Genetic dissection of wheat uppermost-internode diameter and its association with agronomic traits in five recombinant inbred line populations at various field environments

Uppermost-internode diameter (UID) is a key morphological trait associated with spike development and yield potential in wheat. Our understanding of its genetic basis remains largely unknown. Here, quantitative trait loci (QTLs) for UID with high-density genetic maps were identified in five wheat recombinant inbred line (RIL) populations. In total, 25 QTLs for UID were detected in five RIL populations, and they were located on chromosomes 1A, 1D (3 QTL), 2B (2), 2D (3), 3B, 3D, 4A, 4B (3), 4D, 5A (5), 5B (2), 6B, and 7D. Of them, five major and stable QTLs (QUid.sau-2CN-1D.1, QUid.sau-2SY-1D, QUid.sau-QZ-2D, QUid.sau-SC-3D, and QUid.sau-AS-4B) were identified from each of the five RIL populations in multiple environments. QUid.sau-2CN-1D.1, QUid.sau-2SY-1D and QUid.sau-SC-3D are novel QTLs. Kompetitive Allele Specific PCR (KASP) markers tightly linked to them were further investigated for developing near-isogenic lines (NILs) carrying the major loci. Furthermore, candidate genes at these intervals harboring major and stable QTLs were predicted, and they were associated with plant development and water transportation in most cases. Comparison of physical locations of the identified QTL on the ‘Chinese Spring’ reference genome showed that several QTLs including two major ones, QUid.sau-2CN-1D.1 and QUid.sau-2SY-1D, are likely allelic confirming their validity and effectiveness. The significant relationships detected between UID and other agronomic traits and a proper UID were discussed. Collectively, our results dissected the underlying genetic basis for UID in wheat and laid a foundation for further fine mapping and map-based cloning of these QTLs.     

大豆二粒荚长、宽相关QTL间上位效应和QE互作效应分析

【目的】定位大豆二粒荚长、宽QTL,并分析QTL间的上位效应和与环境（QTL-by-environment, QE）的互作效应。【方法】利用Charleston×东农594重组自交系及其F2:14-F2:18代的重组自交系的147个株系为试验材料,164个SSR引物经亲本筛选后用于群体扩增构建的SSR遗传图谱,利用混合区间作图法,对2006-2010年连续5年一个地点的大豆二粒荚长、宽进行QTL定位,并作加性效应、加性×加性上位互作效应及环境互作效应分析。【结果】检测到8对有加性效应的二粒荚长QTL,加性效应的总贡献率27.2%,与环境互作总贡献率达到10.19%;6对有加性效应的二粒荚宽QTL,加性效应的总贡献率16.27%,与环境互作总贡献率达到12.18%。9对影响二粒荚长的加性×加性上位互作效应的QTL,可解释该性状总变异的9.02%;8对影响二粒荚宽的加性×加性上位互作效应的QTL,可解释该性状总变异的8.81%。【结论】上位效应和环境效应在二粒荚长、宽性状的遗传中起了重要作用,因此,在分子标记辅助育种中应该考虑对效应起主要作用的QTL和上位性QTL,又要考虑微效多基因的聚合。     

大豆鲜荚籽粒上位性QTL及其互作效应分析

荚粒是大豆主要的收获器官,直接影响鲜食大豆品种审定和产品出口。然而,荚粒性状由多基因控制,目前主要集中在加性数量性状位点（quantitative trait loci,QTL）发掘方面,对上位性QTL及其互作效应报道甚少。鉴于此,通过鉴定大豆重组自交系（recombinant inbred line,RIL）群体2年4种环境条件下鲜荚和籽粒的长度、宽度、重量等相关性状,发掘控制其上位性QTLs,并研究其互作效应,结果发现,8种测试性状共检测到321对“加性×加性”上位性QTLs,涉及所有染色体,构成复杂的上位性QTLs互作网络,其中包括144对正向效应和177对负向效应QTLs,并以13号染色体分布数量最多;进一步分析发现,存在34对“一因多效”加性×加性上位性QTLs,且加性×加性上位性QTLs间的互作贡献率为1.89%~4.85%,高于其与环境互作贡献率,说明遗传因素为主;上述34对QTLs涉及18条染色体,其中包含定位区间一致的23对“一因多效”QTLs,并有6组上位性QTLs以“一对多”方式发挥功能,16组以“一对一”方式发挥作用。上述结果不仅为实现大豆荚粒性状精准分子遗传改良提供了选择标记,并为进一步揭示大豆荚粒性状分子遗传机制提供了依据。     

