Transcriptomic and bioinformatics analysis of the early time-course of the response to prostaglandin F2 alpha in the bovine corpus luteum☆☆☆

RNA expression analysis was performed on the corpus luteum tissue at five time points after prostaglandin F2 alpha treatment of midcycle cows using an Affymetrix Bovine Gene v1 Array. The normalized linear microarray data was uploaded to the NCBI GEO repository (GSE94069). Subsequent statistical analysis determined differentially expressed transcripts ± 1.5-fold change from saline control with P ≤ 0.05. Gene ontology of differentially expressed transcripts was annotated by DAVID and Panther. Physiological characteristics of the study animals are presented in a figure. Bioinformatic analysis by Ingenuity Pathway Analysis was curated, compiled, and presented in tables. A dataset comparison with similar microarray analyses was performed and bioinformatics analysis by Ingenuity Pathway Analysis, DAVID, Panther, and String of differentially expressed genes from each dataset as well as the differentially expressed genes common to all three datasets were curated, compiled, and presented in tables. Finally, a table comparing four bioinformatics tools’ predictions of functions associated with genes common to all three datasets is presented. These data have been further analyzed and interpreted in the companion article “Early transcriptome responses of the bovine mid-cycle corpus luteum to prostaglandin F2 alpha includes cytokine signaling” [1].

a b s t r a c t RNA expression analysis was performed on the corpus luteum tissue at five time points after prostaglandin F2 alpha treatment of midcycle cows using an Affymetrix Bovine Gene v1 Array. The normalized linear microarray data was uploaded to the NCBI GEO repository (GSE94069). Subsequent statistical analysis determined differentially expressed transcripts 7 1.5-fold change from saline control with P r 0.05. Gene ontology of differentially expressed transcripts was annotated by DAVID and Panther. Physiological characteristics of the study animals are presented in a figure. Bioinformatic analysis by Ingenuity Pathway Analysis was curated, compiled, and presented in tables. A dataset comparison with similar microarray analyses was performed and bioinformatics analysis by Ingenuity Pathway Analysis, DAVID, Panther, and String of differentially expressed genes from each dataset as well as the differentially expressed genes common to all three datasets were curated, compiled, and presented in tables. Finally, a table comparing four bioinformatics tools' predictions of functions associated with genes common to all three datasets is presented. These data have been further analyzed and interpreted in the companion article "Early transcriptome responses of the bovine mid-cycle corpus luteum to prostaglandin F2 alpha includes cytokine signaling" [1]. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Specifications Table
Subject area Biology More specific subject area

Reproductive Biology
Type of data Tables, graphs How data was acquired Collected empirical data, RNA microarray, Ingenuity Pathway Analysis, Panther Database Data format Raw data; Normalized, analyzed, and filtered data; curated bioinformatics predictions Experimental factors The estrous cycles of cows were synchronized using two injections of 25 mg Lutalyse 11 days apart.

Experimental features
Post-pubertal multiparous female cattle (n ¼ 16) of composite breeding were treated by intramuscular injection at midcycle (days 9-10) with saline (n ¼ 4) or PGF2α (n ¼ 12) (25 mg Lutalyse). RNA was isolated from the corpus luteum and analyzed by microarray. Differentially expressed transcripts were subjected to bioinformatics pathway analysis.

Data source location
Lincoln, NE, USA; Omaha, NE, USA Data accessibility Raw data is in the public NCBI repository GEO (GSE94069), curated bioinformatics predictions are presented within the article as tables

Value of the data
This study provides the first transcriptomics analysis of the early time-course (0.5-4 h) of the response to prostaglandin F2 α (PGF2α) and extends previous observations on the global effects of PGF2α action in the bovine corpus luteum at 3 h and longer [2,3].
Prediction of upstream regulators and regulation of canonical pathways based on the transcriptome changes during the PGF2α short time-course.
A complete list of differentially expressed transcripts grouped into self-organizing maps representative of signaling waves after PGF2α treatment.
Canonical pathways and upstream regulators predicted by Ingenuity Pathway Analysis for genes common to three similar datasets [1][2][3].

