摘要
玉米重要性状QTL定位是分子标记辅助选择的前提条件,对于提高育种效率有重要意义。本研究以当前大面积推广的一个优良玉米杂交种郑单958的两个亲本(郑58×昌7-2)构建含有225个家系的F_(2:3)群体为基础材料,构建了SSR分子标记遗传连锁图谱,并对产量和相关性状进行了QTL作图。在5个环境条件下(2007年在郑州、济源、西昌,2008年在郑州、济源)进行田间试验,利用复合区间作图法对穗长、穗粗、穗行数、行粒数、轴粗、单穗重、穗粒重、百粒重9个产量相关性状和抽雄期、吐丝期、散粉期3个生育期性状进行QTL定位和效应分析;利用基于混合线性模型的复合区间作图法,分析产量相关性状和生育期性状的上位性及与环境互作效应。主要结论如下:
1.以225个F_2单株为作图群体,利用180个多态性SSR标记,构建了覆盖玉米全基因组的分子标记遗传连锁图谱,覆盖玉米10条染色体,图谱总长度1 978.7 cM,平均间距为11.0 cM。同IBM群体连锁图谱相比,共同SSR标记在连锁图谱位置和顺序基本一致。在P<0.05和P<0.01水平上观察到22个(12.22%)分子标记发生了偏分离。个体基因型组成来源于母本郑58的纯合染色体片段在8.98%-33.78%之间,平均23.47%;基因型组成中来源于父本昌7-2的纯合染色体片段在10.67%-34.67%之间,平均23.53%。双亲的杂合片段在20.00%-57.78%,平均为47.71%。整个群体中,双亲染色体同源片段的基本分离符合1:2:1的理论比例,该F_(2:3)群体是一个随机群体,为下一步QTL定位奠定基础。
2.在5个环境条件下,对亲本和225个F_(2:3)家系群体的9个产量相关性状和3个生育期性状进行调查。对亲本自交系及F_(2:3)群体的考察性状表型分析,亲本自交系在穗粗、穗行数、轴粗和出籽率性状的均值昌7-2明显大于郑58;而穗长上郑58要明显大于昌7-2;在行粒数上昌7-2和郑58差异不大;F1表现明显的超亲优势;F_(2:3)群体各个性状在所有环境下均表现不同程度的双向超亲分离,呈连续性正态分布。相关性分析表明:产量相关性状间和生育期性状间均存在显著或极显著相关性;同时进行方差分析:所有性状在家系间、环境间、家系和环境互作均呈现显著或极显著的差异。
3. 5个环境条件下及联合分析共检测到111个与9个产量相关性状的QTL,单个QTL的贡献率为3.39%-31.15%,14个QTL的贡献率大于10%,其中穗长QTL qEL3-1和qEL4、穗粗QTL qED3、穗行数QTL qRN3、行粒数QTL qKR5、轴粗QTL qCD5-1和百粒重QTL qHKW1-1在5种环境条件下及合并分析均被检测到,表型贡献率较大且环境稳定性好,可以作为进一步精细定位和分子标记辅助选择的主要目标QTL。此外,还发现在第1染色体umc1703-umc1590、第3染色体bnlg1325-umc2369和bnlg420-umc1209、第5染色体的umc1800-umc2304和第6染色体的umc1257-phi031标记区间检测到多个产量及构成因子的QTL,表现为QTL的关键区段分布。部分显性和加性是产量相关性状的主要遗传基础。
4.对9个产量及其构成因子分别进行上位性及与环境互作分析,没有检测到影响轴粗的上位性QTL,共检测到20对上位性QTL,存在加性×加性、加性×显性、显性×显性效应的互作,贡献率为0.04%-2.41%。说明上位性效应对产量及相关性状的形成也有一定作用。其中穗粒重的2对上位性QTL和出籽率的2对上位性QTL均与环境互作效应显著,贡献率0.33%-0.91%。大多数上位性QTL在单个位点主效应不显著,本身对性状表达没有效应,但通过位点间的互作影响性状的表现。
5. 5个环境条件下及合并分析共检测到52个与3个生育期性状相关的QTL,单个QTL的贡献率为4.28%-19.59%,其中17个QTL的贡献率大于10%,其中抽雄期QTL qTE5-2、散粉期QTL qAN1-2和吐丝期QTL qSE3-1在4种环境条件及合并分析下均被检测到,表型贡献率较大且环境稳定性好,这些主效QTL可以直接用于分子标记辅助选择。在第1染色体1.05-1.07区域(qTE1-1、qTE1-2、qAN1-2、qAN1-3、qAN1-4、qSE1-2、qSE1-3)、第3染色体3.05-3.06区域(qTE3-1、qAN3-1、qSE3-1)、第5染色体5.08区域(qTE5-1、qAN5-6、qSE5-2),发现影响生育期性状的多效性QTL区域,抽雄期、散粉期、吐丝期每一个性状的变异都会对生育期产生影响。
6.对3个生育期性状进行上位性及与环境互作分析,没有检测到影响散粉期的上位性QTL,其它2个性状共检测到4对上位性QTL,存在加性×加性、加性×显性、显性×显性效应的互作,贡献率为0.02%-0.13%。
QTL mapping for important agronomic traits in maize is basic work to marker assistant selection (MAS). In this study, the F_(2:3) population derived from an elite hybrid Zhengdan958 (Zheng58×Chang7-2) was used to detect the inheritance of yields and their related traits in maize. The partants, F1 and the F_(2:3) population were evaluated in five environment. QTL mapping for nine yield traits and three flowering related traits, including Ear Length, Ear diameter, Row Number, Kernels per Row, Cod Diameter, Ear Weight, Kernel Weight per Ear, Rate of Kernel Production, 500 Kernel Weight, and days to tasseling, days to silking, days to anthesis were firstly analyzed by Composite Interval Mapping (CIM) method. Also, using Network 2.0 software with Mixed Linear Model (MCIM), main genetic effect including epistasis and epistatic×environment interactions were analyze. Compared with the single locus QTL and the interaction effects of QTL-by-environment (QE), These results will do great help in fine mapping QTL associated with yield characters and in marker-assisted selection in maize breeding. The main results were summarized as following:
