用户名: 密码: 验证码:
陆地棉双列杂交的遗传效应及表达谱分析
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
棉花是我国也是全球最重要的纤维作物,以陆地棉为主。研究陆地棉品种双列杂交的遗传效应及表达谱,为选择骨干亲本、预测杂种优势及分子设计育种提供理论依据。
     本文以来源不同的10个陆地棉品种为亲本,按双列杂交配制45个正交F_1及其45个F_2,2008~2010年在安徽望江、河南安阳和新疆阿克苏进行同步试验,调查了8个农艺、经济性状,检测了5项纤维品质指标,2008年取盛花期幼蕾进行基因芯片分析。以ADAA与环境互作的遗传模型和条件分析方法及QTLNetwork V3.0新型软件进行数据分析。主要结果如下:
     1、8个农艺、经济性状的遗传主效应及互作效应不同程度起作用。单株铃数、单铃重、衣分、子指、皮棉产量的加加上位性效应和衣分、子指的加加上位性×环境互作效应正向极显著。单铃重、衣分、子指的h_G~2较高,早代选择和异地选择有效;株高、果枝数、单株铃数受环境影响较大,直接选择不大可靠。果枝数、单株铃数、子棉产量和皮棉产量H_(GE)~2较高(31.4%~51.8%),在特定环境可利用杂种优势。以9018、中棉所41、sGK958和2028为亲本可同步改良2~3个产量组分(特别是衣分)而显著提高后代皮棉产量。2028的衣分和子指的加性效应和加加上位性效应、sGK958的衣分和子指的加性效应及其衣分的加加上位性效应均正向极显著,育种价值较大。以3392154-55为亲本可改良后代铃重而提高皮棉产量。
     2、纤维品质的各遗传效应及其与环境的互作效应差异较大。比强度主要受加性效应控制,纯系育种是遗传改良的有效途径。上半部平均长度的h_G~2和HG2较高,可在早代选择,特定环境也可利用杂种优势。整齐度指数、伸长率和马克隆值V_e / V_P超过40%,直接选择效果较差。新陆中9号和sGK958是优质亲本,育高产优质品种首选sGK958作亲本。
     3、遗传相关分析表明,提高衣分改良皮棉产量效果好,不同环境选择有效;但选高产又优质的品种,衣分不宜过高。子指可间接选择纤维品质。特定环境中,提高单铃重可提高皮棉产量和比强度;选植株高的品种,也可间接改良皮棉产量。选纤维长、比强高、马值适中的品系和优势组合是可能的。
     4、主效应杂种优势分析表明,子棉、皮棉产量F_1和F_2的平均优势和超亲优势均较大,纤维品质平均优势较小,超亲优势均为负值。7个F_1的皮棉产量和纤维品质较协调。
     5、对皮棉产量的贡献率分析结果,株高、果枝数、单株成铃数、单铃重和衣分的CR_(D(C→T))正向极显著且较大(57.70%~86.80%),选显性效应高的组合,可提高其皮棉产量。衣分的CR_(AE(C→T))和CR_(DE(C→T))正向极显著且较高(35.91%~36.43%),在特定环境,选高衣分可显著提高选系的皮棉产量;选衣分显性效应高的组合,其皮棉产量会提高。
     6、取盛花期幼蕾,利用基因芯片技术进行表达谱统计分析。检测到73个与皮棉产量显著相关的数量性状转录子(QTTs),其中10个遗传率大于3%。与皮棉产量对应的加性方差小,显性方差大;与产量构成因素对应的加性方差较大,显性方差较小。9018和sGK958的基因对皮棉产量的加性效应贡献值较高,可用于高产育种。相同基因对不同亲本的加性效应贡献值不尽相同。基因对组合皮棉产量显性效应总预测值的贡献多数较高,对其显性效应贡献值具有显著影响的QTT不同,对其皮棉产量及其构成因素有影响的QTT不同,说明其作用机制也不同。
Cotton is the most important fiber crop in China and the world, and upland cotton accounts for more than 95% cotton production. Yangtze River Basin, Yellow River Basin and Xinjiang are the three major cotton growing regions in China. Study of the genetic effects and the expression profile of upland cotton cultivars from the three main growing areas should be helpful for selection for the backbone parents, heterosis prediction and molecular breeding in cotton.
     In this study, 10 representative upland cotton cultivars from China's three major cotton-growing regions, using a diallel mating design method, were used to produce 45 F_1 hybrids and their 45 F_2 generations. Field experiments were carried out in 2008, 2009 and 2010, in three typical ecological regions for cotton production in China, including Wangjiang in Anhui Province, Anyang in Henan Province and Aksu in Xinjiang Uyghur Autonomous Region. Eight morphological and yield traits were investigated and five fiber quality characters were surveyed. Gene microarray analysis was conducted using flowering buds at full bloom stage in 2008. Statistical analysis was conducted using the genetic model including additive-dominance-epitasis and its interaction effect with environment, condition analysis method, QTLNetwork V3.0. The main results are as follows:
     (1) For the eight morphological and yield traits, the main genetic effects and their interaction with environment play a role at varying degrees. Additive-by-additive epistatic effects on boll number per plant, boll weight, lint percentage, seed index and lint yield, interaction between additive-additive epistatic effect and environment on lint percentage and seed index were positively significant. General heritability in the narrow sense (h_G~2 ) for boll weight, lint percentage and seed index were high, indicating that early generation selection was effective. Plant height , number of fruiting branches and boll number per plant were greatly influenced by environment, indicating that direct selection is less reliable. Interaction heritability in the broad sense (H_(GE)~2 ) for the number of fruiting branches , boll number , seed-cotton yield and lint yield were relatively large (31.4% ~ 51.8%), indicating that heterosis can be used in specific environments. Parents 9018, CCRI41, sGK958 and 2028 can be used as hybrid parents to concurrently improve two or three yield components (especially lint percentage) , leading to significantly increase lint yield. The additive effect and additive-addtive epistasis on lint percentage and seed index in parent 2028 was large and positively significant, and should be used in selection breeding. Using 3392154-55 as parent was expected to effectively improve boll weight and thus increase lint yield.
     (2) For the fiber quality traits, both the main genetic effects and their interaction with the environment play a role, but the difference was larger. Fiber strength was mainly affected by additive effects, which can be genetically improved by conventional breeding. h_G~2 and general heritability in the broad sense (H_G~2 ) of upper-half-mean length were large, and early generation selection can also be conducted and heterosis can be utilized in specific environment. V_e / V_P of uniformity index, elongation and micronaire value were above 40%, which means direct selection may be less effective. Xinluzhong 9 and sGK958 were two elite parents with high fiber quality, but sGK958 was good at both lint yield and fiber quality.
     (3) Genetic correlation analysis showed that lint yield can be improved by increasing lint percentage, and selection was effective in different environments. To breed cultivars with high yield and good fiber quality, lint percentage should not be very high. In certain circumstances, higher boll weight should result in the increasing of lint yield and fiber strength . Good quality can be achieved selection for seed index. In some specific environments, selecting taller individuals should indirectly improve lint yield. In different environments, indirect selection and heterosis utilization on the fiber strength can be conducted through selecting on upper-half-mean length.
     (4) The heterosis analysis based on the main effect showed that average population mid-parent heterosis and average population better parent heterosis for seed-cotton yield and lint yield in F_1 and F_2 were large. The average population mid-parent heterosis for the fiber quality traits were small and their average population better parent heterosis were negative. Seven F_1 hybrids exhibited both high lint yield and good fiber quality.
     (5) The contribution ratio analysis of 6 agronomic and economic characteristics to lint yield showed that CR_(P (C→T)) of 5 out of the 6 traits were significantly positive, the CR_(AE (C→T)) of the tested traits were significantly positive, among which lint percentage was large (35.91%), which means that in a particular environment, selecting on that trait was expected to significantly improve lint yield . The CR_(D (C→T)) of plant height, number of fruiting branches per plant, boll number per plant, boll weight, and lint percentage were significantly positive and large (57.70%~86.80%), which means that selecting for hybrids with high dominant effect was expected to improve lint yield. The CR_(DE (C→T)) of lint percentage was significantly high (36.43%), which means that selecting for hybrids with lint percentage with high dominant effect was expected to increase lint yield.
