Genetic analysis and QTL mapping of fruit-related traits in wax gourd (<Emphasis Type="Italic">Benincasa hispida</Emphasis>)

As an important fruit vegetable, fruit-related traits have become one of the breeding hotspots of wax gourd (Benincasa hispida). The fruit traits have an important role on the quality and yield of wax gourd, and QTL mapping of these traits will provide solid basis for fruit character improvement as well as high-yield breeding. In this study, the inheritance of four fruit-related traits, including fruit weight (FW), fruit length (FL), fruit diameter (FD) and flesh thickness (FT), was analyzed. All the frequency distribution of the four traits in an F₂ population showed a single peak skewed distribution, which proved them to be quantitative. Subsequently, based on the high-density genetic map using 140 F₂ individuals, nine QTLs associated with the four traits were detected on chromosome 3, 4, 5, 6, 9, 10 and 11. Four of the nine QTLs had major effect, which were responsible for more than 10.0% of phenotypic variance. Furthermore, the major QTLs of FW, FD and FT shared similar location intervals, which implied that this location might contain some pleiotropic genes. This is the first report on QTL mapping of quantitative trait in wax gourd, which plays an important role for fine mapping of these important fruit traits.     

Genetic linkage map construction and location of QTLs for fruit-related traits in cucumber

A 173‐point genetic linkage map of cucumber (Cucumis sativus L.), consisting of 116 SRAPs, 33 RAPDs, 11 SSRs, 9 SCARs, 3 ISSRs, and 1 STS, was constructed using 130 F₂ progeny derived from a narrow cross between line S94 (Northern China open‐field type) and line S06 (greenhouse European type). The seven linkage groups spanned 1016 cM with a mean marker interval of 5.9 cM. Using the F₂ population and its F₃ derived families, a total of 38 QTLs were detected on five linkage groups with an LOD threshold of 3.0 for nine fruit‐related traits: fruit weight, length, and diameter, fruit flesh thickness, seed‐cavity diameter, fruit‐stalk length, fruit pedicel length, length/diameter and length/stalk ratio. Of the identified QTLs, fsl4.3 for fruit‐stalk length explained the largest portion of phenotypic variation (r² = ～30%). Several QTLs were detected in the same linkage region in different generations and different seasons. Additionally, several QTLs for various fruit traits were mapped to the same or neighbouring marker intervals, suggesting they are possible character associations for controlling cucumber fruit development.     

Identification of QTLs for rice grain size and shape of Iranian cultivars using SSR markers

Grain size is a main component of rice appearance quality. In this study, we performed the SSR mapping of quantitative trait loci (QTLs) controlling grain size (grain length and breadth) and shape (length/breadth ratio) using an F₂ population of a cross between two Iranian cultivars, Domsephid and Gerdeh, comprising of 192 individuals. A linkage map with 88 markers was constructed, which covered 1367.9 cM of the rice genome with an average distance of 18 cM between markers. Interval mapping procedure was used to identify the QTLs controlling three grain traits, and QTLs detected were further confirmed using composite interval mapping. A total of 11 intervals carrying 18 QTLs for three traits were identifed, that included five QTLs for grain length, seven QTLs for grain breadth, and six QTLs for grain shape. A major QTL for grain length was detected on chromosome 3, that explained 19.3% of the phenotypic variation. Two major QTLs for grain breadth were mapped on chromosomes 3 and 8, which explained 34.1% and 20% of the phenotypic variation, respectively. Another two major QTLs were identified for grain shape on chromosomes 3 and 8, which accounted for 27.1% and 20.5% of the phenotypic variance, respectively. The two QTLs that were mapped for grain shape coincided with the major QTLs detected for grain length and grain breadth. Intrestingly, gs2 QTL specific to grain shape was detected on chromosome 2 that explained 15% of the phenotypic variation.     