不同环境下大豆荚粒性状的遗传与QTL分析

【目的】探讨大豆荚粒性状之间以及与产量之间的相互关系及其遗传机制,并定位控制其性状的QTL。【方法】以栽培大豆晋豆23为母本,半野生大豆灰布支黑豆为父本所衍生的474个重组自交系,通过3年2个重复的试验结果,用多年多点联合分析方法对荚粒及产量等9个性状进行遗传分析及数量性状定位。【结果】相关分析结果表明,产量与百粒重、粒长、单株粒重、2粒荚、3粒荚呈现显著或极显著正相关,在三年两地共定位了6个产量QTL、4个百粒重QTL、10个单株粒重QTL、2个粒宽QTL、5个粒长QTL、7个1粒荚QTL、5个2粒荚QTL、7个3粒荚QTL和5个4粒荚QTL。【结论】在不同年份和环境下检测到的QTL,可作为荚粒性状改良的候选染色体区段,用于分子标记辅助选择,同时也要注意环境的影响。     

A stable and major QTL region on chromosome 2 conditions pod shape in cultivated peanut (Arachis hyopgaea L.)

Peanut pod shape is a heritable trait which affects the market acceptance of in-shell peanut products. In order to determine the genetic control of pod shape, six component traits of pod shape (pod length, pod width, pod length/width ratio, pod roundness, beak degree and constriction degree) were measured using an image-based phenotyping method. A recombinant inbred line (RIL) population consisting of 181 lines was phenotyped across three environments. Continuous distributions and transgressive segregations were demonstrated in all measured traits and environments. Significant correlations were found among most component traits with broad-sense heritability ranging from 0.87 to 0.95. Quantitative trait locus (QTL) analysis yielded 26 additive QTLs explaining 3.79 to 52.37% phenotypic variations. A novel, stable and major QTL region conditioning multiple shape features was detected on chromosome 2, which spans a 10.81-Mb genomic region with 543 putative genes. Bioinformatics analysis revealed several candidate genes in this region. In addition, 73 pairs of epistatic interactions involving 92 loci were identified for six component traits explaining 0.94–6.45% phenotypic variations. These results provide new genetic loci to facilitate genomics-assisted breeding of peanut pod shape.     

QTL analysis for plant height and fine mapping of two environmentally stable QTLs with major effects in soybean

Plant height is an important agronomic trait, which is governed by multiple genes with major or minor effects. Of numerous QTLs for plant height reported in soybean, most are in large genomic regions, which results in a still unknown molecular mechanism for plant height. Increasing the density of molecular markers in genetic maps will significantly improve the efficiency and accuracy of QTL mapping. This study constructed a high-density genetic map using 4 011 recombination bin markers developed from whole genome re-sequencing of 241 recombinant inbred lines (RILs) and their bi-parents, Zhonghuang 13 (ZH) and Zhongpin 03-5373 (ZP). The total genetic distance of this bin map was 3 139.15 cM, with an average interval of 0.78 cM between adjacent bin markers. Comparative genomic analysis indicated that this genetic map showed a high collinearity with the soybean reference genome. Based on this bin map, nine QTLs for plant height were detected across six environments, including three novel loci (qPH-b_11, qPH-b_17 and qPH-b_18). Of them, two environmentally stable QTLs qPH-b_13 and qPH-b_19-1 played a major role in plant height, which explained 10.56–32.7% of the phenotypic variance. They were fine-mapped to 440.12 and 237.06 kb region, covering 54 and 28 annotated genes, respectively. Via the function of homologous genes in Arabidopsis and expression analysis, two genes of them were preferentially predicted as candidate genes for further study.     