     (6) Taken young flowering buds as materials, expression profile analysis indicated that 73 quantitive trait transcripts (QTTs) , among which 10 QTTs’heritability were over 3%, significantly related to lint yield were measured in flowering buds. The additive variance for lint yield was lower while the dominance variance was larger. The additive variance for the yield components (lint percentage, boll number per plant and boll weight) were larger while the dominance variance was lower. Predicted values of additive effects of 9018 and sGK958 were higher at the gene expression level.They were good parents for high yield. However, Xinluzhong 9 and CCRI45 went against high yield. The same gene contribute different additive effect on different parents.The total predicted value of dominant effect of different crosses was higher. The QTTs, which have siginificant effects on dominance contribute value and on lint yield and its components, were different. Hence, their mechanism was different.
引文
1.鲍文奎.机会与风险——40年育种研究的思考.植物杂志,1990(4):4~5
    2.曹立勇,占小登,庄杰云,郑康乐,程式华.水稻产量性状的QTL定位与上位性分析.中国农业科学,2003,36(11):1241~1247
    3.曹新川,何良荣,韩路,胡守林,龚平,熊仁次.陆地棉产量性状与品质性状的加性显性相关分析.塔里木农垦大学学报,2004,16(4):17~20
    4.陈柏清,陈青,吴吉祥.陆地棉不同铃期和不同铃位成铃数杂种优势的遗传研究.浙江农业大学学报,1998,24(4):339~343
    5.陈欢,张文英,樊龙江,作物育种方法研究进展与展望.科技通报,2011,27(1):61~65
    6.陈萍,吴娟,柯文辉,张重义,林文雄.烤烟主要化学品质的遗传研究.中国烟草学报,2009,15(1):25~30
    7.陈青,朱军,吴吉祥.陆地棉(Gossypium hiesurum L.)不同铃期单株成铃数和子棉产量的遗传动态分析.浙江农业大学学报,1999,25(2):155~160
    8.陈顺辉,巫升鑫,倪金应,阴长林,潘建菁,林毅,吴正举.烤烟主要数量性状的配合力研究.中国烟草学报,2004,(3):25~28
    9.陈于和,秦素平,张志雯.转Bt抗虫棉与常规棉品种间配合力分析及杂种优势研究.棉花学报,2009 ,21(1):77~80
    10.陈于和,唐灿明,周兆华,张天真,潘家驹,靖深蓉,袁有禄.陆地棉显性无腺体品系杂种优势及配合力研究.棉花学报,1997,9(6):299~303
    11.成磊,梅拥军,郭伟锋,叶超勇.中熟×早熟陆地棉F1产量及形态性状的遗传分析.安徽农业科学,2008,36(15):6249~6251,6260
    12.稻茎蘖数的发育遗传研究.中国农业科学,2002,35(9):1033~1039
    13.邓武明,阳小虎,文凤君,陈胜荣,赵昌斌.甘蓝型油菜产量性状的遗传及相关与通径分析.中国油料作物学报,2003,25(4):27~30
    14.丁胜,鲁乃曾,杨东杰,张利莉,梅拥军.新疆自育海岛棉品种间杂交产量性状的杂种优势分析.新疆农业科学,2010 ,47(1):42~46
    15.范术丽,喻树迅,原日红,宋美珍.短季棉早熟性的遗传效应及其与环境互作研究.西北植物学报,2006,26(11):2270~2275
    16.范术丽,喻树迅,张朝军,原日红,宋美珍.短季棉常用亲本早熟性状的遗传及配合力研究.棉花学报,2004,16(4):211~215
    17.范术丽.短季棉早熟性相关性状的遗传及其QTLs定位研究.[博士学位论文].北京:中国农业科学院,2004
    18.高用明,朱军,宋佑胜,何慈信,石春海,邢永忠.水稻永久F2群体抽穗期QTL的上位性及其与环境互作效应的分析.作物学报,2004,30(9): 849~854
    19.高用明.复杂上位性及其与环境互作的QTL定位方法和杂种优势预测研究.[博士学位论文].杭州:浙江大学,2002
    20.顾铭洪,刘巧泉.作物分子设计育种及其发展前景分析.扬州大学学报(农业与生命科学版),2009,30(1):64~67
    21.郭伟锋,曹新川,胡守林,梅拥军.海岛棉单株成铃性状的发育遗传研究.棉花学报,2010,22(1):83~88
    22.郭伟锋,曹新川,胡守林,梅拥军.海岛棉开花性状的发育遗传研究.华北农学报,2008,23(增刊):173~176
    23.郭小平,赵元明,吴家和,张献龙,聂以春.棉花Bt转基因品系的配合力和杂种优势表现.棉花学报,2006,18(5):304~3082
    24.韩路,王海珍,石淑强,曹新川,胡守林,龚平.陆地棉果枝发育的遗传分析.塔里木农垦大学学报,2004,16(4):14~16
    25.郝德荣,何林池,刘水东,周金凤,邢建美,黄昭平.抗虫棉数量性状遗传距离与杂种优势关系的研究.金陵科技学院学报,2008,24(4):50~55
    26.郝俊杰.陆地棉杂种优势及相关性状的遗传分析.[博士学位论文].武汉:华中农业大学,2008
    27.黄滋康,黄观武.中国棉花杂交种与杂种优势利用.北京:中国农业出版社,2008,1~197
    28.贾赵东,孙敬,张天真.利用7个置换系和渐渗系的双列杂交研究海陆杂种的数量性状遗传.南京农业大学学报,2006,29(2):6~10
    29.金骏培,武耀廷,张天真.皖杂40杂交棉产量与品质性状的杂种优势表现及遗传分析.中国农业科学,2004,37(10):1428~1433
    30.金卫斌,李煦远.组合拉丁方设计在田间试验中的应用.湖北农学院学报,1995,15(3): 161~166
    31.李北齐,赵苏维,王贵强,陈广凤,姜德进.玉米杂交组合产量相关因素的灰色关联度评价.玉米科学, 2006, 14(2): 44~46
    32.李北齐,王贵强,金益,路运才,吴玉梅,李三勋.玉米自交系淀粉含量灰色关联度分析.中国农学通报, 2010, 26(11): 99~102
    33.李成奇,王清连,张金宝,付远志.高产陆地棉百棉1号产量性状的主基因+多基因遗传分析.河南农业科学,2010,8:43~48
    34.李国民,田峰,李鸣,方红.烤烟产量及其品质性状的双列杂交分析.中国烟草学报,1998,4(2):22~28
    35.李俊文,刘爱英,石玉真,龚举武,王涛,商海红,巩万奎,袁有禄.转基因抗虫陆地棉与优质品系杂交铃重、衣分的遗传及其F1杂种优势分析.棉花学报,2010,22(2):163~168
    36.李昆,杨代刚,马雄风,周晓箭,王海凤,孟清芹,裴小雨.强优势杂交棉产量性状的QTL定位,分子植物育种,2010,8(4 ):673~679
    37.李龙云,于霁雯,翟红红,黄双领,李兴丽,张红卫,张金发,喻树迅.棉花纤维发育相关基因表达谱的比较分析.分子植物育种,2010,8(3):488~496
    38.李龙云,于霁雯,翟红红,黄双领,李兴丽,张红卫,张金发,喻树迅.利用基因芯片技术筛选棉纤维伸长相关基因.作物学报,2011, 37(1): 95~104
    39.李艳艳,丰震,赵兰勇,莫镇华,张宝.玫瑰花产量灰色分析、Kriging插值及选择指数研究.中国农业科学, 2008, 41(5):1429~1435
    40.廖伏明,周坤炉,阳和华,徐秋生.杂交水稻亲本遗传差异及其与杂种优势关系.中国水稻科学, 1998, 12(4): 193~199
    41.林建荣,石春海,吴明国.不同环境条件下粳型杂交稻米碾磨品质性状的遗传效应分析.生物数学学报,2003,18(1):116~122
    42.林建荣,石春海,吴明国.粳稻稻米外观和碾磨品质性状与植株农艺性状的遗传关系分析.作物学报,2003,29(4):581~586
    43.林忠旭,冯常辉,郭小平,张献龙.陆地棉产量、纤维品质相关性状主效QTL和上位性互作分析.中国农业科学,2009,42(9):3036~3047
    44.刘乐承,董德坤,曹家树.作物杂种优势机理研究进展.湖北农业科学,2007,46(4):645~650
    45.刘芦苇,祝水金.转基因抗虫棉产量性状的遗传效应及其杂种优势分析.棉花学报,2007,19(1):33~37
    46.刘志文,傅廷栋,刘雪平,涂金星,陈宝元.作物分子标记辅助选择的研究进展、影响因素及其发展策略.植物学通报,2005,22(增刊):82~90
    47.马育华.植物育种的数量遗传学基础[M].南京:江苏科学技术出版社,1982,158~437
    48.梅拥军,郭伟锋,熊仁次.陆地棉产量组分对皮棉产量的遗传贡献分析.棉花学报,2007,19 (2):114~118
    49.梅拥军,叶子弘,张利莉.海岛棉F1产量性状的条件遗传分析(英文).遗传学报,2006,33 (9):841~850
    50.梅拥军,张改生,叶子弘,曹新川,张文英.海岛棉不同果枝品种间杂交纤维品质性状的遗传及F1和F2群体优势分析.作物学报,2004,30(8):796~800
    51.梅拥军,张改生,叶子弘,郭伟锋.海岛棉零式果枝与长果枝品种间杂交F1和F2代产量和纤维品质性状的杂种优势分析.中国农业科学2005,38(6):1106~1112
    52.梅拥军,朱军,张利莉,郭伟锋,胡守林.陆地棉产量组分对主要纤维品质性状的贡献分析.中国农业科学2006,39(4):848~854
    53.孟德尔.植物杂交试验(吴仲贤译).北京:科学出版社,1957
    54.明道绪,张征锋,刘永建.作物杂种优势遗传基础的研究进展.四川农业大学学报, 2002,20(2):177~181
    55.倪先林,张涛,蒋开锋,杨莉,杨乾华,曹应江,文春阳,郑家奎.杂交稻特殊配合力与杂种优势、亲本间遗传距离的相关性.遗传, 2009, 31(8): 849~854
    56.潘海燕,朱军,韩丹夫.分析基因表达谱数据的新方法.浙江大学学报(农业与生命科学版),2004,30(5):492~494
    57.秦永生,刘任重,梅鸿献,张天真,郭旺珍.陆地棉产量相关性状的QTL定位.作物学报, 2009, 35(10): 1812~1821
    58.邵艳华,李俊文,唐淑荣,刘爱英,石玉真,褚平,桑文东,孟俊婷,袁有禄.陆地棉纤维细度相关性状的遗传及相关性分析.棉花学报,2008,20(4):289~294
    59.沈晓佳,孙玉强,刘芦苇,祝水金.转基因抗虫棉纤维品质性状的遗传分析.棉花学报,2009, 21 (3) :163~167
    60.沈新莲,袁有禄,郭旺珍,朱协飞,张天真.棉花高强纤维主效QTL的遗传稳定性及它的分子标记辅助选择效果.高技术通讯,2001,10:13~17
    61.沈新莲.陆地棉纤维品质QTL的筛选、定位及其应用.[博士学位论文].南京:南京农业大学,2005
    62.宋美珍,喻树迅,范术丽,原日红.短季棉早熟不早衰生化性状的遗传分析.西北植物学报,2005,25(5):903~910
    63.宋美珍,喻树迅,范术丽,原日红.短季棉主要农艺性状的遗传分析.棉花学报,2005,17(2):94~98
