鲤鱼(Cyprinus carpio L.)头长、眼径、眼间距QTL的定位

用265个AFLP标记、127个微卫星分子标记、37个EST-SSR标记和16个RAPD标记对大头鲤/荷包红鲤抗寒品系的F2雌核发育群体44个个体进行基因型检测, 构建鲤鱼遗传连锁图谱。利用软件WinQTLCart2.5采用复合区间作图法对头长、眼径、眼间距3个性状进行了QTL分析。结果显示, 共检测到5个与头长性状相关的QTL, 分别定位于鲤鱼连锁图谱的LG2(qHS-2-1)、LG3 (qHS-3-1)、LG40(qHS-40-1)和LG4 (qHS-4-2和qHS-4-3) 上。其中qHS-40-1拥有最大的 LOD值, 为7.94, 可解释的表型变异为 34.29%。qHS-4-2的LOD值最小, 为5.03, 可解释的表型变异为11.52%。5个与头长性状相关的 QTL 加性效应值均为负值。检测到两个与眼径性状相关的QTL, 分别定位于鲤鱼连锁图谱的LG39连锁群(qED-39-1)和LG40连锁群(qED-40-1)上, 其中qED-40-1的LOD值比较大, 为2.76, 其加性效应值为负值, 可以解释5.62%的表型变异; qED-39-1的LOD值为2.72, 加性效应值为正值, 可以解释9.77%的表型变异。检测到两个与眼间距性状相关的QTL, 分别定位到鲤鱼连锁图谱的LG20连锁群(qEC-20-1)和LG28 连锁群(qEC-28-1)上。其中qEC-20-1的LOD值比较大, 为3.77, 加性效应值为正值, 可以解释8.29%的表型变异; qEC-28-1的LOD值为2.79, 对应的加性效应值为负值, 可以解释8.88%的表型变异     

鲤饲料转化率性状的QTL 定位及遗传效应分析

数量性状(QTL)定位是实现分子标记辅助育种、基因选择和定位、培育新品种及加快性状遗传研究进展的重要手段。饲料转化率是鲤鱼的重要经济性状和遗传改良的主要目标, 而通过QTL 定位获得与饲料转化率性状紧密连锁的分子标记以及相关基因是遗传育种的重要工具。研究利用SNP、SSR、EST-SSR 等分子标记构建鲤鱼(Cyprinus carpio L.)遗传连锁图谱并对重要经济性状进行QTL 定位。选用174 个SSR 标记、41 个EST-SSR 标记、345 个SNP 标记对德国镜鲤F2 代群体68 个个体进行基因型检测, 用JoinMap4.0 软件包构建鲤鱼遗传连锁图谱。再用MapQTL5.0 的区间作图法(Interval mapping, IM)和多QTL 区间定位法(MQMMapping, MQM)对饲料转化率性状进行QTL 区间检测, 通过置换实验(1000 次重复)确定连锁群显著性水平阈值。结果显示, 在对饲料转化率性状的多QTL 区间定位中, 共检测到15 个QTLs 区间, 分布在9 个连锁群上, 解释表型变异范围为17.70%—52.20%, 解释表型变异最大的QTLs 区间在第48 连锁群上, 为52.20%。HLJE314-SNP0919(LG25)区间标记覆盖的图距最小, 为0.164 cM; 最大的是HLJ1439-HLJ1438(LG39)区间,覆盖图距为24.922 cM。其中区间HLJ1439-HLJ1438、HLJ922 -SNP0711 解释表型变异均超过50.00%, 可能是影响饲料转化率性状的主效QTLs 区间。与饲料转化率相关的15 个QTLs 的加性效应方向并不一致, 有3个区间具有负向加性效应, 平均为?0.027; 12 个正向加性效应, 平均值为0.06。研究检测出的与鲤鱼饲料转化率性状相关的QTL 位点可为鲤鱼分子标记辅助育种和更进一步的QTL 精细定位打下基础。       

