Abstract：Deeply studied of the genetic mechanisms for ear-related traits in maize (Zea mays) can provide references for using ear-related traits to breed high-yielding maize varieties. Thus, the 2 F1 hybrids and their derived 202 (POP1) and 218 (POP2) F2 populations with the common male parent TS141 were developed to identify quantitative trait loci (QTLs) for ear number per plant (EN), ear weight (EW), cob weight (CW), 100-kernel weight (KW), ear length (EL) and kernel ratio (KR) via composite interval mapping (CIM) in this study. It showed that EN, EW, KW and EL of the 2 F1 showed positive over-parent heterosis significantly, CW showed positive over-parent heterosis weakly, and KR showed mid-parent heterosis significantly. The F1 heterosis index and relative heterosis simultaneously displayed that EW>EN>EL>KW>CW>KR. However, the F2 advantage reduction rate showed that EW>EN>EL>KW>CW>KR. Totally 49 QTLs were identified in the 2 F2 populations, these QTLs were located on the 10 chromosomes and explained 4.10%~15.73% of phenotypic variation in single QTL. QTLs for EW and KR mainly showed additive effects, QTLs for EN, KW and EL mainly showed non-additive effects, and QTLs for CW showed both half of additive and non-additive effects. Eight stable QTLs (sQTLs) were simultaneously identified across POP1 and POP2, namely, the sQTL controlled EW, CW and KR in Bin1.03-1.04, the sQTL controlled KR in Bin1.06-1.07, the sQTL controlled KW in Bin4.04, the sQTL controlled EN in Bin6.05, the sQTL controlled KR in Bin7.02 and the sQTL controlled CW in Bin9.04, respectively. These results can lay a foundation for further revealing genetic mechanism for maize ear-related traits, and these sQTLs are stably expressed under 2 genetic backgrounds may play an important role in controlling maize ear-related traits and can be used as the candidate loci for marker-assisted selection (MAS), fine mapping and positional cloning.
[1]常立国, 何坤辉, 崔婷婷, 等.玉米出籽率的QTL定位及其与环境互作分析[J].农业生物技术学报, 2017, 25(4):517-525
[2]陈志辉, 曹钟洋, 汤彬, 等.大田环境下玉米抗旱相关性状QTL定位[J].华北农学报, 2012, 27(1):79-86
[3]刁西洲, 王红武, 胡小娇, 等.玉米穗部性状遗传和杂种优势分析[J].作物杂志, 2015, (4):36-40
[4]蒋辅燕, 陈洪梅, 张培高, 等.28个玉米杂交组合产量及穗部性状研究[J].西南农业学报, 2013, 26(3):903-908
[5]李永祥, 王阳, 石云素, 等.玉米籽粒构型与产量性状的关系及QTL作图[J].中国农业科学, 2009, 42(2):408-418
[6]李忠南, 王越人, 邬生辉, 等.玉米品种穗轴重和出籽率性状的相关及遗传关系研究[J].玉米科学, 2012, 20(5):33-39
[7]彭云玲, 赵小强, 任续伟, 等.干旱胁迫对不同株型玉米大喇叭口期生长的影响 [J].中国沙漠, 2013, 33(4):1064-1070
[8]彭云玲, 赵小强, 任续伟, 等.开花期干旱胁迫对不同基因型玉米生理特性和产量的影响[J].干旱地区农业研究, 2014, 32(3):9-14
[9]彭云玲, 赵小强, 闫慧萍, 等.不同玉米自交系耐深播性评价及遗传多样性分析[J].草业学报, 2016, 25(7):73-86
[10]石云素, 黎裕, 王天宇, 等.2006. 玉米种质资源描述规范和数据标准[M]. 中国农业出版社, 北京. pp. 1-98. (Shi Y S, Li Y, Wang T Y, et al. 2006. Standard of description for maize germplasm and data[M]. China Agriculture Press. Beijing. pp. 1-98.)
