
Chinese Journal OF Rice Science >
Natural Variation of OsNF-YC10 and Its Correlation with Grain Width in Rice
Received date: 2024-07-17
Revised date: 2024-08-17
Online published: 2025-07-21
【Objective】 Grain width is an important determinant of grain type and grain weight, which can affect rice yield and appearance quality. So far, a large number of genes have been found to affect grain width, but only a limited number of genes have breeding value because mutations of other genes often have negative collateral effects. Hence, it is of great significance to explore new grain width genes and uncover natural variations that have no negative effects on quality and yield. DR610 is a small-grain indica rice and Hagengdao 7 (HG7) is a large-grain japonica rice. 【Method】 In this study, a QTL-seq was performed using the extreme grain weight individuals of the DR610×HG7 F2 population. Through the combined analysis of QTL-seq results and known genes affecting grain type, we found that a nonsense mutation of OsNF-YC10 in DR610 is likely to be the underlying genetic basis of its narrow grain. To determine the correlation between OsNF-YC10 variation and grain width, we analyzed the natural variation of OsNF-YC10 in more than 4000 rice germplasm accessions and its correlation with grain width. 【Result】 A total of 10 major OsNF-YC10 haplotypes were identified with HG7(Hap1) being the predominant haplotype (1464/1509) in japonica rice (1464 of 1509 accessions). The Hap5 (represented by DR610) contains a C(HapC)→T(HapT) nonsense mutation at nucleotide site 1048. The grain width of rice varieties with HapC (3.036 mm, n=1596) was significantly wider than that of HapT (2.938 mm, n= 309), indicating that this natural variation significantly affected the grain width. Further analysis showed that Hap1 and Hap5 are significantly differentiated between japonica and indica, with the latter mainly distributed in the low latitude regions. A molecular marker to distinguish C→T variants was developed using four tetra-primer ARMARMS-PCR, which can be used for marker-assisted selection of grain type. 【Conclusion】 In summary, this study determined the natural variation of OsNF-YC10, which is significantly correlated with the grain width. The finding is of importance to providing an important reference for breeding by design of grain type and weight in rice.
Key words: grain size; grain width; 1000-grain weight; QTL-seq; genotyping; tetra-primer ARMS-PCR
CHEN Jiale, YU Qingtao, ZHENG Chenfan, WANG Qing, TAN Yuanyuan, CHEN Baicui, LI Chengxin, JIANG Meng, SHU Qingyao . Natural Variation of OsNF-YC10 and Its Correlation with Grain Width in Rice[J]. Chinese Journal OF Rice Science, 2025 , 39(4) : 552 -562 . DOI: 10.16819/j.1001-7216.2025.240713
| [1] | Xing Y Z, Zhang Q. Genetic and molecular bases of rice yield[J]. Annual Review of Plant Biology, 2010, 61(1): 421-442. |
| [2] | Yang W F, Zhan P L, Lin S J, Gou Y J, Zhang G Q, Wang S K. Research progress of grain shape genetics in rice[J]. Journal of South China Agricultural University, 2019, 40(5): 203-210. |
| [3] | Li G M, Tang J Y, Zheng J K, Chu C C. Exploration of rice yield potential: Decoding agronomic and physiological traits[J]. The Crop Journal, 2021, 9(3): 577-589. |
