鹰嘴豆种质资源农艺性状遗传多样性分析

以100份鹰嘴豆种质资源为材料,应用聚类分析和主成分分析方法,对15个主要农艺性状的遗传多样性进行分析。结果表明,参试材料存在广泛的遗传多样性。其中,多样性指数最高的是株高,其次是百粒重;性状变异系数最大的是单株荚数,其次是单株粒重;基于各种质间形态标记的遗传差异,将100份鹰嘴豆种质聚类并划分为4大类群。第Ⅰ类群可作为选育丰产中粒型和株高适中的品种,第Ⅱ类群可作为选育矮秆耐密及特异粒色(型)品种,第Ⅲ类群丰产性较差可作为选育子粒球型、光滑的品种,第Ⅳ类群可作为选育大粒型、适宜机械化收获的品种。9个数量性状的主成分分析结果表明,前4个主成分累计贡献率达73.91%,各主成分性状载荷值反映了主要数量性状的育种选择潜力。综合分析种质资源农艺性状,为鹰嘴豆的有效利用提供一定的科学依据。     

基于掖478导入系的玉米百粒重QTL鉴定

玉米百粒重是产量性状的主要组成因子,对其控制位点进行QTL鉴定或基因克隆,将有益于其遗传控制的研究和分子育种的实施。本研究以导入系SL19-41为材料,该导入系是以我国玉米育种中广泛应用的骨干自交系掖478(Ye478)为遗传背景导入QB80染色体片段的纯合系。使用该导入系与Ye478杂交构建分离群体(F2、F2:3家系和BC1F1),通过3个环境下的田间试验,利用Ici Mapping的逐步回归区间作图法进行百粒重QTL定位,以及进行QTL位点连锁标记的表型效应分析。结果表明:鉴定了2个百粒重QTL位点,其中位于第4染色体bnlg1784~umc1194区间QTL位点q KW4-1在3个环境下均被检测到,可解释的表型变异为6.74%~17.81%,阐明了导入系SL19-41百粒重性状的遗传机制,同时也获得了改良版的Ye478(Ye478QB80),为玉米百粒重的遗传改良提供有益的分子标记,也为克隆百粒重基因提供材料来源。     

中国普通菜豆种质资源朊蛋白变异及多样性分析

朊蛋白是研究普通菜豆遗传多样性的一种重要且有效的生化标记。本试验通过SDS-PAEG凝胶电泳检测中国普通菜豆种质资源的朊蛋白变异类型,分析中国普通菜豆种质资源的遗传多样性及组成特点。来自中国13个省(自治区)的445份供试材料共检测到S、Sb、Sd、B、C、CA、T、PA、To、H、H1、CH 12种朊蛋白类型,表明中国普通菜豆种质朊蛋白变异类型丰富,遗传多样性水平较高。其中,Sb型朊蛋白种质最多,占比29.0%;T型其次,占比28.1%。依据朊蛋白类型在不同基因库的特异性,将研究材料明显地区分为中美基因库和安第斯基因库两大类。研究还发现中国普通菜豆种质资源中地方种质朊蛋白类型变异丰富,多样性明显高于现代育成品种或品系。最后,对种质朊蛋白类型与百粒重、子粒颜色、粒型进行相关性分析,结果表明朊蛋白类型与百粒重呈极显著正相关,而朊蛋白类型与子粒颜色、粒型2个性状之间无明显相关性。本研究结果将为普通菜豆种质资源的保护及有效地挖掘优质种质资源提供理论依据。     

不同杂种优势群玉米子粒脱水速率分析

采用烘干法测定170份玉米自交系的子粒的脱水速率及其相关性状,利用覆盖玉米全基因组的210对SSR标记对试验材料进行全基因组扫描,通过Structure V2.3.4软件揭示其群体结构。对不同杂种优势群平均子粒脱水速率进行方差分析,并筛选出各个类群中子粒脱水速率快的自交系。结果表明:子粒脱水速率在不同自交系间存在显著差异,与穗轴和子粒的含水率等性状间存在显著相关性。试验共筛选到子粒脱水速率大于1%的自交系20个;授粉后40 d子粒含水率低于21%的自交系10个。参试自交系分成P、旅大红骨、瑞德、兰卡斯特和唐四平头5个杂种优势群;授粉后40 d子粒脱水速率依次是瑞德群0.92%、兰卡斯特群0.85%、旅大红骨群0.82%、混合群0.80%、P群0.76%、唐四平头群0.56%。本文旨在通过研究不同杂种优势群玉米自交系子粒脱水速率的特性,筛选子粒脱水速率快的自交系,为选育适应机械化作业的玉米杂交种提供借鉴。     

