494 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021964495
    374 rdf:type schema:CreativeWork
    375 https://doi.org/10.3390/ijms16034997 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012212847
    376 rdf:type schema:CreativeWork
    377 https://doi.org/10.3390/ijms18071560 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090742512
    378 rdf:type schema:CreativeWork
    379 https://doi.org/10.3920/978-90-8686-550-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109737727
    380 rdf:type schema:CreativeWork
    381 https://doi.org/10.5713/ajas.15.0605 schema:sameAs https://app.dimensions.ai/details/publication/pub.1073082997
    382 rdf:type schema:CreativeWork
    383 https://www.grid.ac/institutes/grid.164295.d schema:alternateName University of Maryland, College Park
    384 schema:name Animal Genomics and Improvement Laboratory, ARS USDA, 207052350 MD, Beltsville, USA
    385 Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark
    386 Department of Animal and Avian Sciences, University of Maryland, 20742 MD, College Park, USA
    387 Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
    388 rdf:type schema:Organization
    389 https://www.grid.ac/institutes/grid.22935.3f schema:alternateName China Agricultural University
    390 schema:name Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
    391 rdf:type schema:Organization
    392 https://www.grid.ac/institutes/grid.7048.b schema:alternateName Aarhus University
    393 schema:name Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark
    394 Section for Molecular Genetics and Systems Biology, Department of Molecular Biology and Genetics, Aarhus University, 8000, Aarhus C, Denmark
    395 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...