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。       

镜鲤体长、体高、体厚性状QTL定位分析

以镜鲤全同胞家系为材料,用246个SSR和306个SNP标记构建了鲤鱼的连锁图谱,利用GridQTL软件对体长(SL)、体高(H)、体厚(BT)和体长/体高(SLH)进行了QTL定位分析。结果显示:共检测到14个相关的QTL,分布在7个连锁群上。其中,7个与体长相关的QTL——LG6、LG17、LG21、LG23和LG35连锁群上的QTL为显著水平(P<0.05),LG1和LG28上达到极显著水平(P<0.01),可解释表型变异为6.6%~12.6%;3个与体高相关的QTL均为极显著水平(P<0.01)位于LG17、LG23和LG28上,可解释表型变异分别为11.6%、12.7%和15.6%;2个与体厚相关的QTL均为显著水平(P<0.05)位于LG23和LG28上,可解释表型变异分别为8.6%和7.2%;2个与体长/体高相关的QTL均为显著水平(P<0.05)位于LG21和LG35上,可解释表型变异均为8.2%。     

梨分子遗传图谱构建及生长性状的QTL分析

利用鸭梨和京白梨杂交得到的F1(145株)实生苗为作图群体,通过对AFLP和SSR两种分子标记的遗传连锁分析,应用Joinmap 3.0作图软件,368个AFLP标记、34个SSR标记构建了分属18个连锁群的梨分子遗传连锁图谱,各连锁群的LOD值在4.0～7.0范围之间,图谱总长度覆盖梨基因组1395.9cM,平均图距为3.8cM.采用区间作图法,对该群体与生长性状相关的调查数据进行QTL分析,检测到与新梢生长量、新梢茎粗、节间长度、节间数量、树干径、树高及皮孔密度7个农艺性状连锁的QTL位点35个,其中主效QTL位点11个(LOD≥3.5).与生长性状相关的农艺性状QTL位点多集中在LG16连锁群上.     

水稻叶片性状和根系活力的QTL定位

应用由247个株系组成的珍汕97B/密阳46重组自交系(RIL)群体及其分子标记连锁图谱,检测控制剑叶、倒二叶、倒三叶的5个形态性状和控制根系伤流量性状的数量性状座位(QTL)。在9个标记区间检测到控制叶片形态性状的24个QTL,LOD值为2．9～11．8,单个QTL的表型变异贡献率为4．0％～32．5％;分别检测到56对和4对控制叶片形态和根系活力的上位性互作,绝大多数互作发生在2个不表现加性效应的座位之间。与该群体产量性状QTL的研究结果相比较,发现控制叶片性状和根系活力的QTL与产量性状QTL往往处于相似的染色体区间。     

镜鲤体重的QTL定位

本研究利用217个微卫星标记和336个SNPs标记对德国镜鲤F2代68个个体基因组DNA进行基因型检测.其中507个标记共组成62个连锁群,覆盖基因组总长度为2 805.85 cM,标记间平均距离为6.31 cM;利用软件MapQTL 4.0采用区间作图法对体重性状进行QTL定位分析.研究结果共检测到14个与体重性状有关的QTLs,分布于9个连锁群.其中BW-5-1有最大的LOD值,为4.46;BW-1-1的LOD值最小,为2.25.单个QTL平均解释表型变异介于14.10%~45.50%之间,其中贡献率大于20%的主效QTLs有9个.通过BLASTX与斑马鱼蛋白质序列数据库进行序列比对,找到了与斑马鱼酰基辅酶A脱氢酶蛋白、胰淀粉酶α2蛋白、Apoeb protein和甘油醛-3-磷酸脱氢酶蛋白同源的分子标记.本研究结果对分子标记辅助育种具有重要应用价值.     

应用重组自交系群体定位大豆抗虫QTL

以大豆组合科丰1号×南农1138-2衍生的重组自交系(RIL)群体为材料构建遗传连锁图谱, 利用软件 Cartographer V.2.5 采用复合区间作图法检测定位大豆抗虫QTL。以斜纹夜蛾幼虫重为抗性指标, 检测到 1 个与抗虫性有关的 QTL, 位于G20-O连锁群上, 其端距离为31.91 cM, 加性效应估计值为0.0408, 对性状变异的解释率为 11.74％; 以蛹重为抗性指标, 检测到 2 个与抗虫性有关的 QTL, 分别位于G8-D1b+W和G17-L连锁群上, 其端距离分别为 14.71 cM和0.01 cM, 加性效应估计值分别为-0.0139和0.0103, 对性状变异的解释率分别为 11.30％和6.36％。     

