作物学报 ›› 2013, Vol. 39 ›› Issue (09): 1562-1568.doi: 10.3724/SP.J.1006.2013.01562
陈春侠**,陆明洋**,尚爱兰,王玉民,席章营*
CHEN Chun-Xia**,LU Ming-Yang**,SHANG Ai-Lan,WANG Yu-Min,XI Zhang-Ying*
摘要:
籽粒大小是影响玉米产量的关键因素。本研究基于59份玉米染色体单片段代换系(SSSL)纯合体,对玉米百粒重性状进行2年6个试验环境的表型鉴定,利用t测验和重叠群作图的方法对SSSL内代换片段上的百粒重效应进行了QTL分析。共检测出20个百粒重QTL,分布在玉米的8条染色体上,其中14个(70.0%)在2个以上试验环境中被重复检出,4个(20.0%)在4个以上试验环境中被重复检出,在全部6个试验环境中重复检出且基因加性效应值较大的玉米百粒重QTL是位于玉米第5染色体Bin5.05区SSR分子标记bnlg278和umc1680附近的q100kw-5-3。研究结果为玉米籽粒大小性状相关基因的进一步精细定位和克隆奠定了基础。
[1]Peng B(彭勃), Wang Y(王阳), Li Y-X(李永祥), Liu C(刘成), Liu Z-Z(刘志斋), Wang D(王迪), Tan W-W(谭巍巍), Zhang Y(张岩), Sun B-C(孙宝成), Shi Y-S(石云素), Song Y-C(宋燕春), Wang T-Y(王天宇), Li Y(黎裕). QTL analysis for yield components and kernel-related traits in maize under different water regimes. Acta Agron Sin (作物学报), 2010, 36(11): 1832–1842 (in Chinese with English abstract)[2]Tang J-H(汤继华), Yan J-B(严建兵), Ma X-Q(马西青), Teng W-T(滕文涛), Meng Y-J(孟义江), Dai J-R(戴景瑞), Li J-S(李建生). Genetic dissection for grain yield and its components using an “Immortalized F2 Population” in maize. Acta Agron Sin (作物学报), 2007, 33(8): 1299–1303 (in Chinese with English abstract)[3]Zhao P(赵璞), Liu R-X(刘瑞响), Li C-P(李成璞), Xing X-R(邢向茹), Cao X-L(曹晓良), Tao Y-S(陶勇生), Zhang Z-X(张祖新). QTL mapping for grain yield associated traits using Ye478 introgression lines in maize. Sci Agric Sin (中国农业科学), 2011, 44(17): 3508–3519 (in Chinese with English abstract)[4]Messmer R, Fracheboud Y, Banziger M, Vargas M, Stamp P, Ribaut J M. Drought stress and tropical maize: QTL-by-environment interactions and stability of QTLs across environments for yield components and secondary traits. Theor Appl Genet, 2009, 119: 913–930[5]Doebley J, Bacigalupo A, Stec A. Inheritance of kernel weight in two maize-teosinte hybrid populations: Implications for crop evolution. Heredity, 1994, 85: 191–195[6]Goldman I L, Rocheford T R, Dudley J W. Molecular markers associated with maize kernel oil concentration in an Illinois high protein × Illinois low protein cross. Crop Sci, 1994, 34: 908–915[7]Xi Z-Y(席章营), Wu J-Y(吴建宇). Prospect of the secondary populations in crop. J Agric Biotechnol (农业生物技术学报), 2006, 14 (1): 128–134 (in Chinese with English abstract)[8]Eshed Y, Zamir D. An introgression line population of Lyeopersicon pennellii in the cultivated tomato enables the identification and fine mapping of yield associated QTL. Genetics, 1995, 141: 1147–1162[9]He F-H(何凤华). Development of single segment substitution lines (SSSLs) and QTL analysis in rice(Oryza sativa L.). PhD Dissertation of South China Agricultural University, 2003 (in Chinese with English abstract) [10]Xi Z-Y(席章营). Identification and mapping of QTLs based on chromosome single segment substitution lines in rice (Oryza sativa L.). PhD Dissertation of South China Agricultural University (华南农业大学), 2004 (in Chinese with English abstract) [11]He F H, Xi Z Y, Zeng R Z, Talukdar A, Zhang G Q. Identification of QTLs for plant height and its components by using single segment substitution lines in rice (Oryza