软质小麦溶剂保持力关联分析

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张勇, 张晓, 郭杰, 高德荣, 张伯桥. 软质小麦溶剂保持力关联分析. 41(2): 251-258
ZHANG Yong, ZHANG Xiao, GUO Jie, GAO De-Rong, ZHANG Bo-Qiao. Association Analysis of Solvent Retention Capacity in Soft Wheat. Acta Agronomica Sinica, 41(2): 251-258 复制到剪切板

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作物学报编辑部

软质小麦溶剂保持力关联分析

张勇, 张晓, 郭杰, 高德荣, 张伯桥^*

江苏里下河地区农业科学研究所 / 农业部长江中下游小麦生物学与遗传育种重点实验室, 江苏扬州225007

^*通讯作者(Corresponding author): 张伯桥, E-mail: zbq@wheat.org.cn, Tel: 0514-87340868

第一作者联系方式: E-mail: zy@wheat.org.cn

收稿日期:2014-09-30

基金:本研究由江苏省自然科学基金项目(BK2011429), 国家高技术研究发展计划(863计划)项目(2012AA101105), 江苏省“333”工程项目(BRA2013126)和江苏省“六大人才高峰”计划(NY-049)资助;

摘要

溶剂保持力(SRC)是软质小麦鉴定评价的重要指标。为获得与SRC关联的分子标记, 提高育种效率, 对不同硬度类型的176份品种的乳酸SRC、碳酸钠SRC、蔗糖SRC和水SRC进行SSR标记检测, 并结合其在江苏里下河地区连续3个生长季的4种SRC表型数据, 利用MLM模型进行了关联分析。以236对SSR引物共检测出1340个等位变异, 平均每个位点5.5个等位变异, 平均PIC值为0.4663。共检测到28个关联位点( P< 0.005), 单个位点可解释3.19%~21.84%的表型变异; 与乳酸SRC、水SRC、蔗糖SRC和碳酸钠SRC相关联的位点分别为13、7、6和2个; 与水SRC关联的gwm642-1D在3年中均被检测到。在这些关联位点上发现有利等位变异, 其中降低水SRC的等位变异有gwm642-A186、gwm642-A188和gwm337-A178, 降低蔗糖SRC的等位变异有gwm337-A178和gwm337-A186, 降低碳酸钠SRC的等位变异有cfa2257-A129等。这些结果为利用分子标记进行SRC辅助选择提供了重要信息。

关键词: 小麦; 溶剂保持力; 分子标记; 关联分析

Association Analysis of Solvent Retention Capacity in Soft Wheat

ZHANG Yong, ZHANG Xiao, GUO Jie, GAO De-Rong, ZHANG Bo-Qiao^*

Lixiahe Region Institute of Agricultural Sciences of Jiangsu Province / Key Laboratory of Biology and Genetic Improvement in Middle and Lower Yangtze Valley, Ministry of Agriculture, Yangzhou 225007, China

Abstract

Solvent retention capacity (SRC) is an important index for identification and evaluation of soft wheat varieties. This study aimed at identifying SRC associated markers for marker-assisted selection. One hundred and seventy-six wheat varieties (lines) in different hardness types were screened with 236 pairs of SSR primers and their SRC values of lactic acid, water, sucrose, and sodium carbonate were evaluated in three growing seasons in Lixiahe, Jiangsu Province. The association analysis was carried out using the mixed-linear model (MLM). A total of 1340 fragments were amplified on the 236 SSR loci with an average of 5.5 alleles per locus. The average polymorphism information content was 0.4663. Twenty-eight loci were identified to be associated with lactic acid SRC (13), water SRC (7), sucrose SRC (6), and sodium carbonate SRC (2) at the significant level of P < 0.005, and a single locus explained 3.19%-21.84% of phenotypic variation. Marker gwm642 associated with WSRC was detected in three years. Some favorable alleles associated with SRCs were found, such as gwm642-A186, gwm642-A188, and gwm337-A178 for reducing water SRC, gwm337-A178 and gwm337-A186 for reducing sucrose SRC, and cfa2257-A129 for reducing sodium carbonate SRC. These results are informative for marker-assisted selection on SRC properties in wheat.

Keyword: Wheat; Solvent retention capacity (SRC); Molecular marker; Association analysis

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小麦是重要的粮食作物, 目前年种植面积约2333万公顷, 年均总产量超过1亿吨。随着生活水平的提高, 小麦生产和育种也从追求产量转向优质高产协调发展, 从20世纪80年代中期开始, 我国就已开展小麦品质育种研究, 但当时大多数育种单位都强调强筋小麦而忽视弱筋小麦, 在弱筋小麦遗传特性、种质创新、品种选育以及快速鉴定方法等方面均缺乏研究^{[1, 2]}。自2001年我国小麦品质区划^[3]制定和发布后, 弱筋小麦开始受到重视, 宁麦9号、扬麦13和宁麦13等弱筋品种相继育成和大面积推广, 促进了我国弱筋小麦生产的发展, 但现有弱筋品种仍然存在品质性状年度间和地点间波动较大等问题, 弱筋品质总体水平尚待进一步提高^{[4, 5]}。

溶剂保持力(solvent retention capacity, SRC)是指以含水量14%的面粉为基准, 经过离心后, 面粉所保持的溶剂质量占面粉干重的百分比, 该指标主要用于软质小麦的品质评价, 1999年通过AACC认定(AACC 56-11), 已成为美国评价软麦品质的主导方法^{[6, 7, 8]}。检测使用的溶剂有5%乳酸溶液、5%碳酸钠溶液、50%蔗糖溶液和蒸馏水4种, 其中乳酸SRC与麦谷蛋白特性相关, 碳酸钠SRC与破损淀粉数量相关, 蔗糖SRC与戊聚糖特性相关, 而水SRC受面粉所有成分的影响, 反映了面粉的综合特性^[8]。SRC主要受基因型控制^{[9, 10, 11, 12, 13]}。大多数研究表明, 上述4种SRC值与饼干直径呈极显著负相关^{[7, 13, 14, 15]}, 可以利用SRC值对面粉的饼干品质特性进行评价。饼干为含水量低的烘焙食品, 要求面粉具有较低的吸水率、淀粉破损率和戊聚糖含量, 不同SRC值为评价饼干品质提供了更多的面粉品质特性信息^{[14, 16]}。

关联分析是利用自然群体中的连锁不平衡, 鉴定目的性状与遗传标记或者候选基因之间关系, 从而挖掘或定位基因的分析方法^[17]。2001年Thornsberry成功地将该方法应用于玉米开花期变异的研究^[18]。由于关联分析研究对象为自然品种群体, 可利用材料相对广泛, 是解析复杂性状、鉴定目标性状优异等位基因的有效方法^{[19, 20]}, 迄今为止, 在玉米、水稻、小麦等作物中已有较多应用实例^{[21, 22, 23, 24]}。

小麦品质育种过程中, 往往需对种子检测后再进行选择, 无法对育种分离世代材料进行田间直接筛选, 而且在回交或滚动回交育种过程中必须根据籽粒测定结果进行选择后再于下一季进行配组, 严重影响育种进度。2001年Campbell等^[25]采用软白麦NY18× 硬白麦CC的78个重组自交系对碱水保持力进行了QTL作图, 2008年Smith和Souza等^[26]曾在ASA-CSSA-SSSA年会中介绍了利用美国品种对溶剂保持力关联分析的结果, 目前, 还没有利用自然群体对4种SRC进行关联定位的报道。本研究在江苏扬州连续3个生长季种植176份小麦品种(系), 通过分子标记检测和表型分析, 筛选与SRC相关的分子标记, 为品质育种辅助选择提供参考信息。

1 材料与方法

1.1 试验材料

176份不同硬度值类型的小麦品种(系)(见附表)均由江苏里下河地区农业科学研究所种质库收集提供。于2008— 2009、2009— 2010和2010— 2011年度, 连续3个生长季在江苏里下河地区农科所试验基地(江苏扬州)种植, 田间采用随机区组设计, 3次重复, 每小区4行, 每行40粒。行长1.33 m, 行距0.23 m。

