利用龙稻5号/中优早8号RIL群体定位粒形QTL

doi:10.16819/j.1001-7216.2024.230602

中国水稻科学 ›› 2024, Vol. 38 ›› Issue (1): 13-24.DOI: 10.16819/j.1001-7216.2024.230602

利用龙稻5号/中优早8号RIL群体定位粒形QTL

侯本福¹^,²^,³, 杨传铭¹^,²^,³, 张喜娟²^,⁵, 杨贤莉²^,⁵, 王立志²^,⁵, 王嘉宇⁴, 李红宇¹^,^*(), 姜树坤²^,³^,⁵^,^*()

¹黑龙江八一农垦大学农学院, 黑龙江大庆 163319
²黑龙江省农业科学院耕作栽培研究所/黑龙江省寒地作物生理生态重点实验室/黑龙江省农作物低温冷害工程技术研究中心, 哈尔滨 150086
³黑龙江省农业科学院齐齐哈尔分院/黑龙江省松嫩平原西部作物种质资源创新与利用工程技术研究中心, 黑龙江齐齐哈尔 161006
⁴沈阳农业大学水稻研究所, 沈阳 110161
⁵国家耐盐碱水稻技术创新中心东北中心, 哈尔滨 150086

收稿日期:2023-05-13 修回日期:2023-07-14 出版日期:2024-01-10 发布日期:2024-01-16
通讯作者: * email: shukunjiang@haas.cn; ndrice@163.com
基金资助:
黑龙江省属科研院所科研业务费资助项目(CZKYF2022-1-B004);国家自然科学基金资助项目(32071889)

Mapping of Grain Shape QTLs Using RIL Population from Longdao 5/Zhongyouzao 8

HOU Benfu¹^,²^,³, YANG Chuanming¹^,²^,³, ZHANG Xijuan²^,⁵, YANG Xianli²^,⁵, WANG Lizhi²^,⁵, WANG Jiayu⁴, LI Hongyu¹^,^*(), JIANG Shukun²^,³^,⁵^,^*()

¹Agricultural College, Heilongjiang Bayi Agricultural University, Daqing 163319, China
²Crop Cultivation and Tillage Institute, Heilongjiang Academy of Agricultural Sciences/Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region/Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China
³Qiqihar Branch of Heilongjiang Academy of Agricultural Sciences/Heilongjiang Provincial Engineering Technology Research Center of Crop Germplasm Resources Innovation and Utilization in Songnen Plain, Qiqihar 161006, China
⁴Rice Research Institute, Shenyang Agricultural University, Shenyang 110161, China
⁵Northeast Center of National Salt-Alkali Tolerant Rice Technology Innovation Center, Harbin 150086, China

Received:2023-05-13 Revised:2023-07-14 Online:2024-01-10 Published:2024-01-16
Contact: * email: shukunjiang@haas.cn; ndrice@163.com

摘要/Abstract

摘要：

【目的】粒形是决定稻米产量、品质和商品价值的重要数量性状之一。本研究旨在利用水稻重组自交系群体鉴定控制粒形的QTL，为水稻粒形基因的挖掘和长粒形粳稻育种应用奠定基础。【方法】以短圆粒形的粳型超级稻品种龙稻5号（LD5）为母本和细长粒形的早熟籼稻品种中优早8号（ZYZ8）为父本构建包含176个家系的重组自交系群体测定粒长、粒宽、长宽比和粒厚等粒形性状，分析粒形性状间的关系并进行QTL定位和比较分析。【结果】利用区间作图法共检测到8个粒形QTL，分布在3、5、6、7和11号染色体上，表型贡献率范围为4.69%~18.89%，LOD值范围为2.52~8.74。这8个QTL包括3个粒长QTL qGL3、qGL7和qGL11，2个粒宽QTL qGW3和qGW5，2个粒厚QTL qGT3和qGT6，1个长宽比QTL qLWR3。其中，qGL3、qGL7、qGW3、qGW5和qLWR3可以在3个年份稳定检测到。利用多环境联合分析共检测到14个粒形QTL，包括qGL2、qGL3、qGL7和qGL11共4个粒长QTL；qGW3和qGW5共2个粒宽QTL；qGT3、qGT5和qGT6共3个粒厚QTL；qLWR3a、qLWR3b、qLWR5、qLWR7和qLWR11共5个长宽比QTL，分布在2、3、5、6、7和11号染色体上，表型贡献率范围为2.28%~15.78%，LOD值范围为4.20~20.90。与已克隆的粒形基因进行染色体位置比较发现，qGL3/qLWR3区间包含已克隆的GL3.1；qGW5区间包含已克隆的GW5；qLWR3b/qGT3区间包含已克隆的TGW3。【结论】利用区间作图法和多环境联合分析的方法从龙稻5号和中优早8号的重组自交系群体中共鉴定了14个粒形QTL，其中8个QTL是两种方法重复检测到的。这些QTL定位区间内包含已克隆的GL3.1、TGW3和GW5等粒形基因。