    64.宋美珍,喻树迅,范术丽.早熟不早衰品种及后代的抗氧化酶活性的变化.棉花学报,2006,18(1):63~64
    65.宋美珍.短季棉早熟不早衰生化遗传机制及QTL定位. [博士学位论文].北京:中国农业科学院,2006
    66.苏岩,钱前,曾大力.水稻分子设计育种的现状和展望.中国稻米,2010,16(2):5~9
    67.孙其信,倪中福,吴利民,孟凡荣,王章奎,林展.基因差异表达与小麦杂种优势分子机理.见:中国农学会,编.21世纪小麦遗传育种展望——小麦遗传育种国际学术讨论会文集.中国重要会议论文全文数据库,2001,41~51
    68.汤在祥,徐辰武.复杂性状遗传分析策略和方法研究进展.中国农业科学,2008,41(5):1255~1266
    69.万建民.超级稻的分子设计育种.沈阳农业大学学报, 2007, 38(5): 652~661
    70.万建民.作物分子设计育种.作物学报, 2006,32(3):455~462
    71.汪保华,武耀廷,黄乃泰,郭旺珍,朱协飞,张天真.陆地棉重组自交系产量及产量构成因子性状的上位性QTL分析.作物学报,2007,33(11):1755~1762
    72.王武,聂以春,张献龙,孙济中.转基因抗虫组合在棉花杂种优势利用中增产原因剖析.华中农业大学学报,2002,21(5):419~424
    73.王春明,翟虎渠.红花烟草数量性状的遗传研究.Ⅰ.株高性状的遗传分析.南京农业大学学报,1997,20(1):23~27
    74.王国建,朱军,藏荣春,许馥华,季道藩.陆地棉棉仁营养品质及种子物理性状的遗传相关分析.浙江农业大学学报,1996,22(6):585~590
    75.王建康,李慧慧,张学才,尹长斌,黎裕,马有志,李新海,邱丽娟,万建民.中国作物分子设计育种.作物学报, 2011, 37(2): 191~201
    76.王金明.一种变形的拉丁方设计.作物学报,1992,18(4):291~295
    77.王立秋.北方早熟玉米9个主要性状间的灰色关联度分析.玉米科学, 2001, 9(2): 44~46
    78.王士强,胡银岗,佘奎军,周琳璘,孟凡磊.小麦抗旱相关农艺性状和生理生化性状的灰色关联度分析.中国农业科学, 2007, 40(11): 2452~2459
    79.王淑芳,石玉真,刘爱英,熊宗伟,唐淑荣,李俊文,王玉红,袁有禄.陆地棉纤维品质性状主基因与多基因混合遗传分析.中国农学通报,2006,22(2):157~161
    80.温永仙.基于遗传贡献率的陆地棉营养品质性状动态发育研究.生物数学学报,2007,22(3): 539~546
    81.巫升鑫,潘建青,陈顺辉,吴正举,谢小丹,彭怀俊.烤烟若干农艺性状的杂种优势及其遗传分析.中国烟草学报,2001,7(4):17~22陈顺辉
    82.吴吉祥,朱军,季道藩,许馥华.陆地棉产量性状的遗传效应及其与环境互作的分析.遗传,1995, 17(5):1~4
    83.吴吉祥,朱军.不同环境下作物基因型值和杂种优势的分析方法.浙江农业大学学报,1994,20(6):587~592
    84.吴茂清,张献龙,聂以春,贺道华.四倍体栽培棉种产量和纤维品质性状的QTL定位.遗传学报,2003,30:443~452
    85.吴为人,周元昌,李维明.数量性状基因型选择与基因型值选择潜力的比较.科学通报,2002,47:2080~2083
    86.武耀廷,张天真,朱协飞,王广明.陆地棉遗传距离与杂种F1、F2产量及杂种优势的相关分析.中国农业科学,2002,35(1):22~28
    87.肖炳光.烤烟农艺性状和烟叶化学成分的遗传分析.[博士学位论文].杭州:浙江大学,2005
    88.邢朝柱,靖深蓉,郭立平,袁有禄,王海林.转Bt基因棉杂种优势及性状配合力研究.棉花学报,2000, 12 (1)∶6~11
    89.邢朝柱,喻树迅,郭立平,苗成朵,冯文娟,王海林,赵云雷.不同环境下抗虫陆地棉杂交种优势表现及经济性状分析.棉花学报,2007,19(1):3~7
    90.邢朝柱,喻树迅,郭立平,叶子弘,王海林,苗成朵,赵云雷.不同生态环境下陆地棉转基因抗虫杂交棉遗传效应及杂种优势分析.中国农业科学,2007,40(5):1056~1063
    91.邢朝柱.杂交棉遗传效应及基因差异表达与杂种优势关系研究.[博士学位论文].北京:中国农业科学院,2005
    92.徐美兰,金正勋,李晓光,张忠臣,刘海英,张丰转,赵书宇,张海彬. 7个粳稻SSR和SRAP分子标记遗传距离比较及其与产量性状杂种优势的关系.分子植物育种, 2009, 7(6):1084~1092
    93.许乃银,钱大顺,张木莲,狄佳春.陆地棉F2单株结铃数的发育遗传研究.江西农业学报,2004, 16( 3): 22~26
    94.许自成,朱军.双交组合农艺性状的ADAA模型及其分析方法.遗传学报,2000,27(3):247~256
    95.薛勇彪,王道文,段子渊.分子设计育种研究进展.中国科学院院刊,2007,6:486~490
    96.杨曌,张新全,李向林,万里强,何峰.应用灰色关联度综合评价17个不同秋眠级苜蓿的生产性能.草业学报, 2009, 18(5): 67~72
    97.杨代刚,孙济中,刘金兰,张金发.棉花对红铃虫抗性及有关性状的遗传分析.棉花学报,1993, 5(2):62~68
    98.叶子弘,卢正中,朱军.陆地棉种子物理性状的发育遗传研究.棉花学报,2001,13(6):323~329
    99.尹利,逯晓萍,傅晓峰,李美娜,郭建.高丹草杂交种灰色关联度分析与评判.中国草地学报, 2006, 28(3): 21~25,43
    100.余四斌,李建雄,徐才国,谈移芳,高友军,李香花,张启发.上位性效应是水稻杂种优势的重要遗传基础.中国科学(C辑) ,1998,28(4):333~342
    101.喻树迅,范术丽,原日红,余学科,巩万奎.清除活性氧酶类对棉花早熟不早衰特性的遗传影响.棉花学报,1999,11(2):100~105
    201.喻树迅,郭香墨,邢朝柱.我国棉花现代育种技术应用与育种展望(上),中国农业信息,2008,3:19~22
    103.喻树迅,郭香墨,邢朝柱.我国棉花现代育种技术应用与育种展望(下),中国农业信息,2008,4:16~18
    104.喻树迅,宋美珍,范术丽,原日红.短季棉早熟不早衰生化辅助育种技术研究.中国农业科学,2005,38(4):664~670
    105.喻树迅.我国短季棉遗传改良成效评价及其早熟不早衰的生化遗传机制研究.[博士学位论文].西安:西北农林科技大学,2003
    106.喻树迅.中国短季棉育种学.北京:科学出版社,2007,61~291
    107.袁有禄,张天真,郭旺珍,潘家驹, Kohel R J.陆地棉优异纤维品系的铃重和衣分的遗传及杂种优势分析(英文).作物学报,2002, 28(2):196~202
    108.袁有禄,张天真,郭旺珍,Yu J,Kohl R J.棉花高品质纤维性状的主基因与多基因遗传分析.遗传学报,2002,29(9):827~834
    109.张军,武耀廷,郭旺珍,张天真.棉花微卫星标记的PAGE/银染快速检测,棉花学报, 2000,12(5): 267~269
    110.张名位,郭宝江,彭仲明.籼型黑米粒形性状的遗传效应及其与矿质元素含量的遗传相关性.遗传学报,2002,29(8):688~695
    111.张培通,朱协飞,郭旺珍,俞敬忠,张天真.高产棉花品种泗棉3号产量及其产量构成因素的遗传分析.作物学报,2006,32(7):1011~1017
    112.张涛,韩磊,徐建第,蒋开锋,吴先军,汪旭东,郑家奎.杂交香稻亲本遗传距离与产量杂种优势的相关性研究.中国农业科学, 2006, 39(4): 831~835
    113.张涛,倪先林,蒋开锋,杨乾华,杨莉,万先齐,曹应江,郑家奎.水稻功能基因标记遗传距离与杂种优势的相关性研究.中国水稻科学, 2009,23(6): 567~572
    114.张文英,程君奇,朱军,吴为人.上位性及其在遗传育种研究中的应用.生物信息学,2004,02:39~42(50)
    115.张文英,梅拥军,龚平.南疆陆地棉蕾、花、铃空间分布遗传研究.棉花学报,2004,16(1):31~35
    116.张文英,梅拥军.陆地棉铃形和纤维品质的遗传和相关研究.作物学报,2004,30(8):816~820
    117.张文英,梅拥军.陆地棉F1单株成铃数遗传决策系数分析.湖北农学院学报,2004,24(1):6~10
    118.张文英,梅拥军.陆地棉产量构成因素条件变量分析.中国农学通报,2004,20(2):109~113
    119.张文英,徐海明,朱军,基于环境互作的加性-显性-加加上位性模型的多环境指数选择(英文),棉花学报,2010,22(1):89~封三
    120.张正圣,李先碧,刘大军,肖月华,罗明,黄顺礼,张凤鑫.陆地棉高强纤维品系与Bt基因抗虫棉品系的配合力和杂种优势研究.中国农业科学,2002,35(12):1450~1455
    121.赵松义,高春阳,胡日生,朱列书.烤烟农艺性状的杂种优势表现.湖南农业大学学报(自然科学版).2007,33:193~197
    122.赵新华,王伯伦,贾宝艳.辽宁粳稻主要农艺性状的遗传研究.沈阳农业大学学报,2006,37(5): 693~697
    123.赵云雷.棉花杂交种与亲本间DNA胞嘧啶甲基化及其基因差异表达分析.[博士学位论文].武汉:华中农业大学,2007
    124.中国农业科学院棉花研究所.棉花遗传育种学.济南:山东科学技术出版社, 2003, 68~313
    125.中华人民共和国农业部.中华人民共和国农业行业标准NY/T 1297-2007.农作物品种审定规范—棉花.北京:中国农业出版社,2007
    126.中华人民共和国农业部.中华人民共和国农业行业标准NY/T 1302-2007.农作物品种试验技术规程—棉花.北京:中国农业出版社,2007
    127.朱军. Mixed model approaches for estimating genetic variances and covariances.生物数学学报,1992,7(1):1~11
    128.朱军.作物杂种后代基因型值和杂种优势的预测方法.生物数学学报,1993,8(1):32~44
    129.朱军,季道藩,许馥华.作物品种间杂种优势遗传分析的新方法.遗传学报,1993,20(3):262~271
    130.朱军.广义遗传模型与数量遗传分析新方法.浙江农业大学学报,1994,20(6):551~559
    131.朱军.包括基因型环境互作效应的种子遗传模型及其分析方法.遗传学报,1996,23(1):56~68
    132.朱军.数量性状遗传分析的新方法及其在育种中的应用.浙江大学学报(农业与生命科学版),2000,26(1):1~6
    133.朱军.遗传模型分析方法[M].北京:中国农业出版社,1997
    134.朱军, Wang G J, Zhang R C. Genetic analysis on gene effects and GE interaction effects forkernel nutrient quality traits of upland cotton.生物数学学报,1997,12(2):111~120
    135.朱军.复杂性状遗传分析的方法,数量遗传分析与QTL定位研讨班.杭州:浙江大学农学系,2010
    136.左清凡,朱军,刘宜柏,潘晓云,张建中.非等试验设计植株农艺及产量性状的数量遗传分析方法.中国农业科学,2000,33(2):30~33
    137.Abdurakhmonov I Y, Buriev Z T, Saha S, Pepper A E, Musaev J A, Almatov A, Shermatov S E,Kushanov F N, Mavlonov G T, Reddy U K, Yu J Z, Jenkins J N, Kohel R J, Abdukarimov A.Microsatellite markers associated with lint percentage trait in cotton (Gossypium hirsutum).Euphytica, 2007, 156: 141~156