Identification of QTLs for fruit quality traits in Japanese apples: QTLs for early ripening are tightly related to preharvest fruit drop

Many important apple (Malus × domestica Borkh.) fruit quality traits are regulated by multiple genes, and more information about quantitative trait loci (QTLs) for these traits is required for marker-assisted selection. In this study, we constructed genetic linkage maps of the Japanese apple cultivars ‘Orin’ and ‘Akane’ using F₁ seedlings derived from a cross between these cultivars. The ‘Orin’ map consisted of 251 loci covering 17 linkage groups (LGs; total length 1095.3 cM), and the ‘Akane’ map consisted of 291 loci covering 18 LGs (total length 1098.2 cM). We performed QTL analysis for 16 important traits, and found that four QTLs related to harvest time explained about 70% of genetic variation, and these will be useful for marker-assisted selection. The QTL for early harvest time in LG15 was located very close to the QTL for preharvest fruit drop. The QTL for skin color depth was located around the position of MYB1 in LG9, which suggested that alleles harbored by ‘Akane’ are regulating red color depth with different degrees of effect. We also analyzed soluble solids and sugar component contents, and found that a QTL for soluble solids content in LG16 could be explained by the amount of sorbitol and fructose.     

陆地棉高品质品系纤维品质性状QTL的分子标记及定位

为进一步挖掘利用高品质品系NM03102的优异纤维品质性状的基因,利用陆地棉鲁棉研21作为母本、NM03102为父本构建了F2和F2∶3分离群体。通过7892对SSR引物对亲本进行筛选,获得222对多态性引物,进一步对195个F2群体单株分析得到242个标记位点。其中,182个标记位点连锁构建37个连锁群,共覆盖1661.6 cM,每个连锁群平均包含4.9个标记位点,标记间平均相距9.1 cM,其中35个连锁群被定位到了20条染色体上。利用F2和F2∶3纤维品质数据,通过复合区间作图法,共检测到20个纤维品质性状QTL。其中,1个纤维强度的QTL和1个纤维整齐度的QTL与已有的报道一致,1个纤维强度的QTL和1个麦克隆值的QTL在两世代中稳定存在,这为标记辅助选择奠定了基础。     

陆地棉衣分差异群体产量及产量构成因素

 以衣分差异较大的陆地棉品种为材料,构建了包含188个F₂单株的作图群体,应用6111对SSR引物对亲本进行了分子标记筛选,结果仅获得了123个多态性位点,其中88个位点构建了总长为666.7 cM、平均距离为7.57 cM的遗传图谱,覆盖棉花基因组的14.9%。通过复合区间作图法对F₂单株和F_2∶3家系进行QTL检测,共鉴定出了18个控制产量及产量构成因素变异的QTLs,包括2个衣分QTLs、4个子棉产量QTLs、4个皮棉产量QTLs、2个衣指QTLs、3个单株铃数QTLs、2个铃重QTLs和1个子指QTL。 解释的表型变异分别为\{6.9%\}～16.9%、5.6%～16.2%、4.8%～15.6%、7.7%～13.3%、8.2%～11.6%、6.1%～7%和6.6%。不同QTLs在相同染色体区段上的成簇分布表明与产量性状相关的基因可能紧密连锁或一因多效。产量及产量构成因素QTLs的遗传方式主要以显性和超显性效应为主。检测到的主效QTLs可以用于棉花产量及产量构成因素的分子标记辅助选择。     

甘蓝型油菜产量及相关性状的QTL分析

高产是甘蓝型油菜育种的重要目标之一，产量是多基因控制的数量性状。本文通过QTL作图分析了产量及其相关性状的数量性状位点，以甘蓝型油菜中油821和保604 F₁代小孢子培养获得的DH系为作图群体，构建了由20个连锁群组成的，包括251个分子标记( 2个RFLP标记，72个RAPD标记，91个SSR标记，86个SRAP标记)的遗传连锁图(10个标记没有分配到连锁群中)。图谱的平均图距为6.96 cM，共覆盖油菜基因组1 746.5 cM。在此图谱基础上采取复合区间作图法，检测到与油菜产量及其相关性状有关的QTL共17个。其中控制株高的3个分别位于第4、第9和第10连锁群上，对性状的解释率为9.42%～17.58%；与分枝部位有关的4个分别位于第4、第6和第7连锁群上，其中Bp1 和Bp2 均位于第4连锁群，对性状的解释率为8.13%～15.20%；与主花序有效长有关的3个分别位于第4、第10和第16连锁群上，对性状的解释率为7.49%～23.36%；与一次有效分枝有关的2个分别位于第1、第4连锁群上，对性状的解释率为15.29%～19.58%；与角果总数和千粒重有关的分别位于第4连锁群和第9连锁群上，贡献率分别为17.42%和7.64%；与单株产量有关的3个分别位于第3、第4和第15连锁群，共解释26.60%的表型变异。部分性状的QTL在连锁群上成簇分布,对性状贡献率很大，表现主效QTLs的特点，相应的性状之间也呈显著相关，这表明一因多效或者相关的QTLs之间紧密连锁是性状相关的遗传基础。本研究中与主效QTLs连锁的标记可用于油菜产量性状的分子标记辅助选择。     

