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

वीवो आरएनए में: आरएनए इंटरैक्शन स्क्रैप जैव सूचना विज्ञान पाइपलाइन का उपयोग कर

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.

लेखक स्पॉटलाइट: उच्च-थ्रूपुट अनुक्रमण डेटा में काइमेरिक नॉनकोडिंग आरएनए-लक्ष्य आरएनए इंटरैक्शन का विश्लेषण करने के लिए एक कम्प्यूटेशनल पाइपलाइन 

Chimeric छोटे noncoding शाही सेना के लिए कम्प्यूटेशनल विश्लेषण ट्यूटोरियल: लक्ष्य शाही सेना अनुक्रमण पुस्तकालयों

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  

छोटे नॉनकोडिंग आरएनए के लिए स्क्रैप में पीक कॉलिंग और एनोटेशन: लक्ष्य आरएनए इंटरैक्शन स्टडीज

स्क्रैप चलाने के बाद, पीक कॉलिंग करने के लिए संकेतित स्क्रिप्ट कमांड का उपयोग करें। नमूना फ़ोल्डर और एडेप्टर फ़ाइल वाली निर्देशिका के पूर्ण पथ सूचीबद्ध करें। फिर, पीक कॉलिंग के मानदंडों को परिभाषित करें, जिसमें अनुक्रमण पढ़ने की न्यूनतम संख्या, और एक चोटी को पहचानने के लिए आवश्यक अलग-अलग अनुक्रमण पुस्तकालयों की संख्या शामिल है।इंगित करें कि चोटियों को एक ही परिवार के sncRNAs द्वारा योगदान दिया जाना चाहिए, जो miRNAs के लिए प्रासंगिक है जो बीज अनुक्रमों को साझा करते हैं और जीन लक्ष्यों को ओवरलैप करने के लिए बाध्य कर सकते हैं। फिर, संदर्भ निर्देशिका, एमआईआर आधार संक्षिप्त नाम और संदर्भ जीनोम संक्षिप्त नाम के लिए पूर्ण पथ इंगित करें। पीक कॉलिंग के बाद, पीक एनोटेशन स्क्रिप्ट चलाएं।परिणामी चोटियों के लिए पूर्ण पथ प्रदान करें। शिखर से संदर्भ निर्देशिका और एनोटेशन के लिए वांछित प्रजातियों को बुलाते हुए। संयुक्त विज़ुअलाइज़ेशन की सुविधा के लिए सभी वांछित bam फ़ाइलों को मर्ज करने के लिए samtools मर्ज का उपयोग करें।फिर, मर्ज किए गए लाइन-बाय-लाइन सॉर्टिंग के लिए सैमटूल सॉर्ट का उपयोग करें। BAM फ़ाइल। क्रमबद्ध अनुक्रमित करें।SamTools इंडेक्स का उपयोग करके BAM फ़ाइल, जीनोमिक विज़ुअलाइज़ेशन टूल के लिए आवश्यक बाइनरी SamTools फॉर्मेट इंडेक्स फ़ाइल उत्पन्न करती है। अंत में, एकीकृत जीनोमिक्स दर्शक में, सॉर्ट किया गया खोलें। BAM और अनुक्रमित।फ़ाइल द्वारा। पहले प्रकाशित अनुक्रमण डेटा सेट करने के लिए स्क्रैप के एक संशोधित संस्करण के आवेदन इंट्रोन क्षेत्रों के साथ miRNA बातचीत में कमी का पता चला. स्क्रैप के साथ पीक कॉलिंग के माध्यम से उच्च आत्मविश्वास इंटरैक्शन को अलग करने के बाद कमी देखी गई।

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

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

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