玉米雌雄开花间隔天数、结穗率与产量的数量性状位点（QTL）分析

采用SSR标记连锁图谱和复合区间作图法在山西灌溉和干旱胁迫条件下,对玉米(Zea mays L.)自交系黄早四×掖107组合的F_3群体雌雄开花间隔天数(ASI)、结穗率和籽粒产量进行了数量性状位点(QTL)定位及基因效应分析。结果表明,在两种水分处理下,ASI、结穗率与籽粒产量的相关性均达到显著水平(P<0.05)。在灌溉和干旱胁迫卜,分别检测到3个和2个控制ASI的QTL,位于第1、2、3和第2、5染色体上。在灌溉条件下,在第3和第6染色体上各检测到1个控制结穗率的QTL,基因作用方式呈加性或部分显性,可解释19.9％的表型变异;在干旱条件下,在第3、7、10染色体上共检测到4个控制结穗率的QTL,基因作用方式为显性或部分显性,可解释60.4％的表型变异。在灌溉和干旱胁迫下,控制产量的QTL分别定位在第3、6、7和第1、2、4、8染色体上,基因作用方式均以加性或部分显性为主,可解释的表型变异为7.3％～22.0％。在干旱条件下,借助连锁分子标记和基因效应分析,可构建包含ASI、结穗率和产量QTL的选择指数,用于分子标记辅助育种。     

玉米雌雄开花间隔天数、结穗率与产量的数量性状位点(QTL)分析

采用SSR标记连锁图谱和复合区间作图法在山西灌溉和干旱胁迫条件下,对玉米(Zea mays L.)自交系黄早四×掖107组合的F3群体雌雄开花间隔天数(ASI)、结穗率和籽粒产量进行了数量性状位点(QTL)定位及基因效应分析.结果表明,在两种水分处理下,ASI、结穗率与籽粒产量的相关性均达到显著水平(P＜0.05).在灌溉和干旱胁迫下,分别检测到3个和2个控制ASI的QTL,位于第1、2、3和第2、5染色体上.在灌溉条件下,在第3和第6染色体上各检测到1个控制结穗率的QTL,基因作用方式呈加性或部分显性,可解释19.9%的表型变异;在干旱条件下,在第3、 7、10染色体上共检测到4个控制结穗率的QTL,基因作用方式为显性或部分显性,可解释60.4%的表型变异.在灌溉和干旱胁迫下,控制产量的QTL分别定位在第3、6、7和第1、2、4、8染色体上,基因作用方式均以加性或部分显性为主,可解释的表型变异为7.3%～22.0%.在干旱条件下,借助连锁分子标记和基因效应分析,可构建包含ASI、结穗率和产量QTL的选择指数,用于分子标记辅助育种.     

不同发育时期小麦粒重性状QTL的动态分析

利用6044×01-35构建的重组自交系(RIL)群体为试验材料,对小麦粒重性状进行发育动态QTL分析。结果表明,在小麦花后子粒灌浆的7个不同时期,两个试验点共检测到16个与粒重性状相关的QTL。其中开花后20d检测到的单穗粒重QTL位于2A染色体上,解释率达12%,遗传效应超过10;两环境下控制千粒重QTL在7个时期均被检测到。花后的各个时期均能在Xgwm448-Xgpw7399标记区间定位到千粒重QTL。其中花后10d检测到1个千粒重QTL,位于2A染色体的Xgwm448-Xgpw7399标记区间,解释较大的表型变异,达到18%。Qtl8、Qtl13和Qtl14均定位在Xgwm448-Xgpw7399标记区间的同一位置,共同解释11%的表型变异。花后20d和花后25d均检测到1个QTL,位于2A染色体的Xgwm372-Xgwm95标记区间的不同位点,均能解释4%的表型变异。花后40d检测到1个QTL,位于1D染色体的Xwmc93-Xgpw2224标记区间,解释1%的表型变异。从连锁群的位置上看,控制千粒重的QTL主要集中在2A染色体的Xgwm448-Xgpw7399标记区间,这是一个控制千粒重QTL的富集区域,以期进行精细定位和图位克隆。     