大豆蛋白质和油分含量QTL定位及互作分析

【目的】定位大豆蛋白质和油分含量QTL及互作分析,为大豆品质性状QTL精细定位和分子辅助育种提供基础。【方法】以Charleston和东农594为亲本,构建了含147个株系的重组自交系,以F2:19-F2:20代重组自交系为试验材料,利用Windows QTL Cartographer V. 2.5软件的复合区间作图法和多重区间作图法,对该群体的蛋白质和油分含量进行QTL定位分析,并利用QTL Network 2.1软件分析QTL间的上位性效应及环境互作效应。【结果】采用CIM和MIM 2种算法在2011和2012年哈尔滨、红兴隆、佳木斯和牡丹江每年3个地点共6个种植环境下共定位了9个蛋白质和11个油分含量QTL。蛋白质含量QTL分布在6个连锁群,分别在A1、C2、D1a、G、H和O连锁群上,对表型效应的贡献率为5.3%-18.6%,在H连锁群上的qPro-H-1贡献率最大,为18.6%,在D1a连锁群上的qPro-D1a-2贡献率最小,为5.3%,在单种植环境下有5个蛋白质含量QTL被2种算法同时检测到,分别是qPro-O-1、qPro-A1-1、qPro-D1a-1、qPro-D1a-2和qPro-C2-2。油分含量QTL分布在8个连锁群,分别在A1、A2、B1、C2、D1a、E、L和M连锁群上,对表型效应的贡献率为7.1%-24.4%,在B1连锁群上的qOil-B1-2贡献率最大,为24.4%,在C2连锁上的qOil-C2-3贡献率最小,为7.1%,在单种植环境下有2个油分含量的QTL被2种算法同时检测到,分别为qOil-C2-1和qOil-M-1。另外,有2个油分含量QTL在2个以上种植环境重复检测到,为2011年哈尔滨和2011年红兴隆2个种植环境下同时检测出的qOil-A1-1,2011红兴隆、2011牡丹江和2012哈尔滨3个地点同时被检测出的qOil-B1-2。在互作效应分析中,共检测出3对蛋白质上位效应QTL和4对油分上位效应QTL,在蛋白质上位性分析中,上位效应值在0.2068-0.3124,贡献率在0.0227%-0.0265%,分布在A1、C2、D1和E连锁群上,其中,qPro-A1-3与qPro-C2-1效应值为负,其余2对效应值为正,连锁群A1,D1a均有2个QTL发生互作。在油分上位性分析中,上位效应值在0.0926-0.1682,贡献率在0.0294%-0.0754%,分布在A1、C2、I、J、N和O连锁群上,其中,qOil-C2-4与qOil-N-1效应值为负,其余3对效应值为正,在N连锁群的qOil-N-1同时与2个QTL发生互作,分别是C2连锁群上的qOil-C2-1和qOil-C2-4。在与环境互作中,qPro-D1a-3与qPro-E-1在2012年佳木斯地点没检测出,其余6对都检测出与环境的互作效应,贡献率分别为0.0001%-0.0378%,互作效应都较小,明显小于自身的加性效应。【结论】定位到9个蛋白质相关QTL和11个油分相关QTL,并发现3对蛋白质含量上位性效应QTL和4对油分含量上位性QTL。     

大豆对斜纹夜蛾抗性的遗传分析及相关QTL的定位

 以大豆组合皖82-178×通山薄皮黄豆甲衍生的重组自交系群体（RIL）为材料，以斜纹夜蛾幼虫重为抗性鉴定指标，应用主基因＋多基因的混合遗传模型对大豆抗虫性进行遗传分析。结果表明，该群体对斜纹夜蛾的抗性遗传符合两对主基因＋多基因的遗传模型，主基因的遗传率为89.85％。以该群体所构建的遗传连锁图谱为基础，利用软件Cartgrapher（V.2.0）采用复合区间作图法检测到2个与抗虫有关的QTL，分别位于wt-11和wt-12连锁群上，其在对应连锁群的端距离分别为5.51cM、11.51cM，加性效应估计值分别为-0.0619、-0.0419，对性状变异的解释率分别为17.22％和8.60％。     

