RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci

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cg.authorship.typesCGIAR and developing country instituteen_US
cg.authorship.typesCGIAR and advanced research instituteen_US
cg.contributor.affiliationDe La Salle University Manilaen_US
cg.contributor.affiliationInternational Rice Research Instituteen_US
cg.contributor.affiliationDIADE, Univ Montpellieren_US
cg.contributor.affiliationNational Institute of Crop Science, Koreaen_US
cg.contributor.donorRural Development Administration (RDA) of South Koreaen_US
cg.contributor.donorCGIAR Trust Funden_US
cg.contributor.initiativeAccelerated Breedingen_US
cg.coverage.regionAfricaen_US
cg.coverage.regionAsiaen_US
cg.creator.identifierAnish Shrestha: 0000-0002-9192-9709en_US
cg.creator.identifierMark Edward Gonzales: 0000-0001-5050-3157en_US
cg.creator.identifierPhoebe Clare Ong: 0009-0004-7982-7314en_US
cg.creator.identifierJi-Ung Jeung: 0000-0002-7578-2081en_US
cg.creator.identifierDmytro Chebotarov: 0000-0003-1351-9453en_US
cg.creator.identifierRamil Mauleon: 0000-0001-8512-144Xen_US
cg.creator.identifierKenneth McNally: 0000-0002-9613-5537en_US
cg.edition2024en_US
cg.howPublishedFormally Publisheden_US
cg.identifier.doihttps://doi.org/10.1093/gigascience/giae013en_US
cg.isijournalISI Journalen_US
cg.issn2047-217Xen_US
cg.journalGigaScienceen_US
cg.reviewStatusPeer Reviewen_US
cg.subject.actionAreaGenetic Innovationen_US
cg.subject.impactAreaNutrition, health and food securityen_US
cg.volume13en_US
dc.contributor.authorShrestha, Anish M. S.en_US
dc.contributor.authorGonzales, Mark Edward M.en_US
dc.contributor.authorOng, Phoebe Clare L.en_US
dc.contributor.authorLarmande, Pierreen_US
dc.contributor.authorLee, Hyun-Sooken_US
dc.contributor.authorJeung, Ji-Ungen_US
dc.contributor.authorKohli, Ajayen_US
dc.contributor.authorChebotarov, Dmytroen_US
dc.contributor.authorMauleon, Ramil P.en_US
dc.contributor.authorLee, Jae-Sungen_US
dc.contributor.authorMcNally, Kenneth L.en_US
dc.date.accessioned2024-12-20T16:13:03Zen_US
dc.date.available2024-12-20T16:13:03Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/168155en_US
dc.titleRicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS locien_US
dcterms.abstractBackground As the number of genome-wide association study (GWAS) and quantitative trait locus (QTL) mappings in rice continues to grow, so does the already long list of genomic loci associated with important agronomic traits. Typically, loci implicated by GWAS/QTL analysis contain tens to hundreds to thousands of single-nucleotide polmorphisms (SNPs)/genes, not all of which are causal and many of which are in noncoding regions. Unraveling the biological mechanisms that tie the GWAS regions and QTLs to the trait of interest is challenging, especially since it requires collating functional genomics information about the loci from multiple, disparate data sources. Results We present RicePilaf, a web app for post-GWAS/QTL analysis, that performs a slew of novel bioinformatics analyses to cross-reference GWAS results and QTL mappings with a host of publicly available rice databases. In particular, it integrates (i) pangenomic information from high-quality genome builds of multiple rice varieties, (ii) coexpression information from genome-scale coexpression networks, (iii) ontology and pathway information, (iv) regulatory information from rice transcription factor databases, (v) epigenomic information from multiple high-throughput epigenetic experiments, and (vi) text-mining information extracted from scientific abstracts linking genes and traits. We demonstrate the utility of RicePilaf by applying it to analyze GWAS peaks of preharvest sprouting and genes underlying yield-under-drought QTLs. Conclusions RicePilaf enables rice scientists and breeders to shed functional light on their GWAS regions and QTLs, and it provides them with a means to prioritize SNPs/genes for further experiments. The source code, a Docker image, and a demo version of RicePilaf are publicly available at https://github.com/bioinfodlsu/rice-pilaf.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.audienceCGIARen_US
dcterms.audienceDevelopment Practitionersen_US
dcterms.audienceAcademicsen_US
dcterms.audienceDonorsen_US
dcterms.audienceScientistsen_US
dcterms.available2024-06-04en_US
dcterms.bibliographicCitationShrestha, Anish MS, Mark Edward M. Gonzales, Phoebe Clare L. Ong, Pierre Larmande, Hyun-Sook Lee, Ji-Ung Jeung, Ajay Kohli et al. "RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci." GigaScience 13 (2024): giae013.en_US
dcterms.extent1-12en_US
dcterms.issued2024-03-12en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.publisherOxford University Pressen_US
dcterms.subjectdatabasesen_US
dcterms.subjectriceen_US
dcterms.subjectvarietiesen_US
dcterms.subjectagronomic charactersen_US
dcterms.subjectquantitative trait locien_US
dcterms.subjectquantitative trait loci mappingen_US
dcterms.subjectanalysisen_US
dcterms.subjectgenome-wide association studiesen_US
dcterms.subjecttext miningen_US
dcterms.typeJournal Articleen_US

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