1.A genetic linkage map containing 180 SSR polymorphic markers was constructed using 225 F_2 population derieved from the F1 (Zheng58×Chang7-2) , which spanned a total of 1 978.7 cM with an average space between two makers of 11.0 cM. Compared with the IBM map from MaizeGDB website, the order of the markers on ten chromosomes were similar. Among these SSR markers, 22 (12.22%) markers showed the genetic segregation distortion (P<0.05 and P<0.01). The molecular genotypes deriving from parent Zheng58 were 8.98%-33.78%, the average homozygous genotypes of Zheng58 was 23.47%; the molecular genotypes of Chang 7-2 were 10.67%-34.67%, and the average genotypes of Chang 7-2 was 23.53%; the molecular genotypes of F1 were 20.00%-57.78%, and the average genotypes of F1 was 47.71%. The genotypes of the two parents at the marker loci followed 1:2:1 theoretical ratio, so the F_(2:3) population was a random one and was fit for QTL analysis.
2.Under five environment, Nine yield traits and three flowering traits were evaluated among family lines as well as the two parents. Transgressive segregation was observed for all traits in F_(2:3) population, Normal distribution was observed for all traits; The yield relate trait and flowering related traits were significant correlation; the results of analysis of variance (ANOVA) showed significant difference with the lines, the environments, the lines and environment interaction in most of the traits.
3.111 QTLs were detected for 9 yield related traits under five environments. Contribution of single QTL to phenotypic variation varied from 3.39% to 31.15%, there were 14 QTLs showing more than 10% of phenotypic variation; 7 major QTLs for EL (qEL3-1 and qEL4), ED (qED3), RN (qRN3), KR (qKR5), CD (qCD5-1) and HKW (qHKW1-1) were common detected under five different environments and in the combined analysis, with higher contributions and stability, and could be used as stable QTL for further fine mapping and MAS. Moreover, Many QTLs were detected with the umc1703-umc1590, bnlg1325-umc2369 and bnlg420-umc1209, umc1800-umc2304, umc1257-phi031 marker confidence intervals on chromosome 1, 3, 5 and 6, respectively. Partially dominance and additive effect played an important part in the inheritance of yield-related traits.
4.Digenic interactions were also detected for yield and the related traits. Twenty pairs of epistasis QTLs were identified in most of the traits except Cod Diameter, all epistasis QTLs have additive×additive, additive×dominance and dditive×dominance effect, the contribution of epistasis varied from 0.04% to 2.41%. Among the Digenic interaction effects, two pairs of interaction for kernel weight and kernel product percent, respectively, showed significant interaction effects with environments, which account for 0.33%-0.91% phenotype variation. Single locus among most of epistatic QTL was not significant, which had little effects on trait variation. It is important to consider different genotypes and the environment in the breeding.
5.52 QTLs were detected for 3 flowering related traits under five environments. Contribution of single QTL to phenotypic variation varied from 4.28% to 19.59%, 17 QTLs explained more than 10% of phenotype variation; There major QTLs for TE (qTE5-2), AN (qAN1-2) and SE (qSE3-1) were stable under four different environments and in combined analysis. Moreover, Many pleitropic QTLs were also detected at 1.05-1.07 bin(qTE1-1、qTE1-2、qAN1-2、qAN1-3、qAN1-4、qSE1-2、qSE1-3), 3.05-3.06 bin(qTE3-1、qAN3-1、qSE3-1)and 5.08 bin(qTE5-1、qAN5-6、qSE5-2).
6.Digenic interactions were detected for flowering related traits. Totally four pairs of epistasis QTLs were detected for days to tasseling and days to silking, and not detected epistatic QTL for days to anthesis, the type of epistasis QTL included additive×additive, additive×dominance and dominance×dominance effects, the contribution of epistasis varied from 0.02% to 0.13%.
