Whole mitochondrial genome sequencing of domestic horses reveals incorporation of extensive wild horse diversity during domestication View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-12

AUTHORS

Sebastian Lippold, Nicholas J Matzke, Monika Reissmann, Michael Hofreiter

ABSTRACT

BACKGROUND: DNA target enrichment by micro-array capture combined with high throughput sequencing technologies provides the possibility to obtain large amounts of sequence data (e.g. whole mitochondrial DNA genomes) from multiple individuals at relatively low costs. Previously, whole mitochondrial genome data for domestic horses (Equus caballus) were limited to only a few specimens and only short parts of the mtDNA genome (especially the hypervariable region) were investigated for larger sample sets. RESULTS: In this study we investigated whole mitochondrial genomes of 59 domestic horses from 44 breeds and a single Przewalski horse (Equus przewalski) using a recently described multiplex micro-array capture approach. We found 473 variable positions within the domestic horses, 292 of which are parsimony-informative, providing a well resolved phylogenetic tree. Our divergence time estimate suggests that the mitochondrial genomes of modern horse breeds shared a common ancestor around 93,000 years ago and no later than 38,000 years ago. A Bayesian skyline plot (BSP) reveals a significant population expansion beginning 6,000-8,000 years ago with an ongoing exponential growth until the present, similar to other domestic animal species. Our data further suggest that a large sample of wild horse diversity was incorporated into the domestic population; specifically, at least 46 of the mtDNA lineages observed in domestic horses (73%) already existed before the beginning of domestication about 5,000 years ago. CONCLUSIONS: Our study provides a window into the maternal origins of extant domestic horses and confirms that modern domestic breeds present a wide sample of the mtDNA diversity found in ancestral, now extinct, wild horse populations. The data obtained allow us to detect a population expansion event coinciding with the beginning of domestication and to estimate both the minimum number of female horses incorporated into the domestic gene pool and the time depth of the domestic horse mtDNA gene pool. More... »

