四川农业大学小麦研究所, 四川成都611130
Genetic Effects of Key Genomic Regions Controlling Yield-Related Traits in Wheat Founder Parent Fan 6
DENGMei, HEYuan-Jiang, GOULu-Lu, YAOFang-Jie, LIJian, ZHANGXue-Mei, LONGLi, MAJian, JIANGQian-Tao, LIUYa-Xi, WEIYu-Ming, CHENGuo-Yue通讯作者:
收稿日期:2017-05-27
接受日期:2017-11-21
网络出版日期:2017-12-27
版权声明:2017作物学报编辑部作物学报编辑部
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小麦(Triticum aestivum L.)是世界上最重要的粮食作物之一, 养育了全球约35%的人口[1]。在我国, 随着工业化的发展, 地少人多的矛盾日益加剧, 提高产量仍然是小麦育种研究的主要方向[2]。小麦的品种改良和不同时期的小麦品种更换中, 骨干亲本发挥着重要的作用。骨干亲本是指直接用来培育出一批大面积推广的品种, 或由其衍生出许多具有广泛应用价值的亲本育种材料, 通常骨干亲本除本身具备综合的优良性状之外, 还应具有高配合力, 即易与其他材料杂交育成优良品种[3,4]。在我国小麦品种改良进程中, 形成了蚂蚱麦、燕大1817、江东门、成都光头、蚰子麦、碧蚂4号、北京8号、西农6028、五一麦、南大2419、欧柔、阿夫、阿勃、早洋麦、洛夫林10号、墨巴66、繁6、矮孟牛、小偃6号、周8425B等20余个小麦骨干亲本[3]。
Li等[5]试验表明, 北京8号作为骨干亲本的基础是产量性状在衍生品种中广泛的稳定遗传特性, 其重要性状相关的SSR遗传区段在衍生后代中传递良好。Jia等[6]利用骨干亲本南大2419与望江白构建的重组自交系群体定位了产量相关的QTL。袁园园等[7]利用SSR、EST-SSR和STS标记对骨干亲本碧蚂4号的基因组特异位点分析发现, 某些基因组位点在子代中传递频率比较高, 从而推测这些位点或区域可能是碧蚂4号成为骨干亲本的基础, 在育种过程中被育种学家强烈选择。近年来, 一些****利用分子标记对骨干亲本进行了遗传多样性和重要染色体区段分析, 构建作图群体进行基因定位。例如, 肖永贵等[8]利用高通量DArT分子标记和SSR标记对周8425B及其衍生品种进行遗传结构分析, 并对其携带的抗条锈病基因进行定位, 结果表明, 衍生品种携带的4个重要抗条锈病基因均来自于亲本“周8425B”, 分别位于1BL、2BL、3AL和7BL染色体上。此外, 小麦骨干亲本的胚乳品质相关蛋白亚基组成也是重要的研究方向。张学勇等[9]对在我国小麦中发挥重大作用的22个骨干亲本以及63个其他重要品种的蛋白质亚基系统分析, 并对骨干亲本的亚基组成总结分类; 肖静等[10]对骨干亲本矮孟牛及其衍生品种的HMW-GS及品质性状的演化和遗传传递进行分析。
繁6 (IBO1828/印度824/3/五一麦//成都光头/中农483分枝麦/4/中农28B分枝麦/IBO1812//印度824/阿夫)是20世纪60年代末育成的西南麦区的一个重要品种, 70年代的年种植面积超过230万公顷[11]。该品种具有抗条锈病、多花多粒、丰产等优良特性。由繁6衍生出的多个品种、品系, 如绵阳、川麦、川育系列等, 在四川省广泛种植, 极大地推进了四川省小麦的种植及四川地区小麦第5和第6次品种更换[11,12]。从基因组水平对繁6进行遗传解析, 分析其携带优良基因的遗传特性及在衍生品种中的传递规律, 对合理利用该骨干品种有积极意义。陈国跃等[13]利用SSR标记解析了繁6及其衍生品种中条锈病成株抗性的遗传特性, 但繁6中控制产量相关性状的重要基因组区段及关键位点的遗传效应尚不清楚。本研究以繁6及其39份衍生品种为材料, 通过田间多环境表型鉴定, 明确其产量相关性状的表型特征和演变趋势; 同时, 利用已获得的控制小麦产量相关性状“一致性”QTL区段的417个SSR标记[14], 鉴定控制繁6产量相关性状重要基因组区段及关键位点, 并解析其遗传效应, 为骨干亲本利用和小麦分子育种提供参考依据。
1 材料与方法
1.1 供试材料
选用繁6及其衍生品种39份, 包括衍生子1代至子5代各7、12、10、7和3份(附表1)。此外, 将繁6衍生后代品种系谱(附图1)中涉及的中间亲本材料14份、其他骨干亲本19份及候选骨干亲本2份用作表型对照和分子标记数据对比分析材料。所有材料由四川农业大学小麦研究所(四川成都)提供。Supplementary table 1
附表1
附表1试验品种及其系谱
Supplementary table 1Varieties used and their pedigrees
| 编号 No. | 品种 Variety | 世代 Generation | 系谱或亲本类型 Pedigree or parental type |
|---|---|---|---|
| 1 | 繁6 Fan 6 | FP | 伊博1828/印度824/3/五一麦//成都光头/中农483/4/中农28B/伊博1828//印度 824//阿夫 Yibo l828/India 824/3/Wuyimai//Chengduguangtou/Zhonnnon 9483/4/Zhongnong 28B/Yibo l828//India 824//Funo |
| 2 | 川育5号 Chuanyu 5 | 1st | 繁6姊妹系69-1776/大粒早 69-1776 of Fan 6’s sib-line/Dalizao |
| 3 | 川育6号 Chuanyu 6 | 1st | 繁6/川麦10号 Fan 6/Chuanmai 10 |
| 4 | 绵阳12 Mianyang 12 | 1st | 406C3-4-5/繁6 406C3-4-5/Fan 6 |
| 5 | 绵阳11 Mianyang 11 | 1st | 70-5858/繁6 70-5858/Fan 6 |
| 6 | 巴麦18 Bamai 18 | 1st | 内江31/繁6 Neijiang 31/Fan 6 |
| 7 | 蜀万831 Shuwan 831 | 1st | 蜀万761/繁6 Shuwan 761/Fan 6 |
| 编号 No. | 品种 Variety | 世代 Generation | 系谱或亲本类型 Pedigree or parental type |
| 8 | 80-8 | 1st | 繁6变异株 Mutant line of Fan 6 |
| 9 | 川辐4号 Chuanfu 4 | 2nd | 巴麦18/799-6007 Bamai 18/799-6007 |
| 10 | 绵阳15 Mianyang 15 | 2nd | 70-5858/繁6 70-5858/Fan 6 |
| 11 | 绵阳19 Mianyang 19 | 2nd | 绵阳11选系 Selection line of Mianyang 11 |
| 12 | 绵阳20 Mianyang 20 | 2nd | 绵阳11选系 Selection line of Mianyang 11 |
| 13 | 绵阳21 Mianyang 21 | 2nd | 绵阳11选系 Selection line of Mianyang 11 |
| 14 | 绵阳29 Mianyang 29 | 2nd | 绵阳11/江油83-5 Mianyang 11/Jiangyou 83-5 |
| 15 | 川农麦1号 Chuannongmai 1 | 2nd | 绵阳11/川雅84-1 Mianyang 11/Chuanya 84-1 |
| 16 | 川麦21 Chuanmai 21 | 2nd | 绵阳11/77中2882 Mianyang 11/77 zhong 2882 |
| 17 | 川麦22 Chuangmai 22 | 2nd | 绵阳11/川麦20 Mianyang 11/Chuanmai 20 |
| 18 | 渝麦4号 Yumai 4 | 2nd | 77中2882/巴麦18 77 zhong 2882/Bamai 1877 |
| 19 | 川辐1号 Chuanfu 1 | 2nd | β射线处理川育5号种子 Chuanyu 5 by β ray mutagenesis |
| 20 | 川育18 Chuanyu 18 | 2nd | 川育5号/墨460//94 F2-4 Chuanyu 5/Mexipak 460//94F2-4 |
| 21 | 川育7号 Chuanyu 7 | 3rd | 繁6/原110//阿170-8 Fan 6/Yuan 110//A170-8 |
