Fine mapping QTL for female fertility on BTA04 and BTA13 in dairy cattle using HD SNP and sequence data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Johanna K Höglund, Goutam Sahana, Rasmus Froberg Brøndum, Bernt Guldbrandtsen, Bart Buitenhuis, Mogens S Lund

ABSTRACT

BACKGROUND: Female fertility is important for the maintenance of the production in a dairy cattle herd. Two QTL regions on BTA04 and on BTA13 previously detected in Nordic Holstein (NH) and validated in the Danish Jersey (DJ) and Nordic Red (NR) were investigated further in the present study to further refine the QTL locations. Refined QTL regions were imputed to the full sequence data. The genes in the regions were then studied to ascertain their possible effect on fertility traits. RESULTS: BTA04 was screened for number of inseminations (AIS), 56-day non-return rate (NRR), days from first to last insemination (IFL), and the interval from calving to first insemination (ICF) in the range of 38,257,758 to 40,890,784 bp, whereas BTA13 was screened for ICF only in the range from 21,236,959 to 46,150,079 with the HD bovine SNP array for NH, DJ and NR. No markers in the DJ and NR breeds reached significance. By analyzing imputed sequence data the QTL position on BTA04 was narrowed down to two regions in the NH. In these two regions a total of 9 genes were identified. BTA13 was analyzed using sequence data for the NH breed. The highest -log10(P-value) was 19.41 at 33,903,159 bp. Two regions were identified: Region 1: 33,900,143-33,908,994 bp and Region 2: 34,051,815-34,056,728 bp. SNPs within and between these two regions were annotated as intergenic. CONCLUSION: Screening BTA04 and BTA13 for female fertility traits in NH, NR and DJ suggested that the QTL for female fertility were specific for NH. A missense mutation in CD36 showed the strongest association with fertility traits on BTA04. The annotated SNPs on BTA13 were all intergenic variants. It is possible that BTA13 at this stage is poorly annotated such that the associated polymorphisms are located in as-yet undiscovered genes. Fertility traits are complex traits as many different biological and physiological factors determine whether a cow is fertile. Therefore it is not expected that there is a simple explanation with an obvious candidate gene but it is more likely a network of genes and intragenic variants that explain the variation of these traits. More... »