QTL hotspots in eggplant (Solanum melongena) detected with a high resolution map and CIM analysis

Fifty-eight F₂ individuals derived from an interspecific cross between cultivated eggplant, Solanum melongena, and its wild relative, S. linnaeanum, were phenotyped for 42 plant, leaf, flower, and fruit traits. Composite interval mapping analysis using genotypic data from 736 molecular markers revealed the positions of 71 statistically significant (P ≤ 0.05) quantitative trait loci (QTL) influencing 32 of the morphological traits. Although most QTL were location-specific, QTL governing three traits (leaf lobing, leaf prickles and prickle anthocyanin) were detected in both experimental locations. Analysis of three additional traits (stem prickles, fruit calyx prickles and fruit length) in both locations yielded QTL in similar but non-overlapping map positions. The majority (69 %) of the QTL corresponded closely with those detected in previous analyses of this data set. However the increased resolution of the linkage map combined with advances in QTL mapping permitted more precise localization, such that the average interval length of these QTL was reduced by 93 %. Thirty-one percent of the QTL were novel, suggesting that simple linear regression with a low density linkage map (the method used in previous studies of this population) missed a substantial portion of significant QTL. Hotspots of QTL affecting plant hairiness, prickliness, and pigmentation were identified on chromosomes 3, 6, and 10, respectively, and may reflect the pleiotropic activity of single structural or regulatory genes at these positions. Based on synteny between the eggplant, tomato, potato and pepper genomes, putative orthologs were identified for 35 % of the QTL suggesting strong conservation of gene function within the Solanaceae. These results should make it easier to target particular loci for map-based cloning and marker-assisted selection studies.     

Quantitative trait loci influencing fruit-related characteristics of tomato grown in high-temperature conditions

The objective of this study was to identify molecular markers linked to fruit-related traits in the tomato subjected to high temperatures. In total, 160 F₂ plants derived from a cross between a heat-tolerant breeding line, CL5915-93D4-1-0-3 (Solanum esculentum), and a heat-sensitive wild accession, L4422 (S. pimpinellifolium), were grown in a greenhouse. Six traits including fruit number, fruit weight, brix, seed number, fruit setting, and flower number were scored. The distributions of fruit number, fruit set, flower number, and seed number were skewed towards heat susceptibility which is known to be characteristic of L4422. Polymorphic bands were generated by PCR-derived methods of RAPD, ISSR and AFLP Polymorphism, the segregation ratio, and distribution over the genome of the above 3 markers were compared. Ten linkage groups, ranging 20.6–151.6 cM in size, were constructed with 62 informative markers spanning a total of 776.3 cM. Fruit-related quantitative trait loci (QTLs) were non-randomly distributed in the tomato genome. For the 6 traits investigated, 21 QTLs were dispersed on linkage groups 2–5. The genetic effects of the various QTLs were differently exhibited, in our study we have respectively found from 10.5% to 30.2% of the variation explained by the QTL for flower number (FRN4) and brix (BX2). Thirteen QTL-mapped markers were unique to 1 trait, and 4 markers were linked to more than 1 trait. Among them, QTLs linked to the I868-470 marker had effects on fruit weight and brix, and a significant positive correlation between these 2 traits was noted (r = 0.35, P < 0.05). Thus, the I868-470 marker may have the potential for simultaneous selection of high fruit weight and brix. These markers also allowed us to align genome linkage maps across distantly related species and to reveal the co-localization between these QTLs and major genes.     