干旱胁迫和正常灌溉条件下玉米开花相关性状的QTL分析

干旱是影响玉米生产的重要限制因素,特别是花期对干旱胁迫非常敏感.本研究通过对玉米L050× B73的180个F2:3家系进行开花期干旱胁迫处理和分子标记鉴定,重点对开花相关性状进行了数量性状位点(QTL)分析.结果表明,在干旱胁迫处理条件下,存在与出苗到抽雄天数有关的6个QTL,位于第1、6、9染色体上各1个,位于第3染色体上有3个,共可解释的表现型变异为55.0%;基于出苗到散粉天数检测到4个QTL,其中两个位于第3染色体上,位于第1、2染色体上各1个,共可解释的表型变异为52.8%;对出苗到吐丝天数检测到分别位于第3、6染色体上的2个QTL,共可解释的表现型变异为20.4%;对抽雄至吐丝间隔天数(ASI)只检测位于第6染色体上的1个QTL,可解释6.5%的表现型变异.而正常灌溉环境下,检测到出苗到抽雄天数检测到1个QTL,位于第9染色体上,可解释的变异为15.0%;对出苗到散粉天数检测到3个QTL,位于第1、3、9染色体上,共可解释的变异为55.0%;对出苗到吐丝天数检测到4个QTL,分别位于第1、2、3、7染色体上.共可解释表现型变异的46.8%;对ASI检测到分别位于第2、6染色体上的2个QTL,可解释的变异为15.5%.这些QTL的基因效应以显性与超显性为主.     

油菜油分、蛋白质和硫苷含量相关性分析及QTL 定位

为定位与油分、蛋白质和硫苷含量等品质性状相关的数量性状位点(QTL), 以2个含油量较高的甘蓝型油菜(Brassica napus)品系8908B和R1为研究材料, 配置正反交组合。在正反交F₂代群体中, 含油量和蛋白质含量都存在极显著的负相关, 相关系数分别为-0.68和-0.81, 含油量和硫苷含量相关性不显著; 蛋白质含量和硫苷含量在正交群体中相关性不显著, 但在反交群体中存在显著负相关(相关系数r =-0.45)。利用正交F₂代群体中的118个单株, 构建了包含121个标记的遗传连锁图谱, 图谱长1 298.7 cM, 有21个连锁群(LGs)。采用复合区间作图法, 在连锁图上定位了2个与含油量有关的QTL, 分别位于LG8和LG10, 其贡献率分别为4.8%和13.7%, 增效基因都来源于R1; 定位了2个与蛋白质含量有关的QTL: pro1 和 pro2, 分别位于LG1和LG3, 其贡献率分别为15.2%和14.1%, 位点pro1由8908B提供增效基因, pro2则由R1提供增效基因; 定位了4个与硫苷含量有关的QTL, 其中LG20上有2个, LG4和LG8上各1个, 它们的贡献率在1.9%-25.4%之间, 除LG20上glu1的增效基因来自R1外, 其余3个QTL位点均由8908B提供增效基因。     

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。     

甘蓝型油菜遗传图谱的构建及单株产量构成因素的QTL分析

采用常规品系04-1139与高产多角果品系05-1054构建的F2代群体为作图群体, 运用SSR(Simple sequence repeat)和SRAP(Sequence-related amplified polymorphism)构建分子标记遗传图谱并对甘蓝型油菜单株产量构成因素进行QTL分析。遗传图谱包含200个分子标记, 分布于19个连锁群上, 总长度1 700.23 cM, 标记间的平均距离8.50 cM。采用复合区间作图法(Composite interval mapping, CIM)对单株产量构成因素(单株有效角果数、每果粒数和千粒重)进行QTL分析, 共检测到12个QTL: 其中单株有效角果数4个QTL, 分别解释表型变异为35.64%、12.96%、28.71%和34.02%; 每果粒数获得5个QTL, 分别解释表型变异为8.41%、7.87%、24.37%、8.57%和14.31%; 千粒重获得３个QTL, 分别解释表型变异为2.33%、1.81%和1.86%。结果表明: 同一性状的等位基因增效作用可以同时来自高值亲本和低值亲本; 文章中与主效QTL连锁的标记可用于油菜产量性状的分子标记辅助选择和聚合育种。     

鲤鱼体长性状的QTL定位及其遗传效应分析

以大头鲤/荷包红鲤抗寒品系的重组自交系群体及其遗传连锁图谱, 利用Windows Map Manager 2.0的标记回归法进行QTL单标记定位分析和复合区间作图法进行QTL区间检测, 通过置换实验(1 000次重复)确定连锁群显著性水平阈值。在体长性状的标记回归研究中, 共7个标记达到显著水平(P<0.01), 对性状的贡献率为14.00%～27.00%, 其中3个标记达到极显著水平(P<0.001)。HLJ534, HLJ319, HLJ370座位可能与影响鲤鱼体长性状的主效基因连锁。在体长性状的QTL区间定位研究中, 共6个QTL达到连锁群显著水平(P=0.05), 对性状的贡献率为11.33.%～23.12%, 其中2个达到连锁群极显著性水平(P=0.01), 它们的加性效应方向并不一致。HLJ190-HLJ497区间和HLJ479-HLJ483区间是影响鲤鱼体长性状的主效QTL区间。     

Mapping quantitative trait loci (QTL) for body weight, length and condition factor traits in backcross (BC1) family of Common carp (Cyprinus carpio L.)

