研究报告

利用QTL-Seq结合分子标记定位粳稻垩白粒率控制位点qChalk8

展开
  • 河南农业大学 农学院,郑州 450046

收稿日期: 2023-12-13

  修回日期: 2024-03-18

  网络出版日期: 2024-11-15

基金资助

河南省自然科学基金资助项目(232300421156);河南现代农业水稻产业技术体系项目(HARS-22-03-G3)

Mapping of qChalk8 Controlling Chalky Rice Rate in japonica Rice by Combining QTL-Seq with Molecular Markers

Expand
  • College of Agronomy, Henan Agricultural University, Zhengzhou 450046

Received date: 2023-12-13

  Revised date: 2024-03-18

  Online published: 2024-11-15

摘要

【目的】垩白是影响稻米外观品质的重要性状。本研究旨在利用QTL-Seq和分子标记作图定位粳稻垩白粒率调控相关的QTL。【方法】利用高垩白粒率粳稻材料拉木加和低垩白粒率粳稻品种水晶3号构建F2分离群体,将两份独立的F2群体分别种植于河南原阳和海南三亚,两个群体单株垩白粒率考种后分别选取极端个体混池进行QTL-Seq分析,然后使用分子标记作图对稳定的QTL进行验证。【结果】两个F2群体的QTL-Seq分析发现8号染色体存在一个较为稳定的QTL位点qChalk8。进一步通过分子标记作图将该QTL定位于17.6-18.5 Mb,该QTL位点的LOD值为7.08,表型贡献率为15.9%。【结论】利用QTL-Seq和分子标记作图定位了粳稻垩白粒率相关QTL-qChalk8,为粳稻垩白调控基因进一步的精细定位和基因克隆奠定了基础。

本文引用格式

杜彦修, 孙文玉, 袁泽科, 张倩倩, 李富豪, 李俊周, 孙红正 . 利用QTL-Seq结合分子标记定位粳稻垩白粒率控制位点qChalk8[J]. 中国水稻科学, 2024 , 38(6) : 665 -671 . DOI: 10.16819/j.1001-7216.2024.231207

Abstract

【Objective】Chalkiness is an important characteristic that affects the appearance quality of rice grains. This study aims to use QTL-Seq and molecular marker mapping methods to locate QTLs related to chalky rice rates in japonica rice.【Method】F2 segregating populations were constructed using the japonica germplasm Lamujia with a high chalky rice rate and the japonica variety Shuijing 3 with a low chalky rice rate. Two independent F2 populations were planted in Yuanyang, Henan Province, and Sanya, Hainan Province, respectively. The single-plant chalky rice rate was examined, and extreme individuals were pooled for QTL-Seq analysis. Reliable QTLs were then subjected to verification using molecular marker mapping.【Result】QTL-Seq analysis of the two F2 populations revealed the existence of a stable chalky rice rate QTL on chromosome 8, designated as qChalk8. Further molecular marker mapping confined the QTL to a genomic region between 17.6 Mb and 18.5 Mb. The LOD score for qChalk8 was 7.08, and qChalk8 could explain 15.9% of the phenotypic variation.【Conclusion】QTL-Seq and molecular marker mapping successfully identified qChalk8 related to chalky rice rates in japonica rice. The localization of qChalk8 establishes a foundation for further fine mapping and gene cloning of the chalkiness regulatory gene in japonica rice.

