小麦旗叶长、宽及面积的QTL分析

以小麦品种‘小偃81’和‘西农1376’构建的含236个家系的自交重组系(RIL)群体(F2:7、F2:8代)为研究材料,采用完全随机区组设计,连续2年在陕西杨陵、河南驻马店和山东济南于灌浆期(花后20d)随机取每个株系10株测量旗叶长、宽,并利用172个SSR标记构建了遗传连锁图谱,通过基于完备区间作图法的QTL IciMapping V3.2软件,对控制小麦旗叶长、宽和面积的数量性状位点(QTL)进行了加性效应分析。结果发现:(1)9个旗叶长QTLs位于1A、4A、3B、5D和7D染色体上,单个QTL可解释5.10%~16.44%的表型变异;10个旗叶宽QTLs位于1A、3A、5A、7A、3B和5D染色体上,单个QTL可解释4.63%~14.24%的表型变异;12个旗叶面积QTLs位于1A、4A、3B、2D和5D染色体上,单个QTL可解释4.25%~22.67%的表型变异。(2)控制小麦旗叶长、宽和面积的QTLs存在差异,同一QTL在不同性状中的遗传贡献率也不同。(3)同一性状在同一年份,不同地点和在不同年份,相同地点下检测到的QTLs有的相同,但有的差异明显。(4)有些控制不同性状的QTLs在染色体的同一标记区间,表现一因多效。研究表明:位于1A和5D染色体上的2个加性QTLs都同时控制旗叶长、宽和面积,且前者为主效基因,后者遗传贡献率也较大,可用于标记辅助育种和分子聚合育种。     

小麦苗期水分利用效率及其相关性状的QTL分析

以小麦DH群体(旱选10号×鲁麦14)为研究材料,采用复合区间作图法,对小麦幼苗在水分胁迫及非胁迫条件下的水分利用效率(WUE)及其相关性状的QTL进行定位,并对比分析QTL的加性效应.两种水分条件下共检测到14个具显著加性效应的QTL,分布在2A、3A、4A、5A、6A、7A、1B、3B、3D染色体上,可解释表型变异的范围在6.36%～19.73%.其中,非胁迫(对照)条件下检测到10个QTL,包括2个单株WUE的QTL,5个地上部WUE的QTL,1个根系WUE的QTL及2个总耗水量的QTL;水分胁迫条件下上述性状各检测到1个QTL.对于同一性状没有检测到在两种水分条件下均位于同一标记区间的QTL,表明不同水分环境条件下同一性状的QTL表达模式是不同的.论文也讨论了可能用于标记辅助选择的QTL及其分子标记.     

控制水稻重要农艺性状的QTL在盐胁迫与非胁迫条件下的对比研究

基因型与环境的互作(G×E)对数量性状的影响常常掩盖了遗传因子引起的性状变化. 在盐胁迫环境与非胁迫环境下分别调查了水稻(Oriza sativa L.) 5个重要的农艺性状, 总共检测到24个QTL, 分布在除第9, 11号染色体外的各染色体上. 盐胁迫环境中检出了9个QTL: 千粒重1个; 抽穗期2个; 株高1个; 每穗粒数2个; 有效分蘖3个, 占总数的37.5%; 非胁迫环境中则检出了17个QTL: 千粒重5个; 抽穗期6个; 株高3个; 每穗粒数2个; 有效分蘖1个, 占总数的70.8%; 有两个QTL在两种环境中都检测到, 占总数的8.3%, 它们分别是位于第4染色体上控制抽穗期的QTL和位于第6染色体上控制每穗粒数的QTL. 此外, 还检测出3个包含多个QTL的区间, 它们分别位于第1, 4和8染色体上, 其中第1染色体上RG612分子标记附近检出两个QTL, 在盐胁迫环境与非胁迫环境中分别控制有效分蘖和抽穗期这两个重要的农艺性状, 其加性效应均由来源于JX17的等位基因提供; 第4染色体上的C975-RG449区间检测到2个QTL, qrHD-4c在非协迫环境中控制抽穗期, qrGPP-4s则在胁迫环境中控制每穗粒数; 第8染色体上的RG885-GA408区间检测到3个QTL, 在非胁迫环境下分别控制抽穗期、千粒重、株高3个性状, 在胁迫环境下则未能检测到. 通过对水稻在盐胁迫环境与非胁迫环境下的QTL对比研究, 发现水稻第8染色体上几个控制水稻重要农艺性状的QTL明显受盐胁迫的影响.     

