Name: Peak Calling and Annotation in SCRAP for Small Noncoding RNA: Target RNA Interaction Studies
Uploaded: 2023-12-01T14:40:00
Description: Watch this Scientific Journal Video about Peak Calling and Annotation in SCRAP for Small Noncoding RNA: Target RNA Interaction Studies at JoVE.com

peak calling and annotation in scrap for small noncoding rna: target rna interaction studies

In Vivo RNA: RNA Interactions Using the SCRAP Bioinformatics Pipeline

Small noncoding RNAs are highly studied for their post-transcriptional roles in coordinating expression from suites of genes in diverse processes such as differentiation and development, signal processing, and disease1,2,3. The ability to accurately determine the target transcripts of gene-regulatory small noncoding RNAs (sncRNAs), including microRNAs (miRNAs), is of importance to studies of RNA biology at both basic and translational levels. Bioinformatic algorithms that exploit anticipated complementarity between the miRNA seed sequence and its potential targets have been frequently used for the prediction of miRNA:target RNA interactions. While these bioinformatic algorithms have been successful, they also can harbor both false positive and false negative results, as has been reviewed elsewhere4,5,6. Recently, several biochemical approaches have been designed and implemented that allow unambiguous and semiquantitative determination of in vivo sncRNA:target RNA interactions by in vivo crosslinking and ensuing incorporation of a ligation step to physically attach the sncRNA to its target to form a single chimeric RNA4,5,7,8,9,10. Subsequent preparation of sequencing libraries from the chimeric RNAs allows assessment of the sncRNA:target RNA interactions by computational processing of the sequencing data. This video provides a tutorial for installing and using a computational pipeline termed small chimeric RNA analysis pipeline (SCRAP), which is designed to allow robust and reproducible analysis of sncRNA:target RNA interactions from chimeric RNA sequencing libraries6.
A goal of this tutorial is to assist investigators in avoiding excessive reliance on purely predictive bioinformatic algorithms by lowering barriers to the analysis of data generated through biochemical approaches providing chimeric molecular readouts of sncRNA:target RNA interactions. This tutorial provides practical steps and tips to guide entry-level computational scientists through the use of a pipeline, SCRAP, developed for analyzing chimeric RNA sequencing data, which can be generated by several existing biochemical protocols, including crosslinking, ligation, and sequencing of hybrids (CLASH) and covalent ligation of endogenous Argonaute-bound RNAs- crosslinking and immunoprecipitation (CLEAR-CLIP)7,9.
The use of SCRAP offers several advantages for the analysis of chimeric RNA sequencing data, compared to other computational pipelines6. One salient advantage is its extensive annotation and the incorporation of call-outs to well-supported and routinely updated bioinformatic scripts within the pipeline, in comparison to alternative pipelines that often rely on custom and/or unsupported scripts for steps in the pipeline. This feature lends stability to SCRAP, making it more worthwhile for researchers to familiarize themselves with the pipeline and to incorporate its use into their workflow. SCRAP has also been demonstrated to outperform alternative pipelines in calling peaks of sncRNA:target RNA interactions and to have cross-platform functionality, as detailed in a prior publication6.
By the end of this tutorial, users will be able to (i) know platform requirements for SCRAP and install SCRAP pipelines, (ii) install reference genomes and set up command line parameters for SCRAP, and (iii) understand peak calling criteria and perform peak calling and peak annotation.
This video will describe in practical detail how researchers studying RNA biology may install and optimally use the computational pipeline, SCRAP, to analyze sncRNA interactions with target RNAs, such as messenger RNAs, in chimeric RNA-sequencing data obtained through one of the discussed biochemical approaches to sequencing library preparation.
SCRAP is a command line utility. Generally, following the guide below, the user will need to (i) download and install SCRAP (https://github.com/Meffert-Lab/SCRAP), (ii) Install reference genomes and run SCRAP, and (iii) perform peak calling and annotation.
Further details of the computational steps in this procedure can be found at&#160;https://github.com/Meffert-Lab/SCRAP. This article will provide the setup and background information to allow investigators with entry-level computational skills to install, optimize, and use SCRAP on chimeric RNA sequencing library datasets.

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data 

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries

This protocol covers the installation and practical steps for the use of a computational pipeline designed to analyze high throughput sequencing data from chimeric noncoding RNA-target RNA-interactions. The molecular strategy to form chimeric RNAs is a relatively recent development that has advantages when compared to prior biochromatic prediction tools in unambiguously understanding the genome-wide noncoding RNA-target RNA-interaction landscape. Sequencing data generated from the high throughput sequencing of the chimeric RNAs can present an analysis challenge for new adopters of this strategy.We have established an open source cross-platform computational pipeline that is highly annotated to allow entry-level users to analyze data from their chimeric noncoding RNA-target RNA sequencing experiments. In future experiments, the Mefford lab plans to use computational analysis by scrap on dataset generated from our ongoing investigations into post transcriptional regulation in the mammalian nervous system, as well as to maintain an update scrap on our GitHub.

Watch this Scientific Journal Video about Peak Calling and Annotation in SCRAP for Small Noncoding RNA: Target RNA Interaction Studies at JoVE.com

Peak Calling and Annotation in SCRAP for Small Noncoding RNA: Target RNA Interaction Studies  

After running SCRAP, use the indicated script command to perform peak calling. List the full paths to the directory containing the sample folders and the adapter file. Then, define the criteria for peak calling, including the minimum number of sequencing reads, and the number of distinct sequencing libraries needed for a peak to be recognized.Indicate whether peaks must be contributed to by sncRNAs of the same family, which is relevant for miRNAs that share seed sequences and can bind to overlapping gene targets. Then, indicate the full path to the reference directory, MIR base abbreviation, and the reference genome abbreviation. After peak calling, run the peak annotation script.Provide the full path to the resulting peaks. bed from the peak calling to the reference directory and the desired species for annotation. Use samtools merge to merge all the desired bam files to facilitate combined visualization.Then, use the samtools sort for line-by-line sorting of merged. bam file. Index the sorted.bam file using the samtools index, generating a binary samtools format index file required for genomic visualization tools. Finally, in the integrative genomics viewer, open the sorted. bam and indexed.by file. The application of a modified version of SCRAP to previously published sequencing data sets revealed a decrease in miRNA interactions with Intron regions. The reduction was observed after isolating high confidence interactions through peak calling with SCRAP.

Research

JoVE Journal

Biology

An understanding of the in vivo gene regulatory interactions of small noncoding RNAs (sncRNAs), such as microRNAs (miRNAs), with their target RNAs has ...