Ontology type: schema:ScholarlyArticle Open Access: True
2019-12
AUTHORSMarina Naoumkina, Gregory N. Thyssen, David D. Fang, Johnie N. Jenkins, Jack C. McCarty, Christopher B. Florane
ABSTRACTBACKGROUND: Improving cotton fiber length without reducing yield is one of the major goals of cotton breeding. However, genetic improvement of cotton fiber length by breeding has been a challenge due to the narrow genetic diversity of modern cotton cultivars and negative correlations between fiber quality and yield traits. A multi-parent advanced generation inter-cross (MAGIC) population developed through random mating provides an excellent genetic resource that allows quantitative trait loci (QTL) and causal genes to be identified. RESULTS: An Upland cotton MAGIC population, consisting of 550 recombinant inbred lines (RILs) derived from eleven different cultivars, was used to identify fiber length QTLs and potential genes that contribute to longer fibers. A genome wide association study (GWAS) identified a cluster of single nucleotide polymorphisms (SNPs) on chromosome (Chr.) D11 that is significantly associated with fiber length. Further evaluation of the Chr. D11 genomic region among lines of the MAGIC population detected that 90% of RILs have a D11 haplotype similar to the reference TM-1 genome (D11-ref), whereas 10% of RILs inherited an alternative haplotype from one of the parents (D11-alt). The average length of fibers of D11-alt RILs was significantly shorter compared to D11-ref RILs, suggesting that alleles in the D11-alt haplotype contributed to the inferior fiber quality. RNAseq analysis of the longest and shortest fiber length RILs from D11-ref and D11-alt populations identified 949 significantly differentially expressed genes (DEGs). Gene set enrichment analysis revealed that different functional categories of genes were over-represented during fiber elongation between the four selected RILs. We found 12 genes possessing non-synonymous SNPs (nsSNPs) significantly associated with the fiber length, and three that were highly significant and were clustered at D11:24-Mb, including D11G1928, D11G1929 and D11G1931. CONCLUSION: The results of this study provide insights into molecular aspects of genetic variation in fiber length and suggests candidate genes for genetic manipulation for cotton improvement. More... »
PAGES112
http://scigraph.springernature.com/pub.10.1186/s12864-019-5427-5
DOIhttp://dx.doi.org/10.1186/s12864-019-5427-5
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1111954471
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/30727946
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Genetics",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Biological Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Agricultural Research Service",
"id": "https://www.grid.ac/institutes/grid.463419.d",
"name": [
"Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, 70124, New Orleans, LA, USA"
],
"type": "Organization"
},
"familyName": "Naoumkina",
"givenName": "Marina",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Agricultural Research Service",
"id": "https://www.grid.ac/institutes/grid.463419.d",
"name": [
"Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, 70124, New Orleans, LA, USA",
"Cotton Chemistry and Utilization Research Unit, USDA-ARS-SRRC, 1100 Robert E. Lee Blvd, 70124, New Orleans, LA, USA"
],
"type": "Organization"
},
"familyName": "Thyssen",
"givenName": "Gregory N.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Agricultural Research Service",
"id": "https://www.grid.ac/institutes/grid.463419.d",
"name": [
"Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, 70124, New Orleans, LA, USA"
],
"type": "Organization"
},
"familyName": "Fang",
"givenName": "David D.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Agricultural Research Service",
"id": "https://www.grid.ac/institutes/grid.463419.d",
"name": [
"Genetics and Sustainable Agriculture Research Unit, USDA-ARS, 810 Highway 12 East, 39762, Mississippi State, MS, USA"
],
"type": "Organization"
},
"familyName": "Jenkins",
"givenName": "Johnie N.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Agricultural Research Service",
"id": "https://www.grid.ac/institutes/grid.463419.d",
"name": [
"Genetics and Sustainable Agriculture Research Unit, USDA-ARS, 810 Highway 12 East, 39762, Mississippi State, MS, USA"
],
"type": "Organization"
},
"familyName": "McCarty",
"givenName": "Jack C.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Agricultural Research Service",
"id": "https://www.grid.ac/institutes/grid.463419.d",
"name": [
"Cotton Fiber Bioscience Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Southern Regional Research Center (SRRC), 1100 Robert E. Lee Blvd, 70124, New Orleans, LA, USA"
],
"type": "Organization"
},
"familyName": "Florane",
"givenName": "Christopher B.",
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1146/annurev-arplant-050213-035715",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000027733"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0056315",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001294291"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00289981",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002379068",
"https://doi.org/10.1007/bf00289981"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0019379",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005754650"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00122-016-2684-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006607613",
"https://doi.org/10.1007/s00122-016-2684-4"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1105/tpc.105.036434",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007618509"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1104/pp.112.212357",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012315526"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.gene.2005.12.014",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012501249"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0074-7696(08)61300-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012643343"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12864-016-3249-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014336665",
