大豆生物量与产量组分间的相关及关联分析

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晁毛妮, 郝德荣, 印志同, 张晋玉, 宋海娜, 张怀仁, 褚姗姗, 张国正, 喻德跃. 大豆生物量与产量组分间的相关及关联分析. 作物学报, 2014, 40(1): 7-16
CHAO Mao-Ni, HAO De-Rong, YIN Zhi-Tong, ZHANG Jin-Yu, SONG Hai-Na, ZHANG Huai-Ren, CHU Shan-Shan, ZHANG Guo-Zheng, YU De-Yue. Correlation and Association Analysis between Biomass and Yield Components in Soybean. Acta Agron Sin, 2014, 40(1): 7-16 复制到剪切板

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作物学报编辑部

大豆生物量与产量组分间的相关及关联分析

晁毛妮^1,^**, 郝德荣^2,^**, 印志同³, 张晋玉¹, 宋海娜¹, 张怀仁¹, 褚姗姗¹, 张国正¹, 喻德跃^1,^*

¹南京农业大学国家大豆改良中心 / 作物遗传与种质创新国家重点实验室, 江苏南京 210095

²江苏沿江地区农业科学研究所, 江苏南通 226541

³扬州大学农学院 / 作物遗传生理江苏省重点实验室 / 植物功能基因组学教育部重点实验室, 江苏扬州 225009

^* 通讯作者(Corresponding author): 喻德跃, E-mail:dyyu@njau.edu.cn, Tel: 025-84396410, Fax: 025-84395405

第一作者联系方式: E-mail:2011201044@njau.edu.cn

^** 对本文有相同贡献.

收稿日期:2013-09-16

基金:本研究由国家自然科学基金项目(31171573, 31201230, 31271749)和江苏科技支撑计划项目(BE2012328, BK2012768, BE2012747)资助。

摘要

生物量与后期的籽粒产量存在紧密联系, 是决定作物经济产量的主要因素之一。本研究利用自然群体中的1142 SNP在2年环境下通过全基因组关联分析检测大豆基因组中与生物量及产量组分显著关联的SNP。结果表明: (1)生物量、百粒重和单株籽粒产量在自然群体中存在广泛的表型及遗传变异, 并存在极显著的正相关, 其中生物量与单株籽粒产量之间的相关略高于与百粒重; (2)两年环境下共检测到41、56和29个SNP分别与生物量、百粒重和单株籽粒产量显著关联, 其中仅有6、19和1个SNP在2个环境中都被检测到; (3)共检测到15个SNP同时控制2个或2个以上性状, 其中位于第19染色体上的BARC-029051-06057位点被检测到同时与生物量、百粒重和单株籽粒产量3个性状显著关联, 表明有共同的遗传基础, 同时也解释了性状间相关的遗传原因; (4)鉴定到的多个SNP与先前我们对叶绿素荧光参数及多个环境下产量相关性状的定位结果共位。这些显著关联SNP位点的鉴定, 有助于理解生物量及产量相关性状的遗传机制, 从而促进利用分子标记辅助选择聚合有利基因, 实现未来大豆高产育种计划。

关键词: 单核苷酸位点多态性(SNP); 光合作用; 产量; 大豆; 自然群体

Correlation and Association Analysis between Biomass and Yield Components in Soybean

CHAO Mao-Ni^1,^**, HAO De-Rong^2,^**, YIN Zhi-Tong³, ZHANG Jin-Yu¹, SONG Hai-Na¹, ZHANG Huai-Ren¹, CHU Shan-Shan¹, ZHANG Guo-Zheng¹, YU De-Yue^1,^*

¹National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China

² Jiangsu Yanjiang Institute of Agricultural Sciences, Nantong 226541, China

³ Jiangsu Provincial Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou 225009, China

^** Contributed equally to this work

Abstract

Biomass, one of the main factors that determine the effective economic yield, has an important effect on the final seed yield. In this study, a genome-wide association analysis was conducted to detect key single-nucleotide polymorphisms (SNPs) associated with biomass and yield components using 1142 SNPs in a soybean landraces panel. There existed abundant phenotypic and genetic diversities and significant correlations among biomass and yield components in the population, and the correlation between biomass and seed yield was slightly higher than that between biomass and seed weight. Genome-wide association analysis using a mixed linear model detected 41, 56, and 29 SNPs associated with biomass, seed weight and seed yield respectively. Among them, 6, 19, and 1 SNPs were detected in two environments. In addition, 15 SNPs were found co-associated with two or more different traits and BARC-029051-06057 on chromosome 19 was associated with the three traits, which implies a partially common genetic basis for the three traits. Many SNPs detected in our study were found co-associated with soybean chlorophyll, chlorophyll fluorescence parameters and yield components in our previous study. The identification of these significant SNPs will be helpful to better understand the genetic basis of biomass and yield components, and facilitate the pyramiding of favorable alleles for future high-yield breeding by marker-assisted selection in soybean.

Keyword: Single nucleotide polymorphisms (SNP); Photosynthesis; Yield; Soybean; Natural population

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大豆在农业生产中占有重要地位, 是人类重要的植物蛋白源^{[ 1]}, 提高大豆产量一直是大豆育种的核心问题^{[ 2]}。生物量和收获指数是决定作物经济产量的2个主要因素^{[ 3]}。以往通过传统的一些育种途径使得作物产量得到了很大提高, 但主要是通过农艺措施与收获指数的提高^{[ 4, 5, 6]}, 很少是由于生物量的增加。对世界的两大重要作物水稻与小麦而言, 收获指数的提高已经进入瓶颈阶段, 进一步提高作物产量迫切需要增加作物的生物量^{[ 7]}。因此, 对生物量的遗传变异分析及其影响因素的研究逐渐成为目前育种家们选育高产品种的方向之一。

生物量是植株基因型C、N积累能力、栽培措施、环境因素的综合结果^{[ 8]}, 与后期籽粒产量有紧密的相互关系^{[ 9]}。近年来, 大豆育种家已经鉴定许多与产量有关的QTL或SNP, 主要关乎成熟期, 株高, 百粒重和生长习性等与产量相关的性状^{[ 10, 11, 12, 13, 14, 15]}, 但关于生育期内大豆生物量积累的研究却很少, 仅有黄中文等^{[ 16]}利用重组自交系群体作过初步研究, 需要强调的是对育种利用而言, 只有那些在多数环境和多数遗传材料中都稳定表达的QTL才具有应用价值^{[ 17]}。产量性状是非常复杂的数量性状, 具有较低的遗传力且涉及大量基因的表达与调控, 更容易受环境影响^{[ 18]}。在不同的遗传材料中, 或不同的环境条件下, 起主导作用的基因(QTL)可能不同, 因此有必要在在不同遗传背景和多环境下, 继续开展生物量和产量相关性状的定位研究。本研究通过关联分析的方法在自然群体中研究大豆生物量与产量相关性状的遗传关系, 分析其相关的遗传基础, 鉴定控制这些产量影响因子的SNP位点, 以期为改良大豆生物量, 改善“源”的状况, 实现大豆产量增加提供有价值的标记信息。

1 材料与方法

1.1 试验材料

选自全国24个省份不同地理环境、不同生态类型的191栽培大豆地方品种组成的自然群体(图1), 由南京农业大学国家大豆改良中心种质资源库提供。

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	图1 191份栽培大豆地方品种地理分布每个圆圈代表不同的省份, 每个省份的材料数目用圆圈的实心部分表示。Fig. 1 Geographical distribution of 191 soybean landraces in our studyCircles represent different provinces, the number of soybean landraces per province is indicated by closed portion of the circle.

1.2 试验设计

在南京江浦实验站, 采用完全随机设计, 每个品种重复6次, 每重复1盆。为了控制环境对表型性状测定的影响, 根据前3年记载的各材料的熟期, 将试验材料分为4组。分期播种以保证所有材料在采集表型数据时处于类似的生育阶段。2011年播种日期分别为6月7日、17日、27日和7月7日, 2012年为6月8日、18日、28日和7月8日。每盆种9粒, 出苗后7 d, 定苗至2株。在试验材料的生长过程中, 保证充足的营养和水分供应, 以消除营养匮乏和干旱造成的不良影响。

1.3 性状测定和表型数据的收集

于成熟期收集百粒重和单株籽粒产量的表型数据。成熟后每品种人工收获6株, 手工脱粒并烘干至恒重用于测定百粒重和单株籽粒产量。于鼓粒期收集生物量的数据。每品种选取6株, 将大豆植株整个地上部(包括叶、叶柄、茎秆、根及后期的荚)剪下装入纱袋, 于烘箱中105℃杀青15 min, 85℃烘至恒重 (≥72 h), 称重得生物量。

1.4 DNA提取及SNP分型

取大豆苗期幼嫩叶片, 采用改良的CTAB法提取DNA。

从大豆SNP数据库(http://bfgl.anri.barc.usda.gov/soybean/)中选择均匀分布于大豆基因组的2435个SNP标记, 用于GoldenGate assay设计(Illumina, San Diego, CA)。在国家生物基因工程(上海)中心的Illumina Beadlab平台上进行SNP基因分型。根据SNP评分结果, 选择1536个得分高的SNP标记用于进一步GoldenGate assay, 采用2块1536-SNP芯片对191份栽培豆进行SNP基因分型。

在1536个SNP标记中, 有384个标记(25.7%)最小等位基因型频率(minor alleles frequency, MAF)小于10%, 因此本研究选取1142个SNP标记(MAF≥ 10%)用于进一步分析。

1.5 数据分析

用SPSS 17.0的相应程序完成各性状的方差分析、相关分析、描述统计。用TASSEL软件的MLM (mixed linear model)程序完成目标性状的关联分析。MLM将各个体的 Q作为协变量, Kinship值作为随机效应, 将表型数据分别对标记变异进行回归分析, P<0.01时认为该标记与目标性状相关联。群体遗传多样性分析、连锁不平衡估算、群体结构及亲缘关系分析参见郝德荣等^{[ 15]}的方法。

2 结果与分析

2.1 生物量与产量组分间的遗传变异分析

由表1可以看出3个性状在两年环境中均表现出广泛的表型变异, 且品种间差异极显著, 说明现有品种(系)在生物量及产量组分上存在较大的遗传差异, 这些参数的遗传变异可为大豆产量的改良提供广泛的空间。另外, 生物量与产量组分在大豆品种(系)中, 均呈现连续性分布, 近似正态分布(图2), 表明生物量及产量组分可能是受多基因控制的数量性状。数量性状易受环境影响, 在对生物量及产量组分2个环境联合方差分析时, 发现这3个性状的基因型与环境互作均达到极显著水平。