| [4] | 李堂, 曹华盛, 熊亮, 王福军, 李曙光, 顾海永, 罗文永, 何高, 梁世胡. 水稻粒型调控基因功能研究进展[J]. 广东农业科学, 2023, 50(12): 12-28. |
| Li T, Cao H S, Xiong L, Wang F J, Li S G, Gu H Y, Luo W Y, He G, Liang S H. Research progress on the function of rice grain type genes[J]. Guangdong Agricultural Sciences, 2023, 50(12): 12-28. (in Chinese with English abstract) | |
| [5] | Zuo J R, Li J Y. Molecular genetic dissection of quantitative trait loci regulating rice grain size[J]. Annual Review of Genetics, 2014, 48: 99-118. |
| [6] | Li N, Xu R, Li Y H. Molecular networks of seed size control in plants[J]. Annual Review of Plant Biology, 2019, 70: 435-463. |
| [7] | Ren D Y, Ding C Q, Qian Q. Molecular bases of rice grain size and quality for optimized productivity[J]. Science Bulletin, 2023, 68(3): 314-350. |
| [8] | Jia S Z, Xiong Y F, Xiao P P, Wang X, Yao J L. OsNF-YC10, a seed preferentially expressed gene regulates grain width by affecting cell proliferation in rice[J]. Plant Science, 2019, 280: 219-227. |
| [9] | Si L Z, Chen J Y, Huang X H, Gong H, Luo J H, Hou Q Q, Zhou T Y, Lu T Q, Zhu J J, Shangguan Y Y, Chen E W, Gong C X, Zhao Q, Jing Y F, Zhao Y, Li Y, Cui L L, Fan D L, Lu Y Q, Weng Q J, Wang Y C, Zhan Q L, Liu K Y, Wei X H, An K, An G, Han B. OsSPL13 controls grain size in cultivated rice[J]. Nature Genetics, 2016, 48(4): 447-456. |
| [10] | Yuan H, Qin P, Hu L, Zhan S J, Wang S F, Gao P, Li J, Jin M Y, Xu Z Y, Gao Q, Du A P, Tu B, Chen W L, Ma B T, Wang Y P, Li S G. OsSPL18 controls grain weight and grain number in rice[J]. Journal of Genetics and Genomics, 2019, 46(1): 41-51. |
| [11] | Huang J P, Chen Z M, Lin J J, Chen J W, Wei M H, Liu L, Yu F, Zhang Z S, Chen F Y, Jiang L R, Zheng J S, Wang T S, Chen H Y, Xie W Y, Huang S H, Wang H C, Huang Y M, Huang R Y. Natural variation of the BRD2 allele affects plant height and grain size in rice[J]. Planta, 2022, 256(2): 27. |
| [12] | Yan Y, Wei M X, Li Y, Tao H, Wu H Y, Chen Z F, Li C, Xu J H. MiR529a controls plant height, tiller number, panicle architecture and grain size by regulating SPL target genes in rice (Oryza sativa L.)[J]. Plant Science, 2021, 302: 110728. |
| [13] | Li R S, Li Z, Ye J, Yang Y Y, Ye J H, Xu S L, Liu J R, Yuan X P, Wang Y P, Zhang M C, Yu H Y, Xu Q, Wang S, Yang Y L, Wang S, Wei X H, Feng Y. Identification of SMG3, a QTL coordinately controls grain size, grain number per panicle, and grain weight in rice[J]. Frontiers in Plant Science, 2022, 13: 880919. |
| [14] | Takagi H, Abe A, Yoshida K, Kosugi S, Natsume S, Mitsuoka C, Uemura A, Utsushi H, Tamiru M, Takuno S, Innan H, Cano L M, Kamoun S, Terauchi R. QTL-seq: Rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations[J]. The Plant Journal, 2013, 74(1): 174-183. |
| [15] | Bommisetty R, Chakravartty N, Bodanapu R, Naik J B, Panda S K, Lekkala S P, Lalam K, Thomas G, Mallikarjuna S J, Eswar G R, Kadambari G M, Bollineni S N, Issa K, Akkareddy S, Srilakshmi C, Hariprasadreddy K, Rameshbabu P, Sudhakar P, Gupta S, Lachagari V B R, Vemireddy L R. Discovery of genomic regions and candidate genes for grain weight employing next generation sequencing based QTL-seq approach in rice (Oryza sativa L.)[J]. Molecular Biology Reports, 2020, 47(11): 8615-8627. |
