作物学报 ›› 2016, Vol. 42 ›› Issue (11): 1592-1600.doi: 10.3724/SP.J.1006.2016.01592
王辉,梁前进,胡小娇,李坤,黄长玲,王琪,何文昭,王红武*,刘志芳*
WANG Hui,LIANG Qian-Jin,HU Xiao-Jiao,LI Kun,HUANG Chang-Ling,WANG Qi,HE Wen-Zhao,WANG Hong-Wu*,LIU Zhi-Fang*
摘要:
为研究玉米穗部性状对不同种植密度的遗传响应,以郑58和HD568为亲本构建的220个重组自交系群体为材料,于2014年春、2014年冬及2015年春分别在北京和海南进行3个种植密度的田间试验,调查玉米穗长、穗粗、穗行数和行粒数等表型性状。利用SAS软件计算穗部性状的最优线性无偏估计值(BLUP),并采用完备区间作图法进行QTL定位。结果表明,在3个种植密度下共检测到42个QTL,单个QTL可解释4.20%~14.07%的表型变异。3个种植密度下同时检测到位于第2染色体上控制穗行数的QTL。2个种植密度下同时检测到4个与穗粗、穗行数和行粒数有关的QTL,其中第4染色体上1个与穗行数有关的主效QTL,在低、中种植密度下可分别解释表型变异的10.88%和14.07%。此外,在第2、4和9染色体上检测到3个同时调控不同穗部性状的QTL。研究结果表明玉米穗部性状在不同种植密度下的遗传调控发生变化,在不同密度下共同检测到的稳定QTL可应用于精细定位或开发玉米耐密性分子标记用于辅助育种。
| [1]Ku L X, Zhao W M, Zhang J, Wu L C, Wang C L, Wang P A, Zhang W Q, Chen Y H. Quantitative trait loci mapping of leaf angle and leaf orientation value in maize (Zea mays L.). Theor Appl Genet, 2010, 121: 951–959 [2]Yan J B, Tang H, Huang Y Q, Zheng Y L, Li J S. Quantitative trait loci mapping and epistatic analysis for grain yield and yield components using molecular markers with an elite maize hybrid. Euphytica, 2006, 149: 121–131 [3]Li C, Li Y, Sun B, Peng B, Liu C, Liu Z Z, Yang Z Z, Li Q C, Tan W W, Zhang Y, Wang D, Shi Y S, Song Y C, Wang T Y, Li Y. Quantitative trait loci mapping for yield components and kernel-related traits in multiple connected RIL populations in maize. Euphytica, 2013, 19: 303–316 [4]Nikoli? A, An?elkovi? V, Dodig D, Drini? S M, Kravi? N, Mici?-Ignjatovi? D. Identification of QTLs for drought tolerance in maize: II. yield and yield components. Genetika, 2013, 45: 341–350 [5]Liu L, Du Y F, Huo D A, Wang M, Shen X M, Yue B, Qiu F Z, Zheng Y L, Yan J B, Zhang Z X. Genetic architecture of maize kernel row number and whole genome prediction. Theor Appl Genet, 2015, 128: 2243–2254 [6]Zhang Z H, Wu X Y, Shi C N, Wang R N, Li S F, Wang Z H, Liu Z H, Xue Y D, Tang G L, Tang J H. Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population. Mol General Genet, 2015, 291: 437–454 [7]Peter B, Namiko S N, David J. Quantitative variation in maize kernel row number is controlled by the FASCIATED EAR2 locus. Nat Genet, 2013, 45: 334–337 [8]Liu L, Du Y F, Shen X M, Li M F, Sun W, Huang J, Liu Z J, Tao Y S, Zheng Y L, Yan J B, Zhang Z X. KRN4 controls quantitative variation in maize kernel row number. Plos Genet, 2015, 11(11): e1005670 [9]Guo J, Su G, Zhang J, Wang G. Genetic analysis and QTL mapping of maize yield and associate agronomic traits under semi-arid land condition. Afr J Biotechnol, 2008, 7: 1829–1838 [10]Ribaut J M, Jiang C, Gonzalez-De-Leon D, Edmeades G O, Hoisington D A. Identification of quantitative trait loci under drought conditions in tropical maize. 