作物学报 ›› 2022, Vol. 48 ›› Issue (11): 2786-2796.doi: 10.3724/SP.J.1006.2022.14190
刘玉玲1(
), 张红岩1, 滕长才1,2, 周仙莉1, 侯万伟1,2,3,*(
)
LIU Yu-Ling1(
), ZHANG Hong-Yan1, TENG Chang-Cai1,2, ZHOU Xian-Li1, HOU Wan-Wei1,2,3,*(
)
摘要:
淀粉是蚕豆籽粒碳水化合物中含量最丰富的一类。淀粉含量会影响其物理和化学性质, 从而影响蚕豆的品质和用途。了解蚕豆品种的遗传多样性, 寻找与蚕豆淀粉含量紧密连锁的分子标记, 对蚕豆分子标记辅助育种具有重要意义。本研究以260份蚕豆种质为供试材料, 测定了2019和2020两年的总淀粉含量、直链淀粉含量和支链淀粉含量。利用具有显著多态性的132对SSR标记对260份蚕豆材料进行遗传多样性分析与群体遗传结构分析, 并采用Tassel 2.1软件的GLM和MLM两种模型进行标记与淀粉含量的关联分析。结果显示, 表型性状的变异系数变幅为13.21%~20.52%, 平均值为14.85%, 表明供试群体具有一定的表型多样性。132个标记在260份蚕豆材料中共检测到629个多态性位点, 各位点的平均等位基因数为4.77个, 变异范围为2~11个。多态性信息量(PIC)值在0.0385~0.7772之间, 平均为0.4935, PIC值大于平均数的约占50%, 表明本研究选用标记基因多样性较高。聚类分析将260份材料划分为3个类群, 第I类群包括42份材料, 第II类群包括59份材料, 第III类群包括159份材料, 划分结果体现了蚕豆品种间的亲缘关系。群体遗传结构分析将260份材料划分为2个亚群, 表明供试群体结构相对单一, 有利于关联分析。基于GLM和MLM模型, 2年均分别检测到8个与总淀粉、直链淀粉和支链淀粉含量极显著(P<0.01)的关联标记, 单个标记对表型变异的解释率分别为4.54%~9.04%和2.69%~10.39%。SSR-10927标记与支链淀粉含量在2年和2种模型中均显著(P<0.05)关联, 且与总淀粉含量在2019年中的2种模型及2020年的MLM模型中显著(P<0.05)关联, 检出率最高。此研究结果为蚕豆分子标记辅助选择育种以及亲本材料选配奠定了理论基础。
| [1] | 叶茵. 中国蚕豆学. 北京: 中国农业出版社, 2003. pp 1-4. |
| Ye Y. Chinese Broad Bean Science. Beijing: China Agriculture Press, 2003. pp 1-4. (in Chinese) | |
| [2] | 耿友玲, 徐强, 陈银根, 陈学好. 作物品质性状的分子遗传改良. 分子植物育种, 2008, 6: 749-759. |
| Geng Y L, Xu Q, Chen Y G, Chen X H. Molecular genetic improvement of crop quality traits. Mol Plant Breed, 2008, 6: 749-759. (in Chinese with English abstract) | |
| [3] | 谭洪卓, 谭斌, 田晓红, 刘明. 20种中国蚕豆的化学组成、物理特性及其相互关系. 中国粮油学报, 2009, 24(12): 56-60. |
| Tan H Z, Tan B, Tian X H, Liu M. The chemical composition, physical properties and their relationships of 20 Chinese broad beans. Chin Cereals Oils Assoc, 2009, 24(12): 56-60. (in Chinese with English abstract) | |
| [4] | 李鸣晓. 环境和遗传因素对水稻RILs群体淀粉特性的影响. 沈阳农业大学硕士学位论文, 辽宁沈阳, 2019. |
| Li M X. Effects of Environmental and Genetic Factors on Starch Characteristics of Rice RILs Population. MS Thesis Shenyang Agricultural University, Shenyang, Liaoning, China, 2019. (in Chinese with English abstract) | |
| [5] | 岳庆春, 傅迦得, 章辰飞, 吴月燕. 植物关联分析应用研究进展. 江苏农业科学, 2019, 47(18): 24-30. |
| Yue Q C, Fu J D, Zhang C F, Wu Y Y. Research progress in the application of plant association analysis. Jiangsu Agric Sci, 2019, 47(18): 24-30. (in Chinese with English abstract) | |
| [6] | 苗百更, 李佳美, 马文东, 张斯琦, 李修平. 寒地水稻直链淀粉含量关联分析. 分子植物育种, 2018, 16: 2511-2518. |
| Miao B G, Li J M, Ma W D, Zhang S Q, Li X P. Correlation analysis of amylose content in rice in cold regions. Mol Plant Breed, 2018, 16: 2511-2518 (in Chinese with English abstract). | |
| [7] |
Song X H, Zhu G Z, Hou S, Ren Y M, Amjid M W, Li W X, Guo W Z. Genome-wide association analysis reveals loci and candidate genes involved in fiber quality traits under multiple field environments in cotton (Gossypium hirsutum). Front Plant Sci, 2021, 12: 695503.