关键词: 水稻, 粒形, QTL定位, 分子辅助育种

Abstract:

【Objective】Grain shape significantly influences the yield, quality, and commercial value of rice. This study aimed to identify Quantitative Trait Loci (QTLs) controlling grain shape using a rice recombinant inbred line population, thereby facilitating the mining of rice grain shape genes and the breeding of long-grain japonica rice. 【Method】 A population of 176 recombinant inbred lines was developed by crossing the japonica super rice variety Longdao 5 (LD5) with short round grain and the early maturing indica rice variety Zhongyouzao 8(ZYZ8) with long slender grain. Grain shape traits, including grain length(GL), grain width(GW), grain length to width ratio(LWR), and grain thickness(GT), were measured for three years using Smart Grain software, and the interrelationship between these traits was analyzed. Complete Interval Mapping (CIM) and Multi-Environment Trials (MET) were employed for QTL mapping and comparative analysis. 【Result】 Eight QTLs, comprising three for grain length (qGL3, qGL7, and qGL11), two for grain width (qGW3 and qGW5), two for grain thickness (qGT3 and qGT6), and one for grain length to width ratio (qLWR3), were identified on chromosomes 3, 5, 6, 7, and 11 using the CIM method. These QTLs explained 4.69%−18.89% of the phenotypic variation, with an LOD range from 2.52 to 8.74. Additionally, qGL3, qGL7, qGW3, qGW5, and qLWR3 were consistently detected over three years. Fourteen QTLs, including four for grain length, two for grain width, three for grain thickness, and five for grain length to width ratio, were detected on chromosomes 2, 3, 5, 6, 7, and 11 using the MET method. These QTLs explained 2.28%−15.78% of the phenotypic variation, with an LOD range from 4.20 to 20.90. Comparison with cloned grain shape genes revealed the proximity of qGL3/qLWR3a to GL3.1, qGW5 to GW5, and qLWR3b/qGT3 to TGW3. 【Conclusion】 A total of 8 and 14 grain shape QTLs were identified using the CIM and MET methods, respectively, including three cloned grain shape genes (GL3.1, TGW3, and GW5).

Key words: rice, panicle shape, QTL mapping, molecular-marker assisted breeding

侯本福, 杨传铭, 张喜娟, 杨贤莉, 王立志, 王嘉宇, 李红宇, 姜树坤. 利用龙稻5号/中优早8号RIL群体定位粒形QTL[J]. 中国水稻科学, 2024, 38(1): 13-24.

HOU Benfu, YANG Chuanming, ZHANG Xijuan, YANG Xianli, WANG Lizhi, WANG Jiayu, LI Hongyu, JIANG Shukun. Mapping of Grain Shape QTLs Using RIL Population from Longdao 5/Zhongyouzao 8[J]. Chinese Journal OF Rice Science, 2024, 38(1): 13-24.