引文
[1]陈圣,倪大虎,陆徐忠,等.分子标记辅助选择聚合Xa23,Pi9和Bt基因,生物学杂志,2009,26(3):7-9.
[2]代国丽,蔡一林,徐德林,吕学高,王国强,王久光,孙海艳.玉米穗部性状的QTL定位,西南师范大学学报(自然科学版),2009,34(5):133-137.
[3]戴景瑞.我国玉米遗传育种的回顾和展望.玉米遗传育种国际学术讨论会文集.长春,2000,9:1-7.
[4]董淑静,许为钢.小麦条锈病抗性基因研究进展及分子标记辅助聚合育种.中国农学通报,2009,25(13):190-196.
[5]董章辉,石玉真,张建宏,等.棉花纤维长度主效嘶的分子标记辅助选择及聚合效果研究,棉花学报,2009,21(4):279-283.
[6]方宣钧,吴为人,唐纪良编著.作物DNA标记辅助育种.科学出版社,2001.
[7]高用明,万平.QTL复合区间作图中标记筛选的效率及其影响因素研究.遗传学报,2002,29(6):555-561.
[8]高用明,朱军.植物QTL定位方法的研究进展.遗传,2000,22(3):175-179.
[9]高友军,刘文婷,陶勇生,郑用琏.玉米Mu转座因子及其应用.作物学报,2006,32(8):1236-1243.
[10]公强、王天宇、谭学林等.玉米优异早熟种质单330开花相关性状的QTL分析.植物遗传资源学报.2006,7(4):437-441.
[11]韩娅楠,刘福建,王瑞霞,丁俊强,李志敏,李贤唐,吴建宇.玉米生育期QTL定位及上位性互作效应的遗传研究,华北农学报,2010,25(2):84-87.
[12]胡彦民、吴欣、李翠香,等.玉米制种花期相关性状的QTL分析.南京农业大学学报,2008,31(1):11-16.
[13]蒋洪蔚,刘春燕,高运来,等.作物QTL定位常用作图群体.生物技术通报,2008(增刊):12-17.
[14]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(10):1253-1259.
[15]李开忠,李盛旻.玉米穗部性状的遗传性研究.玉米科学,2006,14(3): 13-16.
[16]李新海,刘贤德,李明顺,张世煌.玉米雌雄开花间隔天数、结穗率与产量的数量性状位点(QTL)分析,Acta Botanica Sinica,2003,45(7):852-857
[17]李永祥.玉米耐旱性QTL定位及重要产量相关性状的遗传基础研究.中国农业科学院博士论文,2008,6.
[18]刘美洲.玉米花期、株型、产量性状QTL定位及分析.新疆石河子大学硕士论文,2008,6.
[19]路明.玉米产量及株型性状QTL定位与遗传基础研究.中国农业科学院博士论文,2007,9.
[20]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.
[21]宋秀芳.玉米籽粒油分含量基因的SSR分子标记、定位及相关分析.中国农业大学博士论文,2003,6.
[22]孙发明,焦仁海,刘兴二,徐艳荣.论春玉米区新的育种目标与策略—对郑单958、先玉335国审以后的思考.种子科技,2006,2:43-45.
[23]汤华,严建兵,黄益勤,郑用琏,李建生.玉米5个农艺性状的QTL定位.遗传学报,2005,32(2):203-209.
[24]汤华.玉米产量和农艺性状的数量遗传研究及玉米铝离子胁迫的基因差异表达研究.华中农业大学博士论文,2004,12.
[25]汤继华,严建兵,马西青,滕文涛,孟义江,戴景瑞,李建生.利用“永久F2”群体剖析玉米产量及其相关性状的遗传机制.作物学报,2007,33(8):1299-1303.
[26]滕文涛.利用分子标记划分玉米杂种优势群及定位农艺性状QTL的研究.华中农业大学博士论文,2004.
[27]万建民.作物分子设计育种.作物学报,2006,32(3):455-462.
[28]王翠玲.玉米光周期敏感性及相关性状的QTL定位及杂种优势机理研究.河南农业大学博士论文,2008,6.
[29]王阳,刘成,王天宇,石云素,宋燕春,黎裕.干旱胁迫和正常灌溉条件下玉米产量性状QTL分析.植物遗传资源学报,2007,8(2):179-183.
[30]吴金红,蒋江松,陈惠兰,等.水稻稻瘟病抗性基因Pi-2(t)的精确定位.作物学报,2002,28:505-509.
[31]夏远峰,于明彦,柳迎春,代秀云,刘爱华,岳尧海,许明学.10个玉米自交系产量性状遗传分析.玉米科学,2008,16(6):29-32,37.
[32]向道权,黄健烈,戴景瑞.玉米产量QTL和杂种优势遗传基础研究进展.中国农业大学学报,1999,4(增刊):1-7.
[33]谢惠玲,冯晓曦,吴欣,王松江,袁延乐,张占峰,袁立,胡彦民.玉米穗部性状的QTL分析.河南农业大学学报,2008,42(2):145-149.
