CRISPR for RNA Editing

CRISPR for RNA Editing

Table of Contents

February 22, 2022

The Transcriptomics Revolution

Next-generation sequencing ushered in the age of genomics, which has yielded incredible biological insights. However, the genome is relatively static compared to the dynamic transcriptome of every cell.

The transcriptome refers to the genes that are actually expressed in a cell, as identified by their RNA transcripts. Technologies like single-cell RNA sequencing (scRNA-Seq) have been instrumental in identifying the huge variety in transcriptomes between cell types and even time-sensitive changes in the cell.

Understanding the transcriptome is also relevant in a disease context, where changes to even a single base in the RNA transcript can affect the downstream protein being expressed. An alternative approach to the CRISPR/Cas9-based gene editing tools for editing a person’s genome is RNA editing tools, which have the advantage of being non-heritable, temporary, and highly specific compared to the permanent changes of DNA editing.

Challenges of RNA Editing

In spite of the promising concept of RNA editing, the technology has been slow to be realized. The main challenge is that the size of the RNA editing Cas13 protein is too big for the most commonly used gene therapy delivery vector, adeno-associated viruses (AAVs).

Compact Cas13: A New Approach for RNA Editing

To address this challenge, researchers from MIT developed super compact Cas13b proteins, called Cas13bt. These proteins were shown to be effective in a CRISPR/Cas system to target mammalian RNA transcripts, and are small enough to be packaged inside an AAV.

This development provides an exciting approach to further developing RNA editing-based therapeutics.

Bioinformatics Analysis Tools

There are many analysis steps to translate scRNA-Seq data into actionable biological insights in a therapeutic context like in CRISPR-Cas13 editing. For these gene and RNA therapy approaches to work, bioinformatics tools will be increasingly critical to identify targets in the sequence data.

Working with service providers like Bridge Informatics is a great option. We support your data management, analysis, and pipeline development needs to eliminate common challenges associated with these downstream analysis tasks. Book a free discovery call with us if you’re interested in outsourcing your bioinformatic needs with Bridge Informatics.

Data and Code Availability

For those looking to view the data from the Kennan et al publication, you can find the deep sequencing data for the entire transcriptome in the BioProject under Project ID PRJNA641934. Similarly, you can find the Python scripts used in this analysis in the following GitHub repository:

Jane Cook, Journalist & Content Writer, Bridge Informatics

Jane is a Content Writer at Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in the management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, please email [email protected] or [email protected].


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