图/表 8

参考文献 45

[1]	陈燕红, 胡标林, 张帆涛. 稻米品质遗传分析研究现状[J]. 中国稻米, 2023, 29(1): 44-54.
	Cheng Y H, Hu B L, Zhang F T. Research status of genetic analysis of rice quality[J]. China Rice, 2023, 29(1): 44-54. (in Chinese with English abstract)
[2]	李苗苗, 李儒香, 秦鱼河, 余金琎, 徐光益, 向思茜, 杨正林, 桑贤春, 凌英华, 何光华, 赵芳明. 基于水稻矮秆长粒CSSL-Z688的QTL鉴定及SSSLs培育[J]. 西南大学学报: 自然科学版, 2023, 45(1): 33-44.
	Li M M, Li R X, Qin Y H, Yu J J, Xu G Y, Xiang S Q, Yang Z L, Sang X C, Ling Y H, He G H, Zhao F M. Identification of QTL based on a dwarf and long-large grain rice CSSL-Z688 and development of SSSLs[J]. Journal of Southwest University: Natural Science Edition, 2023, 45(1): 33-44. (in Chinese with English abstract)
[3]	李金吉, 张银霞, 赵娜, 田蕾, 杨淑琴, 李培富. 水稻粒形与千粒质量的QTL分析[J]. 西北农林科技大学学报: 自然科学版, 2021, 49(2): 54-60.
	Li J J, Zhang Y X, Zhao N, Tian L, Yang S Q, Li P F. QTL analysis of rice grain shape and thousand-grain weight[J]. Journal of Northwest A & F University: Natural Science Edition, 2021, 49(2): 54-60. (in Chinese with English abstract)
[4]	郑跃滨, 李智, 赵海燕, 朱光枫, 廖芷依, 竺正航, 王兰. 水稻粒长QTL定位与主效基因的遗传分析[J]. 西北植物学报, 2020, 40(4): 598-604.
	Zheng Y B, Li Z, Zhao H Y, Zhu G F, Liao Z Y, Zhu Z H, Wang L. Mapping quantitative trait loci associated with grain length and genetic analysis of major quantitative loci in rice[J]. Acta Botanica Boreali-Occidentalia Sinica, 2020, 40(4): 598-604. (in Chinese with English abstract)
[5]	Zhou Y, Hou J, Li P B, Yang H Y, Xia D, Zhou H, Alam M, Gao G J, Zhang Q L, He Y Q. Genetic dissection and validation of QTLs for grain shape and weight in rice and fine mapping of qGL1.3, a major QTL for grain length and weight[J]. Molecular Breeding, 2019, 39(12): 1-11.
[6]	向思茜, 李儒香, 徐光益, 邓岢莉, 余金琎, 李苗苗, 杨正林, 凌英华, 桑贤春, 何光华, 赵芳明. 基于水稻长大粒染色体片段代换系Z66的粒形QTL的鉴定及其聚合分析[J]. 作物学报, 2023, 49(3): 731-743.
	Xiang S Q, Li R X, Xu Gu Y, Deng K L, Yu J J, Li M M, Yang Z L, Ling Y H, Sang X C, He G H, Zhao F M. Identification and pyramid analysis of QTLs for grain size based on rice long-large-grain chromosome segment substitution line Z66[J]. Acta Agronomica Sinica, 2023, 49(3): 731-743. (in Chinese with English abstract)
[7]	梁文化, 陈涛, 姚姝, 赵凌, 朱镇, 赵庆勇, 周丽慧, 赵春芳, 路凯, 赫磊, 王才林, 张亚东. 基于高密度遗传图谱定位水稻籽粒长宽比QTL[J]. 江苏农业科学, 2021, 49(23): 47-52.
	Liang W H, Chen T, Yao Z, Zhao L, Zhu Z, Zhao Q Y, Zhou L H, Zhao C F, Lu K, Hao L, Wang C L, Zhang Y D. QTL mapping for grain length-width ratio based on high-density genetic map in rice[J]. Jiangsu Agricultural Sciences, 2021, 49(23): 47-52. (in Chinese with English abstract)
[8]	周梦玉, 宋昕蔚, 徐静, 付雪, 李婷, 朱雨晨, 肖幸运, 毛一剑, 曾大力, 胡江, 朱丽, 任德勇, 高振宇, 郭龙彪, 钱前, 吴明国, 林建荣, 张光恒. 籼稻C84和粳稻春江16B重组自交系遗传图谱构建及籽粒性状QTL定位与验证[J]. 中国水稻科学, 2018, 32(3): 207-218.
	Zhou M Y, Song X W, Xu J, Fu X, Li T, Zhu Y H, Xiao X Y, Mao Y J, Zeng D L, Hu J, Zhu L, Ren D Y, Gao Z Y, Guo L B, Qian Q, Wu M G, Lin J R, Zhang G H. Construction of genetic map and mapping and verification of grain traits QTLs using recombinant inbred lines derived from a cross between indica C84 and japonica CJI6B[J]. Chinese Journal of Rice Science, 2018, 32(3): 207-218. (in Chinese with English abstract)
[9]	宋博文, 王朝欢, 赵哲, 陈淳, 黄明, 陈伟雄, 梁克勤, 肖武名. 基于高密度遗传图谱对水稻粒形QTL定位及分析[J]. 作物学报, 2022, 48(11): 2813-2829.
	Song B W, Wang C H, Zhao Z, Chen C, Huang M, Chen W X, Liang K Q, Xiao W M. Mapping and analysis of QTLs for grain size in rice based on high density genetic map[J]. Acta Agronomica Sinica, 2022, 48(11): 2813-2829. (in Chinese with English abstract)
[10]	姚晓云, 陈春莲, 熊运华, 黄永萍, 彭志勤, 刘进, 尹建华. 水稻加工和外观品质性状QTL鉴定[J]. 中国水稻科学, 2023, 37 (5): 507-517.
	Yao X Y, Chen C L, Xiong Y H, Huang Y P, Peng Z Q, Liu J, Yin J H. Identification of QTL for milling and appearance quality traits in rice(Oryza sativa L.)[J]. Acta Agronomica Sinica, 2023, 37(5): 507-517. (in Chinese with English abstract)
[11]	Fan C C, Xing Y Z, Mao H L, Lu T T, Han B, Xu C G, Li X H, Zhang Q. GS3, a major OTL for grain length and weight and minor OTL for grain width and thickness in rice encodes a putative transmembrane protein[J]. Theoretical and Applied Genetics, 2006, 112(6): 1164-1171.
[12]	Wang Y X, Xiong G S, Hu J, Jiang L, Yu H, Xu J, Fang Y X, Zeng L J, Xu E B, Xu J, Ye W J, Meng X B, Liu R F, Chen H Q, Jing Y H, Wang Y H, Zhu X D, Li J Y, Qian Q. Copy number variation at the GL7 locus contributes to grain size diversity in rice[J]. Nature Genetics, 2015, 47(8): 944-948.
[13]	Wu W G, Liu X Y, Wang M H, Meyer R S, Zhu Z F. A single-nucleotide polymorphism causes smaller grain size and loss of seed shattering during African rice domestication[J]. Nature Plants, 2017, 3: 17064.
[14]	Xia D, Zhou N, Liu R J, Dan W H, Li P B, Wu B. GL3.3, a novel QTL encoding a GSK3/SHAGGY-like kinase, epistatically interacts with GS3 to Produce extra-long grains in rice[J]. Molecular Plant, 2018, 11(5): 754-756.
[15]	Hu Z J, Lu S J, Wang M J, He H H, Sun L, Wang H R, Lin X H, Jiang L, Sun J L, Xin X Y, Kong W, Chu C C, Xue H W, Yang J S, Lou X J, Liu J X. A novel QTL qTGW3 encodes the GSK3/SHAGGY-like kinase OsGSK5/OsSK41 that interacts with OsARF4 to negatively regulate grain size and weight in rice[J]. Molecular Plant, 2018, 11(5): 736-749.
[16]	Si L Z, Chen J Y, Huang X H, Gong H, Lou Q Q, Zhou T Y, Lu T T, 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, Han B. OsSPL13 controls grain size in cultivated rice[J]. Nature Genetics, 2016, 48: 447-456.
[17]	Zhan P L, Ma S P, Xiao Z L, Li F P, Wei X, Lin S J, Wang X L, Ji Z, Fu Y, Pan J H, Zhou M, Liu Y, Chang Z Y, Li L, Bu S H, Liu Z P, Zhu H T, Liu G F, Zhang G Q, Wang S K. Natural variations in grain length 10(GL10) regulate rice grain size[J]. Journal of Genetics and Genomics, 2022, 49(5): 405-413.
[18]	Zhao D S, Li Q F, Zhang C Q, Zhang C, Yang Q Q, Pan L X, Ren X Y, Lu J, Gu M H, Liu Q Q. GS9 acts as a transcriptional activator to regulate rice grain shape and appearance quality[J]. Nature Communications, 2018, 9(1): 1240.
[19]	Qi P, Lin Y S, Song X J, Shen J B, Huang W, Shan J X, Zhu M Z, Jiang L W, Gao J P, Lin H X. The novel quantitative trait locus GL3.1 controls rice grain size and yield by regulating Cyclin-T1;3[J]. Cell Research, 2012, 22(12): 1666-1680.
[20]	Song X J, Huang W, Shi M, Zhu M Z, Lin H X. A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase[J]. Nature Genetics, 2007, 39: 623-630.
[21]	Duan P G, Xu J S, Zeng D L, Zhang B L, Geng M F, Zhang G Z, Huang K, Huang L J, Xu R, Ge S, Qian Q, Li Y H. Natural variation in the promoter of GSE5 contributes to grain size diversity in rice[J]. Molecular Plant, 2017, 10(5): 685-694.