    138.Ahuja S L, Dhayal L S, Prakash R. Comparative yield component analysis in Gossypium hirsutum parents using fiber quality grouping. Euphytica, 2008, 161:391~399
    139.Ahuja S L, Dhayal L S. Combining ability estimates for yield and fiber quality traits in 4×13 line×tester crosses of Gossypium hirsutum,Euphytica. 2007, 153:87-98
    140.Al-Rawi K M, Kohel R J. Diallel analyses of yield and other agronomic characters in Gossypium hirsutum L. Crop Sci, 1969, 9: 779~783
    141.Atchley, W. R. and J. Zhu. Developmental quantitative genetics, conditionalepigenetic variability and growth in mice. Genetics, 1997, 147: 765~776
    142.B.G. Xiao, J. Zhu, X.P. Lu, Y.F. Bai b, Y.P. Li. Analysis on genetic contribution of agronomic traits to total sugar in flue-cured tobacco (Nicotiana tabacum L.). Field Crops Research,2007,102:98~103
    143.Balestre M, Machado J C, Lima J L, Souza J C, Filho L N. Genetic distance estimates among single cross hybrids and correlation with specific combining ability and yield in corn double cross hybrids. Genetics and Molecular Research,2008,7(1): 65~73
    144.Bhandari H S, Pierce C A, Murray L W, Ray I M. Combining Abilities and Heterosis for Forage Yield among High-Yielding Accessions of the Alfalfa Core Collection. Crop Sci, 2007, 47:665~673
    145.Birchler J A, Auger D L, Riddle N C. In search of a molecular basis of heterosis. Plant Cell, 2003,15: 2236~2239
    146.Blenda A, Scheffler J, Scheffler B, Palmer M, Lacape J M, Yu J Z, Jesudurai C, Jung S,Muthukumar S, Yellambalase P, Ficklin S, Staton M, Eshelman R, Ulloa M, Saha S, Burr B, Liu S, Zhang T, Fang D, Pepper A, et al. CMD: a Cotton Microsatellite Database resource for Gossypium genomics. BMC Genomics, 2006, 7: 132
    147.Boppenmaier J, Melchinger A E, Brunklaus-June E, Brunklaus-Jung E,Geiger H H, Herrmann R G. Genetic diversity for RFLP in European maize in breeds. I. Relation to performance of flintxdent crosses for forage trait. Crop Science, 1992, 32: 895~902
    148.Borevita J O, Malloof J N, Lutes J, et al. Quantitative trait loci controlling light and hormone response in two accessions of Arabidopsis thaliana. Genetics, 2002, 160:683~696
    149.Broman K W,Wu H, Sens, et al. R/qtl: QTL mapping in experimental crosses. Bioinformatics, 2003, 19 (7): 889~890
    150.Bruce A.B. The Mendelian theory of heredity and augmention of Vogor. Sciences, 1910, (32):627~628
    151.Campbell B T, Bowman D T, Weaver D B. Heterotic Effects in Topcrosses of Modern and Obsolete Cotton Cultivars. Crop Sci,2008,48:593~600
    152.Cavalli L L. Analysis of linkage quantitative inheritance. In Quantitative Inheritance (Eds E. C. R.Reevea & C. H. Waddington), London: HMSO, 1952, 135~144
    153.Chase K, Adler F R, Lark K G. Epistat: a computer program for identifying and testing interactions between pairs of quantitative trait loci. Theoretical and Applied Genetics, 1997, 94: 724~730
    154.Chen, J. G. and J. Zhu. Genetic effects and genetic environment interactions for cooking quality traits in indica~japonica crosses of rice (Oryza sativa L.). Euphytica, 1999, 109: 9~15
    155.Cockerham CC.An extension of the concept of partitioning hereditary variance for analysis of covariances among relatives when epistasis in present. Genetics, 1954,39:859~882
    156.Coors J G, Pandey S. Genetics and exploitation of heterosis in crops. Crop Science Society of America, Madison, WI, 1999, 33:700~705
    157.Crow J F. Dominance and overdominance. In:J.G. Coors and S. Pandey, eds. The genetics and exploitation of heterosis in crops. Madison, WI:Crop Science Society of America, 1999, 49~58
    158.Davenport, C.B. Degeneration, albinism and inbreeding. Science, 1908, 28: 454~455
    159.Dean, C. F. Heterosis, inbreeding depression, and combining ability in diallel crosses of cigar– wrapper tobacco. Crop Science, 1974,14:482~484
    160.Dudley J W, Moll R H. Interpretation and use of heritability and genetic estimates in plant breeding. Crop Science, 1969,9:257~262
    161.Dudley J W. Molecular markers in plant improvement Manipulation of genes affecting quantitative traits. Crop Science,1993,33:660~668
    162.Dudley JW, Saghai MA, Rufener GK. Molecular markers and grouping of parents in maize breeding programs. Crop Science,1991,31(3):718~723
    163.Duvick D N. Heterosis: Feeding people and protecting natural resources. In: J. G. Coors and S. Pandey, eds.The genetics and exploitation of heterosis in crops . Madison, WI: Crop Science Society of America,1999,19~30
    164.East E M. Heterosis. Genetics,1936,21:375~397
    165.Elston R C, Steward J. The analysis of quantitative traits for simple genetic models from parental,F1 and backcross data. Genetics, 1973,73:695~711
    166.Endrizzi J E, Turcotte E C, Kohel R J. Qualitative genetics, cytology, and cytogenetics. In:R.J.Kohel and C.F.Lewis, eds. Cotton.Madison,Wisconsin,USA:ASA/CSSA/SSSA,Inc., Publishers, 1984,81~129
    167.Everina P, Lukonge, Labuschagne M T, Herselman L. Combining ability for yield and fiber characteristics in Tanzanian cotton germplasm. Euphytica, 2007,161, 383~389
    168.Fan C J and Aycock M K. Diallel crosses among Maryland cultivar. Crop Science,1974, 14:679~682
    169.Gai J Y, Zhang Y M, Wang J K. The Genetic System of Quantitative Traits in Plants. Beijing:China Science Press, 2003
