Genome-wide association study of differences in 14 agronomic traits under low- and high-density planting models based on the 660k SNP array for common wheat

One hundred and ninety-seven wheat accessions from Yellow and Huai Winter Wheat Region (YHW) were evaluated for differences of 14 agronomic traits under low- and high-density plantings. Compared with the high-density plantings, plant height, neck length, uppermost internode length, flag leaf angle and number of sterile spikelets under the low-density plantings reduced, while heading date, flowering date, flag leaf length and width, spike length, number of fertile spikelets, grain number per spike, thousand-kernel weight and grain weight per spike increased. A total of 1,118 markers were detected based on GWAS, and seven QTLs were confirmed. One QTL on chromosomes 5BL and two other QTLs on 5Dl were all tightly associated with flowering date difference. Bioinformatics analysis revealed that two haploblocks in 5Dl were involved, and the Vrn-D1 locus was located in this interval. A region on chromosome 5B at around 531.5 Mb was significantly associated with plant height difference. Two QTLs including AX-94840438 (7BL) and AX-94563647 (7DS) were responsible for neck length or uppermost internode length difference.     

Analysis of contributors to grain yield in wheat at the individual quantitative trait locus level

In wheat, strong genetic correlations have been found between grain yield (GY) and tiller number per plant (TN), fertile spikelet number per spike (FSN), kernel number per spike (KN) and thousand‐kernel weight (TKW). To investigate their genetic relationships at the individual quantitative trait locus (QTL) level, we performed both normal and multivariate conditional QTL analysis based on two recombinant inbred lines (RILs) populations. A total of 79 and 48 normal QTLs were identified in the International Triticeae Mapping Initiative (ITMI)/SHW‐L1 × Chuanmai 32 (SC) populations, respectively, as well as 55 and 35 conditional QTLs. Thirty‐two QTL clusters in the ITMI population and 18 QTL clusters in the SC population explained 0.9%–46.2% of phenotypic variance for two to eight traits. A comparison between the normal and conditional QTL mapping analyses indicated that FSN made the smallest contribution to GY among the four GY components that were considered at the QTL level. The effects of TN, KN and TKW on GY were stronger at the QTL level.     

QTL mapping of sheath blight resistance in a deep-water rice cultivar

Sheath blight, caused by the pathogen Rhizoctonia solani Kühn, is one of the most serious diseases of rice and leads to severe yield loss worldwide. A recombinant inbred line (RIL) population consisting of 121 lines was constructed from a cross between HH1B and RSB03, the latter of which is a deep-water rice variety. Five traits were used to evaluate sheath blight resistance, namely disease rating (DR), lesion length (LL), lesion height (LH), relative lesion length [RLL, the ratio of LL to plant height (PH)], and relative LH (RLH, the ratio of LH to PH). Using the RIL population and 123 molecular markers, we identified 28 quantitative trait loci (QTLs) for the five traits in two environments. These QTLs are located on nine chromosomes and most of them are environment specific. A major QTL for DR (qSBR1) on chromosome 1 was identified with contributions of 12.7% at Shanghai and 42.6% at Hainan, and it collocated with a QTL for PH. The allele at this locus from RSB03 enhances sheath blight resistance and increases PH. Another QTL for DR on chromosome 7 was adjacent to QTLs for heading date (HD) and four other disease traits. RSB03 also carries the resistant allele at this locus and shortens HD. The susceptible parent, HH1B, provides the resistance allele at the locus qSBR8, where QTLs for four other disease traits were identified. QTL mapping results showed that most QTLs for LL, LH, RLL, and RLH are collocated with QTLs for DR. Three QTLs for DR are independent from HD, PH, and four other disease traits, while four QTLs are closely related to HD and PH. Four QTLs for LL, LH, RLL, and RLH are independent from DR, HD, and PH, while there is only one region harboring QTLs for these four traits and HD. Correlation analysis and QTL mapping results indicated that LL, LH, RLL, and RLH might be important indices, like DR, for evaluating the level of resistance to rice sheath blight.     