野生小豆种质资源植株形态性状多样性分析

对来自中国、日本、韩国、缅甸4国的55份野生型、40份半野生型小豆种质资源植株形态性状的多样性进行分析,结果表明,野生型小豆与半野生型小豆在株高、平均成熟期、子粒颜色、百粒重等性状方面有明显的差别。95份小豆种质资源通过聚类分析,截值为1.488时可划分为5大类群。来源于缅甸和中国的野生型小豆种质各聚为1个类群,韩国和日本的种质混聚为3个类群。缅甸种质具平均成熟期长、茎秆粗、主茎分枝数多、百粒重轻等特点。中国贵州野生型种质植株较高、茎秆较细、单荚粒数较多、平均成熟期较长。日本野生型种质具有丰产特征。日本和韩国的半野生型小豆,平均成熟期较其他类群早、百粒重高、明度指数高。     

燕麦种质资源主要农艺性状的遗传多样性分析

燕麦种质资源是燕麦育种的重要基础,对燕麦遗传多样性的研究不仅有助于种质资源的搜集、管理和利用,也有利于进行核心种质的研究。为了解不同地区燕麦种质资源在农艺性状上的遗传多样性,对74份皮、裸燕麦种质资源13个性状的遗传多样性进行了聚类分析与主成分分析。结果表明:各性状的遗传多样性指数较大,多样性指数最高的是主穗粒重,其次是千粒重和穗长;性状变异系数最大的是单株分蘖数,其后依次为单株粒重和主穗粒重,最小的为株高;根据品种间各性状的遗传差异,通过聚类分析将74份资源材料划分为5类,其中36份皮燕麦资源被分为2类,26份裸燕麦资源被分为2类,7份皮燕麦和5份裸燕麦被分为一类,其中,类群Ⅰ可作为高产育种目标的亲本,类群Ⅲ可作为粒型育种目标的亲本,类群Ⅳ、Ⅴ可作为株高和小穗等育种目标的亲本;8个数量性状主成分分析的结果表明,前4个主成分对变异的累计贡献率达86.27%,第一主成分反应产量,第二主成分反应粒型,第三、第四主成分分别反应分蘖数和株高。     

160份外引鹰嘴豆种质主要农艺性状的遗传多样性分析

对引自国际半干旱热带作物研究中心的160份鹰嘴豆种质资源的13个农艺性状进行了评价鉴定,并筛选了特异种质,为我国鹰嘴豆种质资源创新和品种选育提供参考。结果表明,该批鹰嘴豆种质资源具有较为丰富的遗传多样性,7个数量性状的变异系数由大到小分别为主茎分枝数单株荚数百粒重产量株高单荚粒数生育期,6个质量性状的Shannon多样性指数由大到小分别为粒色株型花色种子表面粒形复叶叶型;产量与粒形、单株荚数极显著正相关,与百粒重显著正相关;前4个主成分的累计贡献率为63.417%,其中第1主成分与产量性状和产量有关,第2主成分与生育期有关,第3主成分与形态性状有关,第4主成分与株高和粒形有关;聚类分析在遗传距离为5时将160份资源分为3个类群,其中第Ⅰ类群的株高较高,第Ⅱ类群的产量较高,第Ⅲ类群的籽粒较大;筛选出63份早熟、矮秆、无分枝、多荚、荚粒数多、大粒、高产的特异种质资源。     

控制大豆油分含量和百粒重的QTL定位

油分含量和百粒重是大豆中两个重要的性状。本研究利用东农46和L-100衍生的重组自交系(RIL)群体,经过两年3个地点种植,通过分子标记技术定位与大豆油分含量和百粒重相关的QTL(quantitative trait locus)。结果表明,检测到6个与油分含量相关的QTL,分别位于E、H、G和I连锁群上,可解释的表型贡献率范围为2.12%~2.77%;检测到5个与百粒重相关的QTL,分别位于K、H、B2和G连锁群上,可解释的表型贡献率范围为2.30%~7.59%,在H连锁群上有2个QTL两年均被检测到,标记区间分别为Satt279-Sat_122和Satt192-Satt568。在H连锁群上Satt192-Satt568标记区间内同时检测到与油分含量和百粒重相关的QTL。研究结果为大豆油分含量和百粒重等性状的分子辅助育种提供了理论依据。     