    170.Gardner C O, Eberhart S A. Analysis and Interpretation of the Variety Cross Diallel and Related Populations. Biometrics, 1966, 22: 439~452
    171.Gimelfarb A, Lande R. Simulation of marker assisted selection in hybrid population. Genetical Research, 1994, 63: 39~47
    172.Godoy A S, Palomo G A. Genetic analysis of earliness in upland cotton (Gossypium hirsutum L.).I. Morphological and phenological variables. Euphytica, 1999, 105: 155~160
    173.Gopinath, D. M., V. V. Ramanarao, M. Subrahmanyam and C. L. Narayana. A study of diallel crosses between varieties of Nicotiana tabacum L. for yield components. Euphytica, 1966, 15:171~178
    174.Gou J.Y.,Wang L.J.,Chen S.P.,Hu W.L.,Chen X.Y. Gene expression and metabolite profiles of cotton fiber during cell elongation and secondary cell wall synthesis, Cell Research,2007,17(5):422~434
    175.Graham G I, Wolff D W, Stuber C W. Characterization of a yield quantitative trait locus on chromosome 5 of maize by fine mapping. Crop Sci, 1997, 37: 1601~1610
    176.Griffing B. Concept of general and specific combining ability in relation to diallel crossing systems. Austrilian Journal of Biology Science, 1956, 9: 463~493
    177.Guo W, Cai C, Wang C, Han Z, Song X, Wang K, Niu X, Wang C, Lu K, Shi B, Zhang T. A microsatellite-based, gene-rich linkage map reveals genome structure, function and evolution in Gossypium. Genetics, 2007, 176: 527~541
    178.Guo W, Ma G, Zhu Y, Chen X, Zhang T. Molecular Tagging and Mapping of Quantitative Trait Loci for Lint Percentage and Morphological Marker Genes in Upland Cotton. Journal of Integrative Plant Biology, 2006, 48: 320~326
    179.Gusmini G, Wehner T C, Donaghy S B. SASQuant: A SAS Software Program to Estimate Genetic Effects and Heritabilities of Quantitative Traits in Populations Consisting of 6 Related Generations. Journal of Heredity, 2007, 98, 345~350
    180.Gutierrez A, Basu S, Saha S, Jenkins J N, Shoemaker D B, Cheatham C L, McCarty J C Jr.Genetic Distance among Selected Cotton Genotypes and Its Relationship with F2 Performance. Crop Science, 2002, 42:1841~1847
    181.Hayman, B. I. The theory and analysis of diallel crosses. Genetics,1954,39:789~809
    182.Heckenberger M, Bohn M, Klein D, Melchinger A E. Identification of Essentially Derived Varieties Obtained from Biparental Crosses of Homozygous Lines: II. Morphological Distances and Heterosis in Comparison with Simple Sequence Repeat and Amplified Fragment Length Polymorphism Data in Maize. Crop Science, 2005, 45: 1132~1140
    183.Heitholt J J. Cotton boll retention and its relationship to lint yield. Crop Science, 1993,33: 486~490
    184.Holland J B. Epistacy: A SAS program for detecting two locus epistatic interactions using genetic marker information. Journal of Heredity, 1998,89:374~375
    185.Holland J B. Estimating Genotypic Correlations and Their Standard Errors Using Multivariate Restricted Maximum Likelihood Estimation with SAS Proc MIXED. CropScience, 2006, 46: 642~654
    186.Hollick J B, Chandler V L. Epigenetic allelic states of a maize transcriptional regulatory locus exhibit overdominant gene action. Genetics,1998,150:891~897
    187.Hua J, Xing Y, Wu W, Xu C, Sun X, Yu S, Zhang Q. Single-locus heterotic effects and dominance by dominance interactions can adequately explain the genetic basis of heterosis in an elite rice hybrid. Proceedings of the National Academy of Sciences of the United States of America,2003, 100: 2574~2579
    188.Hua J, Xing Y, Xu C, Sun X, Yu S, Zhang Q. Genetic Dissection of an Elite Rice Hybrid Revealed That Heterozygotes Are Not Always Advantageous for Performance. Genetics, 2004,162: 1885~1895
    189.Jeffrey C Z, Scheffler B E, Elizabeth D, Barbara A T, Zhang T Z, Guo W Z, Chen X Y, Stelly D M, Rabinowicz P D, Town C D, Arioli T, Brubaker C, Cantrell R G, Lacape J M, Ulloa M, Chee P, Gingle A R, Haigler C H, Percy Richard, Saha S, et al. Toward Sequencing Cotton (Gossypium)Genomes. Plant Physiology, 2007, 145: 1303~1310
    190.Ji Xiang Wu,Osman Ariel Gutierrez,Johnie N. Jenkins ,Jack C. McCarty ,Jun Zhu. Quantitative analysis and QTL mapping for agronomic and fiber traits in an RI population of upland cotton. Euphytica ,2009,165:231~245
    191.Jones D F.Dominance of linked factors as a means of accounting for heterosis. Proceedings of the National Academy of Sciences of the United States of America,1917,(3):310~312
    192.Zhu J. New Approaches for Analyzing Quantitative Traits and Their Applications in Cotton.in:J.N.Jenkins and S.Saha,eds.Genetic Improvement of Cotton:Emerging Technologies. Science Publishers,INC.2001,43~64
    193.Kohel R J, Richmond T R. The genetics of flowering response in cotton. IV. Quantitative analysis of photoperiodism of Texas 86, Gossypium hirsutum race latifolium, in a cross with an inbred line of cultivated American Upland cotton. Genetics, 1962, 47: 1535-1542
    194.Kohel R. J.and Lewis G.F..COTTON.American Society of Agronomy,Inc.,Crop Science Society of America,Inc.,Soil Science Society of America,Inc.,Publishers, Madison, Wisconsin,USA,1984
    195.Lacape J M, Nguyen T B, Courtois B, Belot J L, Giband M, Gourlot J P, Gawryziak G, Roques S,Hau B. QTL analysis of cotton fiber quality using multiple Gossypium hirsutum×Gossypium barbadense backcross generations. Crop Science, 2005, 45: 123~140