烤烟6个农艺性状的QTL定位

由于烟草的分子标记开发和遗传图谱构建十分困难,迄今烟草中有关数量性状基因座(QTL)的定位研究仍非常有限。本研究利用一个由207个株系组成的烤烟DH群体及基于该群体所构建的含有24个连锁群、611个SSR标记,总长为1 882.1 cM的遗传图谱,采用复合区间作图方法,对株高(PH)、茎围(SG)、节距(IL)、叶片数(LN)、最大腰叶长(LWL)和最大腰叶宽(WWL) 6个与叶片产量有关的农艺性状进行QTL定位分析。共检测到69个QTL,大部分QTL的效应值较小,仅有4个具有较大的效应值,可解释大约15%~20%的表型变异。6个性状之间大多彼此相关。与此相符,在基因组中发现存在许多小区域,每个区域包含两个或两个以上紧密连锁的不同性状的QTL。     

利用水稻MAGIC群体关联定位抽穗期和株高QTL

利用多亲本高代互交系(multi-parent advanced generation inter-cross,MAGIC)群体(DC1、DC2和8way)及其复合群体DC12(DC1+DC2)和RMPRIL(DC1+DC2+8way)进行关联分析定位水稻抽穗期和株高QTL。2015年和2016年分别在江西和深圳收集3个MAGIC群体抽穗期数据,2016年在两地收集株高数据,结合Rice 55K SNP芯片进行基因分型,利用关联分析方法检测到3个影响抽穗期的主效QTL(q HD3、q HD6和q HD8),分别位于第3、第6和第8染色体,且分别与已知抽穗期基因DTH3、Hd3a和Ghd8在同一区域。检测到5个影响株高的QTL(q PH1.1、q PH1.2、q PH1.3、q PH4和q PH6),其中q PH1.1和q PH1.2位于已知基因Psd1和sd1附近,其余3个QTL为影响株高的新位点,但仅在1个群体和单个环境下被检测到,QTL表达受遗传背景和环境影响大。不同MAGIC群体定位抽穗期和株高的效果不同,在8亲本MAGIC群体8way及复合群体DC12和RMPRIL分别检测到5、5和6个抽穗期和株高QTL,明显多于4亲本群体DC1的2个和DC2的4个,而且作图的精度更高,表现在定位到的QTL显著水平高和与已知基因距离更近,尤其是复合群体的联合分析(如DC12和RMPRIL)的作图优势更为明显。     

利用品质性状的回交选择导入系挖掘水稻抗纹枯病QTL

将优质、抗纹枯病的高秆供体Tarom Molaii和Binam导入半矮秆IR64和特青背景,培育品质性状回交选择构建的4个导入系群体IR64/Tarom Molaii、特青/Tarom Molaii、IR64/Binam和特青/Binam,定位了影响水稻抗纹枯病病级(disease scale, DS)、相对病斑高度(relative lesion height, RH)和株高(plant height, PH)的QTL。结果表明,4个导入系群体的DS与RH高度相关,两者与PH呈显著负相关。导入系后代各性状均呈现超亲分离,出现抗性明显优于双亲的抗病个体,其中40%左右属半矮秆抗病类型。采用单向方差分析,在这4个群体中分别定位到10、8、8和6个影响3个性状的QTL,多数基因座上降低DS和RH即增强抗病性同时增加株高的等位基因均来自两个供体。未在同一供体两个不同背景下检测到影响3个性状的相同QTL,表明抗纹枯病QTL表达有明显的遗传背景效应。PH与DS及PH与RH被定位在同一个显著标记位点的QTL数分别占两个性状QTL总数的38%和52%,表明水稻纹枯病抗性与株高关系密切,两者存在许多连锁位点。与以往相同群体品质性状QTL的定位结果相比,发现品质性状QTL与抗纹枯病QTL大多分布在染色体的不同区域,彼此独立遗传。对利用目标性状选择导入系定位非目标性状QTL的效果、影响因素及育种应用进行了探讨,强调了目标性状选择导入系对非目标性状QTL发掘及育种应用的重要性。     

小麦GMP含量发育动态的QTL定位

利用小麦京771和Pm97034杂交后代重组自交系（RIL）群体,对小麦谷蛋白大聚合体（GMP）含量发育动态进行了QTL定位研究。结果表明,在籽粒灌浆的5个不同时期,共检测到8个条件QTL和10个非条件QTL,但没有一个QTL能在测定的5个时期都有效应。花后12 d,控制GMP形成的基因就已经有了一定的表达量,条件QTL能解释6.21%的表型变异,该基因位于1A染色体上。花后17 d,在1D染色体上测到了1个新表达的条件QTL位点,单独能解释14.14%的表型变异。花后22 d,控制GMP形成的基因的表达比较活跃,非条件分析检测到3个QTL位点,条件分析检测到2个QTL位点,这5个QTL位点分别位于1B、5B、6B和7B染色体上,其效应值都比较低,2个条件QTL共同能解释12.67%的净表型变异。花后27 d,在2D和3B染色体上各检测到2个条件和非条件QTL位点,加性效应值比较大。条件QTL能解释16.37%的表型变异,非条件QTL能解释23.94%的变异。花后32 d,仍有2个新的基因位点在表达,但此时QTL的净表达量已经开始下降,条件QTL仅能解释11.43%的表型变异。     

水稻株高及其构成因素数量性状基因座位的分子标记定位

应用具有８９个标记位点的Ｆ２群体的ＲＦＬＰ图谱，对控制水稻株高及其构成因素的数量性状基因座位进行定位等研究。共定位了３２个ＱＴＬｓ，其中涉及株高的有７个、穗长３个、第一节间长有２个、第二节间长和第三节间长各３个、第四节间长有６个、节间数和第一节间干重各有４个。     

Mapping genes for deep-seeding tolerance in barley

Deep-seeding tolerance, the emergence of seedlings from deep seeded conditions, is involved in stand establishment in semi-arid regions, where the soil surface is too dry for seed germination. Genes determining deep-seeding tolerance in barley were mapped using two doubled haploid populations derived from the following crosses: Harrington × TR306 (H/T)and Step toe × Morex (S/M). Significant quantitative trait loci (QTLs) for deep-seeding tolerance were found in each population. Two QTL sex plained 40% of the phenotypic variation in the H/T population and one QTL (S/M) 8% of the total phenotypic variance. Multiple QTLs accounting for coleoptile length and first internode length were detected in both populations. In the H/T population, there were coincident QTLs for deep-seeding tolerance, coleoptile length and first internode length on the long arm of chromosome 5H. These QTLs correspond with previously reported QTLs for abscisic acid and gibberellic acid response. QTL coincidence may be due to the pleiotropic effects of alleles at a single locus. This information may be useful for breeding programs manipulating morphological and physiological traits in order to develop varieties for semi-arid regions. This revised version was published online in August 2006 with corrections to the Cover Date.     

利用双向导入系解析水稻抽穗期和株高QTL及其与环境互作表达的遗传背景效应

利用粳稻Lemont和籼稻特青相互导入构建的遗传背景基本一致的双向回交导入系群体,分别在北京和海南环境定位影响抽穗期和株高的主效QTL及其环境互作,分析QTL及其与环境互作表达的遗传背景效应。在北京和海南分别检测到影响抽穗期和株高的主效QTL 16个和17个,其中有5个主效QTL (QHd2、QHd8a、QPh3、QPh5和QPh12)在两种背景下同时被检测到,表明多数主效QTL的表达具有遗传背景特异性。两种背景下检测到影响抽穗期的3个主效QTL (QHd8a、QHd9和QHd10b)存在环境互作,其中QHd8a与海南环境的互作在两种背景下提早抽穗2~3 d,与北京环境的互作则延迟抽穗2~3 d,是影响抽穗期的一个重要主效QTL。通过与以往相同亲本来源的7个不同定位群体在不同环境下定位结果的比较,鉴定出一些在不同遗传背景和环境下稳定表达的主效QTL,如QHd3、QHd8a、QPh3和QPh4,适宜用于水稻抽穗期和株高的分子标记改良。基于QTL定位结果,本文对如何通过分子标记辅助改良品种在不同环境下的抽穗期进行了深入探讨。     

基于QTL定位的蓖麻株高性状遗传解析

用YC2(高杆)×YF1(矮杆)和YC1(高杆)×YF1(矮杆)组合衍生的2个F₂代群体, 对蓖麻株高性状进行相关、回归和QTL定位分析。结果表明, 株高与主穗位高、主茎节长和主茎茎粗之间显著正相关, 但与主茎节数不相关;主穗位高与主茎节数、主茎节长和主茎茎粗之间显著正相关;主茎节数与主茎节长之间显著负相关。利用QTLNetwork 2.0软件在YC2×YF1的F₂群体中检测到株高、主穗位高、主茎节数、主茎节长和主茎茎粗的5、4、6、3和2个QTL, 分别解释了45.9%、45.3%、66.1%、55.4%和12.6%的总变异。在YC1×YF1的F₂群体中检测到3、4、5、1和2个上述5性状的QTL, 分别解释了26.0%、25.5%、35.4%、37.4%和7.6%的总变异。证明QTL间的“一因多效”和连锁是株高、主穗位高和主茎节长之间高度相关的遗传基础, 加性效应是株高、主穗位高和主茎节长的主要遗传组分, 互作效应是主茎节数和主茎茎粗的主要遗传组分。建议育种上将主穗位高和主茎节长作为株高早期选择和预测的间接指标,并将多节数和短节间作为高产育种的主攻方向。     

