Project description:In this study, we performed deep sequencing and bioinformatics analyses of short RNAs from Plasmodium falciparum parasites to identify and characterize novel type of small RNAs. A total of 14,828,877 raw reads were produced from small RNA libraries. We detected a new type of small RNA from tranfer RNA known as tRFs.
Project description:A cDNA library was constructed by Novogene (CA, USA) using a Small RNA Sample Pre Kit, and Illumina sequencing was conducted according to company workflow, using 20 million reads. Raw data were filtered for quality as determined by reads with a quality score > 5, reads containing N < 10%, no 5' primer contaminants, and reads with a 3' primer and insert tag. The 3' primer sequence was trimmed and reads with a poly A/T/G/C were removed
Project description:Purpose: The goal of this study is to compare endothelial small RNA transcriptome to identify the target of OASL under basal or stimulated conditions by utilizing miRNA-seq. Methods: Endothelial miRNA profilies of siCTL or siOASL transfected HUVECs were generated by illumina sequencing method, in duplicate. After sequencing, the raw sequence reads are filtered based on quality. The adapter sequences are also trimmed off the raw sequence reads. rRNA removed reads are sequentially aligned to reference genome (GRCh38) and miRNA prediction is performed by miRDeep2. Results: We identified known miRNA in species (miRDeep2) in the HUVECs transfected with siCTL or siOASL. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of endothelial miRNA profiles affected by OASL knockdown with biologic replicates.
Project description:An increasing amount of evidence indicates that fragments derived from longer small RNAs such as snoRNAs, snRNAs, and rRNAs may hold functions relevant to biology and disease. However, they remain poorly understood. Few pipelines exist to analyze the fragmentation of small RNAs, and even fewer take users from raw reads to processed results. Every decision that a user makes when processing small RNA-seq data can greatly impact downstream results. Thus, we sought to develop sRNAfrag, a standardized workflow that can accurately quantify and describe the presence of sRNA fragments, with three inputs: run data, a reference genome, and an annotation file.