[22]	Wan X Y, Weng J F, Zhai H Q, Wang J K, Lei C L, Liu X L, Guo T, Jiang L, Su N, Wan J M. Quantitative trait loci (QTL) analysis for rice grain width and fine mapping of an identified QTL allele gw-5 in a recombination hotspot region on chromosome 5[J]. Genetics, 2008, 179(4): 2239-2252.
[23]	Shomura A, Izawa T, Ebana K, Takeshi E, Hiromi K, Saeko K, Masahiro Y. Deletion in a gene associated with grain size increased yields during rice domestication[J]. Nature Genetics, 2008, 40(8): 1023-1028.
[24]	Li Y B, Fan C C, Xing Y Z, Jiang Y H, Luo L J, Sun L, Shao D, Xu C J, Li X H, Xiao J H, He Y Q, Zhang Q F. Natural variation in GS5 plays an important role in regulating grain size and yield in rice[J]. Nature Genetics, 2011, 43(12): 1266-1269.
[25]	Wang S K, Wu K, Yuan Q B, Liu Z B, Lin X Y, Zeng R Z, Zhu H T, Dong G J, Qian Q, Zhang G Q, Fu X D. Control of grain size, shape and quality by OsSPL16 in rice[J]. Nature Genetics, 2012, 44(8): 950-954.
[26]	Liu D P, Zhao H, Xiao Y H, Zhang G X, Cao S Y, Yin W C, Qian Y W, Yin Y H, Zhang J S, Chen S Y, Chu C C. A cryptic inhibitor of cytokinin phosphorelay controls rice grain size[J]. Molecular Plant, 2022, 15(2): 293-307.
[27]	Liu D P, Yu Z K, Zhang G X, Yin W C, Li L L, Niu M, Meng W J, Zhang X X, Dong N N, Liu J H, Yang Y Z, Wang S M, Chu C C, Tong H N. Diversification of plant agronomic traits by genome editing of brassinosteroid signaling family genes in rice[J]. Plant Physiology, 2021, 187(4): 2563-2576.
[28]	Zhang X J, Wang J F, Huang J, Lan H X, Wang C L, Yin C F, Wu Y Y, Tang H J, Qian Q, Li J Y, Zhang H S. Rare allele of OsPPKL1 associated with grain length causes extra-large grain and a significant yield increase in rice[J]. Proceedings of the National Academy of Sciences, 2012, 109(52): 21534-21539.
[29]	胡慧, 高若愚, 李志新, 徐俊英, 杨隆维, 田雨, 邱先进, 徐建龙. 利用双向导入系定位再生稻外观品质的QTL[J]. 核农学报, 2023, 37(2): 262-273.
	Hu H, Gao R Y, Li Z X, Xu J Y, Yang L W, Tian Y, Qiu X J, Xu J L. QTL identification of appearance quality of ratoon rice using two sets of reciprocal introgression lines[J]. Journal of Nuclear Agricultural Sciences, 2023, 37(2): 262-273. (in Chinese with English abstract)
[30]	Tanabata T, Shibaya T, Hori K, Ebana K, Yano M. SmartGrain: High-throughput phenotyping software for measuring seed shape through image analysis[J]. Plant Physiology, 2012, 160(4): 1871-1880.
[31]	Murray M G, Thompson W F. Rapid isolation of high molecular weight plant DNA[J]. Nucleic Acids Research, 1980, 8(19): 4321-4325.
[32]	刘进, 姚晓云, 刘丹, 余丽琴, 李慧, 王棋, 王嘉宇, 黎毛毛. 不同生态环境下水稻穗部性状QTL鉴定[J]. 中国水稻科学, 2019, 33(2): 124-134.
	Liu J, Yao X Y, Liu D, Xu L Q, Li H, Wang Q, Wang J Y, Li M M. Identification of QTL for panicle traits under multiple environments in rice(Oryza sativa L.)[J]. Acta Agronomica Sinica, 2019, 33(2): 124-134. (in Chinese with English abstract)
[33]	McCouch S R. Gene nomenclature system for rice[J]. Rice, 2008, 1(1): 72-84.
[34]	丁膺宾, 张莉珍, 许睿, 王艳艳, 郑晓明, 张丽芳, 程云连, 吴凡, 杨庆文, 乔卫华, 兰进好. 基于染色体片段置换系的野生稻粒长QTL——qGL12的精细定位[J]. 中国农业科学, 2018, 51(18): 3435-3444.
	Ding Y B, Zhang L Z, Xu R, Wang Y Y, Zheng X M, Zhang L F, Cheng Y L, Wu F, Yang Q W, Qiao W H, Lan J H. Fine mapping of grain length associated QTL, qGL12 in wild rice using a chromosome segment substitution line[J]. Scientia Agricultura Sinica, 2018, 51(18): 3435-3444. (in Chinese with English abstract)
[35]	张波, 裴瑞琴, 杨维丰, 朱海涛, 刘桂富, 张桂权, 王少奎. 利用单片段代换系鉴定巴西陆稻IAPAR9中的粒形基因[J]. 作物学报, 2021, 47(8): 1472-1480.
	Zhang B, Pei R Q, Yang W F, Zhu H T, Liu G F, Zhang G Q, Wang S K. Mapping and identification QTLs controlling grain size in rice (Oryza sativa L.) by using single segment substitution lines derived from IAPAR9[J]. Acta Agronomica Sinica, 2021, 47(8): 1472-1480. (in Chinese with English abstract)
[36]	Ponce K, Zhang Y, Guo L B, Leng Y J, Ye G Y. Genome-wide association study of grain size traits in indica rice multiparent advanced generation intercross (MAGIC) population[J]. Frontiers in Plant Science, 2020, 11(24): 395.
[37]	张亚东, 梁文化, 赫磊, 赵春芳, 朱镇, 陈涛, 赵庆勇, 赵凌, 姚姝, 周丽慧, 路凯, 王才林. 水稻RIL群体高密度遗传图谱构建及粒形QTL定位[J]. 中国农业科学, 2021, 54(24): 5163-5176.
	Zhang Y D, Liang W H, He L, Zhao C F, Zhu Z, Chen T, Zhao Q Y, Zhao L, Yao S, Zhou L H, Lu K, Wang C L. Construction of high-density genetic map and QTL analysis of grain shape in rice RIL population[J]. Scientia Agricultura Sinica, 2021, 54(24): 5163-5176. (in Chinese with English abstract)
[38]	黄涛, 王燕宁, 钟奇, 程琴, 杨朦朦, 王鹏, 吴光亮, 黄诗颖, 李才敬, 余剑峰, 贺浩华, 边建民. 利用染色体片段置换系群体定位和分析水稻粒重和粒形QTL[J]. 中国水稻科学, 2022, 36(2): 159-170.
	Huang T, Wang Y N, Zhong Q, Cheng Q, Yang M M, Wang P, Wu G L, Huang S Y, Li C J, Yu J F, He H H, Bian J M. Mapping and analysis of QTLs for rice grain weight and grain shape using chromosome segment substitution line population. Chinese Journal of Rice Science, 2022, 36(2): 159-170. (in Chinese with English abstract)
[39]	Chan A N, Wang L L, Zhu Y J, Fan Y Y, Zhuang J Y, Zhang Z H. Identification through fine mapping and verification using CRISPR/Cas9-targeted mutagenesis for a minor QTL controlling grain weight in rice[J]. Theoretical and Applied Genetics, 2021, 134(1): 327-337.
[40]	Ying J Z, Ma M, Bai C, Huang X, Liu J L, Fan Y Y, Song X J. TGW3, a major QTL that negatively modulates grain length and weight in rice[J]. Molecular Plant, 2018, 11(5): 750-753.
[41]	Ma M, Shen S Y, Bai C, Wang W Q, Feng X H, Ying J Z, Song X J. Control of grain size in rice by TGW3 phosphorylation of OsIAA10 through potentiation of OsIAA10-OsARF4-mediated auxin signaling[J]. Cell Reports, 2023, 42(3): 112187.
[42]	Xia D, Zhou H, Liu R J, Dan W H, Li P B, Wu B, Chen J X, Wang L Q, Gao G J, Zhang Q L, He Y Q. GL3.3,a novel QTL encoding a GSK3/SHAGGY-like kinase, epistatically interacts with GS3 to produce extra-long grains in rice[J]. Molecular Plant, 2018, 11(5): 754-756.
[43]	Tian P, Liu J F, Mou C L, Shi C L, Zhang H, Zhao Z C, Lin Q B, Wang J, Wang J L, Zhang X, Guo X Z, Cheng Z J, Zhu S S, Ren Y L, Lei C L, Wang H Y, Wan J M. GW5-like, a homolog of GW5, negatively regulates grain width, weight and salt resistance in rice[J]. Journal of Integrative Plant Biology, 2019, 61(11): 1171-1185.
[44]	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.
[45]	刘进, 姚晓云, 王棋, 李慧, 王嘉宇, 黎毛毛. 不同生态环境下籽粒大小相关性状QTL定位[J]. 华北农学报, 2018, 33(2): 133-138.
	Liu J, Yao X Y, Wang Q, Li H, Wang J Y, Li M M. QTL mapping of seed size traits under different environment in rice[J]. Acta Agriculture Boerali-Sinica, 2018, 33(2): 133-138. (in Chinese with English abstract)

