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

Anish M S Shrestha; Mark Edward M Gonzales; Phoebe Clare L Ong; Pierre Larmande; Hyun-Sook Lee; Ji-Ung Jeung; Ajay Kohli; Dmytro Chebotarov; Ramil P Mauleon; Jae-Sung Lee; Kenneth L McNally

doi:10.1093/gigascience/giae013

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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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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

Anish M S Shrestha, Mark Edward M Gonzales, Phoebe Clare L Ong, Pierre Larmande, Hyun-Sook Lee, Ji-Ung Jeung, Ajay Kohli, Dmytro Chebotarov, Ramil P Mauleon, Jae-Sung Lee, …

Gigascience, Vol.13(2024), giae013

04/06/2024

DOI: https://doi.org/10.1093/gigascience/giae013

PMID: 38832465

Appears in Recent Faculty of Science and Engineering Publications

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Abstract

rice

GWAS

QTL analysis

post-GWAS

coexpression network

transcription factor binding

text mining

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.

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Title: 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
Creators: Anish M S Shrestha - De La Salle University
Mark Edward M Gonzales - De La Salle University
Phoebe Clare L Ong - De La Salle University
Pierre Larmande - University of Montpellier
Hyun-Sook Lee - National Institute of Crop Science (Wanju-gun, Republic of Korea)
Ji-Ung Jeung - National Institute of Crop Science (Wanju-gun, Republic of Korea)
Ajay Kohli - International Rice Research Institute
Dmytro Chebotarov - International Rice Research Institute
Ramil P Mauleon - International Rice Research Institute
Jae-Sung Lee - International Rice Research Institute
Kenneth L McNally - International Rice Research Institute
Publication Details: Gigascience, Vol.13(2024), giae013
Publisher: Oxford University Press
Grant note: This research was funded by the Rural Development Administration (RDA) of South Korea as an RDA-IRRI cooperative project (Grant PJ016405, PI: Dr. Ji-Ung Jeong).
Identifiers: 991013193110402368
Copyright: © The Author(s) 2024. Published by Oxford University Press on behalf of GigaScience. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).
Academic Unit: Faculty of Science and Engineering
Language: English
Resource Type: Journal article

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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