参考文献

[1] Gann P J I, Dharwadker D, Cherati S R, Vinzant K, Khodakovskaya M, Srivastava V. Targeted mutagenesis of the vacuolar H+ translocating pyrophosphatase gene reduces grain chalkiness in rice[J]. Plant Journal, 2023, 115(5): 1261-1276.
[2] Misra G, Badoni S, Parween S, Singh R K, Leung H, Ladejobi O, Mott R, Sreenivasulu N. Genome-wide association coupled gene to gene interaction studies unveil novel epistatic targets among major effect loci impacting rice grain chalkiness[J]. Plant Biotechnology Journal, 2021, 19(5): 910-925.
[3] 邱颖欣, 董皓, 李懿星, 王天抗, 宋书锋, 李莉. 水稻垩白性状相关基因研究进展[J]. 杂交水稻, 2023, 38(4): 12-20.
  Qiu Y X, Dong H, Li Y X, Wang T K, Song S F, Li L. Research progress on genes related to chalkiness in rice[J]. Hybrid Rice, 2023, 38(4): 12-20. (in Chinese with English abstract)
[4] 柏晶晶, 胡文彬, 汪丽, 周政, 王立峰, 赵正洪, 何予卿. 水稻垩白主效QTL的定位与分析[J]. 湖南农业科学, 2021(12): 5-8.
  Bai J J, Hu W B, Wang L, Zhou Z, Wang L F, Zhao Z H, He Y Q. Major QTLs mapping and analysis for rice chalkiness[J]. Hunan Agricultural Sciences, 2021(12): 5-8. (in Chinese with English abstract)
[5] 施利利, 张欣, 丁得亮, 王松文, 崔晶. 垩白米含量与稻米品质的关系研究[J]. 食品科技, 2016, 41(9): 177-180.
  Shi L L, Zhang X, Ding D L, Wang S W, Cui J. Study on the relationship between chalky rice content and rice quality[J]. Food Science and Technology, 41(9): 177-180. (in Chinese with English abstract)
[6] Sreenivasulu N, Butardo V, Misra G, Cuevas R, Anacleto R, Kavi K P. Designing climate-resilient rice with ideal grain quality suited for high-temperature stress[J]. Journal of Experimental Botany, 2015, 66(7): 1737-1748.
[7] 王云霞, 杨连新. 水稻品质对主要气候变化因子的响应[J]. 农业环境科学学报, 2020, 39(4): 822-833.
  Wang Y X, Yang L X. Response of rice quality to major climate change factors[J]. Journal of Agro-Environment Science, 2020, 39(4): 822-833. (in Chinese with English abstract)
[8] 景立权, 户少武, 穆海蓉, 王云霞, 杨连新. 大气环境变化导致水稻品质总体变劣[J]. 中国农业科学, 2018, 51(13): 2462-2475.
  Jing L Q, Hu S W, Mu H R, Wang Y X, Yang L X. Change of atmospheric environment leads to deterioration of rice quality[J]. Scientia Agricultura Sinica, 2018, 51(13): 2462-2475. (in Chinese with English abstract)
[9] 张桂莲, 廖斌, 唐文帮, 陈立云, 肖应辉. 稻米垩白性状对高温耐性的QTL分析[J]. 中国水稻科学, 2017, 31(3): 257-264.
  Zhang G L, Liao B, Tang W B, Chen L Y, Xiao Y H. Identifying QTLs for thermo-tolerance of grain chalkiness trait[J]. Chinese Journal of Rice Science, 2017, 31(3): 257-264. (in Chinese with English abstract)
[10] Li Y, Fan C, Xing Y, Yun P, Luo L, Yan B, Peng B, Xie W, Wang G, Li X, Xiao J, Xu C, He Y. Chalk5 encodes a vacuolar H+-translocating pyrophosphatase influencing grain chalkiness in rice[J]. Nature Genetics, 2014, 46(4): 398-404.
[11] Yun P, Zhu Y, Wu B, Gao G, Sun P, Zhang Q, He Y. Genetic mapping and confirmation of quantitative trait loci for grain chalkiness in rice[J]. Molecular Breeding, 2016, 36(12): 162.
[12] Wu B, Yun P, Zhou H, Xia D, Gu Y, Li P, Yao J, Zhou Z, Chen J, Liu R, Cheng S, Zhang H, Zheng Y, Lou G, Chen P, Wan S, Zhou M, Li Y, Gao G, Zhang Q, Li X, Lian X, He Y. Natural variation in WHITE-CORE RATE 1 regulates redox homeostasis in rice endosperm to affect grain quality[J]. Plant Cell, 2022, 34(5): 1912-1932.