玉米种质资源的抗倒伏性评价及鉴定指标筛选

倒伏是影响玉米高产稳产的主要问题之一。本研究以181份玉米自交系为试验材料,对22个与抗倒伏性紧密相关的性状进行测定,采用相关性分析、主成分分析、聚类分析、逐步判别分析和岭回归分析等方法,综合评价玉米自交系的抗倒伏性。相关性分析的结果表明,22个性状间存在不同程度的相关性。主成分分析的结果表明,前7个主成分代表了181份玉米自交系的22个性状74.460%的信息,其贡献率分别为25.700%、12.369%、9.782%、8.159%、7.782%、5.490%和5.177%。聚类分析的结果表明,当遗传距离为3.5时,181份玉米自交系被聚为4大类,第Ⅰ类群有35份自交系、第Ⅱ类群有47份自交系、第Ⅲ类群有49份自交系、第Ⅳ类群有50份自交系。逐步判别分析的结果表明,175份玉米自交系被正确判别,判对概率为96.69%;6份玉米自交系被误判,误判率为3.31%,这说明聚类分析的结果是准确可靠的。进一步利用岭回归方法筛选出半纤维素含量、穿刺强度、第3节间长度、第3节间直径、穗位高和维管束总面积6个性状,建立了可靠的玉米自交系抗倒伏性评价回归模型。在181份玉米自交系中,以AHU24、e220、7026B等35份自交系的抗倒伏能力最强。本研究结果为玉米抗倒伏种质资源的遗传改良和组配抗倒伏杂交种提供借鉴。     

高粱子粒单宁含量和颜色QTL分析

高粱在我国酿酒行业和农业结构调整中均有重要作用。子粒单宁含量和粒色是高粱两个重要的品质性状,但有关高粱子粒单宁和粒色分子遗传的报道还较少。本研究用白粒低单宁的BTx623与浅粉高单宁Rio两个品种为亲本,构建了含325个株系的重组自交系基因定位群体,开展高粱子粒单宁和粒色基因定位研究。筛选出118个SSR标记和8个INDEL亲本多态性标记用于定位群体株系的基因型检测,结合亲本和定位群体子粒单宁和粒色2年测定数据,采用QTL Ici Mapping 4.1软件中的完备区间作图法,对高粱子粒单宁和粒色2个性状进行QTL定位,共检测到3个与单宁含量相关和6个粒色相关的QTL位点。与单宁含量相关的QTL qTan4-1即为已克隆的Sb04g031730,另外检测到新的qTan1-1(txp11~txp279,贡献率1.29%)和qTan2-1(txp298~SB1292,贡献率1.28%),但2014年未检测到。控制粒色的6个QTL中,qGC1-1(贡献率1.00%和12.03%)在txp11~txp279之间;qGC1-2(贡献率2.64%和16.96%)在txp43~txp11之间;qGC1-3(2014年贡献率22.81%)在1d1A3~sam44127标记之间;qGC2-1(2014年贡献率1.00%)在txp72~txp298之间;qGC2-2(贡献率1.19%和3.66%)在txp298~SB1292之间;qGC6-1(2015年贡献率15.08%)在txp57~sam43683之间。本研究为高粱子粒单宁和粒色2个性状的精细定位、基因克隆和分子标记辅助选择研究奠定了基础。     

Molecular mapping of quantitative trait loci for three kernel-related traits in maize using a double haploid population

Kernel size and kernel weight are important factors possibly involved in the determination of grain yield in maize, so identifying the genetic basis of kernel-related traits provides insights into the breeding of high-yield maize varieties. Kernel length (KL), kernel width (KW) and hundred kernel weight (HKW) were evaluated in three various planting conditions for the 240 field-grown double haploid (DH) lines derived from the single-cross hybrid Xianyu335. Variations in KL, KW and HKW were observed among DH lines, and all three traits showed a broad sense heritability of 76%. A total of 964 single nucleotide polymorphisms (SNPs) from the MaizeSNP3072 chip was utilised to create a high-density genetic map of 1546.4 cM and to identify quantitative trait loci (QTLs). Using composite interval mapping, a total of five, seven and five QTLs have been mapped for KL, KW and HKW, respectively. qkl1-2 and qkl4-1 explained 17.8% and 14.2% of the phenotypic variation in KL, respectively, and the other three QTLs contributed 3.2–4.0%. The phenotypic variation explained (PVE) of seven QTLs responsible for KW ranged from 3.3 to 9.5%. Three QTLs for HKW, qhkw1, qhkw5 and qhkw10 each explained more than 10% of the phenotypic variation, and qhkw4 and qhkw9 accounted for 3.0% and 6.0%, respectively. Due to their detection in multiple planting environments, the loci mapped here appear to be potential targets for the improvement of maize grain yield.     