PAGES

328

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2148-11-328

DOI

http://dx.doi.org/10.1186/1471-2148-11-328

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033683727

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22082251


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": "Animals, Wild", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Bayes Theorem", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Biological Evolution", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "DNA, Mitochondrial", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genome, Mitochondrial", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Horses", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mitochondria", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phylogeny", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Max Planck Institute for Evolutionary Anthropology", 
          "id": "https://www.grid.ac/institutes/grid.419518.0", 
          "name": [
            "Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103, Leipzig, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lippold", 
        "givenName": "Sebastian", 
        "id": "sg:person.01130714564.72", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01130714564.72"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, Berkeley", 
          "id": "https://www.grid.ac/institutes/grid.47840.3f", 
          "name": [
            "Center for Theoretical Evolutionary Genomics, Department of Integrative Biology, University of California, Berkeley, 4151 Valley Life Sciences Building, Berkeley, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Matzke", 
        "givenName": "Nicholas J", 
        "id": "sg:person.0614066761.88", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0614066761.88"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Humboldt University of Berlin", 
          "id": "https://www.grid.ac/institutes/grid.7468.d", 
          "name": [
            "Department for Crop and Animal Sciences, Humboldt University Berlin, Invalidenstr. 42, 10115, Berlin, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Reissmann", 
        "givenName": "Monika", 
        "id": "sg:person.01354770637.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01354770637.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of York", 
          "id": "https://www.grid.ac/institutes/grid.5685.e", 
          "name": [
            "Department of Biology, University of York, Wentworth Way, YO10 5DD, Heslington, York, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hofreiter", 
        "givenName": "Michael", 
        "id": "sg:person.01046665765.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01046665765.30"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.tig.2005.11.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000603526"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.livsci.2008.03.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000659483"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/0-387-27733-1_7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001198229", 
          "https://doi.org/10.1007/0-387-27733-1_7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/molbev/msp195", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003955813"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/molbev/msp195", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003955813"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ympev.2003.12.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007642494"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btm404", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007683223"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1046/j.1365-2052.1999.00419.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009367019"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nprot.2009.68", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009828502", 
          "https://doi.org/10.1038/nprot.2009.68"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nprot.2009.68", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009828502", 
          "https://doi.org/10.1038/nprot.2009.68"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2052.2006.01495.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010331437"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2148-7-214", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010584451", 
          "https://doi.org/10.1186/1471-2148-7-214"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1096-0031.1994.tb00179.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012818607"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1096-0031.1994.tb00179.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012818607"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jas.2008.11.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012919043"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1172750", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014099293"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2052.2009.01950.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016637125"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2052.2009.01950.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016637125"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/19.2.301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018196271"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jqs.1509", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018448516"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0903672106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019605188"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-294x.2009.04430.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020079883"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-294x.2009.04430.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020079883"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/molbev/msm088", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020427894"
        ], 
        "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/10.1016/0378-1119(94)90713-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023535700"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0378-1119(94)90713-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023535700"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1673-8527(07)60081-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023665888"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.152330099", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024379613"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0802315105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024667673"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.livprodsci.2004.12.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024908655"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pbio.0050207", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029205478"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/14.9.817", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029580565"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btg180", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036252078"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.291.5503.474", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036278426"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cub.2008.01.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036657218"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btp324", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038266369"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jhered/esi116", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038331152"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/molbev/msi103", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039084795"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.102954.109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040311092"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2009-10-8-r83", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041308110", 