1.2 溶剂保持力测定方法

收获后将籽粒样品磨粉, 参照AACC 56-11方法^{[6, 7]}, 测定5%乳酸SRC、5%碳酸钠SRC、50%蔗糖SRC和水SRC, 标准粉样品用量改为1 g ^{[27, 28]}。

1.3 分子标记检测

选用236个SSR标记检测供试材料, 其中106个为荧光SSR标记, 引物信息从http://www.GrainGenes. org/获得。这些标记覆盖小麦全基因组不同染色体, 每条染色体有6~17个标记, 平均11.2个, 其中2A、5B和5D上有17个, 1A、2B、3B和3D上有14个, 1D上有13个, 2D上有12个, 1B上有11个, 5A、6A、4B和7B上有10个, 3A、7A和7D上有9个, 4A和4D上有7个, 6B和6D上有6个。

取苗期单株叶片, 采用改良CTAB法提取小麦基因组DNA^[29]。PCR扩增程序为94℃预变性5 min; 94℃变性45 s, 65℃退火45 s, 72℃延伸55 s, 2个循环; 此后每2个循环退火温度下降2℃, 直至55℃; 保持55℃退火温度扩增25个循环; 最后72℃延伸10 min, 4℃保存。采用6%聚丙烯酰胺凝胶电泳分离普通SSR引物PCR扩增产物并经银染法检测读取数据, 采用DNA测序仪ABI3730分析荧光SSR引物PCR扩增产物, 通过GeneMapper3.0读取扩增条带。

1.4 数据分析

利用SPSS16.0分析SRC数据方差及计算广义遗传力^[30], 利用Powermarker V3.25分析等位变异数和多态性信息含量^[31], 采用STRUCTRE 2.3.2软件^[32]分析群体结构, 计算相应的Q值。在估计最佳群体亚群数目过程中, K值预设范围为2~12, 参数iterations设定为10 000, burn-in period设定为100 000, 每个K值均运行5次, 最终根据似然值最大的原则选取合适的K值^[33]。利用TASSEL2.1 (http://www.maizegenetics. net/)中的MLM模型(mixed linear model)对4种SRC与标记变异分别进行关联分析^[34], 并计算Kinship。当标记的P< 0.005时认为与SRC性状存在关联。

2 结果与分析

2.1 4种SRC的表现及方差分析

3年度试验结果表明, 4种SRC在品种间存在广泛差异, 品种间、年度间以及品种× 年度互作效应均达极显著水平(表1)。说明SRC除了品种间存在真实差异外, 还易受外部环境因素的影响。

表1 176份小麦品种的溶剂保持力(SRC)变异分析 Table 1 Variations of solvent retention capacity in 176 wheat varieties

2.2 遗传多样性分析及群体结构估算

236对SSR引物在176个品种中共扩增出1340个等位变异, 平均每个位点检测到5.5个等位变异, 平均多态性信息含量PIC值为0.4663。从236个SSR引物中选取了64个不连锁的SSR标记, 利用STRUCTURE2.1软件估算了群体结构, 后验概率平均值ln P(D)从-28014.02呈抛物线状逐渐上升至-21592.32, 随K值增加而持续增大, 无法判断亚群数, 因此计算了概率对数变化率Δ K, 结果在K=5时出现明显峰值(图1), 据此确定供试材料亚群数为5。

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	图1 概率对数变化率Δ KFig. 1 Rate of change in the log probability values of data between successive K-values (Δ K)

2.3 SRC的关联定位

利用236个分子标记对SRC表型数据进行关联分析, 3年度检测到28个位点与4种SRC相关联(P < 0.005), 其中13个与乳酸SRC关联、7个与水SRC关联、6个与蔗糖SRC关联, 2个与碳酸钠SRC关联, 单个位点的表型解释率为3.19%~21.84% (表2)。

表2 与溶剂保持力(SRC)关联的标记位点及其对表型变异的解释率 Table 2 Loci associated with solvent retention capacity (SRC) and their contributions to phenotypic variation

位于1D的gwm642, 3年度均被检测到与水SRC极显著相关联, 且2010-2011年度还与乳酸SRC相关联, 解释表型变异的8.37%~14.42%; 位于1D的gwm337在3年中均被检测到, 与除碳酸钠SRC外的其他3种SRC相关联, 其表型贡献率为12.29%~ 15.75%; 位于7A的cfa2257在2010— 2011年度被检测到, 与蔗糖SRC和碳酸钠SRC相关联, 分别解释表型变异的4.22%和5.71%; 其他位点均在某一年被检测到, 且只与一种SRC相关联。

2.4 与SRC相关联标记的等位变异挖掘

根据3年度关联定位结果, 对gwm642-1D、gwm337-1D和cfa2257-7A等标记的有利等位变异进行了挖掘。gwm642-1D与水SRC关联, 其等位变异A186和A188在3年中均表现降低水SRC, 其效应值在-0.55%至-4.57%范围内; 等位变异A174在2010— 2011年度的效应为3.42%, 但在另外两年为较小的负向效应; 等位变异A202在2009— 2010年度的负向效应较小, 而2008— 2009和2010— 2011年度均表现增加水SRC, 效应值分别为1.94%和2.42% (图2-A)。

携带等位变异gwm642-A188的品种共51个, 按照硬度值分类为软质类型36个, 中硬类型11个, 硬质类型4个, 包括了国内现已育成的主要弱筋品种, 如宁麦9号、扬麦9号、扬麦13、扬麦19、扬辐麦3046、扬辐麦5号、郑麦004、皖麦18、徐州20、绵阳26、绵阳31、石家庄8号等。该等位变异的水SRC平均值为0.8532 (2008— 2009)、0.7597 (2009— 2010)和0.7121 (2010— 2011), 在不同等位变异中是均值最低的。

携带等位变异gwm642-A202的品种共16个, 包括9个硬麦类型, 如藁城8901、中优16、济麦20、鲁麦2号、安农8455、安农2号、扬麦4号、宁麦11等。该等位变异的水SRC平均值分别为0.8997 (2008— 2009)、0.7867 (2009— 2010)和0.7821 (2010— 2011), 在不同等位变异中处于较高水平。

携带等位变异gwm642-A186和A174的品种一半为软麦类型, 另一半为硬麦类型, gwm642-A186的水SRC平均值3年度分别为0.8748、0.7773和0.7317, 在不同等位变异中处于中等偏低水平; 而gwm642- A174的水SRC平均值3年度分别为0.8788、0.7892和0.7920, 在不同等位变异中处于中等偏高水平。

标记gwm337-1D 3年度分别与3种SRC关联, 其等位变异gwm337-A178在3年中均表现负效应, 对水SRC、乳酸SRC和蔗糖SRC的效应值分别为-1.50%、-2.36%和-3.27%; 等位变异gwm337-A168 在2008— 2009年度表现降低水SRC, 效应值为-1.0%, 在2009— 2010年度对乳酸SRC的效应值几乎为0, 在2010— 2011年度对蔗糖SRC表现负效应(-0.5%); 该位点的A182、A184、A188等位变异对3种SRC均为正效应, 3年检测结果一致, 效应值范围为2.0%~ 4.7%; 等位变异gwm337-A186在2010年对乳酸SRC的效应值为0.54%, 在2010— 2011年度则对蔗糖SRC表现负效应, 其值为-3.0% (图2-B)。

在cfa2257-7A位点, 等位变异A129在2010— 2011年度表现降低蔗糖SRC和碳酸钠SRC, 其效应值分别为-1.1%和-2.1%; 等位变异A131则对蔗糖SRC和碳酸钠SRC表现增效, 其效应值分别为1.5%和2.9% (图2-C)。

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图2 标记gwm642-1D (A)、gwm337-1D (B)和cfa2257-7A (C)不同等位变异的表型效应不同花纹图形表示不同类型SRC, 不同背景颜色表示不同环境(年度)。WSRC: 水SRC; LASRC: 乳酸SRC; SSRC: 蔗糖SRC; SCSRC: 碳酸钠SRC。Fig. 2 Phenotypic effects of alleles on loci gwm642-1D (A), gwm337-1D (B), and cfa2257-7A (C)SRC type and environment (growing season) are distinguished by graphic patter and background color, respectively. WSRC: water SRC; LASRC: lactic acid SRC; SSRC: sucrose SRC; SCSRC: sodium carbonate SRC.

