候选古细菌非编码rna及其与温度适应的关系

IF 1.9 4区 生物学 Q2 BIOLOGY
Raúl Arias-Carrasco , Victor Aliaga-Tobar , Sebastian Abades , Vinicius Maracaja-Coutinho
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引用次数: 0

摘要

非编码rna (ncRNAs)在生命所有领域的细胞微调调控中发挥着至关重要的作用。在古细菌中,对ncRNA的研究仍然很少,只有少数ncRNA类别得到了很好的表征。古生菌以其在恶劣环境中生存的能力而闻名,尽管它们也在各种其他栖息地被发现。我们通过二级结构推断和序列相似性搜索确定了270个古菌基因组的ncRNA候选库。在这些基因组中鉴定出33种非编码RNA。所有ncRNA类别与最佳生长温度(OGT)的相关系数为R2 0.65。基于一组高度保守蛋白的多重比对的系统发育分析揭示了在门和属水平上对ncRNA类别的偏好。本研究生成的所有ncRNA数据都揭示了特定ncRNA类别的基因组丰度与最佳生长温度之间的相关性,特别是对于sRNA C/D盒型。所有产生的基因组和ncRNA古菌数据都是宝贵的资源,将刺激实验人员调查他们预测的ncRNA是否正确和具有生物学意义,促进利用该结构域独特特征的进一步关联研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The repertoire of candidate archaeal noncoding RNAs and their association with temperature adaptation
Noncoding RNAs (ncRNAs) play a crucial role in the fine-tuning regulation of cells in all domains of life. In archaea, ncRNAs remain poorly studied, with only a few ncRNA classes well characterised. Archaea are renowned for their ability to survive in harsh environments, though they have been discovered in a variety of other habitats as well. We have determined the ncRNA candidate repertoire across 270 archaeal genomes using secondary structure inferences and sequence similarity searches. Here, 33 non-coding RNA classes were identified in these genomes. The correlation between all ncRNA classes and optimal growth temperature (OGT) was R2 0.65. Phylogenetic analysis based on multiple alignments of a set of highly conserved proteins revealed preferences for ncRNA classes at the phylum and genus levels. All of the ncRNA data generated by this study reveals a correlation between the genomic abundance of specific ncRNA classes and the optimal growth temperature, especially for the sRNA C/D box type. All the genomic and ncRNA archaeal data generated is a valuable resource that will stimulate experimentalists to investigate whether or not their predicted ncRNAs are correct and biologically meaningful, boosting further associative studies using the unique features of this domain.
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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