          "https://doi.org/10.1186/gb-2009-10-8-r83"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.095760.109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041449671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00170671", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044244705", 
          "https://doi.org/10.1007/bf00170671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00170671", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044244705", 
          "https://doi.org/10.1007/bf00170671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature08837", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045898407", 
          "https://doi.org/10.1038/nature08837"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature08837", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045898407", 
          "https://doi.org/10.1038/nature08837"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1096-0031.2008.00217.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048321372"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0005753", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051639765"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10635150490522304", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051847290"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1011559200897", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052697493", 
          "https://doi.org/10.1023/a:1011559200897"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1098/rsbl.2007.0146", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052873231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.1995.10476572", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058304855"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10020070708541034", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058355643"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10635150390235520", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058369386"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10635150802429642", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058369815"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/pdb.prot5448", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060411299"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1168594", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062459264"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1168594", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062459264"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1178158", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062460476"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2408870", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069917845"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2412407", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069920846"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2992406", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1070161995"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/oxfordjournals.molbev.a040258", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082376727"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/aab-47-517-2004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092931539"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011-12", 
    "datePublishedReg": "2011-12-01", 
    "description": "BACKGROUND: DNA target enrichment by micro-array capture combined with high throughput sequencing technologies provides the possibility to obtain large amounts of sequence data (e.g. whole mitochondrial DNA genomes) from multiple individuals at relatively low costs. Previously, whole mitochondrial genome data for domestic horses (Equus caballus) were limited to only a few specimens and only short parts of the mtDNA genome (especially the hypervariable region) were investigated for larger sample sets.\nRESULTS: In this study we investigated whole mitochondrial genomes of 59 domestic horses from 44 breeds and a single Przewalski horse (Equus przewalski) using a recently described multiplex micro-array capture approach. We found 473 variable positions within the domestic horses, 292 of which are parsimony-informative, providing a well resolved phylogenetic tree. Our divergence time estimate suggests that the mitochondrial genomes of modern horse breeds shared a common ancestor around 93,000 years ago and no later than 38,000 years ago. A Bayesian skyline plot (BSP) reveals a significant population expansion beginning 6,000-8,000 years ago with an ongoing exponential growth until the present, similar to other domestic animal species. Our data further suggest that a large sample of wild horse diversity was incorporated into the domestic population; specifically, at least 46 of the mtDNA lineages observed in domestic horses (73%) already existed before the beginning of domestication about 5,000 years ago.\nCONCLUSIONS: Our study provides a window into the maternal origins of extant domestic horses and confirms that modern domestic breeds present a wide sample of the mtDNA diversity found in ancestral, now extinct, wild horse populations. The data obtained allow us to detect a population expansion event coinciding with the beginning of domestication and to estimate both the minimum number of female horses incorporated into the domestic gene pool and the time depth of the domestic horse mtDNA gene pool.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/1471-2148-11-328", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2518202", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1024249", 
        "issn": [
          "1471-2148"
        ], 
        "name": "BMC Evolutionary Biology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "11"
      }
    ], 
    "name": "Whole mitochondrial genome sequencing of domestic horses reveals incorporation of extensive wild horse diversity during domestication", 
    "pagination": "328", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "a0756c3b9da43cc29ed12ff1dc31d7ac3da9e00607ae41b6646c8f879464e4cc"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "22082251"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100966975"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1471-2148-11-328"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1033683727"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1471-2148-11-328", 
      "https://app.dimensions.ai/details/publication/pub.1033683727"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T18:19", 
    "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_8675_00000506.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2F1471-2148-11-328"
  }
]
 

