Your browser doesn't support javascript.
loading
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.
Shrestha, Anish M S; Gonzales, Mark Edward M; Ong, Phoebe Clare L; Larmande, Pierre; Lee, Hyun-Sook; Jeung, Ji-Ung; Kohli, Ajay; Chebotarov, Dmytro; Mauleon, Ramil P; Lee, Jae-Sung; McNally, Kenneth L.
Afiliação
  • Shrestha AMS; Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines.
  • Gonzales MEM; International Rice Research Institute (IRRI), Metro Manila 1301, Philippines.
  • Ong PCL; Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines.
  • Larmande P; Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines.
  • Lee HS; DIADE, Univ Montpellier, Cirad, IRD, 34394 Montpellier, France.
  • Jeung JU; National Institute of Crop Science, Wanju-gun 55365, Republic of Korea.
  • Kohli A; National Institute of Crop Science, Wanju-gun 55365, Republic of Korea.
  • Chebotarov D; International Rice Research Institute (IRRI), Metro Manila 1301, Philippines.
  • Mauleon RP; International Rice Research Institute (IRRI), Metro Manila 1301, Philippines.
  • Lee JS; International Rice Research Institute (IRRI), Metro Manila 1301, Philippines.
  • McNally KL; International Rice Research Institute (IRRI), Metro Manila 1301, Philippines.
Gigascience ; 132024 01 02.
Article em En | MEDLINE | ID: mdl-38832465
ABSTRACT

BACKGROUND:

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.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oryza / Locos de Características Quantitativas / Estudo de Associação Genômica Ampla / Mineração de Dados Idioma: En Revista: Gigascience Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Filipinas

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oryza / Locos de Características Quantitativas / Estudo de Associação Genômica Ampla / Mineração de Dados Idioma: En Revista: Gigascience Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Filipinas