[34]邢永忠,徐才国,华金平,谈移芳,孙新立.水稻株高和抽穗期基因定位和分离.植物学报,2001,43(7):721-726.
[35]邢永忠,徐才国,华金平,谈移芳.水稻穗部性状的QTL与环境互作分析.遗传学报,2001,28(5):439-446.
[36]徐云碧.分子数量遗传学.北京:中国农业大学出版社,1994.
[37]严建兵,汤华,黄益勤,郑用琏,李建生.玉米F2群体分子标记偏分离的遗传分析.遗传学报,2003,(10):913-918.
[38]杨俊品,荣廷昭,向道权,唐海涛,黄烈健,戴景瑞.玉米数量性状定位.作物学报,2005,31(2): 188-196.
[39]杨晓军.玉米重要性状QTL定位与遗传效应分析.新疆农业大学硕士论文,2008,6.
[40]杨引福,郭强,钱劲华.8个玉米自交系主要穗部性状配合力的遗传分析.玉米科学,2008,16(3): 30-33.
[41]张吉民、刘成、石云素,等.干旱胁迫和正常灌溉条件下玉米开花相关性状的QTL分析.植物遗传资源学报,2004,5(2):161-165.
[42]章元明.作物QTL定位方法研究进展.科学通报,2006,51(19):2223-2231.
[43]赵克明.我国历年各地育成的玉米杂交组合一览表.山西农业科学,2003,31(1):67-95.
[44]周芳.玉米杂交种掖单13产量性状QTL定位与分析.沈阳农业大学硕士论文,2007,6.
[45]朱军.复合数量性状基因定位的混合线性模型方法.王连铮,戴景瑞(主编):全国作物育种学术讨论会论文集.北京:中国农业科技出版社,1998.
[46] Agrama HAS,Moussa M E. Mapping QTL in breeding for drought tolerance in maize (Zea mays L.).Euphytica,1996,91:89-97.
[47] Ajmone-Marsan P,Gomi C,Chittb A,Van Vijk R,Stam P,Motto M. Identification of QTLs for grain yield and grain·related traits of maize (Zea may.L.) using an AFLP map,different testers,and cofactor analysis.Theoretical And Appfied Genetics,2001,102:230-243. 50 Ajmone-Marsan P,Monfredini G,Ludwig W F,et al. In an elite cross of maize a major quantitative trait locus controls one fourth of the genetic variation for grain yield.Thero Appl Genet,1995,90:415-424.
[48] Akkaya M S,Bhagwat A A,Cregan P B. Length polymorphisms of simple sequence repeat DNA in soybean.Genetics,1995,132:1131-1139.
[49] Alber B S B,Edwards M D,Stuber C W. Isoenzy matic identification of quantitative trait loci in crosses of elite maize inbreds.Crop Science,1991,31:267-274.
[50] 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.Theor Appl Genet,1997,95:343-352.
[51] 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 (5):1296-1308.
[52] Bailey N T J. The estimation of linkage with differential viability,II and III.Heredity,1949,3:220-228.
[53] Beavis W D,Grant D,Albertsen M,et al. Quantitative trait loci for plant height in four maize population and their associations with quantitative genetic loci.Thor Appl Genet,1991,83:141-145.
[54] Beavis W D,Smith O S,Grant D,et al. Identification of quantitative trait loci using a small sample of topcrossed and F4 progeny from maize.Crop Sci,1994,34(4):882-896.
[55] Berke T G,Rocheford T R. Quantitative trait loci for flowering,plant and ear height,and kernel traits in maize.Crop Sci,1995,35(6):1542-1549.
[56] Boer MP,Wright D,Feng L,Podlich D,Luo L,Cooper M,van Eeuwijk FA. A mixed model QTL analysis for multiple environment trial data using environmental covariables for QTLxE,with an example in maize.Genetics,2007,177:1801-1803.
[57] Bohn M,Khairallah M,Gonzalez D,Hoisington D,Utz H,Deutsch J A,Clark D,Dudley J W,Rocheford T R,LeDeauxb J R. Genetic analysis of corn kernel Chemical composition in the random mated 10 generation of the cross of generations 70 of IHO×ILO.Crop Sci,2006,46: 807-819.
[58] Bryan G J,Collins A J,Stephenson P,Orry A,Smith J B,Gale M D. Isolation and characterization of microsatellites from hexapods bread wheat.Theoretical And Appl Genetics,1997,94:557-563.
[59] Cao G,Zhu J,He C X,Gao Y M,Yan J Q,Wu P. Impacts of epistasis and QTL×environment interaction on the developmental behavior of plant height in rice (Oryza sativa L.).Theor Applied Genet,2001,103:153-160.
[60] Chin E,Senior L,Shu H,Smith J S C. Maize simple repetitive DNA sequences:abundance and allele vailation.Genome,1996,39:866-873.
[61] Cockerham C C,Zcng Z B. DesignⅢwith marker loci.Genetics,1996,143,1437-1456.
[62] Devaux P,Kilian A,Kleinhofs A. Comparative mapping of the barley genome with male and female recombination-derived,doubled-haploid populations.Mol Gen Genet,1995,249:600-608.