PAGES

790

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2164-15-790

DOI

http://dx.doi.org/10.1186/1471-2164-15-790

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029771054

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25216717


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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Animals", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cattle", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Chromosome Mapping", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computational Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Fertility", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genetic Markers", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genome-Wide Association Study", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genomics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "High-Throughput Nucleotide Sequencing", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Linkage Disequilibrium", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phenotype", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Polymorphism, Single Nucleotide", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Quantitative Trait Loci", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Swedish University of Agricultural Sciences", 
          "id": "https://www.grid.ac/institutes/grid.6341.0", 
          "name": [
            "Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, P.O. Box 50, DK-8830, Tjele, Denmark", 
            "Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, P.O. Box 7070, 750 07, Uppsala, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "H\u00f6glund", 
        "givenName": "Johanna K", 
        "id": "sg:person.01203034260.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01203034260.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Aarhus University", 
          "id": "https://www.grid.ac/institutes/grid.7048.b", 
          "name": [
            "Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, P.O. Box 50, DK-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": [
            "Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, P.O. Box 50, DK-8830, Tjele, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Br\u00f8ndum", 
        "givenName": "Rasmus Froberg", 
        "id": "sg:person.0757045612.02", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757045612.02"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Aarhus University", 
          "id": "https://www.grid.ac/institutes/grid.7048.b", 
          "name": [
            "Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, P.O. Box 50, DK-8830, Tjele, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guldbrandtsen", 
        "givenName": "Bernt", 
        "id": "sg:person.0655324301.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0655324301.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Aarhus University", 
          "id": "https://www.grid.ac/institutes/grid.7048.b", 
          "name": [
            "Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, P.O. Box 50, DK-8830, Tjele, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Buitenhuis", 
        "givenName": "Bart", 
        "id": "sg:person.0650267300.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0650267300.38"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Aarhus University", 
          "id": "https://www.grid.ac/institutes/grid.7048.b", 
          "name": [
            "Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, P.O. Box 50, DK-8830, Tjele, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lund", 
        "givenName": "Mogens S", 
        "id": "sg:person.0740177106.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740177106.57"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1371/journal.pone.0065550", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002738930"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2156-15-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004306245", 
          "https://doi.org/10.1186/1471-2156-15-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/29.1.308", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005817660"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/bth457", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008081196"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2052.2010.02064.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015623410"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2052.2010.02064.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015623410"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btp352", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023014918"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0082909", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023839045"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2009-10-4-r42", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024097093", 
          "https://doi.org/10.1186/gb-2009-10-4-r42"
        ], 
        "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": "sg:pub.10.1186/1297-9686-43-43", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030941918", 
          "https://doi.org/10.1186/1297-9686-43-43"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3168/jds.2011-4624", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031598086"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.107524.110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032096953"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ajhg.2009.01.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033548087"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1702", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035781360", 
          "https://doi.org/10.1038/ng1702"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1702", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035781360", 
          "https://doi.org/10.1038/ng1702"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3168/jds.2012-5379", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035908887"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btp324", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038266369"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2156-10-19", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039058389", 
          "https://doi.org/10.1186/1471-2156-10-19"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pgen.1000529", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043446290"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1297-9686-39-2-181", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046658059", 
          "https://doi.org/10.1186/1297-9686-39-2-181"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btq330", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047117020"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.078212.108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047542880"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.genom.7.080505.115623", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047886041"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gks1150", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051654714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2164-9-187", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052463226", 
          "https://doi.org/10.1186/1471-2164-9-187"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3168/jds.s0022-0302(05)72861-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1077038452"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077297430", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3168/jds.2008-1104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1077890248"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-12", 
    "datePublishedReg": "2014-12-01", 
    "description": "BACKGROUND: Female fertility is important for the maintenance of the production in a dairy cattle herd. Two QTL regions on BTA04 and on BTA13 previously detected in Nordic Holstein (NH) and validated in the Danish Jersey (DJ) and Nordic Red (NR) were investigated further in the present study to further refine the QTL locations. Refined QTL regions were imputed to the full sequence data. The genes in the regions were then studied to ascertain their possible effect on fertility traits.\nRESULTS: BTA04 was screened for number of inseminations (AIS), 56-day non-return rate (NRR), days from first to last insemination (IFL), and the interval from calving to first insemination (ICF) in the range of 38,257,758 to 40,890,784 bp, whereas BTA13 was screened for ICF only in the range from 21,236,959 to 46,150,079 with the HD bovine SNP array for NH, DJ and NR. No markers in the DJ and NR breeds reached significance. By analyzing imputed sequence data the QTL position on BTA04 was narrowed down to two regions in the NH. In these two regions a total of 9 genes were identified. BTA13 was analyzed using sequence data for the NH breed. The highest -log10(P-value) was 19.41 at 33,903,159 bp. Two regions were identified: Region 1: 33,900,143-33,908,994 bp and Region 2: 34,051,815-34,056,728 bp. SNPs within and between these two regions were annotated as intergenic.\nCONCLUSION: Screening BTA04 and BTA13 for female fertility traits in NH, NR and DJ suggested that the QTL for female fertility were specific for NH. A missense mutation in CD36 showed the strongest association with fertility traits on BTA04. The annotated SNPs on BTA13 were all intergenic variants. It is possible that BTA13 at this stage is poorly annotated such that the associated polymorphisms are located in as-yet undiscovered genes. Fertility traits are complex traits as many different biological and physiological factors determine whether a cow is fertile. Therefore it is not expected that there is a simple explanation with an obvious candidate gene but it is more likely a network of genes and intragenic variants that explain the variation of these traits.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/1471-2164-15-790", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1023790", 
        "issn": [
          "1471-2164"
        ], 
        "name": "BMC Genomics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "15"
      }
    ], 
    "name": "Fine mapping QTL for female fertility on BTA04 and BTA13 in dairy cattle using HD SNP and sequence data", 
    "pagination": "790", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "8dd2f78834e307d90209ef4523ff3bff39cbe97aeb77760664a4d13b3d4a0602"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "25216717"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100965258"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1471-2164-15-790"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1029771054"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1471-2164-15-790", 
      "https://app.dimensions.ai/details/publication/pub.1029771054"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T22:39", 
    "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_8690_00000550.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2F1471-2164-15-790"
  }
]
 

