Resistify: A Novel NLR Classifier That Reveals Helitron-Associated NLR Expansion in Solanaceae.

IF 2.3 Q3 BIOCHEMICAL RESEARCH METHODS
Bioinformatics and Biology Insights Pub Date : 2025-01-22 eCollection Date: 2025-01-01 DOI:10.1177/11779322241308944
Moray Smith, John T Jones, Ingo Hein
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引用次数: 0

Abstract

Nucleotide-binding domain leucine-rich repeat (NLR) proteins are a key component of the plant innate immune system. In plant genomes, NLRs exhibit considerable presence/absence variation and sequence diversity. Recent advances in sequencing technologies have made the generation of high-quality novel plant genome assemblies considerably more straightforward. Accurately identifying NLRs from these genomes is a prerequisite for improving our understanding of NLRs and identifying novel sources of disease resistance. While several tools have been developed to predict NLRs, they are hampered by low accuracy, speed, and availability. Here, the NLR annotation tool Resistify is presented. Resistify is an easy-to-use, rapid, and accurate tool to identify and classify NLRs from protein sequences. Applying Resistify to the RefPlantNLR database demonstrates that it can correctly identify NLRs from a diverse range of species. Applying Resistify in combination with tools to identify transposable elements to a panel of Solanaceae genomes reveals a previously undescribed association between NLRs and Helitron transposable elements.

抵抗:一种新的NLR分类器,揭示了茄科与helitron相关的NLR扩展。
核苷酸结合域富亮氨酸重复序列(NLR)蛋白是植物先天免疫系统的重要组成部分。在植物基因组中,NLRs表现出相当大的存在/缺失变异和序列多样性。测序技术的最新进展使得高质量的新植物基因组组装的产生更加直接。准确地从这些基因组中识别nlr是提高我们对nlr的理解和识别新的抗病来源的先决条件。虽然已经开发了几种工具来预测nlr,但它们的准确性、速度和可用性都很低。本文介绍了NLR标注工具resisttify。抗性是一种易于使用,快速,准确的工具,从蛋白质序列中识别和分类nlr。对RefPlantNLR数据库的应用表明,它可以正确地从不同的物种中识别nlr。将抗性与工具相结合,对茄科基因组进行转座元件鉴定,揭示了nlr和Helitron转座元件之间先前未描述的关联。
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来源期刊
Bioinformatics and Biology Insights
Bioinformatics and Biology Insights BIOCHEMICAL RESEARCH METHODS-
CiteScore
6.80
自引率
1.70%
发文量
36
审稿时长
8 weeks
期刊介绍: Bioinformatics and Biology Insights is an open access, peer-reviewed journal that considers articles on bioinformatics methods and their applications which must pertain to biological insights. All papers should be easily amenable to biologists and as such help bridge the gap between theories and applications.
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