[11]宋继娟, 柳金来, 周柏明, 等.玉米穗部性状与产量关系的研究 [J].吉林农业科学, 2006, 31(4):11-13
[12]孙海艳, 徐德林, 蔡一林, 等. 玉米穗部性状的多世代联合遗传分析[J].植物遗传资源学报, 2012, 13(6):1005-1010
[13]谭巍巍, 王阳, 李永祥, 等.不同环境下多个玉米穗部性状的QTL分析[J].中国农业科学, 2011, 44(2):233-244
[14]杨光宇, 郑惠玉, 韩春凤.栽培大豆（G.max）×半野生大豆（G.gracilis）后代主要农艺性状遗传参数的初步分析 [J].作物学报, 1992, 18(6):439-446
[15]闫海霞, 柳家友, 吴伟华.夏玉米主要穗部性状与单株产量之间的相关和通径分析[J].山东农业科学, 2008, (1):7-9
[16]张伟强, 库丽霞, 张君, 等.玉米出籽率、籽粒深度和百粒重的QTL分析[J].作物学报, 2013, 39(3):455-463
[17]赵延明.玉米果穗出籽率遗传效应分析[J].中国农学通报, 2009, 25(03):72-74
[18]Almeida G D, Nair S, Borem A, et al.Molecular mapping across three populations reveals a QTL hotspot region on chromosome 3 for secondary traits associated with drought tolerance in tropical maize[J].Molecular Breeding, 2014, 34:701-715
[19]Austin D F, Lee M. Comparative mapping in F2:3 and F6:7 generations of quantitative trait loci for grain yield and yield components in maize [J].Theoretical and Applied Genetics, 1996, 92: 817-826
[20]Dong Y B, Zhang Z W, Shi Q L, et al.QTL consistency for agronomic traits across three generations and potential applications in popcorn[J].Journal of Integrative Agriculture, 2015, 14(12):2547-2557
[21]James M G, Robertson D S, Myers A M, .Characterization of the maize gene sugary 1, a determinant of starch composition in kernels[J].Plant Cell, 1995, 7(4):417-429
[22]Jiao Y P, Peluso P, Shi J H, et al. Improved maize reference genome with single-molecule technologies[J].Nature, 2017, 546:524-527
[23]Li J Z, Zhang Z W, Li Y L, et al. QTL consistency and meta-analysis for grain yield components in three generations in maize[J].Theoretical and Applied Genetics, 2011, 122:771-782
[24]Saghai-Maroof M A, Yue Y G, Xiang Z X, et al. Identification of quantitative trait loci controlling resistance to gray leaf plot disease in maize [J].Theoretical and Applied Genetics, 1996, 93:539-546
[25]Su C, Wang W, Gong S, et al.High density linkage map construction and mapping of yield trait QTLs in maize (Zea mays) using the genotyping-by-sequencing (GBS) technology, [J].Front Plant Science, 2017, 8:706-706
[26]McCouch S R, Cho Y G, Yano P E, et al.Report on QTL nomenclature[J].Rice Genet Newslett, 1997, 14:11-13
[27]Messmer R, Fracheboud Y, Banziger M, et al.Drought stress and tropical maize: QTL-by-environment interactions and stability of QTLs across environments for yield components and secondary traits,[J].Theoretical and Applied Genetics, 2009, 119:913-930
[28]Peng B, Li Y X, Wang Y, et al.. QTL analysis for yield components and kernel-related traits in maize across multi-environments, [J].Theoretical and Applied Genetics, 2011, 22(7):1305-1320
[29]Ribaut J M, Jiang C, Gonzalez-de-Leon D, et al. Identification of quantitative trait loci under drought conditions in tropical maize 2. Yield components and marker-assisted selection strategies[J].Theoretical and Applied Genetics, 1997, 94:887-896
[30]Sabadin P K, de Souza C L, de Souza A P, et al.QTL mapping for yield components in a tropical maize population using microsatellite markers[J].Hereditas, 2008, 145:194-203
[31]Séne M, Thévenot C, Hoffmann D, et al. QTL for grain dry milling properties, composition and virtuousness in maize recombinant inbred lines[J].Theoretical and Applied Genetics, 2001, 102:591-599
[32]Stuber C W, Edwards M D, Wendel J,.F1 molecular marker facilitated investigations of quantitative trait loci in maize. Ⅱ. Factors influencing yield and its component traits,.[J].Crop Science, 1987, 27:639-648
[33]Tuberosa R, Salvi S, Sanguineti M C, et al.Mapping QTL regulating morpho-physiological traits and yields: case studies, shortcomings and perspectives in drought-stress maize,[J].Annals of Botany, 2002, 89:941-963
[34]Upadyayula N, da-Silva H S, Bohn M O, et al.Genetic and QTL analysis of maize tassel and ear inflorescence architecture [J].Theoretical and Applied Genetics, 2006, 112:592-606
[35]Van-Ooijen J W, 2006.JoinMap? 4: software for the calculation of genetic linkage maps in experimental populations[M]. Kyazma BV (http://www.kyazma.nl/index.php/mc.JoinMap/sc. Evaluate/).
[36]Veldboom L R, Lee M, .Molecular-marker-facilitated studies of morphological traits in maize. Ⅱ: Determination of QTLs for grain yield and yield components[J].Theoretical and Applied Genetics, 1994, 89:451-458
[37]Wang S, Basten C J, Zeng Z B, 2007.Windows QTL Cartographer 2.5. Department of statistics[M]. North Carolina State University, Raleigh, NC (http://statgen.ncsu.edu/qtlcart/ WQTLCart.htm).
[38]Zhao X Q, Peng Y L, Zhang J W, et al.Mapping QTLs and meta-QTLs for two inflorescence architecture traits in multiple maize populations under different watering environments , [J].Molecular Breeding, 2017, 37:91-91