| 22 | 川麦45 Chuanmai 45 | 3rd | 绵阳11//川麦22/川辐3号/3/PC17//繁6/川麦18 Mianyang 11//Chuanmai 22 Chuanfu/3/PC 17//Fan 6/Chuanmai 18 |
| 23 | 川育19 Chuanyu 19 | 3rd | 川育5号/墨460//绵阳26 Chuanyu 5/Mexipak 460//Mianyang 26 |
| 24 | 川麦28 Chuanmai 28 | 3rd | 万雅2号/繁6//高加索/繁6///绵阳19 Wanya 2/Fan 6//Kavkaz/Fan 6///Mianyang 19 |
| 25 | 绵阳26 Mianyang 26 | 3rd | 川育9号/绵阳20 Chuanyu 9/Mianyang 20 |
| 26 | 川麦24 Chuanmai 24 | 3rd | 8282-15/绵阳19 8282-15/Mianyang 19 |
| 27 | 川辐2号 Chuanfu 2 | 3rd | β射线诱变川辐1号(77中2882) F1 F1 of Chuanyu 1 (77 zhong 2882) by β-ray mutagenesis |
| 28 | 川辐3号 Chuanfu 3 | 3rd | β射线川辐1号(77中2282) Chuanyu 1 (77 zhong 2882) by β-ray mutagenesis |
| 29 | 绵农3号 Miannong 3 | 3rd | 75-21-4/76-19//绵农1号 75-21-4/76-19//Miannong 1 |
| 30 | 绵农4号 Miannong 4 | 3rd | 75-21-4/76-19//绵农1号 75-21-4/76-19//Miannong 1 |
| 31 | 川育17 Chuanyu 17 | 4th | 绵阳26/G295-4 Mianyang 26/G295-4 |
| 32 | 内麦8号 Neimai 8 | 4th | 绵阳26/92R178 Mianyang 26/92R178 |
| 33 | 内麦9号 Neimai 9 | 4th | 绵阳26/92R178 Mianyang 26/92R178 |
| 34 | 良麦2号 Liangmai 2 | 4th | 绵阳26/异源2号 Mianyang 26/Yiyuan 2 |
| 35 | 科成麦2号 Kechengmai 2 | 4th | 咸阳大穗/E//多花-1/3/贵农20/4/绵阳26 Xianyangdasui/E//Duohua-1/3/Guinong 20/4/Mianyang 26 |
| 36 | 川麦47 Chuanmai 47 | 4th | Syn-CD786/绵阳26//绵阳26 Syn-CD786/Mianyang 26//Mianyang 26 |
| 37 | 川育8号 Chuanyu 8 | 4th | 阿二矮/川育7号 Aerai/Chuanyu 7 |
| 38 | 川育12 Chuanyu 12 | 5th | 川育8号/83-4516 Chuanyu 8/83-4516 |
| 39 | 川农16 Chuannong 16 | 5th | 川育12/87-429 Chuanyu 12/87-429 |
| 40 | 川育14 Chuanyu 14 | 5th | 川育9号/黔花1号//川育8号/4/繁7/高加索//川育5号/3/川育9号 Chuanyu 9/Qianhua 1//Chuanyu 8/4/Fan 7/Kavkaz//Chuanyu 5/3/Chuanyu 9 |
| 41 | 大粒早 Dalizao | MP | Middle parent |
| 42 | 川麦10号 Chuanmai 10 | MP | Middle parent |
| 43 | 蜀万761 Shuwan 761 | MP | Middle parent |
| 44 | 阿二矮 A’er’ai | MP | Middle parent |
| 45 | 异源2号 Yiyuan 2 | MP | Middle parent |
| 46 | Alondra”S” | MP | Middle parent |
| 编号 No. | 品种 Variety | 世代 Generation | 系谱或亲本类型 Pedigree or parental type |
| 47 | 雅安早 Yaanzao | MP | Middle parent |
| 48 | 竹叶青 Zhuyeqing | MP | Middle parent |
| 49 | 玛拉Mara | MP | Middle parent |
| 50 | IBO1828 | MP | Middle parent |
| 51 | 大头黄 Datouhuang | MP | Middle parent |
| 52 | 万雅2号 Wanya 2 | MP | Middle parent |
| 53 | 84-2014 | MP | Middle parent |
| 54 | 川雅84-1 Chuanya 84-1 | MP | Middle parent |
| 55 | 阿勃 Abbondanza | OFP | Other founder parent |
| 56 | 南大2419 Nanda 2419 | OFP | Other founder parent |
| 57 | 小偃6号 Xiaoyan 6 | OFP | Other founder parent |
| 58 | 洛夫林10号 Lovrin 10 | OFP | Other founder parent |
| 59 | 碧玛4号 Bima 4 | OFP | Other founder parent |
| 60 | 蚂蚱麦 Mazhamai | OFP | Other founder parent |
| 61 | 江东门 Jiangdongmen | OFP | Other founder parent |
| 62 | 蚰子麦 Youzimai | OFP | Other founder parent |
| 63 | 燕大1817 Yanda 1817 | OFP | Other founder parent |
| 64 | 欧柔 Orofen | OFP | Other founder parent |
| 65 | 阿夫 Funo | OFP | Other founder parent |
| 66 | 北京8号 Beijing 8 | OFP | Other founder parent |
| 67 | 西农6028 Xinong 6028 | OFP | Other founder parent |
| 68 | 矮孟牛Aimengniu | OFP | Other founder parent |
| 69 | 墨巴66 Mexipak 66 | OFP | Other founder parent |
| 70 | 早洋麦 Early premium | OFP | Other founder parent |
| 71 | 周8425B Zhou 8425B | OFP | Other founder parent |
| 72 | 五一麦 Wuyimai | OFP | Other founder parent |
| 73 | 成都光头 Chengduguangtou | OFP | Other founder parent |
| 74 | 扬麦158 Yangmai 158 | CFP | Candidatefounder parent |
| 75 | 川麦42 Chuanmai 42 | CFP | Candidatefounder parent |
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显示原图|下载原图ZIP|生成PPT附图1骨干亲本繁6及其39个衍生后代品种系谱
-->Supplementary fig. 1The pedigree diagram of the founder parent Fan 6 and 39 derivatives
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1.2 产量相关性状表型鉴定
