RNAseq analysis of heart samples collected from wild-type and ZNF768 null mice 8 hours post-irradiation
Data files
Mar 29, 2025 version files 61.26 MB
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Heart_ZNF768_KO_mouse1.tsv
5.12 MB
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Heart_ZNF768_KO_mouse3.tsv
5.15 MB
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Heart_ZNF768_KO_mouse4.tsv
5.13 MB
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Heart_ZNF768_KO_mouse5.tsv
5.17 MB
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Heart_ZNF768_KO_mouse6.tsv
5.04 MB
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Heart_ZNF768_KO_mouse7.tsv
5.14 MB
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Heart_ZNF768_WT_mouse1.tsv
5.15 MB
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Heart_ZNF768_WT_mouse3.tsv
5.09 MB
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Heart_ZNF768_WT_mouse4.tsv
5.07 MB
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Heart_ZNF768_WT_mouse5.tsv
5.02 MB
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Heart_ZNF768_WT_mouse6.tsv
5.09 MB
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Heart_ZNF768_WT_mouse7.tsv
5.10 MB
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README.md
3.10 KB
Abstract
Cell proliferation is a fundamental process required for organismal development, growth, and maintenance. Failure to control this process leads to several diseases, including cancer. Zinc finger protein 768 (ZNF768) is an emerging transcription factor that plays key roles in driving proliferation. In addition to controlling a gene network supporting cell division, ZNF768 physically interacts and inhibits the activity of the tumor suppressor p53. Although the importance of ZNF768 in promoting cell proliferation has been well demonstrated in vitro, the physiological and pathological roles of ZNF768 in vivo are still unknown. Here, we report the generation and characterization of a ZNF768 null mouse model. ZNF768 null mice are viable but show a growth defect early in life. Mouse embryonic fibroblasts (MEFs) isolated from ZNF768 null embryos exhibit higher p53 levels, premature senescence, and higher sensitivity to genotoxic stress. In line with these findings, ZNF768 null mice showed increased radiosensitivity. This effect was associated not only with higher expression of a subset of p53 targets genes, but also with alterations in genes regulating transmembrane receptor signaling, cell adhesion, and growth. Because ZNF768 levels are elevated in tumors, we tested the impact of ZNF768 loss on cancer development in mice. Here, we show that ZNF768 deletion was sufficient to repress lung tumor development in a KRASG12D-induced cancer mouse model. Overall, our findings establish ZNF768 as an important protein controlling cell proliferation that could potentially be targeted to reduce tumorigenesis.
https://doi.org/10.5061/dryad.j0zpc86r3
Description of the data and file structure
Here we provided RNAseq analyses of heart tissues collected from ZNF768 wild-type and ZNF768 knockout (KO) mice 8 hours after 4 Gy total body irradiation. This in vivo study was originally performed with n=8/group and several in vivo parameters were measured. The RNAseq experiment presented here was performed using 6 animals per group. We use 6 out of 8 mice per group to reduce the cost of the experiment. The weight of the heart was used to define representative samples for the RNAseq experiment. Tximport R package (version 1.34.0) (PMID: 26925227) was applied to import transcript abundances and obtain estimated counts. Differential gene expression analysis was performed with theDESeq2 R package (version 1.46.0) (PMID: 25516281). Here are abundance raw files that present the levels for transcripts are uploaded.
Files and variables
“KO” = Knockout
“WT” = wild-type
“mouse#” = mouse ID
File: Heart_ZNF768_WT_mouse1.tsv
Description: RNAseq analysis of the heart of ZNF768 wild-type (WT) mouse #1.
File: Heart_ZNF768_WT_mouse3.tsv
Description: RNAseq analysis of the heart of ZNF768 wild-type (WT) mouse #3.
File: Heart_ZNF768_WT_mouse4.tsv
Description: RNAseq analysis of the heart of ZNF768 wild-type (WT) mouse #4.
File: Heart_ZNF768_WT_mouse5.tsv
Description: RNAseq analysis of the heart of ZNF768 wild-type (WT) mouse #5.
File: Heart_ZNF768_WT_mouse6.tsv
Description: RNAseq analysis of the heart of ZNF768 wild-type (WT) mouse #6
File: Heart_ZNF768_WT_mouse7.tsv
Description: RNAseq analysis of the heart of ZNF768 wild-type (WT) mouse #7.
File: Heart_ZNF768_KO_mouse1.tsv
Description: RNAseq analysis of the heart of ZNF768 knockout (KO) mouse #1.
File: Heart_ZNF768_KO_mouse3.tsv
Description: RNAseq analysis of the heart of ZNF768 knockout (KO) mouse #3.
File: Heart_ZNF768_KO_mouse4.tsv
Description: RNAseq analysis of the heart of ZNF768 knockout (KO) mouse #4.
File: Heart_ZNF768_KO_mouse5.tsv
Description: RNAseq analysis of the heart of ZNF768 knockout (KO) mouse #5.
File: Heart_ZNF768_KO_mouse6.tsv
Description: RNAseq analysis of the heart of ZNF768 knockout (KO) mouse #6.
File: Heart_ZNF768_KO_mouse7.tsv
Description: RNAseq analysis of the heart of ZNF768 knockout (KO) mouse #7.
Definition of the variables in the tabular data.
target_id – the name of the quantified transcript.
length – the actual length of the transcript in base pairs (bp).
eff_length (effective length) – the estimated effective length of the transcript. It refers to the number of possible start sites within a transcript that could generate a fragment.
est_counts (estimated counts) – the estimated number of reads originating from this transcript.
tpm (transcripts per million) – a normalized expression value.
Code/software
N/A
Access information
N/A
Total RNA was isolated from tissue using TRI Reagent Solution (ThermoFisher Scientific, #AM9738) and the Monarch Total RNA Miniprep Kit (NEB, #T2010) and RNA concentration was estimated from absorbance at 260 nm. The NEBNext Ultra II directional RNA library prep kit for Illumina (NEB, #E7760L) was used to prepare mRNA sequencing libraries using 800 ng of total RNA as a template. Adaptor ligated DNA was purified with the AxyPrep Mag PCR Clean-up kit (Axygen, #MAG-PCR-CL) and a PCR enrichment step of 9 cycles was done. The quality of final amplified libraries was examined with a DNA screentape D1000 on a TapeStation 2200 and the quantification was done on the QuBit 3.0 fluorometer (ThermoFisher Scientific). Subsequently, mRNA-seq librairies with unique dual index were pooled together in equimolar ratio and sequenced for paired-end 100 pb sequencing on an Illumina NovaSeq 6000 at the Next-Generation Sequencing Platform, Genomics Center, CHU de Québec-Université Laval Research Center, Québec City, Canada. The mean coverage/sample was 35M paired-end reads. The quality of sequencing reads was first assessed using FastQC (version 0.12.0) (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Adapter sequences and low-quality bases were removed using Trim Galore (version 0.6.10) (https://github.com/FelixKrueger/TrimGalore) and the reads were next aligned to the mouse genome (GRCm39) using Kallistoworkflow (version 0.46.1) (PMID: 27043002).