doi: 10.3389/fpls.2021.695503 |
| [8] | 郭晋杰, 刘文斯, 郑云霄, 刘函, 赵永锋, 祝丽英, 黄亚群, 贾晓艳, 陈景堂. 基于4个测交群体玉米籽粒品质相关性状关联分析. 农业生物技术学报, 2019, 27: 809-824. |
| Guo J J, Liu W S, Zheng Y X, Liu H, Zhao Y F, Zhu L Y, Huang Y Q, Jia X Y, Chen J T. Based on the correlation analysis of corn kernel quality traits in 4 testcross populations. Agric Biotechnol, 2019, 27: 809-824. (in Chinese with English abstract) | |
| [9] |
王长进, 徐运林, 程昕昕, 周毅, 余海兵. 甜玉米种子营养品质主要性状全基因组关联分析. 浙江农业学报, 2020, 32: 383-389.
doi: 10.3969/j.issn.1004-1524.2020.03.01 |
| Wang C J, Xu Y L, Cheng X X, Zhou Y, Yu H B. Whole- genome association analysis of main traits of sweet corn seed nutritional quality. Zhejiang Agric Sci, 2020, 32: 383-389. (in Chinese with English abstract) | |
| [10] |
Schönhals E M, Ding J, Ritter E, Paulo M J, Cara N, Tacke E, Hofferbert H R, Lübeck J, Strahwald J, Gebhardt C. Physical mapping of QTL for tuber yield, starch content and starch yield in tetraploid potato (Solanum tuberosum L.) by means of genome wide genotyping by sequencing and the 8.3 K SolCAP SNP array. BMC Genomics, 2017, 18: 642.
doi: 10.1186/s12864-017-3979-9 pmid: 28830357 |
| [11] | 吴艳艳, 黄伟华, 黄永才, 刘洁云, 田青兰, 牟海飞, 李小泉. 栽培种西番莲完全型SSR的高通量鉴定及标记开发. 分子植物育种, 2018, 16: 6738-6743. |
| Wu Y Y, Huang W H, Huang Y C, Liu J Y, Tian Q L, Mou H F, Li X Q. High-throughput identification and marker development of the complete SSR of cultivated species Passiflora. Mol Plant Breed, 2018, 16: 6738-6743. (in Chinese with English abstract) | |
| [12] | 张红岩. 基于SSR标记的蚕豆DNA指纹图谱构建及品种纯度鉴定. 中国农业科学院硕士学位论文, 北京, 2018. |
| Zhang H Y. Construction of Faba Bean DNA Fingerprinting and Identification of Variety Purity Based on SSR Markers. MS Thesis of Chinese Academy of Agricultural Sciences, Beijing, China, 2018. (in Chinese with English abstract) | |
| [13] |
Ma Y, Bao S Y, Yang T, Hu J G, Guan J P, He Y H, Wang X J, Wan Y L, Sun X L, Jiang J Y, Gong C X, Zong X X. Genetic linkage map of Chinese native variety faba bean (Vicia faba L.) based on simple sequence repeat markers. Plant Breed, 2013, 132: 397-400.
doi: 10.1111/pbr.12074 |
| [14] | 姜俊烨. 蚕豆微核心种质构建及SSR遗传连锁图谱加密. 中国农业科学院硕士学位论文, 北京, 2014. |
| Jiang J Y. Construction of Broad Bean Micro-core Collection and Encryption of SSR Genetic Linkage Map. MS Thesis of Chinese Academy of Agricultural Sciences, Beijing, China, 2014. (in Chinese with English abstract) | |
| [15] |
Yang T, Jiang J Y, Zhang H Y, Liu R, Strelkov S, Hwang S F, Chang K F, Yang F, Miao Y M, He Y H, Zong X X. Density enhancement of a faba bean genetic linkage map (Vicia faba) based on simple sequence repeats markers. Plant Breed, 2019, 138: 207-215.
