中国农业科学 ›› 2018, Vol. 51 ›› Issue (17): 3237-3248.doi: 10.3864/j.issn.0578-1752.2018.17.001

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

小麦新品种淮麦33的遗传构成分析

杨子博1,2,王安邦1,冷苏凤3,顾正中1,周羊梅1

 
  

  1. 1江苏徐淮地区淮阴农业科学研究所,江苏淮安 223001;2江苏省环洪泽湖生态农业生物技术重点实验室(淮阴师范学院),江苏淮安 223300;3江苏省种子管理站,南京 210036
  • 收稿日期:2018-04-08 出版日期:2018-09-01 发布日期:2018-09-01
  • 通讯作者: 周羊梅,E-mail:464023502@qq.com。顾正中,E-mail:hynksgzz@163.com
  • 作者简介:杨子博,E-mail:yangzibo1986@126.com
  • 基金资助:
    国家重点研发计划(2017YFD0100703)、淮安市自然科学研究计划(HAB201721)、江苏省农业重大新品种创制项目(PZCZ201706)、淮安市农业科学院院长基金(HNY201701)、江苏省环洪泽湖生态农业生物技术重点实验室自主研发项目(17HZHL006)

Genetic Analysis of the Novel High-Yielding Wheat Cultivar Huaimai33

YANG ZiBo1, 2, WANG AnBang1, LENG SuFeng3, GU ZhengZhong1, ZHOU YangMei1   

  1. 1Agriculture Science Research Institute of Huaiyin in Xuzhou and Huaiyin Area of Jiangsu Province, Huaian 223001, Jiangsu; 2Jiangsu Key Laboratory for Eco-Agricultural Biotechnology around Hongze Lake (Huaiyin Normal University),  Huaian 223300, Jiangsu; 3Seed Administration Bureau of Jiangsu Province, Nanjing 210036
  • Received:2018-04-08 Online:2018-09-01 Published:2018-09-01

摘要: 【目的】解析高产广适小麦新品种淮麦33的遗传构成,探讨双亲烟农19和郑麦991对其产量相关性状的遗传贡献,为小麦品种改良及亲本选配提供依据。【方法】利用部分农艺及品质性状、高分子量谷蛋白亚基组成及覆盖小麦21条染色体的625个SSR分子标记分析淮麦33及其双亲的遗传构成;比对已知的产量性状相关QTL,分析双亲的产量相关区段对淮麦33的遗传贡献。【结果】淮麦33的每平方米穗数和千粒重均介于两亲本之间,穗粒数和小区产量均显著高于两亲本;与烟农19相比,其株高显著降低。淮麦33的高分子量谷蛋白亚基组成为(1、17+18和2+12),其中1和17+18亚基均来自于母本烟农19,2+12亚基来自于父本郑麦991。SSR分子标记分析表明,双亲对淮麦33的遗传贡献和理论值相比出现了较大偏离,淮麦33分别继承了烟农19和郑麦991两亲本73.9%和26.1%的遗传物质。淮麦33与烟农19具有较大的遗传相似度,遗传相似系数为0.78。在不同基因组和染色体水平上,双亲对淮麦33的遗传贡献率差异较大,其中,烟农19在A、B和D基因组水平的遗传贡献率均较高,分别为75.1%、69.4%和68.7%;除6A染色体外,烟农19在其他20条染色体上的遗传贡献率均高于郑麦991,其中在2A染色体上达到100%,在1A、3A、2B、3B和4B等5条染色体上均超过90%。在遗传距离大于5 cM的染色体区段中,淮麦33来源于烟农19和郑麦991的染色体区段分别有34个和7个,其中在2D染色体上来源于烟农19的染色体区段最多,在5A染色体上来源于郑麦991的区段最多。淮麦33有38个不同于双亲的特异位点,主要分布在1B、1D、2A、2B、2D、3A、3B、3D、4A、4B、5A、5B、6B、6D和7A等15条染色体上。比对已知产量性状相关QTL,共发现10个产量相关区段,有6个来源于烟农19,分别位于1A、2D、3B、4B、4D和7A染色体上;3个来源于郑麦991,分别位于4A和5A染色体上;1个为淮麦33特异区段,位于6D染色体上。【结论】明确了小麦新品种淮麦33的遗传构成,其更多地继承了母本烟农19的遗传物质;发现淮麦33中来源于不同亲本的产量相关区段。

