4.6 Article

sRNA Profiler: A User-Focused Interface for Small RNA Mapping and Profiling

期刊

CELLS
卷 10, 期 7, 页码 -

出版社

MDPI
DOI: 10.3390/cells10071771

关键词

viroid; RNA silencing; small RNA; vd-sRNA; deep-sequencing; sRNA profiling

资金

  1. Natural Sciences and Engineering Research Council of Canada (NSERC) [155219-17]
  2. Universite de Sherbrooke

向作者/读者索取更多资源

Viroids are circular, non-coding RNA pathogens that infect plants and trigger the host plant's RNA silencing machinery. A python-based software tool was developed to profile and map sRNAs on circular genomes, showing efficiency in analyzing deep-sequencing data and potentially serving as a key tool for researchers to evaluate sRNA production and profile them on their target RNA species.
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.

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