2. yield components and marker-assisted selection strategies. Theor Appl Genet, 1997, 94: 887–896 [11]Gonzalo M, Holland J B, Vyn T J, Mclntyre L M. Direct mapping of density response in a population of B73 × Mo17 recombinant inbred lines of maize (Zea mays L.). Heredity, 2010, 104: 583–599 [12]Guo J, Chen Z, Liu Z, Wang B B, Song W B, Li W, Chen J, Dai J R, Lai J S. Identification of genetic factors affecting plant density response through QTL mapping of yield component traits in maize (Zea mays L.). Euphytica, 2011, 182: 409–422 [13]刘小刚. 玉米茎秆强度QTL定位研究. 中国农业科学院硕士学位论文, 北京, 2014 Liu X G. Quantitative Trait Locus Analysis of Stalk Strength in Maize. MS Thesis of Chinese Academy of Agricultural Sciences, Beijing, China, 2014 (in Chinese with English abstract) [14]马飞前. 玉米茎秆纤维性状QTL定位. 中国农业科学院硕士学位论文, 北京, 2014 Ma F Q. Mapping of Quantitative Trait Loci (QTL) for Stalk Fiber Traits in Maize. MS Thesis of Dissertation of Chinese Academy of Agricultural Sciences, Beijing, China, 2014 (in Chinese with English abstract) [15]Ganal M W, Gregor D, Andreas P, Aurélie B, Buckler E S, Alain C, Clarke J D, Graner E M, Hansen M, Joets J, Paslier M-C L, McMullen M D, Montalent P, Rose M, Sch?n C C, Sun Q, Walter H, Martin O C, Matthieu F. A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. Plos One, 2011, 6(12): e28334 [16]Van Ooijen J: JoinMap4.software for the Calculation of Genetic Linkage Maps in Experimental Populations. Kyazma B V, Wageningen, Netherlands, 2006. p 56 [17]Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M A R, Bender D, Maller J, Sklar P, Bakker P I W, Daly M J, Sham P C. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Human Genet, 2007, 81: 559–575 [18]Wang J K. QTL IciMapping: Integrated Software for Building Linkage Maps and Mapping Quantitative Trait Genes. International Plant and Animal Genome Conference XXI 2013. Scherago International, San Diego, CA, 2013 [19]Kosambi D D. The estimation of map distance from recombination valves. Annu Eugenia, 1994, 12: 172–175 [20]Knapp S, Stroup W, Ross W. Exact confidence intervals for heritability on a progeny mean basis1. Crop Sci, 1985, 25: 192–194 [21]Piepho H P, M?hring J, Melchinger A E, Büchse A. BLUP for phenotypic selection in plant breeding and variety testing. Euphytica, 2008, 161: 209–228 [22]王建康. 数量性状基因的完备区间作图方法. 