Data
The .cel and .chp files and normalized linear microarray data are available at the NCBI GEO repository: GSE94069
Cows were also treated with an intra-muscular injection of PGF2α (n ¼ 12) and at each of four time points post-injection (0.5, 1, 2, and 4 h), three cows per time point were subjected to a bilateral ovariectomy through a right flank approach under local anesthesia [4,5]. The CL was removed from each ovary, weighed and o 5 mm 3 sections were snap-frozen in liquid N 2 for subsequent protein and RNA analysis. Plasma progesterone concentrations were determined using the ImmuChem Progesterone DA Coated Tube radioimmunoassay kit (MP Biomedicals, Santa Ana, CA) with an intra-assay coefficient of variation of 9.13% and inter-assay coefficient of variation of 7.99%. The University of Nebraska-Lincoln Institutional Animal Care and Use Committee approved all procedures and facilities used in this animal experiment and animal procedures were performed in June 2009 (Control, 0.5, and 1 h) or October 2010 (2 and 4 h) at the University of Nebraska-Lincoln, Animal Sciences Department. Statistical differences in animal characteristics were determined using Kruskal-Wallis test followed by Dunn's post-test or one-way ANOVA followed by Bonferroni's multiple comparison test as appropriate (GraphPad Prism, La Jolla, CA).

Affymetrix bovine gene chip microarray
Luteal tissue from saline-treated (n ¼ 3), and PGF2α treated animals [0.5 h (n ¼ 3), 1 h (n ¼ 3), 2 h (n ¼3), and 4 h (n ¼ 3)] were homogenized and RNA was extracted using a Stratagene RNA Isolation    ⁎ Original file has pathways with P-value 4 0.02 and sorted from largest to smallest based on z-score then smallest to largest P-value, Fisher's exact test P-value limit set to 0.05

Microarray statistics
The microarray data were preprocessed using the robust multi-array average (RMA) method from Affymetrix expression console software (Affymetrix Inc., Santa Clara, CA) to normalize data at the exon level. The mean intensities of multiple probe sets of the same gene were calculated under each array to obtain the corresponding gene expression intensities. The data was filtered to keep the genes with a raw expression value after preprocessing to be 10 or more for at least three samples. Linear Models for Microarray Analysis (LIMMA) [6] in the Bioconductor suite [7] under the statistical program R [8] was applied to compare the log ratio between each of the PGF2α time points and the saline control after adjusting for the box effect. LIMMA applies a linear model and empirical Bayes method for assessing differential expression of the microarray data. Transcripts with a fold-change of at least 1.5 and a Benjamini-Hochberg adjusted P-value of less than 0.05 for each treatment condition versus control were identified as differentially expressed genes.

Self-organizing maps and statistics
Microarray data was filtered to keep genes with a raw expression value after preprocessing to be 30 or more for at least three samples. The log ratio between each of the time points and the saline control were compared using Linear Models of Microarray Analysis in the Bioconductor suite in R. The self-organizing map (SOM) clustering algorithm GeneCluster 2.0 [9] was applied to differentially expressed genes that had a greater than 1.5-fold change in expression and P-value r 0.05 between PGF2α-treated samples and the saline control. The mean normalized log 2 intensity values from each of the five examined biological conditions were used as transcript expression profiles in the clustering analysis. The number of iterations in SOM clustering was set to 500,000 to generate SOMs and hierarchical clustering (correlation-based distance, average link).

Dataset comparisons
Two previously published microarray datasets GSE23348 [2] and GSE27961 [3] examined the effect of in vivo PGF2α or analog treatment on the bovine luteal transcriptome using Affymetrix Bovine Whole Genome Gene Chips (GPL 2112). The datasets were chosen for comparison to the transcriptome dataset presented herein based on the use of a similar bovine gene array platform and similarities in the experimental protocol comparing mid-cycle control CL expression profiles to CL profiles after treatment with PGF2α analog for 4 h (GSE23348) or 6 h (GSE27961). Original.CEL and. CHP files were downloaded from the GEO database and processed as described above in the Statistical Methods. The differentially expressed mRNAs at 4 or 6 h were compared between the three microarray datasets to determine the similarities among the datasets.
Description of the methods are derived from the companion article [1] in Molecular and Cellular Endocrinology.