[63] Dholakia B B,Ammiraju S S,Lagu M D,R?der M S,Rao V S,Dhaliwal H S,Ranjekar P K, Gupta V S. Molecular marker analysis of kernel size and shape in bread wheat.Plant Breeding,2003,122:392-397.
[64] Ding J Q,Wang X M,Subhash C,et al. Identification of QTL for maize resistance to common smut by using recombinant inbred lines developed from the Chinese hybrid Yuyu22.Theor Appl Genet,2008,49:147-154.
[64] Doebley J,Bacigalupo A,Stec A. Inheritance of kernel weight in two maize-teosinte hybrid populations:implications for crop evolution.Journal of Heredity,1994,85:191-195.
[65] Doebley J,Stec A,Gustus C. Teosinte branched and the origin of maize:Evidence for epistasis and the evolution of dominance.Genetics,1995,141:333-346.
[66] Doebley J,Stec A,Hubbard L. The evolution of apical dominance in maize.Nature,1997,386:485-488.
[67] Duvick D N,Smith JSC,Cooper M. Long-term selection in a commercial hybrid maizebreeding program.Plant Breed Rev,2004, 24(2):109-151.
[68] Duvick D N. Biotechnology in the 1930s:The development of hybrid maize.Nat Rev Genet, 2001,2:69-74.
[69] Edwards K J,Thompson H,Edwards D,de Saizieu A,Sparks C,Thompson J A,Greenland A J,Eyers M,Schuch W. Construction and characterization of a yeast artificial chromosome library containing three haploid maize genome equivalents.Plant Molecular Biology,1992,19:299-308.
[70] Edwards M D,Helentjads T,Wright S et al. Molecular facilitated investigations of quantitatice trait loci in maize.4. Analysis based off genome saturation isozyme and restriction fragment length polymorphis markers.Theor Appl Genet,1992:765-774.
[71] Edwards M D,Stuber C W,Wendel J F. Molecular-marker-facilitated investigations of quantitative trait loci in maize.I. Numbers,genomic distribution and types of gene action.Genetics,1987,116(1):113-125.
[72] Esteban Bortiri,George Chuck,Erik Vollbrecht,Torbert Rocheford,Rob Martienssen,Sarah Hake. ramosa2 Encodes a LATERAL ORGAN BOUNDARY Domain Protein that Determines the Fate of Stem Cells in Branch Meristems of Maize. Plant Cell,2006, 18:574-585.
[73] Fan C C,Xing Y Z,Mao T T,Han B,Xu C G,Li X H,Zhang Q F. GS3 a major QTL for grain length and weight and minor QTL for grain width and thickness in rice,encodes a putative transmembrane protein.Theor Appl Genet,2006,112,1164-1171.
[74] Frary A,Nesbitt T C,Grandillo S,Knaap E,Cong B,Liu J P,Mellor J,Elber R,Alpert K B,Tanksley S D. fw2.2:A quantitative trait locus key to the evolution of tomato fruit size.Science,2000,289:85-88.
[75] Fussell B.The Story of Corn.2nd edn.North Point Press,New York,NY.1999.
[76] Gao M,Chibbar R N.Isolation,characterization and expression analysis of starch synthase IIa cDNA from wheat (Triticum aestivum L).Genome,2000,43:768-775.
[77] Gardiner J M,Coe E H,Melia-Hancock S,Hoisington D A,Chao S. Development of a core RFLP map in maize using an immortalized F2 population.Genetics,1993,134:917-930.
[78] Goldman I L,Rocheford T R,Dudley JW,et al. Molecular markers associated with maize kernel oil concentration in an Illinois High Protein Illinois Low Protein cross. CropSci,1994,34(4):908-915.
[79] Gonzalo M,J B Holland,T J Vyn,L M McIntyre. Direct mapping of density response in a population of B73×Mo17 recombinant inbred lines of maize (Zea Mays L.).Heredity, 2010, 104-583-599
[80] Graner A,Jahoor A,Schondelmaier J,Siedler H,Pollen K,Fischbeck G,Wenzel G,Herrmann R G. Construction of an RFLP map of barley.Theoretical and Applied Genetics,1991,83:250-256.
[81] Helentjaris T,Slocum M,Wright S,Schaefer A,Niehhuis J. Construction of genetic linkage maps in maize and tomato using restriction fragment length polymorphisms.Theor Appl Genet,1986,72:761-769.
[82] Ho J C,McCouch S R,Smith M E. Improvement of hybrid yield advanced backcross QTL analysis in elite maize.Theoretical and Applied Genetics,2002,105(2):440-448.
[83] Huang X,Qian Q,Liu Z,et al. Natural variation at the DEP1 locus enhances grain yield in rice. Nat Genet,2009,41;494-497.
[84] Jansen R C. Interval mapping of multiple quantitative trait loci.Genetics,1993,135:205-211.
[85] Jean-Marcel Ribaut,Michel Ragot. Marker-assisted selection to improve drought adaptation in maize:the backcross approach,perspectives,limitations and alternatives.Journal of Experimental Botany,2007,58(2):351-360.
