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 a...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 comparison 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.展开更多
基金supported by the National Natural Science Foundation of China(32072547 and 32102320)the Key-Area Research and Development Program of Guangdong Province(2022B0202070003)+2 种基金supported by the open competition program of top 10 critical priorities of Agricultural Science and Technology Innovation for the 14th Five-Year Plan of Guangdong Province(2022SDZG05)the Hainan Yazhou Bay Seed Lab(JBGS-B21HJ0001)the Meyers lab on small RNA classification and miRNA annotation is supported by US National Science Foundation Award(2130883)。
文摘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 comparison 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.
