牙鲆遗传作图及生长性状QTL定位

采用牙鲆日本群体和韩国群体杂交的92个F₁个体作为分离群体, 利用微卫星标记和Joinmap 4.0作图软件构建了牙鲆遗传连锁图谱。共有221个SSR标记用于连锁图谱构建, 雌性图谱中, 共178个微卫星标记定位到22个连锁群上, 观测总长度为(G _oa )599.0 cM, 覆盖率(C _oa )达76.27%。雄性图谱中, 共194个微卫星标记定位到23个连锁群上, G _oa 为693.4 cM, C _oa 为78.82%。对全长、体质量、体高3组数据进行主成分分析处理, 得到可解释3个性状的89.6%特征的一组数据, 命名为牙鲆生长性状GT。用WinQTLCart 2.5软件的复合区间作图，在已构建的遗传连锁图谱上对牙鲆生长性状GT进行QTL定位, 取LOD经验值2.5为QTL存在的阈值; 对微卫星标记进行性状—标记之间的回归分析。本研究共定位3个与牙鲆生长性状GT相关的QTLs, qGT-f4 qGT-m20 qGT-f20,可解释表型变异率分别为27.60%, 13.74%, 10.27%。在性状—标记之间的回归分析中, 得到22个与生长性状GT相关(P<0.05)的微卫星标记, 单个标记可解释表型变异率介于3.70%~10.42%, 其中6个微卫星标记scaffold558_51720、scaffold558_26183、scaffold903_69232、scaffold485_47120 、scaffold1262_77386、scaffold809_65154与生长性状GT之间呈极显著相关(P><0.01), 可解释表型变异率分别为10.42%、7.31%、10.07%、10.07%、8.39%和11.26%。

Genetic mapping and QTLs analysis of growth traits in olive flound-er(Paralichthys olivaceus)

Using a population including 92 F₁ individuals obtained from the cross olive flounder from Japan ×olive flounder from Korea as the segregating population, genetic linkage maps of flounder were constructed using the SSR marker by joinmap4.0 software .A total of 221 SSR markers were fixed to the genetic linkage map. 178 SSR markers were linked to 22 linkage groups in female map and 194 SSR markers are linked to23 linkage groups in male map. The lengths of the female and male maps are 599.0 cM and 693.4 cM and covered 76.27% and 78.82% of the genome, respectively. Principal component analysis was handled with three sets of data, overall length, weight and body depth.1 set of data that can explain 89.6% of the three traits was obtained, which was named growth-trait, GT of flounder. Based on the linkage maps, trait- marker regression and complexity interval mapping were analyzed to fix QTLs related to growth traits by WinQTLCart 2.5 software, the experiential LOD-value of 2.5 was the threshold value of existing QTLs. Three QTLs related to growth traits were obtained from this research , qGT-f4,qGT-m20 and qGT-f20, and the variance explained by the three loci were 27.60%, 13.74%, 10.27%, respectively. Twenty-two SSR markers related to growth traits (P<0.05) were obtained from trait- marker regression analyzing. The variance explained by single SSR, ranged from 3.70% to 11.26%. The six markers, scaffold558_51720, scaffold558_26183, scaffold903_69232, scaffold485_47120, scaffold1262_77386 and scaffold809_65154 were highly significantly ( P< 0.01) correlated with growth traits, and the variance explained by the six were 10.42%,7.31%,10.07%,10.07%,8.39%,11.26% respectively.