[86] Jian Yang,Chengcheng Hu,Xiuzhi Y,et al. Software for Mapping QTL with Epistatic and QE interaction effects in Experimental Populations.Institute of Bioinformatics,Zhejiang University,Hangzhou,China.(http://ibi.zju.edu.cn/software/qtlnetwork/index.html),2005.
[87] Jiang C J,Zeng Z B. Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics, 1995,140:1111-1127.
[88] Kao C H,Zeng Z B,Teasdale R D. Multiple interval mapping for quantitative trait loci.Genetics,1999,152:1203-1216.
[89] Kinoshita T. Report of the committee on gene symbolization, nomenclature and linkage group.Rice Genet Newsl,1991,8:2-37.
[90] Kinoshita T. Report of the committee on gene symbolization, nomenclature and linkage group.Rice Genet Newsl,1993,10:7-39.
[91] Knapp S J,Stroup W W,Ross W M. Exact confidence intervals for heritability on progeny mean basis.Crop Sci,1985,25:192-194.
[92] Koester R,Sisco P H,Stuber C W. Identification of quantitative trait loci controlling days to flowering and plant height in two near isogenic lines of maize.Crop Sci,1993,33:1209-1216.
[93] Konishi S,Izawa T,Lin S Y,Ebana K,Fukuta Y,Sasaki T,Yano M. An SNP Caused Loss of Seed Shattering During Rice Domestication.Science,2006,312:1392-1396.
[94] Kozaki A,Hake S,Colasanti J.The maize ID1 flowering time regulator is a zinc finger protein with novel DNA binding properties.Nucleic Acids Res,2004,32:1710-1720.
[95] Lander E S,Botstein S. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps.Genetics,1989,121:185-199.
[96]Xiangjun Li,Ying Yang,Jialing Yao,Guoxing Chen,Xianghua Li,Qifa Zhang,Changyin Wu. FLEXIBLE CULM 1 encoding a cinnamyl-alcohol dehydrogenase controls culm mechanical strength in rice.Plant Mol Biol,2009,69:685-697.
[97] Lima M,Souza c,Bento D,Souza,A Cadini-Garcia L. Mapping QTL for Grain Yield and Plant Traits in a Tropical Maize.Molecular Breeding,2006,17,3,227-239.
[98] Lincoln S,Daly M,Lander E. Constructing genetics maps with MAPMAKER/EXP 3.0. Whitehead Institute Technical Report,Whitehead Institute,Cambridge,Massachusctts,USA.1992.
[99] Liu J,Eck J V,Cong B,Tanksley S D. A new class of regulatory genes underlying the cause of pear shaped tomato fruit.PNAS,2002,99 (20):13302-13306.
[100] Lorieux M,Goffinet B,Perrier X,Gonzalez de Leon D,Lanaud C. Maximum-likelihood models for mapping genetic markers with segregation distortion.1.Backcross populations.Theor Appl Genet,1995a,90:73–80.
[101] Lu H,Bernardo J,Ohm H W. Mapping QTL for popping expansion volume in popcorn with simple sequence repeat markers.Theor Appl Genet,2003,106(3).423-427.
[102] Lu H,Romero-Severson J,Bernardo R. Chromosomal regions associated with segregation distortion in maize.Theor Appl Genet,2002,105:622-628.
[103] Lukens L N,Doebley J. Epistatic and environmental interactions for quantitative trait loci involved in maize evolution.Genetical Research,1999,74:291-302.
[104] Ma X Q,Tang J H,Teng W T,Yan J B,Meng Y J,Li J S. Epistatic interaction is an important genetic basis of grain yield and its components in maize.Mol Breeding,2007,20:41-51.
[105] McCouch S R,Kochert G,Yu Z H,Wang Z Y,Khush G S,CoffmanW R,Tanksley S D. Molecular mapping of rice chromosomes.Theoretical and Applied Genetics.1988.76:815-829.
[106] 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.
[107] Milboume D,Meyer R C,Collins A J,Ramsay L D,Gebhardt C,Waugh R. Isolation,characterization and mapping of simple sequence repeat loci in potato.Mol Gen Genet,1998,259:233-245.
[108] Motoyuki Ashikaria,Makoto Matsuoka. Identification,isolation and pyramiding of quantitative trait loci for rice breeding.Trends in Plant Science,2006,11(7):344-350.
[109] Natalya S,McMullen M D,Schultz L,et al. Development and mapping of SSR markers for maize.Plant Mol Bio,2002,48:463-481.
[110] Paterson M D,Damon S,Hewwit J D,et al.Mendelian factors undearlying quantitative traits in tomato:Comparison across species,generations and environments.Genetics,1991,127:181-197.
[111] Pereira M G,Lee M,Bramel-Cox P,Woodman W,Doebley J,Whitkus R. Construction of anRFLP map in sorghum and comparative mapping in maize.Genome,1994,37:236-243.