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.10.1186/1471-2164-15-790'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-15-790'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-15-790'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-15-790'


 

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

251 TRIPLES      21 PREDICATES      70 URIs      35 LITERALS      23 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1471-2164-15-790 schema:about N0d2d9e42805c41ed8913b24b2985e455
2 N17e9247f578c401bbfd3ca422e172173
3 N1acdd331388a4bbf96b71945b4f50fd2
4 N231acb50e6c8443bac6c4a5124cb0788
5 N4dec138e8dee4d6db43934360cdb455e
6 N5f8c4409522d4647801f6dfe05815da9
7 N7a37f83c693a4d1ba1cb99454c48392a
8 N847714de7a3845799da5cb8731d5ee7e
9 N985419758a314d88b03df2b9045ebb32
10 Na36d27fc63034ae59f6dbae0cf7afad3
11 Ncb3670fed56b40b19b4b36e0eb78f3b4
12 Nd561046340fb4b15b75903a498a7dff5
13 Ne7a9eac18bb84824be9755851dc58c1c
14 Nfe8d32c43f284151a2ba92dce1303725
15 anzsrc-for:06
16 anzsrc-for:0604
17 schema:author N1a426fcc880f43e5a4bf03204df9e7bd
18 schema:citation sg:pub.10.1038/ng.3034
19 sg:pub.10.1038/ng1702
20 sg:pub.10.1186/1297-9686-39-2-181
21 sg:pub.10.1186/1297-9686-43-43
22 sg:pub.10.1186/1471-2156-10-19
23 sg:pub.10.1186/1471-2156-15-8
24 sg:pub.10.1186/1471-2164-9-187
25 sg:pub.10.1186/gb-2009-10-4-r42
26 https://app.dimensions.ai/details/publication/pub.1077297430
27 https://doi.org/10.1016/j.ajhg.2009.01.005
28 https://doi.org/10.1093/bioinformatics/bth457
29 https://doi.org/10.1093/bioinformatics/btp324
30 https://doi.org/10.1093/bioinformatics/btp352
31 https://doi.org/10.1093/bioinformatics/btq330
32 https://doi.org/10.1093/nar/29.1.308
33 https://doi.org/10.1093/nar/gks1150
34 https://doi.org/10.1101/gr.078212.108
35 https://doi.org/10.1101/gr.107524.110
36 https://doi.org/10.1111/j.1365-2052.2010.02064.x
37 https://doi.org/10.1146/annurev.genom.7.080505.115623
38 https://doi.org/10.1371/journal.pgen.1000529
39 https://doi.org/10.1371/journal.pone.0065550
40 https://doi.org/10.1371/journal.pone.0082909
41 https://doi.org/10.3168/jds.2008-1104
42 https://doi.org/10.3168/jds.2011-4624
43 https://doi.org/10.3168/jds.2012-5379
44 https://doi.org/10.3168/jds.s0022-0302(05)72861-7
45 schema:datePublished 2014-12
46 schema:datePublishedReg 2014-12-01
47 schema:description BACKGROUND: Female fertility is important for the maintenance of the production in a dairy cattle herd. Two QTL regions on BTA04 and on BTA13 previously detected in Nordic Holstein (NH) and validated in the Danish Jersey (DJ) and Nordic Red (NR) were investigated further in the present study to further refine the QTL locations. Refined QTL regions were imputed to the full sequence data. The genes in the regions were then studied to ascertain their possible effect on fertility traits. RESULTS: BTA04 was screened for number of inseminations (AIS), 56-day non-return rate (NRR), days from first to last insemination (IFL), and the interval from calving to first insemination (ICF) in the range of 38,257,758 to 40,890,784 bp, whereas BTA13 was screened for ICF only in the range from 21,236,959 to 46,150,079 with the HD bovine SNP array for NH, DJ and NR. No markers in the DJ and NR breeds reached significance. By analyzing imputed sequence data the QTL position on BTA04 was narrowed down to two regions in the NH. In these two regions a total of 9 genes were identified. BTA13 was analyzed using sequence data for the NH breed. The highest -log10(P-value) was 19.41 at 33,903,159 bp. Two regions were identified: Region 1: 33,900,143-33,908,994 bp and Region 2: 34,051,815-34,056,728 bp. SNPs within and between these two regions were annotated as intergenic. CONCLUSION: Screening BTA04 and BTA13 for female fertility traits in NH, NR and DJ suggested that the QTL for female fertility were specific for NH. A missense mutation in CD36 showed the strongest association with fertility traits on BTA04. The annotated SNPs on BTA13 were all intergenic variants. It is possible that BTA13 at this stage is poorly annotated such that the associated polymorphisms are located in as-yet undiscovered genes. Fertility traits are complex traits as many different biological and physiological factors determine whether a cow is fertile. Therefore it is not expected that there is a simple explanation with an obvious candidate gene but it is more likely a network of genes and intragenic variants that explain the variation of these traits.