年份Year	性状 Trait	亲本 Parents		群体 Population
年份Year	性状 Trait	龙稻5号 Longdao 5	中优早8号 Zhongyouzao 8	平均值 Mean	群体区间 Range	偏度 Skewness	峰度 Kurtosis
2020	粒长 Grain length /mm	6.81±0.33	8.98±0.38**	8.18±0.62	6.43~9.65	0.11	−0.45
	粒宽 Grain width /mm	3.43±0.21	3.24±0.13**	3.30±0.25	2.65~3.94	0.05	−0.26
	粒厚 Grain thickness/mm	2.13±0.07	1.96±0.18*	1.98±0.15	1.53~2.33	−0.07	0.16
	长宽比 Length to width ratio	1.99±0.14	2.78±0.16**	2.50±0.26	1.91~3.38	0.48	0.33
2021	粒长 Grain length /mm	6.53±0.30	8.67±0.30**	7.73±0.59	6.24~9.30	0.08	−0.31
	粒宽 Grain width/mm	3.50±0.10	3.20±0.13**	3.28±0.26	2.68~3.89	0.02	−0.48
	粒厚 Grain thickness	2.10±0.04	1.93±0.22*	1.96±0.14	1.54~2.36	−0.11	0.03
	长宽比 Length to width ratio	1.86±0.08	2.72±0.13**	2.37±0.24	1.80~3.41	0.56	1.27
2022	粒长 Grain length/mm	6.86±0.27	9.04±0.24**	8.08±0.64	6.35~9.67	0.09	−0.53
	粒宽 Grain width /mm	3.48±0.15	3.22±0.17**	3.29±0.24	2.71~3.88	0.00	−0.53
	粒厚 Grain thickness /mm	2.08±0.08	1.92±0.06**	1.95±0.14	1.60~2.29	−0.01	−0.25
	长宽比 Length to width ratio	1.98±0.12	2.82±0.15**	2.48±0.26	1.87~3.48	0.53	0.94