    196.Lalitha Devi, D., R. Lakshminarayana and J. B. Atluri. Genetic variability and correlation studies on seed and other quantitative characters in Nicotiana tabacum L. Tobacco Research, 2002, 28(2):90~96
    197.Lande R. The minimum number of genes contributing to quantitative variation betweenand within populations. Genetics,1981,99:541~553
    198.Lee J A, Miller P A, Rawlings J O. Interaction of combining ability effects with environments in diallel crosses of upland cotton (Gossypium hirsutum L.). Crop Science, 1967, 7: 477~481
    199.Lee M, Godshalk E B, Lamkey K R, Woodman W W. Association of restriction fragment length polymorphisms among maize in breeds with agronomic performance of their crosses. Crop Science, 1989, 29: 1067~1071
    200.Li L Z, Lu K Y, Chen Z M, et al. Dominance, overdominance and epistasis condition the heterosis in two heterotic rice hybrids. Genetics,2008,180:1725~1742
    201.Li W X,Ning H L,Li W B,Lu W H.Developmental Genetic Analysis of Seed Size in Soybean(Glycine max). Acta Genetica Sinica, August 2006,33(8):746~756
    202.Li Z K, Luo L J, Mei H W, et al. Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice I. Biomass and grain yield. Genetics,2001,158:1737~1753
    203.Li Z K, Pinson S R M, Park W D, et al.Epistasis for three grain yield components in rice (Oryza sativa L.).Genetics,1997,145:453~465
    204.Lide Han, Jian Yang, Jun Zhu.Analysis of Genetic Effects of Nuclear-Cytoplasmic Interac-tion on Quantitative Traits: Genetic Model for Diploid Plants. Journal of Genetics and Genomics, 2007, 34(6): 562~568
    205.Liu G F, Yang J, Xu H M, Zhu J.Influence of Epistasis and QTL×Environment Interaction on Heading Date of Rice (Oryza sativa L.). Journal of Genetics and Genomics, 2007,34(7):608~615
    206.Liu G F, Yang J, Xu H M, Hayat Y, Zhu J. Genetic analysis of grain yield conditioned on its component traits in rice (Oryza sativa L.). Australian Journal of Agricultural Research, 2008, 59, 189~195
    207.Malberg R L, Held S,Waits A, et al. Epistasis for fitness-related quantitative traits in Arabidopsis thaliana grown in the field and in the greenhouse. Genetics, 2005, 171:2013~2027
    208.Marani A. Heterosis and F2 performance of intraspecific crosses among varieties of Gossypium hirsutum L. and of G.barbadense L.Crop Science,1968,8:111~113
    209.Mather K, Jinks J L. Biometrical Genetics, 3rd edn. London: Chapman and Hall, 1982
    210.McCarty J C, Wu J, Jenkins J N. Use of Primitive Derived Cotton Accessions for Agronomic and Fiber Traits Improvement: Variance Components and Genetic Effects. Crop Science, 2007, 47:100~110
    211.McCARTY Jack C, WU Ji-Xiang ,JENKINS Johnie N, GUO Xiang-mo. Evaluating American and China Cotton Cultivars and Their Crosses for Improvement. Cotton Science,2005 ,17 (1):47~55
    212.Mei Y J, Ye Z H,Zhang L L. Genetic Analysis for F1 Yield Traits with ConditionalApproach in Island Cotton (Gossypium barbadense L.). Acta Genetica Sinica, 2006,33(9):841~850
    213.Meredith W R, Jr, Bridge R R. The relationship between F2 and selected F3 progenies in cotton (Gossypium hirsutum L.).Crop Science,1973,13:354~356
    214.Meredith W R, Jr. Yield and fiber quality potential for second-generation cotton hybrids. Crop Science,1990,30:1045~1048
    215.Meredith W R, Jr., Bridge R R. Heterosis and gene action in cotton, Gossypium hirsutum L. Crop Science, 1972, 12: 304~310
    216.Meredith W R. Quantitative Genetics.in: R.J.Kohel and C.F.Lewis,eds.Cotton. Madison, Wisconsin,USA:ASA,Inc.,CSSA,Inc.,SSSA,Inc.,Publishers,1984,24:131~150
    217.Miller, R. G., The jackknife: a review. Biometrika,1974,61:1-15
    218.Murray L W, Ray I M, Dong H, Segovia-Lerma A. Clarification and reevaluation of population-based diallel analyses: Gardner and Eberhart analyses II and III revisited. Crop Science,2003, 43:1930~1937
    219.Nei M, Li W. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Sciences of the United States of America , 1979,76(10):5269~5273
    220.Paterson A H, Brubaker C L, Wendel J F. A rapid method for extraction of cotton (Gossypium spp)genomic DNA suitable for RFLP or PCR analysis. Plant Molecular Biology Reporter, 1993,11(2): 122~127
    221.Paterson A, Saranga, Menz, Jiang. Wright QTL analysis of genotype×environment interactions affecting cotton fiber quality. Theoretical and Applied Genetics, 2003, 106: 384~396
    222.Peleman J D, Voort J R. Breeding by design.Trends Plant Science, 2003,8:330~334
    223.Podich D W, Cooper M. QU-GENE: a simulation platform for quantitative analysis of genetic models. Bioinformatics, 1998, 14:632~653
    224.Podlich D W, Winkler C R, Cooper M1 Mapping as you go: An effective approach for marker assisted selection of complex traits1. Crop Science, 2004, 44 : 1560~1571
    225.Quisenberry J E. Inheritace of Plant Height in Cotton. II. Diallel Analyses among 6Semidwarf Strains. Crop Science, 1977, 17: 347~350
    226.Ragsdale P I, Wayne S C. Germplasm Potential for Trait Improvement in Upland Cotton: Diallel Analysis of Within-Boll Seed Yield Components. Crop Science, 2007, 47:1013~1017
    227.SAS Institute. SAS Version 8.02 for Windows. Cary, NC, USA: SAS Institute Inc, 1999
    228.Segovia-Lerma A, Murray L W, Townsend M S, Ray I M. Population-based diallel analyses among nine historically recognized alfalfa germplasms. Theoretical and Applied Genetics, 2004, 109: 1568~1575