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.10.1186/1471-2148-11-328'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2148-11-328'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2148-11-328'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2148-11-328'


 

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

312 TRIPLES      21 PREDICATES      94 URIs      31 LITERALS      19 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1471-2148-11-328 schema:about N3663e7c3a3fe4128932c92dd35cdbc2c
2 N43ae704be2a94d429f83074d7d1102ee
3 N44dc19b6958f4db3a679dba8b1c33930
4 N7780a87795eb42bf84dcb4142e09b665
5 N7be5e0e6ac794ef39b1de3a41abbb82d
6 N93eafe43c7af4a59a8ac81000ae9e516
7 Na29d4d5ac496487699718c1673355ac6
8 Nb97c7f4200b943a0bc2fb032249a5b97
9 Nbf8c0ef60c8049e4b542b467f581bb84
10 Nd9ed0b7350cb45feb75ba6f54b4fb5d2
11 anzsrc-for:06
12 anzsrc-for:0604
13 schema:author Nb33ece2242a24126b41eaf81cc5e8399
14 schema:citation sg:pub.10.1007/0-387-27733-1_7
15 sg:pub.10.1007/bf00170671
16 sg:pub.10.1023/a:1011559200897
17 sg:pub.10.1038/nature08837
18 sg:pub.10.1038/nprot.2009.68
19 sg:pub.10.1186/1471-2148-7-214
20 sg:pub.10.1186/gb-2009-10-8-r83
21 https://doi.org/10.1002/jqs.1509
22 https://doi.org/10.1016/0378-1119(94)90713-7
23 https://doi.org/10.1016/j.cub.2008.01.019
24 https://doi.org/10.1016/j.jas.2008.11.006
25 https://doi.org/10.1016/j.livprodsci.2004.12.004
26 https://doi.org/10.1016/j.livsci.2008.03.002
27 https://doi.org/10.1016/j.tig.2005.11.006
28 https://doi.org/10.1016/j.ympev.2003.12.006
29 https://doi.org/10.1016/s1673-8527(07)60081-2
30 https://doi.org/10.1046/j.1365-2052.1999.00419.x
31 https://doi.org/10.1073/pnas.0802315105
32 https://doi.org/10.1073/pnas.0903672106
33 https://doi.org/10.1073/pnas.152330099
34 https://doi.org/10.1080/01621459.1995.10476572
35 https://doi.org/10.1080/10020070708541034
36 https://doi.org/10.1080/10635150390235520
37 https://doi.org/10.1080/10635150490522304
38 https://doi.org/10.1080/10635150802429642
39 https://doi.org/10.1093/bioinformatics/14.9.817
40 https://doi.org/10.1093/bioinformatics/19.2.301
41 https://doi.org/10.1093/bioinformatics/btg180
42 https://doi.org/10.1093/bioinformatics/btm404
43 https://doi.org/10.1093/bioinformatics/btp324
44 https://doi.org/10.1093/bioinformatics/btp352
45 https://doi.org/10.1093/jhered/esi116
46 https://doi.org/10.1093/molbev/msi103
47 https://doi.org/10.1093/molbev/msm088
48 https://doi.org/10.1093/molbev/msp195
49 https://doi.org/10.1093/oxfordjournals.molbev.a040258
50 https://doi.org/10.1098/rsbl.2007.0146
51 https://doi.org/10.1101/gr.095760.109
52 https://doi.org/10.1101/gr.102954.109
53 https://doi.org/10.1101/pdb.prot5448
54 https://doi.org/10.1111/j.1096-0031.1994.tb00179.x
55 https://doi.org/10.1111/j.1096-0031.2008.00217.x
56 https://doi.org/10.1111/j.1365-2052.2006.01495.x
57 https://doi.org/10.1111/j.1365-2052.2009.01950.x
58 https://doi.org/10.1111/j.1365-294x.2009.04430.x
59 https://doi.org/10.1126/science.1168594
60 https://doi.org/10.1126/science.1172750
61 https://doi.org/10.1126/science.1178158
62 https://doi.org/10.1126/science.291.5503.474
63 https://doi.org/10.1371/journal.pbio.0050207
64 https://doi.org/10.1371/journal.pone.0005753
65 https://doi.org/10.2307/2408870
66 https://doi.org/10.2307/2412407
67 https://doi.org/10.2307/2992406
68 https://doi.org/10.5194/aab-47-517-2004
69 schema:datePublished 2011-12
70 schema:datePublishedReg 2011-12-01
71 schema:description BACKGROUND: DNA target enrichment by micro-array capture combined with high throughput sequencing technologies provides the possibility to obtain large amounts of sequence data (e.g. whole mitochondrial DNA genomes) from multiple individuals at relatively low costs. Previously, whole mitochondrial genome data for domestic horses (Equus caballus) were limited to only a few specimens and only short parts of the mtDNA genome (especially the hypervariable region) were investigated for larger sample sets. RESULTS: In this study we investigated whole mitochondrial genomes of 59 domestic horses from 44 breeds and a single Przewalski horse (Equus przewalski) using a recently described multiplex micro-array capture approach. We found 473 variable positions within the domestic horses, 292 of which are parsimony-informative, providing a well resolved phylogenetic tree. Our divergence time estimate suggests that the mitochondrial genomes of modern horse breeds shared a common ancestor around 93,000 years ago and no later than 38,000 years ago. A Bayesian skyline plot (BSP) reveals a significant population expansion beginning 6,000-8,000 years ago with an ongoing exponential growth until the present, similar to other domestic animal species. Our data further suggest that a large sample of wild horse diversity was incorporated into the domestic population; specifically, at least 46 of the mtDNA lineages observed in domestic horses (73%) already existed before the beginning of domestication about 5,000 years ago. CONCLUSIONS: Our study provides a window into the maternal origins of extant domestic horses and confirms that modern domestic breeds present a wide sample of the mtDNA diversity found in ancestral, now extinct, wild horse populations. The data obtained allow us to detect a population expansion event coinciding with the beginning of domestication and to estimate both the minimum number of female horses incorporated into the domestic gene pool and the time depth of the domestic horse mtDNA gene pool.