[13] Gao Y, Liu C, Li Y, Zhang A, Dong G, Xie L, Zhang B, Ruan B, Hong K, Xue D, Zeng D, Guo L, Qian Q, Gao Z. QTL analysis for chalkiness of rice and fine mapping of a candidate gene for qACE9[J]. Rice, 2016, 9(1): 41.
[14] Nguyen K, Grondin A, Courtois B, Gantet P. Next-generation sequencing accelerates crop gene discovery[J]. Trends in Plant Science, 2019, 24(3): 263-274.
[15] Zegeye W, Zhang Y, Cao L, Cheng S. Whole genome resequencing from bulked populations as a rapid QTL and gene identification method in rice[J]. International Journal of Molecular Sciences, 2018, 19(12): 4000.
[16] Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform[J]. Bioinformatics, 2009, 25(14): 1754-1760.
[17] McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo M. The genome analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data[J]. Genome Research, 2010, 20(9): 1297-1303.
[18] Mansfeld B, Grumet R. QTLseqr: An R package for bulk segregant analysis with next-generation sequencing[J]. Plant Genome, 2018, 11(2): 180006.
[19] Wang K, Li M, Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data[J]. Nucleic Acids Research, 2010, 38(16): e164.
[20] Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth B, Remm M, Rozen S. Primer3: New capabilities and interfaces[J]. Nucleic Acids Research, 2012, 40(15): e115.
[21] Meng L, Li H, Zhang L, Wang J. QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations[J]. The Crop Journal, 2015, 3(3): 269-283.
[22] Jiang L, Zhong H, Jiang X, Zhang J, Huang R, Liao F, Deng Y, Liu Q, Huang Y, Wang H, Tao Y, Zheng J. Identification and pleiotropic effect analysis of GSE5 on rice chalkiness and grain shape[J]. Frontiers in Plant Science, 2021, 12: 814928.
[23] 严旭, 左艳春, 王红林, 李杨, 李影正, 寇晶, 周晓康, 唐祈林, 杜周和. 禾本科三倍体:形成、鉴定与利用[J]. 植物学报, 2021, 56(3): 372-387.
  Yan X, Zuo Y C, Wang H L, Li Y, Li Y Z, Kou J, Zhou X K, Tang Q L, Du Z H. Triploid in Poaceae: Formation, detection, and utilization[J]. Chinese Bulletin of Botany, 2021, 56(3): 372-387.
[24] Yang W, Xiong L, Liang J, Hao Q, Luan X, Tan Q, Lin S, Zhu H, Liu G, Liu Z, Bu S, Wang S, Zhang G. Substitution mapping of two closely linked QTLs on chromosome 8 controlling grain chalkiness in rice[J]. Rice, 2021, 14(1): 85.
[25] Qiu X, Chen K, Lü W, Ou X, Zhu Y, Xing D, Yang L, Fan F, Yang J, Xu J, Zheng T, Li Z. Examining two sets of introgression lines reveals background-independent and stably expressed QTL that improve grain appearance quality in rice (Oryza sativa L.)[J]. Theoretical and Applied Genetics, 2017, 130(5): 951-967.
[26] Zhao X, Daygon V, McNally K, Hamilton R, Xie F, Reinke R, Fitzgerald M. Identification of stable QTLs causing chalk in rice grains in nine environments[J]. Theoretical and Applied Genetics, 2016, 129(1): 141-153.
[27] Li J, Yang H, Xu G, Deng K, Yu J, Xiang S, Zhou K, Zhang Q, Li R, Li M, Ling Y, Yang Z, He G, Zhao F. QTL analysis of Z414, a chromosome segment substitution line with short, wide grains, and substitution mapping of qGL11 in rice[J]. Rice, 2022, 15(1): 25.
文章导航

/

浙ICP备05004719号-5
公安备案号:33010302003356
地址:浙江省杭州市富阳区水稻所路28号 邮编:311400 电话:0571-63370278 E-mail:cjrs@263.net
本系统由北京玛格泰克科技发展有限公司设计开发
总访问量: 今日访问: 在线人数: