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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Related Experiment Video

Updated: Sep 30, 2025

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

Published on: September 16, 2019

Expanding the DNA-encoded library toolbox: identifying small molecules targeting RNA.

Qiuxia Chen¹, You Li¹, Chunrong Lin¹

¹HitGen Inc., Shuangliu District, Chengdu, China.

Nucleic Acids Research

|March 15, 2022

Summary

This summary is machine-generated.

DNA-encoded library technology now efficiently screens RNA targets, overcoming false positives with optimized methods. This expands drug discovery capabilities for identifying novel RNA-binding small molecules.

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Last Updated: Sep 30, 2025

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

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Highly Efficient Ligation of Small RNA Molecules for MicroRNA Quantitation by High-Throughput Sequencing

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An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

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Published on: February 17, 2023

Area of Science:

Medicinal Chemistry
Molecular Biology
Drug Discovery

Background:

DNA-encoded library (DEL) technology is a key method for small molecule identification.
Current DEL strategies are mainly applied to protein targets, limiting broader applications.
DEL selection on RNA targets, like HIV-1 TAR, often yields false-positive DNA-RNA binding signals.

Purpose of the Study:

To develop and validate an optimized DEL selection strategy for RNA targets.
To minimize non-specific DNA-RNA interactions and improve signal accuracy.
To demonstrate the feasibility of identifying potent small molecules against RNA targets.

Main Methods:

Developed an optimized DEL selection strategy using RNA patches and competitive elution.
Implemented k-mer analysis and motif search for differentiating false-positive signals.
Applied the strategy to screen for ligands against the Escherichia coli FMN Riboswitch.

Main Results:

The optimized strategy significantly reduced background noise and false positives.
Enriched compounds against the FMN Riboswitch exhibited double-digit nanomolar binding affinity.
Identified compounds showed functional potency in FMN competition assays.

Conclusions:

Small molecule identification against RNA targets using DEL selection is feasible.
The developed experimental and computational approach enhances RNA ligand screening.
This work expands the application scope of DEL selection in drug discovery.