关键词: 淮麦33, 高分子量谷蛋白亚基, SSR标记, 遗传构成

Abstract: 【Objective】 Huaimai33 is a new wheat cultivar featuring high yield and good adaptation, which was derived from a cross between Yannong19 and Zhengmai991. In this study, the genetic contributions of the two parent cultivars to Huaimai33 were determined by comparing their agronomical performance and genome composition. 【Method】 The grain yield, quality traits, and high-molecular-weight glutenin subunit (HMW-GS) composition of Huaimai33 and its parents were evaluated. The parental origins of Huaimai33 chromosomal segments were identified using 625 simple sequence repeat (SSR) markers, and the segments were analyzed for their effects on yield and yield-related traits by linking them to known quantitative trait loci (QTLs) reported in previous studies. 【Result】 The spike number per square meter and thousand grain weight of Huaimai33 were between those of Yannong19 and Zhengmai991; in contrast, Huaimai33 showed significantly higher grains per spike and plot yield than both of its parents. The plant height of Huaimai33 was significantly lower compared with Yannong19. The HMW-GS composition of Huaimai33 was 1, 17+18, and 2+12, among which the 1 and 17+18 subunits were derived from female parent Yannong19 and the 2+12 subunit was derived from the male parent Zhengmai991. SSR marker analysis showed that the two parents contributed differently to the genome of Huaimai33; that is, 73.9% of the Huaimai33 genome originated from Yannong19, and 26.1% from Zhengmai991. Huaimai33 therefore was highly similar to Yannong19, with a genetic similarity coefficient of 0.78. Furthermore, Yannong19 contributed more to Huaimai33 than Zhengmai991 in subgenomes A (75.1%), B (69.4%) and D (68.7%). This was also the case at the level of individual chromosomes with the exception of 6A. In particular, chromosome 2A in its entirety, and over 90% each of chromosomes 1A, 3A, 2B, 3B, and 4B were conferred by Yannong19. Of the Huaimai33 chromosomal segments greater than 5 cM in size, 34 segments came from Yannong19 and only 7 from Zhengmai991. Chromosome 2D contains the most segments from Yannong19 of all chromosomes, whereas 5A holds the most from Zhengmai991. Interestingly, Huaimai33 had 38 loci that were absent in both parents, which were distributed on chromosomes 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 5A, 5B, 6B, 6D, and 7A. Based on marker-trait associations identified in previous studies, 10 genomic regions in Huaimai33 were associated with effects on yield and yield-related traits. Of these regions, 6 were contributed by Yannong19 (on chromosomes 1A, 2D, 3B, 4B, 4D, and 7A), 3 by Zhengmai991 (on chromosomes 4A and 5A), and the last was Huaimai33 specific (on chromosome 6D). 【Conclusion】 Defining the genetic composition of Huaimai33 showed that the genome fractions of the parent Yannong19 were maintained more frequently than Zhengmai991 during development. The chromosomal segments from different parents on grain yield had been found. This would improve our understanding of how to develop elite cultivars and their key agronomical traits through breeding.