大豆荚数性状相关QTL的加性、上位性及QE互作效应分析

本研究利用Charleston×东农594得到的147个F2:14-F2:19重组自交系群体,对11个环境条件下大豆荚数性状相关QTL的加性、上位性及其与环境互作效应进行了分析.在6年11个不同遗传背景条件下的多环境联合分析中定位了11个QTL具有加性效应,其加性(A)贡献率和AE互作贡献率都是微效的.联合分析同时定位到20对QTL具有上位效应,并发现上位QTL的2种作用模式,一种是同一连锁群上2个QTL间的上位性互作,另一种是不同连锁群上2个QTL间的上位性互作.鉴定出9个具有加性效应的QTL能在多个环境条件下被检测到,17对具有上位性效应的QTL能在多个环境条件下被检测到,部分QTL的上位性效应解释的表型变异大于5％.这些在不同环境或不同遗传背景下检测到的QTL,可作为大豆荚数相关性状改良的候选标记,用于分子标记辅助选择或图位克隆.     

基于四交群体的玉米叶夹角和叶向值QTL定位分析

选育耐密紧凑株型是增加玉米单位面积产量的重要途径之一,而叶夹角和叶向值是衡量株型的重要参数。本研究选用叶夹角和叶向值存在差异的玉米自交系郑58、PH6WC、87-1和自330构建1个四交(郑58/豫87-1//PH6WC/自330)组合,以228个四交F1单株为作图群体,构建了1张含225个SSR位点,全长1 387.2cM的玉米分子标记遗传连锁图谱,标记间平均间距为6.19cM。基于四交群体应用区间作图法检测4个环境下的QTL,共检测到13个叶夹角相关QTL,分别位于第1、2、3、4、5、7和10染色体上,单个QTL可解释5.1%~20.0%的表型变异;检测到15个叶向值相关QTL,分别位于第1、2、4、5、7、8和9染色体上,单个QTL可解释5.4%~20.1%的表型变异。其中qLA-E2-2和qLA-E4-2落在同一标记区间umc1692-umc2297(bin 5.03),分别解释16.6%和13.2%的表型变异;qLO-E1-1、qLO-E3-2和qLA-E4-1落在同一标记区间umc1568-bnlg1953(bin1.02),分别解释10.1%、19.9%和12.3%的表型变异;qLO-E2-1和qLO-E3-1落在同一标记区间phi056-phi427913(bin 1.01),分别解释13.8%和10.0%的表型变异。这些多个环境共同检测到的QTL将为玉米耐密理想株型育种中叶夹角叶向值的分子标记辅助选择提供有益信息,加速耐密株型玉米品种的选育。     

Detection of quantitative trait loci (QTL) associated with spring regrowth in alfalfa (Medicago sativa L.)

Spring regrowth is an important trait for perennial plants including alfalfa, the most cultivated forage legume worldwide. However, the genetic and genomic basis of the trait is largely unknown in alfalfa due to its complex genetic background of the tetroploid genome. The objective of this study was to identify quantitative trait loci (QTLs) associated with spring regrowth using high-resolution genetic linkage maps we constructed previously. In total, 36 significant additive effect QTLs for the trait were detected. Among them, 10 QTLs individually explained more than 10% of the phenotypic variation (PVE) with four in P1 and six in P2. Six overlapped QTLs intervals were detected with two and four intervals distributed in P1 and P2, respectively. In P1, both overlapped genomic regions were located on homolog 7D. In P2, the four QTLs with PVE>10% were co-localized on homolog 6D. Meanwhile, six pairs of significant epistatic QTLs were identified in P2. Screening of potential candidate genes associated with four overlapped QTLs (qCP2019-8, qLF2019-5, qLF2020-4, and qBLUP-3) narrowed down one candidate annotated as MAIL1. The Arabidopsis homolog gene has been reported to play an important role in plant growth. Therefore, the detected QTLs are valuable resources for genetic improvement of alfalfa spring vigor using marker-assisted selection (MAS), and further identification of the associated genes would provide insights into genetic control of spring regrowth in alfalfa.     

