Microarray dataset supporting a role for ATF4 in isoginkgetin-induced gene expression in HCT116 cells.

Isoginkgetin (IGG) is a compound originally derived from the leaves of Ginkgo biloba trees. It was subsequently identified through a chemical screen to be an inhibitor of both the major and minor spliceosome, with an IC50 value of 30 µM [1]. Little is currently known about the overall effects of spliceosome inhibition on human cells. Here, we treated HCT116 and a p53 null subline of colon cancer cells with 30 µM IGG for 8 hours. Total RNA was isolated, and Affymetrix oligonucleotide microarray analysis was completed using samples from two biologically independent experiments. A relatively small number of transcripts were differentially expressed in these cell lines. There was considerable overlap in the upregulated but not the downregulated transcripts. PANTHER Reactome analysis of these shared upregulated transcripts identified enriched pathways involving the ATF4 transcription factor important in the integrated stress response [2].


Specifications
Genetics: General Specific subject area Genome wide changes in gene expression following isoginkgetin treatment Type of data

Value of the Data
• This microarray data provides information on the transcriptional response of HCT116 and HCT116 p53 null cells following treatment with the pre-mRNA splicing inhibitor, IGG. The data set includes both gene level and individual probe level signal intensities. • The gene level analysis can be used to gain understanding of the changes in gene expression in the presence and absence of p53 in response to IGG. • The probe (exon) level analysis can be used to generate additional information on pre-mRNA splicing and alternative splicing. • The data provided here and linked through the Gene Expression Omnibus (GEO) repository could be used by investigators interested in 1. cellular responses to spliceosome inhibition, 2. the effect of IGG on pre-mRNA splicing and 3. the effects of IGG on non-coding RNAs.

Data Description
The dataset includes gene level and probe level analysis of the cellular responses to the splicing inhibitor IGG in HCT116 colon cancer cells and an isogenic subline deleted of p53 (HCT116 p53 -/-) [3] . IGG significantly increased the expression of 53 mRNAs and decreased the abundance of 26 in the parental HCT116 cell line ( Tables 1 and 2 ). In the p53 knockout subline, IGG significantly increased the expression of 82 and decreased the expression of 53 mRNAs ( Tables 3  and 4 ). Only 22 of the increased and 3 of the decreased mRNAs were common to both cell lines and therefore they were regulated in a p53-independent manner ( Fig. 1 A and B). Panther Reactome Analysis of these shared transcripts identified only 3 over-represented pathways among these shared transcripts. Two of the 3 p53-independent responses "Response of EIF2AK1 (HRI) to heme deficiency" and "ATF4 activates genes in response to endoplasmic reticulum stress" involve the ATF4 transcription factor [2] .   Table 3 List of upregulated transcripts in the HCT116 p53 -/-subline following IGG treatment.     1 Panther Reactome Pathways that were enriched. ' > ' indicates that the Reactome Pathway above is nested. 2 Fold enrichment above expected. 3 The probability of observing this enrichment in a random list of genes of this size determined by Fisher exact test with Bonferroni correction for multiple testing. Fig. 1. Venn diagrams representing IGG upregulated and downregulated transcripts in HCT116 and its p53 null subline. IGG increased (A) and decreased (B) the expression of mRNAs in HCT116 expressing and deleted of p53 (p53 + / + and p53 -/-). Images were created from data in Tables 1-4 at https://bioinformatics.psb.ugent.be/webtools/Venn/ .

Cell culture and drug treatment
HCT116 and HCT116 p53-/-colon cancer cells were seeded in 6cm dishes at 250,0 0 0 cells/dish 24 hours prior to drug treatment. Cells were treated with 30 μM IGG, an equivalent volume of DMSO as a vehicle control, or left untreated for 8 hours. Two biologically independent experiments were performed.

RNA isolation and microarrays
After 8 hours of treatment, media was removed, and cells were washed with PBS. Total RNA was isolated using the Qiagen RNAeasy Mini RNA isolation kit according to manufacturer's in-structions. RNA purity and concentration was determined using the DeNovix DS-11 spectrophotometer. RNA was sent for Agilent Bioanalyzer quality assessment and RNA was then processed for analysis of the Human Transcriptome 2.0 Array at the Stemcore facility at the Ottawa Hospital research institute (OHRI), Ottawa, ON Canada.

Data analysis
Analysis was performed at the probe-and gene-level using the Transcriptome Analysis Console (TAC) 4.0 Software from Affymetrix. Microarray data was analysed using the Affymetrix Transcriptome Analysis Console (TAC) 4.0 software with default settings. A gene was considered expressed in a particular condition if it was detected in 50% of more of the samples and the sample had a DABG p-value of less than 0.05. A one-way between-subject unpaired ANOVA was used to determine statistical significance and was subject to false discovery rate (FDR) multi-test correction (Benjamini-Hochberg Step-Up FDR) for both analyses. A threshold of a 1.5-fold change was also applied and unknown transcripts were removed to identify upregulated ( Tables 1 and  3 ) and downregulated ( Tables 2 and 4 ) transcripts. Panther reactome analysis of RNAs induced in both cell lines ( Fig. 1 A) was performed online ( http://geneontology.org/ ).

Declaration of Competing Interest
The authors have no competing interests to declare