小麦籽粒品质性状的QTL分析

利用小麦中国春(母本)和兰考大粒(父本)F2群体构建了169个标记的分子遗传图谱,将F2∶3家系分别种植于3个环境中,利用基于完备区间混合模型的单环境作图模型和多环境作图模型对小麦籽粒容重、硬度、蛋白含量和结合水含量性状进行了QTL分析。结果显示:(1)两种作图模型下,检测到容重的6个共同QTL(QTW-6B-6、QTW-7B-6、QTW-7B-9、QTW-5D-2、QTW-6D-1、QTW-6D-4),单环境模型下遗传贡献率为1.99%~6.57%,多环境模型下遗传贡献率为3.66%~20.07%,其中QM TW-7B-9、QM TW-6D-1和QM TW-6D-4在多环境模型中表现为主效QTL。(2)检测到硬度的3个共同QTL(QHD-4A-5、QHD-7A-1和QHD-7B-9),单环境模型下的遗传贡献率为6.00%~6.95%,多环境模型中遗传贡献率为5.43%~9.64%。(3)检测到蛋白含量1个共同QTL(QPR-6D-1),单环境模型下的遗传贡献率为5.39%,多环境模型中遗传贡献率为10.06%,表现为主效QTL。(4)检测到籽粒结合水含量1个共同QTL(QMO-1B-4),单环境模型下的遗传贡献率为39.20%,多环境模型下的遗传贡献率为75.01%,均表现为主效QTL。(5)1B染色体上存在同时控制籽粒容重、硬度、蛋白和结合水含量的QTL,说明1B染色体对小麦品质的影响可能很大。研究表明,小麦容重、硬度、蛋白含量、结合水含量的遗传主要受加性效应控制。该研究初步定位的一些重要QTL可为进一步精细定位、基因挖掘和育种早代品质性状分子标记辅助选择提供依据。     

小麦高密度遗传图谱构建及抗旱相关生理性状的遗传解析

生理调控是小麦应对干旱胁迫的主要途径,解析小麦抗旱相关生理性状的遗传基础,发掘利用分子标记将为小麦抗旱性的高效改良提供有力支撑。本研究以加倍单倍体(DH)群体(旱选10号×鲁麦14)的150个株系为材料,利用小麦660K SNP芯片及SSR标记构建高密度遗传图谱,解析不同水分环境下孕穗期及灌浆中期小麦冠层温度(CT)、叶绿素含量(SPAD value)和植被覆盖指数(NDVI)的遗传基础。遗传图谱覆盖小麦21条染色体,分为30个连锁群,总长度4082.44 c M,标记间平均距离为2.20 c M。共检测到抗旱相关生理性状QTL 86个,分布于除3D以外的20条染色体上。冠层温度、叶绿素含量和植被覆盖指数的QTL数目分别为30、40和34个;17个QTL具有一因多效性,其中4个QTL与冠层温度和植被覆盖指数相关,8个QTL与冠层温度和叶绿素含量相关,7个QTL与叶绿素含量和植被覆盖指数相关,位于4D染色体的QPT52与3种性状均相关。本研究为小麦抗旱基因挖掘及分子育种提供了参考信息和技术支撑。     