48 schema:genre research_article
49 schema:inLanguage en
50 schema:isAccessibleForFree true
51 schema:isPartOf N149ed7bcffde407396871e0d048a24b0
52 Nf6767891fba6417fa3ad1e63c8f1a8d1
53 sg:journal.1023790
54 schema:name Fine mapping QTL for female fertility on BTA04 and BTA13 in dairy cattle using HD SNP and sequence data
55 schema:pagination 790
56 schema:productId N3dd074e0cbf44cb7a0d8ee73e17fc0f8
57 N4f650440d7d243a9bf9c3b17017018a0
58 N72aea200a5734529bd07972519d02f79
59 N7df30e0ad11646fabd675eac352ad18c
60 Nd3789cf4428e465d8c8b36092b37e1ce
61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029771054
62 https://doi.org/10.1186/1471-2164-15-790
63 schema:sdDatePublished 2019-04-10T22:39
64 schema:sdLicense https://scigraph.springernature.com/explorer/license/
65 schema:sdPublisher N5ae430c6191542918b390d6c284b3e58
66 schema:url http://link.springer.com/10.1186%2F1471-2164-15-790
67 sgo:license sg:explorer/license/
68 sgo:sdDataset articles
69 rdf:type schema:ScholarlyArticle
70 N0d2d9e42805c41ed8913b24b2985e455 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
71 schema:name Fertility
72 rdf:type schema:DefinedTerm
73 N149ed7bcffde407396871e0d048a24b0 schema:issueNumber 1
74 rdf:type schema:PublicationIssue
75 N17e9247f578c401bbfd3ca422e172173 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
76 schema:name Genomics
77 rdf:type schema:DefinedTerm
78 N1a426fcc880f43e5a4bf03204df9e7bd rdf:first sg:person.01203034260.48
79 rdf:rest Nfbf70d2e381c4995b958b0b5d9f2461d
80 N1acdd331388a4bbf96b71945b4f50fd2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
81 schema:name Polymorphism, Single Nucleotide
82 rdf:type schema:DefinedTerm
83 N1bd9495474ab42e6ab6c5ad3bbbbe4f5 rdf:first sg:person.0655324301.37
84 rdf:rest Na30a22b3fa3943a983539a497b74944f
85 N231acb50e6c8443bac6c4a5124cb0788 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
86 schema:name Female
87 rdf:type schema:DefinedTerm
88 N3dd074e0cbf44cb7a0d8ee73e17fc0f8 schema:name pubmed_id
89 schema:value 25216717
90 rdf:type schema:PropertyValue
91 N4dec138e8dee4d6db43934360cdb455e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
92 schema:name Chromosome Mapping
93 rdf:type schema:DefinedTerm
94 N4f650440d7d243a9bf9c3b17017018a0 schema:name dimensions_id
95 schema:value pub.1029771054
96 rdf:type schema:PropertyValue
97 N5ae430c6191542918b390d6c284b3e58 schema:name Springer Nature - SN SciGraph project
98 rdf:type schema:Organization
99 N5f8c4409522d4647801f6dfe05815da9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
100 schema:name Cattle
101 rdf:type schema:DefinedTerm
102 N60033de75a3b44049bd7d993d2cabb57 rdf:first sg:person.0757045612.02
103 rdf:rest N1bd9495474ab42e6ab6c5ad3bbbbe4f5
104 N72aea200a5734529bd07972519d02f79 schema:name nlm_unique_id
105 schema:value 100965258
106 rdf:type schema:PropertyValue
107 N7a37f83c693a4d1ba1cb99454c48392a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
108 schema:name Animals
109 rdf:type schema:DefinedTerm
110 N7df30e0ad11646fabd675eac352ad18c schema:name doi
111 schema:value 10.1186/1471-2164-15-790
112 rdf:type schema:PropertyValue
113 N847714de7a3845799da5cb8731d5ee7e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Genome-Wide Association Study
115 rdf:type schema:DefinedTerm
116 N985419758a314d88b03df2b9045ebb32 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