"https://doi.org/10.1186/s12864-016-3249-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12864-016-3249-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014336665",
"https://doi.org/10.1186/s12864-016-3249-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.tig.2012.06.003",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014959561"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.546",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017784241",
"https://doi.org/10.1038/ng.546"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.546",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017784241",
"https://doi.org/10.1038/ng.546"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2164-12-445",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018998297",
"https://doi.org/10.1186/1471-2164-12-445"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2229-7-22",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021325263",
"https://doi.org/10.1186/1471-2229-7-22"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00122-015-2506-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022047922",
"https://doi.org/10.1007/s00122-015-2506-0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00438-015-1021-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022373309",
"https://doi.org/10.1007/s00438-015-1021-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00438-015-1021-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022373309",
"https://doi.org/10.1007/s00438-015-1021-y"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btp352",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1023014918"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11032-004-4731-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024004925",
"https://doi.org/10.1007/s11032-004-4731-0"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1104/pp.010724",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024927818"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btq057",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025260149"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1105/tpc.104.026690",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025262379"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/oxfordjournals.molbev.a026131",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026460145"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12864-016-2560-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026763326",
"https://doi.org/10.1186/s12864-016-2560-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1006/meth.2001.1262",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027621591"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1006/meth.2001.1262",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027621591"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/pbi.12693",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030798198"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1046/j.1525-142x.2001.00079.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030936181"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00122-002-1025-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034953694",
"https://doi.org/10.1007/s00122-002-1025-y"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/bts444",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036147444"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.2991",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036408106",
"https://doi.org/10.1038/ng.2991"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1214/aos/1013699998",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036427477"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.3207",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037216172",
"https://doi.org/10.1038/nbt.3207"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.1007879107",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037284278"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00425-010-1246-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038379862",
"https://doi.org/10.1007/s00425-010-1246-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00425-010-1246-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038379862",
"https://doi.org/10.1007/s00425-010-1246-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00122-009-1223-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038388102",
"https://doi.org/10.1007/s00122-009-1223-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00122-009-1223-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038388102",
"https://doi.org/10.1007/s00122-009-1223-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00122-009-1223-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038388102",
"https://doi.org/10.1007/s00122-009-1223-y"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1105/tpc.108.059741",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1039213231"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkw910",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1040763873"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.fcr.2011.12.002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041685849"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00438-002-0721-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042129634",
"https://doi.org/10.1007/s00438-002-0721-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.93.22.12637",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044791295"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/pl00002908",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045255473",
"https://doi.org/10.1007/pl00002908"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/pl00002908",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045255473",