表1 大豆自然群体中生物量与产量组分的描述统计 Table 1 Descriptive statistics of soybean biomass and yield components in soybean natural population

2.2 生物量与产量组分间的相关

各性状之间存在极显著相关, 且在不同年份中生物量与百粒重和单株籽粒产量的相关存在相同的趋势即生物量与单株籽粒产量之间的相关略高于与百粒重(表2)。在2011年, 最高的相关系数存在于单株籽粒产量与百粒重之间, 而在2012年最高的相关则存在于单株籽粒产量和生物量之间, 这种差异可能是由于生物量和单株籽粒产量遗传力较低, 易受环境影响, 而百粒重在不同环境下相对稳定。

表2 大豆生物量与产量组分间的相关系数 Table 2 Correlation coefficients between biomass and yield components in soybean natural population

2.3 生物量与产量组分的关联分析

为矫正群体结构和遗传亲缘关系对关联分析的影响, 采用MLM(Q+K)模型对大豆生物量及产量组分与1142个SNP进行了全基因组关联分析。利用1142个SNP标记, 在 P≤0.01 (-lg P≥2.00)水平, 两年共检测到41、56和29个SNP与生物量、百粒重和单株籽粒产量显著关联(表3)。在所有检测到的SNP位点中, 大部分位点仅在特定环境中被检测到, 只有少部分在2个环境中均与生物量或产量组分关联。其中与生物量显著关联的SNP位点中, 有6个在2年环境中均被检测到; 与百粒重显著关联的SNP位点中, 有19个SNP在两年环境中均被检测到; 与单株籽粒产量显著关联的SNP位点中, 很少检测到在2年环境中都存在的SNP, 只有1个SNP在2年环境中均能被检测到。这与产量性状易受环境影响, 需要多年多点实验研究的结果一致。

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	图2 大豆品种(系)生物量、百粒重和单株籽粒产量的频率分布Fig. 2 Frequency distribution of biomass, 100-seed weight, and seed yield for soybean varieties (lines)

共检测到15个SNP同时控制2个或2个以上的性状: (1)与生物量关联的SNP中, 位点BARC- 013333-00485具有较低的 P值, 在2年环境中均能被检测到且与单株籽粒产量共位; 位点BARC- 029051-06057在2年环境均能被检测到, 且同时控制生物量、百粒重和单株籽粒产量3个性状; 位点BARC-030807-06945与单株籽粒产量共位, 但仅在一个环境中被检测到。这3个SNP可能包含同时控制生物量及产量组分的基因。(2)与百粒重关联的SNP中, 共有6个同时控制2个或2个以上的性状, 且均与单株籽粒产量共位。其中位点BARC- 028709-05992在两年环境中均被检测到与单株籽粒产量共位, 对该位点的继续研究有助于鉴定同时控制百粒重和单株籽粒产量的基因; 位点BARC- 029051-06057仅在一个环境被检测到, 但是同时与生物量和单株籽粒产量共位, 这个位点可能存在同时控制3个性状的基因; (3)与单株籽粒产量关联的SNP中, 有6个同时控制2个或2个以上的性状, 且大部分均在一个环境中被检测到与其他性状共位, 只有位点BARC-028709-05992在2年环境中均被检测到与百粒重共位。

参照郝德荣等对叶绿素荧光参数^{[ 19]}及对多个环境产量相关性状^{[ 15]}定位结果: (1)与生物量关联的SNP位点中, 3个与叶绿素含量共位, 2个与多个环境下被检测到与单株荚数和单株粒数的SNP共位。 (2)与百粒重关联的SNP位点中, 8个与叶绿素含量和快速叶绿素荧光参数显著关联的SNP共位; 8个与多个环境下的产量相关性状定位结果共位, 且均与多个环境下检测到与百粒重关联的SNP共位; (3)与单株籽粒产量关联的SNP位点中, 4个与叶绿素含量和快速叶绿素荧光参数关联的SNP共位; 1个与多个环境下检测到与单株荚数和单株粒数的SNP共位; 1个与多个环境下检测到与百粒重和产量的SNP共位。

3 讨论

大豆鼓粒期(R6)是决定大豆产量的关键时期^{[ 20, 21]}, 此时不仅光合速率及光化学活性高, 而且光合产物也明显增加, 更重要的是这些光合产物大量运往结实器官中^{[ 21]}。张贤泽等^{[ 20]}对大豆鼓粒期的群体光合速率研究发现其和产量呈高度相关, 相关系数 r = 0.9289。黄中文等^{[ 16]}利用重组自交系群体对地下和地上部生物量与产量相关的动态的研究发现, 随生长进程, 相关系数逐渐增加, 至鼓粒期达到最大。但是关于生物量与产量之间也存在不相关的报道^{[ 22]}, 一个可能原因是所用的材料或群体大小不同。因此有必要在具有更大生物量和产量变异范围群体中开展这方面的研究。本文发现, 鼓粒期生物量与百粒重及单株籽粒产量呈极显著正相关, 这启示育种者提高鼓粒期生物量是大豆获得高产至关重要的因素, 提高该时期植株的生物量将有助于结实器官中光合产物的积累。

随着二代测序技术的迅速发展, 植物基因组数据海量增加, 显著增加了利用分子标记进行重要性状基因定位的有效性和利用MAS育种的可行性^{[ 23]}。这些技术允许我们系统地分析来自于不同地理区域的品种, 利用高通量的测定工具和全基因组关联分析的方法, 鉴定新的目标基因用于作物改良。为了检测大豆基因组内与生物量, 百粒重和单株籽粒产量相关的SNP, 本研究在自然群体中, 利用关联分析的方法定位研究这些性状。在两年环境下共检测到个41、56和29个SNP与生物量、百粒重和单株籽粒产量显著关联, 其中仅有6、19和1个SNP在2个环境中均被稳定检测到分别与生物量、百粒重和单株籽粒产量显著关联。2年环境下, 与生物量和单株籽粒产量稳定关联的SNP较少可能与其遗传率较低、遗传基础复杂且易受环境影响有关^{[ 15, 16]}。Fulton等^{[ 24]}研究认为, 在多个不同的环境中都能检测到的QTL可能比那些对表型变异表现出高解释率、但只能在特定环境中检测到的QTL更有用。对照郝德荣等^{[ 15]}在5个环境中对产量相关性状定位的研究结果, 3个以上环境与百粒重关联的SNP位点中, BARC- 018515-02927、BARC-018985-03048、BARC- 028709- 05992、BARC-029185-06106、BARC-030931-06978、BARC-040075-07652和BARC-040407-07733与本文在2个环境中均能稳定检测到的与百粒重关联SNP中共位; 3个环境中与产量关联的BARC-028709- 05992位点与在本研究的两个环境中均能检测到与单株籽粒产量显著关联。这些在多年环境中稳定表达的SNP在育种中可能具有较大的利用价值。另外, 本研究共检测到15个SNP同时控制2个或2个以上性状。位于第19染色体上的BARC-029051-06057位点被检测到同时与生物量、百粒重和单株籽粒产量3个性状关联; Thumma等^{[ 25]}指出, 如果两个性状的QTL在染色体上共区间, 则表明这两个性状间很有可能存在因果关系。对这些共位SNP的鉴定表明, 这3个性状间存在紧密的联系, 该结果与3个性状间相关分析结果一致; 同时生物量与百粒重和单株籽粒产量的共位表明控制它们的基因可能存在一因多效现象。共区间内可能含有控制生物量的基因, 该基因的表达可同时影响百粒重及单株籽粒产量。这些结果对于我们通过提高光合性能, 增加鼓粒期生物量来增加作物产量提供了一定的理论基础。

表3 自然群体中与大豆生物量及产量组分显著关联的SNP位点 Table 3 SNPs with significant association signals (-lg P≥2.00, P ≤0.01) for soybean biomass and yield components detected in soybean natural population

(续表3-1) 自然群体中与大豆生物量及产量组分显著关联的SNP位点 Table 3(Continued) SNPs with significant association signals (-lg P≥2.00, P ≤0.01) for soybean biomass and yield components detected in soybean natural population

标记 Marker	染色体 Chr.	图位 Position	显著性 -lg P		贡献率 R²		共位性状 Co-located traits
标记 Marker	染色体 Chr.	图位 Position	2011	2012	2011	2012	共位性状 Co-located traits
百粒重Seed weight
BARC-041325-07964	1	49225474	2.02	ns	2.03	nd
BARC-043251-08566	1	54220124	2.12	ns	2.12	nd
BARC-025183-06457	2	10630264	ns	2.10	nd	1.55
BARC-040187-07679	2	45947482	2.21	ns	2.22	nd
BARC-014927-01924	3	39794924	2.59	ns	2.57	nd
BARC-029185-06106	3	40131490	6.61	5.98	5.52	4.93	SW^cABS/RC^b
BARC-028709-05992	3	40654334	2.89	3.81	2.27	3.07	SY^acABS/RC^bETo/ABS^bPI_ABS^bETo/TRo^bSW^c
BARC-029415-06172	3	40805223	2.62	2.49	2.6	2.47
BARC-029415-06173	3	40805223	2.62	2.49	2.6	2.47
BARC-030319-06856	3	47004061	ns	2.49	nd	2.47
BARC-024297-04834	4	1113839	2.21	ns	1.64	nd
BARC-029605-06243	4	1135712	2.14	ns	2.15	nd
BARC-015061-02551	4	31994543	ns	2.28	nd	1.68	SY^a CCI^b
BARC-041047-07901	4	48958879	2.26	ns	1.68	nd	SY^a
BARC-019085-03298	5	35086840	2.89	ns	2.85	nd
BARC-025707-05009	6	16658998	2.08	ns	2.11	nd
BARC-038923-07396	6	48634819	2.05	ns	2.05	nd
BARC-029831-06445	7	2471566	ns	2.17	nd	2.18
BARC-014665-01613	8	12471297	2.31	ns	2.31	nd
BARC-032791-09038	8	14265200	2.10	ns	2.1	nd
BARC-038877-07374	8	17940650	2.30	ns	2.3	nd	SY^a
BARC-019733-04335	8	18092162	2.30	2.02	2.3	2.01
BARC-021577-04150	8	18143243	2.17	ns	2.18	nd
BARC-018515-02927	9	44398393	3.27	3.71	3.23	3.61	SW^c
BARC-028317-05828	9	44665115	2.60	3.23	2.59	3.16
BARC-031123-06999	9	44972687	ns	2.64	nd	2.62	CCI^b
BARC-016773-02317	10	38523322	2.07	2.30	1.51	1.69
BARC-041935-08142	10	49905563	2.05	ns	1.49	nd
BARC-040407-07733	11	30159557	3.61	2.64	3.55	2.6	SN^cSW^c
BARC-040075-07652	11	30159839	3.61	2.64	3.55	2.6	SN^cSW^c
BARC-044181-08640	12	553693	ns	2.06	nd	1.49
BARC-040509-07765	12	3002434	ns	2.16	nd	1.58	ABS/RC^b
BARC-030931-06978	13	1699386	3.57	3.60	3.52	3.51	SW^c
BARC-018985-03048	13	1766981	4.88	4.97	4.75	4.79	SW^c
BARC-018551-02971	13	8529286	ns	2.36	nd	2.34
BARC-024259-04819	13	20484707	2.28	2.62	2.28	2.59
BARC-041671-08065	13	30268682	2.21	ns	1.64	nd
BARC-042075-08173	13	32480622	ns	2.01	nd	1.45
BARC-014657-01608	13	37023802	2.13	ns	2.16	nd
BARC-018741-03001	13	41885605	2.74	ns	2.76	nd
BARC-024525-04961	14	3997614	2.21	2.01	2.21	2
BARC-045151-08895	14	7917464	ns	2.07	nd	2.06	SY^aCCI^b
BARC-018959-03045	15	1303817	2.44	2.39	2.44	2.36
BARC-042857-08439	15	3828443	2.68	ns	2.07	nd
BARC-039433-07497	15	4395340	2.89	2.13	2.88	2.12
BARC-029343-06156	15	42276598	2.38	3.79	1.81	3.07