Genome‐wide association study for 13 agronomic traits reveals distribution of superior alleles in bread wheat from the Yellow and Huai Valley of China

Bread wheat is a leading cereal crop worldwide. Limited amount of superior allele loci restricted the progress of molecular improvement in wheat breeding. Here, we revealed new allelic variation distribution for 13 yield‐related traits in series of genome‐wide association studies (GWAS) using the wheat 90K genotyping assay, characterized in 163 bread wheat cultivars. Agronomic traits were investigated in 14 environments at three locations over 3 years. After filtering SNP data sets, GWAS using 20 689 high‐quality SNPs associated 1769 significant loci that explained, on average, ~20% of the phenotypic variation, both detected already reported loci and new promising genomic regions. Of these, repetitive and pleiotropic SNPs on chromosomes 6AS, 6AL, 6BS, 5BL and 7AS were significantly linked to thousand kernel weight, for example BS00021705_51 on 6BS and wsnp_Ex_c32624_41252144 on 6AS, with phenotypic variation explained (PVE) of ~24%, consistently identified in 12 and 13 of the 14 environments, respectively. Kernel length‐related SNPs were mainly identified on chromosomes 7BS, 6AS, 5AL and 5BL. Plant height‐related SNPs on chromosomes 4DS, 6DL, 2DS and 1BL were, respectively, identified in more than 11 environments, with averaged PVE of ~55%. Four SNPs were confirmed to be important genetic loci in two RIL populations. Based on repetivity and PVE, a total of 41 SNP loci possibly played the key role in modulating yield‐related traits of the cultivars surveyed. Distribution of superior alleles at the 41 SNP loci indicated that superior alleles were getting popular with time and modern cultivars had integrated many superior alleles, especially for peduncle length‐ and plant height‐related superior alleles. However, there were still 19 SNP loci showing less than percentages of 50% in modern cultivars, suggesting they should be paid more attention to improve yield‐related traits of cultivars in the Yellow and Huai wheat region. This study could provide useful information for dissection of yield‐related traits and valuable genetic loci for marker‐assisted selection in Chinese wheat breeding programme.     

High-density linkage mapping of yield components and epistatic interactions in maize with doubled haploid lines from four crosses

Grain yield (GY) is a genetically complex and physiologically multiplicative trait which can be decomposed into the components kernel number (KN) and 100-kernel weight (HKW). Genetic analysis of these less complex yield component traits may give insights into the genetic architecture and predictive ability of complex traits. Here, we investigated how the incorporation of component traits and epistasis in quantitative trait locus (QTL) mapping approaches influences the accuracy of GY prediction. High-density genetic maps with 7,000–10,000 polymorphic single nucleotide polymorphisms were constructed for four biparental populations. The populations comprised between 99 and 227 doubled haploid maize lines which were phenotyped in field trials in two environments. Heritability was highest for HKW (88–89 %), intermediate for KN (72–80 %), and lowest for GY (64–83 %). Mapped QTL explained in total 21–55 %, 22–67 %, and 24–75 % of the genotypic variance for GY, KN, and HKW, respectively. Support intervals of QTL were short, indicating that QTL were located with high precision. Co-located QTLs with same parental origin of favorable alleles were detected within populations for different traits and between populations for the same traits. Using GY predictions based on the detected QTL, prediction accuracies (r) determined by cross validation ranged from 0.18 to 0.52. Epistatic models did not outperform the corresponding additive models. In conclusion, models based on QTL positions of component traits support the identification of favorable alleles for multiplicative traits and provide a basis to select superior inbred lines by marker-assisted breeding.     