2010—2011和2011—2012年度, 分别于四川农业大学温江和崇州试验基地进行田间表型鉴定, 采用随机区组设计, 3次重复, 3个行区, 行长2.0 m, 行距0.3 m, 每行约20株, 生育期内常规田间管理。按《小麦种质资源描述规范和数据标准》[15]测定各产量相关性状。小麦蜡熟期, 随机取各供试材料10株, 测量其株高、穗长、小穗数和有效分蘖数; 收获时, 随机取各供试材料10株, 在室内测量小穗粒数、穗粒数、穗粒重和千粒重。10个单株的表型平均值作为该小区的一个表型观测数据。1.3 基因组DNA提取及SSR标记检测
取每个品种(系) 5个单株幼嫩叶片混合, 参照CTAB法提取基因组DNA[16]。基于本实验室已构建的小麦产量与品质相关性状“一致性”QTL遗传图谱[14], 筛选出417个SSR标记。参考http://wheat.pw.usda. gov/和http://www.scabusa.gov/数据库及R?der等[17]、Pestsova等[18]报道的引物信息。SSR扩增体系为20 μL, 含10× buffer 2 μL、10 mmol L-1 dNTP 1.6 μL、1.25 μmol L-1引物1 μL、500 U μL-1Taq DNA聚合酶0.15 μL、10 ng μL-1模板DNA 1 μL和ddH2O 14.25 μL。扩增程序为94℃预变性5 min, 然后按照94℃变性30 s, 50℃、55℃或60℃退火30 s, 72℃延伸1 min进行40个循环; 最后72℃延伸7 min。扩增产物经6%非变性聚丙烯酰胺凝胶电泳分离、银染。按照0、1统计SSR扩增带型, 建立分子标记数据库, 在相同迁移位置处有带记为l, 无带记为0, 形成0-1分子矩阵。1.4 产量相关性状关联分析
利用STRUCTURE V2.3.4软件分析群体遗传结构, 估计最佳群体组群数K值。K取值范围为2~10, 将MCMC (Monte Carlo Markov Chains)开始时的不作数迭代(Length of burn-in period)设为20 000次, 再将不作数迭代后的MCMC设为200 000次, 对每个K值进行5次独立的重复计算。依据似然值最大的原则选择最佳K值。应用TASSEL 3.0软件(http://www.maizegenetics.net/)混合线性模型(mixed linear model, MLM)[19]对产量相关表型鉴定数据和SSR分子标记数据进行关联分析, 显著水平设为P<0.05。以STRUCTURE V2.3.4计算得到的Q值和TASSEL 3.0软件计算得到的Kinship值作为关联分析的协变量[19]。2 结果与分析
2.1 骨干亲本繁6及其衍生品种产量相关性状表型特征分析
同时期比较发现, 繁6株高、小穗数、穗长、小穗粒数、穗粒重、千粒重和有效分蘖均高于四川主栽品种雅安早(表1)。繁6不同世代衍生品种各性状演变趋势无显著差异, 不同程度地继承了繁6多花多实等优良特性(表1)。繁6及其衍生系品种产量相关性状间存在显著或极显著相关(表2), 推测可能正是这些产量因子之间的协调发展成就了繁6作为我国最重要的小麦骨干亲本之一, 也是其作为骨干亲本在育种中被广泛应用的表型基础。Table 1
表1
表1繁6及其衍生后代品种产量相关性状比较
Table 1Comparison of yield related traits in Fan 6 and its derivatives
| 品种或世代 Variety or generation | 株高 PH (cm) | 穗长 SL (cm) | 小穗数 SLN | 小穗粒数 KNSL | 穗粒数 KNS | 穗粒重 KWS (g) | 千粒重 TKW (g) | 有效分蘖 ETN |
|---|---|---|---|---|---|---|---|---|
| 对照品种 Control variety | 110.61 | 15.51 | 25.00 | 4.6 | 87.76 | 1.78 | 48.88 | 7.0 |
| 繁6 Fan 6 | 90.10 | 10.27 | 24.90 | 4.7 | 72.29 | 3.03 | 39.85 | 6.2 |
| 繁6衍生后代 Derivated generations from Fan 6 | ||||||||
| 第1代 1st generation (n=7) | 87.46 | 11.16 | 22.79 | 4.3 | 66.57 | 2.95 | 39.85 | 6.1 |
| 第2代 2nd generation (n=12) | 91.73 | 12.38 | 22.95 | 3.8 | 66.86 | 2.65 | 45.20 | 5.6 |
| 第3代 3rd generation (n=10) | 86.67 | 12.81 | 22.63 | 4.1 | 67.73 | 2.53 | 44.91 | 4.0 |
| 第4代 4th generation (n=7) | 89.49 | 13.29 | 23.56 | 3.6 | 78.51 | 1.89 | 42.16 | 4.8 |
| 第5代 5th generation (n=3) | 82.21 | 9.89 | 21.43 | 4.2 | 70.86 | 1.95 | 42.35 | 6.2 |
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Table 2
表2
表2繁6及其衍生后代品种产量相关性状相关系数
Table 2Correlation coefficient between yield related traits in Fan 6 and its derivatives
| 性状 Trait | 株高 PH | 穗长 SL | 小穗数 SLN | 小穗粒数 KNSL | 有效分蘖 ETN | 穗粒数 KNS | 穗粒重 KWS | 千粒重 TKW |
|---|---|---|---|---|---|---|---|---|
| 株高PH | 0.12 | -0.02 | -0.16 | 0.29 | 0.04 | 0.26 | -0.18 | |
| 穗长SL | 0.28 | -0.02 | -0.05 | 0.24 | -0.17 | 0.35* | -0.11 | |
| 小穗数SLN | 0.14 | 0.27 | -0.45** | 0 | 0.44** | -0.12 | 0.05 | |
| 小穗粒数KNSL | 0.31 | 0.13 | 0.14 | 0.14 | 0.55** | -0.02 | -0.03 | |
| 有效分蘖ETN | 0.24 | -0.22 | -0.18 | 0.01 | 0.22 | -0.44** | 0.29 | |
| 穗粒数KNS | 0.47** | 0.14 | 0.33 | 0.86** | 0.07 | 0.76** | -0.70 | |
| 穗粒重KWS | 0.48** | 0.42* | 0.22 | 0.61** | 0.03 | 0.75** | 0.84** | |
| 千粒重TKW | 0.03 | 0.41* | -0.03 | -0.29 | 0.02 | -0.29 | 0.33* |
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2.2 控制小麦产量相关性状QTL区段SSR位点在繁6及其衍生后代小麦品种中的遗传特征
在417对SSR引物中, 172对(41.2%)在繁6及其衍生后代中表现扩增多态性, 共获得721个等位变异, 每个位点2~11个等位变异, 平均3.9个。在721个等位变异中有185个繁6特异等位变异, 其中136个传递至繁6不同衍生代中, 其遗传频率为7.7%~100.0% (表3), 绝大部分(118个, 占63.8%)的遗传频率高于50%。Xwmc134、Xgwm264b、Xwmc419、Xgwm154、Xwmc657、Xwmc737、Xgpw7812、Xbarc84、Xgwm219、Xbarc1096和Xcfa2257共11个SSR标记位点的遗传频率超过80%, 这说明在育种过程中, 人为定向连续选择可能是导致这些遗传位点得以保留并遗传下去的重要原因, 进而推测这些高频率位点可能与控制小麦产量相关性状的位点/基因/区段相关。Table 3
表3
表3繁6特异SSR等位位点在其衍生后代中的遗传传递
Table 3Transmission of specific alleles from Fan 6 to its derivated generations
| 繁6衍生世代 Fan 6-derived generation | 品种数 Number of varieties | 变异位点 Number of specific alleles | 传递频率Transmission frequency (%) | |
|---|---|---|---|---|
| 范围 Range | 平均Average | |||