年份Year	性状 Trait	亲本 Parents		群体 Population
年份Year	性状 Trait	龙稻5号 Longdao 5	中优早8号 Zhongyouzao 8	平均值 Mean	群体区间 Range	偏度 Skewness	峰度 Kurtosis
2020	粒长 Grain length /mm	6.81±0.33	8.98±0.38**	8.18±0.62	6.43~9.65	0.11	−0.45
	粒宽 Grain width /mm	3.43±0.21	3.24±0.13**	3.30±0.25	2.65~3.94	0.05	−0.26
	粒厚 Grain thickness/mm	2.13±0.07	1.96±0.18*	1.98±0.15	1.53~2.33	−0.07	0.16
	长宽比 Length to width ratio	1.99±0.14	2.78±0.16**	2.50±0.26	1.91~3.38	0.48	0.33
2021	粒长 Grain length /mm	6.53±0.30	8.67±0.30**	7.73±0.59	6.24~9.30	0.08	−0.31
	粒宽 Grain width/mm	3.50±0.10	3.20±0.13**	3.28±0.26	2.68~3.89	0.02	−0.48
	粒厚 Grain thickness	2.10±0.04	1.93±0.22*	1.96±0.14	1.54~2.36	−0.11	0.03
	长宽比 Length to width ratio	1.86±0.08	2.72±0.13**	2.37±0.24	1.80~3.41	0.56	1.27
2022	粒长 Grain length/mm	6.86±0.27	9.04±0.24**	8.08±0.64	6.35~9.67	0.09	−0.53
	粒宽 Grain width /mm	3.48±0.15	3.22±0.17**	3.29±0.24	2.71~3.88	0.00	−0.53
	粒厚 Grain thickness /mm	2.08±0.08	1.92±0.06**	1.95±0.14	1.60~2.29	−0.01	−0.25
	长宽比 Length to width ratio	1.98±0.12	2.82±0.15**	2.48±0.26	1.87~3.48	0.53	0.94