玉米雌穗性状遗传分析与形成机制*

雌穗是玉米重要的生殖器官,雌穗发育决定成熟果穗大小及单穗粒重,进而直接影响玉米产量。雌穗性状主要包括穗长、穗粗、穗行数、行粒数、穗重、单穗粒重等,均为多基因控制的数量遗传性状,且其遗传结构各不相同。解析雌穗性状的遗传基础,优化雌穗结构,是玉米增产的重要途径。前人通过数量性状位点(quantitative trait locus mapping,QTL)定位和全基因组关联分析(genome-wide association study, GWAS)等方法,已经鉴定出较多雌穗性状相关的遗传位点,但是目前已鉴定功能的基因较少,所建立的遗传位点一致性图谱并不完整,因此难以全面揭示雌穗性状遗传结构。通过综合前人雌穗性状遗传定位进展,现将已鉴定QTL位点和显著关联SNP整合至玉米B73参考基因组V4版本,并鉴定出雌穗性状定位热点区间,对深入解析雌穗性状遗传结构、指导雌穗性状基因克隆和理解雌穗发育分子机制均具有重要意义。     

玉米自交系遗传变异的RFLP分析

利用ＲＦＬＰ标记研究了１３个玉米（Ｚｃａ ｎａｙｓ Ｌ．）自交系的遗传变异。从３０对探针／酶组合中筛选出杂交带型清晰、稳定、重复性好的２４对组合,在１３个自交系中获得８５个等位基因杂交片段,平均每个位点为３．３条,平均多态性指数为０．４９９。１３个自交系之间的遗传相似系数为０．５２３－０．８０２,平均为０．６４９。ＵＰＧＭＡ聚类分析表明,供试自交系共分为５个类群,分群结果与其系谱关系基本吻合;表明     

RFLP Detection of Genetic Variation of Maize Inbred Lines

Genetic similarities of 13 inbred lines of maize (Zea mays L.) were analyzed by restriction fragment length polymorphisms (RFLPs). The objectives of the study were to detect genetic similarities among 13 inbreds and to assign them to heterotic groups. By means of 24 probe-enzyme combinations (PECs) selected for locus specificity, clear patterns and reproducibility, 85 alleles were found with an average of 3.3 alleles per locus. The allelic frequency data were used to estimate genetic similarities among lines, and as a result the diversity index of 0.499 was obtained. Genetic similarities between the pairs of 13 lines ranged from 0.523 up to 0.802 with an average of 0.649. The UPGMA clustering algorithm analysis classified the 13 lines into five groups, which generally corresponded to known maize heterotic groups based on pedigree information. The authors concluded that RFLP-based markers could be used for investigating genetic relationships between maize inbred lines and assigning them to heterotic groups, but it seemed that a large number of PECs were needed to obtain reliable estimates of genetic similarity.     

Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms

Characterization of genetic diversity is of great value to assist breeders in parental line selection and breeding system design. We screened 770 maize inbred lines with 1,034 single nucleotide polymorphism (SNP) markers and identified 449 high-quality markers with no germplasm-specific biasing effects. Pairwise comparisons across three distinct sets of germplasm, CIMMYT (394), China (282), and Brazil (94), showed that the elite lines from these diverse breeding pools have been developed with only limited utilization of genetic diversity existing in the center of origin. Temperate and tropical/subtropical germplasm clearly clustered into two separate groups. The temperate germplasm could be further divided into six groups consistent with known heterotic patterns. The greatest genetic divergence was observed between temperate and tropical/subtropical lines, followed by the divergence between yellow and white kernel lines, whereas the least divergence was observed between dent and flint lines. Long-term selection for hybrid performance has contributed to significant allele differentiation between heterotic groups at 20% of the SNP loci. There appeared to be substantial levels of genetic variation between different breeding pools as revealed by missing and unique alleles. Two SNPs developed from the same candidate gene were associated with the divergence between two opposite Chinese heterotic groups. Associated allele frequency change at two SNPs and their allele missing in Brazilian germplasm indicated a linkage disequilibrium block of 142 kb. These results confirm the power of SNP markers for diversity analysis and provide a feasible approach to unique allele discovery and use in maize breeding programs.     

Mapping of Genes for Cooking and Eating Qualities in Thai Jasmine Rice (KDML105)