小麦幼苗耐热性的QTL定位分析

以小麦DH群体(‘旱选10号’ב鲁麦14’)为材料,在高温(热胁迫)及常温(对照)两种条件下考察小麦幼苗的根干重、苗干重、幼苗生物量、叶片叶绿素含量、叶绿素荧光参数及其耐热指数,并应用基于混合线性模型的复合区间作图法分析幼苗性状及其耐热指数QTL的数量、染色体分布及表达情况,以及QTL与环境的互作效应。结果显示:(1)亲本‘旱选10号’的耐热性明显优于‘鲁麦14’,且杂交后代的耐热性出现超亲分离。(2)控制幼苗耐热相关性状的QTL位点在染色体2D、6B、3A、4A、5A和7A上分布较多,而控制幼苗性状耐热指数的QTL在染色体6A、6B、3A、2D、5A和7A上分布较多,QTL位点在染色体上的分布有区域化的趋势。(3)控制幼苗性状的单个加性QTL和上位性QTL解释的表型变异分别平均为2.48%和2.65%;而控制耐热指数的单个加性QTL和上位性QTL解释的表型变异分别平均为8.84%和1.98%。(4)在热胁迫和对照条件下共检测到与幼苗性状及其耐热指数有关的加性效应QTL 13个和上位性效应QTL 28对,分布在除4D和6D以外的19条染色体上。研究表明,控制幼苗性状的QTL以上位性效应为主,而其耐热指数的QTL以加性效应为主。     

利用回交导入系剖析水稻苗期和分蘖期耐盐性的遗传重叠

以籼稻品种IR64为受体,来自伊朗的粳稻农家品种Binam为供体培育的99个BC2F8回交导入系为材料,定位了水稻在2叶1心期和分蘖期控制耐盐相关性状的数量性状基因座（QTL）．共检测到影响苗期叶片盐害级别、幼苗存活天数和地上部钾、钠离子浓度的QTL 13个,影响分蘖期株高、分蘖数和地上部鲜重的QTL 22个．多数分蘖期QTL对盐胁迫表现出明显的表达差异,根据表达情况将这些QTL分成3组,第1组为在对照条件下表达的11个QTL;第2组为在对照和盐胁迫条件下共同表达的5个QTL,其中有3个（QPh5,QPh8,QTn9）在两种环境下的基因效应大小和方向一致,其表达受盐胁迫影响较小;第3组为受盐胁迫诱导表达的6个QTL．检测到13个影响胁迫与对照差值即性状稳定性的QTL,除QPh4,QTn2和QFw2a外,其余10个基因座增加性状稳定性或提高耐盐性的等位基因均来自Binam．上述受盐胁迫影响较小的3个QTL和影响性状稳定性的13个QTL对耐盐性有贡献,属耐盐QTL．比较苗期和分蘖期耐盐QTL的分布,发现多数（69％）影响苗期和分蘖期的耐盐QTL在遗传上相互独立,仅在第1,2,8和11染色体的4个相同或相邻区域定位到影响两个时期的耐盐QTL,表明苗期和分蘖期的耐盐性存在部分的遗传重叠．通过标记辅助选择将苗期和分蘖期的重要耐盐QTL进行累加,或针对苗期和分蘖期的重叠耐盐QTL进行选择,有可能培育出苗期和分蘖期均耐盐的水稻品种．     

玉米雄穗分枝数与主轴长的QTL鉴定

在包含103个SSR标记的连锁图谱基础上, 运用复合区间作图法检测玉米组合(N87-1×9526 )F3家系在正常与干旱胁迫环境下的雄穗分枝数与主轴长性状QTL。雄穗分枝数在正常环境下被检测到2个QTL座位, 分别位于第5和7连锁群上; 在胁迫环境下被检测到4个QTL座位分别位于 2、5、7和10连锁群上, 其中位于第5和7连锁群上的QTL不仅具有一致性而且与本作图群体中曾检测到的耐旱相关性状QTL存在连锁。雄穗主轴长在正常环境下被检测到2个QTL位于第2和第6连锁群上, 在干旱胁迫环境下被检测到了3个QTL分别于第2、4和10连锁群上, 其中位于第2染色体上的QTL是两种环境下所共同检测到的QTL。分析QTL的遗传作用方式表明, 雄穗分枝数以部分加性效应为主, 而雄主轴长全部表现为显性和超显性。     

