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Published on: January 21, 2020
FungiSNC: An integrated database for fungi small non-coding RNAs based on high-throughput sequencing
Xiaoqiang Lang1, Jinjing Luo2, Fazhi Li1
1Microbiology and intelligent biomanufacturing Key Laboratory of Sichuan Province, College of Life Science, Sichuan University, Chengdu, Sichuan 610041, China.
Introduction:
Small non-coding RNAs (sncRNAs) have been proven to play crucial roles in various biological processes such as development, stress responses, virulence, and pathogenicity. However, to the best of our knowledge, none of the currently available databases can store, manage, and analyze the vast amounts of sncRNA sequencing data. A comprehensive web-based platform for the integration and analysis of sncRNAs in fungi and their potential functions is still lacking.
Objectives:
To provide an integrated database for fungi sncRNAs. It represents the first comprehensive platform encompassing diverse categories of sncRNAs.
Methods:
We implemented a standardized analytical workflow encompassing (i) data preprocessing of both public repositories and in-house sRNA-seq datasets, (ii) systematic sncRNA detection and classification, and (iii) functional annotation analysis, with all results integrated into a relational database featuring embedded analytical tools for user-friendly exploration.
Results:
We herein present FungiSNC (https://rnainformatics.org.cn/FungiSNC), an integrated database for fungal sncRNAs. It represents the first comprehensive platform encompassing diverse categories of sncRNAs, including siRNAs (small-interfering RNAs), predicted milRNAs (microRNA-like RNAs) and phasiRNAs (phased, secondary, small-interfering RNAs), rRNAs (ribosomal RNAs), tRNAs (transfer RNAs), snRNAs (small nuclear RNAs), snoRNAs (small nucleolar RNAs), piRNAs (piwi-interacting RNAs) and tRFs (tRNA-derived small RNA fragments), aggregating 989 next generation sequencing (NGS) samples from 29 fungal species.
Conclusions:
FungiSNC (Fungal Small Non-Coding RNA Database), is the first comprehensive platform dedicated to the curation, annotation, and functional analysis of fungal sncRNA sequencing data. By bridging fragmented data resources with advanced computational tools, FungiSNC aims to facilitate mechanistic exploration of sncRNA-mediated regulatory networks in fungal biology, with important implications for antifungal therapy and agricultural biocontrol.
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