(续表3-2) 自然群体中与大豆生物量及产量组分显著关联的SNP位点

(续表3-2) 自然群体中与大豆生物量及产量组分显著关联的SNP位点 Table 3-2(Continued)SNPs with significant association signals (-lg P≥2.00, P ≤0.01) for soybean biomass and yield components detected in soybean natural population

标记 Marker	染色体 Chr.	图位 Position	显著性 -lg P		贡献率 R²		共位性状 Co-located traits
标记 Marker	染色体 Chr.	图位 Position	2011	2012	2011	2012	共位性状 Co-located traits
BARC-040087-07654	15	47628308	2.02	2.82	1.48	2.18	ETo/ABS^b ETo/Tro^b PI_ABS^b
BARC-042895-08450	16	31292708	ns	2.11	nd	2.11	CCI^b
BARC-032251-08930	17	15485936	2.24	ns	2.24	nd
BARC-018479-02918	18	1243529	2.24	ns	2.24	nd
BARC-038795-07333	18	50205922	2.02	ns	2.02	nd
BARC-018117-02529	19	5531602	2.44	ns	2.52	nd
BARC-013481-00498	19	42334572	3.34	3.26	3.3	3.19
BARC-044913-08838	19	43125170	2.15	ns	2.17	nd
BARC-029051-06057	19	47906580	ns	2.24	nd	1.63	SY^a Biomass^a
BARC-021827-04218	19	48091800	ns	2.41	nd	2.38	SW^c
单株籽粒产量Seed yield per plant
BARC-030807-06945	1	53063797	ns	4.51	nd	4.35	Biomass^a PN^cSN^c
BARC-014927-01924	3	39794924	ns	2.02	nd	2.39
BARC-028709-05992	3	40654334	2.92	3.88	2.73	3.71	SY^cSW^acABS/RC^bETo/ABS^bPI_ABS^b
BARC-016977-02171	4	7533029	2.07	ns	2.5	nd
BARC-015061-02551	4	31994543	ns	2.60	nd	2.34	SW^aCCI^b
BARC-041047-07901	4	48958879	3.61	ns	3.48	nd
BARC-040033-07641	5	34734702	ns	2.21	nd	2.61
BARC-028171-05783	5	37928020	ns	2.47	nd	2.21
BARC-020259-04536	5	37999262	ns	2.40	nd	2.15
BARC-027726-06646	8	9489476	2.03	ns	2.45	nd
BARC-028297-05816	8	14653588	ns	2.10	nd	1.83
BARC-038877-07374	8	17940650	2.24	ns	2.7	nd
BARC-013333-00485	8	45285760	ns	2.89	nd	3.42	Biomass^a
BARC-021491-04133	9	6593074	ns	2.70	nd	2.46
BARC-018911-03272	10	3519980	2.08	ns	2.5	nd
BARC-032347-08952	10	43920755	2.24	ns	2.02	nd
BARC-018693-02992	10	47121190	2.66	ns	3.2	nd	CCI^b
BARC-025709-05013	12	39889639	2.31	ns	2.09	nd
BARC-028887-06033	13	36556810	ns	2.92	nd	3.41
BARC-025561-06521	13	36822597	ns	2.66	nd	2.41
BARC-045151-08895	14	7917464	ns	2.54	nd	2.98	SW^aCCI^b
BARC-013235-00458	15	50333637	ns	2.49	nd	2.93
BARC-016069-02054	16	1351860	2.40	ns	2.9	nd
BARC-039151-07458	17	41489651	4.07		3.99
BARC-031583-07115	19	36278536	2.59	ns	2.39	nd
BARC-022451-04330	19	37951038	ns	2.07	nd	3.27
BARC-029051-06057	19	47906580	ns	2.77	nd	2.54	Biomass^a SW^a
BARC-021827-04218	19	48091720	3.06	ns	3.65	nd
BARC-021343-04041	20	2049166	2.39	ns	2.18	nd

^a: 参照本研究结果共位的性状;^b: 参照郝德荣等对叶绿素荧光定位结果, 与本研究共位的性状^{[ 19]};^c: 参照郝德荣等^{[ 15]}对多个环境产量定位结果, 与本研究共位的性状; R²: 贡献率; ns: 相应的环境中关联不显著; nd: 没有数据; CCI: 叶绿素含量; F_v/ F_m: PSII最大光化学产量; ABS/RC: 单位反应中心吸收的光能; ETo/Tro: 用于电子传递的量子产额; ETo/ABS: 用于电子传递的量子产额; PI_ABS: 以吸收光能为基础的性能指数; SW: 百粒重; PN: 单株荚数; SN: 单株粒数; SY: 单株籽粒产量。

^a: The traits co-located with the results of the present study;^b: The traits co-located with the previous results of the chlorophyll and chlorophyll fluorescence^{[19]; c}: The traits co-located with the previous results of yield and yield components in soybean across multiple environments^{[ 15]}; R²: Contribution rate; ns: Marker was not detected at significant level in corresponding environment; nd: no data; CCI: Chlorophyll content; F_v/ F_m: quantum efficiency of open reaction center; ABS/RC: energy absorbed by RC of photosynthetic apparatus; ETo/TRo: probability that a trapped exciton moves an electron into the electron transport chain beyond QA^-; ETo/ABS: Quantum yield for electron transport; PI_ABS: performance index; SW: 100-seed weight; PN: number of pods per plant; SN: number of seeds per plant; SY: seed yield per plant.

(续表3-2) 自然群体中与大豆生物量及产量组分显著关联的SNP位点 Table 3-2(Continued) SNPs with significant association signals (-lg P≥2.00, P ≤0.01) for soybean biomass and yield components detected in soybean natural population

作物生物量的主要决定因素是整个生育期光合速率的累计量, 反映了植物源强度的高低, 也是植物光合效率的体现; 单株荚数和单株粒数则反映了植物库的大小及强度^{[ 26, 27]}, 库的强度则直接决定了同化物的分配; 而百粒重和单株籽粒产量事实上是光合有效辐射事件的产物, 是源、库关系协调的最终表现。大豆产量形成的实质是源库流互作的过程^{[ 27]}。在本文鉴定到与生物量相关的SNP中, BARC-030807- 06945和BARC-042035-08159与郝德荣等^{[ 15]}对单株荚数和株粒数的定位结果共位; 这些结果表明源、库之间可能具有共同的遗传基础, 且高度协调来完成整个生长过程,但是也存在单独控制源、流、库的基因或QTL, 对于某些具有较高收获指数的材料, 提高生物量及光合效率可能更有效果。

叶绿素是植物叶绿体内参与光合作用的重要色素之一^{[ 28]}, 快速叶绿素荧光参数则在对植物无损伤的情况下更加方便、准确地反映光合器官内各生理生化反应步骤上的能量传递情况^{[ 29]}, 因而, 叶绿素含量和快速叶绿素荧光参数均有可能影响光合速率的大小。参照郝德荣等^{[ 19]}对叶绿素荧光参数定位结果, 本研究与生物量关联的SNP位点中BARC- 028289-05814、BARC-029969-06761和BARC- 029969-06762与郝德荣等对叶绿素含量的定位结果共位, 表明这些位点可能包含同时控制叶绿素含量和生物量的基因, 控制叶绿素含量的基因也可能通过影响光合效率而影响作物的生物量; 与百粒重和单株籽粒产量关联的位点中, 存在多个SNP与快速叶绿素荧光参数及叶绿素含量共位。这些位点的存在表明光合效率和大豆产量之间存在紧密联系。另外, 本研究中位点BARC-028709-05992在2个环境中均被检测到与百粒重和单株籽粒产量关联, 且与多个叶绿素荧光参数^{[ 19]}及对多个环境产量相关性状^{[ 15]}定位结果共位, 对该位点的继续研究有助于鉴定同时控制百粒重和单株籽粒产量的及光合相关性状的基因。有明确的证据表明C₃植物的最大光合速率在自然群体中存在很大的变异^{[ 30]}, 鉴定那些决定这些变异的遗传基础, 将提供新的信息来制定改良作物产量的新策略。对大豆而言 ε_i(有效辐射的截获效率)和 ε_p(生物量转换为种子的部分即收获指数)已经最大化( ε_i = 0.9 / ε_p = 0.6), 只有很少的改良空间^{[ 18]}, 但大豆 ε_c值(有效辐射转换为生物量的效率)却远远低于理论值。试图改变光合代谢来改变 ε_c值对于增加大豆生物量及最终实现大豆单株产量的提高是很有意义的。需要指出的是, 光合速率的微小增加(6%~10%)可以导致生物量的巨大增加(30%)^{[ 31]}。因此, 阐明光合作用的机制, 提高光合效率是增加作物产量的一个新目标^{[ 18]}。同时, 高光效种质的发掘及从种质资源库中寻找更有效的等位基因进行遗传转化可能是今后植物高产研究的一个重要方向。