| 第1代 1st generation | 7 | 51 | 8.3-91.7 | 49.2 |
| 第2代 2nd generation | 12 | 28 | 7.7-76.9 | 40.4 |
| 第3代 3rd generation | 10 | 25 | 14.3-100.0 | 44.6 |
| 第4代 4th generation | 7 | 17 | 14.3-71.4 | 42.9 |
| 第5代 5th generation | 3 | 15 | 15.7-84.9 | 45.4 |
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2.3 小麦产量相关性状-SSR标记关联分析
利用172个产量相关多态性SSR标记, 在繁6及其衍生后代中鉴定出21个显著相关标记, 其中9个与株高关联, 6个与千粒重关联, 4个与穗长关联, 3个与小穗数关联, 1个与小穗粒数关联, 1个与有效分蘖关联, 有的标记同时与多个性状关联。如Xbarc10与株高和穗长关联, 变异解释率分别为12.41%和14.25%; Xcfd14与小穗数和千粒重关联, 变异解释率分别为13.42%和10.21%。检测到4个繁6特异等位变异具有高遗传频率, 分别在Xbarc10、Xgwm526、Xbarc100和Xcfa2170位点, 依次与株高、穗长、小穗数和千粒重相关联(表4)。参考Somers等[20]整合的小麦SSR遗传图谱, 发现2个与农艺性状相关位点位于高频率遗传位点所形成的染色体区段内。其中, Xgwm526与株高和小穗数关联, 位于2A的Xgdm93.3-Xgwm526.2染色体区段; Xbarc100与千粒重关联, 位于5A的Xbarc100-Xgwm156.1染色体区段。Table 4
表4
表4产量相关性状显著关联的SSR位点
Table 4SSR loci significantly associated with yield-related traits in Fan 6 and its derivatives
| 性状 Trait | 标记 Marker | 染色体 Chromosome | P值 P-value | R2 (%) |
|---|---|---|---|---|
| 株高 Plant height | Xgwm614 | 2A | 0.0167 | 11.76 |
| Xcfd80 | 6A | 0.0220 | 8.83 | |
| Xwmc722 | 4D | 0.0255 | 7.51 | |
| Xcfd51 | 2D | 0.0525 | 5.55 | |
| Xbarc10 | 5A | 0.0068 | 12.41 | |
| Xwmc505 | 3A | 0.0123 | 9.82 | |
| Xcfa2170 | 1D | 0.0027 | 13.16 | |
| Xgwm526 | 2A | 0.0044 | 12.01 | |
| Xbarc96 | 5B | 0.0164 | 8.49 | |
| 穗长 Spike length | Xbarc61 | 1B | 0.0187 | 0.0946 |
| Xbarc10 | 2B/4B/5A/7B | 0.0158 | 0.1425 | |
| Xcfa2201 | 2B | 0.0260 | 0.0890 | |
| Xgpw363 | 1B | 0.0101 | 0.1095 | |
| 小穗数Spikelet number per spike | Xgwm415 | 5A | 0.0246 | 0.1462 |
| Xcfd14 | 7D | 0.0048 | 0.1342 | |
| Xgwm526 | 2A | 0.0368 | 0.0751 | |
| 小穗粒数 Kernal number per spikelet | Xbarc174 | 1B/2B/7A | 0.0390 | 0.1074 |
| 千粒重 Thousand-kernel weight | Xbarc100 | 5A | 0.0164 | 0.0821 |
| Xcfd14 | 7D | 0.0090 | 0.1021 | |
| Xcfd19 | 1D/5D/6D | 0.0282 | 0.0715 | |
| Xwmc285 | 4D | 0.0072 | 0.1375 | |
| Xwmc723 | 7B | 0.0132 | 0.0872 | |
| Xgwm333 | 7B | 0.0086 | 0.1337 | |
| 有效分蘖 Effective tiller number | Xbarc56 | 5A | 0.0024 | 0.1516 |
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3 讨论
在利用骨干亲本进行小麦育种的实践中, 育种家“操纵”着小麦品种后代变异方向, 高产、抗病和优质等农艺性状表型受到强烈选择, 使小麦骨干亲本衍生后代具有“安排”的进化方向, 进而特定优良基因或位点有明显稳定遗传[21]。例如, 司清林等[22]利用247对SSR引物对阿夫和8个阿夫子一代衍生品种(系)的亲本进行分析, 发现3个SSR位点Xwmc398、Xgwm400和Xgwm268在阿夫衍生品种(系)中明显稳定传递, 并被育种家持续选择。李小军等[7]通过对小麦骨干亲本欧柔及其23份衍生品种进行农艺性状调查和SSR扫描, 发现来自小麦骨干亲本欧柔的43个SSR特异等位变异位点在一代品种的传递频率高于理论比例0.38; 其中, 有41个特异等位变异位点在其衍生二代品种的传递频率高于理论比例0.18; 并发现来自欧柔特异21个等位变异位点被育种家持续选择, 推测这些特异位点在中国小麦品种改良中发挥了重要作用。陈国跃等[13]利用控制小麦条锈病成株抗性QTL区段的80个SSR标记对繁6及其后代衍生品种的其他亲本进行分子扫描, 证实繁6的条锈病成株抗性及其控制遗传位点在其衍生后代品种中得到定向选择, 并在西南麦区小麦条锈病抗性育种中发挥了重要作用。本研究发现骨干亲本繁6的产量相关性状能在其衍生后代品种中稳定遗传下来。产量相关性状在繁6和其衍生群体间存在显著相关性, 各个产量相关性状之间的协同表达也成为繁6及其衍生品种在四川乃至西南麦区具有种植优势的重要因素。繁6及其衍生群体的平均遗传贡献率为44.5%, 最低为7.7%, 最高为100.0%。在全基因组水平, 繁6对其第1至第5代衍生品种的平均贡献率分别为49.2%、40.4%、44.6%、42.9%和45.4% (表3), 远高于理论的标准值50%、25%、12.5%和6.25%, 繁6所携带某些特异位点在子代中存在高频率的遗传, 这与周8425B、胜利麦/燕大1817、碧蚂4号、欧柔等其他骨干亲本衍生群体的报道一致[5,7-8,23-25], 推测这些位点可能与农艺或胁迫表型相关联, 在育种过程中被强烈选择[26,27]。本研究利用性状-标记关联分析, 通过混合线性模型(MLM), 共鉴定出21个SSR标记分别与6个产量相关性状相关联。Jantasuriyaratdeng等[28]在3个环境下均检测到位于染色体7A上的2个控制小麦小穗数QTL区段。已报道小麦5A染色体上存在控制适应性和产量的基因和位点, 例如Vrn-A1[29,30]、穗形态基因Q[31,32], 以及株高和产量相关的QTL[33,34]。在本研究中, 与小穗相关性状(小穗数和小穗粒数)关联的SSR位点位于染色体2A、5A、7A和7D (表4), 与已报道的小穗相关性状定位区域一致, 表明这一染色体区段或标记位点在繁6及其衍生群体中, 对小穗相关性状控制起着重要的作用。在2A和7D上发现的关联标记Xcfd14和Xgwm526, 可能是控制小穗数的新位点。5A上Xbarc56位点控制小麦有效分蘖, 这与Li等[35]在永久性F2群体中发现的控制小麦有效分蘖QTL一致。株高是由穗长和节间长度等多个因素构成的复杂性状[36]。本研究鉴定的9个株高相关SSR位点中, 有2个分别定位于5A和5B, 与已报道的QTL_height_1B_1, QTL_ height_5A_1和QTL_height_5B_1一致[37]。
4 结论
小麦骨干亲本繁6产量相关性状在衍生后代小麦品种中能稳定遗传。检测出11个来自繁6的等位变异对衍生品种(系)的遗传频率大于80%, 推测这些等位变异位点及其所在染色体区域可能在育种过程中被强烈选择。鉴定出21个SSR标记与小麦产量相关性状显著相关, 其中具有高遗传频率的繁6特异SSR是Xbarc10、Xgwm526、Xbarc100和Xcfa2170, 可在用繁6做育种亲本时进行分子标记辅助选择。The authors have declared that no competing interests exist.