72 schema:genre research_article
73 schema:inLanguage en
74 schema:isAccessibleForFree true
75 schema:isPartOf N7dd3e5476b694b0d9619b6cfd1aa35a5
76 N8f6b03fb36234c568c5c9c0386e514a0
77 sg:journal.1024249
78 schema:name Whole mitochondrial genome sequencing of domestic horses reveals incorporation of extensive wild horse diversity during domestication
79 schema:pagination 328
80 schema:productId N0c5168cf20e4438b8d04771bd69cfa97
81 N5c6a0b15184c4095ad0c2cc996d4640f
82 N5d0b39425ec3427dac17b5a606d9fc5b
83 Na958623860fc43e0b6c150952212395b
84 Ne95139b18a7e46d5a89b626c353db25a
85 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033683727
86 https://doi.org/10.1186/1471-2148-11-328
87 schema:sdDatePublished 2019-04-10T18:19
88 schema:sdLicense https://scigraph.springernature.com/explorer/license/
89 schema:sdPublisher Neaa8028c20ac4181b396e02d4c56370f
90 schema:url http://link.springer.com/10.1186%2F1471-2148-11-328
91 sgo:license sg:explorer/license/
92 sgo:sdDataset articles
93 rdf:type schema:ScholarlyArticle
94 N0c5168cf20e4438b8d04771bd69cfa97 schema:name dimensions_id
95 schema:value pub.1033683727
96 rdf:type schema:PropertyValue
97 N3663e7c3a3fe4128932c92dd35cdbc2c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
98 schema:name Animals, Wild
99 rdf:type schema:DefinedTerm
100 N36837296dff34590a48fc7bb0849b3b1 rdf:first sg:person.01354770637.37
101 rdf:rest Nbdf97459323f4f6b99f6c3d48ff08211
102 N43ae704be2a94d429f83074d7d1102ee schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
103 schema:name Phylogeny
104 rdf:type schema:DefinedTerm
105 N44dc19b6958f4db3a679dba8b1c33930 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
106 schema:name DNA, Mitochondrial
107 rdf:type schema:DefinedTerm
108 N5c6a0b15184c4095ad0c2cc996d4640f schema:name readcube_id
109 schema:value a0756c3b9da43cc29ed12ff1dc31d7ac3da9e00607ae41b6646c8f879464e4cc
110 rdf:type schema:PropertyValue
111 N5d0b39425ec3427dac17b5a606d9fc5b schema:name nlm_unique_id
112 schema:value 100966975
113 rdf:type schema:PropertyValue
114 N7780a87795eb42bf84dcb4142e09b665 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Animals
116 rdf:type schema:DefinedTerm
117 N7be5e0e6ac794ef39b1de3a41abbb82d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
118 schema:name Mitochondria
119 rdf:type schema:DefinedTerm
120 N7dd3e5476b694b0d9619b6cfd1aa35a5 schema:issueNumber 1
121 rdf:type schema:PublicationIssue
122 N82c2c8742b934e08b9eee1bdb54a3817 rdf:first sg:person.0614066761.88
123 rdf:rest N36837296dff34590a48fc7bb0849b3b1
124 N8f6b03fb36234c568c5c9c0386e514a0 schema:volumeNumber 11
125 rdf:type schema:PublicationVolume
126 N93eafe43c7af4a59a8ac81000ae9e516 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Genome, Mitochondrial
128 rdf:type schema:DefinedTerm
129 Na29d4d5ac496487699718c1673355ac6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Biological Evolution
131 rdf:type schema:DefinedTerm
132 Na958623860fc43e0b6c150952212395b schema:name doi
133 schema:value 10.1186/1471-2148-11-328
134 rdf:type schema:PropertyValue
135 Nb33ece2242a24126b41eaf81cc5e8399 rdf:first sg:person.01130714564.72
136 rdf:rest N82c2c8742b934e08b9eee1bdb54a3817
137 Nb97c7f4200b943a0bc2fb032249a5b97 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
138 schema:name Horses
139 rdf:type schema:DefinedTerm
140 Nbdf97459323f4f6b99f6c3d48ff08211 rdf:first sg:person.01046665765.30
141 rdf:rest rdf:nil
142 Nbf8c0ef60c8049e4b542b467f581bb84 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Female
144 rdf:type schema:DefinedTerm
145 Nd9ed0b7350cb45feb75ba6f54b4fb5d2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
146 schema:name Bayes Theorem
147 rdf:type schema:DefinedTerm
148 Ne95139b18a7e46d5a89b626c353db25a schema:name pubmed_id
149 schema:value 22082251
150 rdf:type schema:PropertyValue
151 Neaa8028c20ac4181b396e02d4c56370f schema:name Springer Nature - SN SciGraph project
152 rdf:type schema:Organization
153 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
154 schema:name Biological Sciences
155 rdf:type schema:DefinedTerm
156 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
157 schema:name Genetics
158 rdf:type schema:DefinedTerm
159 sg:grant.2518202 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2148-11-328
160 rdf:type schema:MonetaryGrant
161 sg:journal.1024249 schema:issn 1471-2148
162 schema:name BMC Evolutionary Biology
163 rdf:type schema:Periodical
164 sg:person.01046665765.30 schema:affiliation https://www.grid.ac/institutes/grid.5685.e