117 schema:name Genetic Markers
118 rdf:type schema:DefinedTerm
119 Na30a22b3fa3943a983539a497b74944f rdf:first sg:person.0650267300.38
120 rdf:rest Nf64b3317abb441dfbf34be75db09f74f
121 Na36d27fc63034ae59f6dbae0cf7afad3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
122 schema:name Quantitative Trait Loci
123 rdf:type schema:DefinedTerm
124 Ncb3670fed56b40b19b4b36e0eb78f3b4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
125 schema:name Linkage Disequilibrium
126 rdf:type schema:DefinedTerm
127 Nd3789cf4428e465d8c8b36092b37e1ce schema:name readcube_id
128 schema:value 8dd2f78834e307d90209ef4523ff3bff39cbe97aeb77760664a4d13b3d4a0602
129 rdf:type schema:PropertyValue
130 Nd561046340fb4b15b75903a498a7dff5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Phenotype
132 rdf:type schema:DefinedTerm
133 Ne7a9eac18bb84824be9755851dc58c1c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Computational Biology
135 rdf:type schema:DefinedTerm
136 Nf64b3317abb441dfbf34be75db09f74f rdf:first sg:person.0740177106.57
137 rdf:rest rdf:nil
138 Nf6767891fba6417fa3ad1e63c8f1a8d1 schema:volumeNumber 15
139 rdf:type schema:PublicationVolume
140 Nfbf70d2e381c4995b958b0b5d9f2461d rdf:first sg:person.0727046246.31
141 rdf:rest N60033de75a3b44049bd7d993d2cabb57
142 Nfe8d32c43f284151a2ba92dce1303725 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name High-Throughput Nucleotide Sequencing
144 rdf:type schema:DefinedTerm
145 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
146 schema:name Biological Sciences
147 rdf:type schema:DefinedTerm
148 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
149 schema:name Genetics
150 rdf:type schema:DefinedTerm
151 sg:journal.1023790 schema:issn 1471-2164
152 schema:name BMC Genomics
153 rdf:type schema:Periodical
154 sg:person.01203034260.48 schema:affiliation https://www.grid.ac/institutes/grid.6341.0
155 schema:familyName Höglund
156 schema:givenName Johanna K
157 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01203034260.48
158 rdf:type schema:Person
159 sg:person.0650267300.38 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
160 schema:familyName Buitenhuis
161 schema:givenName Bart
162 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0650267300.38
163 rdf:type schema:Person
164 sg:person.0655324301.37 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
165 schema:familyName Guldbrandtsen
166 schema:givenName Bernt
167 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0655324301.37
168 rdf:type schema:Person
169 sg:person.0727046246.31 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
170 schema:familyName Sahana
171 schema:givenName Goutam
172 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0727046246.31
173 rdf:type schema:Person
174 sg:person.0740177106.57 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
175 schema:familyName Lund
176 schema:givenName Mogens S
177 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740177106.57
178 rdf:type schema:Person
179 sg:person.0757045612.02 schema:affiliation https://www.grid.ac/institutes/grid.7048.b
180 schema:familyName Brøndum
181 schema:givenName Rasmus Froberg
182 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757045612.02
183 rdf:type schema:Person
184 sg:pub.10.1038/ng.3034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028025360
185 https://doi.org/10.1038/ng.3034
186 rdf:type schema:CreativeWork
187 sg:pub.10.1038/ng1702 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035781360
188 https://doi.org/10.1038/ng1702
189 rdf:type schema:CreativeWork
190 sg:pub.10.1186/1297-9686-39-2-181 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046658059
191 https://doi.org/10.1186/1297-9686-39-2-181
192 rdf:type schema:CreativeWork
193 sg:pub.10.1186/1297-9686-43-43 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030941918
194 https://doi.org/10.1186/1297-9686-43-43
195 rdf:type schema:CreativeWork
