摘要
为了从分子水平研究大菱鲆生长激素作用机制及进化机制。以大菱鲆(Scophthalmus maximus)为材料从脑垂体中提取mRNA,利用SMART-RACE技术建立大菱鲆脑垂体cDNA文库,并从该文库中克隆出大菱鲆生长激素(growthHormone,GH)cDNA全长序列。测序结果表明,克隆的大菱鲆GH cDNA序列全长为876 bp,包括108 bp的5’UTR和174 bp的3’UTR序列。该基因的开放阅读框全长591 bp,编码由197氨基酸残基组成的生长激素成熟肽序列,用生物软件DNASTAR计算大菱鲆生长激素蛋白分子量为1 909.22,等电点为6.24。将大菱鲆与漠斑牙鲆、褐牙鲆等共7种鲆鲽鱼类GH成熟肽氨基酸序列进行比较分析,结果显示大菱鲆与其他6种鲆鲽鱼类序列同源性均为70%左右,而鲆科鱼类与鲽科鱼类间生长激素基因同源性很高(≥80%),说明大菱鲆与鲆科、鲽科鱼类的同源性较低。另外,运用PAUP软件对7种鲆蝶科鱼类与另外8种不同种属鱼类进行了分子系统进化树分析,结果与根据传统的形态学和生化特征分类进化地位基本一致,大菱鲆单独形成1个分支且与鲆科和鲽科鱼类相距较远,此结果为在形态学分类基础上进一步定义菱鲆属鱼类分类提供了理论依据。
The growth hormone(GH) gene has been cloned from a number of fishes and was used to clarify phylogenetie relationships. In order to better understand the physiological functions and evolution mechanism of the growth hormone of Turbot(Scophthalmus maximus), We cloned the full-length cDNA of the growth hormone(SmGH) gene. by Switching Mechanism At 5' end of the RNA Transcript(SMART) RACE technology. The SmGH full-length cDNA of Turbot is 876 nucleotides long, codes for a polypeptide of 197 amino acids, including a signal peptide of 17 amino acids. The 5' and 3' UTR of the messenger RNA are 108 and 174 nucleotides long, respectively. Homologous analysis of SmGH cDNA only showed about 70 % identity with the organisms of Pleuronectiformes, on the other hand, Paralichthys lethostigma showed 97.6 % of similarity with Paralichthys orbignyanu and 94.8 % with Paralichthys olivceus. The deduced amino acid sequences of SmGH of 7 species of Pleuronectiformes and 8 outgroup species were used for the phylogenetic analysis, which was performed by PAUP software with the maximum parsimony method. The result was consistent with morphology of Pleuroneetiformes on the whole. In the topology founded, the Turbot formed an independent branch and showed far relationship with species of Bothidae and Pleuronectidae, it seems reasonable to speculate that Scophthalmus should be separated from Bothidae and become a new family of Pleuronectiformes.
出处
《中国海洋大学学报(自然科学版)》
CAS
CSCD
北大核心
2008年第5期726-732,共7页
Periodical of Ocean University of China
基金
教育部科学技术研究重点项目(108083)资助