QTL	Chr.	标记区间 Marker interval	2020			2021						增效等位基因来源 Positive allele
QTL	Chr.	标记区间 Marker interval	LOD	表型贡献率Var./%	加性效应Add.	LOD	表型贡献率Var./%	加性效应 Add.	LOD	表型贡献率Var./%	加性效应 Add.	增效等位基因来源 Positive allele
qGL3	3	R3M30−RM3513	8.05	18.52	0.28	7.69	16.52	0.28	8.74	18.89	0.31	ZYZ8
qGL7	7	RM3404−RM11	2.90	5.37	0.16	3.33	5.73	0.16	2.90	5.30	0.16	ZYZ8
qGL11	11	RM1124−STS11.1	2.52	4.69	0.14							ZYZ8
qGW3	3	STS3.10−RM3684	4.46	9.53	−0.09	4.44	9.13	−0.09	4.03	8.54	−0.08	LD5
qGW5	5	R5M13−RM3476	3.20	7.48	−0.08	3.94	9.22	−0.09	3.21	7.8	−0.08	LD5
qGT3	3	RM503−RM700	3.21	8.05	−0.05	3.70	9.34	−0.04	2.76	6.36	−0.04	LD5
qGT6	6	RM3827−RM1340				2.53	6.09	0.04				ZYZ8
qLWR3a	3	R3M30−RM3513	5.34	12.46	0.10	5.76	13.33	0.10	6.10	14.33	0.11	ZYZ8

QTL	Chr.	标记区间 Marker interval	2020			2021						增效等位基因来源 Positive allele
QTL	Chr.	标记区间 Marker interval	LOD	表型贡献率Var./%	加性效应Add.	LOD	表型贡献率Var./%	加性效应 Add.	LOD	表型贡献率Var./%	加性效应 Add.	增效等位基因来源 Positive allele
qGL3	3	R3M30−RM3513	8.05	18.52	0.28	7.69	16.52	0.28	8.74	18.89	0.31	ZYZ8
qGL7	7	RM3404−RM11	2.90	5.37	0.16	3.33	5.73	0.16	2.90	5.30	0.16	ZYZ8
qGL11	11	RM1124−STS11.1	2.52	4.69	0.14							ZYZ8
qGW3	3	STS3.10−RM3684	4.46	9.53	−0.09	4.44	9.13	−0.09	4.03	8.54	−0.08	LD5
qGW5	5	R5M13−RM3476	3.20	7.48	−0.08	3.94	9.22	−0.09	3.21	7.8	−0.08	LD5
qGT3	3	RM503−RM700	3.21	8.05	−0.05	3.70	9.34	−0.04	2.76	6.36	−0.04	LD5
qGT6	6	RM3827−RM1340				2.53	6.09	0.04				ZYZ8
qLWR3a	3	R3M30−RM3513	5.34	12.46	0.10	5.76	13.33	0.10	6.10	14.33	0.11	ZYZ8

数量性状基因	染色体	标记区间	LOD值	表型贡献率	加性效应
QTL	Chr.	Marker interval	LOD value	Var./%	Add.
qGL2	2	RM6933―ID2	4.20	3.14	0.12
qGL3	3	R3M30―RM3513	20.90	15.78	0.26
qGL7	7	RM3404―RM11	8.26	5.02	0.15
qGL11	11	RM1124―STS11.1	8.51	5.85	0.16
qGW3	3	STS3.10―RM3684	6.20	4.55	―0.06
qGW5	5	STS5.2―RM3476	10.85	9.43	―0.08
qGT3	3	RM503―RM7000	6.83	5.26	―0.34
qGT5	5	R5M13―RM3476	4.84	4.37	―0.31
qGT6	6	RM3827―RM1340	5.07	3.85	0.29
qLWR3a	3	R3M30―RM3513	16.61	8.71	0.10
qLWR3b	3	STS3.10―RM3684	14.77	9.96	0.11
qLWR5	5	STS5.2―RM3476	4.64	2.01	0.05
qLWR7	7	RM3404―RM11	6.97	3.40	0.06
qLWR11	11	RM1124―STS11.1	4.99	2.28	0.05