Key words: Huaimai 33, high-molecular-weight glutenin subunit, SSR markers, genetic components

 
[1]    何中虎, 庄巧生, 程顺和, 于振文, 赵振东, 刘旭. 中国小麦产业发展与科技进步. 农学学报, 2018, 8(1): 99-106.
He Z H, Zhuang Q S, Cheng S H, Yu Z W, Zhao Z D, Liu X. Wheat production and technology improvement in China. Journal of Agriculture, 2018, 8(1): 99-106. (in Chinese)
[2]    袁园园, 王庆专, 崔法, 张景涛, 杜斌, 王洪刚. 小麦骨干亲本碧蚂4号的基因组特异位点及其在衍生后代中的传递. 作物学报, 2010, 36(1): 9-16.
Yuan Y Y, Wang Q Z, Cui F, Zhang J T, Du B, Wang H G. Specific loci in genome of wheat milestone parent Bima 4 and their transmission in derivatives. Acta Agronomica Sinica, 2010, 36(1): 9-16. (in Chinese)
[3]    肖永贵, 殷贵鸿, 李慧慧, 夏先春, 阎俊, 郑天存, 吉万全, 何中虎. 小麦骨干亲本8425B”及其衍生品种的遗传解析和抗条锈病基因.中国农业科学, 2011, 44(19): 3919-3929.
Xiao Y G, Yin G H, Li H H, Xia X C, Yan J, Zheng T C, Ji W Q, He Z H. Genetic diversity and genome-wide association analysis of stripe rust resistance among the core wheat parent Zhou 8425B and its derivatives. Scientia Agricultura Sinica, 2011, 44(19): 3919-3929. (in Chinese)
[4]    于海霞, 肖静, 田纪春. 小麦骨干亲本矮孟牛及其衍生后代遗传解析. 中国农业科学, 2012, 45(2): 199-207.
Yu H X, Xiao J, Tian J C. Genetic dissection of milestone parent Aimengniu and its derivatives. Scientia Agricultura Sinica, 2012, 45(2): 199-207. (in Chinese)
[5]    盖红梅, 李玉刚, 王瑞英, 李振清, 王圣健, 高峻岭, 张学勇. 鲁麦14对山东新选育小麦品种的遗传贡献. 作物学报, 2012, 38(6): 954-961.
Ge H M, Li Y G, Wang R Y, Li Z Q, Wang S J, Gao J L, Zhang X Y. Genetic contribution of Lumai 14 to novel wheat varieties developed in Shandong province. Acta Agronomica Sinica, 2012, 38(6): 954-961. (in Chinese)
[6]    韩俊, 张连松, 李静婷, 石丽娟, 解超杰, 尤明山, 杨作民, 刘广田, 孙其信, 刘志勇. 小麦骨干亲本“胜利麦/燕大1817”杂交组合后代衍生品种遗传构成解析. 作物学报, 2009, 35(8):1395-1404.
Han J, Zhang L S, Li J T, Shi L J, Xie C J, You M S, Yang Z M, Liu G T, Sun Q X, Liu Z Y. Molecular dissection of core parental cross “Triumph/Yanda 1817” and its derivatives in wheat breeding program. Acta Agronomica Sinica, 2009, 35(8): 1395-1404. (in Chinese)
[7]    赵春华, 樊小莉, 王维莲, 张玮, 韩洁, 陈梅, 纪军, 崔法, 李俊明. 小麦候选骨干亲本科农9204遗传构成及其传递率. 作物学报, 2015, 41(4): 574-584.
Zhao C H, Fan X L, Wang W L, Zhang W, Han J, Chen M, Ji J, Cui F, Li J M. Genetic composition and its transmissibility analysis of wheat candidate backbone parent Kenong 9204. Acta Agronomica Sinica, 2015, 41(4): 574-584. (in Chinese)
[8]    Ge H M, You G X, Wang L F, Hao C Y, Dong Y C, Li Z S, Zhang X Y. Genome selection sweep and association analysis shed light on future breeding by design in wheat. Crop Science, 2012, 52(3): 1218-1228.
[9]    李玉刚, 任民, 孙绿, 王圣健, 韩梅, 李振清, 翟晓灵, 代小雁, 侯元江, 盖红梅. 利用SSRSNP标记分析鲁麦14对青农2号的遗传贡献. 作物学报, 2018, 44(2): 159-168.
Li Y G, Ren M, Sun L, Wang S J, Han M, LI Z Q, Zhai X L, Dai X Y, Hou Y J, Ge H M. Genetic contribution of Lumai 14 to Qingnong 2 revealed by SSR and SNP markers. Acta Agronomica Sinica, 2018, 44(2): 159-168. (in Chinese)
[10]   李小军, 胡铁柱, 李淦, 姜小苓, 冯素伟, 董娜, 张自阳, 茹振钢, 黄勇. 小麦品种百农AK58及其姊妹系的遗传构成分析. 作物学报, 2012, 38(3): 436-446.
