Abstract
Small RNAs(sRNAs),found extensively in plants,play an essential role in plant growth and development.Although various sRNA analysis tools have been developed for plants,the use of most of them depends on programming and command-line environments,which is a challenge for many wet-lab biologists.Furthermore,current sRNA analysis tools mostly focus on the analysis of certain type of sRNAs and are resource-intensive,normally demanding an immense amount of time and effort to learn the use of numerous tools or scripts and assemble them into a workable pipeline to get the final results.Here,we present sRNAminer,a powerful stand-alone toolkit with a user-friendly interface that integrates all common functions for the analysis of three major types of plant sRNAs:microRNAs(miRNAs),phased small interfering RNAs(phasiRNAs),and heterochromatic siRNAs(hc-siRNAs).We constructed a curated or"golden"set of MIRNA and PHAS loci,which was used to assess the performance of sRNAminer in com-parison to other existing tools.The results showed that sRNAminer outperformed these tools in multiple aspects,highlighting its functionality.In addition,to enable an efficient evaluation of sRNA annotation results,we developed Integrative Genomics Viewer(IGV)-sRNA,a modified genome browser optimized from IGV and we incorporated it as a functional module in sRNAminer.IGV-sRNA can display a wealth of sRNA-specific features,enabling a more comprehensive understanding of sRNA data.sRNAminer and IGV-sRNA are both platform-independent software that can be run under all operating systems.They are now freely available at https://github.com/kli28/sRNAminer and https://gitee.com/CJchen/IG V-sRNA.
基金项目
国家自然科学基金(32072547)
国家自然科学基金(32102320)
Key-Area Research and Development Program of Guangdong Province(2022B0202070003)
open competition program of top 10 critical priorities of Agricultural Science and Technology Innovation for the 14th Five-Y(2022SDZG05)
Hainan Yazhou Bay Seed Lab(JBGS-B21HJ0001)
US National Science Foundation Award(2130883)
NETL
NSTL
万方数据