Data from: The Hsp40 co-chaperone DNAJC7 regulates polyglutamine aggregation and exhibits context-dependent effects on polyglycine aggregation
Data files
Mar 03, 2026 version files 928.96 MB
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G100_FRET-high.fastq.gz
173.34 MB
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G100_FRET-low.fastq.gz
171.09 MB
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human_chap_crispri.g2s.txt
68.16 KB
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human_chap_crispri.uniq.var.fa
95.35 KB
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Q79_FRET-high_Screen1.fastq.gz
92.05 MB
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Q79_FRET-high_Screen2.fastq.gz
209.72 MB
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Q79_FRET-low_Screen1.fastq.gz
118.12 MB
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Q79_FRET-low_Screen2.fastq.gz
164.47 MB
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README.md
2.94 KB
Abstract
Protein-encoding nucleotide repeat expansion diseases, including polyglutamine (polyQ) and polyglycine (polyG) diseases, are characterized by the accumulation of aggregation-prone proteins. In the polyQ diseases, including Huntington’s disease and several spinocerebellar ataxias, substantial prior evidence supports a pathogenic role for mutant polyQ-expanded protein misfolding and aggregation, with molecular chaperones showing promise in suppressing disease phenotypes in cellular and animal models. The goal of this study is to establish a scalable cell-based model to systematically evaluate genetic modifiers of protein aggregation in both polyQ and polyG diseases. We developed FRET-based reporter systems that model polyQ and polyG aggregation in human cells and used them to perform high-throughput CRISPR interference screens targeting all known molecular chaperones. In the polyQ model, the screen identified multiple Hsp70 chaperones (HSPA8, HSPA4) and Hsp40 co-chaperones (DNAJB6, DNAJB1) previously implicated in polyQ aggregation and additionally revealed the Hsp40 co-chaperone DNAJC7 as a potent and previously unrecognized suppressor of polyQ aggregation. In contrast, in a FRET-based polyG aggregation model of neuronal intranuclear inclusion disease, CRISPRi screening showed minimal overlap of chaperone modifiers of the polyQ screen. Direct knockdown of DNAJC7 also did not affect polyG aggregation, yet overexpressed DNAJC7 co-localized with both polyQ and polyG aggregates in cells and reduced their aggregation. In addition to establishing new inducible, scalable cellular models for polyQ and polyG aggregation, this work expands the role of DNAJC7 in regulating folding of disease-associated proteins.
Dataset DOI: 10.5061/dryad.0gb5mkmdh
Description of the data and file structure
The data included in this submission are the raw FASTQ files generated from sequencing of CRISPR sgRNA protospacers from HEK293T cells toward identifying molecular chaperone modifiers of polyglutamine (polyQ) or polyglycine (polyG) protein aggregation. Also included are the two tables containing information on the sgRNA protospacer sequences and their target genes; these tables were used to align the protospacer sequences from each FASTQ file to the targeted gene. The polyQ screen was performed twice, and the polyG screen was performed once.
Files and variables
File: human_chap_crispri.g2s.txt
Description: A table that provides the targeted gene for each sgRNA identifier
Variables: N/A
File: human_chap_crispri.uniq.var.fa
Description: A table that provides sgRNA protospacer for each sgRNA identifier
File: G100_FRET-high.fastq.gz
Description: The protospacer sequences from the FRET-high cell population of the polyG chaperone screen.
File: G100_FRET-low.fastq.gz
Description: The protospacer sequences from the FRET-low cell population of the polyG chaperone screen.
File: Q79_FRET-high_Screen1.fastq.gz
Description: The protospacer sequences from the first FRET-high cell population of the first polyQ chaperone screen.
File: Q79_FRET-low_Screen1.fastq.gz
Description: The protospacer sequences from the FRET-low cell population of the first polyQ chaperone screen.
File: Q79_FRET-low_Screen2.fastq.gz
Description: The protospacer sequences from the FRET-low cell population of the second polyQ chaperone screen.
File: Q79_FRET-high_Screen2.fastq.gz
Description: The protospacer sequences from the FRET-high cell population of the second polyQ chaperone screen.
Code/software
The pipelines we used to analyze the sequencing files have been previously described in the following links:
sgcount: https://github.com/noamteyssier/sgcount
crispr_screen https://github.com/noamteyssier/crispr_screen/
In brief, 'sgcount' is used to align the protospacer sequences from each FASTQ file to the reference sequences provided in human_chap_crispri.g2s.txt and human_chap_crispri.uniq.var.fa. 'crispr_screen' is then used to analyze differential abundance of sgRNAs and gene level knockdown phenotypes between different conditions (FRET-high versus FRET-low).
No specific software is otherwise required for the analysis of the above files. The FASTQ files made available here are for evaluation by CRISPR screen analysis pipeline based on user preference.
HEK293T cells containing CRISPRi machinery1 were transduced with lentiviral constructs expressing doxycycline-inducible, nuclear-localized polyQ or polyG proteins that are aggregation-prone. The proteins were also fluorescently tagged (mScarlet and mNeonGreen). This fluorescence pair allows FRET-based readout of protein aggregation. We subsequently generated a monoclonal cell line for the FRET-paired polyQ or polyG inducible protein expression, and designated it as NLS-FRET-Q79 or NLS-FRET-G100, respectively.
The cell lines were transduced with a sgRNA library consisting of 2071 sgRNAs targeting nearly all known molecular chaperones (356 genes) along with non-targeting controls, as previously described2. On Day 2, with ∼30 % of the cells showing BFP positivity, the cells were passaged and replated with 2 μg/ml puromycin (Gibco, A1113803). This was repeated on day 5. On day 7, with > 70 % of cells showing BFP positivity, the cells were passaged and 20 million cells were plated without puromycin and with the addition of 2 ng/ml doxycycline. The cells were regularly passaged until day 5. The cells were dissociated with trypsin, resuspended in complete DMEM, and sorted using the BD FACSAria Fusion Cell Sorter into FRET-low (∼6 million cells) and FRET-high (∼2 million cells). Sorting and gDNA isolation for the polyQ chaperone screen was performed twice (two separate times from the same starting population of library-transduced cells). Sorting for the polyG chaperone screen was performed once. Genomic DNA was isolated using a Monarch gDNA extraction kit according to manufacturer protocols. sgRNA-encoding regions were then amplified, followed by sequencing of the protospacers by Illumina NextSeq2000.
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