对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[ 16, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]}。例如, 本研究检测到第11染色体上2个紧密相邻的SNP位点(BARC- 040407-07733和BARC-040075-07652)在所有环境中均与百粒重显著关联, 这2个标记位于Specht等^{[ 35]}检测到的百粒重QTL位点Sat_095相同的基因组区域; 而位于同一染色体上的与生物量稳定关联的BARC-016279-02316位点则与黄中文等^{[ 16, 33]}检测到的R6期生物量和收获期生物量QTL ( qSBB1-2、 qBMB1-1)处于相同QTL内。与生物量关联的BARC- 022037-04263 (位于第17染色体)则与Kim等^{[ 34]}利用2个重组自交系群体检测到的叶长QTL (Satt372)紧密相邻。这些结果表明, 本研究利用SNP进行的全基因组关联分析可以有效地检测控制大豆生物量及产量组分的QTL。这些一致性SNP/QTL位点将是进一步研究大豆生物量及产量组分遗传机制的候选区域, 对这些关键位点候选基因的挖掘与研究, 对于今后提高大豆的生物量及最终的作物产量将提供重要分子信息。在本研究中, 为了保证试验条件的一致性, 最大程度缩减环境因素对产量的影响, 试验分两年在南京进行, 突出了遗传差异, 所发掘的SNP位点具有普适性。但是, 大豆是光温敏感作物, 将各生态区材料集中在一个地方种植有可能并不能真实地表现出其产量特性, 因此, 在以后的研究中, 为了进一步估计环境因素对结果的影响及鉴定那些在多个环境中能够稳定表达的SNP, 今后仍需在异地及多年环境安排全部材料再做统一鉴定, 以验证本研究结果。

4 结论

大豆鼓粒期的生物量与百粒重和单株籽粒产量存在极显著的正相关及共同的遗传基础。在自然群体中两年共鉴定到41、56和29个SNP分别与生物量、百粒重和单株籽粒产量显著关联, 其中仅有6、19和1个SNP在2个环境中均被稳定检测到。共检测到15个SNP同时控制2个或2个以上性状。鉴定到的多个SNP与郝德荣等定位的叶绿素荧光参数及多个环境产量相关性状共位, 这些位点的存在对于挖掘产量及光合作用有关的基因提供了有价值的标记信息。

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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[20]	张贤泽, 马占峰, 赵淑文, 庞士铨. 大豆不同品种光合速率与产量关系的研究. 作物学报, 1986, 12: 43-48 Zhang Z X, Ma Z F, Zhao S W, Pang S C. The relationship between net photosynthetic rate and yield formation in soybean. Acta Agron Sin, 1986, 12: 43-48 (in Chinese with English abstract) [本文引用:2] [CJCR: 1.8267]
[21]	杜维广, 张桂茹, 满为群, 栾晓燕, 陈怡, 谷秀芝. 大豆科学, 1999, 18: 154-159 Du W G, Zhang G R, Man W Q, Luan X Y, Chen Y, Gu X Z. Study on relationship between soybean photosynthesis and yield. Soybean Sci, 1999, 18: 154-159 (in Chinese with English abstract) [本文引用:2]
[22]	Mehetre S S, Jamadagni B M. Biomass partitioning and growth characters in relation to plant architecture in soybean. Soybean Genet Newsl, 1996, 23: 92-97 [本文引用:1]
[23]	Schneeberger K, Weigel D. Fast-forward genetics enabled by new sequencing technologies. Trends Plant Sci, 2011, 16: 282-288 [本文引用:1] [JCR: 11.047]
[24]	Fulton T M, Beck-Bunn T, Emmatty D, Eshed Y, Lopez J, Petiard V, Uhlig J, Zamir D, Tanksley S D. QTL analysis of an advanced backcross of lycopersicon peruvianum to the cultivated tomato and comparisons with QTLs found in other wild species. Theor Appl Genet, 1997, 95: 881-894 [本文引用:1] [JCR: 3.297]
[25]	Thumma B R, Naidu B P, Chand ra A, Cameron D F, Bahnisch L M, Liu C. Identification of causal relationships among traits related to drought resistance in Stylosanthes scabra using QTL analysis. J Exp Bot, 2001, 52: 203-214 [本文引用:1] [JCR: 5.364]
[26]	龚月桦, 高俊凤. 高等植物光合同化物的运输与分配. 西北植物学报, 1999, 19: 564-570 Gong Y H, Gao J F. Transport and partitioning of photoassimilate in higher plant. Acta Bot Boreal-Occident Sin, 1999, 19: 564-570 (in Chinese with English abstract) [本文引用:1]
[27]	王玲玲, 杜吉到, 郑殿峰, 宋微微, 陈丽霞, 田静斋, 吕美芳. 大豆源库流关系的研究进展. 大豆科学, 2009, 28: 167-171 Wang L L, Du J D, Zheng D F, Song W W, Chen L X, Tian J Z, Lü M F. Advances in the studies of relation among source sink and flux of soybean. Soybean Sci, 2009, 28: 167-171 (in Chinese with English abstract) [本文引用:2]
[28]	Liu W, Fu Y, Hu G, Si H, Zhu L, Wu C, Sun Z. Identification and fine mapping of a thermo-sensitive chlorophyll deficient mutant in rice (Oryza sativa L. ). Planta, 2007, 226: 785-795 [本文引用:1] [JCR: 3.0]
[29]	印志同, 孟凡凡, 宋海娜, 晁毛妮, 许晓明, 邓德祥, 喻德跃. 大豆开花盛期快速叶绿素荧光参数的 QTL 分析. 中国农业科学, 2011, 44: 4980-4987 Yin Z T, Meng F F, Song H N, Chao M N, Xu X M, Deng D X, Yu D Y. QTL mapping for fast chlorophyll fluorescence parameters in soybean. Sci Agric Sin, 2011, 44: 4980-4987 (in Chinese with English abstract) [本文引用:1] [CJCR: 1.4522]
[30]	Flood P J, Harbinson J, Aarts M G M. Natural genetic variation in plant photosynthesis. Trends Plant Sci, 2011, 16: 327-335 [本文引用:1] [JCR: 11.047]
[31]	Lefebvre S, Lawson T, Fryer M, Zakhleniuk O V, Lloyd J C, Raines C A. Increased sedoheptulose-1, 7-bisphosphatase activity in transgenic tobacco plants stimulates photosynthesis and growth from an early stage in development. Plant Physiol, 2005, 138: 451-460 [本文引用:1] [JCR: 6.535]
[32]	Orf J H, Chase K, Jarvik T, Mansur L M, Cregan P B, Adler F R, Lark K G. Genetics of soybean agronomic traits: I. Comparison of three related recombinant inbred populations. Crop Sci, 1999, 39: 1642-1651 [本文引用:1] [JCR: 1.641]
[33]	黄中文, 赵团结, 喻德跃, 陈受宜, 盖钧镒. 大豆产量有关性状QTL的检测. 中国农业科学, 2009, 42: 4155-4165 Huang Z W, Zhao T J, Yu D Y, Chen S Y, Gai J Y. Detection of QTLs of yield related traits in soybean. Sci Agric Sin, 2009, 42: 4155-4165 (in Chinese with English abstract) [本文引用:2] [CJCR: 1.4522]
[34]	Kim H K, Kang S T, Suh D Y. Analysis of quantitative trait loci associated with leaflet types in two recombinant inbred lines of soybean. Plant Breed, 2005, 124: 582-589 [本文引用:2] [JCR: 1.596]
[35]	Specht J E, Chase K, Macrand er M, Graef G L, Chung J, Markwell J P, Germann M, Orf J H, Lark K G. Soybean response to water: a QTL analysis of drought tolerance. Crop Sci, 2001, 41: 493-509 [本文引用:2] [JCR: 1.641]
[36]	Mian M A R, Bailey M A, Tamulonis J P, Shipe E R, Carter T E, Parrott W A, Ashley D A, Hussey R S, Boerma H R. Molecular markers associated with seed weight in two soybean populations. Theor Appl Genet, 1996, 93: 1011-1016 [本文引用:1] [JCR: 3.297]
[37]	Csanadi G, Vollmann J, Stift G, Lelley T. Seed quality QTLs identified in a molecular map of early maturing soybean. Theor Appl Genet, 2001, 103: 912-919 [本文引用:1] [JCR: 3.297]
[38]	Lee S H, Park K Y, Lee H S, Park E H, Boerma H R. Genetic mapping of QTLs conditioning soybean sprout yield and quality. Theor Appl Genet, 2001, 103: 702-709 [本文引用:1] [JCR: 3.297]
[39]	Guzman P S, Diers B W, Neece D J, St Martin S K, LeRoy A R, Grau C R, Hughes T J, Nelson R L. QTL associated with yield in three backcross-derived populations of soybean. Crop Sci, 2007, 47: 111-122 [本文引用:1] [JCR: 1.641]
[40]	Funatsuki H, Kawaguchi K, Matsuba S, Sato Y, Ishimoto M. Mapping of QTL associated with chilling tolerance during reproductive growth in soybean. Theor Appl Genet, 2005, 111: 851-861 [本文引用:1] [JCR: 3.297]
[41]	Hoeck J A, Fehr W R, Shoemaker R C, Welke G A, Johnson S L, Cianzio S R. Molecular marker analysis of seed size in soybean. Crop Sci, 2003, 43: 68-74 [本文引用:1] [JCR: 1.641]
[42]	Hyten D L, Pantalone V R, Sams C E, Saxton A M, Land au-Ellis D, Stefaniak T R, Schmidt M E. Seed quality QTL in a prominent soybean population. Theor Appl Genet, 2004, 109: 552-561 [本文引用:1] [JCR: 3.297]

2008

0.0

0.1053

... 大豆在农业生产中占有重要地位, 是人类重要的植物蛋白源^[1], 提高大豆产量一直是大豆育种的核心问题^[2] ...

1995

0.0

0.1053

... 大豆在农业生产中占有重要地位, 是人类重要的植物蛋白源^[1], 提高大豆产量一直是大豆育种的核心问题^[2] ...

2010

0.0

... 生物量和收获指数是决定作物经济产量的2个主要因素^[3] ...

1989

2.041

0.0

... 以往通过传统的一些育种途径使得作物产量得到了很大提高, 但主要是通过农艺措施与收获指数的提高^[4,5,6], 很少是由于生物量的增加 ...

1998

1.641

0.0

... 以往通过传统的一些育种途径使得作物产量得到了很大提高, 但主要是通过农艺措施与收获指数的提高^[4,5,6], 很少是由于生物量的增加 ...

2010

2.474

0.0

... 以往通过传统的一些育种途径使得作物产量得到了很大提高, 但主要是通过农艺措施与收获指数的提高^[4,5,6], 很少是由于生物量的增加 ...

2011

5.364

0.0

... 对世界的两大重要作物水稻与小麦而言, 收获指数的提高已经进入瓶颈阶段, 进一步提高作物产量迫切需要增加作物的生物量^[7] ...

