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Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction

Single nucleotide variants (SNVs) are prevalent genetic factors shaping individual trait profiles and disease susceptibility. The recent development and optimizations of base editors, rubber and pencil genome editing tools now promise to enable direct functional assessment of SNVs in model organisms...

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Autores principales: Cornean, Alex, Gierten, Jakob, Welz, Bettina, Mateo, Juan Luis, Thumberger, Thomas, Wittbrodt, Joachim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9033269/
https://www.ncbi.nlm.nih.gov/pubmed/35373735
http://dx.doi.org/10.7554/eLife.72124
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author Cornean, Alex
Gierten, Jakob
Welz, Bettina
Mateo, Juan Luis
Thumberger, Thomas
Wittbrodt, Joachim
author_facet Cornean, Alex
Gierten, Jakob
Welz, Bettina
Mateo, Juan Luis
Thumberger, Thomas
Wittbrodt, Joachim
author_sort Cornean, Alex
collection PubMed
description Single nucleotide variants (SNVs) are prevalent genetic factors shaping individual trait profiles and disease susceptibility. The recent development and optimizations of base editors, rubber and pencil genome editing tools now promise to enable direct functional assessment of SNVs in model organisms. However, the lack of bioinformatic tools aiding target prediction limits the application of base editing in vivo. Here, we provide a framework for adenine and cytosine base editing in medaka (Oryzias latipes) and zebrafish (Danio rerio), ideal for scalable validation studies. We developed an online base editing tool ACEofBASEs (a careful evaluation of base-edits), to facilitate decision-making by streamlining sgRNA design and performing off-target evaluation. We used state-of-the-art adenine (ABE) and cytosine base editors (CBE) in medaka and zebrafish to edit eye pigmentation genes and transgenic GFP function with high efficiencies. Base editing in the genes encoding troponin T and the potassium channel ERG faithfully recreated known cardiac phenotypes. Deep-sequencing of alleles revealed the abundance of intended edits in comparison to low levels of insertion or deletion (indel) events for ABE8e and evoBE4max. We finally validated missense mutations in novel candidate genes of congenital heart disease (CHD) dapk3, ube2b, usp44, and ptpn11 in F0 and F1 for a subset of these target genes with genotype-phenotype correlation. This base editing framework applies to a wide range of SNV-susceptible traits accessible in fish, facilitating straight-forward candidate validation and prioritization for detailed mechanistic downstream studies.
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spelling pubmed-90332692022-04-23 Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction Cornean, Alex Gierten, Jakob Welz, Bettina Mateo, Juan Luis Thumberger, Thomas Wittbrodt, Joachim eLife Developmental Biology Single nucleotide variants (SNVs) are prevalent genetic factors shaping individual trait profiles and disease susceptibility. The recent development and optimizations of base editors, rubber and pencil genome editing tools now promise to enable direct functional assessment of SNVs in model organisms. However, the lack of bioinformatic tools aiding target prediction limits the application of base editing in vivo. Here, we provide a framework for adenine and cytosine base editing in medaka (Oryzias latipes) and zebrafish (Danio rerio), ideal for scalable validation studies. We developed an online base editing tool ACEofBASEs (a careful evaluation of base-edits), to facilitate decision-making by streamlining sgRNA design and performing off-target evaluation. We used state-of-the-art adenine (ABE) and cytosine base editors (CBE) in medaka and zebrafish to edit eye pigmentation genes and transgenic GFP function with high efficiencies. Base editing in the genes encoding troponin T and the potassium channel ERG faithfully recreated known cardiac phenotypes. Deep-sequencing of alleles revealed the abundance of intended edits in comparison to low levels of insertion or deletion (indel) events for ABE8e and evoBE4max. We finally validated missense mutations in novel candidate genes of congenital heart disease (CHD) dapk3, ube2b, usp44, and ptpn11 in F0 and F1 for a subset of these target genes with genotype-phenotype correlation. This base editing framework applies to a wide range of SNV-susceptible traits accessible in fish, facilitating straight-forward candidate validation and prioritization for detailed mechanistic downstream studies. eLife Sciences Publications, Ltd 2022-04-04 /pmc/articles/PMC9033269/ /pubmed/35373735 http://dx.doi.org/10.7554/eLife.72124 Text en © 2022, Cornean et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Developmental Biology
Cornean, Alex
Gierten, Jakob
Welz, Bettina
Mateo, Juan Luis
Thumberger, Thomas
Wittbrodt, Joachim
Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction
title Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction
title_full Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction
title_fullStr Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction
title_full_unstemmed Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction
title_short Precise in vivo functional analysis of DNA variants with base editing using ACEofBASEs target prediction
title_sort precise in vivo functional analysis of dna variants with base editing using aceofbases target prediction
topic Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9033269/
https://www.ncbi.nlm.nih.gov/pubmed/35373735
http://dx.doi.org/10.7554/eLife.72124
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