Body weight and length are economical important traits in aquaculture species influenced by quantitative trait loci (QTL) and environmental factors. In this study, a backcross (BC1) common carp family, with 86 progeny, was utilized to construct genetic map for preliminary QTL mapping. The genetic map was constructed with 366 markers, including 191 SNP from gene, coverage 50 linkage groups with an average marker distance of 18.5 cM. A total of fourteen QTLs associated with body weight (BW), body length (BL) and condition factor (K) were detected on ten linkage groups (LGs). Among these QTLs detected, three (qBW8, qBL8 and qK8) were associated with BW, BL and K respectively, were mapped on LG8. qBW8 and qK8 were identified on similar interval neared locus HLJ2394 explained 14.9 and 20.9 % of the phenotype variance, while qBL8 was identified on separate nearby locus HLJ571 with 30.8 % of phenotype variance. Two QTLs, qBW13 and qK13, related with BW and K separately, were found on LG13 at different locus with phenotype variance of 25.3 and 20.9 %. Other two QTLs, qBW19 and qBL19, associated to BW and BL were mapped on same region near SNP0626 on LG19, and explained 10.3 and 15.6 % of phenotype variance. While other seven QTLs related with BW and BL were located on different LGs. Confidential interval was ranged from 1.1 to 10 cM in the present study. These markers, with lower QTL interval, have great influence on the body weight and length. Therefore, these QTLs will be helpful to find out the genes related with specific trait.     

Integration genetic linkage map construction and several potential QTLs mapping of Chinese shrimp (Fenneropenaeus chinensis) based on three types of molecular markers

In this study, totally 54 selected polymorphic SSR loci of Chinese shrimp (Fenneropenaeus chinensis), in addition with the previous linkage map of AFLP and RAPD markers, were used in consolidated linkage maps that composed of SSR, AFLP and RAPD markers of female and male construction, respectively. The female linkage map contained 236 segregating markers, which were linked in 44 linkage groups, and the genome coverage was 63.98%. The male linkage map contained 255 segregating markers, which were linked in 50 linkage groups, covering 63.40% of F. chinensis genome. There were nine economically important traits and phenotype characters of F. chinensis were involved in QTL mapping using multiple-QTL mapping strategy. Five potential QTLs associated with standard length (q-standardl-01), with cephalothorax length (q-cephal-01), with cephaloghorax width (q-cephaw-01), with the first segment length (q-firsel-01) and with anti-WSSV (q-antiWSSV-01) were detected on female LG1 and male LG44 respectively with LOD> 2.5. The QTL q-firsel-01 was at 73.603 cM of female LG1. Q-antiWSSV-01 was at 0 cM of male LG44. The variance explained of these five QTLs was from 19.7-33.5% and additive value was from -15.9175 to 7.3675. The closest markers to these QTL were all SSR, which suggested SSR marker was superior to AFLP and RAPD in the QTL mapping.     

A Genome-Wide Association Study Reveals That Genes with Functions for Bone Development Are Associated with Body Conformation in Catfish

Body conformation is of great scientific and commercial interest for aquaculture fish species because it affects biological adaptation of the organism to environments, and is of economic importance to the aquaculture industry considering its direct effect on fillet yield. Catfish is the primary aquaculture species in the USA. Two major species used in the aquaculture industry, channel catfish and blue catfish, differ in body shape and therefore the backcross progenies serve as a good model for quantitative trait locus (QTL) analysis. Here, a genome-wide association study (GWAS) with hybrid catfish was conducted to identify the QTL for body conformation, including deheaded body length (DBL), body length (BL), body depth (BD), and body breadth (BB), which were all standardized by cubic root of body weight. Overall, the results indicate that the traits are polygenic. For DBL, linkage group (LG) 2 and LG 24 contain significant QTL, and LG 13 and LG 26 contain suggestively associated QTL (?log₁₀(P value) > 4.5). Compared with DBL, additional SNPs were identified to be associated with body length on LG 2, LG 7, and LG 18. Although no significant QTL for body depth was found, three suggestively associated QTLs were identified on LG 5, LG 13, and LG 14. No SNP for body breadth reached the threshold for suggestive association. Genes close to the associated SNPs were determined, many of which are known to be involved in bone development. This work therefore provides the basis for future identification of causal genes for the control of body conformation.     