作物学报, 2009, 35: 239–245 Wang J K. Inclusive composite interval mapping of quantitative trait genes. Acta Agron Sin, 2009, 35: 239–245 (in Chinese with English abstract) [23]Cai L, Li K, Yang X, Li J. Identification of large-effect QTL for kernel row number has potential for maize yield improvement. Mol Breed, 2014, 34: 1087–1096 [24]Yang C, Liu J, Rong T Z. Detection of quantitative trait loci for ear row number in F2 populations of maize. Genet Mol Res, 2015, 14: 14229–14238 [25]Li K, Yan J, Li J, Yang X. Genetic architecture of rind penetrometer resistance in two maize recombinant inbred line populations. BMC Plant Biol, 2014, 14: 152 [26]秦伟伟, 李永祥, 李春辉, 陈林, 吴迅, 白娜, 石云素, 宋燕春, 张登峰, 王天宇, 黎裕. 基于高密度遗传图谱的玉米籽粒性状QTL定位. 作物学报, 2015, 41: 1510–1518 Qin W W, Li Y X , Li C H, Chen L, Wu X, Bai N, Shi Y S, Song Y C, Zhang D F, Wang T Y, Li Y. QTL mapping for kernel related traits based on a high-density genetic map. Acta Agron Sin, 2015, 41: 1510–1518 (in Chinese with English abstract) [27]吕学高, 蔡一林, 陈天青, 徐德林, 王伟林, 刘志斋, 王久光. 玉米穗部性状QTL定位. 西南大学学报: 自然科学版, 2008, 30(2): 64–70 Lü X G, Cai Y L, Chen T Q, Xu D L, Wang W L, Liu Z Z, Wang J G. QTL mapping for ear traits in maize (Zea mays L.). J Southwest Univ (Nat Sci Edn), 2008, 30(2): 64–70 (in Chinese with English abstract) [28]Veldboom L R, Lee M. Genetic mapping of quantitative trait loci in maize in stress and nonstress environments: I. Grain yield and yield components. Crop Sci, 1996, 36: 1310–1319 [29]兰进好, 李新海, 高树仁, 张宝石, 张世煌. 不同生态环境下玉米产量性状QTL分析. 作物学报, 2005, 31: 1253–1259 Lan J H, Li X H, Gao S R, Zhang B S, Zhang S H. QTL analysis of yield components in maize under different environments. Acta Agron Sin, 2005, 31: 1253–1259 (in Chinese with English abstract) [30]Brown P J, Upadyayula N, Mahone G S, Tian F, Bradbury P J, Myles S, Holland J B, Flint-Garcia S, McMullen M D, Buckler E S, Rocheford T R. Distinct genetic architectures for male and female inflorescence traits of maize. PloS Genet, 2011, 7: 1276–1280 [31]Würschum T. Mapping QTL for agronomic traits in breeding population. Theor Appl Genet, 2012, 125: 201–210 [32]Cai L C, Li K, Yang X H, Li J S. Identification of large-effect QTL for kernel row number has potential for maize yield improvement. Mol Breed, 2014, 34: 1087–1096 [33]Tuberosa R, Salvi S, Sanguineti M C, Landi P, Maccaferri M, Conti S. Mapping QTLs regulating morpho-physiological traits and yield: case studies, shortcomings and perspectives in drought-stressed maize. Ann Bot, 2002, 89: 941–963 [34]Zhuang J Y, Lin H X, Lu J, Qian H R, Hittalmani S, Huang N, Zheng K L. Analysis