Detection of quantitative trait loci (QTLs) for seedling traits and drought tolerance in wheat using three related recombinant inbred line (RIL) populations

In order to detect quantitative trait loci (QTLs) for drought tolerance in wheat during seed germination conditional and unconditional QTL analyses of eight seedling traits were conducted under two water regimes using three related F₉ recombinant inbred line populations with a common female parent. A total of 87 QTLs for the eight seedlings traits and 34 specific QTLs related to drought tolerance were detected. Seventy-one of these QTLs were major QTLs with contributions to phenotypic variance of >10 %. Of the 34 QTLs related to drought tolerance only eight were also detected by unconditional analysis of seedling traits under osmotic stress conditions indicating that most of the QTLs related to drought tolerance could not be detected by unconditional QTL analysis. Therefore, conditional QTL analysis of stress-tolerance traits such as drought tolerance was feasible and effective. Of 11 important QTL clusters located on chromosomes 1BL, 1D, 2A, 2B, 2D, 4A, 6B, and 7B, nine were detected in multiple populations and eight were detected by both unconditional and conditional analyses.     

基于QTL定位分析小麦株高的杂种优势

为探讨小麦株高杂种优势的分子遗传基础,以小麦品种花培3号和豫麦57杂交F1经染色体加倍获得的DH群体168个株系为材料,构建了一套含168个杂交组合的"永久F2"群体。利用复合区间作图法,在3个环境中进行了基于QTL定位的株高杂种优势分析,共检测到3个加性效应位点、2个显性效应位点、4对上位效应位点(包括加性×加性、加性×显性、显性×加性和显性×显性)和20个杂种优势位点。位于2D、4D和5B2染色体上的QPh2D、QPh4D和QPh5B2在3个环境中同时被检验到,受环境影响小,表达稳定。在2D染色体上相近的区域定位出多个杂种优势位点,其中QPh2D-2和QPh2D-7可解释杂种优势表型变异的29.77%和55.77%。在7D染色体的Xwmc273.2-Xcfd175之间定位出同一个杂种优势位点Qph7D-2。结果表明,在2D、4D和7D染色体上这些区域存在一些对小麦株高的杂种优势起重要作用的位点。     

QTL mapping for developmental behavior of plant height in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

A recombinant inbred line (RIL) population with 305 lines derived from a cross of Hanxuan 10 × Lumai 14 was used to identify the dynamic quantitative trait loci (QTL) for plant height (PH) in wheat (Triticum aestivum L.). Plant heights of RILs were measured at five stages in three environments. Total of seven genomic regions covering PH QTL clusters on different chromosomes identified from a DH population derived from the same cross as the RIL were used as the candidate QTLs and extensively analyzed. Five additive QTLs and eight pairs of epistatic QTLs significantly affecting plant height development were detected by unconditional QTL mapping method. Six additive QTLs and four pairs of epistatic QTLs were identified using conditional mapping approach. Among them, three additive QTLs (QPh.cgb-1B.3, QPh.cgb-4D.1, QPh.cgb-5B.2) and three pairs of epistatic QTLs (QPh.cgb-1B.1–QPh.cgb-1B.3, QPh.cgb-2A.1–QPh.cgb-2D.1, QPh.cgb-2D.1–QPh.cgb-5B.2) were common QTLs detected by both methods. Three QTLs (QPh.cgb-4D.1, QPh.cgb-5B.3, QPh.cgb-5B.4) were expressed under both drought and well-water conditions. The present data are useful for wheat genetic manipulations through molecular marker-assisted selection (MAS), and provides new insights into understanding the genetic mechanism and regulation network underlying the development of plant height in crops. Our result in this study indicated that combining unconditional and conditional mapping methods could make it possible to reveal not only the stable/conserved QTLs for the developmental traits such as plant height but also the dynamic expression feature of the QTLs.     