Li X J, Hu T Z, Li G, Jiang X L, Feng S W, Dong N, Zhang Z Y, Ru Z G, Huang Y. Genetic analysis of broad-grown wheat cultivar Bainong AK58 and its Sib lines. Acta Agronomica Sinica, 2012, 38(3): 436-446. (in Chinese)
[11]   李俊, 万洪深, 杨武云, 王琴, 朱欣果, 胡晓蓉, 魏会廷, 汤永禄, 李朝苏, 彭正松, 周永红. 小麦新品种川麦104的遗传构成分析. 中国农业科学, 2014, 47(12): 2281-2291.
Li J, Wan H S, Yang W Y, Wang Q, Zhu X G, Hu X R, Wei H T, Tang Y L, Li C S, Peng Z S, Zhou Y H. Dissection of genetic components in the new high-yielding wheat cultivar Chuanmai 104. Scientia Acricultura Sinica, 2014, 47(12): 2281-2291. (in Chinese)
[12]   邹少奎, 殷贵鸿, 唐建卫, 韩玉林, 李楠楠, 李顺成, 黄峰, 王丽娜, 张倩, 高艳. 小麦新品种周麦23号的遗传构成分析及其特异引物筛选. 中国农业科学, 2015, 48(19): 3941-3951.
Zou S K, Yin G H, Tang J W, Han Y L, Li N N, Li S C, Huang F, Wang L N, Zhang Q, Gao Y. Genetic analysis of new wheat variety Zhoumai 23 and screening of specific primers. Scientia Acricultura Sinica, 2015, 48(19): 3941-3951. (in Chinese)
[13]   邹少奎, 殷贵鸿, 唐建卫, 韩玉林, 李顺成, 李楠楠, 黄峰, 王丽娜, 张倩, 高艳. 小麦品种周麦22号的分子遗传基础及其特异引物筛选. 麦类作物学报, 2017, 37(4): 472-482.
Zou S K, Yin G H, Tang J W, Han Y L, Li S C, Li N N, Huang F, Wang L N, Zhang Q, Gao Y. Molecular and genetic basis of wheat variety Zhoumai 22 and specific primers screening. Journal of Triticeae Crops, 2017, 37(4): 472-482. (in Chinese)
[14]   周羊梅, 顾正中, 王安邦, 杨子博. 高产稳产小麦新品种‘淮麦33’选育及性状分析. 中国农学通报, 2016, 32(27): 47-52.
Zhou Y M, Gu Z Z, Wang A B, Yang Z B. Agronomic traits and breeding of ‘Huaimai No.33’: a new winter wheat variety with high and stable yield. Chinese Agricultural Science Bulletin, 2016, 32(27): 47-52. (in Chinese)
[15]   张玲丽, 李秀全, 杨欣明, 李洪杰, 王辉, 李立会. 小麦优良种质资源高分子量麦谷蛋白亚基组成分析. 中国农业科学, 2006, 39(12): 2406-2414.
Zhang L L, Li X Q, Yang X M, Li H J, Wang H, Li L H. High-Molecular-Weight glutenin subunit composition of Chinese wheat germplasm. Scientia Agricultura Sinica, 2006, 39(12): 2406-2414. (in Chinese)
[16]   Payne P I, Lawrence G J. Catalogue of alleles for the complex gene loci, Glu-A1, Glu-B1 and Glu-D1 which code for high molecular weight subunits of glutenin in hexaploid wheat. Cereal Research Communications, 1983, 11: 29-35.
[17]   Xue S L, Zhang Z Z, Lin F, Kong Z X, Cao Y, Li C J, Yi H Y, Mei M F, Zhu H L, Wu J Z, Xu H B, Zhao D M, Tian D G, Zhang C Q, Ma Z Q. A high-density intervarietal map of the wheat genome enriched with markers derived from expressed sequence tags. Theoretical and Applied Genetics, 2008, 117: 181-189.
[18]   Somers D J, Isaac P, Edwards K. A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 2004, 109(6): 1105-1114.
[19]   Lü X B, Zhang Y B, Song Q J, Liu D N, Zhang C L, Zhao H B. Qualitative difference between HMW-GS 5+10 and 2+12 NILs of four spring wheat cultivars with high-quality genetic background. Agricultural Science in China, 2004, 3: 568-574.
[20]   Hai L, Guo H J, Wagner C, Xiao S H, Friedt W. Genomic regions for yield and yield parameters in Chinese winter wheat (Triticum aestivum L.) genotypes tested under varying environments correspond to QTL in widely different wheat materials. Plant Science, 2008, 175(3): 226-232.
[21]   Kumar N, Kulwal P L, Balyan H S, Gupta P K. QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat. Molecular Breeding, 2007, 19(2): 163-177.