小麦重组自交系(RILs)群体碳同位素分辨率的QTL分析

为了探知小麦水分利用效率(WUE)碳同位素分辨率(Δ)的遗传机理,以小麦重组自交系(RILs)群体为材料,在不同水分条件下研究Δ的遗传规律,并进行QTL定位。结果表明:(1)RILs群体的Δ值呈正态分布,Δ属于数量性状遗传。(2)共检测到11个主效QTL,主要位于2B、3B、7B、1D和3D染色体上,表型贡献率在10.83%~46.87%之间,有9个加性QTL(A-QTL)与环境发生互作,互作贡献率在1.02%~3.15%之间。(3)检测到5对影响Δ的上位QTL(AA-QTL),其中3对AA-QTL与环境发生互作,互作贡献率在0.86%~2.01%之间。(4)加性效应及贡献率大于上位性效应及贡献率,A-QTL与环境互作贡献率大于AA-QTL与环境互作贡献率,表明RILs群体中Δ遗传变异主要受加性效应影响,控制Δ的主效基因作用较大,受水分环境影响较小。     

小麦抗旱相关生理性状的QTL分析

利用RIL群体131个系,在小麦中首次对超氧化物岐化酶活性、可溶性蛋白含量、脯氨酸含量、硝酸还原酶活性、气孔导度等5个抗旱相关生理性状进行了QTL定位,共检测到超氧化物岐化酶活性、可溶性蛋白含量、硝酸还原酶活性等3个性状5个加性QTL,涉及1D、2B、5A、7B共4条染色体,可解释表型变异的8.74％～36.96％。其中．3个QTL即QSDd,sdau-7B、Qspc,sdau-1D、QNra,sdau-1D贡献率较大,分别为29.28％、23.11％和36．96％,其加性效应都源于山农483。讨论了可能用于标记辅助选择的QTL及其分子标记。     

QTL mapping for some grain traits in bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Grain traits are important agronomic attributes with the market value as well as milling yield of bread wheat. In the present study, quantitative trait loci (QTL) regulating grain traits in wheat were identified. Data for grain area size (GAS), grain width (GWid), factor form density (FFD), grain length-width ratio (GLWR), thousand grain weight (TGW), grain perimeter length (GPL) and grain length (GL) were recorded on a recombinant inbred line derived from the cross of NW1014?×?HUW468 at Meerut and Varanasi locations. A linkage map of 55 simple sequence repeat markers for 8 wheat chromosomes was used for QTL analysis by Composite interval mapping. Eighteen QTLs distributed on 8 chromosomes were identified for seven grain traits. Of these, five QTLs for GLWR were found on chromosomes 1A, 6A, 2B, and 7B, three QTLs for GPL were located on chromosomes 4A, 5A and 7B and three QTLs for GAS were mapped on 5D and 7D. Two QTLs were identified on chromosomes 4A and 5A for GL and two QTLs for GWid were identified on chromosomes 7D and 6A. Similarly, two QTLs for FFD were found on chromosomes 1A and 5D. A solitary QTL for TGW was identified on chromosome 2B. For several traits, QTLs were also co-localized on chromosomes 2B, 4A, 5A, 6A, 5D, 7B and 7D. The QTLs detected in the present study may be validated for specific crosses and then used for marker-assisted selection to improve grain quality in bread wheat.     

Conditional and unconditional QTL mapping of drought-tolerance-related traits of wheat seedling using two related RIL populations

For discovering the quantitative trait loci (QTLs) contributing to early seedling growth and drought tolerance during germination, conditional and unconditional analyses of 12 traits of wheat seedlings: coleoptile length, seedling height, longest root length, root number, seedling fresh weight, stem and leaves fresh weight, root fresh weight, seedling dry weight, stem and leaves dry weight, root dry weight, root to shoot fresh weight ratio, root-to-shoot dry weight ratio, were conducted under two water conditions using two F_8:9 recombinant inbred line (RIL) populations. The results of unconditional analysis are as follows: 88 QTLs accounting for 3.33–77.01% of the phenotypic variations were detected on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6B, 6D, 7A, 7B and 7D. Among these QTLs, 19 were main-effect QTLs with a contribution rate greater than 10%. The results of the conditional QTL analysis of 12 traits under osmotic stress on normal water conditions were as follows: altogether 22 QTLs concerned with drought tolerance were detected on chromosomes 1B, 2A, 2B, 3B, 4A, 5D, 6A, 6D, 7B, and 7D. Of these QTLs, six were main-effect QTLs. These 22 QTLs were all special loci directly concerned with drought tolerance and most of them could not be detected by unconditional analysis. The finding of these QTLs has an important significance for fine-mapping technique, map-based cloning, and molecular marker-assisted selection of early seedling traits, such as growth and drought tolerance.     