of QTL environment interaction for yield components and plant height in rice. Theor Appl Genet, 1997, 95: 799–808 [35]Chen J, Zhu J. Genetic effects and genotype × environment interactions for cooking quality traits in Indica-japonica crosses of rice (Oryza sativa L.). Euphytica, 1999, 109: 9–15 [36]Shi C H, He C X, Zhu J, Chen J G. Analysis of genetic effects and genotype × environment interaction effects for apparent quality traits of indica rice. Chin J Rice Sci, 1999, 13: 179–182 (in English with Chinese abstract) [37]Huang N, Angeles E R, Domingo J, Magpantay S, Singh S, Zhang G, Kumaravadivel N, Bennett J, Khush G S. Pyramiding of bacterial blight resistance genes in rice: marker-assisted selection using RFLP and PCR. Theor Appl Genet, 1997, 95: 313–320 [38]Tanksley S D, Ahn N, Causse M, Coffman R, Fulton T, McCouch S R, Second G, Tai T, Wang Z, Wu K, Yu Z. RFLP mapping of the rice genome. In: Rice Genetics II. Los Banos, Laguna: IRRI, 1991. pp 435–442 |
| [1] | 刘恩波, 陈静, 李红星, 于宁宁, 任佰朝, 赵斌, 刘鹏, 张吉旺. 遮阴改变源-库平衡和调节碳水化合物代谢进而抑制夏玉米幼穗发育[J]. 作物学报, 2026, 52(6): 1891-1901. |
| [2] | 梁进宇, 尹嘉德, 王红丽, 张国平, 侯慧芝, 董博, 马明生. 基于无人机高光谱和机器学习的旱地饲用玉米叶片氮含量估测[J]. 作物学报, 2026, 52(6): 1788-1801. |
| [3] | 孙淑凤, 许振南, 黄嘉鑫, 翁建峰, 李新海. 玉米MAPK家族全基因组鉴定及其对拟轮枝镰孢菌感染的响应[J]. 作物学报, 2026, 52(5): 1291-1308. |
| [4] | 张宁宁, 滕雨菲, 任娜娜, 魏兴卓, 闫书豪, 樊可心, 王永宏, 陈文康, 张兴华, 朱万超, 徐淑兔, 薛吉全. 201份玉米自交系抗旱表型评价及可塑性分析[J]. 作物学报, 2026, 52(5): 1309-1325. |
| [5] | 张鸿蓉, 王菲儿, 李盼, 仇海龙, 朱静, 赵连豪, 南运有, 何蔚, 樊志龙, 胡发龙, 柴强, 殷文. 减量20%灌水与25%有机肥替代化肥提高青贮玉米产量的光合特性[J]. 作物学报, 2026, 52(5): 1487-1500. |
| [6] | 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. |
| [7] | 韩亚鑫, 何冠华, 张小琼, 张登峰, 李永祥, 刘旭洋, 王天宇, 黎裕, 邹华文, 李春辉. 基于RNA-Seq和BSA-Seq联合分析挖掘玉米侧根密度基因资源[J]. 作物学报, 2026, 52(5): 1341-1352. |
| [8] | 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. |
| [9] | 张全军, 吴东丽, 刘聪, 朱永超, 杨大生, 孔祥胜. 1981—2024年长江中下游油菜发育期时空格局演变特征[J]. 作物学报, 2026, 52(4): 1140-1152. |
| [10] | 蔡宏玮, 于爱忠, 姜科强, 王鹏飞, 王玉珑, 霍建喆, 庞小能, 尹波, 尚永盼. 干旱灌区有机肥替代部分化肥促进甜玉米产量提升的关键机制[J]. 作物学报, 2026, 52(4): 1166-1180. |
| [11] | 田红丽, 杨扬, 范亚明, 易红梅, 郭丹丹, 王凤格, 赵久然. 适于玉米品种鉴定的一套三等位变异SNP新型标记组合[J]. 作物学报, 2026, 52(4): 993-1005. |
| [12] | 杨亚莉, 徐明睿, 马越飞, 海艺蕊, 刘凯栋, 刘万茂, 孙颖. 玉米根尖及整根响应缺铁的转录组比较研究[J]. 作物学报, 2026, 52(4): 1006-1021. |
| [13] | 马海会, 张国平, 杨思存, 王红丽. 不同密度下氮肥运筹对半干旱区青贮玉米碳氮积累与转运特征的影响[J]. 作物学报, 2026, 52(4): 1193-1207. |
| [14] | 马亮, 马璐, 张舒钰, 章慧敏, 王仁明, 宋旭东, 张振良, 冒宇翔, 陆虎华, 陈国清, 郝德荣, 周广飞. 玉米苞叶数目转录组分析及候选基因鉴定[J]. 作物学报, 2026, 52(3): 790-801. |
| [15] | 孟成, 王哲. 玉米ZmPFK基因家族全基因组鉴定及响应胁迫表达分析[J]. 作物学报, 2026, 52(3): 764-779. |
|
||