Thai jasmine rice, KDML 105, is known as the best quality rice.It is known not only for its aroma but also for its good cookingand eating qualities. Amylose content (AC), gel consistency(GC) and gelatinization temperature (GT) are important traitsdetermining rice quality. A population of recombinant inbredlines (RIL) derived from KDML105 x CT9993 cross was used tostudy the genetic control of AC, GC and GT traits. A total of191 markers were used in the linkage map construction. The 1605.3cM linkage map covering nearly the whole rice genome was usedfor QTL (define QTL) analysis. Four QTLs for AC were detectedon chromosomes 3, 4, 6 and 7. These QTLs accounted for 80% ofphenotypic variation explained (PVE) in AC. The presence ofone major gene as well as several modifiers was responsiblefor the expression of the trait. Two QTLs on chromosome 6 andone on chromosome 7 were detected for GC, which accounts for57% of PVE. A single gene of major effect along with modifiergenes controls GC from this cross. The QTLs in the vicinityof waxy locus were major contributors in the expression of ACand GC. The finding that the position of QTLs for AC and GCwere near each other may reflect tight linkage or pleiotropy.Three QTLs were detected, one on chromosome 2 and two on chromosome6, which accounted for 67% of PVE in GT. Just like AC and GC,one major gene and modifier genes governed the variation inGT resulting from the KDML105 x CT9993 cross. Breeding for cookingand eating qualities will largely rely on the preferences ofthe end users.     

Characterization of QTL for oil content in maize kernel

Kernel oil content in maize is a complex quantitative trait. Phenotypic variation in kernel oil content can be dissected into its component traits such as oil metabolism and physical characteristics of the kernel, including embryo size and embryo-to-endosperm weight ratio (EEWR). To characterize quantitative trait loci (QTL) for kernel oil content, a recombinant inbred population derived from a cross between normal line B73 and high-oil line By804 was genotyped using 228 molecular markers and phenotyped for kernel oil content and its component traits [embryo oil content, embryo oil concentration, EEWR, embryo volume, embryo width, embryo length, and embryo width-to-length ratio (EWLR)]. A total of 58 QTL were identified for kernel oil content and its component traits in 26 genomic regions across all chromosomes. Eight main-effect QTL were identified for kernel oil content, embryo oil content, embryo oil concentration, EEWR, embryo weight, and EWLR, each accounting for over 10?% of the phenotypic variation in six genomic regions. Over 90?% of QTL identified for kernel oil content co-localized with QTL for component traits, validating their molecular contribution to kernel oil content. On chromosome 1, the QTL that had the largest effect on kernel oil content (qKO1-1) was associated with embryo width; on chromosome 9, the QTL for kernel oil content (qKO9) was related to EEWR (qEEWR9). Embryo oil concentration and embryo width were identified as the most important component traits controlling the second largest QTL for kernel oil content on chromosome 6 (qKO6) and a minor QTL for kernel oil content on chromosome 5 (qKO5-2), respectively. The dissection of kernel oil QTL will facilitate future cloning and/or functional validation of kernel oil content, and help to elucidate the genetic basis of kernel oil content in maize.     

Discovering Candidate Chromosomal Regions Linked to Kernel Size-Related Traits via QTL Mapping and Bulked Sample Analysis in Maize

Kernel size-related traits, including kernel length, kernel width, and kernel thickness, are critical components in determining yield and kernel quality in maize (Zea mays L.). Dissecting the phenotypic characteristics of these traits, and discovering the candidate chromosomal regions for these traits, are of potential importance for maize yield and quality improvement. In this study, a total of 139 F2:3 family lines derived from EHel and B73, a distinct line with extremely low ear height (EHel), was used for phenotyping and QTL mapping of three kernel size-related traits, including 10-kernel length (KL), 10-kernel width (KWid), and 10-kernel thickness (KT). The results showed that only one QTL for KWid, i.e., qKWid9 on Chr9, with a phenotypic variation explained (PVE) of 13.4% was detected between SNPs of AX-86298371 and AX-86298372, while no QTLs were detected for KL and KT across all 10 chromosomes. Four bulked groups of family lines, i.e., Groups I to IV, were constructed with F2:3 family lines according to the phenotypic comparisons of KWid between EHel and B73. Among these four groups, Group I possessed a significantly lower KWid than EHel (P = 0.0455), Group II was similar to EHel (P = 0.34), while both Group III and Group IV were statistically higher than EHel (P < 0.05). Besides, except Group IV exhibited a similar KWid to B73 (P = 0.11), KWid of Groups I to III were statistically lower than B73 (P < 0.00). By comparing the bulked genotypes of the four groups to EHel and B73, a stable chromosomal region on Chr9 between SNPs of AX-86298372 to AX-86263154, entirely covered by qKWid9, was identified to link KWid with the positive allele of increasing phenotypic effect to KWid from B73, similar to that of qKWid9. A large amount of enzyme activity and macromolecule binding-related genes were annotated within this chromosomal region, suggesting qKWid9 as a potential QTL for KWid in maize.