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。     

苹果叶片相关性状的QTL定位及其遗传效应分析

利用苹果栽培品种‘红富士’和新疆野苹果优系‘红肉苹果’杂交的110个F1株系为作图群体,构建了苹果的分子遗传图谱,采用区间作图法对苹果9个叶片相关性状(叶片长度、叶片宽度、叶片厚度、叶柄长度、叶片面积、总叶绿素含量、叶绿素a含量、叶绿素b含量和类胡萝卜素含量)进行了QTL定位分析。结果显示:从110个F1株系中共检测到20个控制叶片相关性状的QTL位点,分布在第1、2、3、4、5、7、8、10、11、12、16、17连锁群上;各QTL位点的LOD值在2.58~3.55之间,其中主效QTL位点2个(LOD≥3.5),可解释11.63%~16.36%的表型变异。获得紧密连锁的特异标记(CH05d11-435m、CH04c06-201m)为进一步进行QTL精细定位提供了参考。     

猪2号染色体遗传连锁图谱的构建与QTL定位分析

构建了猪2号染色体的遗传连锁图谱,并进一步进行了重要生产性状数量性状位点的定位,结果表明,7个微卫星位点均为中高度多态性位点,多态信息含量为0．40182－0．58477,可以满足遗传连锁图谱构建的要求,构建的资源家系遗传连锁图谱总长152．9cM,位点的排列顺序与USDA结果一致,但除了Sw2516与Sw1201标记区间外,所有标记区间距离均大于USDA图谱,将连锁图谱与性状记忆结合起来,进一步进行了猪数量性状位点定位的研究,在2号染色体发现了显著影响活体估测瘦肉率等活体估测性状的QTLs,此外还发现眼肌高度和背最长肌大理石纹的QTLs,其中影响活体估测瘦肉率的QTL达到了染色体显著的水平（P＜0．01）,且解释性状的表型变异达21．55％,影响眼肌高度和背最长肌大理石纹的QTLs分别可以解释10．12％和10．97％的表型变异,影响活体估测性状的QTLs加性效应与显性效应作用方向相反,影响眼肌高度的QTL加性效应与显性效应相同,在大白猪中具有增效等位基因,定位的QTLs效应较大,为在群体中开展分子标记辅助育种奠定了理论基础。     

基于整合图谱的鲤生长相关性状QTL的分布及变异规律

单个群体数量性状位点(QTL)的检测和识别效率通常是有限的,而多个群体能提高QTL的检测效率并能更好地了解其等位基因的变异和分布.本研究利用4个群体构建了鲤鱼的整合图谱,在此基础上比较分析了不同群体QTL的分布及变异.整合图谱长度为2371.6cM,包含257个微卫星(SSR)和421个SNP标记分布于42个连锁群,平均标记间隔为3.7cM.将4个群体的体重、体长、体高和体厚共67个QTL定位到整合图谱上进行比较分析,发现仅有1个QTL为3个群体共享,9个QTL为2群体共享,未发现4个群体均共享的QTL.QTL的比较分析结果表明,共享QTL可能在控制不同鲤鱼种质间生长性状中起主要作用.此外,探讨了QTL在不同群体间变化的原因和规律,同时揭示了主效和微效基因在不同群体中的遗传表现,为QTL定位策略和分子育种改良鲤生长性状提供理论基础.     

Mapping of Quantitative Trait Loci for Butter Content and Hardness in Cocoa Beans (Theobroma cacao L.)

Cocoa butter is an important raw material for the chocolate, pharmaceutical, and cosmetic industries. The butter content and quality in cocoa beans are genetically controlled characteristics, and affect its commercial value and industrial applicability. In the present work, an F₂ population derived from the cross between the ICS-1 and Scavina-6 cocoa clones was used for molecular mapping. A linkage map was constructed based on amplified fragment length polymorphism, random amplified polymorphic DNA, and simple sequence repeat markers, resulting in a total of 273 markers, distributed in 14 linkage groups (LGs). Phenotyping of butter content was performed after ether extraction and butter hardness was determined by sweeping differential calorimetry. One quantitative trait locus (QTL) associated to butter content was mapped at linkage group 9 (LG9) and two QTLs for butter hardness were identified at linkage groups 9 and 7 (LG9 and LG7). The two QTLs mapped at the LG9 explained 51.0% and 28.8% of the phenotypic variation for butter content and hardness, respectively. These QTLs were concentrated in the same map region, suggesting a close genetic linkage or pleiotropic effect. The QTLs identified may be useful in further marker-assisted selection breeding programs aimed at cocoa butter quality improvement.     

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.     

Construction of a High-Density Microsatellite Genetic Linkage Map and Mapping of Sexual and Growth-Related Traits in Half-Smooth Tongue Sole (Cynoglossus semilaevis)