大豆二粒荚库容含量的多年QTL分析

 【目的】定位大豆二粒荚长、宽QTL,培育二粒荚高库容含量的品种,稳定或提高大豆的产量。【方法】以美国大豆品种Charleston为母本、东北农业大学大豆品系东农594为父本及其F2:14-F2:18代的重组自交系的147个株系为试验材料,164个SSR引物经亲本筛选后用于群体扩增,并构建遗传图谱。利用前两年1个地点和后三年2个地点的调查数据对亲本二粒荚长、宽性状进行调查及QTL分析。【结果】采用WinQTL Cartographer V2.0软件的CIM和MIM分析方法对QTL检测结果表明,多年多点的种植环境下,共检测到19个二粒荚长QTL分别位于A1、B2、C2、D1a、D1b、N和G连锁群上,检测到17个二粒荚宽QTL分别位于A1、C2、D1a、D1b、N和H连锁群上。在得到的这些QTL中,2种算法都能检测到的包括7个二粒荚长QTL,其连锁标记包括Satt200—qTSPL-a1-1—Satt042、Sat_214—qTSPL-d1a-1—Sat_112、Satt198—qTSPL-d1a-3—Satt502、Satt370—qTSPL-d1a-6—Satt402、Sat_092—qTSPL-c2-4—Satt289、Satt277—qTSPL-c2-5—Sct_188和Satt168—qTSPL-b2-1—Sat_083;1个二粒荚宽QTL,其连锁标记为Satt528—qTSPW-d1a-2—Satt182。在2年以上能被检测到包括8个二粒荚长QTL,其连锁标记为Satt200—qTSPL-a1-1—Satt042、Sat_119—qTSPL-a1-2—Sat_105、Sat_214—qTSPL-d1a-1—Sat_112、Satt220—qTSPL-d1a-4—Sat_162、Satt370—qTSPL-d1a-6—Satt402、Satt168—qTSPL-b2-1—Sat_083、Sat_092—qTSPL-c2-4—Satt289和Satt277—qTSPL-c2-5—Sct_188;4个二粒荚宽QTL,其连锁标记为Satt076—qTSPW-c2-1—Satt072、Satt335—qTSPW-c2-2—Sat_120、Satt200—qTSPW-a1-1—Satt042和Satt182—qTSPW-d1a-3—Satt584。【结论】得到不同方法和不同年份重复检测率较高的二粒荚长QTL和二粒荚宽QTL的连锁分子标记,为大豆二粒荚长、宽QTL的定位和今后改良大豆产量潜力提供了有力依据。     

多环境条件下大豆异黄酮主要组分的QTL定位

 【目的】利用不同定位方法,对不同环境条件下大豆异黄酮主要组分进行QTL定位研究,为大豆异黄酮分子标记辅助育种提供理论依据。【方法】以异黄酮含量有显著差异的鲁黑豆2号（3 697.24 μg•g-1）和南汇早黑豆（1 816.67 μg•g-1）为亲本构建的F5∶7-8重组自交系为材料,分析RIL群体的SSR标记多态性,结合HPLC法鉴定异黄酮主要组分含量。【结果】绘制了一张包含161个多态性SSR标记,全长3 546.54 cM的大豆遗传连锁图谱。利用ICIMapping 3.2软件的ICIM、IM和SMA 3种定位方法,共定位到4种环境下与异黄酮主要组分相关的14个QTL。【结论】3个标记区间在多个环境和多种定位方法下均被检测到,分别是Sat_003—Satt306、Satt070—Satt122和Satt571—Satt270。     