165 schema:familyName Hofreiter
166 schema:givenName Michael
167 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01046665765.30
168 rdf:type schema:Person
169 sg:person.01130714564.72 schema:affiliation https://www.grid.ac/institutes/grid.419518.0
170 schema:familyName Lippold
171 schema:givenName Sebastian
172 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01130714564.72
173 rdf:type schema:Person
174 sg:person.01354770637.37 schema:affiliation https://www.grid.ac/institutes/grid.7468.d
175 schema:familyName Reissmann
176 schema:givenName Monika
177 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01354770637.37
178 rdf:type schema:Person
179 sg:person.0614066761.88 schema:affiliation https://www.grid.ac/institutes/grid.47840.3f
180 schema:familyName Matzke
181 schema:givenName Nicholas J
182 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0614066761.88
183 rdf:type schema:Person
184 sg:pub.10.1007/0-387-27733-1_7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001198229
185 https://doi.org/10.1007/0-387-27733-1_7
186 rdf:type schema:CreativeWork
187 sg:pub.10.1007/bf00170671 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044244705
188 https://doi.org/10.1007/bf00170671
189 rdf:type schema:CreativeWork
190 sg:pub.10.1023/a:1011559200897 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052697493
191 https://doi.org/10.1023/a:1011559200897
192 rdf:type schema:CreativeWork
193 sg:pub.10.1038/nature08837 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045898407
194 https://doi.org/10.1038/nature08837
195 rdf:type schema:CreativeWork
196 sg:pub.10.1038/nprot.2009.68 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009828502
197 https://doi.org/10.1038/nprot.2009.68
198 rdf:type schema:CreativeWork
199 sg:pub.10.1186/1471-2148-7-214 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010584451
200 https://doi.org/10.1186/1471-2148-7-214
201 rdf:type schema:CreativeWork
202 sg:pub.10.1186/gb-2009-10-8-r83 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041308110
203 https://doi.org/10.1186/gb-2009-10-8-r83
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1002/jqs.1509 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018448516
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1016/0378-1119(94)90713-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023535700
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1016/j.cub.2008.01.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036657218
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1016/j.jas.2008.11.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012919043
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1016/j.livprodsci.2004.12.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024908655
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1016/j.livsci.2008.03.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000659483
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1016/j.tig.2005.11.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000603526
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1016/j.ympev.2003.12.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007642494
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1016/s1673-8527(07)60081-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023665888
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1046/j.1365-2052.1999.00419.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1009367019
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1073/pnas.0802315105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024667673
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1073/pnas.0903672106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019605188
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1073/pnas.152330099 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024379613
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1080/01621459.1995.10476572 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058304855
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1080/10020070708541034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058355643
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1080/10635150390235520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058369386
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1080/10635150490522304 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051847290
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1080/10635150802429642 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058369815
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1093/bioinformatics/14.9.817 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029580565
242 rdf:type schema:CreativeWork
243 https://doi.org/10.1093/bioinformatics/19.2.301 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018196271
244 rdf:type schema:CreativeWork
245 https://doi.org/10.1093/bioinformatics/btg180 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036252078
