DOI: 10.5061/dryad.k3j9kd5cb
title: Base editing strategies to convert CAG to CAA diminish the disease-causing mutation in Huntington's disease

description: An expanded CAG repeat in the huntingtin gene (HTT) causes
 Huntington's disease (HD). Since the length of uninterrupted CAG
 repeat, not polyglutamine, determines the age-at-onset in HD, base editing
 strategies to convert CAG to CAA are anticipated to delay onset by
 shortening the uninterrupted CAG repeat. Here, we developed base editing
 strategies to convert CAG in the repeat to CAA and determined their
 molecular outcomes and effects on relevant disease phenotypes. Base
 editing strategies employing combinations of cytosine base editors and
 gRNAs efficiently converted CAG to CAA at various sites in the CAG repeat
 without generating significant indels, off-target edits, or transcriptome
 alterations, demonstrating their feasibility and specificity. Candidate BE
 strategies converted CAG to CAA on both expanded and non-expanded CAG
 repeats without altering HTT mRNA and protein levels. In addition, somatic
 CAG repeat expansion, which is the major disease driver in HD, was
 significantly decreased in the liver by a candidate BE strategy treatment
 in HD knock-in mice carrying canonical CAG repeats. Notably, CAG repeat
 expansion was abolished entirely in HD knock-in mice carrying
 CAA-interrupted repeats, supporting the therapeutic potential of
 CAG-to-CAA conversion strategies in HD and potentially other repeat
 expansion disorders.
description: To determine the molecular
 consequences of candidate BE strategies, we performed RNAseq analysis. We
 transfected HEK293 cells with BE4max+empty vector, BE4max+gRNA 1, or 
 BE4max+gRNA2 for 72hours. Subsequently, genomic DNA for MiSeq analysis and
 cell pellets for RNAseq analysis were generated from replica plates
 Genome-wide RNAseq analysis (Tru-Seq strand specific large insert RNA
 sequencing) was performed by the Broad Institute. Sequence data were
 processed by STAR aligner (Dobin 2013, 23104886) as part of the Broad
 Institute's standard RNAseq analysis pipeline. For differential gene
 expression (DGE) analysis, we used transcripts per million (TPM) data
 computed by the TPMCalculator (https://github.com/ncbi/TPMCalculator)
 (Alvarez 2019, 30379987). Expression levels in approximately 19,000
 protein-coding genes based on Ensembl
 (ftp://ftp.ensembl.org/pub/release-75/gtf/homo_sapiens/) were normalized
 The DGE analysis was performed by the generalized linear model using a
 library of “glm” in R package v3.3.1 (https://www.r-project.org/) after
 adjustment for two principal components based on RNAseq data, followed by
 multiple test correction using an FDR method. A multiple test corrected
 p-value less than 0.05 was considered statistically significant.
description: Expression data can be opened by text editors,
 Microsoft Excel, and R. Metadata can be opened by the same programs.
 README.md file can be opened by text editors.
description: # Base editing strategies to convert CAG to CAA in Huntington's
 disease ### HD.BE.RNAseq.Meta.Data.230116.csv: Sample characteristics and
 meta-data Description of columns in the metadata file * Sample: Name of
 the sample for each RNAseq sample * Cell: HEK293 cells that were used for
 RNAseq analysis * Group: experimental group including empty vector-treated
 controls (n=4), gRNA 1-tretaed samples (n=4), and gRNA2-treated samples
 (n=4) * Replicate: replicate number * PC1: principal component 1 value *
 PC2: principal component 2 value * PC3: principal component 3 value * PC4:
 principal component 4 value * PC5: principal component 5 value * PC6:
 principal component 6 value * PC7: principal component 7 value * PC8:
 principal component 8 value * PC9: principal component 9 value * PC10:
 principal component 10 value * PC11: principal component 11 value * PC12:
 principal component 12 value ### HD.BE.RNAseq.12.Sample.230116.txt: RNAseq
 expression data