2009

0.0

1.8267

Acta Agron Sin. 2009, 35(8):1483 - 1490 DOI:10.3724/SP.J.1006.2009.01483

Dynamic Analysis of Biomass Accumulation and Partition in Soybean with Different Yield Levels

大豆不同产量水平生物量积累与分配的动态分析

HUANG Zhong-Wen^1,2,ZHAO Tuan-Jie¹,GAI Jun-Yi^1,*

黄中文^1,2，赵团结¹，盖钧镒^1,*

1Soybean Research Institute，Nanjing Agricultural University/National Center for Soybean Improvement/National Key Laboratory for Crop Genetics and Germplasm Enhancement，Nanjing 210095，Jiangsu；2Department of Agronomy,Henan Institute of Science and Technology,Xinxiang 453003,China

The dynamic correlation between yield and above- and below-ground biomass and the dynamic partition of biomass of high, medium and low yield lines were studied by using the population of recombinant inbred lines NJRIKY derived from a cross between parents with different biomass and yield potential levels to obtain some information for dynamic control of biomass accumulation in high yield breeding and management of soybean. The results obtained were as follows: (1) Yield was significantly and positively correlated with above- and below-ground biomass accumulation, their correlation increased during the growing stages and the peak correlation occurred at seed filling stage (R5–R6) withr= 0.76 for below-ground biomass and 0.79 for above-ground biomass. (2) The high yield lines (2 500–2 800 kg ha^-1) had a significant higher below-ground and above-ground biomass accumulation than the medium yield and low yield lines. Both below- and above-ground biomass accumulation reached the peak at seed filling stage with the highest below-ground biomass of 660–700kg ha^-1and above-ground biomass of 720–780 kg ha^-1 at R5.(3) The composition of high yield lines was not consistent in the two years. Lines with decreased yield had also a decreased biomass, which demonstrated reduction of biomass accumulation caused by different environments was the reason for yield decrease. (4) The dynamic partition of biomass to stem and petiole during growing stages in high yield lines (30.8% and 10.6% at R5, respectively) was significantly higher than that in medium and low yield lines and the dynamic partition of biomass to leaf and root during growing stages in high yield lines (34.1% and 9.7% at R5, respectively) was significantly lower than that in medium and low yield lines. The results implied that the more increase of yield in the future depends on the comprehensive genetic improvement of both biomass and harvest index and the successive advancement of growth regulation technology in soybean.

利用亲本间生物量、产量有较大差异的重组自交家系群体(NJRIKY)，在相对控制遗传背景的条件下研究地下和地上部生物量与产量相关的动态，比较高中低产家系生物量累积和分配的动态特征，为大豆高产栽培管理和育种提供生物量动态调控与选择的依据。结果表明: (1)地下部和地上部生物量与产量显著相关，随生长进程，相关系数逐渐增加，至鼓粒期(R5~R6期)相关系数达到最大，r分别约0.76和0.79；(2)大田条件2 500~2 800 kg hm^-2以上的高产家系，地下部和地上部生物量显著高于中、低产家系，最大累积值均出现在鼓粒期，地下部和地上部生物量最大值分别为660~700 kg hm^-2和7 200~7 800 kg hm^-2。(3)两年高产组所包含的家系不尽相同，产量下降的家系相应生物量也下降，这归因于环境所致的生物量累积不足；(4)高产家系各器官生物量分配动态特征为茎秆、叶柄占同时期全生物量的比例显著高于中、低产家系，R5时分别为30.8%和10.6%，而叶、根比例显著低于中、低产家系，R5时分别为34.1%和9.7%。未来大豆产量的突破有赖于品种生物量与收获指数的综合改良和生长调控技术的继续改进。

... 生物量是植株基因型C、N积累能力、栽培措施、环境因素的综合结果^[8], 与后期籽粒产量有紧密的相互关系^[9] ...

2005

1.641

0.0

... 生物量是植株基因型C、N积累能力、栽培措施、环境因素的综合结果^[8], 与后期籽粒产量有紧密的相互关系^[9] ...

1999

1.641

0.0

... 近年来, 大豆育种家已经鉴定许多与产量有关的QTL或SNP, 主要关乎成熟期, 株高, 百粒重和生长习性等与产量相关的性状^{[10,11,12,13,14,15]}, 但关于生育期内大豆生物量积累的研究却很少, 仅有黄中文等^[16]利用重组自交系群体作过初步研究, 需要强调的是对育种利用而言, 只有那些在多数环境和多数遗传材料中都稳定表达的QTL才具有应用价值^[17] ...

2002

1.641

0.0

2004

1.641

0.0

2007

1.641

0.0

2009

3.297

0.0

Theor Appl Genet. 2009, 119(3):417 - 427 DOI:10.1007/s00122-009-1049-7

QTL in mega-environments: I. Universal and specific seed yield QTL detected in a population derived from a cross of high-yielding adapted?×?high-yielding exotic soybean lines

Laura Palomeque(1) Liu Li-Jun(2) Wenbin Li(3) Bradley Hedges(4) Elroy R. Cober(5) Istvan Rajcan(1)

1.Department of Plant Agriculture, Crop Science Building, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, Canada
2.Soybean Research Institute of Heilongjiang, Harbin, Heilongjiang People’s Republic of China
3.Soybean Research Institute of the Northeast Agricultural University, Harbin, Heilongiang People’s Republic of China
4.Pioneer Hi-bred Ltd, A DuPont Company, Chatham, ON Canada
5.Agriculture and Agrifood Canada, Eastern Cereal and Oilseed Crop Research Centre, Ottawa, ON Canada

Modern soybean [(Glycine max (L.) Merrill] breeding programs rely primarily on the use of elite × elite line crosses to develop high-yielding cultivars. Favorable alleles for traits of interest have been found in exotic germplasm but the successful introduction of such alleles has been hampered by the lack of adaptation of the exotic parent to local mega-environment and difficulties in identifying superior progeny from elite × exotic crosses. The objective of this study was to use a population derived from a cross between an adapted and an exotic elite line to understand the genetic causes underlying adaptation to two mega-environments (China and Canada). A cross between a high-yielding Canadian cultivar ‘OAC Millennium’ and an elite Chinese cultivar ‘Heinong 38’ was performed to develop a recombinant inbred line (RIL) population. The RIL population was evaluated in China and Canada in multiple environments from 2004 to 2006. Significant variation for seed yield was observed among the RILs in both the Chinese and Canadian environment. Individual RILs performed differently between the Chinese and Canadian environments suggesting differential adaptation to intercontinental mega-environments. Seven seed yield quantitative trait loci (QTL) were identified of which five were mega-environment universal QTL (linked to markers Satt100, Satt162, Satt277, Sat_126, and the interval of Satt139-Sat_042) and two were mega-environment-specific QTL (at marker intervals, Satt194-SOYGPA and Satt259-Satt576). Seed yield QTL located near Satt277 has been confirmed and new QTL have been identified explaining between 9 and 37% of the phenotypic variation in seed yield. The QTL located near Satt100 explained the greatest amount of variation ranging from 18 to 37% per environment. Broad sense heritability ranged from 89 to 64% among environments. Epistatic effects have been identified in both mega-environments with pairs of markers explaining between 9 and 14% of the phenotypic variation in seed yield. An improved understanding of the type of QTL action as either universal or mega-environment-specific QTL as well as their interaction may facilitate the development of strategies to introgress specific high-yielding alleles from Chinese to North American germplasm and vice versa to sustain efforts in breeding of high-yielding soybean cultivars.

2012

3.297

0.0

. 2012, 124:447-458

Identification of single nucleotide polymorphisms and haplotypes associated with yield and yield components in soybean (Glycine max) landraces across multiple environments

Hao D , Cheng H , Yin Z , Cui S , Zhang D , Wang H , Yu D

Genome-wide association analysis is a powerful approach to identify the causal genetic polymorphisms underlying complex traits. In this study, we evaluated a population of 191 soybean landraces in five environments to detect molecular markers associated with soybean yield and its components using 1,536 single-nucleotide polymorphisms (SNPs) and 209 haplotypes. The analysis revealed that abundant phenotypic and genetic diversity existed in the studied population. This soybean population could be divided into two subpopulations and no or weak relatedness was detected between pair-wise landraces. The level of intra-chromosomal linkage disequilibrium was about 500 kb. Genome-wide association analysis based on the unified mixed model identified 19 SNPs and 5 haplotypes associated with soybean yield and yield components in three or more environments. Nine markers were found co-associated with two or more traits. Many markers were located in or close to previously reported quantitative trait loci mapped by linkage analysis. The SNPs and haplotypes identified in this study will help to further understand the genetic basis of soybean yield and its components, and may facilitate future high-yield breeding by marker-assisted selection in soybean.

... MLM将各个体的Q作为协变量, Kinship值作为随机效应, 将表型数据分别对标记变异进行回归分析, P[15]的方法 ...

... 参照郝德荣等对叶绿素荧光参数^[19]及对多个环境产量相关性状^[15]定位结果: (1)与生物量关联的SNP位点中, 3个与叶绿素含量共位, 2个与多个环境下被检测到与单株荚数和单株粒数的SNP共位 ...

... 2年环境下, 与生物量和单株籽粒产量稳定关联的SNP较少可能与其遗传率较低、遗传基础复杂且易受环境影响有关^[15,16] ...

... 对照郝德荣等^[15]在5个环境中对产量相关性状定位的研究结果, 3个以上环境与百粒重关联的SNP位点中, BARC- 018515-02927、BARC-018985-03048、BARC- 028709- 05992、BARC-029185-06106、BARC-030931-06978、BARC-040075-07652和BARC-040407-07733与本文在2个环境中均能稳定检测到的与百粒重关联SNP中共位 ...

... 在本文鉴定到与生物量相关的SNP中, BARC-030807- 06945和BARC-042035-08159与郝德荣等^[15]对单株荚数和株粒数的定位结果共位 ...

... 另外, 本研究中位点BARC-028709-05992在2个环境中均被检测到与百粒重和单株籽粒产量关联, 且与多个叶绿素荧光参数^[19]及对多个环境产量相关性状^[15]定位结果共位, 对该位点的继续研究有助于鉴定同时控制百粒重和单株籽粒产量的及光合相关性状的基因 ...