基于90K芯片标记的小麦芒长QTL定位

【目的】麦芒对小麦的抗逆性以及穗部光合等方面具有重要影响。研究旨在挖掘控制芒长的主效QTL及与其紧密连锁或共分离的分子标记,为全基因组分子标记辅助选择育种、近等基因系的构建、候选基因的筛选以及基因克隆提供依据。【方法】以小偃81/周8425B、小偃81/西农1376这2个组合的F₉代RIL群体（分别含有102个和120个家系）为作图群体,利用覆盖小麦21条染色体组的90K标记构建2个遗传连锁图谱,于2016年10月至2017年6月将这2个F₉群体衍生的F_9﹕10群体分别种植在陕西杨凌、河南南阳和河南驻马店,小麦蜡熟期对芒长进行表型鉴定,用完备区间模型和多环境的联合分析对此性状进行QTL定位。【结果】构建了覆盖小麦21条染色体的2张遗传图谱,图谱长度分别为4 412.14和4 281.67 cM,平均遗传距离为分别为2.65和2.31 cM。2个连锁图谱的连锁标记数表明,90K标记在小麦基因组A、B和D间分布不均衡,但均表现为B基因组的标记数＞A基因组的标记数＞D基因组的标记数。对于2个连锁图谱的公共标记而言D基因组公共标记最少,从侧面反映出D基因组具有较高的保守性。2个RIL群体在陕西杨凌、河南南阳和河南驻马店3个环境下共检测到6个控制芒长的QTL。其中主效位点Qal5A-1在2个群体3种环境下都能被检测到,属于环境钝感QTL,表型变异贡献率变幅为46.01%-79.82%,对芒长具有强烈的抑制作用,加性效应来自短芒亲本小偃81,该主效QTL位点被定位在5A染色体末端,与分子标记RAC875_c8121_1147紧密连锁。另外Qal6B-1、Qal1B-1、Qal3B-1、Qal2D-1和Qal2D-2这5个QTL,分别被定位在6B、1B、3B、和2D染色体上,其表型变异的贡献率分别为1.39%、3.66%、3.93%、5.53%和3.51%,为微效QTL。小偃81/周8425B组合的RIL群体共检测的2个QTL,其中1个主效位点Qal5A-1和1个微效QTL位点Qal6B-1,2个QTL表型变异的贡献率总和为79.91%。小偃81/西农1376组合的RIL群体检测出5个QTL,1个主效位点Qal5A-1和4个微效位点Qal1B-1、Qal3B-1、Qal2D-1和Qal2D-2,5个QTL表型变异的贡献率总和为63.96%。多环境的联合分析得到了6个QTL,其互作效应的表型变异贡献率都远低于加性效应的表型变异贡献率,说明QTL与环境间的互作不是影响芒长的主要因素;加性效应值在不同的环境下近似相等,进一步表明这6个QTL在3个环境间有着稳定的遗传效应。【结论】2个群体检测到1个主效位点Qal5A-1,此位点能够稳定表达且与分子标记RAC875_c8121_1147紧密连锁,表型变异贡献率46.01%-79.82%,对芒长具有较强的抑制作用。     

Comparative mapping of QTLs for H+ secretion of root in maize (Zea mays L.) and cross phosphorus levels on two growth stages

H⁺ is a root secretion that affects P acquisition and P-use efficiency (PUE) under deficient phosphorus in maize. The secretion of H⁺, difference value of H⁺ between deficient and normal phosphorus (DH), and relative H⁺ (RH) as well as the quantitative trait loci (QTLs) associated with these traits were determined for a F_2:3 population derived from the cross of two contrasting maize (Zea mays L.) genotypes, 082 and Ye107. By using composite interval mapping (CIM), a total of 14, 8, and 9 distinct QTLs were identified for H⁺, DH, and RH, respectively. Most loci of QTLs for traits H⁺, DH, and RH had different cross environments. It showed that H⁺ secretion possessed an environment-sensitive and multi-gene nature. The gene × environment interaction was actually reflected by H⁺ secretion. One region for QTL of trait H⁺ was detected at the interval of bnlg2228-bnlg100 (bin 1.08) on chromosome 1. Coincident QTLs in the important genomic region reflected the cross phosphorus levels, different cross growth stages, and two different cross environments. The QTL explained 10% to 14% total phenotypic variance of H⁺. Therefore, the above segment (bnlg2228-bnlg100) (bin 1.08) identified on chromosome 1 may be used in the future for MAS to improve the phosphorus efficiency in maize.     

