Chapter 11
Identification and Quantification of Small RNAs
Di Sun, Zeyang Ma, Jiaying Zhu, and Xiuren Zhang
Abstract
RNA silencing plays a critical role in diverse biological processes in plants including growth, development,
and responses to abiotic and biotic stresses. RNA silencing is guided by small non-coding RNAs (sRNAs)
with the length of 21–24 nucleotides (nt) that are loaded into Argonaute (AGO) to repress expression of
target loci and transcripts through transcriptional or posttranscriptional gene silencing mechanisms. Identification and quantitative characterization of sRNAs are crucial steps toward appreciation of their functions
in biology. Here, we developed a step-by-step protocol to precisely illustrate the process of cloning of sRNA
libraries and correspondingly computational analysis of the recovered sRNAs. This protocol can be used in
all kinds of organisms, including Arabidopsis, and is compatible with various high-throughput sequence
technologies such as Illumina Hiseq. Thus, we wish that this protocol represents an accurate way to identify
and quantify sRNAs in vivo.
Key words Small RNA, RNA silencing, Library construction, High-throughput sequencing, Computational analysis
1 Introduction
RNA silencing is a fundamental mechanism for regulating gene
expression in diverse biological contexts in eukaryotic organisms.
RNA silencing is implemented through a ribonucleoprotein complex, also known as RNA-inducing silencing complexes (RISC) that
is composed of sRNAs and AGOs proteins. sRNAs can be separated
into different classes depending on their originalities and biogenesis
processes. Among sRNAs, microRNAs (miRNAs) and trans-acting
small interfering RNAs (ta-siRNAs) are typically 21 nt long and
loaded into AGO proteins to cleave complementary transcripts
and/or inhibit their translation in cytoplasm [1]. Some species of
sRNAs, typically 24 nt long, guide AGOs to execute transcriptional
gene silencing in nucleus [1].
Understanding of function and mechanisms of sRNAs entails
precise identification and quantification of sRNA populations
in vivo. In earlier studies in the sRNA field, computational prediction [2], sRNA blot [3], and quantitative RT-PCR [4, 5] are
Jose J. Sanchez-Serrano and Julio Salinas (eds.), Arabidopsis Protocols, Methods in Molecular Biology, vol. 2200,
https://doi.org/10.1007/978-1-0716-0880-7_11, © Springer Science+Business Media, LLC, part of Springer Nature 2021
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