sativa L.). Rice Sci, 2005, 12: 151–156[12]Liu G F, Zhang Z M, Zhu H T, Zhao F M, Ding X H, Zeng R Z, Li W T, Zhang G Q. Detection of QTLs with additive effects and additive-by-environment interaction effects on panicle number in rice (Oryza sativa L.) with single segment substitution lines. Theor Appl Genet, 2008, 116: 923–931 [13]Wang B-T(王帮太), Zhang S-H(张书红), Xi Z-Y(席章营). QTL Mapping for ear length based on chromosome single segment substitution lines of 87-1 Zong3 in maize. J Maize Sci (玉米科学), 2012, 20(3):9–14 (in Chinese with English abstract) [14]Lu M Y, Li X H, Shang A L, Wang Y M, Xi Z Y. Characterization of a set of chromosome single-segment substitution lines derived from two sequenced elite maize inbred lines. Maydica, 2012, 56: 399–407[15]Liu G F, Zeng R Z, Zhu H T, Zhang Z M, Ding X H, Zhao F M, Li W T, Zhang G Q. Dynamic expression of nine QTLs for tiller number detected with single segment substitution lines in rice. Theor Appl Genet, 2009, 118: 443–453 [16]Zhang N, Brewer M T, van der Knaap E. Fine mapping of fw3.2 controlling fruit weight in tomato. Theor Appl Genet, 2012, 125: 273–284[17]Frary A, Nesbitt T C, Frary A, Grandillo S, van der Knaap E, Cong B, Liu J, Meller J, Elber R, Alpert KB, Tanksley S D. fw2.2: A quantitative trait locus key to the evolution of tomato fruit size. Science, 2000, 289: 85–88[18]Paterson A H, DeVerna J W, Lanini B, Tanksley S D. Fine mapping of quantitative trait loci using selected overlapping recombinant chromosomes, in an interspecies cross of tomato. Genetics, 1990, 124: 735–742[19]McCouch S R, Cho Y G, Yano M, Paul E, Blinstruub M, Morishima H, Kinosita T. Report on QTL nomenclature. Rice Genet Newsl, 1997, 14: 11–13[20]Guo J F, Su G Q, Zhang J P, Wang G Y. Genetic analysis and QTL mapping of maize yield and associate agronomic traits under semi-arid land condition. Afr J Biotechnol, 2008, 7:1829–1838[21]Lu G H, Tang J H, Yan J B, Ma X Q, Li J S, Chen S J, Ma J C, Liu Z X, Zhu L, Zhang Y R, Dai J R. Quantitative trait loci mapping of maize yield and its components under different water treatments at flowering time. J Integr Plant Biol, 2006, 48: 1233−1243[22]Yang J-P(杨俊品), Rong T-Z(荣廷昭), Xiang D-Q(向道权), Tang H-T(唐海涛), Huang L-J(黄烈健), Dai J-R(戴景瑞). QTL mapping of quantitative traits in maize. Acta Agron Sin (作物学报), 2005, 31(2): 188–196 (in Chinese with English abstract)[23]Veldboom L R, Lee M. Molecular-marker-facilitated studies of morphological traits in maize. II: Determination of QTLs for grain yield and yield components. Theor Appl Genet, 1994, 89: 451–458[24]Yan J-B(严建兵), Tang H(汤华), Huang Y-Q(黄益勤), Zheng Y-L(郑用琏), Chander S, Li J-S(李建生). QTL mapping major and epistatic analysis for yield and yield components using molecular markers. Chin Sci Bull (科学通报), 2006, 51(12):1413–1421 (in Chinese)[25]Li J Z, Zhang Z W, Li Y L, Wang Q L, Zhou Y G. QTL consistency and meta-analysis for grain yield components in three generations in maize. Theor Appl Genet, 2011, 122: 771–782[26]Melchinger A E, Utz H F, Schon C C. Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects. Genetics, 1998, 149: 383–403[27]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[28]Yang J-P(杨俊品), Rong T-Z(荣廷昭). Improvement of RFLP marker facilitated studies of QTLs in maize. J Maize Sci (玉米科学), 1999, 7(1): 18–24 (in Chinese with English abstract)[29]Liu Z-H(刘宗华), Tang J-H(汤继华), Wei X-T(卫晓轶), Wang C-L(王春丽), Tian G-W(田国伟), Hu Y-M(胡彦民), Chen W-C(陈伟程). QTL mapping of ear traits under low and high nitrogen conditions in maize. Sci Agric Sin (中国农业科学), 2007, 40(11): 2409–2417 (in Chinese with English abstract)[30]Yang G H, Li Y L, Wang Q L, Zhou Y G, Zhou Q, Shen B T, Zhang F F, Liang X J. Detection and integration of quantitative trait loci or grain yield components and oil content in two connected recombinant inbred line populations of high-oil maize. Mol Breed, 2012, 29: 313–333[31]Lan J-H(兰进好), Li X-H(李新海), Gao S-R(高树仁), Zhang B-S(张宝石), Zhang S-H(张世煌). QTL analysis of yield components in maize under different environments. Acta Agron Sin (作物学报), 2005, 31(10): 1253–1259 (in Chinese with English abstract) [32]Xiang D-Q(向道权), Cao H-H(曹海河), Cao Y-G(曹永国), Yang J-P(杨俊品), Huang J-J(黄烈健), Wang S-C(王守才), Dai J-R(戴景瑞). Construction of a yield genetic map and location of for component traits in maize by quantitative trait loci SSR markers. Acta Genet Sin (遗传学报), 2001, 28(8): 778–784 (in Chinese with English abstract)[33]Austin D F, Lee M. Detection of quantitative trait loci for grain yield and yield components in maize across generations in stress and nonstress environments. Crop Sci, 1998, 38: 1296–1308[34]Wang Y(王阳), Liu C(刘成), Wang T-Y(王天宇), Shi Y-S(石云素), Song Y-C(宋燕春), Li Y(黎裕). QTL analysis of yield components in maize under diferent water regirues. J Plant Genet Resour (植物遗传资源学报), 2007, 8(2): 179–183 (in Chinese with English abstract)[35]Ma J-L(马金亮). Analysis of QTL for yield and related traits using founder inbred lines in maize. Master dissertation of Henan Agricultural University, 2010 (in Chinese with English abstract)[36]Yano M, Kojima S, Takahashi Y, Lin H X, Sasaki T. Genetic control of flowering time in rice, a short-day plant. Plant Physiol, 2001, 127: 1425–1429[37]Yano M, Harushima Y, Nagamura Y, Kurata N, Minobe Y, Sasaki T. Identification of quantitative trait loci controlling heading date in rice using a high-density linkage map. Theor Appl Genet, 1997, 95: 1025–1032[38]Lin S Y, Sasaki T, Yano M. Mapping quantitative trait loci controlling seed dormancy and heading date in rice, Oryza sativa L., using backcross inbred lines. Theor Appl Genet, 1998, 96: 997–1003[39]Yamamoto T, Lin H X, Sasaki T, Yano M. Identification of heading date quantitative trait locus Hd6 and characterization of its epistatic interactions with Hd2 in rice using advanced backcross progeny. Genetics, 2000, 154: 885–891[40]Lin H X, Ashikari M, Yamanouchi U, Sasaki T, Yano M. Identification and characterization of a quantitative trait locus Hd9, controlling heading date in rice. Breed Sci, 2002, 52: 