Ontology type: schema:ScholarlyArticle Open Access: True
2013-12
AUTHORSAnna Esteve-Codina, Yogesh Paudel, Luca Ferretti, Emanuele Raineri, Hendrik-Jan Megens, Luis Silió, María C Rodríguez, Martein AM Groenen, Sebastian E Ramos-Onsins, Miguel Pérez-Enciso
ABSTRACTBACKGROUND: In contrast to international pig breeds, the Iberian breed has not been admixed with Asian germplasm. This makes it an important model to study both domestication and relevance of Asian genes in the pig. Besides, Iberian pigs exhibit high meat quality as well as appetite and propensity to obesity. Here we provide a genome wide analysis of nucleotide and structural diversity in a reduced representation library from a pool (n=9 sows) and shotgun genomic sequence from a single sow of the highly inbred Guadyerbas strain. In the pool, we applied newly developed tools to account for the peculiarities of these data. RESULTS: A total of 254,106 SNPs in the pool (79.6 Mb covered) and 643,783 in the Guadyerbas sow (1.47 Gb covered) were called. The nucleotide diversity (1.31x10-3 per bp in autosomes) is very similar to that reported in wild boar. A much lower than expected diversity in the X chromosome was confirmed (1.79x10-4 per bp in the individual and 5.83x10-4 per bp in the pool). A strong (0.70) correlation between recombination and variability was observed, but not with gene density or GC content. Multicopy regions affected about 4% of annotated pig genes in their entirety, and 2% of the genes partially. Genes within the lowest variability windows comprised interferon genes and, in chromosome X, genes involved in behavior like HTR2C or MCEP2. A modified Hudson-Kreitman-Aguadé test for pools also indicated an accelerated evolution in genes involved in behavior, as well as in spermatogenesis and in lipid metabolism. CONCLUSIONS: This work illustrates the strength of current sequencing technologies to picture a comprehensive landscape of variability in livestock species, and to pinpoint regions containing genes potentially under selection. Among those genes, we report genes involved in behavior, including feeding behavior, and lipid metabolism. The pig X chromosome is an outlier in terms of nucleotide diversity, which suggests selective constraints. Our data further confirm the importance of structural variation in the species, including Iberian pigs, and allowed us to identify new paralogs for known gene families. More... »
PAGES148
http://scigraph.springernature.com/pub.10.1186/1471-2164-14-148
DOIhttp://dx.doi.org/10.1186/1471-2164-14-148
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1022388901
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/23497037
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, Inbred Strains",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Breeding",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Chromosome Mapping",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Genetic Variation",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Nucleotides",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Polymorphism, Single Nucleotide",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Swine",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Centro Nacional de An\u00e1lisis Gen\u00f3mico",
"id": "https://www.grid.ac/institutes/grid.452341.5",
"name": [
"Center for Research in Agricultural Genomics (CRAG), Campus UAB, 08193, Bellaterra, Spain",
"Departament de Ci\u00e8ncia Animal i dels Aliments, Universitat Aut\u00f2noma de Barcelona, 08193, Bellaterra, Spain",
"Centre Nacional d'An\u00e0lisi Gen\u00f2mica (CNAG), Barcelona, Spain"
],
"type": "Organization"
},
"familyName": "Esteve-Codina",
"givenName": "Anna",
"id": "sg:person.01331776746.94",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01331776746.94"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Wageningen University & Research",
"id": "https://www.grid.ac/institutes/grid.4818.5",
"name": [
"Animal Breeding and Genomics Centre, Wageningen University, De Elst 1, 6708 WD, Wageningen, The Netherlands"
],
"type": "Organization"
},
"familyName": "Paudel",
"givenName": "Yogesh",
"id": "sg:person.0672455554.04",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0672455554.04"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Autonomous University of Barcelona",
"id": "https://www.grid.ac/institutes/grid.7080.f",
"name": [
"Center for Research in Agricultural Genomics (CRAG), Campus UAB, 08193, Bellaterra, Spain"
],
"type": "Organization"
},
"familyName": "Ferretti",
"givenName": "Luca",
"id": "sg:person.0604607310.31",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0604607310.31"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Centro Nacional de An\u00e1lisis Gen\u00f3mico",
"id": "https://www.grid.ac/institutes/grid.452341.5",
"name": [
"Centre Nacional d'An\u00e0lisi Gen\u00f2mica (CNAG), Barcelona, Spain"
],
"type": "Organization"
},
"familyName": "Raineri",
"givenName": "Emanuele",
"id": "sg:person.01034067302.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01034067302.26"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Wageningen University & Research",
"id": "https://www.grid.ac/institutes/grid.4818.5",
"name": [
"Animal Breeding and Genomics Centre, Wageningen University, De Elst 1, 6708 WD, Wageningen, The Netherlands"
],
"type": "Organization"
},
"familyName": "Megens",
"givenName": "Hendrik-Jan",
"id": "sg:person.01324213132.08",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01324213132.08"
],
"type": "Person"
},
{
"affiliation": {
"name": [
"Departamento de Mejora Gen\u00e9tica Animal, INIA, 28040, Madrid, Spain"
],
"type": "Organization"
},
"familyName": "Sili\u00f3",
"givenName": "Luis",
"id": "sg:person.01220410373.52",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01220410373.52"
],
"type": "Person"
},
{
"affiliation": {
"name": [
"Departamento de Mejora Gen\u00e9tica Animal, INIA, 28040, Madrid, Spain"
],
"type": "Organization"
},
"familyName": "Rodr\u00edguez",
"givenName": "Mar\u00eda C",
"id": "sg:person.01334636773.07",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334636773.07"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Wageningen University & Research",
"id": "https://www.grid.ac/institutes/grid.4818.5",
"name": [
"Animal Breeding and Genomics Centre, Wageningen University, De Elst 1, 6708 WD, Wageningen, The Netherlands"
],
"type": "Organization"
},
"familyName": "Groenen",
"givenName": "Martein AM",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Autonomous University of Barcelona",
"id": "https://www.grid.ac/institutes/grid.7080.f",
"name": [
"Center for Research in Agricultural Genomics (CRAG), Campus UAB, 08193, Bellaterra, Spain"
],
"type": "Organization"