[112] Piepho H P. A quick method for computing approximate thresholds for quantitative trait loci detection.Genetics,2001,157:425-432.
[113] Ragot M,P H Sisco,D A Hoisington.Molecular-marker-mediated characterization of favorable exotic alleles and quantitative trait loci in maize.Crop Sci,1995,35:1306-1315.
[114] Ribaut J,Hoisington D,Deutseh J A,et a1. Identification of quantitative trait loci under drought conditions in tropical maize.2.Flowering parameters and the anthesis-silking interval.Theor Appl Genet,1996,92:905-914.
[115] Romagosa I S,Ullrich E,Han F,Hayes P M. Use of the genetic main effects and multiplicative interaction model in QTL mapping for adaptation in barley.Theoretical and Applied Genetics, 1996,93:30-37.
[116] Salah E D E A,Carlos A B,Anton J M P,Vered R,Maarten K. A QTL for flowering time in Aribiodopsis reveals a novel allele of CRY2.Nature Genet,2001,29:435-440.
[117] Sari-Gorla M,Krajewski P,Fonzo N D,Villa M,Frova C. Genetic analysis of drought tolerance in maize by molecular markers.II.Plant height and flowering.Theoretical and Applied Genetics 1999,99:289-295.
[118] SAS Institute,Inc.,SAS Users Guide v6.03:Statistic. SAS Institute,Cary,NC,1996.
[119] Sax K. The association of size differences with seed-coat pattern and pigmentation in Phaseolus vulgaris.Genetics,1923,8:552-560.
[120] Schon C C,Melchinger A E,Boppenmaier J,et al. RFLP mapping in maize:quantitative trait loci affecting testcross performance of elite European flint lines.Crop Sci,1994,34 (2):378-389.
[121] Schon C C,Utz H F,Groh S,Tmberg B,Openshaw S,Melchinger A E. QTL mapping based on resampling in a vast maize testcross experiment and its relevance to quantitative genetics for complex traits.Genetics,2004,167:485-498.
[122] Senior L,Chin E,Lee M,Smith JS C,Stuber C W. Simple sequence repeat markers developed from maize sequences found in the GENBANK database:map construction.Crop Sci,1996,36:1676-1683.
[123] Silvio Salvi,Roberto Tuberosa,Elena Chiapparino,Marco Maccaferri,Stanislas Veillet,Leon van Beuningen,Peter Isaac,Keith Edwards,Ronald L.Phillips. Toward positional cloning of Vgt1,a QTL controlling the transition from the vegetative to the reproductive phase in maize.Plant Molecular Biology,2002,48:601-613.
[124] Soller M,Beckmann J S. Marker-based mapping of quantitative trait loci using replicated progenies.Theor Appl Genet,1990,67:25-33.
[125] Song X,Huang W,Shi M,et al. A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase.Nat Genet,2007,39:623-630.
[126] Stratton D A,Haley C S,Knott S A. Reaction norm functions and QTL-environment interactions for flowering time in Arabidopsis thaliana.Heredity,1998,8l(2):144-155.
[127] 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.Crop Sci, 1987,27:639-648.
[128] Stuber C W,lincoln S E,Wolff,Helentjaris T,Lander E. Identification of genetic factors contributing to heterosis in a hybrid from elite maize inbred lines using molecular markers.Genetics,1992,132:823-839.
[129] Stuber C W. Success in the use of molecular markers for yield enhancement in corn.Proc 49th Annual Corn and Sorghum Industry Research Conf.American Seed Trade Assoc, 1994,49:232-234.
[130] Tammino G,Tingey S. Simple sequence repeats for germplasm analysis and mapping in maize.Genome,l996,39:277-287.
[131] Tanksley S D. Mapping polygenes. Annu Rev Genet, 1993, 37: 205-233.
[132] Temnykh S,Park W D,Ayres N,Cartinhour S,Hauck N,Lipovich L,Cho YG,Ishii T,McCouch S R. Mapping and genome organization of microsatellite sequences in rice(Oryza sativa L.) Theoretical and Applied Genetics,2000,100:697-712.
[133] Thornsberry J M,Goodman M M,Doebley J,Kresovich S,Nielsen D,Buckler E S. Dwarf8 polymorphisms associate with variation in flowering time.Nature Genetics,2001,28:286-289.
[134] Uauy C,Distelfeld A,Fahima T,Blechl A,Dubcovsky J. A NAC gene regulating senescence improves grain protein,zinc,and iron content in wheat.Science.2006,314,1298-1301.
[135] Utz H F,Melchinger A E,Schon C C. Bias and sampling error of the estimated proportion of genotypic variance explained by quantitative trait loci determined from experimental data in maize using cross validation and validation with independent samples. Genetics,2000,154:1839-1849.
[136] VeldboomL R,Lee M. Molecular-marker-facilitated studies of morphological traits in maize.II.Determination of QTLs for gain yield and yield components.Thero Appl Genet, 1994,89 (4):451-458.