作者已声明无竞争性利益关系。
参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
| [1] | . |
| [2] | . International wheat breeding shows trend in four aspects based on the information presented at 7^th International Wheat Conference. Improvement of yield potential needed to be continued, and conservation agriculture is widely used to reduce input costs. M . International wheat breeding shows trend in four aspects based on the information presented at 7^th International Wheat Conference. Improvement of yield potential needed to be continued, and conservation agriculture is widely used to reduce input costs. M |
| [3] | |
| [4] | . <span id="ChDivSummary" name="ChDivSummary">骨干亲本形成的遗传基础研究已经成为作物优异种质分子评价的重要部分,对作物育种具有非常重要的实践意义。为此,就小麦骨干亲本的遗传多样性、重要基因组区段及有利基因发掘的研究进行了阐述,并介绍了以连锁不平衡研究为基础开始在植物系谱群体进行数量性状研究的几种策略。 </span> . <span id="ChDivSummary" name="ChDivSummary">骨干亲本形成的遗传基础研究已经成为作物优异种质分子评价的重要部分,对作物育种具有非常重要的实践意义。为此,就小麦骨干亲本的遗传多样性、重要基因组区段及有利基因发掘的研究进行了阐述,并介绍了以连锁不平衡研究为基础开始在植物系谱群体进行数量性状研究的几种策略。 </span> |
| [5] | . Founder parents have contributed significantly to the improvement of wheat. Beijing 8 has been used as a founder parent in developing many outstanding improved cultivars in China. The widely grown cultivars Beijing 8 and 6 additional derivatives both derived from the cross 'Bima 4 x Early Premium' in China, were characterised using seven morphological traits and 537 microsatellite markers. Phenotypic comparisons revealed that Beijing 8 was similar for certain characteristics to the widely grown cultivars Shijiazhuang 54 and Jinan 2, hinting that acceptable performance for yield components may be the basis for Beijing 8 serving as a founder parent. Simple sequence repeat analysis indicated that Bima 4 contributed more genome information to the derivatives than Early Premium. Fifty-nine unique simple sequence repeat alleles, present in Beijing 8 and absent in other cultivars, were observed. Nearly all loci were in close proximity to the positions of known genes conferring important traits. Furthermore, pedigree tracking found that the frequencies of alleles unique to Beijing 8 varied from 0 to 0.96 in its 51 descendants, suggesting that some of them underwent rigorous selection during breeding. |
| [6] | . Understanding the genetics underlying yield formation of wheat is important for increasing wheat yield potential in breeding programs. Nanda2419 was a widely used cultivar for wheat production and breeding in China. In this study, we evaluated yield components and a few yield-related traits of a recombinant inbred line (RIL) population created by crossing Nanda2419 with the indigenous cultivar Wangshuibai in three to four trials at different geographical locations. Negative and positive correlations were found among some of these evaluated traits. Five traits had over 50% trial-wide broad sense heritability. Using a framework marker map of the genome constructed with this population, quantitative trait loci (QTL) were identified for all traits, and epistatic loci were identified for seven of them. Our results confirmed some of the previously reported QTLs in wheat and identified several new ones, including QSn.nau-6D for effective tillers, QGn.nau-4B.2 for kernel number, QGw.nau-4D for kernel weight, QPh.nau-4B.2 and QPh.nau-4A for plant height, and QFlw.nau-5A.1 for flag leaf width. In the investigated population, Nanda2419 contributed all QTLs associated with higher kernel weight, higher leaf chlorophyll content, and a major QTL associated with wider flag leaf. Seven chromosome regions were related to more than one trait. Four QTL clusters contributed positively to breeding goal-based trait improvement through the Nanda2419 alleles and were detected in trials set in different ecological regions. The findings of this study are relevant to the molecular improvement of wheat yield and to the goal of screening cultivars for better breeding parents. |
| [7] | . 为探讨小麦骨干亲本碧蚂4号的遗传构成及其特异位点在衍生后代中的传递特点,利用覆盖小麦全基因组的1239个SSR、EST-SSR和STS标记对碧蚂4号子一代衍生品种（系）的4个亲本进行标记筛选,获得33个特异标记可用于76份碧蚂4号衍生材料的分析。在子一代和子二代材料中,除标记Xgwm577外的32个标记均能扩增出碧蚂4号特异带,且分别有8个和10个标记位点的传递频率大于50%;在子三代和子四代材料中能扩增出碧蚂4号特异带的标记分别有29个和20个,传递频率大于50%的标记位点分别有8个和4个;Xgwm261、Xedm80、SWES222和CFE223在4个世代中的传递频率都保持在50%以上;有18个标记位点对衍生品种（系）的遗传贡献率大于25%;推测这些基因组位点及其附近的染色体区域可能是被育种家强烈选择的部分,碧蚂4号含有一些特殊的与重要农艺性状相关的基因组位点/区段,可能是其成为骨干亲本的遗传基础。 . 为探讨小麦骨干亲本碧蚂4号的遗传构成及其特异位点在衍生后代中的传递特点,利用覆盖小麦全基因组的1239个SSR、EST-SSR和STS标记对碧蚂4号子一代衍生品种（系）的4个亲本进行标记筛选,获得33个特异标记可用于76份碧蚂4号衍生材料的分析。在子一代和子二代材料中,除标记Xgwm577外的32个标记均能扩增出碧蚂4号特异带,且分别有8个和10个标记位点的传递频率大于50%;在子三代和子四代材料中能扩增出碧蚂4号特异带的标记分别有29个和20个,传递频率大于50%的标记位点分别有8个和4个;Xgwm261、Xedm80、SWES222和CFE223在4个世代中的传递频率都保持在50%以上;有18个标记位点对衍生品种（系）的遗传贡献率大于25%;推测这些基因组位点及其附近的染色体区域可能是被育种家强烈选择的部分,碧蚂4号含有一些特殊的与重要农艺性状相关的基因组位点/区段,可能是其成为骨干亲本的遗传基础。 |
| [8] | . . |
| [9] | . 对在我国小麦育种中发挥过重要作用的22个骨干亲本、在生产上曾发挥过巨大增产效益的45个品种,以及1 8个优质面包品种的高分子量谷蛋白亚基组成进行了比较系统的分析.结果表明,骨干亲本在Glu-A1位点有两种等位变异类型"0"和"1";Glu-B1有"7+8"、"7+9"、"14+15"、"17+18"、"6+8"5个等位变异类型,但主要以"7+8"和"7+9"为主;Glu-D1有"2+12"、"2+10"、"5+10"、"4+10"、"4+12"、"2+11"6个等位变异类型,以"2+12"和"2+11"为主要类型.在骨干亲本中仅有一个"早洋麦"(Early Prermium)携带"5+10";一个St2422/464携带"14+15".此外,两个比较重要的材料"玛拉"(Mara)和"阿龙爪"(Alondra)携带"5+10".在大面积推广品种中,只有"扬麦5号"为"5+10"携带者;"小偃6号"和"豫麦7号"携带"14+15";"阿夫"、"农大139"、"郑州683"、"繁6"等4个品种携带"1 7+18".我国第一批优质小麦品种主要有两个类群,即"5+10"和"14+15",前者以"中作813-1"及其变异后代选系为代表,后者以"小偃6号"和其衍生品种为主.此外,还查明"17+18",来源于意大利品种"阿夫"(Funo,或选系).上述结果基本反映了50年来我国小麦品种的谷蛋白组成的变化情况.研究还表明,出自同一组合的对料在谷蛋白亚基组成上可能会存在很大差异,在品质育种中不应简单地等同对待,而要作详细的生化和加工品质分析. . 对在我国小麦育种中发挥过重要作用的22个骨干亲本、在生产上曾发挥过巨大增产效益的45个品种,以及1 8个优质面包品种的高分子量谷蛋白亚基组成进行了比较系统的分析.结果表明,骨干亲本在Glu-A1位点有两种等位变异类型"0"和"1";Glu-B1有"7+8"、"7+9"、"14+15"、"17+18"、"6+8"5个等位变异类型,但主要以"7+8"和"7+9"为主;Glu-D1有"2+12"、"2+10"、"5+10"、"4+10"、"4+12"、"2+11"6个等位变异类型,以"2+12"和"2+11"为主要类型.在骨干亲本中仅有一个"早洋麦"(Early Prermium)携带"5+10";一个St2422/464携带"14+15".此外,两个比较重要的材料"玛拉"(Mara)和"阿龙爪"(Alondra)携带"5+10".在大面积推广品种中,只有"扬麦5号"为"5+10"携带者;"小偃6号"和"豫麦7号"携带"14+15";"阿夫"、"农大139"、"郑州683"、"繁6"等4个品种携带"1 7+18".我国第一批优质小麦品种主要有两个类群,即"5+10"和"14+15",前者以"中作813-1"及其变异后代选系为代表,后者以"小偃6号"和其衍生品种为主.此外,还查明"17+18",来源于意大利品种"阿夫"(Funo,或选系).上述结果基本反映了50年来我国小麦品种的谷蛋白组成的变化情况.研究还表明,出自同一组合的对料在谷蛋白亚基组成上可能会存在很大差异,在品质育种中不应简单地等同对待,而要作详细的生化和加工品质分析. |
| [10] | . . |
| [11] | . . |
| [12] | . . |
| [13] | . . |
| [14] | . A β-amylase cDNA clone isolated from barley has been used to locate β-amylase encoding sequences on wheat, rye, and Aegilops umbellulata chromosomes by hybridisation to restriction endonuclease digested DNA obtained from wheat aneuploid and wheat-alien addition lines. Structural genes were identified on homoeologous group 4 and 5 chromosomes, confirming the results of isozyme studies. In addition, a further set of structural genes was found on homoeologous group 2 chromosomes. It is proposed that there are two homoeoallelic series, β- Amy-1 on group 4 or 5 chromosomes, and β- Amy-2 on group 2 chromosomes. Evidence is presented that each locus contains one or two β-amylase structural genes, and it is suggested that the large number of isozymes seen upon IEF are due to post-translational modifications. |