doi: 10.1111/pbr.12679 |
| [16] | 杨访问, 吕春雨, 廖芳丽, 陈宏伟, 李莉, 万正煌, 沙爱华, 焦春海. 41份非洲和湖北蚕豆种质资源SSR遗传多样性分析. 分子植物育种, 2020, 18: 2619-2625. |
| Yang F W, Lyu C Y, Liao F L, Chen H W, Li L, Wan Z H, Sha A H, Jiao C H. SSR genetic diversity analysis of 41 African and Hubei faba bean germplasm resources. Mol Plant Breed, 2020, 18: 2619-2625. (in Chinese with English abstract) | |
| [17] | 张红岩, 郭兴莲, 杨涛, 刘荣, 黄宇宁, 季一山, 王栋, 宗绪晓. 利用SSR标记分析蚕豆品种(品系)与优异种质的遗传多样性. 中国蔬菜, 2018, (2): 34-41. |
| Zhang H Y, Guo X L, Yang T, Liu R, Huang Y N, Ji Y S, Wang D, Zong X X. Using SSR markers to analyze the genetic diversity of faba bean varieties (lines) and excellent germplasm. China Veget, 2018, (2): 34-41. (in Chinese with English abstract) | |
| [18] |
El-Esawi M A. SSR analysis of genetic diversity and structure of the germplasm of faba bean (Vicia faba L.). Comptes Rendus Biol, 2017, 340: 474-480.
doi: 10.1016/j.crvi.2017.09.008 |
| [19] | 田莹莹, 侯万伟, 刘玉皎. 蚕豆粒型性状的遗传分析及QTL检测. 分子植物育种, 2018, 16: 1174-1183. |
| Tian Y Y, Hou W W, Liu Y J. Genetic analysis and QTL detection of faba bean grain type traits. Mol Plant Breed, 2018, 16: 1174-1183. (in Chinese with English abstract) | |
| [20] |
Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol, 2005, 14: 2611-2620.
pmid: 15969739 |
| [21] | 田承华, 程庆军, 高海燕, 高鹏, 张俊珍, 郭睿, 贺文文. 高粱种质资源SSR标记遗传多样性与农艺性状关联分析. 安徽农业科学, 2018, 46(32): 26-32. |
| Tian C H, Cheng Q J, Gao H Y, Gao P, Zhang J Z, Guo R, He W W. Association analysis of genetic diversity and agronomic traits of sorghum germplasm resources with SSR markers. Anhui Agric Sci, 2018, 46(32): 26-32. (in Chinese with English abstract) | |
| [22] | 张金霞, 刘贺梅, 孙建权, 殷春渊, 王和乐, 胡秀明, 田芳慧, 王书玉. 分子标记技术在水稻品种改良中的应用. 中国种业, 2021, (9): 14-18. |
| Zhang J X, Liu H M, Sun J Q, Yin C Y, Wang H L, Hu X M, Tian F H, Wang S Y. Application of molecular marker technology in rice variety improvement. China Seed Ind, 2021, (9): 14-18. (in Chinese with English abstract) | |
| [23] |
Abid G, Mingeot D, Udupa S M, Muhovski Y, Watillon B, Sassi K, M’ hamdi M, Souissi M, Mannai K, Barhoumi F, Jebara M. Genetic relationship and diversity analysis of faba bean (Vicia faba L. var. minor) genetic resources using morphological and microsatellite molecular markers. Plant Mol Biol Rep, 2015, 33: 1755-1767.
doi: 10.1007/s11105-015-0871-0 |
| [24] |
叶君, 吴晓华, 李元清, 崔国惠, 王小兵, 赵春芝, 杨蕾, 张三粉, 张海斌, 于美玲. 基于表型性状的藜麦种质资源遗传多样性分析. 北方农业学报, 2020, 48(1): 1-6.
doi: 10.12190/j.issn.2096-1197.2020.01.01 |
| Ye J, Wu X H, Li Y Q, Cui G H, Wang X B, Zhao C Z, Yang L, Zhang S F, Zhang H B, Yu M L. Genetic diversity analysis of quinoa germplasm resources based on phenotypic traits. Northern J Agric, 2020, 48(1): 1-6. (in Chinese with English abstract) | |
| [25] | 王复标, 石军, 郑卓, 司二杰, 黄廷友, 孙惠敏. 水稻遗传多样性及其农艺性状与SSR标记的关联分析. 四川大学学报(自然科学版), 2019, 56: 976-982. |
| Wang F B, Shi J, Zheng Z, Si E J, Huang T Y, Sun H M. Association analysis of rice genetic diversity and agronomic traits with SSR markers. J Sichuan Univ (Nat Sci Edn), 2019, 56: 976-982. (in Chinese with English abstract) | |
| [26] | 文自翔, 赵团结, 郑永战, 刘顺湖, 王春娥, 王芳, 盖钧镒. 中国栽培和野生大豆农艺品质性状与SSR标记的关联分析: I. 群体结构及关联标记. 作物学报, 2008, 34: 1169-1178. |
| Wen Z X, Zhao T J, Zheng Y Z, Liu S H, Wang C E, Wang F, Gai J Y. Association analysis of agronomic quality traits and SSR markers in chinese cultivated and wild soybeans: I. Population structure and associated markers. Acta Agron Sin, 2008, 34: 1169-1178. (in Chinese with English abstract) | |
| [27] | Price A L, Zaitlen N A, Reich D, Patterson N. New approaches to population stratification in genome-wide association studies. Nat Rev Genet, 2010, 11: 459-463. |
| [28] |
Zhang Z W, Ersoz E, Lai C Q, Todhunter R J, Tiwari H K, Gore M A, Bradbury P J, Yu J M, Arnett D K, Ordovas J M, Buckler E S. Mixed linear model approach adapted for genome-wide association studies. Nat Genet, 2010, 42: 355-360.