3 讨论

本研究通过3年度的关联分析定位了28个与SRC极显著的标记(P < 0.005), 除1B、3D、5A、5B、6B和6D外, 其余染色体上均有标记被关联到。而这些被关联的标记大多仅一年被检测到, 只有2个标记3年度均被检测到, 其中一个标记与水SRC相关联(gwm642-1D), 另一个在不同年度分别与不同的SRC相关联(gwm337-1D)。SRC受基因型控制, 但环境对其影响较大^{[8, 10, 36, 37]}。尽管在试验过程中从田间种植管理到收获等各方面均力求一致, 但不同年度间的气候条件存在差异, 从而影响了定位结果的稳定性。此外, 由于4种SRC间存在较高的相关性^[36], 可能某些位点能同时影响多个SRC性状(表3)^[26]。本文所定位的gwm337-1D在3年度与不同类型SRC极显著相关联, 推测该位点可能与多个SRC性状有关, 而由于不同年份间不同SRC的变幅不同, 因此可能出现上一年度部分SRC被极显著关联到而到下一年度却又与另一种SRC相关联的现象, 此定位结果还有待进一步的验证。由于本研究为同一地点3年度试验, 为使定位的结果能够更为准确, 应增加试验地点, 多年多点的品质检测结果将能更好地验证和补充已有结果的准确性。

对gwm642-1D不同等位变异比较发现, A188主要存在于软麦品种, 即在该等位变异存在的情况下品种应该大多表现出软麦的品质特性, 但仍然会存在一些硬麦类型品种, 因此利用该标记对SRC进行辅助筛选时还要考虑品种的硬度表现。此外, 对参试品种分析发现有些弱筋品种存在A188等位变异但硬度值偏高, 如郑麦004, 其硬度值为61, 3年度水SRC均较低, 分别为0.7447、0.7515和0.7129, 徐麦25其硬度值为52, 3年度水SRC也较低, 分别为0.8365、0.7472和0.7255。对于这类中等硬度类型的品种, 仍然可以通过标记进行辅助筛选, 但须结合除硬度外其他品质指标进行综合评价。

Smith和Souza等^[26]采用关联分析的方法定位出一部分与SRC等紧密连锁的分子标记(表3), 其结果表明2B上存在着控制4种SRC的相关位点。本研究选用的位于2B的引物有14个, 部分与其所用引物相同, 部分在连锁图上与其所用引物相近。Smith和Souza等所定位的标记gwm429和barc98在本试验中3年度关联结果均未达极显著水平, 而本研究在0.005显著水平下关联到位于2B的标记仅有wmc361, 该标记2008— 2009年度与乳酸SRC极显著相关联, 与Smith和Souza等的定位的结果相距较远。马庆^[38]以RIL群体对SRC进行过QTL定位, 检测到1个与水SRC相关的QTL (5DS)、2个与乳酸SRC相关的QTL (5D和6D)和1个与碳酸钠SRC相关的QTL (4D)。本研究使用了与其相同或在连锁图上相近的分子标记, 结果在4D上未检测到与碳酸钠SRC相关联的标记, 而是在7A和7D上定位到2个; 与乳酸SRC极显著相关联的标记有13个, 其中2010— 2011年度在5D上检测到与乳酸SRC极显著相关联的标记gwm174, 与马庆定位标记区间相距较远, 6D上未检测到与乳酸SRC相关联的标记; 控制水SRC的标记主要位于1A、1D、3B和7D上, 其中1D上存在着较为稳定的控制水SRC的位点。本研究定位结果与其他已有研究结果间存在的差异可能与所采用的定位群体材料和定位方法的不同有关。

表3 与溶剂保持力(SRC)关联的2B染色体标记均方 Table 3 Mean square terms for association of solvent retention capacity (SRC) data with chromosome 2B markers

4 结论

一地三年试验共检测到28个与SRC极显著相关联的标记, 其中与乳酸SRC关联的位点最多, 有13个, 与碳酸钠SRC关联的位点最少, 仅有2个, 单个位点的表型解释率为3.19%~21.84%, 其中gwm642-1D在3年中均被检测到与水SRC极显著相关联。在1D上存在较为稳定的控制SRC的位点。等位变异gwm642-A186、A188和gwm337-A178可降低水SRC值, 等位变异gwm337-A178和A186可降低蔗糖SRC值, cfa2257-A129可降低碳酸钠SRC值。

附表试验品种(系)的硬度值及分类 Supplementary table Hardness and the category of wheat varieties/lines tested

品种 Variety	硬度 Hardness	类型 Type	品种 Variety	硬度 Hardness	类型 Type	品种 Variety	硬度 Hardness	类型 Type	品种 Variety	硬度 Hardness	类型 Type
豫麦50	9	ES	扬辐麦3046	27	S	小偃5号	39	MS	普冰4302	65	H
京411	18	VS	鄂麦9号	27	S	扬85-85	43	MS	镇麦9号	65	H
浙丰2号	18	VS	扬麦9号	27	S	镇7630	43	MS	济麦21	66	H
徐州21	18	VS	农大139	27	S	小偃4号	43	MS	襄麦48	66	H
徐州20	18	VS	济南13	27	S	宁麦13	44	MS	淮麦16	66	H
矮孟牛	19	VS	烟农15	27	S	丰产3号	45	MH	碧玛4号	67	H
济南16	19	VS	宁麦8号	28	S	山农辐63	47	MH	鲁麦14	67	H
川麦41	19	VS	宁麦6号	28	S	鲁麦3号	48	MH	石麦12	67	H
川麦107	20	VS	泰山1号	28	S	豫麦54	49	MH	Halt	67	H
烟辐188	20	VS	宛7107	28	S	徐州25	52	MH	苏麦6号	68	H
选7	20	VS	ARGELATO	28	S	合春12	52	MH	周优102	68	H
臧2726	20	VS	鲁麦21	29	S	济南9号	52	MH	郑麦9023	68	H
陕7859	20	VS	临麦2号	29	S	苏麦5号	56	MH	绵阳30	68	H
南大2419	20	VS	晋麦52	29	S	徐州26	56	MH	安农8455	68	H
赣162	20	VS	川9920	30	S	小偃54	56	MH	鲁麦2号	69	H
豫麦18	20	VS	扬麦13	30	S	北京11	57	MH	济麦22	69	H
偃展4110	21	VS	郑州741	30	S	豫麦41	57	MH	普冰06-X4794	69	H
福绵2号	21	VS	晋麦33	30	S	高优503	58	MH	皖麦32	69	H
皖麦50	22	VS	扬7-2	30	S	石家庄8号	58	MH	皖麦47	70	H
扬麦15	22	VS	扬麦1号	30	S	石麦15	58	MH	川麦39	70	H
H35	22	VS	宁麦3号	30	S	淮麦17	58	MH	中优16	71	H
鲁麦15	22	VS	扬麦5号	30	S	镇麦5号	60	MH	扬麦4号	71	H
淮麦18	22	VS	扬麦14	31	S	扬麦17	60	MH	冀麦36	71	H
豫麦13	22	VS	甘83 (元45)	31	S	农大116	60	MH	K35	71	H
川农16	23	VS	徐州8785	31	S	长旱58	61	MH	安农2号	72	H
太空5号	23	VS	宁丰小麦	31	S	徐麦27	61	MH	普冰04-3507	73	H
川麦37	23	VS	扬麦3号	31	S	郑麦004	61	MH	烟农19	73	H
安农0721	23	VS	绵阳31	31	S	扬麦16	61	MH	宁麦10号	73	H
西农6028	23	VS	绵阳15	32	S	豫麦51	62	MH	宁麦11	74	H
扬麦19	23	VS	宁麦7号	33	S	徐州15	62	MH	淮麦21	74	H
皖麦18	24	VS	淮麦11	33	S	晋麦20	62	MH	济南17	74	H
豫麦49	24	VS	苏麦3号	33	S	河农822	63	MH	云麦27	75	H
宁麦9号	24	VS	豫麦2号	33	S	安农92484	63	MH	普冰4313	75	H
扬辐麦5号	24	VS	绵农4号	33	S	法展5号	63	MH	镇麦168	75	H
镇麦6号	24	VS	阿夫	34	S	陕麦150	63	MH	Jagger	75	H
扬辐麦2号	24	VS	镇7495	34	S	福繁17	63	MH	Norm	78	H
阿勃	25	S	皖麦48	35	MS	豫麦34	63	MH	陕229	78	H
绵阳26	25	S	新麦19	35	MS	淮麦20	64	MH	江东门	78	H
淮麦22	26	S	川育21526	35	MS	欧柔	64	MH	IWWSN15-22	80	H
NR98117-20S	26	S	襄麦5号	36	MS	咸农39	64	MH	浙农大85品8	80	H
鄂麦6号	26	S	郑引1号	36	MS	宁麦12	64	MH	Bobwhite	81	VH
陇春11	26	S	镇麦1号	37	MS	碧玛1号	64	MH	藁城8901	81	VH
湘麦10号	27	S	扬麦2号	38	MS	扬麦158	65	H	济麦20	83	VH
绵阳11	27	S	扬麦6号	38	MS	郑6辐	65	H	胜利麦	84	VH

