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
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 t...
| Main Authors: | , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Oxford University Press
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/168155 |
| _version_ | 1855514023621033984 |
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| author | 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. |
| author_browse | Chebotarov, Dmytro Gonzales, Mark Edward M. Jeung, Ji-Ung Kohli, Ajay Larmande, Pierre Lee, Hyun-Sook Lee, Jae-Sung Mauleon, Ramil P. McNally, Kenneth L. Ong, Phoebe Clare L. Shrestha, Anish M. S. |
| author_facet | 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. |
| author_sort | Shrestha, Anish M. S. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace168155 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Oxford University Press |
| publisherStr | Oxford University Press |
| record_format | dspace |
| spelling | CGSpace1681552025-12-08T10:11:39Z 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. databases rice varieties agronomic characters quantitative trait loci quantitative trait loci mapping analysis genome-wide association studies 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. 2024-01-02 2024-12-20T16:13:03Z 2024-12-20T16:13:03Z Journal Article https://hdl.handle.net/10568/168155 en Open Access application/pdf Oxford University Press Shrestha, 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. |
| spellingShingle | databases rice varieties agronomic characters quantitative trait loci quantitative trait loci mapping analysis genome-wide association studies text mining 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. 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 |
| 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| topic | databases rice varieties agronomic characters quantitative trait loci quantitative trait loci mapping analysis genome-wide association studies text mining |
| url | https://hdl.handle.net/10568/168155 |
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