doi: 10.1038/ng.546 |
| [1] | 习千辉, 徐梓瑗, 刘梦梦, 王宏艺, 郎凯琳, 井震海, 陈锋, 赵磊. 小麦籽粒铜含量的全基因组关联分析及候选基因预测[J]. 作物学报, 2026, 52(6): 1604-1617. |
| [2] | 毛嘉琦, 黄朋雨, 赵佳佳, 郑兴卫, 武棒棒, 郝宇琼, 屈非, 刘成, 马朋涛, 郑军. 山西小麦品种白粉病抗性评价及抗病基因分子检测[J]. 作物学报, 2026, 52(6): 1669-1681. |
| [3] | 唐宽强, 李公允, 宋美毅, 赵雪, 常春玲. 大豆株高性状全基因组关联分析及预测模型构建[J]. 作物学报, 2026, 52(6): 1743-1756. |
| [4] | 杨扬, 常诗惠, 田红丽, 易红梅, 王璐, 任洁, 范亚明, 刘亚维, 王凤格, 赵久然. 不同生态区国审玉米品种的遗传多样性分析[J]. 作物学报, 2026, 52(5): 1352-1364. |
| [5] | 杨欣雨, 崔文涛, 迪力尼格尔·阿力木, 汪凯翔, 吴鹏昊, 任姣姣. 玉米穗上叶片数全基因组关联分析和全基因组选择[J]. 作物学报, 2026, 52(5): 1573-1590. |
| [6] | 闫安, 蒋昆炜, 王蓉圆, 田林, 张璐, 王韵, 徐建龙. 水稻剑叶小维管束数基因SVN7的鉴定与克隆[J]. 作物学报, 2026, 52(5): 1364-1372. |
| [7] | 徐建霞, 丁延庆, 曹宁, 程斌, 高旭, 李文贞, 王若若, 王磊, 张立异. 397份高粱种质资源在贵州表型多样性分析及综合评价[J]. 作物学报, 2026, 52(4): 1073-1087. |
| [8] | 田春艳, 陆鑫, 吴才文, 徐超华, 刘家勇, 边芯, 桃联安. 基于荧光SSR的甘蔗创新种质遗传多样性分析及育种潜力评估[J]. 作物学报, 2026, 52(4): 1057-1072. |
| [9] | 侯洁, 付朵朵, 武海峰, 郝宇琼, 郑兴卫, 武棒棒, 周凯, 李晓华, 郑军, 赵佳佳. 山西省小麦地方品种的染色体多样性及遗传效应分析[J]. 作物学报, 2026, 52(3): 746-763. |
| [10] | 张超, 郭欢, 李忠玲, 岳淑宁, 赵娜. 基于BSA-seq技术定位玉米籽粒花青素关联基因[J]. 作物学报, 2026, 52(3): 780-789. |
| [11] | 鲁雅妮, 丁超杰, 张煜, 杜习军, 齐学礼, 胡琳, 许为钢. 河南省200份小麦品种苗期茎基腐病抗性鉴定与全基因组关联分析[J]. 作物学报, 2026, 52(2): 363-375. |
| [12] | 李诗晴, 王茜, 王素华, 张耀文, 王丽侠. 绿豆种质资源苗期耐盐性鉴定及相关基因发掘[J]. 作物学报, 2026, 52(2): 376-388. |
| [13] | 李璐琪, 程宇坤, 白斌, 雷斌, 耿洪伟. 小麦叶片气孔相关性状全基因组关联分析[J]. 作物学报, 2025, 51(9): 2266-2284. |
| [14] | 梅飘, 刘丁丁, 叶圆圆, 张晨禹, 丁诗琦, 李亚奇, 王培鑫, 梅菊芬, 马春雷. 基于茶树液相功能芯片的白化茶树资源遗传多样性分析[J]. 作物学报, 2025, 51(9): 2358-2370. |
| [15] | 李云香, 郭千纤, 侯万伟, 张小娟. 引进ICARDA小麦苗期根系抗旱性状的全基因组关联分析[J]. 作物学报, 2025, 51(9): 2387-2398. |
|
||