196 sg:pub.10.1186/1471-2156-10-19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039058389
197 https://doi.org/10.1186/1471-2156-10-19
198 rdf:type schema:CreativeWork
199 sg:pub.10.1186/1471-2156-15-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004306245
200 https://doi.org/10.1186/1471-2156-15-8
201 rdf:type schema:CreativeWork
202 sg:pub.10.1186/1471-2164-9-187 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052463226
203 https://doi.org/10.1186/1471-2164-9-187
204 rdf:type schema:CreativeWork
205 sg:pub.10.1186/gb-2009-10-4-r42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024097093
206 https://doi.org/10.1186/gb-2009-10-4-r42
207 rdf:type schema:CreativeWork
208 https://app.dimensions.ai/details/publication/pub.1077297430 schema:CreativeWork
209 https://doi.org/10.1016/j.ajhg.2009.01.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033548087
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1093/bioinformatics/bth457 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008081196
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1093/bioinformatics/btp324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038266369
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1093/bioinformatics/btp352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023014918
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1093/bioinformatics/btq330 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047117020
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1093/nar/29.1.308 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005817660
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1093/nar/gks1150 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051654714
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1101/gr.078212.108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047542880
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1101/gr.107524.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032096953
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1111/j.1365-2052.2010.02064.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1015623410
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1146/annurev.genom.7.080505.115623 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047886041
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1371/journal.pgen.1000529 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043446290
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1371/journal.pone.0065550 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002738930
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1371/journal.pone.0082909 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023839045
236 rdf:type schema:CreativeWork
237 https://doi.org/10.3168/jds.2008-1104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077890248
238 rdf:type schema:CreativeWork
239 https://doi.org/10.3168/jds.2011-4624 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031598086
240 rdf:type schema:CreativeWork
241 https://doi.org/10.3168/jds.2012-5379 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035908887
242 rdf:type schema:CreativeWork
243 https://doi.org/10.3168/jds.s0022-0302(05)72861-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077038452
244 rdf:type schema:CreativeWork
245 https://www.grid.ac/institutes/grid.6341.0 schema:alternateName Swedish University of Agricultural Sciences
246 schema:name Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, P.O. Box 7070, 750 07, Uppsala, Sweden
247 Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, P.O. Box 50, DK-8830, Tjele, Denmark
248 rdf:type schema:Organization
249 https://www.grid.ac/institutes/grid.7048.b schema:alternateName Aarhus University
250 schema:name Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, P.O. Box 50, DK-8830, Tjele, Denmark
251 rdf:type schema:Organization
 




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


...