2008

0.0

1.8267

Acta Agron Sin. 2008, 34(6):944 - 951 DOI:10.3724/SP.J.1006.2008.00944

Correlation and QTL Mapping of Biomass Accumulation, Apparent Har-vest Index, and Yield in Soybean

大豆生物量积累、收获指数及产量间的相关与QTL分析

HUANG Zhong-Wen¹²,ZHAO Tuan-Jie¹,YU De-Yue¹,CHEN Shou-Yi³,GAI Jun-Yi^1*

黄中文^1,2;赵团结¹;喻德跃¹;陈受宜³;盖钧镒^1,*

1 Soybean Research Institute, Nanjing Agricultural University / National Center for Soybean Improvement / National Key Laboratory for Crop Ge-netics and Germplasm Enhancement, Nanjing 210095, Jiangsu; 2 Department of Agronomy, Henan Institute of Science and Technology, Xinxiang 453003, Henan; 3 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China

Since soybean seed yield is the product of both biomass accumulation and harvest index, the objective of the present study was to measure the correlations of seed yield with the other two traits as well as with biomass accumulation at different seed development stages, to map their QTLs, and to reveal the QTL basis of the correlations. A RIL population, NJRIKY, derived from the cross between Nannong 1138-2 and Kefeng 1, quite diverse in biomass, harvest index and yield, was used to study the correla-tion among biomass accumulation, apparent harvest index and yield, to map the QTLs of the traits for revealing the genetic basis of the correlation among the traits. The results obtained were as follows: (1) Yield was closely and positively correlated with bio-mass accumulation and their correlation increased in the process of growth with the highest R2=0.76 at harvest stage. There ap-peared some negative exponential correlation between yield and biomass at R1, R3, and R5, with the biomass of 1 000, 2 300, and 5 500 kg ha^-1 as the highest turning point, respectively. A linear correlation of yield with biomass at harvest stage [BM (H)] was detected, but without upper limit of the biomass found in the present experiment. There was an exponential correlation between yield and apparent harvest index, with 0.42 as the turning point, positive relationship as less than 0.42 and negative relationship as larger than 0.42. (2) 9, 10, and 10 QTLs for yield, apparent harvest index and BM (H) were detected in NJRIKY and 2, 3, and 3 QTLs of them respectively detected in both years. In addition, 6, 9, and 6 QTLs for biomass at R1, R3, and R5 were identified in the population, respectively, with 2 of them being detected across R1 through R5 in both years. (3) Among the 9 yield QTLs, 6 marker intervals were found to have QTLs conferring biomass and apparent harvest index, which implied a partially common genetic basis among the three traits.

利用亲本间生物量、收获指数和产量有较大差异的南农1138-2和科丰1号杂交衍生的大豆重组自交家系(NJRIKY), 研究始花期(R1)、始荚期(R3)、始粒期(R5)、收获期生物量以及表观收获指数和产量间的相关, 并进行QTL定位, 分析相关的遗传基础。结果表明, (1) 生物量与产量显著相关, 相关程度随生长进程逐渐增加, 收获期生物量与产量相关最高, R²=0.76。R1、R3、R5期生物量与产量的相关呈负指数曲线相关, 生物量分别达到1 000、2 300和5 500 kg hm^-2时, 产量不再随生物量的增加而增加。收获期生物量与产量呈直线正相关, 在试验范围内未发现高产的收获期生物量上限。表观收获指数与产量呈指数曲线相关, 小于0.42时与产量具正变关系, 大于0.42时与产量具负变关系。收获期生物量与表观收获指数呈指数曲线相关, 表观收获指数增加生物量降低。(2) 检测到产量、表观收获指数、收获期生物量有关的QTL分别为9、10和10个, 其中两年稳定的QTL分别有2、3、3个。检测到R1、R3和R5期生物量有关的QTL分别有6、9和6个, 其中3个时期在两年均能稳定表达的有2个。(3)在9个产量QTL中的6个区间, 还同时检测到生物量和表观收获指数有关的QTL, 该3性状有部分QTL共享同一连锁区间, 表明有其共同的遗传基础, 同时也解释了性状间相关的遗传原因。

... 黄中文等^[16]利用重组自交系群体对地下和地上部生物量与产量相关的动态的研究发现, 随生长进程, 相关系数逐渐增加, 至鼓粒期达到最大 ...

... 2年环境下, 与生物量和单株籽粒产量稳定关联的SNP较少可能与其遗传率较低、遗传基础复杂且易受环境影响有关^[15,16] ...

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

... 而位于同一染色体上的与生物量稳定关联的BARC-016279-02316位点则与黄中文等^[16,33]检测到的R6期生物量和收获期生物量QTL (qSBB1-2、qBMB1-1)处于相同QTL内 ...

2009

0.0

1.8267

2011

5.215

0.0

. 2011, 35:38-52

Accelerating yield potential in soybean: potential targets for biotechnological improvement

Ainsworth E A , Yendrek C R , Skoneczka J A , Long S P

Soybean (Glycine max Merr.) is the world's most widely grown legume and provides an important source of protein and oil. Global soybean production and yield per hectare increased steadily over the past century with improved agronomy and development of cultivars suited to a wide range of latitudes. In order to meet the needs of a growing world population without unsustainable expansion of the land area devoted to this crop, yield must increase at a faster rate than at present. Here, the historical basis for the yield gains realized in the past 90 years are examined together with potential metabolic targets for achieving further improvements in yield potential. These targets include improving photosynthetic efficiency, optimizing delivery and utilization of carbon, more efficient nitrogen fixation and altering flower initiation and abortion. Optimization of investment in photosynthetic enzymes, bypassing photorespiratory metabolism, engineering the electron transport chain and engineering a faster recovery from the photoprotected state are different strategies to improve photosynthesis in soybean. These potential improvements in photosynthetic carbon gain will need to be matched by increased carbon and nitrogen transport to developing soybean pods and seeds in order to maximize the benefit. Better understanding of control of carbon and nitrogen transport along with improved knowledge of the regulation of flower initiation and abortion will be needed to optimize sink capacity in soybean. Although few single targets are likely to deliver a quantum leap in yields, biotechnological advances in molecular breeding techniques that allow for alteration of the soybean genome and transcriptome promise significant yield gains.

... 产量性状是非常复杂的数量性状, 具有较低的遗传力且涉及大量基因的表达与调控, 更容易受环境影响^[18] ...

... 6), 只有很少的改良空间^[18], 但大豆ε_c值(有效辐射转换为生物量的效率)却远远低于理论值 ...

... 因此, 阐明光合作用的机制, 提高光合效率是增加作物产量的一个新目标^[18] ...

2012

1.554

0.0

Euphytica. 2012, 186(3):919 - 931 DOI:10.1007/s10681-012-0697-x

Genome-wide association analysis detecting significant single nucleotide polymorphisms for chlorophyll and chlorophyll fluorescence parameters in soybean (Glycine max) landraces

Derong Hao⁽¹⁾⁽²⁾,Maoni Chao⁽¹⁾,Zhitong Yin⁽³⁾,Deyue Yu

⁽¹⁾

1.National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China

2.Jiangsu Yanjiang Institute of Agricultural Sciences, Nantong, 226541, China

3.Jiangsu Provincial Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009, China

Abstract
Chlorophyll fluorescence parameters are generally used to characterize the intrinsic action of photosystem II (PSII), which is interrelated with the photosynthetic capacity. Mapping of quantitative trait loci for chlorophyll fluorescence parameters and associated traits is important for genetic improvement in soybean. In this study, a genome-wide association analysis was conducted to detect key single-nucleotide polymorphisms (SNPs) associated with chlorophyll content (chl) and chlorophyll fluorescence using 1,536 SNPs in a soybean landraces panel. The analysis revealed significant correlations among chl and five chlorophyll fluorescence parameters, including maximum quantum yield of PSII primary photochemistry in the dark-adapted state (Fv/Fm), light energy absorbed per reaction center (ABS/RC), quantum yield for electron transport (ETo/ABS), probability that a trapped exciton moves an electron into the electron transport chain beyond QA⁻ (ETo/TRo), and performance index on absorption basis (PI_ABS). Genome-wide association analysis using a mixed linear model detected 51 SNPs associated with chl and chlorophyll fluorescence parameters. Among these identified SNPs, 14 SNPs were co-associated with two or more different traits in this study, and 8 SNPs were co-associated with soybean yield and yield components in our previous study. These significant SNPs will help to better understand the genetic basis of photosynthesis-related physiological traits, and facilitate the pyramiding of favorable alleles for photosynthetic traits in soybean marker assisted selection schemes for high photosynthetic efficiency.

... 参照郝德荣等^[19]对叶绿素荧光参数定位结果, 本研究与生物量关联的SNP位点中BARC- 028289-05814、BARC-029969-06761和BARC- 029969-06762与郝德荣等对叶绿素含量的定位结果共位, 表明这些位点可能包含同时控制叶绿素含量和生物量的基因, 控制叶绿素含量的基因也可能通过影响光合效率而影响作物的生物量 ...

1986

0.0

1.8267

... 3 讨论大豆鼓粒期(R6)是决定大豆产量的关键时期^[20,21], 此时不仅光合速率及光化学活性高, 而且光合产物也明显增加, 更重要的是这些光合产物大量运往结实器官中^[21] ...

... 张贤泽等^[20]对大豆鼓粒期的群体光合速率研究发现其和产量呈高度相关, 相关系数r = 0 ...

1999

0.0

1996

0.0

... 但是关于生物量与产量之间也存在不相关的报道^[22], 一个可能原因是所用的材料或群体大小不同 ...

2011

11.047

0.0

Trend Plant Sci. 2011, 16(5):282 - 288 DOI:10.1016/j.tplants.2011.02.006

Fast-forward genetics enabled by new sequencing technologies

New sequencing technologies are dramatically accelerating progress in forward genetics, and the use of such methods for the rapid identification of mutant alleles will be soon routine in many laboratories. A straightforward extension will be the cloning of major-effect genetic variants in crop species. In the near future, it can be expected that mapping by sequencing will become a centerpiece in efforts to discover the genes responsible for quantitative trait loci. The largest impact, however, might come from the use of these strategies to extract genes from non-model, non-crop plants that exhibit heritable variation in important traits. Deployment of such genes to improve crops or engineer microbes that produce valuable compounds heralds a potential paradigm shift for plant biology.

... 随着二代测序技术的迅速发展, 植物基因组数据海量增加, 显著增加了利用分子标记进行重要性状基因定位的有效性和利用MAS育种的可行性^[23] ...

1997

3.297

0.0

... Fulton等^[24]研究认为, 在多个不同的环境中都能检测到的QTL可能比那些对表型变异表现出高解释率、但只能在特定环境中检测到的QTL更有用 ...

2001

5.364

0.0

... Thumma等^[25]指出, 如果两个性状的QTL在染色体上共区间, 则表明这两个性状间很有可能存在因果关系 ...

1999

0.0

... 单株荚数和单株粒数则反映了植物库的大小及强度^[26,27], 库的强度则直接决定了同化物的分配 ...

