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齿肋赤藓早期光诱导蛋白ELIPs的生物信息学分析

周雅 高贝 张道远

生物信息学Issue(4):233-241,9.
生物信息学Issue(4):233-241,9.DOI:10.3969/j.issn.1672-5565.2014.04.01

齿肋赤藓早期光诱导蛋白ELIPs的生物信息学分析

Bioinformatics analysis of early light-induced protein(ELIPs) in Syntrichia caninervis

周雅 1高贝 2张道远1

作者信息

  • 1. 中国科学院新疆生态与地理研究所,中国科学院干旱区生物地理与生物资源重点实验室,新疆 乌鲁木齐830011
  • 2. 中国科学院大学,北京100049
  • 折叠

摘要

Abstract

Thirty nine ScELIPs unigenes were obtained based on the transcriptome data of Syntrichia caninervis, an extremely desiccation tolerance moss. ScELIP1 and ScELIP2 have complete ORF. Several bioinformatics methods were utilized to analyze and verify the characteristics of ScELIPs such as homologous relationships, physicochemical properties, conserved domain, signal peptide, hydrophobicity, subcellular localization, secondary structure, transmembrane structure, functional domain, three dimensional structure, active sites and so on. The results showed that ORF of ScELIP1 and ScELIP2 are 711 bp and 624 bp and encode 236 and 207 amino acids, respectively. Both of them contain a complete Chloroa_b-bind-functional domain. Subcellular location prediction revealed that the two ScELIPs are both located at the thylakoid membrane of chloroplast. Secondary structure prediction demonstrated that they both have three transmembrane helixes, among which the first and the third one form a double symmetric structure through the Glu and Arg residues. The ScELIPs has at least four active chlorophyll a binding sites. Finally, protein sequence alignment and phylogenetic analysis revealed that ScELIP1 has the closest relationship with moss physcomitrella patens and Tortula ruralis, while ScELIP2 is closer to higher vascular plants, showing the evolutionary trend clue from moss to vascular plants. This study laid a solid foundation for the subsequently cloning and functional research of ELIPs.

关键词

早期光诱导蛋白/生物信息学/齿肋赤藓

Key words

Early light-induced protein/Bioinformatics/Syntrichia caninervis

分类

生物科学

引用本文复制引用

周雅,高贝,张道远..齿肋赤藓早期光诱导蛋白ELIPs的生物信息学分析[J].生物信息学,2014,(4):233-241,9.

基金项目

国家重点基础研究发展计划(973计划)(No.2014CB954203)资助。 (973计划)

生物信息学

1672-5565

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