Mining SSR and SNP/Indel sites in expressed sequence tag libraries of Radopholus similis

Q2 Medicine

In Silico Biology Pub Date : 2010-02-15 DOI:10.1145/1722024.1722042

A. Riju, P. Lakshmi, P. Nima, N. Reena, S. Eapen

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引用次数: 0

Abstract

The objective of this study is to explore the single sequence repeats (SSRs) and single nucleotide polymorphims (SNPs) in expressed sequence tags (ESTs) of Radopholus similis. We retrieved 7380 EST sequences consisting different tissues/condition libraries from dbEST of National Centre for Biotechnology Information (NCBI). A total of 1449 SSRs were detected by MISA perl script. Hexa-nucleotide repeats (836 nos.) followed by mononucleotide repeats (207 nos.) were found to be more abundant than other types of repeats. Putative SNP/Indels were found out with the help of AutoSNP. As many as 1038 SNPs and 108 small indels (insertion/deletion) were found with a density of one SNP/191 bp and one indel/1.8 kbp. Candidate SNPs were categorized according to nucleotide substitution as either transition (C↔T or G↔A) or transversion (C↔G, A↔T, C↔A or T↔G). We observed a higher number of transversions type substitution (537) than transitions (501). However considering the individual substitutions, G↔A (281) and C↔T (220) were found to be predominant than purine to pyrimidine base substitutions. Since the SSR and SNP markers are invaluable tools for genetic analysis, the identified SSRs and SNPs of R. similis could be used in diversity analysis, genetic trait mapping, association studies and marker assisted selection.

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类人猿表达序列标签库中SSR和SNP/Indel位点的挖掘

本研究的目的是探讨相似Radopholus similis表达序列标签(est)中的单序列重复序列(SSRs)和单核苷酸多态性(snp)。我们从美国国家生物技术信息中心(NCBI)的dbEST数据库中检索了7380条EST序列，这些序列包含不同的组织/条件库。MISA perl脚本共检测到1449个SSRs。六核苷酸重复序列(836个)和单核苷酸重复序列(207个)比其他类型的重复序列更丰富。假定的SNP/Indels是在AutoSNP的帮助下发现的。共发现1038个SNP和108个小缺失(插入/缺失)，密度分别为1个SNP/191 bp和1个indel/1.8 kbp。候选snp根据核苷酸替换分为过渡(C↔T或G↔A)或转换(C↔G, A↔T, C↔A或T↔G)。我们观察到更多的翻转型取代(537)比过渡(501)。然而，考虑到单个替换，我们发现G↔A(281)和C↔T(220)比嘌呤到嘧啶基替换更占优势。由于SSR和SNP标记是遗传分析的宝贵工具，因此鉴定出的相似根SSR和SNP可用于多样性分析、遗传性状定位、关联研究和标记辅助选择。

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 Computer Science-Computational Theory and Mathematics

CiteScore

2.20

自引率

0.00%

发文量

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.