2009

0.0

... 单株荚数和单株粒数则反映了植物库的大小及强度^[26,27], 库的强度则直接决定了同化物的分配 ...

... 大豆产量形成的实质是源库流互作的过程^[27] ...

2007

3.0

0.0

Planta. 2007, 226(3):785 - 795 DOI:10.1007/s00425-007-0525-z

Identification and fine mapping of a thermo-sensitive chlorophyll deficient mutant in rice (Oryza sativaL.)

Wenzhen Liu(12) Yaping Fu(2) Guocheng Hu(2) Huamin Si(2) Li Zhu(2) Chao Wu(2) Zongxiu Sun(2)

1.Zhejiang University College of Life Sciences 310029 Hangzhou ZJ China
2.China National Rice Research Institute State Key Laboratory of Rice Biology 359 Tiyuchang Road 310006 Hangzhou ZJ China

A thermo-sensitive chlorophyll deficient mutant was isolated from more than 15,000 transgenic rice lines. The mutant displayed normal phenotype at 23°C or lower temperature (permissive temperature). However, when grown at 26°C or higher (nonpermissive temperature) the plant exhibited an abnormal phenotype characterized by yellow green leaves. Genetic analysis revealed that a single nuclear-encoded recessive gene is responsible for the mutation, which is tentatively designed ascde1(t) (chlorophyll deficient 1, temporally). PCR analysis and hygromycin resistance assay indicated the mutation was not caused by T-DNA insertion. To isolate thecde1(t) gene, a map-based cloning strategy was employed and 15 new markers (five SSR and ten InDels markers) were developed. A high-resolution physical map of the chromosomal region around thecde1(t) gene was made using F₂ and F₃ population consisting of 1,858 mutant individuals. Finally, thecde1(t) gene was mapped in 7.5 kb region between marker ID10 and marker ID11 on chromosome 2. Sequence analysis revealed only one candidate gene,OsGluRS, in the 7.5 kb region. Cloning and sequencing of the target region from thecde1(t) mutant showed that a missense mutation occurred in the mutant. So theOsGluRS gene (TIGR locus Os02 g02860) which encode glutamyl-tRNA synthetase was identified as theCde1(t) gene.

... 叶绿素是植物叶绿体内参与光合作用的重要色素之一^[28], 快速叶绿素荧光参数则在对植物无损伤的情况下更加方便、准确地反映光合器官内各生理生化反应步骤上的能量传递情况^[29], 因而, 叶绿素含量和快速叶绿素荧光参数均有可能影响光合速率的大小 ...

2011

0.0

1.4522

Sci Agric Sin. 2011, 44(24):4980 - 4987 DOI:10.3864/j.issn.0578-1752.2011.24.002

QTL Mapping for Fast Chlorophyll Fluorescence Parameters in Soybean

大豆开花盛期快速叶绿素荧光参数的QTL分析

YIN Zhi-Tong, MENG Fan-Fan, SONG Hai-Na, CHAO Mao-Ni, XU Xiao-Ming, DENG De-Xiang, YU De-Yue

印志同, 孟凡凡, 宋海娜, 晁毛妮, 许晓明, 邓德祥, 喻德跃

1.南京农业大学国家大豆改良中心/作物遗传与种质创新国家重点实验室，南京 210095
2.扬州大学农学院/作物遗传生理江苏省重点实验室/植物功能基因组学教育部重点实验室，江苏扬州 225009
3.南京农业大学生命科学学院，南京210095

【Objective】 The present study is aimed to identify QTL associated with fast chlorophyll fluorescence parameters (JIP parameters), examine the genetic relationships among different parameters, and compare the genetic base underlying the parameters between the two growth stages of R2 and R6 in soybean. 【Method】 A pot experiment was carried out to evaluate five JIP parameters at R2 growth stage using 184 recombinant inbred lines (RILs) derived from a cross between two varieties of Kefeng 1 and Nannong 1138-2, and then the QTL of above parameters were detected and mapped. 【Result】 A total of 16 QTL, located on linkage groups (LGs) A1, C2, D2, I, M, N and O, respectively, were identified, and explained phenotypic variation ranging from 4.40% to 20.06% with the LOD score from 2.40 to 5.65. Three major genomic regions were detected to be associated with several parameters simultaneously, which were between markers Satt286 and Satt316 on LG C2, marker Sat_418 and Satt650 on LG I, and marker Sat_231 and sat_196 on LG O, respectively. 【Conclusion】 Different JIP parameters might be controlled by the same or different genes. Most of the QTL associated with JIP parameters were not detected consistently at R2 and R6 growth stage, indicating that the genetic mechanism underlying the JIP parameters is relatively complicated. The marker interval between Sat_231 and Sat_196 on LG O was detected at both R2 and R6 growth stage, and this genomic region may contain stably expressing genes underlying the intrinsic features of the photosynthetic apparatus and be useful in the breeding practice of soybean.

【目的】定位大豆R2时期（开花盛期）快速叶绿素荧光参数（JIP参数）QTL，分析不同参数间的遗传关系，比较参数在R2和R6时期（鼓粒盛期）遗传基础的异同。【方法】以大豆品种科丰1号和南农1138-2及其杂交衍生的184份重组自交系为材料，在盆栽条件下测定R2时期JIP参数，检测其QTL。【结果】检测到16个JIP参数QTL，分布在连锁群A1、C2、D2、I、M、N和O上，单个QTL的LOD值为2.40—5.65，贡献率为4.40%—20.06%；检测到3个同时控制多个参数的染色体区间，分别是连锁群C2上标记区间Satt286—Satt316、连锁群I上标记区间Sat_418—Satt650和连锁群O上标记区间Sat_231—Sat_196。【结论】不同JIP参数间既有共同的控制基因（QTL），也有各自独特的控制基因；JIP参数多数QTL不能在R2和R6时期重复检测到，控制其表达的遗传机制较为复杂；连锁群O上标记区间Sat_231—Sat_196在大豆R2和R6时期均检测到，该区间可能存在稳定表达的控制光合器官内禀结构和功能的基因，具有一定的育种价值。

2011

11.047

0.0

Trend Plant Sci. 2011, 16(6):327 - 335 DOI:10.1016/j.tplants.2011.02.005

Natural genetic variation in plant photosynthesis

Natural genetic variation in plant photosynthesis is a largely unexplored and as a result an underused genetic resource for crop improvement. Numerous studies show genetic variation in photosynthetic traits in both crop and wild species, and there is an increasingly detailed knowledge base concerning the interaction of photosynthetic phenotypes with their environment. The genetic factors that cause this variation remain largely unknown. Investigations into natural genetic variation in photosynthesis will provide insights into the genetic regulation of this complex trait. Such insights can be used to understand evolutionary processes that affect primary production, allow greater understanding of the genetic regulation of photosynthesis and ultimately increase the productivity of our crops.

... 有明确的证据表明C₃植物的最大光合速率在自然群体中存在很大的变异^[30], 鉴定那些决定这些变异的遗传基础, 将提供新的信息来制定改良作物产量的新策略 ...

2005

6.535

0.0

... 需要指出的是, 光合速率的微小增加(6%~10%)可以导致生物量的巨大增加(30%)^[31] ...

1999

1.641

0.0

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

2009

0.0

1.4522

Sci Agric Sin. 2009, 42(12):4155 - 4165

Detection of QTLs of Yield Related Traits in Soybean

大豆产量有关性状QTL的检测

HUANG Zhong-wen, ZHAO Tuan-jie, YU De-yue, CHEN Shou-yi, GAI Jun-yi

黄中文,赵团结,喻德跃,陈受宜,盖钧镒

（国家大豆改良中心/南京农业大学大豆研究所/作物遗传与种质创新国家重点实验室）

【Objective】 The present study was aimed to reveal the correlation between yield and biomass, leaf area and yield components, and to detect and map the QTLs of the yield-related traits. 【Method】 The 184 recombinant inbred lines derived from a cross between geographically and genetically distant parents, Kefeng 1 from northern China and Nannong 1138-2 from southern China, were tested in two years and then analyzed for detecting and mapping QTLs of the traits related to yield. 【Result】 A very significant positive correlation was observed between yield and above ground biomass, leaf area index, root weight, canopy width and canopy height with r values of 0.5-0.7. Seven QTLs of above ground biomass were mapped with contribution rate of 6.2%-21.1% and one QTL (qSBO-1) repeatedly detected in both years while eight QTLs of root weight mapped with contribution rate of 5.2%-20.1% and one QTL (qRTB1-1) repeatedly detected. Five QTLs of R1 leaf area index were mapped with contribution rate of 6.4%-17.2% while five QTLs of R3 leaf area index mapped with contribution rate of 7.3%-26.2% and one QTL (qLAIR3A2) repeatedly detected. Four QTLs of canopy width were mapped with contribution rate of 6.3%-13.1% and one QTL (qCWD1b-2) repeatedly detected while 11 QTLs of canopy height mapped with contribution rate of 5.2%-9.2% and four QTLs repeatedly detected. Six, two and one QTL of 100-seed weight, number of seeds per pod and number of pods per plant, respectively, were mapped with their contribution rate of 6.9%-15.7%. Five and three QTLs of number of pods on branches and number of pods on main stem, respectively, were mapped with their contribution rate of 6.3%-11.1%. Eight and three QTLs of number of nodes on main stem and effective number of branches, respectively, were mapped with their contribution rate of 4.7%-15.2%. There was one QTL shared by above ground biomass and root weight, two QTLs shared by R1 and R3 leaf area index, two QTLs by canopy width and height, one by yield and number of pods per plant, one by 100-seed weight and number of pods on branches, one by number of seeds per pod and number of nodes on main stem, and one by number of pods on branches and effective number of branches. 【Conclusion】 A total of 68 QTLs were mapped for 13 yield-related traits. Among them, only a small part was repeatedly detected in both years, implied their expression depended on years or environmental conditions. Although significant correlations existed among the traits extensively, only a small part of the QTLs was shared between the traits, which indicted different gene systems for various traits. There were few QTLs with large contribution found in the yield-related traits, thus breeding technology for pyramiding multiple genes should be considered for yield improvement.

