Cas13d-mediated isoform-specific RNA knockdown with a unified computational and experimental toolbox.


Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
13 Sep 2023
Historique:
pubmed: 25 9 2023
medline: 25 9 2023
entrez: 25 9 2023
Statut: epublish

Résumé

Alternative splicing is an essential mechanism for diversifying proteins, in which mature RNA isoforms produce proteins with potentially distinct functions. Two major challenges in characterizing the cellular function of isoforms are the lack of experimental methods to specifically and efficiently modulate isoform expression and computational tools for complex experimental design. To address these gaps, we developed and methodically tested a strategy which pairs the RNA-targeting CRISPR/Cas13d system with guide RNAs that span exon-exon junctions in the mature RNA. We performed a high-throughput essentiality screen, quantitative RT-PCR assays, and PacBio long read sequencing to affirm our ability to specifically target and robustly knockdown individual RNA isoforms. In parallel, we provide computational tools for experimental design and screen analysis. Considering all possible splice junctions annotated in GENCODE for multi-isoform genes and our gRNA efficacy predictions, we estimate that our junction-centric strategy can uniquely target up to 89% of human RNA isoforms, including 50,066 protein-coding and 11,415 lncRNA isoforms. Importantly, this specificity spans all splicing and transcriptional events, including exon skipping and inclusion, alternative 5' and 3' splice sites, and alternative starts and ends.

Identifiants

pubmed: 37745416
doi: 10.1101/2023.09.12.557474
pmc: PMC10515814
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : NIGMS NIH HHS
ID : F32 GM142213
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA279135
Pays : United States
Organisme : NCI NIH HHS
ID : R21 CA272345
Pays : United States
Organisme : NHGRI NIH HHS
ID : DP2 HG010099
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI176601
Pays : United States

Auteurs

Megan D Schertzer (MD)

New York Genome Center, New York, NY.
Department of Computer Science, Columbia University, New York, NY.

Andrew Stirn (A)

New York Genome Center, New York, NY.
Department of Computer Science, Columbia University, New York, NY.

Keren Isaev (K)

New York Genome Center, New York, NY.
Department of Systems Biology, Columbia University, New York, NY.

Laura Pereira (L)

New York Genome Center, New York, NY.

Anjali Das (A)

New York Genome Center, New York, NY.
Department of Computer Science, Columbia University, New York, NY.

Claire Harbison (C)

New York Genome Center, New York, NY.

Stella H Park (SH)

New York Genome Center, New York, NY.
Department of Biomedical Engineering, Columbia University, New York, NY.

Hans-Hermann Wessels (HH)

New York Genome Center, New York, NY.
Department of Biology, New York University, New York, NY.

Neville E Sanjana (NE)

New York Genome Center, New York, NY.
Department of Biology, New York University, New York, NY.

David A Knowles (DA)

New York Genome Center, New York, NY.
Department of Computer Science, Columbia University, New York, NY.
Department of Systems Biology, Columbia University, New York, NY.
Data Science Institute, Columbia University, New York, NY.

Classifications MeSH