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全基因组预测樟疫霉的候选效应分子(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2015年02期
Page:
69-74
Column:
研究论文
publishdate:
2015-04-01

Article Info:/Info

Title:
Prediction for candidate effector proteins from Phytophthora cinnamomi genome
Article ID:
1000-2006(2015)02-0069-06
Author(s):
HAN Changzhi
The Key Laboratory of Forest Disaster Warning and Control of Yunnan Province, College of Forestry, Southwest Forestry University, Kunming 650224,China
Keywords:
Phytophthora cinnamomi candidate effector genome secreted protein
Classification number :
S763
DOI:
10.3969/j.issn.1000-2006.2015.02.012
Document Code:
A
Abstract:
Phytophthora cinnamomi can devastate the important food crops and lauraceae plants, and cause serious harm in many countries. To study the pathogenesis and prevention methods of Ph. cinnamomi, based on the typical character of the pathogen effector, candidate effector proteins were predicted from 328 457 proteins in Ph. cinnamomi using the prediction programs including SignalP, ProtComp, TMHMM, big-PI Fungal Predictor and TargetP. The results showed that 3 439 secreted proteins were found with the 50-300 aa in length of amino acids, and the number of cysteine-rich and the length of the signal peptide were analyzed. The results showed that there were many redundant proteins in 3 439 secreted proteins, the proportion was up to 50%, and containing 1 to 10 cysteine, and the signal peptide length was 17 to 26. Further, based on the conserved motif RXLR in the effector of oomycetes, 160 candidate effector proteins were identified from 1 549 secreted proteins with a unique amino acid sequence. Above bioinformatics analysis method could effectively achieve the candidate effector proteins in Ph. cinnamomi, which provided an important theoretical basis to further clarify the function of effectors.

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Last Update: 2015-03-31