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Kashima M, Sakamoto RL, Saito H, Ohkubo S, Tezuka A, Deguchi A, Hashida Y, Kurita Y, Iwayama K, Adachi S, Nagano AJ. Genomic Basis of Transcriptome Dynamics in Rice under Field Conditions. PLANT & CELL PHYSIOLOGY 2021; 62:1436-1445. [PMID: 34131748 PMCID: PMC8600290 DOI: 10.1093/pcp/pcab088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 05/09/2021] [Accepted: 06/15/2021] [Indexed: 05/07/2023]
Abstract
How genetic variations affect gene expression dynamics of field-grown plants remains unclear. Expression quantitative trait loci (eQTL) analysis is frequently used to find genomic regions underlying gene expression polymorphisms. This approach requires transcriptome data for the complete set of the QTL mapping population under the given conditions. Therefore, only a limited range of environmental conditions is covered by a conventional eQTL analysis. We sampled sparse time series of field-grown rice from chromosome segment substitution lines (CSSLs) and conducted RNA sequencing (RNA-Seq). Then, by using statistical analysis integrating meteorological data and the RNA-Seq data, we identified 1,675 eQTLs leading to polymorphisms in expression dynamics under field conditions. A genomic region on chromosome 11 influences the expression of several defense-related genes in a time-of-day- and scaled-age-dependent manner. This includes the eQTLs that possibly influence the time-of-day- and scaled-age-dependent differences in the innate immunity between Koshihikari and Takanari. Based on the eQTL and meteorological data, we successfully predicted gene expression under environments different from training environments and in rice cultivars with more complex genotypes than the CSSLs. Our novel approach of eQTL identification facilitated the understanding of the genetic architecture of expression dynamics under field conditions, which is difficult to assess by conventional eQTL studies. The prediction of expression based on eQTLs and environmental information could contribute to the understanding of plant traits under diverse field conditions.
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Affiliation(s)
- Makoto Kashima
- Research Institute for Food and Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194, Japan
| | | | - Hiroki Saito
- Graduate School of Agriculture, Kyoto University, Kitashirakawa-oiwake, Sakyo-ku, Kyoto 606-8317, Japan
- Tropical Agriculture Research Front, Japan International Research Center for Agricultural Sciences, Maezato 1091-1, Ishigaki, Okinawa 907-0002, Japan
| | - Satoshi Ohkubo
- Graduate School of Agriculture, Kyoto University, Kitashirakawa-oiwake, Sakyo-ku, Kyoto 606-8317, Japan
- Institute of Global Innovation Research, Tokyo University of Agriculture and Technology, Saiwaicho 3-5-8, Fuchu, Tokyo 183-8509, Japan
| | - Ayumi Tezuka
- Research Institute for Food and Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194, Japan
| | - Ayumi Deguchi
- Research Institute for Food and Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194, Japan
| | - Yoichi Hashida
- Research Institute for Food and Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194, Japan
| | - Yuko Kurita
- Research Institute for Food and Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194, Japan
| | - Koji Iwayama
- Faculty of Data Science, Shiga University, Bamba 1-1-1, Hikone, Shiga 522-0069, Japan
| | - Shunsuke Adachi
- Institute of Global Innovation Research, Tokyo University of Agriculture and Technology, Saiwaicho 3-5-8, Fuchu, Tokyo 183-8509, Japan
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Pang H, Chen Q, Li Y, Wang Z, Wu L, Yang Q, Zheng X. Comparative analysis of the transcriptomes of two rice subspecies during domestication. Sci Rep 2021; 11:3660. [PMID: 33574456 PMCID: PMC7878495 DOI: 10.1038/s41598-021-83162-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Accepted: 01/28/2021] [Indexed: 11/11/2022] Open
Abstract
Two subspecies of rice, Oryza sativa ssp. indica and O. sativa ssp. japonica, with reproductive isolation and differences in morphology and phenotypic differences, were established during the process of rice domestication. To understand how domestication has changed the transcriptomes of the two rice subspecies and given rise to the phenotypic differences, we obtained approximately 700 Gb RNA-Seq data from 26 indica and 25 japonica accessions, and identified 97,005 transcribed fragments and 4579 novel transcriptionally active regions. The two rice subspecies had significantly different gene expression profiles, we identified 1,357 (3.3% in all genes) differentially expressed genes (DEGs) between indica and japonica rice. Combining existing gene function studies, it is found that some of these differential genes are related to the differentiation of the two subspecies, such as grain shape and cold tolerance, etc. Functional annotation of these DEGs indicates that they are involved in cell wall biosynthesis and reproductive processes. Furthermore, compared with the non-DEGs, the DEGs from both subspecies had more 5'flanking regions with low polymorphism to divergence ratios, indicating a stronger positive selection pressure on the regulation of the DEGs. This study improves our understanding of the rice genome by comparatively analyzing the transcriptomes of indica and japonica rice and identifies DEGs those may be responsible for the reproductive isolation and phenotypic differences between the two rice subspecies.
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Affiliation(s)
- Hongbo Pang
- College of Life Science, Shenyang Normal University, Shenyang, 110034, China
| | - Qiang Chen
- Experimental Teaching Center, Shenyang Normal University, Shenyang, 110034, China
| | - Yueying Li
- College of Life Science, Shenyang Normal University, Shenyang, 110034, China
| | - Ze Wang
- College of Life Science, Shenyang Normal University, Shenyang, 110034, China
| | - Longkun Wu
- College of Life Science, Shenyang Normal University, Shenyang, 110034, China
| | - Qingwen Yang
- Center for Crop Germplasm Resources, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xiaoming Zheng
- Center for Crop Germplasm Resources, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
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