基于小 RNA 深度测序数据鉴定 microRNAs 和天然反义转录物衍生的内源性 siRNAs。

Identification of MicroRNAs and Natural Antisense Transcript-Originated Endogenous siRNAs from Small-RNA Deep Sequencing Data.

机构信息

Department of Computer Science and Engineering, Fudan University, Shanghai, China.

Department of Computer Science and Engineering, Washington University, St. Louis, MO, USA.

出版信息

Methods Mol Biol. 2021;2170:125-131. doi: 10.1007/978-1-0716-0743-5_9.

DOI:10.1007/978-1-0716-0743-5_9

PMID:32797455

Abstract

Next Generation Sequencing (NGS) is becoming a routine experimental technology. It has been a great success in recent years to profile small-RNA species using NGS. Indeed, a large quantity of small-RNA profiling data has been generated from NGS, and computational methods have been developed to process and analyze NGS data for the purpose of identification of novel and expressed small noncoding RNAs and analysis of their roles in nearly all biological processes and pathways in eukaryotes. We discuss here the computational procedures and major steps for identification of microRNAs and natural antisense transcript-originated small interfering RNAs (nat-siRNAs) from NGS small-RNA profiling data.

摘要

下一代测序（NGS）正在成为一种常规的实验技术。近年来，利用 NGS 对小 RNA 物种进行分析取得了巨大成功。事实上，已经从 NGS 生成了大量的小 RNA 分析数据，并且已经开发了计算方法来处理和分析 NGS 数据，以鉴定新的和表达的小非编码 RNA，并分析它们在真核生物中几乎所有生物过程和途径中的作用。在这里，我们讨论了从 NGS 小 RNA 分析数据中鉴定 microRNAs 和天然反义转录物起源的小干扰 RNA（nat-siRNAs）的计算程序和主要步骤。