RNA Group/Groupe ARN, Département de Biochimie, Faculté de Médecine des Sciences de la Santé, Pavillon de Recherche Appliquée au Cancer, Université de Sherbrooke, 3201 Rue Jean-Mignault, Sherbrooke, QC J1E 4K8, Canada.
Département de Physique, Université de Sherbrooke, 2500 Boul. Université, Sherbrooke, QC J1K 2R1, Canada.
Cells. 2021 Jul 13;10(7):1771. doi: 10.3390/cells10071771.
Viroids are circular, highly structured, single-stranded, non-coding RNA pathogens known to infect and cause disease in several plant species. They are known to trigger the host plant's RNA silencing machinery. The detection of viroid-derived small RNAs (vd-sRNA) in viroid-infected host plants opened a new avenue of study in host-viroid pathogenicity. Since then, several viroid research groups have studied the vd-sRNA retrieved from different host-viroid combinations. Such studies require the segregation of 21- to 24-nucleotide long small RNAs (sRNA) from a deep-sequencing databank, followed by separating the vd-sRNA from any sRNA within this group that showed sequence similarity with either the genomic or the antigenomic strands of the viroid. Such mapped vd-sRNAs are then profiled on both the viroid's genomic and antigenomic strands for visualization. Although several commercial interfaces are currently available for this purpose, they are all programmed for linear RNA molecules. Hence, viroid researchers must develop a computer program that accommodates the sRNAs derived from the circular viroid genome. This is a laborious process, and consequently, it often creates a bottleneck for biologists. In order to overcome this constraint, and to help the research community in general, in this study, a python-based pattern matching interface was developed so as to be able to both profile and map sRNAs on a circular genome. A "matching tolerance" feature has been included in the program, thus permitting the mapping of the sRNAs derived from the quasi-species. Additionally, the "topology" feature allows the researcher to profile sRNA derived from both linear and circular RNA molecules. The efficiency of the program was tested using previously reported deep-sequencing data obtained from two independent studies. Clearly, this novel software should be a key tool with which to both evaluate the production of sRNA and to profile them on their target RNA species, irrespective of the topology of the target RNA molecule.
类病毒是一类环状、高度结构、单链、无编码 RNA 病原体，已知能感染并引起几种植物物种的疾病。它们被认为能触发宿主植物的 RNA 沉默机制。在感染类病毒的宿主植物中检测到类病毒衍生的小 RNA (vd-sRNA)，为宿主-类病毒致病性的研究开辟了新途径。自那时以来，几个类病毒研究小组研究了从不同的宿主-类病毒组合中回收的 vd-sRNA。此类研究需要从深度测序数据库中分离出 21 至 24 个核苷酸长的小 RNA (sRNA)，然后将 vd-sRNA 与该组内任何与类病毒基因组或抗原基因组链具有序列相似性的 sRNA 分离。然后在类病毒的基因组和抗原基因组链上对这些映射的 vd-sRNA 进行分析以进行可视化。尽管目前有几个商业界面可用于此目的，但它们都是为线性 RNA 分子设计的。因此，类病毒研究人员必须开发一种适应源自环状类病毒基因组的 sRNA 的计算机程序。这是一个繁琐的过程，因此，它经常成为生物学家的瓶颈。为了克服这一限制，并帮助整个研究社区，在本研究中，开发了一个基于 Python 的模式匹配接口，以便能够在环状基因组上对 sRNA 进行分析和映射。该程序包含一个“匹配容限”功能，从而允许对源自准种的 sRNA 进行映射。此外，“拓扑”功能允许研究人员对源自线性和环状 RNA 分子的 sRNA 进行分析。该程序的效率通过使用来自两个独立研究的先前报道的深度测序数据进行了测试。显然，这种新软件应该是一种关键工具，用于评估 sRNA 的产生，并对其目标 RNA 物种进行分析，而不管目标 RNA 分子的拓扑结构如何。
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