},
"familyName": "Ramos-Onsins",
"givenName": "Sebastian E",
"id": "sg:person.01234126756.66",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01234126756.66"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Instituci\u00f3 Catalana de Recerca i Estudis Avan\u00e7ats",
"id": "https://www.grid.ac/institutes/grid.425902.8",
"name": [
"Center for Research in Agricultural Genomics (CRAG), Campus UAB, 08193, Bellaterra, Spain",
"Departament de Ci\u00e8ncia Animal i dels Aliments, Universitat Aut\u00f2noma de Barcelona, 08193, Bellaterra, Spain",
"Institut Catal\u00e0 de Recerca i Estudis Avan\u00e7ats (ICREA), Carrer de Llu\u00eds Companys 23, 08010, Barcelona, Spain"
],
"type": "Organization"
},
"familyName": "P\u00e9rez-Enciso",
"givenName": "Miguel",
"id": "sg:person.01041433710.67",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01041433710.67"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1093/molbev/msn049",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002112540"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/genetics.107.078865",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002999964"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/genetics.107.078865",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002999964"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1365-2052.2011.02301.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003580508"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrg2958",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004346662",
"https://doi.org/10.1038/nrg2958"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/oxfordjournals.molbev.a026425",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004655800"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1084/jem.20111680",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006484913"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btr708",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008059544"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1420-9101.2007.01305.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009926505"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/genetics.110.121012",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1010520751"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/genetics.110.121012",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1010520751"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0014782",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011124548"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature11622",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011485493",
"https://doi.org/10.1038/nature11622"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1046/j.1365-2052.2003.01010.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012265447"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/gb-2010-11-9-r91",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014630789",
"https://doi.org/10.1186/gb-2010-11-9-r91"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/molbev/msr251",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016602296"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/18.2.337",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016789793"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1749-6632.2011.06345.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017692434"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1006/tpbi.1995.1025",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018949399"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1601-183x.2010.00612.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019620763"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1365-2052.2012.02317.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020752088"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1365-2052.2012.02374.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020920353"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1126/science.1197005",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022546312"
],
"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/10.1111/j.1365-2052.2006.01436.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024486194"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2164-10-374",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025479442",
"https://doi.org/10.1186/1471-2164-10-374"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.074187.107",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025684251"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/hdy.2010.61",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025927778",
"https://doi.org/10.1038/hdy.2010.61"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2202-13-37",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026757054",
"https://doi.org/10.1186/1471-2202-13-37"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.livsci.2006.10.002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027035088"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1365-294x.2011.05308.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030628800"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1365-294x.2007.03633.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033929776"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.121327.111",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034859406"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.1185",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034942023",
"https://doi.org/10.1038/nmeth.1185"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s002390010085",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034978009",
"https://doi.org/10.1007/s002390010085"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1017/s1466252310000174",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035356033"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/hdy.2011.13",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036183679",
"https://doi.org/10.1038/hdy.2011.13"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pgen.1000341",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036194312"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pgen.1003100",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036519196"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2105-13-239",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036852204",
"https://doi.org/10.1186/1471-2105-13-239"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2105-13-239",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036852204",
"https://doi.org/10.1186/1471-2105-13-239"
],