    229.Semel Y, Nissenbaum J, Menda N, Zinder M, Krieger U, Issman N, Pleban T, LippmanZ, Gur A,Zamir D. Overdominant quantitative trait loci for yield and fitness in tomato. Proceedings of the National Academy of Sciences of the United States of America,2006, 103: 12981~12986
    230.Sen S, Churchill G A. A statistical framework for quantitative trait mapping. Genetics,2001,159:371~387
    231.Shen X L, Guo W Z, Lu Q X, Zhu X F, Yuan Y L, Zhang T Z. Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in Upland cotton. Euphytica, 2007, 155:371~380
    232.Shen X L, Guo W Z, Yu J, Kohel R J, Zhang T Z. Molecular mapping of QTLs for fiber qualities in three diverse lines in upland cotton using SSR marker. Molecular Breeding, 2005, 15(2): 169~181
    233.Shen X L, Zhang T Z, Guo W Z, Zhu X F, Zhang X Y, Mapping Fiber and Yield QTLs with Main, Epistatic, and QTL×Environment Interaction Effects in Recombinant Inbred Lines of Upland Cotton. Crop Science, 2006, 46:61~66
    234.Shull G.H..The composition of a field of Maize.Am Breed Assoc.,1908,(4):298~301
    235.Smith O S, Smith J S C, Bowen S L, Tenborg R A, Wall S J. Similarities among a group of elite maize in breeds as measured by pedigree, F1 grain yield, grain yield heterosis, and RFLPs. Theoretical and Applied Genetics, 1990, 80: 833-840
    236.Soengas P, Ordas B, Malvar R A, Revilla P, Ordas A. Combining Abilities and Heterosis for Adaptation in Flint Maize Populations. Crop Science, 2006, 46:2666~2669
    237.Stuber C W, Lincoln S E , Wolff D W, et al. Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers.Genetics,1992,132:823~839
    238.Stuber, C W. Heterosis in plant breeding. Plant Breeding Reviews.1994,12:227~251
    239.Sun Q, Wu L, Ni Z, Meng F, Wang Z, Lin Z. Differential gene expression patterns in leaves between hybrids and their parental inbreds are correlated with heterosis in a wheat diallel cross.Plant Science, 2004, 166: 651~657
    240.Tan C J, Sun Y J, Xu H S, et al. Identification of quantitative trait locus and epistatic interaction for degenerated spikelets on the top of panicle in rice. Plant Breeding, 2011, 130: 177~184
    241.Tang B, Jenkins J N, McCarty J C, Watson C E. F2 hybrids of host plant germplasm and cotton cultivars: II.Heterosis and combining ability for fiber properties. Crop Science, 1993, 33:706~710
    242.Ulloa M, Saha S, Jenkins JN, Meredith WR Jr, McCarty JC Jr, Stelly D M. Chromosomal assignment of RFLP linkage groups harboring important QTLs on an intraspecific cotton (Gossypium hirsutum L.) Joinmap. Journal of Heredity, 2005, 96: 132~144
    243.Ulloa M. Heritability and correlations of agronomic and fiber traits in an okra-Leaf upland cotton population. Crop Science, 2006, 46: 1508~1514
    244.Waghmare V N, Rong J K, Rogers C J, Pierce G J, Wendel J F, Paterson A H. Genetic mapping of a cross between Gossypium hirsutum (cotton) and the Hawaiian endemic, Gossypium tomentosum. Theoretical and Applied Genetics, 2005, 111: 665~676
    245.Wang B, Wu Y, Guo W, Zhu X, Huang N, Zhang T. QTL Analysis and Epistasis Effects Dissection of Fiber Qualities in an Elite Cotton Hybrid Grown in Second Generation. Crop Science.2007, 47:1384~1392
    246.WANG D L,ZHU J,LI Z K, et al.Mapping QTLs with epistasis effects and QTL×environment interactions by mixed linear model approaches. Theoretical and Applied Genetics, 1999,99:1256~1264
    247.Wang J K, Gai J Y. Mixed inheritance model for resistance to agromyzid bean fly(Melanagromyza sojae Zehntner)in soybean. Euphytica, 2001, 122: 9~18
    248.Wang J, Chapman S C, Bonnett D G, Rebetzke G J, Jonathan C. Application of population genetic theory and simulation models to efficiently pyramid multiple genes via marker-assisted selection. Crop Science, 2007, 47: 582~590
    249.Wang J, Podlich D W, Cooper M, DeLacy I H. Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits. Theoretical and Applied Genetics, 2001, 103: 804~816
    250.Wang S C, Basten C J, Zeng Z B. Windows QTL cartographer 2.5 department of statistics [EB/OL], North Carolina State University, Raleigh, NC. http://statgen,ncsu.edu/qtlcart/WQTLCart.htm. 2007-04-13
    251.Warner J N. A method for estimating heritability. Agronomy Journal, 1952, 44: 427~430
    252.Wen Y X,Zhu Jun. Multivariable Conditional Analysis for Complex Trait and Its Components. Acta Genetica Sinica, 2005, 32(3):289~296
    253.Wright S. The genetics of quantitative variability. In: Wright S, editor. Evolution and genetics of populations. 2nd ed. Volume 1. Chicago (IL): University of Chicago Press, 1968, 373~420
    254.Wu R L. Quantitative genetic variation of leaf size and shape in a mixed diploid and triploid population of Populus. Genetical Research, 2000, 75: 215~222
    255.Wu R, Bradshaw H D, J r, Stettler R F. Molecular genetics of growth and development in Populus(Salicaceae).V.Mapping quantitative trait loci affecting leaf variation. American Journal of Botany, 1997, 84: 143~153
    256.Wu R, Stettler R F. Quantitative genetics of growth and development in Populus I.A three-generation comparison of tree architecture during the first two years of growth. Theoretical and Applied Genetics, 1994, 88: 1046~1054
    257.Xiao J, Li J, Yuan L, McCouch S R, Tanksley S D. Genetic diversity and its relationship to hybrid performance and heterosis in rice as revealed by PCR-based markers. Theoretical and Applied Genetics, 1996, 92: 637~643
    258.Xiao J, Li J, Yuan L, Tanksley S D. Dominance is the Major Genetic Basis of Heterosis in Rice as Revealed by QTL Analysis Using Molecular Markers. Genetics, 1995, 140: 745~754