"https://doi.org/10.1007/pl00002908"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1365-313x.2004.02016.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046563795"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0090830",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1047946842"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2164-15-397",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049727319",
"https://doi.org/10.1186/1471-2164-15-397"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/gb-2010-11-3-r25",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050509557",
"https://doi.org/10.1186/gb-2010-11-3-r25"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11032-011-9549-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051417188",
"https://doi.org/10.1007/s11032-011-9549-y"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1104/pp.105.069906",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051818913"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1105/tpc.107.055657",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053398182"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2135/cropsci1976.0011183x001600060010x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1069017361"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2135/cropsci2008.09.0547",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1069030763"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3198/jpr2008.02.0080crg",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1071120472"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2135/cssaspecpub7.c4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1088346274"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/j.1537-2197.1974.tb06045.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100749589"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/j.1537-2197.1973.tb10209.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100753171"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41588-018-0119-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1103817437",
"https://doi.org/10.1038/s41588-018-0119-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12870-018-1414-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1106910447",
"https://doi.org/10.1186/s12870-018-1414-2"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-12",
"datePublishedReg": "2019-12-01",
"description": "BACKGROUND: Improving cotton fiber length without reducing yield is one of the major goals of cotton breeding. However, genetic improvement of cotton fiber length by breeding has been a challenge due to the narrow genetic diversity of modern cotton cultivars and negative correlations between fiber quality and yield traits. A multi-parent advanced generation inter-cross (MAGIC) population developed through random mating provides an excellent genetic resource that allows quantitative trait loci (QTL) and causal genes to be identified.\nRESULTS: An Upland cotton MAGIC population, consisting of 550 recombinant inbred lines (RILs) derived from eleven different cultivars, was used to identify fiber length QTLs and potential genes that contribute to longer fibers. A genome wide association study (GWAS) identified a cluster of single nucleotide polymorphisms (SNPs) on chromosome (Chr.) D11 that is significantly associated with fiber length. Further evaluation of the Chr. D11 genomic region among lines of the MAGIC population detected that 90% of RILs have a D11 haplotype similar to the reference TM-1 genome (D11-ref), whereas 10% of RILs inherited an alternative haplotype from one of the parents (D11-alt). The average length of fibers of D11-alt RILs was significantly shorter compared to D11-ref RILs, suggesting that alleles in the D11-alt haplotype contributed to the inferior fiber quality. RNAseq analysis of the longest and shortest fiber length RILs from D11-ref and D11-alt populations identified 949 significantly differentially expressed genes (DEGs). Gene set enrichment analysis revealed that different functional categories of genes were over-represented during fiber elongation between the four selected RILs. We found 12 genes possessing non-synonymous SNPs (nsSNPs) significantly associated with the fiber length, and three that were highly significant and were clustered at D11:24-Mb, including D11G1928, D11G1929 and D11G1931.\nCONCLUSION: The results of this study provide insights into molecular aspects of genetic variation in fiber length and suggests candidate genes for genetic manipulation for cotton improvement.",
"genre": "research_article",
"id": "sg:pub.10.1186/s12864-019-5427-5",
"inLanguage": [
"en"
],
"isAccessibleForFree": true,
"isPartOf": [
{
"id": "sg:journal.1023790",
"issn": [
"1471-2164"
],
"name": "BMC Genomics",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "20"
}
],
"name": "Genetic and transcriptomic dissection of the fiber length trait from a cotton (Gossypium hirsutum L.) MAGIC population",
"pagination": "112",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"ccb2c5ea671c2455696f88088bc7d76a8cd021541420693f0bb5a0586828f463"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"30727946"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"100965258"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1186/s12864-019-5427-5"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1111954471"
]
}
],
"sameAs": [
"https://doi.org/10.1186/s12864-019-5427-5",
"https://app.dimensions.ai/details/publication/pub.1111954471"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T09:09",
"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/v90/0000000338_0000000338/records_47966_00000002.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1186%2Fs12864-019-5427-5"
}
]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/s12864-019-5427-5'
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/s12864-019-5427-5'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12864-019-5427-5'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12864-019-5427-5'
This table displays all metadata directly associated to this object as RDF triples.
286 TRIPLES
21 PREDICATES
84 URIs
21 LITERALS
9 BLANK NODES