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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 microarray-based...

Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

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Related Experiment Video

Updated: Jun 14, 2026

In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

Published on: May 5, 2023

Function-based gene identification using enzymatically generated normalized shRNA library and massive parallel

Michael Shtutman¹, Anil Maliyekkel, Yu Shao

¹Cancer Center, Ordway Research Institute, Albany, NY 12208, USA.

Proceedings of the National Academy of Sciences of the United States of America

|April 7, 2010

Summary

This summary is machine-generated.

This study developed a novel RNA interference (RNAi) library to identify genes that regulate cell growth. The library successfully identified potential cancer drug targets by screening for genes inhibiting breast carcinoma cell growth.

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Pooled shRNA Library Screening to Identify Factors that Modulate a Drug Resistance Phenotype

Pooled shRNA Library Screening to Identify Factors that Modulate a Drug Resistance Phenotype

Published on: June 17, 2022

Area of Science:

Molecular Biology
Genetics
Cancer Research

Background:

Developing effective strategies for function-based gene identification is crucial for understanding cellular processes and disease mechanisms.
RNA interference (RNAi) offers a powerful tool for gene silencing, but optimizing short hairpin RNA (shRNA) efficacy remains a challenge.
Identifying novel cancer targets requires efficient high-throughput screening methods.

Purpose of the Study:

To create and validate a comprehensive shRNA library for function-based gene identification.
To establish structural criteria for enhancing shRNA efficacy.
To identify novel cancer drug targets by screening for genes that inhibit breast carcinoma cell growth.

Main Methods:

Enzymatic generation of a normalized human cDNA-derived shRNA library in an inducible lentiviral vector.
Measurement of RNAi activities for 101 shRNA clones targeting 100 human genes and 201 shRNAs targeting firefly luciferase.
Structure-activity analysis to derive criteria for shRNA efficacy.
Selection of shRNAs inhibiting breast carcinoma cell growth to identify potential oncogenes and cancer targets.

Main Results:

Structure-activity analysis identified criteria that increased active shRNA frequencies up to 5-fold.
Screening identified 119 potential cancer drug targets, enriched in cancer-associated pathways.
Short interfering RNAs (siRNAs) targeting 19 of 22 validated genes inhibited cell growth, confirming target identification efficiency.

Conclusions:

The developed shRNA library and structure-activity analysis provide an efficient strategy for high-throughput target gene identification.
This approach successfully identified novel genes and pathways implicated in cancer, offering promising avenues for drug development.
The validated strategy demonstrates significant potential for accelerating the discovery of new cancer therapies.