Mapping QTLs for Swimming Ability Related Traits in Cyprinus carpio L.

Body height (BH), head length (HL), snout length (SL), and tail length (TL) are important traits related with swimming ability of fish. Therefore, improving these traits will increase the production which is the basic goal of aquaculture breeding. To understand the genetic basis of swimming ability related traits in Cyprinus carpio L., a high-density linkage map spanning 3,301 cM in 50 linkage groups was utilized for quantitative trait locus (QTL) mapping. Mapping family comprised 190 offspring and 627 molecular markers were genotyped with average distance of 5.6 cM. A total of 15 QTLs including four (qBH13, qBH30, qBH33, qBH48) for BH, four (qHL10, qHL18, qHL29, qHL48) for HL, three (qSL24, qSL27, qSL45) for SL, and four (qTL15, qTL17, qTL18, qTL44) for TL were detected on 13 linkage groups LG10, LG13, LG15, LG17, LG18, LG24, LG27, LG29, LG30, LG33, LG44, LG45, and LG48. Each LG consisted on single QTL except LG18 and LG48. LG18 was found with two QTLs associated with HL and TL. While LG48 was comprised, the QTLs related with BH and HL. The phenotype variance was recorded from 12.6 to 40.6 %. Five QTLs, qHL48, qSL45, qTL15, qTL18, and qTL44, explained phenotype variance of >20 % with a significant levels of 0.047, 0.049, 0.037, 0.025, and 0.023, respectively. The neighbored loci of these QTLs were considered as main region of chromosomes controlling the traits. These identified genetic regions will be the main source of discovering gene(s) associated with swimming ability related traits in C. carpio L.     

High-Density Genetic Linkage Mapping in Turbot (Scophthalmus maximus L.) Based on SNP Markers and Major Sex- and Growth-Related Regions Detection

This paper describes the development of a high density consensus genetic linkage map of a turbot (Scophthalmus maximus L.) family composed of 149 mapping individuals using Single Nucleotide Polymorphisms (SNP) developed using the restriction-site associated DNA (RAD) sequencing technique with the restriction enzyme, PstI. A total of 6,647 SNPs were assigned to 22 linkage groups, which is equal to the number of chromosome pairs in turbot. For the first time, the average marker interval reached 0.3958 cM, which is equal to approximately 0.1203 Mb of the turbot genome. The observed 99.34% genome coverage indicates that the linkage map was genome-wide. A total of 220 Quantitative Traits Locus (QTLs) associated with two body length traits, two body weight traits in different growth periods and sex determination were detected with an LOD > 5.0 in 12 linkage groups (LGs), which explained the corresponding phenotypic variance (R²), ranging from 14.4–100%. Among them, 175 overlapped with linked SNPs, and the remaining 45 were located in regions between contiguous SNPs. According to the QTLs related to growth trait distribution and the changing of LGs during different growth periods, the growth traits are likely controlled by multi-SNPs distributed on several LGs; the effect of these SNPs changed during different growth periods. Most sex-related QTLs were detected at LG 21 with a linkage span of 70.882 cM. Additionally, a small number of QTLs with high feasibility and a narrow R² distribution were also observed on LG7 and LG14, suggesting that multi LGs or chromosomes might be involved in sex determination. High homology was recorded between LG21 in Cynoglossus semilaevis and turbot. This high-saturated turbot RAD-Seq linkage map is undoubtedly a promising platform for marker assisted selection (MAS) and flatfish genomics research.     

Construction of the First High-Density Genetic Linkage Map and Analysis of Quantitative Trait Loci for Growth-Related Traits in <Emphasis Type="Italic">Sinonovacula constricta</Emphasis>

The razor clam (Sinonovacula constricta) is an important aquaculture species, for which a high-density genetic linkage map would play an important role in marker-assisted selection (MAS). In this study, we constructed a high-density genetic map and detected quantitative trait loci (QTLs) for Sinonovacula constricta with an F₁ cross population by using the specific locus amplified fragment sequencing (SLAF-seq) method. A total of 315,553 SLAF markers out of 467.71 Mreads were developed. The final linkage map was composed of 7516 SLAFs (156.60-fold in the parents and 20.80-fold in each F₁ population on average). The total distance of the linkage map was 2383.85 cM, covering 19 linkage groups with an average inter-marker distance of 0.32 cM. The proportion of gaps less than 5.0 cM was on average 96.90%. A total of 16 suggestive QTLs for five growth-related traits (five QTLs for shell height, six QTLs for shell length, three QTLs for shell width, one QTL for total body weight, and one QTL for soft body weight) were identified. These QTLs were distributed on five linkage groups, and the regions showed overlapping on LG9 and LG13. In conclusion, the high-density genetic map and QTLs for S. constricta provide a valuable genetic resource and a basis for MAS.     