利用非条件和条件QTL解析油菜产量相关性状的遗传关系

基于前期研究中构建的Sollux/Gaoyou DH群体在9个环境中的表型数据和新版遗传图谱,对油菜角果长度进行QTL定位,估测QTL的加性、上位性和环境互作效应。并通过条件QTL方法,解析角果长度与角果粒数和粒重之间的遗传关系,以期利用标记辅助,探讨通过选择角果长度基因型以增加角果粒数、提高千粒重,最终达到增加产量的可能性。结果共检测到在3个环境以上稳定表达的控制角果长度QTL 8个,加性效应值在0.09~0.26 cm之间,效应总和解释群体遗传总变异的60%。8对上位性QTL效应值在0.035~0.075 cm之间,效应总和为加性总效应的38%。QTL与环境互作效应只在少数位点和个别环境中显著。条件QTL研究表明,q SLA2、q SLC1-2和q SLC8-1位点,角果长度的变化对角果粒数影响较大;而通过选择q SLA7、q SLC1-2、q SLC8-1和q SLC8-2长角果标记基因型,可望同时提高角果粒数和千粒重。6个主效QTL 11个连锁标记基因型和表现型的关联分析,验证了条件QTL分析结果,表明通过对q SLA2、q SLA7、q SLC8-1和q SLC8-2位点6个连锁标记(ZAAS423、SUC1-3、ZAAS12a、ZAASA7-28、ZAAS433和ZAAS437)长角果基因型的聚合,可增长角果约2 cm,间接增加角果粒数2粒,同时提高千粒重0.4 g,从而可望实质性地提高油菜产量水平。     

Both major and minor QTL associated with plant height can be identified using near-isogenic lines in maize

Plant height (PH) and ear height (EH) are important agronomic traits in maize (Zea mays L.) breeding. To investigate the influence of the genetic background on the detection of quantitative trait locus (QTL) conferring PH and EH, related mapping populations were developed from a near isogenic line (NIL) and its recurrent parent. Through joint-environment analyses, a total of four QTLs for PH were identified within the introgressed regions of the used NIL. Compared with the mapping results of RILs, extra PH QTLs could be detected within the target region of the used NIL on chromosome 4, but a previous PH QTL within this region was lost. The missed detection of a previous PH QTL also occurred on chromosome 6. As such, the genetic background of the recurrent parent exerted its influence on the detection of height QTL in this study. Meanwhile, according to the analyses of recombination events, qPEH6, a major height QTL on chromosome 6, was narrowed down to a region of approximately 1 Mb. Sequence analysis revealed that GRMZM2G014119, which encodes an ubiquitin-like protein related to the auxin response, was roughly assumed to be the candidate gene responsible for qPEH6.     

用单片段代换系（SSSLs）研究水稻株高及其构成因素QTL加性及上位性效应

株高是典型的数量性状,易受遗传背景和环境等因素的影响。单片段代换系和双片段聚合系减少了个体间遗传背景的干扰,是鉴定QTL和研究QTL上位性的新型遗传材料。本研究采用随机区组试验设计方法以初级单片段代换系间杂交衍生的16个次级单片段代换系和15个双片段聚合系分析了株高及其构成因素QTL的加性效应及加性×加性上位性效应。共鉴定出11个QTL,其中3个株高QTL,1个倒1节间长QTL,2个倒2节间长QTL,2个倒3节间长QTL和3个倒4节间长QTL,分布于第4、6和10染色体上。鉴定出23对双基因互作,其中7对为没有显著效应的座位间互作,16对为有显著效应的QTL与没有显著效应的座位间互作。结果表明,QTL加性效应和QTL间的上位性效应都是株高及构成因素的重要遗传组成。通过单片段代换系杂交衍生的次级单片段代换系和双片段聚合系可提高QTL鉴定和上位性分析的灵敏度。     

Identification of QTLs controlling quantitative characters in rice using RFLP markers