Combined GWAS and QTL mapping revealed candidate genes and SNP network controlling recovery and tolerance traits associated with drought tolerance in seedling winter wheat

To date, very little research on drought tolerance has been conducted at the seedling stage in winter wheat. In this study, two types of traits, namely tolerance and recovery traits, associated with drought tolerance were scored in biparental mapping population (BPP) and association mapping population (A-set). The results of this study revealed no or weak significant correlation between the two types of traits. Based on GWAS and QTL mapping analyses, all QTLs associated with recovery traits were completely different from those associated with tolerance traits except one QTL in each population that was found to be associated with one tolerance trait and one recovery trait. The analysis of SNP and gene networks confirmed the results of combined GWAS and QTL mapping. One SNP marker located on the 2B chromosome (S2B_26494801) was found to be associated with recovery traits in both populations. The results of this study provided new information on understanding and improving drought tolerance in winter wheat.     

Location of genes involved in ear compactness in wheat (Triticum aestivum) by means of molecular markers

Quantitative trait loci (QTLs) for three traits related to ear morphology (spike length, number of spikelets, and compactness as the ratio between number of spikelets and spike length) in wheat (Triticum aestivum L.) were mapped in a doubled-haploid (DH) population derived from the cross between the cultivars Courtot and Chinese Spring. A molecular marker linkage map of this cross that had previously been constructed based on 187 DH lines and 380 markers was used for QTL mapping. The genome was well covered (85%) except chromosomes 1D and 4D and a set of anchor loci regularly spaced (one marker each 15.5 cM) were chosen for marker regression analysis. The presence of a QTL was declared at a significance threshold = 0.001. The population was grown in one location under field conditions during three years (1994, 1995 and 1998). For each trait, 4 to 6 QTLs were identified with individual effects ranging between 6.9% and 21.8% of total phenotypic variation. Several QTLs were detected that affected more than one trait. Of the QTLs 50% were detected in more than one year and two of them (number of spikelets on chromosome 2B, and compactness on chromosome 2D) emerged from the data from the three years. Only one QTL co-segregated with the gene Q known to be involved in ear morphology, namely the speltoid phenotype. However, this chromosome region explained only a minor part of the variation (7.5–11%). Other regions had a stronger effect, especially two previously unidentified regions located on chromosomes 1A and 2B. The region on the long arm of chromosome 1A was close to the locus XksuG34-1A and explained 12% of variation in spike length and 10% for compactness. On chromosome 2B, the QTL was detected for the three traits near the locus Xfbb121-2B. This QTL explained 9% to 22% of variation for the traits and was located in the same region as the gene involved in photoperiod response (Ppd2). Other regions were located at homoeologous positions on chromosomes 2A and 2D.     

QTL mapping of 1000-kernel weight, kernel length, and kernel width in bread wheat (Triticum aestivum L.)

Kernel size and morphology influence the market value and milling yield of bread wheat (Triticum aestivum L.). The objective of this study was to identify quantitative trait loci (QTLs) controlling kernel traits in hexaploid wheat. We recorded 1000-kernel weight, kernel length, and kernel width for 185 recombinant inbred lines from the cross Rye Selection 111 × Chinese Spring grown in 2 agro-climatic regions in India for many years. Composite interval mapping (CIM) was employed for QTL detection using a linkage map with 169 simple sequence repeat (SSR) markers. For 1000-kernel weight, 10 QTLs were identified on wheat chromosomes 1A, 1D, 2B, 2D, 4B, 5B, and 6B, whereas 6 QTLs for kernel length were detected on 1A, 2B, 2D, 5A, 5B and 5D. Chromosomes 1D, 2B, 2D, 4B, 5B and 5D had 9 QTLs for kernel width. Chromosomal regions with QTLs detected consistently for multiple year-location combinations were identified for each trait. Pleiotropic QTLs were found on chromosomes 2B, 2D, 4B, and 5B. The identified genomic regions controlling wheat kernel size and shape can be targeted during further studies for their genetic dissection.     

