DOI: 10.5061/dryad.0zpc8673k
title: DNA-PKcs RNASeq data: DNA-PKcs wilde-type or kinase-dead protein regulate basal and etoposide-induced gene expression changes

description: Maintenance of the genome is essential for cell survival, and impairment
 of the DNA damage response is associated with multiple pathologies
 including cancer and neurological abnormalities. DNA-PKcs is a DNA repair
 protein and a core component of the classical nonhomologous end-joining
 pathway, but it also has roles in modulating gene expression and thus, the
 overall cellular response to DNA damage. Using cells producing either
 wild-type (WT) or kinase-inactive (KR) DNA-PKcs, we assessed global
 alterations in gene expression in the absence or presence of DNA damage.
 We evaluated differential gene expression in untreated cells and observed
 differences in genes associated with cellular adhesion, cell cycle
 regulation, and inflammation-related pathways. Following exposure to
 etoposide, we compared how KR versus WT cells responded transcriptionally
 to DNA damage. Downregulated genes were mostly involved in protein, sugar,
 and nucleic acid biosynthesis pathways in both genotypes, but enriched
 biological pathways were divergent, again with KR cells manifesting a more
 robust inflammatory response compared to WT cells. To determine what major
 transcriptional regulators are controlling the differences in gene
 expression noted, we used pathway analysis and found that many master
 regulators of histone modifications, proinflammatory pathways, cell cycle
 regulation, Wnt/β-catenin signaling, and cellular development and
 differentiation were impacted by DNA-PKcs status. Finally, we have used
 qPCR to validate selected genes among the differentially regulated
 pathways to validate RNA sequence data. Overall, our results indicate that
 DNA-PKcs, in a kinase-dependent fashion, decreases proinflammatory
 signaling following genotoxic insult. As multiple DNA-PK kinase inhibitors
 are in clinical trials as cancer therapeutics utilized in combination with
 DNA-damaging agents, understanding the transcriptional response when
 DNA-PKcs cannot phosphorylate downstream targets will inform the overall
 patient response to combined treatment.
description: The dataset contains ensemble ID, gene name if applicable,
 comparisons between genotypes with and without drug (etoposide) treatment.
 Within each comparison are log fold change, average expression, p value,
 and adjusted p value.<strong> </strong>
 <strong>Cells culture:</strong> V3-derived Chinese
 Hamster Ovary (CHO) cell lines were kindly provided by Dr. Katherine Meek,
 complemented with either human wild-type (WT), null (Null) or kinase
 inactivate DNA-PKcs, by K3753R mutation (KR), as previously reported (21).
 All cell lines were cultured in alpha-MEM (LifeTechnologies, Waltham, MA)
 supplemented with 10% FBS (MilliporeSigma, St. Louis, MO), 1%
 penicillin/streptomycin (LifeTechnologies), 200 µg/ml G418
 (LifeTechnologies) and 10 µg/ml puromycin (Santa Cruz Biotechnology, Santa
 Cruz, CA) at 37ºC with 5% CO<sub>2</sub>and 100% humidity. All
 standard laboratory chemicals were purchased from MilliporeSigma unless
 otherwise indicated. Cells were cultured on 100 mm dishes overnight and
 next day, after washing, trizol reagent (MilliporeSigma) was applied to
 cells and the cell lysate was collected. Total RNA isolation was according
 to the manufacturer’s instructions. Total RNA was dissolved in
 nuclease-free water followed by spectrophotometric analysis of the RNA
 quantity; RNA was subjected to electrophoresis on an agarose gel to permit
 evaluation of both RNA quality and assure no DNA contamination was
 observed. <strong>Differentially expressed gene
 analysis:</strong> The low-quality raw reads (fastq format) were
 filtered based on Q30 and GC content, then the Illumina adaptors were
 trimmed of reads for a minimum read length of 36 bases using Trimmomatic
 v0.34 (Bolger, Lohse, and Usadel 2014). The index of the Chinese hamster
 reference genome (CHOK1GS_HDv1) was built using HISAT2 v2.1.0 (Kim,
 Langmead, and Salzberg 2015). Hisat2 v2.2.1 tool was utilized to align the
 reads to the genome sequences in FASTA format and output aligned reads in
 binary alignment map (BAM) format were translated into the transcriptomes
 of each sample using stringtie v2.0 tool which uses a novel network flow
 algorithm as well as an optional de novo assembly step to assemble and
 quantitate full-length transcripts representing multiple splice variants
 for each gene locus (Pertea et al. 2015). The stringtie outputs (GTF
 files) were merged to create a single master transcriptome GTF with exact
 same naming and numbering scheme across all transcripts. The feature
 counts tool implemented under subread v2.0 was utilized to quantify
 transcripts assembled by stringtie mapped to each gene  (Liao, Smyth, and
 Shi 2014). Eventually, the differentially expressed (DE) gene profiles
 were statistically analyzed through edgeR and limma R libraries (Ritchie
 et al. 2015; Robinson, McCarthy, and Smyth 2010).