    259.Xing C Z, Zhao Y L, Yu S X, Guo L P, Zhang X L, Wang H L. Relationship between leaves gene differential expression in full opening flower stages of hybrids & their parents and heterosis in pest-resistant cotton. Acta Genetica Sinica, 2006, 33 (10): 948~956
    260.Xiong L Z, Yang G P, Xu C G. Relationship of differential gene expression in leaves with heterosis and heterozygosity in a rice diallel cross. Molecular Breeding, 1998, 4: 129~136
    261.Xu Y, Kang D, Shi Z,Shen H, Wehner T. Inheritance of resistance to zucchini yellow mosaic virus and watermelon mosaic virus in watermelon. Journal of Heredity, 2004 95:498~502
    262.Xu, Z. C. and J. Zhu. An approach for predicting heterosis based on an additive, dominance and additive 174 additive model with environment interaction. Heredity, 1999, 82: 510~517
    263.Yamada T, Jones E S, Cogan N O I, Vecchies A C, Nomura T, Hisano H, Shimamoto Y, Smith K F, Hayward M D, Forster J W. QTL analysis of morphological,developmental,and winter hardiness-associated traits in perennial ryegrass. Crop Science, 2004, 44:925~935
    264.Yan, X. F., J. Zhu, S. Y. Xu and Y. H. Xu. Genetic effects of embryo and endosperm for four malting quality traits of barley. Euphytica, 1999, 106: 27~34
    265.Yan, X. F., S. Y. Su, Y. H. Xu and J. Zhu. Genetic investigation of contributions of embryo and endosperm genes to malt kolbach index, alpha–amylase activity and wort nitrogen content in barley. Theoretical and Applied Genetics, 1998, 96: 709~715
    266.YANG J, HU C C, YE X Z, ZHU J.QTLNetwork [EB/OL],Institute of Bioinformatics, Zhejiang University.Hangzhou,China. http://ibi.zju.edu.cn/software/qtlnetwork.2006-09-20
    267.Ye, Z. H., Z. Z. Lu and J. Zhu. Genetic analysis for developmental behavior of some seed quality traits in upland cotton (Gossypium hirsutum L.).Euphytica, 2003,129: 183~191
    268.Young E F, Murray J C, Heterosis and inbreeding depression in diploid and tetraploid cottons.Crop Science,1966,6:436~438
    269.Yu C,Hu S,Zhao H,Guo A,Sun G.Genetic distances revealed by morphological characters, isozymes,proteins and RAPD markers and their relationships with hybrid performance in oilseed rape(Brassica napus L.). Theoretical and Applied Genetics,2005,110:511~518
    270.Yu J W, Yu S X, Lu C R, Wang W, Fan S L, Song M Z, Lin Z X, Zhang X L, Zhang J F.A high-density linkage map of cultivated allotertrapoid cotton based on SSR, TRAP, SRAP and AFLP markers.Journal of Integrative Plant Biology,2007,49:716~724
    271.Yu S X, Song M Z, Fan S L. Biochemical Genetics of Short-season Cotton Cultivars that Express Early Maturity Without Senescence, Journal of Integrative Plant Biology.2005, 47(3):334~342
    272.Yu S, Li J X, Xu C G, Tan Y F, Gao Y J, Li X H, Zhang Q F, Saghai Maroof M A. Importance of epistasis as the genetic basis of heterosis in an elite rice hybrid. Proceedings of the National Academy of Sciences of the United States of America, 1997, 94: 9226~9231
    273.Zhang Q F, Gao Y J, Saghai Maroof M A, Yang S H, Li J X. Molecular divergence and hybrid performance in rice. Molecular Breeding, 1995, 1(2): 133~142
    274.Zhang Q F, Zhou Z Q, Yang G P, Xu C G, Liu K D, Saghai Maroof M A. Molecular marker heterosis gosity and hybridperformance in indica and japonica rice. Theoretical and Applied Genetics, 1996, 93: 1218~1224
    275.Zhang W Y, Xu H M, Zhu J. Index selection on seed traits under direct, cytoplasmic and maternal effects in multiple environments. Journal of Genetics and Genomics,2009,36 41~49
    276.Zhang X Q, Wang X D, Jiang P D, Hua S J, Zhang H P,Dutt Y. Relationship between molecular marker heterozygosity and hybrid performance in intra- and interspecific hybrids of cotton,Plant Breeding, 2007, 126: 385~391
    277.Zhang Y D, Kang M S, Lamkey K R. DIALLEL-SAS05: A Comprehensive Program for Griffing’s and Gardner–Eberhart Analyses. Agronomy Journal, 2005, 97:1097~1106
    278.Zhang Y M, Gai J Y, Yang Y H, The EIM algorithm in the joint segregation analysis of quantitative traits. Genetic Research, 2003, 81:157~163
    279.Zhang Z S, Xiao Y H, Luo M, Li X B, Luo X Y, Hou L, Li D M, Pei Y. Construction of a genentic linkage map and QTL analysis of fiber-related traits in upland cotton (Gossypium hirsutum L). Euphytica, 2005:1~9
    280.Zhao Y, Xing C,Fan S, Song M. Analysis of DNA Methylation in Cotton Hybrids and Their Parents. Molecular Biology, 2008, 42 (1):217
    281.Zhou P, Tan Y, He Y, Zhang Q. Simultaneous improvement for four quality traits of Zhenshan 97,an elite parent of hybrid rice by molecular marker assisted selection. Theoretical and Applied Genetics, 2003, 106 : 326~331
    282.Zhu, J. and B. S. Wier. Analysis of cytoplasmic and maternal effects.Ⅰ.A genetic model for diploid plant seeds and animals. Theor. Appl. Genet., 1994, 89: 153~159
    283.Zhu, J. and B. S. Wier. Analysis of cytoplasmic and maternal effects.Ⅱ.Genetic models for triploid endosperms. Theoretical and Applied Genetics, 1994, 89: 160~166
    284.Zhu, J., Analysis of conditional genetic effects and variance components in developmental genetics. Genetics, 1995,141: 1633~1639
    285.Zhu, J. and B. S. Weir. Mixed model approaches for diallel analysis based on a biomodel. Genetics Research, 1996, 68: 233~240

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700