| [16] | Bommisetty R, Chakravartty N, Hariprasad K R, Rameshbabu P, Sudhakar P, Bodanapu R, Naik J B, Bhaskar Reddy B V, Lekkala S P, Gupta S, Tanti B, Lachagari V B R, Vemireddy L R. Identification of a novel QTL for grain number per panicle employing NGS-based QTL-seq approach in rice (Oryza sativa L.)[J]. Plant Biotechnology Reports, 2023, 17(2): 191-201. |
| [17] | 王豪, 张健, 王加峰, 杨瑰丽, 郭涛, 陈志强, 王慧. 基于QTL-seq的水稻粒质量QTL定位及候选基因分析[J]. 华北农学报, 2020, 35(2): 18-28. |
| Wang H, Zhang J, Wang J F, Yang G L, Guo T, Chen Z Q, Wang H. QTL Mapping and candidate gene analysis of rice grain weight based on QTL-seq. Acta Agriculturae Boreali-Sinica, 2020, 35(2): 18-28. (in Chinese with English abstract) | |
| [18] | Sun H Z, Yuan Z K, Li F H, Zhang Q Q, Peng T, Li J Z, Du Y X. Mapping of qChalk1 controlling grain chalkiness in japonica rice[J]. Molecular Biology Reports, 2023, 50(7): 5879-5887. |
| [19] | Yuan H, Xu Z Y, Tan X Q, Gao P, Jin M Y, Song W C, Wang S G, Kang Y H, Liu P X, Tu B, Wang Y P, Qin P, Li S G, Ma B T, Chen W L. A natural allele of TAW1 contributes to high grain number and grain yield in rice[J]. The Crop Journal, 2021, 9(5): 1060-1069. |
| [20] | Alexandrov N, Tai S, Wang W, Mansueto L, Palis K, Fuentes R R, Ulat V J, Chebotarov D, Zhang G, Li Z, Mauleon R, Hamilton R S, McNally K L. SNP-Seek database of SNPs derived from 3000 rice genomes[J]. Nucleic Acids Research, 2015, 43(D1): D1023-D1027. |
| [21] | Zhao H, Yao W, Ouyang Y D, Yang W N, Wang G W, Lian X M, Xing Y Z, Chen L L, Xie W B. RiceVarMap: A comprehensive database of rice genomic variations[J]. Nucleic Acids Research, 2015, 43(D1): D1018-D1022. |
| [22] | Chen S, Zhou Y, Chen Y, Gu J. Fastp: An ultra-fast all-in-one FASTQ preprocessor[J]. Bioinformatics, 2018, 34(17): i884-i890. |
| [23] | Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform[J]. Bioinformatics, 2009, 25(14): 1754-1760. |
| [24] | Danecek P, Bonfield J K, Liddle J, Marshall J, Ohan V, Pollard M O, Whitwham A, Keane T, McCarthy S A, Davies R M, Li H. Twelve years of SAMtools and BCFtools[J]. GigaScience, 2021, 10(2): giab008. |
| [25] | McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo M A. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data[J]. Genome Research, 2010, 20(9): 1297-1303. |
| [26] | Abe A, Kosugi S, Yoshida K, Natsume S, Takagi H, Kanzaki H, Matsumura H, Yoshida K, Mitsuoka C, Tamiru M, Innan H, Cano L, Kamoun S, Terauchi R. Genome sequencing reveals agronomically important loci in rice using MutMap[J]. Nature Biotechnology, 2012, 30(2): 174-178. |
| [27] | Altschul S F, Madden T L, Schäffer A A, Zhang J, Zhang Z, Miller W, Lipman D J. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs[J]. Nucleic Acids Research, 1997, 25(17): 3389-3402. |
| [28] | Medrano R F V, de Oliveira C A. Guidelines for the Tetra-primer ARMS-PCR technique development[J]. Molecular Biotechnology, 2014, 56(7): 599-608. |
| [29] | Zhang K, Calabrese P, Nordborg M, Sun F Z. Haplotype block structure and its applications to association studies: power and study designs[J]. The American Journal of Human Genetics, 2002, 71(6): 1386-1394. |
/
| 〈 |
|
〉 |