硬度值为3年SKCS硬度仪检测数据的平均值, 依据AACC 55-31标准分类。ES: 极软; VS: 很软; S: 软; MS: 中软; MH: 中硬; H: 硬; VH: 很硬。

Hardness value was the average of three years tested by SKCS and the categorized according to AACC55-31 standard. ES: extremely soft; VS: very soft; S: soft; MS: medium soft; MH: medium hard; H: hard; VH: very hard.

附表试验品种(系)的硬度值及分类 Supplementary table Hardness and the category of wheat varieties/lines tested

The authors have declared that no competing interests exist.

作者已声明无竞争性利益关系。

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[38]	马庆. 小麦溶剂保持力的QTL定位及其与加工品质的关系, 扬州: 扬州大学硕士学位论文, 江苏扬州, 2009 Ma Q. QTL Mapping for Common Wheat SRC and Relationship with Processing Quality. MS Thesis of Yangzhou University, Yangzhou, China, 2009 (in Chinese with English abstract) [本文引用:1]

2006

0.0

1.007

昝香存, 周桂英, 吴丽娜, 王爽, 胡学旭, 陆伟, 王步军. 我国小麦品质现状分析. 麦类作物学报, 2006, 26(6): 46-49

Zan X

, Zhou G

, Wu L

, Wang

, Hu X

, Lu

, Wang B

Present status of wheat quality in China.

J Triticeae Crops, 2006, 26(6) : 46-49 (in Chinese with English abstract)

1 334 samples of 369 wheat cultivars grown in different regions from 2003~2005,were used to investigate and evaluate grain quality,milling quality,rheological characteristics,and processing quality.The results showed that the coefficient of variation of s

为给小麦生产及粮食购销、加工企业提供小麦品种品质方面的信息，2003～2005年从全国各地征集了1334份小麦样品（包括369个品种），对其籽粒品质、面粉品质、面团特性及加工品质进行了测定和评价。结果表明，在所测试的品质性状中，稳定时间的变异系数最高（83．28％），其次为最大阻力、形成时间、拉伸面积、沉淀值、降落数值、延伸性、湿面筋和蛋白质含量，容重、出粉率和吸水率的变异系数较低（2．44％、2．84％、6．06％）。稳定时间、拉伸面积、形成时间、沉淀值、最大阻力等品质性状在品种间和年度间变化较大。与国家标准相比对，2003、2004和2005年测试样品中分别达到强筋和弱筋小麦国家标准主要指标的品种数为7、24、39个和2、6、12个。与农业部1986、1990、1994年三次面包品质测定结果相比较，我国强筋小麦的烘焙品质呈逐步改良趋势。

... 随着生活水平的提高, 小麦生产和育种也从追求产量转向优质高产协调发展, 从20世纪80年代中期开始, 我国就已开展小麦品质育种研究, 但当时大多数育种单位都强调强筋小麦而忽视弱筋小麦, 在弱筋小麦遗传特性、种质创新、品种选育以及快速鉴定方法等方面均缺乏研究^[1,2] ...

2010

0.0

1.007

张伯桥, 张晓, 高德荣, 吕国锋, 朱冬梅, 马谈斌. 吹泡仪参数作为弱筋小麦品质育种选择指标的评价. 麦类作物学报, 2010, 30: 29-33

Zhang B

, Zhang

, Gao D

, Lü G

, Zhu D

, Ma T

The value of alveograph parameters used as selection index in weak-gluten wheat breeding.

J Triticeae Crops, 2010, 30: 29-33 (in Chinese with English abstract)

为了研究吹泡仪参数在弱筋小麦育种中的应用价值,通过对42个不同品质类型品种2年度的品质测定及长江中下游麦区9个推广品种的不同肥料处理试验,分析了吹泡仪参数在品种间的差异及其与其他品质性状的相关性,并分析了吹泡仪参数在不同肥料处理下的稳定性.结果表明,吹泡仪参数在品种间的变异系数大于SDS沉淀值、蛋白质含量、干面筋含量、湿面筋含量和面筋指数的变异系数,可以较好地反映品种间的品质差异;吹泡仪P值与SDS沉淀值、面筋指数和除形成时间外的所有粉质仪参数呈极显著相关,L值与蛋白质含量、干面筋含量、湿面筋含量呈极显著相关,W值与除干面筋外的所有品质指标都呈极显著相关;在不同肥料运筹模式下,多数品种的P值、L值和P/L值的变异系数都小于粉质仪参数稳定时间的变异系数.吹泡仪参数P值、L值和W值是弱筋小麦品质育种的理想选择指标. Abstract： In order to evaluate the value of Alveograph parameters in weak-gluten wheat breeding, 42 cultivars were planted in two crop season to study the difference of Alveograph parameters between different cultivars and the correlation between Alveograph parameters and other quality traits. Nine cultivars, including 6 weak-gluten cultivars were planted under 4 fertilizer treatments to study the stability of Alveograph parameters. The results showed that the variance coefficient of Alveograph parameters in different cultivars were larger than that of SDS sedimentation value, protein content, dry gluten content, wet gluten content and gluten index, such that it could reveal the quality difference in cultivars well. P value correlated significantly with SDS sedimentation, gluten index and all Farinograph parameters except development time, and L value correlated significantly with protein content, dry gluten content and wet gluten content, whereas W value correlated significantly with all quality traits except dry gluten content. According to the result of 9 cultivars under 4 fertilizer treatments, the variance coefficient of P value, L value and P/L were smaller than that of stability time. That indicated Alveograph parameters would not change greatly under different treats. So Alveograph parameters P value, L value and W value were the perfect index for quality selection in the process of weak-gluten wheat breeding.

2002

0.0

1.889

何中虎, 林作楫, 王龙俊, 肖志敏, 万富世, 庄巧生. 中国小麦品质区划的研究. 中国农业科学, 2002, 35: 359-364

He Z

, Lin Z

, Wang L

, Xiao Z

, Wan F

, Zhuang Q

Classification on Chinese wheat regions based on quality.

Sci Agric Sin, 2002, 35: 359-364 (in Chinese with English abstract)

中国农业科学院作物育种栽培研究所

根据生态因子对品质表现的影响 ,土壤质地、肥力水平及栽培措施对品质的影响 ,品种品质的遗传特性及其与生态环境的协调性 ,以及我国小麦的消费状况、商品率和可操作性的原则 ,将我国小麦产区分为 3大品质区域 ,即北方强筋、中筋白粒冬麦区 ,南方中筋、弱筋红粒冬麦区和中筋、强筋红粒春麦区。还提出了推进优质专用小麦产业带建设的意见

... 自2001年我国小麦品质区划^[3]制定和发布后, 弱筋小麦开始受到重视, 宁麦9号、扬麦13和宁麦13等弱筋品种相继育成和大面积推广, 促进了我国弱筋小麦生产的发展, 但现有弱筋品种仍然存在品质性状年度间和地点间波动较大等问题, 弱筋品质总体水平尚待进一步提高^[4,5] ...

