Empirical Evaluation of in silico Microsatellites Mining Tools Designed Using Nextgen Technology in Crops

Umang, P. Bharti, Akhtar Husain
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引用次数: 1

Abstract

Microsatellites are found in genome sequences of all prokaryotes and eukaryotes. They are the primary source of studying genetic variations, molecular breeding, gene discovery, disease identification, and hypervariability in a plant's genome. Many web-based and standalone computing tools have been developed to analyze sequence data using next-generation sequencing tools with several new features and objectives. Researchers always need a variety of in silico microsatellite exploring tools to analyze research data apart from extracting them. This evaluation aims to chronologically provide up-todate information on tools and databases designed explicitly to study genome-wide specifications of simple sequence repeats in crop cultivars. The study was conducted to empirically assess these tools and databases to find the next-generation technology used in designing the standalone tool, web interface & relational database. Also, to compare their processing adequateness in terms of features, such as the primer-related information, flanking sequences, statistics information of repeats, coding /non-coding, and other genomic features of the identified motif. This study may help researchers in agriculture to determine the most popular next-generation sequencing tool and technologies used to analyze microsatellite-related features and fill the gap for future applications.
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利用下一代技术设计的农作物微卫星采掘工具的经验评价
微卫星存在于所有原核生物和真核生物的基因组序列中。它们是研究遗传变异、分子育种、基因发现、疾病鉴定和植物基因组高变异性的主要来源。许多基于网络和独立的计算工具已经开发出来,使用具有几个新功能和目标的下一代测序工具来分析序列数据。研究人员除了提取研究数据外,还需要各种硅微卫星探测工具来分析研究数据。该评价旨在按时间顺序提供用于研究作物品种中简单序列重复序列全基因组规格的工具和数据库的最新信息。本研究对这些工具和数据库进行了实证评估,以发现在设计独立工具、web界面和关系数据库时使用的下一代技术。同时,从引物相关信息、侧翼序列、重复序列统计信息、编码/非编码以及识别基序的其他基因组特征等方面比较它们的处理是否适当。这项研究可能有助于农业研究人员确定最流行的下一代测序工具和技术,用于分析微卫星相关特征,并填补未来应用的空白。
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