Integration genetic linkage map construction and several potential QTLs mapping of Chinese shrimp (<Emphasis Type="Italic">Fenneropenaeus chinensis</Emphasis>) based on three types of molecular markers

In this study, totally 54 selected polymorphic SSR loci of Chinese shrimp (Fenneropenaeus chinensis), in addition with the previous linkage map of AFLP and RAPD markers, were used in consolidated linkage maps that composed of SSR, AFLP and RAPD markers of female and male construction, respectively. The female linkage map contained 236 segregating markers, which were linked in 44 linkage groups, and the genome coverage was 63.98%. The male linkage map contained 255 segregating markers, which were linked in 50 linkage groups, covering 63.40% of F. chinensis genome. There were nine economically important traits and phenotype characters of F. chinensis were involved in QTL mapping using multiple-QTL mapping strategy. Five potential QTLs associated with standard length (q-standardl-01), with cephalothorax length (q-cephal-01), with cephaloghorax width (q-cephaw-01), with the first segment length (q-firsel-01) and with anti-WSSV (q-antiWSSV-01) were detected on female LG1 and male LG44 respectively with LOD > 2.5. The QTL q-firsel-01 was at 73.603 cM of female LG1. Q-antiWSSV-01 was at 0 cM of male LG44. The variance explained of these five QTLs was from 19.7–33.5% and additive value was from −15.9175 to 7.3675. The closest markers to these QTL were all SSR, which suggested SSR marker was superior to AFLP and RAPD in the QTL mapping.     

An AFLP, SRAP, and SSR Genetic Linkage Map and Identification of QTLs for Fruit Traits in Pear (Pyrus L.)

In this study, a population of 97 F₁ seedlings from a cross between the interspecific hybrid (European × Chinese species) pear ‘Bayuehong’ (BYH) and the Chinese pear ‘Dangshansuli’ (DS) was used for establishing linkage maps and for quantitative trait loci (QTL) discovery. Using amplified length polymorphism (AFLP), simple sequence repeat (SSR), and sequence-related amplified polymorphism (SRAP) markers, along with the S locus for self-incompatibility, two parental linkage maps were constructed. The map of BYH consisted of 214 markers (143 AFLPs, 64 SRAPs, 6 SSRs, and S) mapped on all 17 linkage groups of the pear genome with a total length of 1,352.7 cM. The map of DS was comprised of 122 markers (83 AFLPs, 37 SRAPs, 1 SSR, and S) distributed along all 17 linkage groups and covering 1,044.3 cM. Based on phenotypic data from two successive years (2007 and 2008) for six fruit traits, including fruit weight (in grams), fruit diameter (in centimeters), fruit length (in centimeters), soluble solids content, fruit shape index, and maturity date, 19 QTLs were detected. These QTLs were mapped on LG 01, LG 02, LG 05, LG 07, LG 08, LG 10 of the BYH map and LG 02, LG 06, LG 15 of the DS map and accounting for 7.1 to 22.0 % of the observed phenotypic variance. Four QTLs, Pfi-8-1 for fruit shape index, Pfm-8-1 for fruit maturity date, Pfw-7-1 and Pfw-8-1 for fruit weight (in grams), with LOD scores ≥3.5, were deemed as major genes. QTLs Pfi-8-1, Pfm-8-1, and Pfw-8-1 were co-localized on LG 08 of the BYH map, along with Pfl-8-1 for fruit length. It was observed that on LG 07 of the BYH map, QTLs for fruit length, fruit shape index, and fruit weight were clustered. When QTL locations from both years were compared, Pfl-7-1 and Pfl-7-2 for fruit length, Pfi-2-1 and Pfi-2-2 for fruit shape index, and Pfm-8-1 and Pfm-8-2 for fruit maturity date were stably mapped onto the same linkage groups, respectively. Moreover, Pfm-8-1 and Pfm-8-2 were also located within the same region of LG 08 of the BYH map.