2009

0.0

0.895

姚金保, 马鸿翔, 张平平, 姚国才, 杨学明, 张鹏. 中国弱筋小麦品质研究进展. 江苏农业学报, 2009, 25: 919-924

Yao J

, Ma H

, Zhang P

, Yao G

, Yang X

, Zhang

Progress on soft wheat quality research in China.

Jiangsu J Agric Sci, 2009, 25: 919-924 (in Chinese with English abstract)

近10多年来,中国在弱筋小麦品质区划、品质评价体系以及品种选育等方面取得了较大进展,育成了宁麦9号、扬麦13等23个弱筋专用小麦品种,并在弱筋小麦优势区发挥了重要作用.但是,在弱筋小麦品种改良和生产过程中,还存在种质资源匮乏、品质不过硬且波动性大等问题.针对这些问题和不足,文中就弱筋小麦育种提出了今后应当注意的几个方面.

2012

0.0

1.007

张晓, 张勇, 高德荣, 别同德, 张伯桥. 中国弱筋小麦育种进展及生产现状. 麦类作物学报, 2012, 32: 184-189

Zhang

, Zhang

, Gao D

, Bie T

, Zhang B

The Development and present of weak-gluten situation of its wheat breeding production.

J Triticeae Crops, 2012, 32: 184-189 (in Chinese with English abstract)

Superior weak gluten wheat is suitable for the produce of biscuits, cakes and Chinese southern steamed bread.With high speed economic development of China, biscuits and cakes are in great demand. So the superior weak gluten wheat is great in demand.Breeding of weak gluten wheat has got remarkable achievements in China during the past ten years.A series of weak gluten wheat varieties were released and widely planted; the predominant production area along the river and the coast of Jiangsu Province has been developed.Moreover, the principal problems in weak gluten wheat breeding were analyzed and the strategy for weak gluten breeding was brought up to activate the development of weak gluten wheat industry.

优质弱筋小麦适合制作饼干、糕点、南方馒头等食品。随着我国经济高速发展，饼干、糕点的需求量快速增长，与此相适应，优质弱筋小麦的需求量也将持续增加。经过十几年的工作，我国已育成了一批优质弱筋小麦品种应用于生产，形成了以江苏沿江沿海为重点的优势区域。本文总结了我国弱筋小麦育种进展和生产现状，分析了当前存在的主要问题，提出了相应的发展策略与建议，以期推动我国弱筋小麦产业的稳健发展。

2009

0.64

0.0

... 溶剂保持力(solvent retention capacity, SRC)是指以含水量14%的面粉为基准, 经过离心后, 面粉所保持的溶剂质量占面粉干重的百分比, 该指标主要用于软质小麦的品质评价, 1999年通过AACC认定(AACC 56-11), 已成为美国评价软麦品质的主导方法^[6,7,8] ...

... 2 溶剂保持力测定方法收获后将籽粒样品磨粉, 参照AACC 56-11方法^[6,7], 测定5%乳酸SRC、5%碳酸钠SRC、50%蔗糖SRC和水SRC, 标准粉样品用量改为1 g ^[27,28] ...

2000

0.64

0.0

... 大多数研究表明, 上述4种SRC值与饼干直径呈极显著负相关^[7,13,14,15], 可以利用SRC值对面粉的饼干品质特性进行评价 ...

... 2 溶剂保持力测定方法收获后将籽粒样品磨粉, 参照AACC 56-11方法^[6,7], 测定5%乳酸SRC、5%碳酸钠SRC、50%蔗糖SRC和水SRC, 标准粉样品用量改为1 g ^[27,28] ...

2011

2003

1.513

0.0

... SRC主要受基因型控制^{[9,10,11,12,13]} ...

2008

0.0

1.007

夏云祥, 马传喜, 司红起, 乔玉强, 何贤芳. 小麦溶剂保持力的基因型和环境及其互作效应分析. 麦类作物学报, 2008, 28: 448-451

Xia Y

, Ma C

, Si H

, Qiao Y

, He X

Effects of genotype, environment and genotype × environment interaction on solvent retention capacity in common wheat.

J Triticeae Crops, 2008, 28: 448-451 (in Chinese with English abstract)

为阐明基因型和环境及基因型与环境互作效应对小麦溶剂保持力的影响,以品质差异较大的19份小麦品种(系)为材料,对4个地点的小麦溶剂保持力进行了分析,同时用各溶剂保持力的变异系数与平均变异系数的比值作为稳定性参数,初步分析了各溶剂保持力的稳定性.结果表明:(1)4种溶剂保持力的基因型、环境及基因型与环境互作效应间差异均极显著;(2)基因型效应是影响小麦溶剂保持力的主要因素,其方差占总方差的56.7%～83.4%,远大于环境及基因型与环境互作效应的影响;(3)环境对蔗糖溶剂保持力的影响最大,其次是碳酸钠溶剂保持力和乳酸溶剂保持力,水溶剂保持力受环境的影响较小;(4)溶剂保持力的稳定性因基因型而异,同时基因型间各溶剂保持力的稳定性变化趋势亦不一致.这些研究结果可为优质小麦品种选育和生产提供参考依据.

... SRC主要受基因型控制^{[9,10,11,12,13]} ...

... SRC受基因型控制, 但环境对其影响较大^[8,10,36,37] ...

2001

1.513

0.0

... SRC主要受基因型控制^{[9,10,11,12,13]} ...

2002

1.251

0.0

... SRC主要受基因型控制^{[9,10,11,12,13]} ...

2004

0.0

1.007

张岐军, 何中虎, 闫俊, 钱森和, 张艳, 葛秀秀, 王继忠. 溶剂保持力在软质小麦品质评价中的应用. 麦类作物学报, 2004, 24(4): 140-142

Zhang Q

, He Z

, Yan

, Qian S

, Zhang

, Ge X

, Wang J

Application of Solvent Retention Capacity in Soft Wheat Quality Evaluation.

J Triticeae Crops, 2004, 24(4): 140-142 (in Chinese with English abstract)

Evaluation method has become a limiting factor for soft wheat research and development in China. Solvent retention capacity (SRC) is a new and effective method for evaluating soft wheat quality and has close relationship with soft wheat quality such as co

评价方法是制约国内软质小麦品质研究的重要因素。溶剂保持力(SRC)是近几年发展起来的预测软麦品质的新方法，国内外研究表明，此方法简单易行，与软质小麦品质高度相关，因此它是评价软麦品质非常有效的方法之一。本文详细介绍了溶剂保持力在国内外软麦育种及品质评价中的应用以及操作步骤，目的是为育种工作者及品质测试人员提供简单有效的评价方法。

... SRC主要受基因型控制^{[9,10,11,12,13]} ...

... 大多数研究表明, 上述4种SRC值与饼干直径呈极显著负相关^[7,13,14,15], 可以利用SRC值对面粉的饼干品质特性进行评价 ...

2004

1.251

0.0

... 大多数研究表明, 上述4种SRC值与饼干直径呈极显著负相关^[7,13,14,15], 可以利用SRC值对面粉的饼干品质特性进行评价 ...

... 饼干为含水量低的烘焙食品, 要求面粉具有较低的吸水率、淀粉破损率和戊聚糖含量, 不同SRC值为评价饼干品质提供了更多的面粉品质特性信息^[14,16] ...

2010

0.0

1.667

姚金保, Souza

, 马鸿翔, 张平平, 姚国才, 杨学明, 任丽娟, 张鹏. 软红冬小麦品质性状与饼干直径的关系. 作物学报, 2010, 36: 695-700

Yao J

, Souza

, Ma H

, Zhang P

, Yao G

, Yang X

, Ren L

, Zhang

Relationship between quality traits of soft red winter wheat and cookie diameter.

