SCRAP: a bioinformatic pipeline for the analysis of small chimeric RNA-seq data.
SCRAP: a bioinformatic pipeline for the analysis of small chimeric RNA-seq data.
复制标题
DOI：
10.1261/rna.079240.122
复制
发表时间：
2022-10-31
期刊：
影响因子：
--
通讯作者：
中科院分区：
文献类型：
--
作者：
microRNA（miRNAs）是一类小的非编码RNA（sncRNA），通过与mRNA靶点的不完全碱基配对参与转录后基因调控，导致转录抑制和结合转录物的不稳定。历史上用于预测miRNA靶标的基于序列的算法在可靠地反映体内相互作用方面面临固有的挑战。最近的策略已经通过在RNA诱导的沉默复合物（RISC）内将sncRNA交联和连接到其靶标，然后对嵌合sncRNA：靶标RNA进行高通量测序来直接分析miRNA-靶标相互作用。尽管这些直接分析方法的优势，但用于有效分析所得嵌合sncRNA：靶RNA测序数据的标准化管道并不容易获得。在这里，我们提出了SCRAP，一个强大的小型嵌合RNA分析管道，用于嵌合sncRNA的生物信息学处理：靶RNA测序数据。SCRAP由两个部分组成，每个部分都针对嵌合小RNA测序读段的独特特征进行了专门优化：第一，读段处理和比对，第二，峰调用和注释。我们将SCRAP应用于基准嵌合sncRNA：通过不同的分子方法产生的靶RNA测序数据集，并将SCRAP与现有的嵌合RNA分析管道进行比较。SCRAP具有最低的硬件要求，是跨平台的，并包含广泛的注释，以拓宽处理小嵌合RNA测序数据的可访问性，并使人们能够深入了解小非编码RNA在调节不同生物系统中的靶点。
MicroRNAs (miRNAs) are small noncoding RNAs (sncRNAs) that function in post-transcriptional gene regulation through imperfect base pairing with mRNA targets, which results in inhibition of translation and typically destabilization of bound transcripts. Sequence-based algorithms historically used to predict miRNA targets face inherent challenges in reliably reflecting in vivo interactions. Recent strategies have directly profiled miRNA–target interactions by crosslinking and ligation of sncRNAs to their targets within the RNA-induced silencing complex (RISC), followed by high-throughput sequencing of the chimeric sncRNA:target RNAs. Despite the strength of these direct profiling approaches, standardized pipelines for effectively analyzing the resulting chimeric sncRNA:target RNA sequencing data are not readily available. Here we present SCRAP, a robust small chimeric RNA analysis pipeline for the bioinformatic processing of chimeric sncRNA:target RNA sequencing data. SCRAP consists of two parts, each of which is specifically optimized for the distinctive characteristics of chimeric small RNA sequencing reads: first, read processing and alignment and second, peak calling and annotation. We apply SCRAP to benchmark chimeric sncRNA:target RNA sequencing data sets generated by distinct molecular approaches, and compare SCRAP to existing chimeric RNA analysis pipelines. SCRAP has minimal hardware requirements, is cross-platform, and contains extensive annotations to broaden accessibility for processing small chimeric RNA sequencing data and enable insights into the targets of small noncoding RNAs in regulating diverse biological systems.
登录
查看更多内容
影响因子：
14.9
作者：
Gene Ontology Consortium
通讯作者：
Gene Ontology Consortium
影响因子：
8.8
作者：
Duan, Ye;Veksler-Lublinsky, Isana;Ambros, Victor
通讯作者：
Ambros, Victor
影响因子：
64.5
作者：
Hafner M;Landthaler M;Burger L;Khorshid M;Hausser J;Berninger P;Rothballer A;Ascano M Jr;Jungkamp AC;Munschauer M;Ulrich A;Wardle GS;Dewell S;Zavolan M;Tuschl T
通讯作者：
Tuschl T
影响因子：
48
作者：
Baruzzo G;Hayer KE;Kim EJ;Di Camillo B;FitzGerald GA;Grant GR
通讯作者：
Grant GR
影响因子：
10.5
作者：
Han, JJ;Lee, Y;Kim, VN
通讯作者：
Kim, VN