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Related Concept Videos

CRISPR and crRNAs02:53

CRISPR and crRNAs

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Bacteria and archaea are susceptible to viral infections just like eukaryotes; therefore, they have developed a unique adaptive immune system to protect themselves. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) are present in more than 45% of known bacteria and 90% of known archaea.
The CRISPR-Cas system stores a copy of foreign DNA in the host genome and uses it to identify the foreign DNA upon reinfection. CRISPR-Cas has three different...
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Pooled CRISPR-Based Genetic Screens in Mammalian Cells
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CEDA: integrating gene expression data with CRISPR-pooled screen data identifies essential genes with higher

Yue Zhao1,2, Lianbo Yu1,3, Xue Wu1

  • 1Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.

Bioinformatics (Oxford, England)
|October 17, 2022
PubMed
Summary
This summary is machine-generated.

We developed a new method, CRISPR screen with Expression Data Analysis (CEDA), to improve the identification of essential genes from CRISPR screens by integrating gene expression data. CEDA enhances sensitivity for detecting essential genes, especially those with moderate single-guide RNA fold changes.

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Area of Science:

  • Genomics
  • Computational Biology
  • Molecular Biology

Background:

  • Clustered regularly interspaced short palindromic repeats (CRISPR)-based genetic perturbation screens are vital for understanding gene function.
  • Experimental noise in CRISPR screens, particularly for lowly expressed genes, can lead to inaccurate results and a high false positive rate.

Purpose of the Study:

  • To develop a robust statistical method for analyzing CRISPR screen data that accounts for gene expression levels.
  • To improve the identification of essential genes by integrating gene expression profiles with CRISPR screen data.
  • To enhance the sensitivity and reliability of CRISPR screening analysis.

Main Methods:

  • Developed CRISPR screen with Expression Data Analysis (CEDA), a statistical method integrating gene expression profiles and CRISPR screen data.
  • Stratified genes based on expression levels and employed a three-component mixture model for single-guide RNA (sgRNA) log-fold changes.
  • Utilized Empirical Bayesian prior and expectation-maximization algorithm for parameter estimation and false discovery rate inference.

Main Results:

  • CEDA effectively identifies essential genes, particularly those with higher expression levels.
  • Demonstrated comparable reliability to existing methods but with significantly higher sensitivity in detecting essential genes with moderate sgRNA fold changes.
  • Generated an additional list of hit genes from existing CRISPR data by leveraging gene expression information.

Conclusions:

  • Integrating gene expression data with CRISPR screens using CEDA improves the identification of essential genes.
  • CEDA offers a more sensitive approach for detecting essential genes compared to traditional methods, especially when sgRNA fold changes are moderate.
  • The CEDA method provides a valuable tool for researchers to gain deeper insights into gene function from CRISPR screening experiments.