246 rdf:type schema:CreativeWork
247 https://doi.org/10.1093/bioinformatics/btm404 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007683223
248 rdf:type schema:CreativeWork
249 https://doi.org/10.1093/bioinformatics/btp324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038266369
250 rdf:type schema:CreativeWork
251 https://doi.org/10.1093/bioinformatics/btp352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023014918
252 rdf:type schema:CreativeWork
253 https://doi.org/10.1093/jhered/esi116 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038331152
254 rdf:type schema:CreativeWork
255 https://doi.org/10.1093/molbev/msi103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039084795
256 rdf:type schema:CreativeWork
257 https://doi.org/10.1093/molbev/msm088 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020427894
258 rdf:type schema:CreativeWork
259 https://doi.org/10.1093/molbev/msp195 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003955813
260 rdf:type schema:CreativeWork
261 https://doi.org/10.1093/oxfordjournals.molbev.a040258 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082376727
262 rdf:type schema:CreativeWork
263 https://doi.org/10.1098/rsbl.2007.0146 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052873231
264 rdf:type schema:CreativeWork
265 https://doi.org/10.1101/gr.095760.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041449671
266 rdf:type schema:CreativeWork
267 https://doi.org/10.1101/gr.102954.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040311092
268 rdf:type schema:CreativeWork
269 https://doi.org/10.1101/pdb.prot5448 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060411299
270 rdf:type schema:CreativeWork
271 https://doi.org/10.1111/j.1096-0031.1994.tb00179.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1012818607
272 rdf:type schema:CreativeWork
273 https://doi.org/10.1111/j.1096-0031.2008.00217.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1048321372
274 rdf:type schema:CreativeWork
275 https://doi.org/10.1111/j.1365-2052.2006.01495.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1010331437
276 rdf:type schema:CreativeWork
277 https://doi.org/10.1111/j.1365-2052.2009.01950.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1016637125
278 rdf:type schema:CreativeWork
279 https://doi.org/10.1111/j.1365-294x.2009.04430.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1020079883
280 rdf:type schema:CreativeWork
281 https://doi.org/10.1126/science.1168594 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062459264
282 rdf:type schema:CreativeWork
283 https://doi.org/10.1126/science.1172750 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014099293
284 rdf:type schema:CreativeWork
285 https://doi.org/10.1126/science.1178158 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062460476
286 rdf:type schema:CreativeWork
287 https://doi.org/10.1126/science.291.5503.474 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036278426
288 rdf:type schema:CreativeWork
289 https://doi.org/10.1371/journal.pbio.0050207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029205478
290 rdf:type schema:CreativeWork
291 https://doi.org/10.1371/journal.pone.0005753 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051639765
292 rdf:type schema:CreativeWork
293 https://doi.org/10.2307/2408870 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069917845
294 rdf:type schema:CreativeWork
295 https://doi.org/10.2307/2412407 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069920846
296 rdf:type schema:CreativeWork
297 https://doi.org/10.2307/2992406 schema:sameAs https://app.dimensions.ai/details/publication/pub.1070161995
298 rdf:type schema:CreativeWork
299 https://doi.org/10.5194/aab-47-517-2004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092931539
300 rdf:type schema:CreativeWork
301 https://www.grid.ac/institutes/grid.419518.0 schema:alternateName Max Planck Institute for Evolutionary Anthropology
302 schema:name Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103, Leipzig, Germany
303 rdf:type schema:Organization
304 https://www.grid.ac/institutes/grid.47840.3f schema:alternateName University of California, Berkeley
305 schema:name Center for Theoretical Evolutionary Genomics, Department of Integrative Biology, University of California, Berkeley, 4151 Valley Life Sciences Building, Berkeley, CA, USA
306 rdf:type schema:Organization
307 https://www.grid.ac/institutes/grid.5685.e schema:alternateName University of York
308 schema:name Department of Biology, University of York, Wentworth Way, YO10 5DD, Heslington, York, UK
309 rdf:type schema:Organization
310 https://www.grid.ac/institutes/grid.7468.d schema:alternateName Humboldt University of Berlin
311 schema:name Department for Crop and Animal Sciences, Humboldt University Berlin, Invalidenstr. 42, 10115, Berlin, Germany
312 rdf:type schema:Organization
 




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


...