[137] Vieira C,Pasyukova E G,Zeng Z B,Hacker J B,Lyman R F,Mackay T F C. Genotype-environment interaction for quantitative trait loci affecting life span in Drosophila melanogater.Genetics,2000,154:213-227.
[138] Vollbrecht E,Springer P S,Goh L,Iv ESB,Martienssen. Architecture of floral branch systems in maize and related grasses.Nature, 2005,436,1119-1126.
[139] Walker D,Boerma H R,All J,Parrott W. Combining cry1Ac with QTL alleles from PI229358 to improve soybean resistance to lepidopteran pests.Molecular Breeding,2002,9:43-51.
[140] Wang D L,Zhu J,Li Z K,Paterson A H. Mapping QTLs with epistatic effects and QTL×environment interactions by mixed liner model approaches.Theor Appl Genet,1999, 99:1255-1264.
[141] Wang E,Wang J,Zhu X,et al. Control of rice grain-filling and yield by a gene with a potential signature of domestication.Nat Genet,2008,40:1370-1374.
[142] Wang S,Basten C J,Zeng Z B. Windows QTL Cartographer 2.5 Department of Statistics,North Carolina State University,Raleigh,NC,2006.
[143] Weller J I,Ezra E. Genetic analysis of somatic cell score and female fertility of Israeli Holsteins with an individual animal model.J Dairy Sci,1997,80:586-593.
[144] Wendel J F,Edwards M D,Smber C W. Evidence for multilocus genetic control of preferential fertilization in maize.Heredity,1987,58:297-302.
[145] Werner J D,Borevitz J O,Warthmann N,Trainer G T,Ecker J R,Chory J,Weigel D. Quantitative trait locus mapping and DNA array hybridization identify an FLM deletion as a cause for natural flowering-time variation.PNAS,2005,102:2460-2465.
[146] Willmot D B,Dudley J W,Rocheford T R,Bari A. Effect of random mating on marker-QTL associations for grain quality traits in the cross of illinois High oil×illinois Low oil.Maydica, 2006,51:187-199.
[147] Xiao Y N,Li X H,George M L,Li M S,Zhang S H,Zheng Y L. Quantitative trait locus analysis of drought tolerance and yield in maize in China. Plant Molecular Biol Reporter, 2005,23:155-165.
[148] Xu Y,Zhu L,Xiao J,Huang N,McCouch S R. Chromosomal regions associated with segregation distortion of molecular markers in F2,backcross,doubled-haploid,and recombinant inbred populations in rice (Oryza sativa L.).Mol Gen Genet,1997,253:535-545.
[149] Xue W,Xing Y,Weng X,et al. Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice.Nat Genet,2008,40:761-767.
[150] Y Z Xing,Y F Tan,J P Hua,X L Sun,C G Xu,Q Zhang. Characterization of the main effects,epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice.Theor Appl Genet,2002,105:248-257.
[151] Yamamoto T,Kuboki Y,Lin S Y,Sasaki T,Yano M. Fine mapping of quantitative trait loci Hd-1, Hd-2 and Hd-3,controlling heading date of rice,as single Mendelian factors.Theor Appl Genet, 1998,9,37-44.
[152] Yan J B,Tang H,Huang Y Q,Zheng Y L,Li J S. Quantitative trait loci mapping and epistaticanalysis for grain yield and yield components using molecular markers with an elite maize hybrid. Euphytica,2006,149:121-131.
[153] Yan J Q,Zhu J,He C X,Benmoussa M,Wu P. Molecular marker assisted dissection of genotype×environment interaction for plant type traits in rice (Oryza sativa L.).Crop Sci,1999,39:538-544.
[154] Zeng Z B. Precision mapping of quantitative trait loci.Genetics,1994,136:1457-1468.
[155] Zeng Z B. QTL mapping and the genetic basis of adaptation:recent developments.Genetica, 2005,123:25-37.
[156] Zeng Z B. Theoretical basis of separation of multiple linked gene effects on mapping quantitative trait loci.Proc Natl Acad Sci USA,1993,90:10972-10976.
[157] Zheng P,Allen W B,Roesler K,Williams M E,Zhang S,Li J,Glassman K,Ranch J,Nubel D, Solawetz W,Bhattramakki D,Llaca V,Deschamps S,Zhong G,Tarczynski M C,Shen B. A phenylalanine in DGAT is a key determinant of oil content and composition in maize.Nature genetics,2008,40(3):257-373.
[158] Zhou W C,Kolb F L,Bai G H,Domier L L,Boze L K,Smith N J. Validation of a major QTL for scab resistance with SSR markers and use of marker-assisted selection in wheat.Plant Breeding,2003,122:40-44.
[159] Zhu J,Weir B S. Mixed model approaches for the genetics of quantitative traits.In:Chen LS, Ruan SG, Zhu J(eds) Advanced topics in biomathematics:Proc Int Conf on Mathematical Biology, World Scientific Publishing Co, Singapore, pp 321-330,1998.
[160] Zhuang J,Lin H,Lu J,Qian H. Analysis of QTL×environment interaction for yield components and plant height in rice.Theor Appl Genet,1997,95:799-808.