Fine mapping of major QTLs for alkaline tolerance at the seedling stage in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.) through genetic linkage analysis combined with high-throughput DNA sequencing

Exploiting genes and quantitative trait loci (QTLs) related to maize (Zea mays L.) alkaline tolerance is helpful for improving alkaline resistance. To explore the inheritance of maize alkaline tolerance at the seedling stage, a mapping population comprising 151 F_2:3 lines derived from the maize cross between Zheng58, tolerant to alkaline, and Chang7-2, sensitive to alkaline, was used to establish a genetic linkage map with 200 SSR loci across the 10 maize linkage groups, with an average interval of 6.5 cM between adjacent markers. QTLs for alkaline resistant traits of alkaline tolerance rating (ATR), germination rate (GR), relative conductivity (RC), weight per plant (WPP) and proline content (PC) were detected. The obtained results were as follows: Five QTLs on chromosomes 2, 5 and 6 (GR and WPP: chr. 2; PC and ATR: chr. 5; and RC: chr. 6) were mapped. For precise mapping of the QTLs related to alkaline resistance, two bulked deoxyribonucleic acid (DNA) pools were constructed using individual DNAs from the most tolerant 30 F₂ individuals and the most sensitive 30 F₂ individuals according to the ATR and used to establish a high density map of SLAF markers strongly associated with the ATR by specific locus amplified fragment sequencing (SLAF-Seq) combined with super bulked segregant analysis (superBSA). One marker-intensive region involved three SLAFs at 296,000–6,203,000 bp on chromosome 5 that were closely related to the ATR. Combined with preliminary QTL mapping with superBSA, two major QTLs on chromosome 5 associated with alkaline tolerance at the maize seedling stage were mapped to marker intervals of dCap-SLAF31521 and dCap-SLAF31535 and phi024 and dCap-SLAF31521, respectively. These QTL regions involved 9 and 75 annotated genes, respectively. These results will be helpful for improving maize alkaline tolerance at the seedling stage by marker-assisted selection programs and will be useful for fine mapping QTLs for maize breeding.     

Identification of quantitative trait loci across interspecific F2, F2:3 and testcross populations for agronomic and fiber traits in tetraploid cotton

The most widely grown tetraploid Gossypium hirsutum and G. barbadense differ greatly in yield potential and fiber quality and numerous quantitative trait loci (QTLs) have been reported. However, correspondence of QTLs between experiments and populations is poor due to limited number of markers, small population size and inaccurate phenotyping. The purpose of the present study was to map QTLs for yield, yield components and fiber quality traits using testcross progenies between a large interspecific F₂ population and a commercial cotton cultivar as the tester. The results were compared to these from its F₂ and F_2:3 progenies. Of the 177 QTLs identified from the three populations, 65 fiber QTLs and 51 yield QTLs were unique with an average of 8–12 QTLs per traits. All the 26 chromosomes carried QTLs, but differed in the number of QTLs and the number of QTLs between fiber and yield QTLs. The congruence of QTLs identified across populations was higher (20–60 %) for traits with higher heritabilities including fiber quality, seed index and lint percentage, but lower (10–25 %) for lower heritability traits-seedcotton and lint yields. Major QTLs, QTL clusters for the same traits and QTL ‘hotspots’ for different traits were also identified. This research represents the first report using a testcross population in QTL mapping in interspecific cotton crosses and provides useful information for further comparative analysis and marker-assisted selection.     

Mapping QTLs in breeding for drought tolerance in maize (Zea mays L.)

Summary Grain yield in the maize (Zea mays L) plant is sensitive to drought in the period three weeks either side of flowering. Maize is well-adapted to the use of restriction fragment length polymorphisms (RFLPs) to identify a tight linkage between gene(s) controlling the quantitative trait and a molecular marker. We have determined the chromosomal locations of quantitative trait loci (QTLs) affecting grain yield under drought, anthesis-silking interval, and number of ears per plant. The F₃ families derived from the cross SD34(tolerant) × SD35 (intolerant) were evaluated for these traits in a two replicated experiment. RFLP analysis of the maize genome included non-radioactive DNA-DNA hybridization detection using chemiluminescence. To identify QTLs underlying tolerance to drought, the mean phenotypic performances of F₃ families were compared based on genotypic classification at each of 70 RFLP marker loci. The genetic linkage map assembled from these markers was in good agreement with previously published maps. The phenotypic correlations between yield and other traits were highly significant. In the combined analyses, genomic regions significantly affecting tolerance to drought were found on chromosomes 1,3,5,6, and 8. For yield, a total of 50% of the phenotypic variance could be explained by five putative QTLs. Different types of gene action were found for the putative QTLs for the three traits.     