[22]   Jia H Y, Wan H S, Yang S H, Zhang Z Z, Kong Z X, Xue S L, Zhang L X, Ma Z Q. Genetic dissection of yield-related traits in a recombinant inbred line population created using a key breeding parent in China’s wheat breeding. Theoretical and Applied Genetics, 2013, 126(8): 2123-2139.
[23]   Wang R X, Hai L, Zhang X Y, You G X, Yan C S, Xiao S H. QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai × Yu8679. Theoretical and Applied Genetics, 2009, 118(2): 313-325.
[24]   Huang X Q, Cöster H, Ganal M W, Röder M S. Advanced backcross QTL analysis for the identification of quantitative trait loci alleles from wild relatives of wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 2003, 106(8): 1379-1389.
[25]   McCartney C A, Somers D J, Humphreys D G, Lukow O, Ames N, Noll J, Cloutier S, McCallum B D. Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452 × 'AC Domain'. Genome, 2005, 48(5): 870-883.
[26]   Su J Y, Zheng Q, Li H W, Li B, Jing R L, Tong Y P, Li Z S. Detection of QTLs for phosphorus use efficiency in relation to agronomic performance of wheat grown under phosphorus sufficient and limited conditions. Plant Science, 2009, 176(6): 824-836.
[27]   Ellis M H, Rebetzke G J, Azanza F, Richards R A, Spielmeyer W. Molecular mapping of gibberellin-responsive dwarfing genes in bread wheat. Theoretical and Applied Genetics, 2005, 111(3): 423-430.
[28]   Narasimhamoorthy B, Gill B S, Fritz A K, Nelson J C, Brown-Guedira G L. Advanced backcross QTL analysis of a hard winter wheat × synthetic wheat population. Theoretical and Applied Genetics, 2006, 112(5): 787-796.
[29]   Huang X Q, Cloutier S, Lycar L, Radovanovic N, Humphreys D G, Noll J S, Somers D J, Brown P D. Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.). Theoretical and Applied Genetics, 2006, 113(4): 753-766.
[30]   Cuthbert J L, Somers D J, Br?lé-Babel A L, Brown P D, Crow G H. Molecular mapping of quantitative trait loci for yield and yield components in spring wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 2008, 117: 595-608.
[31]   Carter A H, Garland-Campbell K, Kidwell K K. Genetic mapping of quantitative trait loci associated with important agronomic traits in the spring wheat (Triticum aestivum L.) cross ‘Louise’ × ‘Penawawa’. Crop Science, 2011, 51: 84-95.
[32]   Huang X Q, Kempf H, Ganal M W, Röder M S. Advanced backcross QTL analysis in progenies derived from a cross between a german elite winter wheat variety and a synthetic wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 2004, 109(5): 933-943.
[33]   Pinto R S, Reynolds M P, Mathews K L, McIntyre C L, Olivares-Villegas J J, Chapman S C. Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects. Theoretical and Applied Genetics, 2010, 121(6): 1001-1021.
[34]   McIntyre C L, Mathews K L, Rattey A, Chapman S C, Drenth J, Ghaderi M, Reynolds M, Shorter R. Molecular detection of genomic regions associated with grain yield and yield-related components in an elite bread wheat cross evaluated under irrigated and rainfed conditions. Theoretical and Applied Genetics, 2010, 120(3): 527-541.