两种供氮水平下水稻生长后期相关性状的QTL定位

以特青为母本与Lemont杂交,然后用特青为轮回亲本回交,建立特青背景下的染色体片段置换系（CSSL）群体。在正常和低氮条件下分别在生长后期对株高（PH）、单株穗数（PN）、叶绿素含量（CC）、地上部干物重（SDW）和单株籽粒产量（YD）等性状进行了QTL分析,共检测到31个QTL。其中在正常供氮水平下控制PH、PN、CC、SDW和YD的QTL数目均为3个;在低氮水平下检测到5、4、5和2个影响PH、PN、CC和SDW的QTL,在低氮水平下没有检测到控制YD的位点。大部分QTL集中在第2、3、7、11和12染色体上,影响不同性状或在两种供氮水平下影响同一性状的QTL在染色体上成串或成簇分布。其中RM30-RM439、RM18-RM478、RM309-RM270、RM235-RM17等区域同时检测到控制两个以上性状的QTL,表现出明显的一因多效现象。推测仅在低氮水平下检测到的QTL可能跟水稻对低氮胁迫耐性有一定的关联。     

Detection of QTLs for heading time and photoperiod response in wheat using a doubled-haploid population.

The genetic basis of heading time in wheat (Triticum aestivum L.) was investigated through the study of flowering under normal autumn sown field conditions as well as photoperiod responses under a controlled environment. Quantitative trait loci (QTLs) for these traits were mapped in a doubled-haploid (DH) population derived from a cross between the wheat cultivars 'Courtot' and 'Chinese Spring'. A molecular marker linkage map of this cross that was previously constructed based on 187 DH lines and 380 markers was used for QTL mapping. The genome was well covered (85%) except for chromosomes 1D and 4D, and a set of anchor loci regularly spaced over the genome (one marker each 15.5 cM) was chosen for marker regression analysis. The presence of a QTL was declared at a significance threshold of alpha = 0.005. The population was grown under field conditions in Clermont-Ferrand, France during two years (1994-1995), in Norwich, U.K. over one year (1998), and also under controlled environments in Norwich. For each trait, between 2 and 4 QTLs were identified with individual effects ranging between 6.3% and 44.4% of the total phenotypic variation. Two QTLs were detected that simultaneously affected heading time and photoperiod response. For heading time, these two QTLs were detected in more than one year. One QTL located on chromosome arm 2BS near the locus Xfbb121-2B, co-segregated with the gene Ppd-B1 known to be involved in photoperiod response. This chromosome region explained a large part of the variation (23.4-44.4% depending on the years or the traits). Another region located on chromosome arm 7BS between the loci Xfbb324-7B and Xfbb53-7B also had a strong effect (7.3-15.3%). This region may correspond to a QTL for earliness per se.     

GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton

A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-01041-y.     

Enrichment of a common wheat genetic map and QTL mapping for fatty acid content in grain

DArT and SSR markers were used to saturate and improve a previous genetic map of RILs derived from the cross Chuan35050 × Shannong483. The new map comprised 719 loci, 561 of which were located on specific chromosomes, giving a total map length of 4008.4 cM; the rest 158 loci were mapped to the most likely intervals. The average chromosome length was 190.9 cM and the marker density was 7.15 cM per marker interval. Among the 719 loci, the majority of marker loci were DArTs (361); the rest included 170 SSRs, 100 EST-SSRs, and 88 other molecular and biochemical loci. QTL mapping for fatty acid content in wheat grain was conducted in this study. Forty QTLs were detected in different environments, with single QTL explaining 3.6-58.1% of the phenotypic variations. These QTLs were distributed on 16 chromosomes. Twenty-two QTLs showed positive additive effects, with Chuan35050 increasing the QTL effects, whereas 18 QTLs were negative with increasing effects from Shannong483. Six sets of co-located QTLs for different traits occurred on chromosomes 1B, 1D, 2D, 5D, and 6B.