Gene identification in Phytophthora capsici through expressed sequence tags

Q2 Medicine
N. Reena, A. Chandrasekar, A. Riju, P. Nima, S. Eapen, M. Anandaraj
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引用次数: 1

Abstract

Expressed Sequence Tags (ESTs) are a rich source of information for gene discovery. In this paper, we describe the annotation of ESTs of Phytophthora capsici whose complete genome is not yet available. P. capsici is an Oomycete plant pathogen capable of infecting wide range of plants including cucumber, squash, melons, pumpkin, pepper, tomato and eggplant. In India it causes severe economic losses in black pepper, chillies and cocoa. Towards the understanding of gene function in P. capsici, we undertook the functional annotation of ESTs available at NCBI. A total of 56,457 ESTs were downloaded from NCBI and assembled into 5966 contigs. Functional categorization of these ESTs was performed using database similarity search. By functional analysis, we estimated that 84.73% of transcripts encode significant proteins. The most prominent sequences corresponds to members of metabolic pathways, avirulence-associated protein, beta-tubulin, calcium/calmodulin dependent protein kinase 3, catalase, endo-1, 4-betaglucanase, cyst germination specific acidic repeat protein precursor, elicitin-like protein, glucanase inhibitor protein, heat shock protein, Kazal-like serine protease inhibitor, mitogen-activated protein kinase, ribosomal protein, serine/threonine kinase, syntaxin and ubiquitin. This EST-gene discovery information can be used to design sequence specific markers for P. capsici identification.
辣椒疫霉基因序列标记的基因鉴定
表达序列标签(est)是基因发现的丰富信息来源。本文描述了辣椒疫霉(Phytophthora capsici)全基因组的ESTs注释。辣椒疫病是一种卵菌属植物病原体,可侵染黄瓜、南瓜、瓜类、南瓜、辣椒、番茄和茄子等多种植物。在印度,它给黑胡椒、辣椒和可可造成了严重的经济损失。为了进一步了解辣椒辣椒的基因功能,我们对NCBI提供的est进行了功能注释。从NCBI中下载了56,457个ESTs,并将其组装成5966个contigs。利用数据库相似度搜索对ESTs进行功能分类。通过功能分析,我们估计84.73%的转录本编码重要蛋白。最突出的序列对应于代谢途径成员、毒力相关蛋白、β -微管蛋白、钙/钙调蛋白依赖性蛋白激酶3、过氧化氢酶、内切- 1,4 - β葡聚糖酶、囊肿萌发特异性酸性重复蛋白前体、卵磷脂样蛋白、葡聚糖酶抑制剂蛋白、热休克蛋白、卡扎尔样丝氨酸蛋白酶抑制剂、丝裂原活化蛋白激酶、核糖体蛋白、丝氨酸/苏氨酸激酶、合胞素和泛素。该est基因发现信息可用于辣椒辣椒的序列特异性标记设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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