Summary Segregation of plant height (PH), tiller number (TN), panicle number (PN), average panicle length per plant (PL), average primary branch number per panicle per plant (PBN) and 1000 grain weight (1000G) were specific in an F₂ population derived from a cross of Palawan, a tall Javanica variety, and IR42, an Indica semidwarf variety. One hundred and four informative RFLP markers covering all 12 chromosomes were used for detecting putative QTLs controlling the traits. Orthogonal contrasts and interval mapping analysis were used for the analysis. QTL detected for PH on the region of chromosome 1, where semidwarfing gene sd-1 locus is located, seems to be a multiple allelic locus. An additional QTL for PH was identified on chromosome 2. Two QTLs for TN were detected on chromosomes 4 and 12. The QTL on chromosome 4 seemed also to govern the variation in PN. Four QTLs were found for the other traits, two of them for PL were located on chromosomes 6 and 2, one for PBN on chromosome 6 and the other for 1000G on chromosome 1. Additive gene actions were found to be predominant, except one QTL for PH and one QTL for PL, but partial or incomplete dominance also existed for the QTLs detected.     

燕大1817/北农6号重组自交系群体穗部性状的QTL定位

小麦穗部性状与单株产量密切相关。本研究以小麦骨干亲本燕大1817与优良品系北农6号衍生的269个重组自交系为材料,通过在北京和河北石家庄的2年田间试验数据,利用本实验室已构建的高密度SNP和SSR遗传连锁图谱进行穗长、穗粒数和穗粒重QTL定位。采用完备复合区间作图法共检测到29个穗部性状加性效应QTL,其中10个穗长QTL分布于1B、2D、3A、3B、4A、5A、5B、6A和7D染色体上,解释的表型变异率为2.96%~9.63%,QSl.cau-4A.2在所有5个环境中均能被检测到,解释的表型变异为5.89%~9.62%,另有7个QTL能在2个或2个以上环境中被检测到;8个穗粒数相关QTL分布于1A、3A、3D、4A和5B染色体上,解释的表型变异为4.06%~11.17%,为单个环境QTL。11个与穗粒重相关QTL分布于1A、1B、2A、2D、3A、4D、5A、5B和6B染色体上,解释的表型变异为2.79%~16.12%,其中QGws.cau-1B、QGws.cau-3A和QGws.cau-6B.2在2个或者2个以上环境中能被检测到。另外,鉴定出6个分布于1A、2D、3A、4A和5B染色体上的QTL富集区段。     

QTL Mapping of Important Agronomic Traits on Chromosomes Showing Marker Segregation Distortion in Interspecific Backcross Cotton Populations

[Objective] The purpose of this study was to map QTLs for yield, maturity, and fiber quality traits of cotton interspecific hybrid populations and to mine favorable alleles from the cotton genome for QTL fine mapping, gene cloning, and molecular marker-assisted selection. [Method] Four BC₁F₁ populations, E(E3), E(3E), (E3)E, and (3E)E, were developed by crossing sea island cotton 3-79 ("3") and upland cotton 'Emian 22' ("E"), and with "Emian 22" as the recurrent parent. BC1F2 populations derived from BC1F1 populations were phenotyped to allow mapping of QTLs for yield-, maturity-, and fiber quality-related traits on chromosomes showing segregation distortion. [Result] A normal distribution test indicated that six fiber quality-related traits, except for the micronaire value in E (E3) and the short fiber ratio in all populations, followed a normal distribution pattern; in contrast, earliness-related traits were not normally distributed in all populations, which suggests that genotype-environment interactions have strong effects on maturity-related traits. Using composite interval mapping, 47 QTLs were detected on three chromosomes (2, 16, and 18): 15 in (E3)E, 13 in (3E)E, 12 in E(E3), and 7 in E(3E), with the phenotypic variation explained (PVE) ranging from 8.8%–30.9%. A total of 27 fiber-related QTLs were discovered, with the PVE ranging from 9.0%–30.9%. Five yield-related QTLs (PVE = 8.8%–17.4%) and 13 maturity-related QTLs (PVE = 9.4%–19.4%) were also identified. [Conclusion] Comparison analysis showed that most QTLs in our study were consistent with the MetaQTL, including QTLs for boll weight, fiber length, fiber length uniformity, lint percentage, and micronaire value on chromosome 2; QTLs for fiber length, fiber strength, and fiber length uniformity on chromosome 16; and QTLs for boll weight, date of boll opening, fiber length, fiber strength, fiber length uniformity, and micronaire value on chromosome 18. Several detected QTLs in our study were not found in the MetaQTL, such as QTLs for date of boll opening and lint percentage on chromosome 16 and a QTL for the date from seedling to flowering stages on chromosome 18. These newly identified QTLs may provide novel insights for cotton QTL analysis.