35–41[41]LeCLere S, Schmelz E A, Chourey P S. Sugar levels regulate tryptophan-dependent auxin biosynthesis in developing maize kernels. Plant Physiol, 2010, 153: 306–318[42]Sheridan W F, Neuffer M G. Defective kernel mutants of maize II. Morphological and embryo culture studies. Genetics, 1980, 95:945–960[43]Sheridan W F, Neuffer M G. Genetic control of embryo and endosperm development in maize. In: Reddy G M, Coe E H, eds. Gene Structure and Function in Higher Plants. New Delhi: Oxford & IBH Publishing Company, 1986. pp 105–122[44]Scanlon M J, Stinard P S, James M G, Myers A M, Robertson D S. Genetic analysis of 63 mutations affecting maize kernel development isolated from mutator stocks. Genetics, 1994, 136: 281-294[45]Neuffer M G, Sheridan W, Bendbow E. Rescue of lethal defective kernel mutants by genetic manipulation. Maize Genetics Cooperation Newsletter, 1978, 52:84-88[46]Neuffer M G, England D J. Induced mutations with confirmed locations. Maize Genetics Cooperation Newsletter, 1995, 69:43-46[47]Lai J S, Li R Q, Xu X, Jin W W, Xu M L, Zhao H N, Xiang Z K, Song W B, Ying K, Zhang M, Jiao Y P, Ni P X, Zhang J G, Li D, Guo X S, Ye K X, Jian M, Wang B, Zheng H S, Liang H Q, Zhang X Q, Wang S C, Chen S J, Li J S, Fu Y, Springer N M, Yang H M, Wang J, Dai J R, Schnable P S, Wang J. Genome-wide patterns of genetic variation among elite maize inbred lines. Nat Genet, 2010, 42: 1027–1030 |
[1] | 肖颖妮, 于永涛, 谢利华, 祁喜涛, 李春艳, 文天祥, 李高科, 胡建广. 基于SNP标记揭示中国鲜食玉米品种的遗传多样性[J]. 作物学报, 2022, 48(6): 1301-1311. |
[2] | 崔连花, 詹为民, 杨陆浩, 王少瓷, 马文奇, 姜良良, 张艳培, 杨建平, 杨青华. 2个玉米ZmCOP1基因的克隆及其转录丰度对不同光质处理的响应[J]. 作物学报, 2022, 48(6): 1312-1324. |
[3] | 胡文静, 李东升, 裔新, 张春梅, 张勇. 小麦穗部性状和株高的QTL定位及育种标记开发和验证[J]. 作物学报, 2022, 48(6): 1346-1356. |
[4] | 王丹, 周宝元, 马玮, 葛均筑, 丁在松, 李从锋, 赵明. 长江中游双季玉米种植模式周年气候资源分配与利用特征[J]. 作物学报, 2022, 48(6): 1437-1450. |
[5] | 杨欢, 周颖, 陈平, 杜青, 郑本川, 蒲甜, 温晶, 杨文钰, 雍太文. 玉米-豆科作物带状间套作对养分吸收利用及产量优势的影响[J]. 作物学报, 2022, 48(6): 1476-1487. |
[6] | 陈静, 任佰朝, 赵斌, 刘鹏, 张吉旺. 叶面喷施甜菜碱对不同播期夏玉米产量形成及抗氧化能力的调控[J]. 作物学报, 2022, 48(6): 1502-1515. |
[7] | 徐田军, 张勇, 赵久然, 王荣焕, 吕天放, 刘月娥, 蔡万涛, 刘宏伟, 陈传永, 王元东. 宜机收籽粒玉米品种冠层结构、光合及灌浆脱水特性[J]. 作物学报, 2022, 48(6): 1526-1536. |
[8] | 单露英, 李俊, 李亮, 张丽, 王颢潜, 高佳琪, 吴刚, 武玉花, 张秀杰. 转基因玉米NK603基体标准物质研制[J]. 作物学报, 2022, 48(5): 1059-1070. |
[9] | 于春淼, 张勇, 王好让, 杨兴勇, 董全中, 薛红, 张明明, 李微微, 王磊, 胡凯凤, 谷勇哲, 邱丽娟. 栽培大豆×半野生大豆高密度遗传图谱构建及株高QTL定位[J]. 作物学报, 2022, 48(5): 1091-1102. |
[10] | 许静, 高景阳, 李程成, 宋云霞, 董朝沛, 王昭, 李云梦, 栾一凡, 陈甲法, 周子键, 吴建宇. 过表达ZmCIPKHT基因增强植物耐热性[J]. 作物学报, 2022, 48(4): 851-859. |
[11] | 刘磊, 詹为民, 丁武思, 刘通, 崔连花, 姜良良, 张艳培, 杨建平. 玉米矮化突变体gad39的遗传分析与分子鉴定[J]. 作物学报, 2022, 48(4): 886-895. |
[12] | 闫宇婷, 宋秋来, 闫超, 刘爽, 张宇辉, 田静芬, 邓钰璇, 马春梅. 连作秸秆还田下玉米氮素积累与氮肥替代效应研究[J]. 作物学报, 2022, 48(4): 962-974. |
[13] | 徐宁坤, 李冰, 陈晓艳, 魏亚康, 刘子龙, 薛永康, 陈洪宇, 王桂凤. 一个新的玉米Bt2基因突变体的遗传分析和分子鉴定[J]. 作物学报, 2022, 48(3): 572-579. |
[14] | 王娟, 张彦威, 焦铸锦, 刘盼盼, 常玮. 利用PyBSASeq算法挖掘大豆百粒重相关位点与候选基因[J]. 作物学报, 2022, 48(3): 635-643. |
[15] | 宋仕勤, 杨清龙, 王丹, 吕艳杰, 徐文华, 魏雯雯, 刘小丹, 姚凡云, 曹玉军, 王永军, 王立春. 东北主推玉米品种种子形态及贮藏物质与萌发期耐冷性的关系[J]. 作物学报, 2022, 48(3): 726-738. |
|