| [15] | |
| [16] | . 小麦（Triticum aestivum L.）品质相关性状是由多个基因控制的数量性状,发掘控制小麦品质相关性状的真实主效数量性状位点（quantitative trait loci,QTL）是利用分子手段进行品质改良的有效途径.本研究收集了已发表的控制小麦品质相关性状的585个QTL定位数据,利用元分析技术获得264个控制小麦品质相关性状一致性QTL（meta quantitative trait loci,MQTL）,其中34个与吸水率（water absorption,ABS）相关,26个与面粉蛋白质含量（flour protein content,FPC）相关,84个与籽粒蛋白质含量（grain protein content,GPC）相关,52个与籽粒硬度（kernel hardness,KH）相关,39个与沉降值（sedimentation value,SV）相关,29个与湿面筋含量（wet gluten content,WGC）相关.基于BioMercator软件及标记映射技术,将来自不同遗传作图群体的小麦品质相关性状QTL整合到一张参考图谱上,建立控制小麦品质相关性状的QTL一致性图谱,进一步发现控制小麦品质相关性状的MQTL区段在染色体上呈非均匀性分布,且部分性状QTL集中成簇.控制小麦品质相关性状的真实QTL区段（或位点）的发现及其整合图谱的构建,为小麦品质相关性状基因的发掘、候选基因的确定以及分子标记辅助选育提供了参考资料. . 小麦（Triticum aestivum L.）品质相关性状是由多个基因控制的数量性状,发掘控制小麦品质相关性状的真实主效数量性状位点（quantitative trait loci,QTL）是利用分子手段进行品质改良的有效途径.本研究收集了已发表的控制小麦品质相关性状的585个QTL定位数据,利用元分析技术获得264个控制小麦品质相关性状一致性QTL（meta quantitative trait loci,MQTL）,其中34个与吸水率（water absorption,ABS）相关,26个与面粉蛋白质含量（flour protein content,FPC）相关,84个与籽粒蛋白质含量（grain protein content,GPC）相关,52个与籽粒硬度（kernel hardness,KH）相关,39个与沉降值（sedimentation value,SV）相关,29个与湿面筋含量（wet gluten content,WGC）相关.基于BioMercator软件及标记映射技术,将来自不同遗传作图群体的小麦品质相关性状QTL整合到一张参考图谱上,建立控制小麦品质相关性状的QTL一致性图谱,进一步发现控制小麦品质相关性状的MQTL区段在染色体上呈非均匀性分布,且部分性状QTL集中成簇.控制小麦品质相关性状的真实QTL区段（或位点）的发现及其整合图谱的构建,为小麦品质相关性状基因的发掘、候选基因的确定以及分子标记辅助选育提供了参考资料. |
| [17] | . Hexaploid bread wheat (Triticum aestivum L. em. Thell) is one of the world's most important crop plants and displays a very low level of intraspecific polymorphism. We report the development of highly polymorphic microsatellite markers using procedures optimized for the large wheat genome. The isolation of microsatellite-containing clones from hypomethylated regions of the wheat genome increased the proportion of useful markers almost twofold. The majority (80%) of primer sets developed are genome-specific and detect only a single locus in one of the three genomes of bread wheat (A, B, or D). Only 20% of the markers detect more than one locus. A total of 279 loci amplified by 230 primer sets were placed onto a genetic framework map composed of RFLPs previously mapped in the reference population of the International Triticeae Mapping Initiative (ITMI) Opata 85 x W7984. Sixty-five microsatellites were mapped at a LOD >2.5, and 214 microsatellites were assigned to the most likely intervals. Ninety-three loci were mapped to the A genome, 115 to the B genome, and 71 to the D genome. The markers are randomly distributed along the linkage map, with clustering in several centromeric regions. |
| [18] | . Abstract The potential of Aegilops tauschii, the diploid progenitor of the D genome of wheat, as a source of microsatellite markers for hexaploid bread wheat was investigated. By screening lambda phage and plasmid libraries of Ae. tauschii genomic DNA, dinucleotide microsatellites containing GA and GT motifs were isolated and a total of 65 functional microsatellite markers were developed. All primer pairs that were functional in Ae. tauschii amplified well in hexaploid wheat. Fifty-five loci amplified by 48 primer sets were placed onto a genetic framework map of the reference population of the International Triticeae Mapping Initiative (ITMI) 'Opata 85' x 'W7984'. The majority of microsatellite markers could be assigned to the chromosomes of the D genome of wheat. The distribution of the markers along the chromosomes is random. Chromosomal location of 22 loci nonpolymorphic in the reference population was determined using nullitetrasomic lines of Triticum aestivum 'Chinese Spring'. The results of this study demonstrate the value of microsatellite markers isolated from Ae. tauschii for the study of bread wheat. The microsatellite markers developed improve the existing wheat microsatellite map and can be used in a wide range of genetic studies and breeding programs. |
| [19] | . Abstract As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach to two samples: a family-based sample of 14 human families, for quantitative gene expression dissection, and a sample of 277 diverse maize inbred lines with complex familial relationships and population structure, for quantitative trait dissection. Our method demonstrates improved control of both type I and type II error rates over other methods. As this new method crosses the boundary between family-based and structured association samples, it provides a powerful complement to currently available methods for association mapping. |
| [20] | . A microsatellite consensus map was constructed by joining four independent genetic maps of bread wheat. Three of the maps were F-1-derived, doubled- haploid line populations and the fourth population was 'Synthetic' x 'Opata', an F-6-derived, recombinant-inbred line population. Microsatellite markers from different research groups including the Wheat Microsatellite Consortium, GWM, GDM, CFA, CFD, and BARC were used in the mapping. A sufficient number of common loci between genetic maps, ranging from 52 to 232 loci, were mapped on different populations to facilitate joining the maps. Four genetic maps were developed using MapMaker V3.0 and JoinMap V3.0. The software CMap, a comparative map viewer, was used to align the four maps and identify potential errors based on consensus. JoinMap V3.0 was used to calculate marker order and recombination distances based on the consensus of the four maps. A total of 1,235 microsatellite loci were mapped, covering 2,569 cM, giving an average interval distance of 2.2 cM. This consensus map represents the highest-density public microsatellite map of wheat and is accompanied by an allele database showing the parent allele sizes for every marker mapped. This enables users to predict allele sizes in new breeding populations and develop molecular breeding and genomics strategies. |
| [21] | . Studies were conducted to (i) identify molecular probes that have a high probability of detecting polymorphisms among soybean [Glycine max (L.) Merr.] genotypes, (ii) determine the potential for analyzing genome structure using a molecular genetic map, and (iii) demonstrate the feasibility of a molecular pedigree analysis using mapped RFLP markers. Genomic DNA of 51 genotypes representing U.S. midwestern soybean germplasm was digested with the restriction enzymes HindIII, Dral, EcoRI, EcoRV, and TaqI. A random sample of 32 probes detected polymorphisms between paired comparisons of the 51 genotypes with a frequency from 0 to 72%. On average, no enzyme was strikingly better than any other for detecting polymorphisms. Homeologous chromosomal segments were detected, although they were clearly only remnants with recombination distance disparities and many rearrangements. The soybean genome, if indeed an ancient tetraploid, appears to be highly shuffled or diploidized. RFLP data were compared with the pedigrees of the cultivars Harosoy, Corsoy, Williams, and Clark, using from 58 to 105 mapped markers. Markers on Linkage Groups A and E were analyzed in detail to determine the map positions of polymorphisms and to identify chromosomal segments involved in cultivar development. The polymorphism percentage as detected by molecular markers coincided with genetic distance expectations based on pedigrees. These studies have demonstrated that probe-enzyme combinations can be identified that will be applicable to discerning differences among a broad range of genotypes. Additionally, it has been demonstrated that a detailed RFLP map can be used to increase our understanding of genome evolution and genome structure and, when combined with pedigrees, can be used to determine the ancestral sources of markers in a given cultivar's genome. |