High-density genetic linkage maps of half-smooth tongue sole were developed with 1007 microsatellite markers, two SCAR markers and an F1 family containing 94. The female map was composed of 828 markers in 21 linkage groups, covering a total of 1447.3 cM, with an average interval 1.83 cM between markers. The male map consisted of 794 markers in 21 linkage groups, spanning 1497.5 cM, with an average interval of 1.96 cM. The female and male maps had 812 and 785 unique positions, respectively. The genome length of half-smooth tongue sole was estimated to be 1527.7 cM for the females and 1582.1 cM for the males. Based on estimations of the map lengths, the female and male maps covered 94.74 and 94.65% of the genome, respectively. The consensus map was composed of 1007 microsatellite markers and two SCAR markers in 21 linkage groups, covering a total of 1624 cM with an average interval of 1.67 cM. Furthermore, 159 sex-linked SSR markers were identified. Five sex-linked microsatellite markers were confirmed in their association with sex in a large number of individuals selected from different families. These sex-linked markers were mapped on the female map LG1f with zero recombination. Two QTLs that were identified for body weight, designated as We-1 and We-2, accounted for 26.39% and 10.60% of the phenotypic variation. Two QTLs for body width, designated Wi-1 and Wi-2, were mapped in LG4f and accounted for 14.33% and 12.83% of the phenotypic variation, respectively. Seven sex-related loci were mapped in LG1f, LG14f and LG1m by CIM, accounting for 12.5–25.2% of the trait variation. The results should prove to be very useful for improving growth traits using molecular MAS.     

甘蓝分子连锁图的构建与品质性状的QTL定位

以两个不同生态型甘蓝(Brassica oleracea var．capitata)品种杂交得到的F2代为作图群体,用RAPD标记构建甘蓝分子连锁图。通过对520个随机引物进行筛选,236个引物在两亲本间表现多态性,多态性比例为47．7％。选取111个引物对群体进行分析,构建了一张含有135个标记位点,9个连锁群,覆盖长度为1023．7cM的分子连锁图。利用该图谱对甘蓝叶球紧实度和中心柱长两性状进行了QTL定位分析。检测到3个与叶球紧实度相关的QTL,总贡献率为62．5％;检测到4个与中心柱长相关的QTL,总贡献率为59．1％。     

Novel pleiotropic loci controlling panicle architecture across environments in japonica rice （Oryza sativa L.）

To identify quantitative trait loci (QTLs) controlling panicle architecture in japonica rice, a genetic map was constructed based on simple sequence repeat (SSR) markers and 254 recombinant inbred lines (RILs) derived from a cross between cultivars Xiushui 79 and C Bao. Seven panicle traits were investigated under three environments. Single marker analysis indicated that a total of 27 SSR markers were highly associated with panicle traits in all the three environments. Percentage of phenotypic variation explained by single locus varied from 2% to 35%. Based on the mixed linear model, a total of 40 additive QTLs for seven panicle traits were detected by composite interval mapping, explaining 1.2%-35% of phenotypic variation. Among the 9 QTLs with more than 10% of explained phenotypic variation, two QTLs were for the number of primary branches per panicle (NPB), two for panicle length (PL), two for spikelet density (SD), one for the number of secondary branches per panicle (NSB), one for secondary branch distribution density (SBD), and one for the number of spikelets per panicle (NS), respectively. qPLSD-9-1 and qPLSD-9-2 were novel pleiotropic loci, showing effects on PL and SD simultaneously. qPLSD-9-1 explained 34.7% of the phenotypic variation for PL and 25.4% of the phenotypic variation for SD, respec- tively. qPLSD-9-2 explained 34.9% and 24.4% of the phenotypic variation for PL and SD, respectively. The C Bao alleles at the both QTLs showed positive effects on PL, and the Xiushui 79 alleles at the both QTLs showed positive effects on SD. Genetic variation of panicle traits are mainly attributed to additive effects. QTL × environment interactions were not significant for additive QTLs and additive × additive QTL pairs.     

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1298．7cM,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：pr01和pr02,分别位于LG1和LG3,其贡献率分别为15．2％和14．1％,位点pr07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glu7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。     

Identification of molecular markers linked to quantitative trait loci for soybean resistance to corn earworm

 One hundred and thirty nine restriction fragment length polymorphisms (RFLPs) were used to construct a soybean (Glycine max L. Merr.) genetic linkage map and to identify quantitative trait loci (QTLs) associated with resistance to corn earworm (Helicoverpa zea Boddie) in a population of 103 F₂-derived lines from a cross of ‘Cobb’ (susceptible) and PI229358 (resistant). The genetic linkage map consisted of 128 markers which converged onto 30 linkage groups covering approximately 1325 cM. There were 11 unlinked markers. The F₂-derived lines and the two parents were grown in the field under a plastic mesh cage near Athens, Ga., in 1995. The plants were artificially infested with corn earworm and evaluated for the amount of defoliation. Using interval-mapping analysis for linked markers and single-factor analysis of variance (ANOVA), markers were tested for an association with resistance. One major and two minor QTLs for resistance were identified in this population. The PI229358 allele contributed insect resistance at all three QTLs. The major QTL is linked to the RFLP marker A584 on linkage group (LG) ‘M’ of the USDA/Iowa State University public soybean genetic map. It accounts for 37% of the total variation for resistance in this cross. The minor QTLs are linked to the RFLP markers R249 (LG ‘H’) and Bng047 (LG ‘D1’). These markers explain 16% and 10% of variation, respectively. The heritability (h²) for resistance was estimated as 64% in this population. Received: 15 October 1997 / Accepted: 4 November 1997     

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.