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Related Concept Videos

RNA-seq03:21

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...
Experimental RNAi02:15

Experimental RNAi

RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
RNA Interference01:23

RNA Interference

RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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Related Experiment Video

Updated: May 28, 2026

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

Published on: June 17, 2022

High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing.

David Sims1, Ana M Mendes-Pereira, Jessica Frankum

  • 1The Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK.

Genome Biology
|October 25, 2011
PubMed
Summary
This summary is machine-generated.

RNA interference (RNAi) screening uses short hairpin RNA (shRNA) libraries to study biological processes. New open-source tools, shALIGN and shRNAseq, simplify the analysis of complex RNAi screening data generated by next-generation sequencing.

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Last Updated: May 28, 2026

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Area of Science:

  • Genomics and Molecular Biology
  • Bioinformatics and Computational Biology

Background:

  • RNA interference (RNAi) screening is a powerful technology for dissecting biological processes and disease phenotypes.
  • The increasing availability of genome-wide short hairpin RNA (shRNA) libraries has accelerated research but presents significant data generation and analysis challenges.

Purpose of the Study:

  • To present comprehensive experimental protocols for RNAi screening.
  • To introduce novel open-source computational tools, shALIGN and shRNAseq, for the rapid deconvolution of RNAi screening data.
  • To provide an efficient, flexible, and scalable computational pipeline for RNAi screen analysis.

Main Methods:

  • Development and implementation of shALIGN and shRNAseq computational methodologies.
  • Utilizing next-generation sequencing for high-throughput RNAi screening data acquisition.
  • Establishment of complete experimental protocols for conducting RNAi screens.

Main Results:

  • shALIGN and shRNAseq enable rapid deconvolution of RNAi screening data.
  • The developed computational pipeline ensures efficient screen analysis.
  • The methodology is designed for flexibility and scalability to accommodate future advancements in shRNA library technology.

Conclusions:

  • The described protocols and computational tools significantly address the challenges in RNAi screening data analysis.
  • This work facilitates the broader application of RNAi screening for biological discovery.
  • The open-source nature of the tools promotes accessibility and future development in the field.