| [22] | . . |
| [23] | . Understanding the genetics underlying yield formation of wheat is important for increasing wheat yield potential in breeding programs. Nanda2419 was a widely used cultivar for wheat production and breeding in China. In this study, we evaluated yield components and a few yield-related traits of a recombinant inbred line (RIL) population created by crossing Nanda2419 with the indigenous cultivar Wangshuibai in three to four trials at different geographical locations. Negative and positive correlations were found among some of these evaluated traits. Five traits had over 50% trial-wide broad sense heritability. Using a framework marker map of the genome constructed with this population, quantitative trait loci (QTL) were identified for all traits, and epistatic loci were identified for seven of them. Our results confirmed some of the previously reported QTLs in wheat and identified several new ones, including QSn.nau-6D for effective tillers, QGn.nau-4B.2 for kernel number, QGw.nau-4D for kernel weight, QPh.nau-4B.2 and QPh.nau-4A for plant height, and QFlw.nau-5A.1 for flag leaf width. In the investigated population, Nanda2419 contributed all QTLs associated with higher kernel weight, higher leaf chlorophyll content, and a major QTL associated with wider flag leaf. Seven chromosome regions were related to more than one trait. Four QTL clusters contributed positively to breeding goal-based trait improvement through the Nanda2419 alleles and were detected in trials set in different ecological regions. The findings of this study are relevant to the molecular improvement of wheat yield and to the goal of screening cultivars for better breeding parents. |
| [24] | . . |
| [25] | . . |
| [26] | . Abstract The external appearance of flowering plants is determined to a large extent by the forms of flower-bearing branch systems, known as inflorescences, and their position in the overall structure of the plant. Branches and branching patterns are produced by tissues called shoot apical meristems. Thus, inflorescence architecture reflects meristem number, arrangement and activity, and the duration of meristem activity correlates with branch length. The inflorescences of maize, unlike those of related grasses such as rice and sorghum, predominantly lack long branches, giving rise to the tassel and familiar corncob. Here we report the isolation of the maize ramosa1 gene and show that it controls inflorescence architecture. Through its expression in a boundary domain near the nascent meristem base, ramosa1 imposes short branch identity as branch meristems are initiated. A second gene, ramosa2, acts through ramosa1 by regulating ramosa1 gene expression levels. ramosa1 encodes a transcription factor that appears to be absent in rice, is heterochronically expressed in sorghum, and may have played an important role in maize domestication and grass evolution. |
| [27] | . Association mapping is a method for detection of gene effects based on linkage disequilibrium (LD) that complements QTL analysis in the development of tools for molecular plant breeding. In this study, association mapping was performed on a selected sample of 95 cultivars of soft winter wheat. Population structure was estimated on the basis of 36 unlinked simple-sequence repeat (SSR) markers. The extent of LD was estimated on chromosomes 2D and part of 5A, relative to the LD observed among unlinked markers. Consistent LD on chromosome 2D was <1 cM, whereas in the centromeric region of 5A, LD extended for 5 cM. Association of 62 SSR loci on chromosomes 2D, 5A, and 5B with kernel morphology and milling quality was analyzed through a mixed-effects model, where subpopulation was considered as a random factor and the marker tested was considered as a fixed factor. Permutations were used to adjust the threshold of significance for multiple testing within chromosomes. In agreement with previous QTL analysis, significant markers for kernel size were detected on the three chromosomes tested, and alleles potentially useful for selection were identified. Our results demonstrated that association mapping could complement and enhance previous QTL information for marker-assisted selection. |
| [28] | . Recombinant inbred lines of the International Triticeae Mapping Initiative (ITMI) mapping population were used to localize genetic loci that affect traits related to the free-threshing habit (percent threshability, glume tenacity, and spike fragility) and to spike morphology (spike length, spikelet number, and spike compactness) of wheat ( Triticum aestivum L.). The ITMI population was planted in three environments during 1999 and 2000, and phenotypic and genotypic data were used for composite interval mapping. Two quantitative trait loci (QTL) that consistently affected threshability-associated traits were localized on chromosomes 2D and 5A. Coincident QTL on the short arm of 2D explained 44% of the variation in threshability, 17% of the variation in glume tenacity, and 42% of the variation in rachis fragility. QTL on chromosomes 2D probably represent the effect of Tg, a gene for tenacious glumes. Coincident QTL on the long arm of 5A explained 21% and 10% of the variation in glume tenacity and rachis fragility, respectively. QTL on 5A are believed to represent the effect of Q. Overall, free-threshing-related characteristics were predominantly affected by Tg and to a lesser extent by Q. Other QTL that were significantly associated with threshability-related traits in at least one environment were localized on chromosomes 2A, 2B, 6A, 6D, and 7B. Four QTL on chromosomes 1B, 4A, 6A, and 7A consistently affected spike characteristics. Coincident QTL on the short arm of chromosome 1B explained 18% and 7% of the variation in spike length and spike compactness, respectively. QTL on the long arm of 4A explained 11%, 14%, and 12% of the variation in spike length, spike compactness, and spikelet number, respectively. A QTL on the short arm of 6A explained 27% of the phenotypic variance for spike compactness, while a QTL on the long arm of 7A explained 18% of the variation in spikelet number. QTL on chromosomes 1B and 6A appear to affect spike dimensions by modulating rachis internode length, while QTL on chromosomes 4A and 7A do so by affecting the formation of spikelets. Other QTL that were significantly associated with spike morphology-related traits, in at least one environment, were localized on chromosomes 2B, 3A, 3D, 4D, and 5A. |