利用已测序水稻品种分析其农艺性状基因座

水稻重要农艺性状的基因定位研究在育种上具有重要意义。2004年在海南陵水县种植两个完全测序水稻品种日本晴与9311的F₂群体及双亲，分别考察了其单株分蘖数、穗数、有效分蘖数、穗长、主穗长、抽穗期、株高和剑叶8个农艺性状3次重复的平均值。用已构建的连锁遗传图谱（Nipponbare/9311-F₂遗传图谱）及Excel 2000和Mapmaker/QTL 1.1b软件对这8个性状间的相互关系和基因位点进行了分析。结果在LOD>2.0和P＜0.005的条件下共检测到41个QTLs，它们分布在水稻所有染色体上，单个QTL对性状表型贡献率11.0%～46.4%，其中大于20%的有22个。对选用已测序材料为亲本构建图谱来探讨水稻农艺性状的分子基础及其育种意义进行了讨论。     

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.     

栽培种花生荚果大小相关性状QTL定位

以远杂9102为母本,徐州68-4为父本杂交衍生的F5和F6共188个家系,构建了一张包含365个标记,总长度713.07 c M,标记间平均距离1.96 c M的栽培种花生遗传图谱。图谱包含22个连锁群,各连锁群平均长度12.37~81.39 c M,连锁群上标记数量3~46个。结合2013和2014年采集的荚果表型数据,采用Win QTLcart 2.5软件的复合区间作图法(composite interval mapping,CIM)进行QTL定位和效应估计。2个环境下共检测到41个QTL,其中与荚果长、宽、厚和百果重相关的QTL分别为13、7、13和8个,表型变异解释率为3.14%~18.27%。有6个QTL在2种环境下被重复检测到,其中百果重相关的2个(q HPWLG13.1、q HPWLG14.1),分布在LG13和LG14连锁群,遗传贡献率为6.95%~14.60%;与荚果长相关的3个(q LPLG2.2、q LPLG13.1、q LPLG14.1),分布在LG2、LG13和LG14连锁群,遗传贡献率为3.14%~18.27%;与荚果厚相关的1个(q TPLG3.4),分布在LG3连锁群,遗传贡献率为8.24%~9.24%。本研究涉及性状存在9个QTL热点区,每个热点区涉及2~3个性状,表型贡献率为3.57%~18.27%。     

Construction of a genetic linkage map and QTL analysis of fiber-related traits in upland cotton (Gossypium hirsutum L.)

A genetic linkage map with 70 loci (55 SSR, 12 AFLP and 3 morphological loci) was constructed using 117 F₂ plants obtained from a cross between two upland cotton cultivars Yumian 1 and T586, which have relatively high levels of DNA marker polymorphism and differ remarkably in fiber-related traits. The linkage map comprised of 20 linkage groups, covering 525 cM with an average distance of 7.5 cM between two markers, or approximately 11.8% of the recombination length of the cotton genome. The present genetic linkage map was used to identify and map the quantitative trait loci (QTLs) affecting lint percentage and fiber quality traits in 117 F_2:3 family lines. Sixteen QTLs for lint percentage and fiber quality traits were identified in six linkage groups by multiple interval mapping: four QTLs for lint percentage, two QTLs for fiber 2.5% span length, three QTLs for fiber length uniformity, three QTLs for fiber strength, two QTLs for fiber elongation and two QTLs for micronaire reading. The QTL controlling fiber-related traits were mainly additive, and meanwhile including dominant and overdominant. Several QTLs affecting different fiber-related traits were detected within the same chromosome region, suggesting that genes controlling fiber traits may be linked or the result of pleiotropy.     