【目的】研究大豆产量和生物量、叶面积指数、冠层以及产量构成因素间的相关性,定位控制这些性状的QTL。【方法】以地理和遗传来源均有较大差异的北方亲本科丰1号和南方亲本南农1138-2所衍生的184个重组自交家系2年有重复的田间试验结果进行产量有关性状的QTL分析。【结果】（1）产量与地上部生物量、叶面积指数、根重、冠层宽和高等均有极显著正相关,相关系数0.5～0.7。（2）地上部生物量检测到7个QTL,贡献率6.2%～21.1%,其中2年重复检出1个（qSBO-1）;根重8个QTL,贡献率5.2%～20.1%,重复检出1个（qRTB1-1）。（3）开花期叶面积指数5个QTL,贡献率6.4%～17.2%;结荚期叶面积指数5个QTL,贡献率7.3%～26.2%,重复检出1个（qLAIR3A2）;冠层宽4个QTL,贡献率6.3%～13.1%,重复检出1个（qCWD1b-2）;冠层高11个QTL,贡献率5.2%～9.2%,重复检出4个（qCHH-1、qCHO-1、qCHO-2和qCHO-3）。（4）百粒重6个,荚粒数2个,荚数1个QTL,贡献率6.9%～15.7%;分枝荚数5个,主茎荚数3个QTL,贡献率6.3%～11.1%;主茎节数8个QTL,有效分枝数3个QTL,贡献率4.7%～15.2%。（5）根重和地上部生物量各有1个,R1(始花期)和R3(始荚期)叶面积指数各有2个,冠层宽和高各有2个,产量与荚数各有1个,百粒重和分枝荚数各有1个,荚粒数和主茎节数各有1个,分枝荚数与有效分枝数各有1个共享的QTL。【结论】大豆产量有关的13个性状共检测到68个QTL;年份间有重复检出的,但不多,其表达较大程度上与环境有关;尽管性状间普遍有相关、有共享的QTL,但不多,各有其遗传体系;产量有关性状中很少有贡献率大的主效QTL,产量育种要考虑多数基因聚合的技术。

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

2005

1.596

0.0

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

... 与生物量关联的BARC- 022037-04263 (位于第17染色体)则与Kim等^[34]利用2个重组自交系群体检测到的叶长QTL (Satt372)紧密相邻 ...

2001

1.641

0.0

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

... 例如, 本研究检测到第11染色体上2个紧密相邻的SNP位点(BARC- 040407-07733和BARC-040075-07652)在所有环境中均与百粒重显著关联, 这2个标记位于Specht等^[35]检测到的百粒重QTL位点Sat_095相同的基因组区域 ...

1996

3.297

0.0

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

2001

3.297

0.0

Theor Appl Genet. 2001, 103(6-7):912 - 919 DOI:10.1007/s001220100621

Seed quality QTLs identified in a molecular map of early maturing soybean

G. Csanádi(1) J. Vollmann(2) G. Stift(1) T. Lelley(1)

1.Department of Plant Biotechnology, Institute for Agrobiotechnology, Konrad Lorenz Strasse 20, A-3430 Tulln, Austria e-mail: lelley@ifa-tulln.ac.at Tel.: +43 2272/66280 204 AT
2.Department of Plant Breeding, University of Agricultural Sciences Vienna, Gregor Mendel Strasse 33, A-1180 Vienna, Austria AT

This study identified QTLs influencing seed quality characters in a cross of two early maturing soybean (Glycine max [L.] Merr.) cultivars (Ma.Belle and Proto) adapted to the short growing seasons of Central Europe. A molecular linkage map was constructed by using 113 SSR, 6 RAPD and 1 RFLP markers segregating in 82 individuals of an F₂ population. The map consists of 23 linkage groups and corresponds wellto previously published soybean maps. Using phenotypic data of the F₂-derived lines grown in five environments, four markers for protein content, three for oil content and eight for seed weight were identified. Four from fifteen seed quality QTL-regions identified in the present study were also found by other authors. Markers associated with seed weight QTLs were consistent across all environments and proved to have effects large enough to be useful in a marker-assisted breeding program, whereas protein and oil QTLs showed environmental interactions.

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

2001

3.297

0.0

Theor Appl Genet. 2001, 103(5):702 - 709 DOI:10.1007/s001220100595

Genetic mapping of QTLs conditioning soybean sprout yield and quality

S. H. Lee(1) K. Y. Park(2) H. S. Lee(1) E. H. Park(3) H. R. Boerma(4)

1.School of Plant Science, Seoul National University, Suwon 441-744, The Republic of Korea KR
2.National crop Experiment Station, Suwon 441-100, The Republic of Korea KR
3.Faculty of Biological Resources, Yeungnam University, Gyongsan 712-749, The Republic of Korea KR
4.Department of Crop and Soil Sciences, The University of Georgia, Athens, GA 30602-7272, USA US

Soybean sprouts have been used as a food in the Orient since ancient times. In this study, 92 restriction fragment length polymorphism (RFLP) loci and two morphological markers (W1andT) were used to identify quantitative trait loci (QTLs) associated with soybean sprout-related traits in 100 F₂-derived lines from the cross of ’Pureunkong’×’Jinpumkong 2’. The genetic map consisted of 76 loci which covered about 756 cM and converged into 20 linkage groups. Eighteen markers remained unlinked. Phenotypic data were collected in 1996 and 1997 for hypocotyl length, percentage of abnormal seedlings, and sprout yield 6 days after germination at 20°C. Hypocotyl length was determined as the average length from the point of initiation of the first secondary root to the point of attachment of the cotyledons. The number of decayed seeds and seedlings, plus the number of stunted seedlings (less than 2-cm growth), was recorded a s abnormal seedlings. Seed weight was determined based on the 50-seed sample. Sprout yield was recorded as the total fresh weight of soybean sprouts produced from the 50-seed sample divided by the dry weight of the 50-seed sample. Four QTLs were associated with sprout yield in the combined analysis across 2 years. For the QTL linked to L154 on the Linkage Group (LG) G the positive allele was derived from Pureunkong (R²= 0.19), whereas at the other three QTLs (A089 on LG B1, A668n on LG K and B046 on LG L) the positive alleles were from Jinpumkong 2. QTLs conditioning seed weight were linked to markers A802n (LG B1), A069 (LG E), Cr321 (LG F) and A235 (LG G). At these four markers, the Jinpumkong allele increased seed weight. Markers K011n on LG B1,W1 on LG F and A757 on LG L were linked to QTLs conditioning hypocotyl length; and Bng119, K455n and K418n to QTLs conditioning the abnormal seedlings. The QTLs conditioning sprout yield were in the same genomic locations as the QTLs for seed weight identified in this population or from previously published research, indicating that QTLs for sprout yield are genetically linked to seed-weight QTLs or else that seed-weight QTLs pleiotropically condition sprout yield. These data demonstrate that effective marker-assisted selection may be feasible for enhancing sprout yield in a soybean. The transgressive segregation of sprout yield, as well as the existence of two QTLs conditioning greater than 10% of the phenotypic variation in sprout yields provides an opportunity to select for progeny lines with a greater sprout yield than currently preferred cultivars such as Pureunkong.

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

2007

1.641

0.0

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

2005

3.297

0.0

Theor Appl Genet. 2005, 111(5):851 - 861 DOI:10.1007/s00122-005-0007-2

Mapping of QTL associated with chilling tolerance during reproductive growth in soybean

H. Funatsuki(1) K. Kawaguchi(12) S. Matsuba(1) Y. Sato(1) M. Ishimoto(1)

1.National Agricultural Research Center for Hokkaido Region (NARCH), Hitsujigaoka, Toyohira-Ku, Sapporo, 062-8555 Japan
2.Ministry of Agriculture, Forestry and Fisheries, Kasumigaseki, Tokyo, 100-8950 Japan

Low temperatures in summer bring about drastic reduction in seed yield of soybean [Glycine max (L.) Merr.]. To identify quantitative trait loci (QTL) associated with chilling tolerance during the reproductive growth in soybean, a recombinant inbred line (RIL) population consisting of 104 F₆-derived lines was created from a cross between two cultivars, chilling-tolerant Hayahikari and chilling-sensitive Toyomusume. The RIL were genotyped with 181 molecular and phenotypic markers and were scored with regard to chilling tolerance, which was evaluated by comparison of seed-yielding abilities in two artificial climatic environments at chilling and usual temperatures. Three QTL were detected for chilling tolerance in seed-yielding ability. Two of them,qCTTSW1 andqCTTSW2, were mapped near QTL for flowering time, and the latter had an epistatic interaction with a marker locus located near another QTL for flowering time, where no significant QTL for chilling tolerance was detected. The analysis of an F₂ population derived from the cross between Hayahikari and an RIL of the Hayahikari genotype at all QTL for flowering time confirmed the effect of the third QTL,qCTTSW3, on chilling tolerance and suggested thatqCTTSW1 was basically independent of the QTL for flowering time. The findings and QTL found in this study may provide useful information for marker-assisted selection (MAS) and further genetic studies on soybean chilling tolerance.

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

2003

1.641

0.0

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...

2004

3.297

0.0

Theor Appl Genet. 2004, 109(3):552 - 561 DOI:10.1007/s00122-004-1661-5

Seed quality QTL in a prominent soybean population

D. L. Hyten(15) V. R. Pantalone(1) C. E. Sams(1) A. M. Saxton(2) D. Landau-Ellis(1) T. R. Stefaniak(3) M. E. Schmidt(4)

1.Department of Plant Sciences The University of Tennessee 252 Ellington Plant Science Building, 2431 Joe Johnson Drive Knoxville TN 37996 USA
2.Department of Animal Science The University of Tennessee Knoxville TN 37996 USA
3.Department of Agronomy University of Kentucky Lexington KY 40546 USA
4.Department of Plant, Soil, and General Agriculture Southern Illinois University Carbondale IL 62901 USA
5.Soybean Genomics and Improvement Laboratory USDA-ARS-PSI Building 006, 10300 Baltimore Avenue Beltsville MD 20705 USA

Soybean [Glycine max (L.) Merr.] is a versatile crop due to its multitude of uses as a high protein meal and vegetable oil. Soybean seed traits such as seed protein and oil concentration and seed size are important quantitative traits. The objective of this study was to identify representative protein, oil, and seed size quantitative trait loci (QTL) in soybean. A recombinant inbred line (RIL) population consisting of 131 F₆-derived lines was created from two prominent ancestors of North American soybeans ( lsquo

Essex

and

Williams

) and the RILs were grown in six environments. One hundred simple sequence repeat (SSR) markers spaced throughout the genome were mapped in this population. There were a total of four protein, six oil, and seven seed size QTL found in this population. The QTL found in this study may assist breeders in marker-assisted selection (MAS) to retain current positive QTL in modern soybeans while simultaneously pyramiding additional QTL from new germplasm.

... 对照前人用连锁分析检测到的与生物量和产量相关性状的QTL, 本研究检测到的SNP位于这些QTL内或与其紧密相邻^{[16,32,33,34,35,36,37,38,39,40,41,42]} ...