关键词: 大豆, 大豆胞囊线虫, 抗病基因, 表达分析

Abstract:

【Objective】This experiment was designated to mining the Heterodera glycines Ichinohe (SCN) resistcance genes, and to analyze their expression in different cultivars and different organs of the same cultivar, so as to explore the explore of these genes in the resistance reaction. 【Method】 Software BioMercator2.1 was used to integrate SCN resistance QTLs of different derived studies onto GmComposite2003, and the consensus QTLs were obtained by Meta-Analysis. Software hmmsearch was used to mine the candidate SCN resistance genes. RT-PCR and semi-quantitative RT-PCR were conducted to clone the candidate full-length SCN resistance genes, and to investigate the expression levels of these genes. 【Result】 A total of 27consensus QTLs were obtained through Meta-Analysis, which were used for resistance gene detection by the hmmsearch. A total of 77 coding sequences (SCN R-gene), located in these 27 consensus QTLs, were identified, which could be classified into 6 classes. Among these 6 classes, the PK-LRR-TM and the PK were two main types, which accounted for about 77% of all. Four genes in the resistance genes cluster of Gm16 were successfully cloned by RT-PCR method. The semi-quantitative RT-PCR showed that Glyma16g31490.1 was specifically expressed in the SCN resistance cultivar L-10 but not in Heinong 37 (cultivar susceptible to SCN), and the expression level was higher in root than that in leaf for L-10.【Conclusion】The result of sequence analysis revealed that the cloned four genes on Gm16 has a higher homology with the other PK-LRR-TM type resistance genes. Subsequent semi-quantitative RT-PCR showed that Glyma16g31490.1 was specifically expressed among different cultivars or different organs of the same cultivar, which indicated that this gene may play a role in the SCN resistance, and also proved that this method, based on Meta-Analysis and domains annotations, is an effective tool for mining SCN resistance genes.

Key words: soybean (Glycine max L.), Heterodera glycines, resistance gene, expression analysis