| [29] | . |
| [30] | . |
| [31] | . |
| [32] | . The Q gene encodes an AP2-like transcription factor that played an important role in domestication of polyploid wheat. The chromosome 5A Q alleles (5AQ and 5Aq) have been well studied, but much less is known about the q alleles on wheat homoeologous chromosomes 5B (5Bq) and 5D (5Dq). We investigated the organization, evolution, and function of the Q/q homoeoalleles in hexaploid wheat (Triticum aestivum L.). Q/q gene sequences are highly conserved within and among the A, B, and D genomes of hexaploid wheat, the A and B genomes of tetraploid wheat, and the A, S, and D genomes of the diploid progenitors, but the intergenic regions of the Q/q locus are highly divergent among homoeologous genomes. Duplication of the q gene 5.8 Mya was likely followed by selective loss of one of the copies from the A genome progenitor and the other copy from the B, D, and S genomes. A recent V(329)-to-I mutation in the A lineage is correlated with the Q phenotype. The 5Bq homoeoalleles became a pseudogene after allotetraploidization. Expression analysis indicated that the homoeoalleles are coregulated in a complex manner. Combined phenotypic and expression analysis indicated that, whereas 5AQ plays a major role in conferring domestication-related traits, 5Dq contributes directly and 5Bq indirectly to suppression of the speltoid phenotype. The evolution of the Q/q loci in polyploid wheat resulted in the hyperfunctionalization of 5AQ, pseudogenization of 5Bq, and subfunctionalization of 5Dq, all contributing to the domestication traits. |
| [33] | . Chromosome 5A of wheat carries major gene loci for agronomic traits including the vernalization requirement (Vrn-A1) and ear morphology (Q). To determine whether the genetic variation for ear emergence time and plant height is attributable to either of these major genes as pleiotropic effects or independent QTL, we combined a RFLP map constructed from 120 recombinant substitution lines derived from a cross between 'Chinese Spring' (Cappelle-Desprez 5A) and CS(Triticum spelta 5A) with data collected from field trials over 3 years. For ear emergence time the main effects on flowering time were by Vrn-A1 and QEet.ocs5A.1, the latter a QTL in the 28.6-cM Xedo584/Q interval linked to Q by less than 10 cM. The CS(T. spelta 5A) allele at QEet.ocs-5A.1 contributed to an earlier ear emergence time by 2.7- 6.0 days, which was approximately equal to the effects of Vrn-A1. For plant height, three QTLs were identified on the long arm and linked in repulsion. The CS(T. spelta 5A) allele at Vrn-A1 or closely linked to Xfba068 contributed to a height reduction of 3.5 6.1 cm, whereas both the Q allele and Qt.ocs-5A.1 allele within the Xcdo1088/Xbcd9 interval from CS(Cappelle-Desprez 5A) produced a shorter plant. When plant height was partitioned into culm length and car length, the Vrn-A1 allele and CS(Cappelle-Desprez 5A) allele at QCl.ocs-5.4.1 within the Xcd1088/Xbcd9 interval were found to contribute to a shorter culm. CS(T. spelta 5A) allele at q was a major determinant of a long ear, together with minor effects at QEl.ocs-5A.1 within the Xcdo1088/Xbcd9 interval. |
| [34] | . Chromosome 5A of wheat is known to carry a number of genes affecting adaptability and productivity. To localize quantitative trait loci (QTLs) controlling grain yield and its components, an RFLP map was constructed from 118 single-chromosome recombinant lines derived from the F 1 between Chinese Spring (Cappelle-Desprez 5A) and Chinese Spring ( Triticum spelta 5A). The map was combined with the field-trial data scored over 3 years. A total of five regions in chromosome 5A contributed effects on yield traits. Increases in grain yield, 50-grain weight and spikelet number/ear were determined by complementary QTL alleles from both parents. The effects associated with the vernalization requirement gene Vrn-A1 or a closely linked QTL were significant only in the favorable growing season where the later-flowering vrn-A1 allele from Cappelle-Desprez 5A produced a higher tiller number/plant and spikelet number/ear. The effects of the ear morphology gene q or closely linked QTL(s) were detected for grain yield and ear grain weight. Three other QTLs with minor effects were dispersed along chromosome 5A. These QTLs had large interactions with years due to changes in the magnitude of the significant response. The alleles from T. spelta, however, conferred a higher yield performance. |
| [35] | . |
| [36] | . Plant height (PH) in wheat is a complex trait; its components include spike length (SL) and internode lengths. To precisely analyze the factors affecting PH, two F 8:9 recombinant inbred line (RIL) populations comprising 485 and 229 lines were generated. Crosses were performed between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY). Possible genetic relationships between PH and PH components (PHC) were evaluated at the quantitative trait locus (QTL) level. PH and PHC (including SL and internode lengths from the first to the fourth counted from the top, abbreviated as FIITL, SITL, TITL, and FOITL, respectively) were measured in four environments. Individual and the pooled values from four trials were used in the present analysis. A QTL for PH was mapped using data on PH and on PH conditioned by PHC using IciMapping V2.2. All 21 chromosomes in wheat were shown to harbor factors affecting PH in two populations, by both conditional and unconditional QTL mapping methods. At least 11 pairwise congruent QTL were identified in the two populations. In total, ten unconditional QTL and five conditional QTL that could be detected in the conditional analysis only have been verified in no less than three trials in WJ and WY. In addition, three QTL on the short arms of chromosomes 4B, 4D, and 7B were mapped to positions similar to those of the semi-dwarfing genes Rht - B1 , Rht - D1 and Rht13 , respectively. Conditional QTL mapping analysis in WJ and WY proved that, at the QTL level, SL contributed the least to PH, followed by FIITL; TITL had the strongest influence on PH, followed by SITL and FOITL. The results above indicated that the conditional QTL mapping method can be used to evaluate possible genetic relationships between PH and PHC, and it can efficiently and precisely reveal counteracting QTL, which will enhance the understanding of the genetic basis of PH in wheat. The combination of two related populations with a large/moderate population size made the results authentic and accurate. |
| [37] | . Abstract- and a potentially new allele of . The description of these effects offers new opportunities for the manipulation of crop height, biomass and yield in wheat breeding programmes. |