"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/10.1016/s0309-1740(98)90036-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038313508"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.106161.110",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045023304"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/genetics.110.114397",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045585344"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1534/genetics.110.114397",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045585344"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1523/jneurosci.2623-05.2006",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045681294"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btq330",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1047117020"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2148-11-171",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048627936",
"https://doi.org/10.1186/1471-2148-11-171"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1365-2052.2012.02335.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048849888"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00239-004-0313-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050935236",
"https://doi.org/10.1007/s00239-004-0313-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00239-004-0313-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050935236",
"https://doi.org/10.1007/s00239-004-0313-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth0810-576",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052651674",
"https://doi.org/10.1038/nmeth0810-576"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0309-1740(98)00072-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1054652782"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1046/j.1523-1739.2000.99322.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1056742974"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/envhis/emq143",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1059567772"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1210/jc.2004-0191",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064287690"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.7150/ijbs.3.153",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1073618654"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1074616182",
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1074662815",
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1075016613",
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/jn/138.2.397",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1077592224"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1078957195",
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1079560051",
"type": "CreativeWork"
}
],
"datePublished": "2013-12",
"datePublishedReg": "2013-12-01",
"description": "BACKGROUND: In contrast to international pig breeds, the Iberian breed has not been admixed with Asian germplasm. This makes it an important model to study both domestication and relevance of Asian genes in the pig. Besides, Iberian pigs exhibit high meat quality as well as appetite and propensity to obesity. Here we provide a genome wide analysis of nucleotide and structural diversity in a reduced representation library from a pool (n=9 sows) and shotgun genomic sequence from a single sow of the highly inbred Guadyerbas strain. In the pool, we applied newly developed tools to account for the peculiarities of these data.\nRESULTS: A total of 254,106 SNPs in the pool (79.6 Mb covered) and 643,783 in the Guadyerbas sow (1.47 Gb covered) were called. The nucleotide diversity (1.31x10-3 per bp in autosomes) is very similar to that reported in wild boar. A much lower than expected diversity in the X chromosome was confirmed (1.79x10-4 per bp in the individual and 5.83x10-4 per bp in the pool). A strong (0.70) correlation between recombination and variability was observed, but not with gene density or GC content. Multicopy regions affected about 4% of annotated pig genes in their entirety, and 2% of the genes partially. Genes within the lowest variability windows comprised interferon genes and, in chromosome X, genes involved in behavior like HTR2C or MCEP2. A modified Hudson-Kreitman-Aguad\u00e9 test for pools also indicated an accelerated evolution in genes involved in behavior, as well as in spermatogenesis and in lipid metabolism.\nCONCLUSIONS: This work illustrates the strength of current sequencing technologies to picture a comprehensive landscape of variability in livestock species, and to pinpoint regions containing genes potentially under selection. Among those genes, we report genes involved in behavior, including feeding behavior, and lipid metabolism. The pig X chromosome is an outlier in terms of nucleotide diversity, which suggests selective constraints. Our data further confirm the importance of structural variation in the species, including Iberian pigs, and allowed us to identify new paralogs for known gene families.",
"genre": "research_article",
"id": "sg:pub.10.1186/1471-2164-14-148",
"inLanguage": [
"en"
],
"isAccessibleForFree": true,
"isFundedItemOf": [
{
"id": "sg:grant.3788351",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.3778710",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1023790",
"issn": [
"1471-2164"
],
"name": "BMC Genomics",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "14"
}
],
"name": "Dissecting structural and nucleotide genome-wide variation in inbred Iberian pigs",
"pagination": "148",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"6aaa2828adb1a09100e18f292c72c0b8c7b0c660f4b1908d70262a38035c9f36"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"23497037"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"100965258"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1186/1471-2164-14-148"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1022388901"
]
}
],
"sameAs": [
"https://doi.org/10.1186/1471-2164-14-148",
"https://app.dimensions.ai/details/publication/pub.1022388901"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T01:05",
"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_8697_00000505.jsonl",
"type": "ScholarlyArticle",
"url": "http://link.springer.com/10.1186%2F1471-2164-14-148"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
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.10.1186/1471-2164-14-148'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-14-148'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-14-148'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-14-148'
This table displays all metadata directly associated to this object as RDF triples.
368 TRIPLES
21 PREDICATES
96 URIs
29 LITERALS
17 BLANK NODES