QTL mapping of seedling traits in cucumber using recombinant inbred lines

Seedling traits are important for development, flower bud differentiation, fruit production and fruit quality of cucumber (Cucumis sativus L.). In this study, 160 recombinant inbred lines (RILs), derived from crossing wild cucumber inbred line PI 183967 (C. sativus var. hardwickii) with ‘931’ northern China cultivated cucumber inbred line 931, were employed to identify quantitative trait loci (QTLs) of cotyledon length (Cl), cotyledon width (Cw), hypocotyl length (Hl), first true leaf length (Fll), first true leaf width (Flw), aboveground fresh biomass (Afb) and aboveground dry biomass (Adb) at seedling stage. A genetic map including 307 SSR markers was developed which spanned 993.3 cM, with an average genetic distance of 3.23 cM between adjacent markers. 36 QTLs associated with the seven traits were detected on chromosomes 1, 2, 3, 5 and 6 in four environments (spring and autumn of 2012 and 2013), explaining 6.1 to 23.6% of the observed phenotypic variations. Among the 36 QTLs, 21 were responsible for more than 10% of observed phenotypic variations. We obtained 2, 2, 1 and 3 QTL loci for the traits of Fll, Flw, Afw and Adw, respectively. In addition, genes in the genetic region spanned by SSR15321‐SSR07711 on chr. 5 may contribute to Flw, Afw and Adw.     

Molecular mapping of the brace root traits in sorghum (Sorghum bicolor L. Moench)

The presence and morphology of plant brace roots are important root architecture traits. Brace roots contribute significantly to effective anchorage and water and nutrient uptake during late growth and development, and more importantly, have a substantial influence on grain yield under soil flooding or water limited conditions. However, little is known about the genetic mechanisms that underlie brace root traits. In this study, quantitative trait loci (QTLs) for presence of brace roots from the sorghum landrace “Sansui” were mapped and associated molecular markers were identified. A linkage map was constructed with 109 assigned simple sequence repeat markers using a F₂ mapping population derived from the cross Sansui/Jiliang 2. Two QTLs associated with presence of brace roots were localized on chromosomes 6 and 7. The major QTL on chromosome 7 between markers Dsenhsbm7 and Xcup 70 explained about 52.5% of the phenotypic variation, and the minor QTL on chromosome 6 was flanked by Xtxp127 and Xtxp6 and accounted for 7.0% of phenotypic variation. These results will provide information for the improvement of sorghum root architecture associated with brace roots.     

QTL analysis of cooked rice grain elongation, volume expansion, and water absorption using a recombinant inbred population

The traits of elongation, volume expansion, and water absorption are very important in determining the quality of cooked rice grains. In this study, quantitative trait loci (QTL) analysis of these traits was performed using a recombinant inbred population derived from a cross between two indica cultivars, ‘Zhenshan 97’ and ‘Minghui 63 ,’ which are the parents of the most widely grown hybrid rice in China. Using a linkage map based on 221 molecular marker loci covering a total of 1796 cM, a total of 33 QTLs were identified for the nine traits tested. QTLs were detected on chromosomes 1– 3 , 5– 9 , and 11 , respectively. The QTLs identified included three for cooked rice grain length elongation (chromosomes 2 , 6 , and 11), six for width expansion (chromosomes 1‐ 3 , 6 , 9 , and 11) and two for water absorption (chromosomes 2 and 6). Interestingly, a single QTL located near the wx gene on chromosome 6 seemed to influence all the traits tested for the cooked rice quality.     

Quantitative trait locus mapping of floral and related traits using an F2 population of Aquilegia

The objective of this study was to determine quantitative trait loci (QTL) underlying ten floral and related traits in Aquilegia. The traits assessed were calyx diameter, corolla diameter, petal length, petal blade length, sepal length, sepal width, spur length, spur width, plant height and flower number. These are important traits for ornamental value and reproductive isolation of Aquilegia. QTL analysis of these traits was conducted using single‐marker analysis and composite interval mapping (CIM). We used an F₂ population consisting of 148 individuals derived from a cross between the Chinese wild species Aquilegia oxysepala and the cultivar Aquilegia flabellata ‘pumila’. Resulting CIM analysis identified 39 QTLs associated with these traits, which were mapped on seven linkage groups. These QTLs could explain 1.22–53.28% of the phenotypic variance. Thirty‐one QTLs, which explained more than 10% of the phenotypic variation, were classified as major QTLs. Graphical representations of the QTLs on seven linkage groups were made. Our research provides the potential for future molecular assisted selection breeding programmes and the cloning of target genes through fine mapping.