利用龙稻5号/中优早8号RIL群体定位粒形QTL

Mapping of Grain Shape QTLs Using RIL Population from Longdao 5/Zhongyouzao 8

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 45

相关文章 15

编辑推荐

Metrics

[1]	汪邑晨, 朱本顺, 周磊, 朱骏, 杨仲南. 光/温敏核不育系的不育机理及两系杂交稻的发展与展望 [J]. 中国水稻科学, 2024, 38(5): 463-474.
[2]	许用强, 徐军, 奉保华, 肖晶晶, 王丹英, 曾宇翔, 符冠富. 水稻花粉管生长及其对非生物逆境胁迫的响应机理研究进展 [J]. 中国水稻科学, 2024, 38(5): 495-506.
[3]	何勇, 刘耀威, 熊翔, 祝丹晨, 王爱群, 马拉娜, 王廷宝, 张健, 李建雄, 田志宏. 利用CRISPR/Cas9技术编辑OsOFP30基因创制水稻粒型突变体 [J]. 中国水稻科学, 2024, 38(5): 507-515.
[4]	吕阳, 刘聪聪, 杨龙波, 曹兴岚, 王月影, 童毅, Mohamed Hazman, 钱前, 商连光, 郭龙彪. 全基因组关联分析(GWAS)鉴定水稻氮素利用效率候选基因 [J]. 中国水稻科学, 2024, 38(5): 516-524.
[5]	杨好, 黄衍焱, 王剑, 易春霖, 石军, 谭楮湉, 任文芮, 王文明. 水稻中八个稻瘟病抗性基因特异分子标记的开发及应用 [J]. 中国水稻科学, 2024, 38(5): 525-534.
[6]	杨铭榆, 陈志诚, 潘美清, 张汴泓, 潘睿欣, 尤林东, 陈晓艳, 唐莉娜, 黄锦文. 烟-稻轮作下减氮配施生物炭对水稻茎鞘同化物转运和产量形成的影响 [J]. 中国水稻科学, 2024, 38(5): 555-566.
[7]	熊家欢, 张义凯, 向镜, 陈惠哲, 徐一成, 王亚梁, 王志刚, 姚坚, 张玉屏. 覆膜稻田施用炭基肥对水稻产量及氮素利用的影响 [J]. 中国水稻科学, 2024, 38(5): 567-576.
[8]	郭展, 张运波. 水稻对干旱胁迫的生理生化响应及分子调控研究进展[J]. 中国水稻科学, 2024, 38(4): 335-349.
[9]	韦还和, 马唯一, 左博源, 汪璐璐, 朱旺, 耿孝宇, 张翔, 孟天瑶, 陈英龙, 高平磊, 许轲, 霍中洋, 戴其根. 盐、干旱及其复合胁迫对水稻产量和品质形成影响的研究进展[J]. 中国水稻科学, 2024, 38(4): 350-363.
[10]	许丹洁, 林巧霞, 李正康, 庄小倩, 凌宇, 赖美玲, 陈晓婷, 鲁国东. OsOPR10正调控水稻对稻瘟病和白叶枯病的抗性[J]. 中国水稻科学, 2024, 38(4): 364-374.
[11]	候小琴, 王莹, 余贝, 符卫蒙, 奉保华, 沈煜潮, 谢杭军, 王焕然, 许用强, 武志海, 王建军, 陶龙兴, 符冠富. 黄腐酸钾提高水稻秧苗耐盐性的作用途径分析[J]. 中国水稻科学, 2024, 38(4): 409-421.
[12]	胡继杰, 胡志华, 张均华, 曹小闯, 金千瑜, 章志远, 朱练峰. 根际饱和溶解氧对水稻分蘖期光合及生长特性的影响[J]. 中国水稻科学, 2024, 38(4): 437-446.
[13]	刘福祥, 甄浩洋, 彭焕, 郑刘春, 彭德良, 文艳华. 广东省水稻孢囊线虫病调查与鉴定[J]. 中国水稻科学, 2024, 38(4): 456-461.
[14]	陈浩田, 秦缘, 钟笑涵, 林晨语, 秦竞航, 杨建昌, 张伟杨. 水稻根系和土壤性状与稻田甲烷排放关系的研究进展[J]. 中国水稻科学, 2024, 38(3): 233-245.
[15]	缪军, 冉金晖, 徐梦彬, 卜柳冰, 王平, 梁国华, 周勇. 过量表达异三聚体G蛋白γ亚基基因RGG2提高水稻抗旱性[J]. 中国水稻科学, 2024, 38(3): 246-255.