Acta Agron Sin, 2010, 36: 695-700 (in Chinese with English abstract)

Fifty-seven soft red winter wheat ( Triticum aestivum L.) genotypes including two cultivars released in Jiangsu Province and 55 advanced lines were subjected to quality tests of sixteen parameters, such as solvent retention capacity (SRC) and RVA viscosity parameters. The results showed that there were great variations among wheat genotypes for quality traits and cookie diameter. Significant correlations were observed between cookie diameter and 1000-kernel weight ( r = - 0.3910, P r = 0.5548, P r = - 0.3032, P r = - 0.5667, P r = - 0.8579, P r = - 0.8643, P r = - 0.6120, P r = - 0.7566, P r = 0.4337, P r = - 0.2702, P r = - 0.6158, P

1 Institute of Agricultural Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China; 2 USDA/ARS Soft Wheat Quality Laboratory, 1680 Madison Avenue, Wooster, Ohio 44691-4096, USA

以57份软红冬小麦品种(系)为材料，通过测定出粉率、面粉颗粒度、蛋白质含量、溶剂保持力和RVA参数等指标，研究了小麦品质性状与饼干直径的关系。结果表明，品种(系)间的品质性状和饼干直径变异较大。在16个品质性状中，有11个与饼干直径呈显著或极显著相关，其中碳酸钠SRC、水SRC、蔗糖SRC与饼干直径的相关最密切，相关系数分别为 - 0.8643 ( P - 0.8579 ( P - 0.7566 ( P

... 大多数研究表明, 上述4种SRC值与饼干直径呈极显著负相关^[7,13,14,15], 可以利用SRC值对面粉的饼干品质特性进行评价 ...

2009

2.546

0.0

Pasha

, Anjum F

, Butt

Genotypic variation of spring wheats for solvent retention capacities in relation to end-use quality.

LWT-Food Sci Technol, 2009, 42: 418-423

Abstract The solvent retention capacity (SRC) test is useful to measure flour components contributing to end-use functionality especially where the sample number is large and grain quantities are limited. The water, sodium carbonate, lactic acid, and sucrose SRC values ranged 78.0–98.0, 95.0–127.5, 101.5–139.0, and 125.0–163.0 g/100 g, respectively in 50 spring wheat varieties. Water SRC positively correlated with cookie spread ratio ( r = 0.29) while Lactic acid SRC and Sucrose SRC positively correlated with cookie thickness ( r = 0.31) and ( r = 0.23). Negative correlation coefficients were observed in water SRC and cookie thickness ( r = −0.27). Lactic acid SRC also negatively correlated with cookie spread ratio ( r = −0.34). Sodium carbonate SRC was found to be negatively correlated with cookie diameter ( r = −0.19) and cookie spread ratio ( r = −0.16). The SRC test is a promising method for the evaluation of soft wheat varieties on the basis of their biochemical characteristics.

2003

25.962

0.0

... 关联分析是利用自然群体中的连锁不平衡, 鉴定目的性状与遗传标记或者候选基因之间关系, 从而挖掘或定位基因的分析方法^[17] ...

2001

35.209

0.0

Thornsberry J

, Goodman M

, Doebley

, Kresovich

, Nielsen

, Buckler E

Dwarf8 polymorphisms associate with variation in flowering time.

Nat Genet, 2001, 28: 286-289

... 2001年Thornsberry成功地将该方法应用于玉米开花期变异的研究^[18] ...

2005

6.582

0.0

Flint-Garcia S

, Thuillet A

, Yu

, Pressoir

, Romero S

, Mitchell S

, Doebley

, Kresovich

, Goodman M

, Buckler E

. Maize association population: a high-resolution platform for quantitative trait locus dissection. Plant J, 2005, 44: 1054-1064

1 US Department of Agriculture – Agricultural Research Service, Plant Genetics Research Unit, Columbia, MO 65211, USA 2 Division of Plant Sciences, University of Missouri, Columbia, MO 65211, USA, 3 Department of Genetics, University of Wisconsin, Madison, WI 65211, USA, 4 Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA, 5 Department of Crop Science, North Carolina State University, Raleigh, NC 27695, USA, and 6 US Department of Agriculture – Agricultural Research Service, US Plant, Soil and Nutrition Research Unit, Ithaca, NY 14853, USA * (fax +1 607 255 6249; e-mail esb33@cornell.edu ).

> Crop improvement and the dissection of complex genetic traits require germplasm diversity. Although this necessary phenotypic variability exists in diverse maize, most research is conducted using a small subset of inbred lines. An association population of 302 lines is now available – a valuable research tool that captures a large proportion of the alleles in cultivated maize. Provided that appropriate statistical models correcting for population structure are included, this tool can be used in association analyses to provide high-resolution evaluation of multiple alleles. This study describes the population structure of the 302 lines, and investigates the relationship between population structure and various measures of phenotypic and breeding value. On average, our estimates of population structure account for 9.3% of phenotypic variation, roughly equivalent to a major quantitative trait locus (QTL), with a high of 35%. Inclusion of population structure in association models is critical to meaningful analyses. This new association population has the potential to identify QTL with small effects, which will aid in dissecting complex traits and in planning future projects to exploit the rich diversity present in maize.

... 由于关联分析研究对象为自然品种群体, 可利用材料相对广泛, 是解析复杂性状、鉴定目标性状优异等位基因的有效方法^[19,20], 迄今为止, 在玉米、水稻、小麦等作物中已有较多应用实例^{[21,22,23,24]} ...

2005

3.518

0.0

Gupta P

, Rustgi

, Kulwal P

Linkage disequilibrium and association studies in higher plants: present status and future prospects.

Plant Mol Biol, 2005, 57: 461-485

During the last two decades, DNA-based molecular markers have been extensively utilized for a variety of studies in both plant and animal systems. One of the major uses of these markers is the construction of genome-wide molecular maps and the genetic analysis of simple and complex traits. However, these studies are generally based on linkage analysis in mapping populations, thus placing serious limitations in using molecular markers for genetic analysis in a variety of plant systems. Therefore, alternative approaches have been suggested, and one of these approaches makes use of linkage disequilibrium (LD)-based association analysis. Although this approach of association analysis has already been used for studies on genetics of complex traits (including different diseases) in humans, its use in plants has just started. In the present review, we first define and distinguish between LD and association mapping, and then briefly describe various measures of LD and the two methods of its depiction. We then give a list of different factors that affect LD without discussing them, and also discuss the current issues of LD research in plants. Later, we also describe the various uses of LD in plant genomics research and summarize the present status of LD research in different plant genomes. In the end, we discuss briefly the future prospects of LD research in plants, and give a list of softwares that are useful in LD research, which is available as electronic supplementary material (ESM)

1.Molecular Biology Laboratory, Department of Genetics & Plant Breeding, Ch. Charan Singh University, Meerut, 250 004 (UP) India

2011

1.681

0.0

Bryant

, Proctor

, Hawkridge

, Jackson

, Yeater

, Counce

, Yan

, McClung

, Fjellstrom

. Genetic variation and association mapping of silica concentration in rice hulls using a germplasm collection. Genetica, 2011, 139: 1383-1398

1. USDA-ARS, Dale Bumpers National Rice Research Center, 2890 Hwy 130 E, Stuttgart, AR, 72160, USA 2. Department of Food Science, University of Arkansas, Fayetteville, AR, 72701, USA 3. Department of Physics, University of Arkansas, Fayetteville, AR, 72701, USA 4. USDA-ARS, Southern Plains Area, College Station, TX, 77840, USA 5. University of Arkansas Rice Research and Extension Center, Stuttgart, AR, 72160, USA

An association analysis on the genetic variability for silica concentration in rice hulls was performed using a “ Mini -Core” set of 174 accessions representative of the germplasm diversity found in the USDA world collection of rice. Hull silica concentration was determined in replicated trials conducted in two southern states in the USA and was analyzed for its association with 164 genome-wide DNA markers. Among the accessions, the average silica concentration ranged from 120 to 251 mg g −1 . Ample variation was seen within each of the five sub-populations of rice, as well as the 14 geographic regions that the accessions originated from. There was also an effect due to location and accession × location (G × E) interaction demonstrating the importance of assessing silica concentration across multiple environments. Twelve markers on ten chromosomes were significantly associated with hull silica concentration. Six markers (RM5644, RM5371, RM1335, RM283, RM263, and RM178) corroborated quantitative trait locus for silica concentration identified in other mapping studies. Our results provide germplasm and genetic markers that will assist breeding efforts to develop cultivars that have either high or low hull silica concentration. High silica hulls are good raw material for silica based industrial compounds, while low silica hulls are more biodegradable.

