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基于网络的数据集成用于在侵染谷物的真菌禾谷镰刀菌中选择候选致病相关蛋白。

Network-based data integration for selecting candidate virulence associated proteins in the cereal infecting fungus Fusarium graminearum.

机构信息

Department of Computational and Systems Biology, Rothamsted Research, Harpenden, United Kingdom.

出版信息

PLoS One. 2013 Jul 4;8(7):e67926. doi: 10.1371/journal.pone.0067926. Print 2013.

Abstract

The identification of virulence genes in plant pathogenic fungi is important for understanding the infection process, host range and for developing control strategies. The analysis of already verified virulence genes in phytopathogenic fungi in the context of integrated functional networks can give clues about the underlying mechanisms and pathways directly or indirectly linked to fungal pathogenicity and can suggest new candidates for further experimental investigation, using a 'guilt by association' approach. Here we study 133 genes in the globally important Ascomycete fungus Fusarium graminearum that have been experimentally tested for their involvement in virulence. An integrated network that combines information from gene co-expression, predicted protein-protein interactions and sequence similarity was employed and, using 100 genes known to be required for virulence, we found a total of 215 new proteins potentially associated with virulence of which 29 are annotated as hypothetical proteins. The majority of these potential virulence genes are located in chromosomal regions known to have a low recombination frequency. We have also explored the taxonomic diversity of these candidates and found 25 sequences, which are likely to be fungal specific. We discuss the biological relevance of a few of the potentially novel virulence associated genes in detail. The analysis of already verified virulence genes in phytopathogenic fungi in the context of integrated functional networks can give clues about the underlying mechanisms and pathways directly or indirectly linked to fungal pathogenicity and can suggest new candidates for further experimental investigation, using a 'guilt by association' approach.

摘要

鉴定植物病原真菌中的毒力基因对于了解感染过程、宿主范围以及制定控制策略非常重要。在综合功能网络的背景下分析已验证的植物病原真菌中的毒力基因,可以提供与真菌致病性直接或间接相关的潜在机制和途径的线索,并通过“关联定罪”的方法为进一步的实验研究提出新的候选基因。在这里,我们研究了在全球范围内重要的子囊菌禾谷镰刀菌中 133 个已被实验证实与毒力有关的基因。我们使用了一个整合了基因共表达、预测蛋白-蛋白相互作用和序列相似性信息的综合网络,并利用 100 个已知与毒力有关的基因,总共发现了 215 个与毒力有关的新蛋白,其中 29 个被注释为假设蛋白。这些潜在的毒力基因大多数位于染色体区域,这些区域的重组频率较低。我们还探讨了这些候选基因的分类多样性,发现了 25 个可能是真菌特有的序列。我们详细讨论了几个潜在的与毒力相关的新基因的生物学相关性。在综合功能网络的背景下分析已验证的植物病原真菌中的毒力基因,可以提供与真菌致病性直接或间接相关的潜在机制和途径的线索,并通过“关联定罪”的方法为进一步的实验研究提出新的候选基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d165/3701590/998e97540196/pone.0067926.g001.jpg

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