[35]   Deng S M, Wu X R, Wu Y Y, Zhou R H, Wang H G, Jia J Z, Liu S B. Characterization and precise mapping of a QTL increasing spike number with pleiotropic effects in wheat. Theoretical and Applied Genetics, 2011, 122(2): 281-289.
[36]   Cui F, Zhao C H, Ding A M, Li J, Wang L, Li X F, Bao Y G, Li J M, Wang H G. Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL population. Theoretical and applied genetics, 2014, 127(3): 659-675.
[37]   Reif J C, Maurer H P, Korzun V, Ebmeyer E, Miedaner T, Würschum T. Mapping QTLs with main and epistatic effects underlying grain yield and heading time in soft winter wheat. Theoretical and Applied Genetics, 2011, 123(2): 283-292.
[38]   Groos C, Robert N, Bervas E, Charmet G. Genetic analysis of grain protein-content, grain yield and thousand-kernel weight in bread wheat. Theoretical and Applied Genetics, 2003, 106(6): 1032-1040.
[39]   Sun X Y, Wu K, Zhao Y, Kong F M, Han G Z, Jiang H M, Huang X J, Li R J, Wang H G, Li S S. QTL analysis of kernel shape and weight using recombinant inbred lines in wheat. Euphytica, 2009, 165(3): 615-624.
[40]   Röder M S, Huang X Q, Börner A. Fine mapping of the region on wheat chromosome 7D controlling grain weight. Functional Integrative Genomics, 2008, 8(1): 79-86.
[41]   李伟. 干旱胁迫条件下小麦冠层及产量性状的QTL定位[D]. 郑州: 河南农业大学, 2008.
Li W. QTL mapping for canopy and yield traits in wheat under drought stress[D]. Zhengzhou: Henan Agricultural university, 2008. (in Chinese)
[42]   Wang Z Q, Yu C Y, Liu X, Liu S J, Yin C B, Liu L L, Lei J G, Jiang L, Yang C, Chen L M, Zhai H Q, Wan J M. Identification of Indica rice chromosome segments for the improvement of Japonica inbreds and hybrids. Theoretical and Applied Genetics, 2012, 124(7): 1351-1364.
[43]   Wang J S, Liu W H, Wang H, Li L L, Wu J, Yang X M, Li X Q, Gao A N. QTL mapping of yield-related traits in the wheat germplasm 3228. Euphytica, 2011, 177(2): 277-292.
[44]   Tsilo T G, Hareland G A, Simsek S, Chao S M, Anderson J A. Genome mapping of kernel characteristics in hard red spring wheat breeding lines. Theoretical and Applied Genetics, 2010, 121(4): 717-730.
[45]   Czyczy?o-Mysza I,Marcińska I,Skrzypek E, Chrupek M,Grzesiak S,Hura T,Stoja?owski S,My?ków B,Pawe? Milczarski P, Quarrie S. Mapping QTLs for yield components and chlorophyll a fluorescence parameters in wheat under three levels of water availability. Plant Genetic Resources, 2011, 9(2): 291-295
[46]   Wang E T, Xu X, Zhang L, Zhang H, Lin L, Wang Q, Li Q, Ge S, Lu B R, Wang W, He Z H. Duplication and independent selection of cell-wall invertase genes GIF1 and OsCIN1 during rice evolution and domestication. BMC Evolutionary Biology, 2010, 10: 108-120.
[47]   Salem Farag K F M. The inheritance and molecular mapping of genes for post-anthesis drought tolerance (PADT) in wheat [D]. Halle-Wittenberg: Martin Luther University, 2004.
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