description: This README File was generated 2024-02-28 ## GENERAL INFORMATION 1. Title
 of Dataset: Comparative Analysis of Basal and Etoposide-Induced
 Alterations in Gene Expression by DNA-PKcs Kinase Activity 2. Materials
 & Methods a) Cell culture: V3-derived Chinese Hamster Ovary (CHO) cell
 lines were kindly provided by Dr. Katherine Meek, complemented with either
 human wild-type (WT), null (Null) or kinase inactivate DNA-PKcs, by K3753R
 mutation (KR), as previously reported (21) and designated as WT, Null and
 KR respectively in this study. All cell lines were cultured in alpha-MEM
 (LifeTechnologies, Waltham, MA) supplemented with 10% FBS (MilliporeSigma,
 St. Louis, MO), 1% penicillin/streptomycin (LifeTechnologies), 200 µg/ml
 G418 (LifeTechnologies) and 10 µg/ml puromycin (Santa Cruz Biotechnology,
 Santa Cruz, CA) at 37ºC with 5% CO2 and 100% humidity. All standard
 laboratory chemicals were purchased from MilliporeSigma unless otherwise
 indicated. Cells were cultured on 100 mm dishes overnight and next day,
 after washing, trizol reagent (MilliporeSigma) was applied to cells and
 the cell lysate was collected. Total RNA isolation was according to
 manufacturer’s instructions. Total RNA was dissolved in nuclease-free
 water followed by spectrophotometric analysis of the RNA quantity; RNA was
 subjected to electrophoresis on an agarose gel to permit evaluation of
 both RNA quality and assure no DNA contamination was observed. b)
 Differentially expressed gene analysis: The low-quality raw reads (fastq
 format) were filtered based on Q30 and GC content, then the Illumina
 adaptors were trimmed of reads for a minimum read length of 36 bases using
 Trimmomatic v0.34 (Bolger, Lohse, and Usadel 2014). The index of the
 Chinese hamster reference genome (CHOK1GS_HDv1) was built using HISAT2
 v2.1.0 (Kim, Langmead, and Salzberg 2015). Hisat2 v2.2.1 tool was utilized
 to align the reads to the genome sequences in FASTA format and output
 aligned reads in binary alignment map (BAM) format were translated into
 the transcriptomes of each sample using stringtie v2.0 tool which uses a
 novel network flow algorithm as well as an optional de novo assembly step
 to assemble and quantitate full-length transcripts representing multiple
 splice variants for each gene locus (Pertea et al. 2015). The stringtie
 outputs (GTF files) were merged to create a single master transcriptome
 GTF with exact same naming and numbering scheme across all transcripts.
 The feature counts tool implemented under subread v2.0 was utilized to
 quantify transcripts assembled by stringtie mapped to each gene (Liao,
 Smyth, and Shi 2014). Eventually, the differentially expressed (DE) gene
 profiles were statistically analyzed through edgeR and limma R libraries
 (Ritchie et al. 2015; Robinson, McCarthy, and Smyth 2010). ## Description
 of the Data and file structure The data is RNAseq data that will describe
 up versus down regulated genes. 1. Legend KR: kinase-inactivated DNA-PKcs
 WT: wild-type DNA-PKcs D: DMSO treated E: Etoposide treated Null: Lacks
 DNA-PKcs logFC: log fold-change AveExpr: Average expression P.Value: P
 Value adj. P. Val: adjusted P Value 1. File List a)
 all9obs_PK_with_comparison.xls ## Sharing/access Information Links to
 publications that use this data: Ali, S.I., Najaf-Panah, M.J., Pyper,
 K.B., Lujan, F.E., Sena,J., & Ashley, A.K. (2024) Comparative Analysis
 of Basal and Etoposide-Induced Alterations in Gene Expression by DNA-PKcs
 Kinase Activity Frontiers in Genetics
 [https://doi.org/10.3389/fgene.2024.1276365](https://doi.org/10.3389/fgene.2024.1276365).