2014

0.0

1.667

张焕欣, 翁建峰, 张晓聪, 刘昌林, 雍洪军, 郝转芳, 李新海. 玉米穗行数全基因组关联分析. 作物学报, 2014, 40: 1-6

Zhang H

, Weng J

, Zhang X

, Liu C

, Yong H

, Hao Z

, Li X

, Genome-wide association analysis of kernel row number in maize. Acta Agron Sin, 2014, 40: 1-6 (in Chinese with English abstract)

Kernel row number (KRN) is one of grain yield components in maize ( Zea mays L.). Investigation of its genetic architecture will help develop high-yield varieties in maize. In this study, the KRN in a panel of 203 maize inbred lines was detected in Urumqi of Xinjiang, Gongzhuling of Jilin, and Sanya of Hainan in 2007, and used to perform the genome-wide analysis for KRN using MaizeSNP50 BeadChip. A total of nine SNPs were found to be significantly associated with KRN at a threshold of P auxin signaling F-box containing protein, kn1 protein, AP2 domain containing protein and leucine-rich repeat transmembrane protein kinase respectively. In summary, these identified genes and SNPs will offer essential information for cloning yield-related genes in maize.

Institute of Crop Science, Chinese Academy of Agricultural Sciences / National Engineer Laboratory of Crop Molecular Breeding, Beijing 100081, China

穗行数是玉米产量的重要组成性状，其遗传解析对高产育种具有指导意义。本文以 203 份主要玉米自交系为材料， 2007 年在新疆乌鲁木齐、吉林公主岭和海南三亚进行穗行数测定；采用分布于玉米基因组的 41 101 个单核苷酸多态性 (SNP) 标记对穗行数进行关联分析。共鉴定出 9 个与穗行数显著关联 ( P 的 SNP ，分别位于染色体框 1.02 、 1.10 、 7.03 、 8.02 、 9.06 和 10.03 。 8 个 SNP 位于已定位的数量性状座位 (QTL) 区间内。在显著 SNP 位点 LD 区域内发掘出 4 个候选基因，分别编码含 F-box 结构域的生长素受体蛋白、玉米 kn1 蛋白、 AP2 结构域蛋白和富亮氨酸重复的跨膜蛋白激酶。采用全基因组关联分析策略发掘穗行数基因位点及候选基因，将为克隆控制玉米产量性状基因奠定基础。

2012

4.397

0.0

Niedziela

, Bednarek P

, Cichy

, Budzianowski

, Kilian

, Aniol

Aluminum tolerance association mapping in triticale.

BMC Genomics, 2012, 13: 67

1. Plant Breeding and Acclimatization Institute, 05-870, Błonie, Radzików, Poland 2. Plant Breeding Company-Strzelce, Breeding Department Małyszyn, 66-400, Gorzów Wlkp., Myśliborska Str. 81, Poland 3. Diversity Array Technology Pty Ltd, 1 Wilf Crane Crescent, Yarralumla, ACT, 2600, Australia

2012

3.73

0.0

Wang

, Ge

, Hao

, Dong

, Zhang

Identifying loci influencing 1000-kernel weight in wheat by microsatellite screening for evidence of selection during breeding.

PloS One, 2012, 7: e29432

Chinese wheat mini core collection (262 accessions) was genotyped at 531 microsatellite loci representing a mean marker density of 5.1 cM. One-thousand-kernel weights (TKW) of lines were measured in five trials (three environments in four growing seasons). Structure analysis based on 42 unlinked SSR loci indicated that the materials formed two sub-populations, viz., landraces and modern varieties. A large difference in TKW (7.08 g, P ) was found between the two sub-groups. Therefore, TKW is a major yield component that was improved in the past 6 decades; it increased from a mean 31.5 g in the 1940s to 44.64 g in the 2000s, representing a 2.19 g increase in each decade. Analyses based on a mixed linear model (MLM), population structure (Q) and relative kinship (K) revealed 22 SSR loci that were significantly associated with mean TKW (MTKW) of the five trials estimated by the best linear unbiased predictor (BLUP) method. They were mainly distributed on chromosomes of homoeologous groups 1, 2, 3, 5 and 7. Six loci, cfa2234-3A , gwm156 -3B, barc 56-5A, gwm234 -5B, wmc 17-7A and cfa2257 -7A individually explained more than 11.84% of the total phenotypic variation. Favored alleles for breeding at the 22 loci were inferred according to their estimated effects on MTKW based on mean difference of varieties grouped by genotypes. Statistical simulation showed that these favored alleles have additive genetic effects. Frequency changes of alleles at loci associated with TKW are much more dramatic than those at neutral loci between the sub-groups. The numbers of favored alleles in modern varieties indicate there is still considerable genetic potential for their use as markers for genome selection of TKW in wheat breeding. Alleles that can be used globally to increase TKW were inferred according to their distribution by latitude and frequency of changes between landraces and the modern varieties.

2001

1.513

0.0

... 2001年Campbell等^[25]采用软白麦NY18× ...

2008

0.0

... 硬白麦CC的78个重组自交系对碱水保持力进行了QTL作图, 2008年Smith和Souza等^[26]曾在ASA-CSSA-SSSA年会中介绍了利用美国品种对溶剂保持力关联分析的结果, 目前, 还没有利用自然群体对4种SRC进行关联定位的报道 ...

... 此外, 由于4种SRC间存在较高的相关性^[36], 可能某些位点能同时影响多个SRC性状(表3)^[26] ...

... Smith和Souza等^[26]采用关联分析的方法定位出一部分与SRC等紧密连锁的分子标记(表3), 其结果表明2B上存在着控制4种SRC的相关位点 ...

2002

1.251

0.0

... 2 溶剂保持力测定方法收获后将籽粒样品磨粉, 参照AACC 56-11方法^[6,7], 测定5%乳酸SRC、5%碳酸钠SRC、50%蔗糖SRC和水SRC, 标准粉样品用量改为1 g ^[27,28] ...

2007

0.0

0.895

周淼平, 吴宏亚, 余桂红, 张旭, 马鸿翔. 小麦溶剂保持力微量测定方法的建立. 江苏农业学报, 2007, 23: 270-275

Zhou M

, Wu H

, Yu G

, Zhang

, Ma H

Microdetermination of solvent retention capacity in wheat.

Jiangsu J Agric Sci, 2007, 23: 270-275 (in Chinese with English abstract)

采用15个不同硬度小麦的0.5 g面粉或0.5 g全麦粉进行4种溶剂保持力的测定,并与标准的5.0 g面粉测定方法比较.结果显示: 0.5 g面粉测定法的测定结果与5.0 g面粉测定法(标准方法)的相关极显著,水、碳酸钠、蔗糖和乳酸溶剂保持力的相关系数分别为0.98、0.96、0.95和0.98,表明0.5 g面粉测定法可以替代标准测定方法用于软质小麦的早代筛选;0.5 g全麦粉测定法的乳酸溶剂保持力与标准方法的相关极显著,相关系数为0.73,但水、碳酸钠和蔗糖溶剂保持力与标准方法的相关不显著,因此不能替代标准方法用于软质小麦的早代筛选.

... 2 溶剂保持力测定方法收获后将籽粒样品磨粉, 参照AACC 56-11方法^[6,7], 测定5%乳酸SRC、5%碳酸钠SRC、50%蔗糖SRC和水SRC, 标准粉样品用量改为1 g ^[27,28] ...