花生每荚种子数相关性状QTL的定位

【目的】花生是重要的油料作物和经济作物,高产一直是花生育种的主要目标,决定产量的因素是单位面积的种子数和仁重。单位面积种子数是种植密度、每株荚数和每荚种子数的乘积。因此,对花生每荚果种子数相关性状进行QTL分析,有助于发掘该性状相关基因/位点,为花生产量相关性状分子育种提供重要的理论依据。【方法】以四粒红×冀农黑3号构建的RIL群体为研究材料,于2018年（E1）和2020年（E2）在河北省保定市河北农业大学清苑试验站（115°30′E,38°40′N）种植鉴定,收获时调查统计单仁果数、双仁果数以及多仁果数表型值,利用河北农业大学花生创新团队实验室构建的高密度遗传图谱,采用QTL Icimapping V4.2中的完备区间作图法对2个环境下的每荚种子数相关性状进行QTL定位与分析。【结果】单仁果率与双仁果率均呈正态分布,多仁果率呈偏正态分布。3个性状的QTL定位分析结果表明,共检测到11个QTL,可解释4.66%—22.34%的表型变异,加性效应为-9.35—9.42。其中,定位到5个多仁果率QTL,可解释3.19%—22.34%的表型变异,有1个QTL的加性效应为负值（-4.77）,来自冀农黑3号,其余4个QTL的加性效应为正值（3.59—9.42）,均来自母本四粒红;定位到2个单仁果率QTL,可解释4.97%—6.43%的表型变异,加性效应均为负值（-4.45和-4.54）,均来自冀农黑3号;定位到4个双仁果率QTL,可解释3.46%—20.87%的表型变异,加性效应均为负值（-9.35—-3.84）,均来自冀农黑3号。这些QTL中,6个为主效QTL,其中,qRMSPA05被重复检测到,且可遗传表型变异为16.58%—17.34%,加性效应为7.69—8.12。【结论】定位6个主效QTL和1个主效稳定的多仁果率QTL,有助于改良花生产量性状,可以作为遗传改良的重要候选区段,用于分子标记辅助选择与精细定位研究。     

不同环境下多个玉米穗部性状的QTL分析

 【目的】探讨穗部性状之间的相互关系及其遗传机制。【方法】以优良玉米自交系黄早四为共同亲本,分别与掖478和齐319杂交,构建两套F2:3群体为研究材料(分别缩写为Y/H和Q/H),在2007年和2008年分别在北京、河南、新疆等3个地点共6个环境下进行了穗长、穗粗、穗行数和穗粒重4个性状的表型鉴定,采用单环境分析和多年多点的联合分析方法对其进行了数量性状位点(QTL)分析。【结果】在单环境分析中,2个群体分别检测到33个QTL和 46个QTL,主要分布在第4、5、6、7、10染色体上。进一步分析发现,在Y/H群体中共定位到4个环境钝感的QTL(即在2或2以上环境下均能被检测到的QTL,且在联合分析中与环境无互作效应),其中以位于第4、5染色体上的qGW1-4-1、qKRE1-5-1对表型的贡献率最大,在不同的环境中对表型的贡献率均大于10%;在Q/H群体中共定位到6个环境钝感的QTL,其中以qKRE2-3-2、qED2-2-1对表型的贡献率最大,分别解释7.23%—18.3%和7.1%—15.6%表型变异。通过多个环境的联合分析,Y/H和Q/H群体分别检测到2个和6个QTL与环境存在显著互作,且以穗粒重与环境互作的QTL最多,而其它性状的大部分QTL与环境的互作效应不显著。上位性分析结果表明,只有少数几个显著QTL位点参与上位性互作,而大部分上位性QTL为非显著位点间的互作,对表型的贡献率较小。比较分析2个群体的QTL定位结果,在2个群体间共检测到4对共有QTL,分别与穗粒重和穗行数相关,位于bin1.10、bin5.05、bin6.05和bin7.02。【结论】这些在不同环境或不同遗传背景下检测到的QTL,可作为穗部性状改良的候选染色体区段,用于分子标记辅助选择或图位克隆,但是同时也要注意上位性和环境对它们的影响。     

Comparison and analysis of QTLs for grain and hull thickness related traits in two recombinant inbred line(RIL) populations in rice(Oryza sativa L.)

