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Shrestha AMS, Gonzales MEM, Ong PCL, Larmande P, Lee HS, Jeung JU, Kohli A, Chebotarov D, Mauleon RP, Lee JS, McNally KL. 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 2024; 13:giae013. [PMID: 38832465 PMCID: PMC11148593 DOI: 10.1093/gigascience/giae013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 02/21/2024] [Accepted: 03/12/2024] [Indexed: 06/05/2024] Open
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.
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Affiliation(s)
- Anish M S Shrestha
- Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Mark Edward M Gonzales
- Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines
| | - Phoebe Clare L Ong
- Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, College of Computer Studies, De La Salle University, Manila 1004, Philippines
| | - Pierre Larmande
- DIADE, Univ Montpellier, Cirad, IRD, 34394 Montpellier, France
| | - Hyun-Sook Lee
- National Institute of Crop Science, Wanju-gun 55365, Republic of Korea
| | - Ji-Ung Jeung
- National Institute of Crop Science, Wanju-gun 55365, Republic of Korea
| | - Ajay Kohli
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Dmytro Chebotarov
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Ramil P Mauleon
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Jae-Sung Lee
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
| | - Kenneth L McNally
- International Rice Research Institute (IRRI), Metro Manila 1301, Philippines
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Liu X, Deng X, Kong W, Sun T, Li Y. The Pyramiding of Elite Allelic Genes Related to Grain Number Increases Grain Number per Panicle Using the Recombinant Lines Derived from Indica-japonica Cross in Rice. Int J Mol Sci 2023; 24:ijms24021653. [PMID: 36675168 PMCID: PMC9865901 DOI: 10.3390/ijms24021653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/08/2023] [Accepted: 01/10/2023] [Indexed: 01/19/2023] Open
Abstract
Indica(xian)-japonica(geng) hybrid rice has many heterosis traits that can improve rice yield. However, the traditional hybrid technology will struggle to meet future needs for the development of higher-yield rice. Available genomics resources can be used to efficiently understand the gene-trait association trait for rice breeding. Based on the previously constructed high-density genetic map of 272 high-generation recombinant inbred lines (RILs) originating from the cross of Luohui 9 (indica, as female) and RPY geng (japonica, as male) and high-quality genomes of parents, here, we further explore the genetic basis for an important complex trait: possible causes of grain number per panicle (GNPP). A total of 20 genes related to grains number per panicle (GNPP) with the differences of protein amino acid between LH9 and RPY were used to analyze genotype combinations, and PCA results showed a combination of PLY1, LAX1, DTH8 and OSH1 from the RPY geng with PYL4, SP1, DST and GNP1 from Luohui 9 increases GNPP. In addition, we also found that the combination of LAX1-T2 and GNP1-T3 had the most significant increase in GNPP. Notably, Molecular Breeding Knowledgebase (MBK) showed a few aggregated rice cultivars, LAX1-T2 and GNP1-T3, which may be a result of the natural geographic isolation between the two gene haplotypes. Therefore, we speculate that the pyramiding of japonica-type LAX-T2 with indica-type GNP1-T3 via hybridization can significantly improve rice yield by increasing GNPP.
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Affiliation(s)
- Xuhui Liu
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Xiaoxiao Deng
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Weilong Kong
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Tong Sun
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Yangsheng Li
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China
- Correspondence:
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Zhang M, Lai L, Liu X, Liu J, Liu R, Wang Y, Liu J, Chen J. Overexpression of Nitrate Transporter 1/Peptide Gene OsNPF7.6 Increases Rice Yield and Nitrogen Use Efficiency. LIFE (BASEL, SWITZERLAND) 2022; 12:life12121981. [PMID: 36556346 PMCID: PMC9786031 DOI: 10.3390/life12121981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 11/09/2022] [Accepted: 11/11/2022] [Indexed: 11/29/2022]
Abstract
Overuse of nitrogen fertilizer in fields has raised production costs, and caused environmental problems. Improving nitrogen use efficiency (NUE) of rice is essential for sustainable agriculture. Here we report the cloning, characterization and roles for rice of OsNPF7.6, a member of the nitrate transporter 1/peptide transporter family (NPF). The OsNPF7.6 protein is located in the plasma membrane, expressed in each tissue at all stages and is significantly regulated by nitrate in rice. Our study shows that the overexpression of OsNPF7.6 can increase the nitrate uptake rate of rice. Additionally, field experiments showed that OsNPF7.6 overexpression increased the total tiller number per plant and the grain weight per panicle, thereby improving grain yield and agronomic NUE in rice. Thus, OsNPF7.6 can be applied to be a novel target gene for breeding rice varieties with high NUE, and provide a reference for breeding higher yielding rice.
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Affiliation(s)
- Min Zhang
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, China
| | - Liuru Lai
- School of Agriculture, Shenzhen Campus, Sun Yat-sen University, Shenzhen 518107, China
| | - Xintong Liu
- School of Agriculture, Shenzhen Campus, Sun Yat-sen University, Shenzhen 518107, China
| | - Jiajia Liu
- Shandong Jinchunyu Seed Technology Co., Ltd., Jining 272200, China
| | - Ruifang Liu
- The High School Affiliated to Renmin University of China, Shenzhen 518119, China
| | - Yamei Wang
- School of Agriculture, Shenzhen Campus, Sun Yat-sen University, Shenzhen 518107, China
| | - Jindong Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing 100081, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
- Correspondence: (J.L.); (J.C.)
| | - Jingguang Chen
- School of Agriculture, Shenzhen Campus, Sun Yat-sen University, Shenzhen 518107, China
- Correspondence: (J.L.); (J.C.)
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