1992

1985

1.513

0.0

... 0分析SRC数据方差及计算广义遗传力^[30], 利用Powermarker V3 ...

2005

5.323

0.0

... 25分析等位变异数和多态性信息含量^[31], 采用STRUCTRE 2 ...

2000

4.389

0.0

... 2软件^[32]分析群体结构, 计算相应的Q值 ...

2005

6.275

0.0

Evanno

, Regnaut

, Goudet

Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

Mol Ecol, 2005, 14: 2611-2620

Department of Ecology and Evolution, Biology building, University of Lausanne, CH 1015 Lausanne, Switzerland * Jérôme Goudet, Fax: + 41 21 692 42 65; E-mail: Jerome.goudet@unil.ch

> The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software structure allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters ( K ) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated ‘log probability of data’ does not provide a correct estimation of the number of clusters, K . However, using an ad hoc statistic Δ K based on the rate of change in the log probability of data between successive K values, we found that structure accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

... 在估计最佳群体亚群数目过程中, K值预设范围为2~12, 参数iterations设定为10 000, burn-in period设定为100 000, 每个K值均运行5次, 最终根据似然值最大的原则选取合适的K值^[33] ...

2006

35.209

0.0

, Pressoir

, Briggs W

, Bi I

, Yamasaki

, Doebley

, McMullen

M D

, Gaut

B S

, Nielsen

D M

, Holland

J B

, Kresovich

, Buckler

E S

. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet, 2006, 38: 203-208

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 1, 2 . 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.

... net/)中的MLM模型(mixed linear model)对4种SRC与标记变异分别进行关联分析^[34], 并计算Kinship ...

2004

3.658

0.0

Somers D

, Isaac

, Edwards

A high-density microsatellite consensus map for bread wheat (Triticum aestivum L. ).

Theor Appl Genet, 2004, 109: 1105-1114

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 × 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.

1.Cereal Research Centre Agriculture and Agri-Food Canada 195 Dafoe Rd. Winnipeg MB Canada R3T 2?M9 2.Norwich Research Park IDnagenetics, Hill House Colney Lane Norwich NR4-7UH UK 3.University of Bristol School of Biological Sciences Woodland Rd. Bristol BS8-1UG UK

2012

0.0

1.007

张勇, 金艳, 张伯桥, 张晓, 徐亮, 徐扬, 徐辰武, 程顺和. 不同来源品种在长江下游麦区的溶剂保持力特性及相关分析. 麦类作物学报, 2012, 32: 750-756

Zhang

, Jin

, Zhang B

, Zhang

, Xu

, Xu C

, Cheng S

Characteristics of solvent retention capacity (SRC) of different varieties planted in the low Yangtze wheat region and analysis on their correlations.

J Triticeae Crops, 2012, 32: 750-756 (in Chinese with English abstract)

To evaluate the characteristics of wheat varieties from different regions in Solvent Retention Capacity (SRC) and utilize the resources with low SRC value in wheat breeding, the four indexes of SRC including water SRC, lactic acid (LA) SRC, sodium carbonate (NaC)SRC and sucrose(Suc) SRC,hardness and protein content of 195 varieties from different wheat regions were investigated with samples grown in year 2009 and 2010 in Yangzhou, Jiangsu Province. The results indicated that there were significant differences in the four indexes of SRC, hardness and protein content among those wheat varieties. In year 2009 and 2010, the water SRC had the lowest value, the average was 87.27% and 77.54%, respectively. The LA SRC had the lower value, the average was 95.99% and 84.17% , respectively. The average of NaC SRC and Suc SRC both was more than 100% and fluctuated with different years.A very significant correlation was found among four indexes of SRC in two years, of which the correlation coefficient between LA SRC and NaC SRC was 0.607, whereas the correlation coefficient between the LA SRC and Water SRC was 0.675. The hardness had significant and positive correlations with Water SRC, LA SRC,NaC SRC and the 'gluten performance index', among which the LA SRC had the highest correlation with hardness and the correlation coefficients were 0.721 and 0.779, respectively. The protein content had significant and positive correlations with LA SRC, Suc SRC and NaC SRC, but with lower correlation coefficients. Some varieties such as Wanmai 50,Yangfumai 3046, Ningmai 9, Yumai 49 and Yangmai19 with low water SRC values in two years could be benefit in soft wheat breeding, and the water SRC, lactic acid SRC and hardness could be effective indexes to soft wheat breeding.

为给弱筋小麦育种提供指导，收集了195份来自不同麦区的小麦品种，分别于2008和2009年秋播种植于江苏扬州，并对收获种子进行了4种SRC（包括水、乳酸、碳酸钠和蔗糖SRC）、硬度及蛋白质含量的检测。结果表明，4种SRC、硬度和蛋白质含量在品种间及年度间差异均达极显著水平。两年度均以水SRC含量最低，分别为87.27%和77.54%；乳酸SRC次低，分别为95.99%和84.17%；蔗糖SRC和碳酸钠SRC年度间互有高低，其平均值均大于100%。4种SRC值间存在极显著正相关，其中2009年乳酸SRC和碳酸钠SRC之间的相关系数达0.607，2010年乳酸SRC和水SRC之间的相关系数达0.675。硬度与水、乳酸、碳酸钠等3种SRC及“面筋性能指数”存在极显著正相关，其中与乳酸SRC的两年相关系数分别高达0.721和0.779。蛋白质含量与乳酸、蔗糖、碳酸钠等3种SRC相关极显著但相关系数较小。从参试品种中筛选出了SRC两年均表现较低的品种皖麦50、扬辐麦3046、宁麦8号、豫麦49、扬麦19等，在育种中可更好地加以利用。在育种中主要可利用水SRC和乳酸SRC以及硬度检测来提高弱筋小麦育种效率。

... SRC受基因型控制, 但环境对其影响较大^[8,10,36,37] ...

... 此外, 由于4种SRC间存在较高的相关性^[36], 可能某些位点能同时影响多个SRC性状(表3)^[26] ...

2012

0.0

1.667

张勇, 金艳, 张伯桥, 张晓, 徐亮, 徐扬, 程顺和, 徐辰武. 我国不同麦区小麦品种的面粉溶剂保持力. 作物学报, 2012, 38: 2131-2137

Zhang

, Jin

, Zhang B

, Zhang

, Xu

, Cheng S

, Xu C

Solvent retention capacities of varieties from different wheat regions in China.

Acta Agron Sin, 2012, 38: 2131-2137 (in Chinese with English abstract)

Solvent retention capacity (SRC) is an important index for predicting flour functionality in soft wheat, which includes water SRC, 50% lactic acid SRC, 5% sodium carbonate SRC, and 50% sucrose SRC. To understand the SRCcharacter of wheat varieties in China, We measured four types of SRC in 181 varieties from different wheat regions in 2008–2009 and 2009–2010 growing seasons. According to analysis of variance, all types of SRC were significantly influenced by genotype, year, and wheat region ( P P

1Agricultural College of Yangzhou University, Yangzhou 225007, China; 2 Lixiahe Region Institute of Agricultural Sciences of Jiangsu Province / Key Laboratory of Biology and Genetic Improvement in Middle and Lower Yangtze Valley, Ministry of Agriculture, Yangzhou 225007, China

溶剂保持力(SRC)是评价软麦品质的一项重要指标。为了解我国不同麦区小麦品种溶剂保持力的差异, 2008—2009和2009—2010生长季测定了181个小麦品种的4种溶剂保持力, 并分析其遗传变异及不同麦区品种SRC特点。结果表明, 4种SRC值在品种、年度和麦区间均差异显著 ( P P P

... SRC受基因型控制, 但环境对其影响较大^[8,10,36,37] ...

2009

0.0

... 马庆^[38]以RIL群体对SRC进行过QTL定位, 检测到1个与水SRC相关的QTL (5DS)、2个与乳酸SRC相关的QTL (5D和6D)和1个与碳酸钠SRC相关的QTL (4D) ...