Grain traits are major constraints in rice production, which are key factors in determining grain yield and market values. This study used two recombinant inbred line(RIL) populations, RIL-JJ(japonica/japonica) and RIL-IJ(indica/japonica) derived from the two crosses Shennong 265/Lijiangxintuanheigu(SN265/LTH) and Shennong 265/Luhui 99(SN265/LH99). Sixty-eight quantitative trait loci(QTLs) associated with 10 grain traits were consistently detected on the 12 chromosomes across different populations and two environments. Although 61.75% of the QTLs clustered together across two populations, only 16.17% could be detected across two populations. Eight major QTLs were detected on the 9, 10 and 12 chromosomes in RIL-JJ under two environments, a novel QTL clustered on the 10 chromosome, q GT10, q BT10 and q TGW10, have a higher percentage of explained phenotypic variation(PVE) and additive effect; 15 major QTLs were detected on the 5, 8, 9, and 11 chromosomes in RIL-IJ under two environments, a novel clustered QTL, q GT8 and q TGW8, on the 8 chromosome have a higher additive effect. Finally, the analysis of major QTL-BSA mapping narrowed the q TGW10 to a 1.47-Mb region flanked by simple sequence repeat markers RM467 and RM6368 on chromosome 10. A comparison of QTLs for grain traits in two different genetic backgrounds recombinant inbred line populations confirmed that genetic background had a significant impact on grain traits. The identified QTLs were stable across different populations and various environments, and 29.42% of QTLs controlling grain traits were reliably detected in different environments. Fewer QTLs were detected for brown rice traits than for paddy rice traits, 7 and 17 QTLs for brown rice out of 25 and 43 QTLs under RIL-JJ and RILIJ populations, respectively. The identification of genes constituting the QTLs will help to further our understanding of the molecular mechanisms underlying grain shape.     

Identification of genetic loci for grain yield-related traits in the wheat population Zhongmai 578/Jimai 22

The identification of stable quantitative trait locus (QTL) for yield-related traits and tightly linked molecular markers is important for improving wheat grain yield. In the present study, six yield-related traits in a recombinant inbred line (RIL) population derived from the Zhongmai 578/Jimai 22 cross were phenotyped in five environments. The parents and 262 RILs were genotyped using the wheat 50K single nucleotide polymorphism (SNP) array. A high-density genetic map was constructed with 1 501 non-redundant bin markers, spanning 2 384.95 cM. Fifty-three QTLs for six yield-related traits were mapped on chromosomes 1D (2), 2A (9), 2B (6), 2D, 3A (2), 3B (2), 4A (5), 4D, 5B (8), 5D (2), 7A (7), 7B (3) and 7D (5), which explained 2.7–25.5% of the phenotypic variances. Among the 53 QTLs, 23 were detected in at least three environments, including seven for thousand-kernel weight (TKW), four for kernel length (KL), four for kernel width (KW), three for average grain filling rate (GFR), one for kernel number per spike (KNS) and four for plant height (PH). The stable QTLs QKl.caas-2A.1, QKl.caas-7D, QKw.caas-7D, QGfr.caas-2B.1, QGfr.caas-4A, QGfr.caas-7A and QPh.caas-2A.1 are likely to be new loci. Six QTL-rich regions on 2A, 2B, 4A, 5B, 7A and 7D, showed pleiotropic effects on various yield traits. TaSus2-2B and WAPO-A1 are potential candidate genes for the pleiotropic regions on 2B and 7A, respectively. The pleiotropic QTL on 7D for TKW, KL, KW and PH was verified in a natural population. The results of this study enrich our knowledge of the genetic basis underlying yield-related traits and provide molecular markers for high-yield wheat breeding.     

利用分子标记定位籼稻落粒性QTL

利用2个籼稻品种H359和Acc8558杂交产生的重组自交系群体及相应的分子标记连锁图,采用复合区间定位方法,对籼稻落粒性进行了QTL定位分析.共检测到7个QTL,分别位于第1、2、4、6、7染色体上.这些QTL对表型变异的贡献率在2.49%-9.81%之间,总体可解释39.2%的表型方差.未检测到主效基因.在7个QTL中,有6个来自H359的等位基因均使落粒率降低,这与两亲本间落粒性的差异相吻合.