Dataset on transcriptional profiles and the developmental characteristics of PDGFRα expressing lung fibroblasts

The following data are derived from key stages of acinar lung development and define the developmental role of lung interstitial fibroblasts expressing platelet-derived growth factor alpha (PDGFRα). This dataset is related to the research article entitled “Temporal, spatial, and phenotypical changes of PDGFRα expressing fibroblasts during late lung development” (Endale et al., 2017) [1]. At E16.5 (canalicular), E18.5 (saccular), P7 (early alveolar) and P28 (late alveolar), PDGFRαGFP mice, in conjunction with immunohistochemical markers, were utilized to define the spatiotemporal relationship of PDGFRα+ fibroblasts to endothelial, stromal and epithelial cells in both the proximal and distal acinar lung. Complimentary analysis with flow cytometry was employed to determine changes in cellular proliferation, define lipofibroblast and myofibroblast populations via the presence of intracellular lipid or alpha smooth muscle actin (αSMA), and evaluate the expression of CD34, CD29, and Sca-1. Finally, PDGFRα+ cells isolated at each stage of acinar lung development were subjected to RNA-Seq analysis, data was subjected to Bayesian timeline analysis and transcriptional factor promoter enrichment analysis.

expression of CD34, CD29, and Sca-1. Finally, PDGFRα þ cells isolated at each stage of acinar lung development were subjected to RNA-Seq analysis, data was subjected to Bayesian timeline analysis and transcriptional factor promoter enrichment analysis. &

Data
The data presented herein are representative of the key stages of acinar lung development and define the developmental role of lung interstitial fibroblasts expressing platelet-derived growth factor alpha (PDGFRα). Cells expressing PDGFRα were analyzed at E16.5, E18.5, P7 and P28. The spatiotemporal localization of PDGFRα GFP E18.5 at (Fig. 1) demonstrates the relationship of PDGFRα þ fibroblasts to proximal and distal saccular lung structures. Flow cytometry using direct flow cytometry of whole-lung single cell suspension preparation and selection by differential adherence in tissue culture to enrich and analyze PDGFRα þ fibroblast populations is presented in Fig. 2. PDGFRα GFP expression was assessed at E16.5, P7, and P28 for GFP dim and GFP bright sub-populations. For the two distinct sub-populations present at P7, the relative abundance of myofibroblasts (αSMA þ ) and lipofibroblasts (LipidTOX þ ) within each population is presented (Fig. 3). Fig. 4 shows data on temporal changes in neutral lipid, αSMA, proliferation, and cell surface expression of CD34, CD29, and Sca-1 in CD326 þ , CD31 þ , CD140 þ and CD140a neg stromal cells. The gene expression profile from RNA-Seq data provides information in cell-cycle gene changes of isolated PDGFRα þ fibroblasts throughout acinar lung development ( Fig. 5 and Table 1), individual genes upregulated at E18.5 in PDGFRα þ fibroblasts (Table 2), and changes in contractile gene expression in PDGFRα þ fibroblasts (Table 3).
Additionally, data from computational transcription factor binding site analyses (Table 4), ChIP-Seq enrichment profiles (Table 5), and promoter sequences of individual genes dynamically expressed by PDGFRα þ fibroblasts during acinar lung development. The three transcription factors identified by ChIP-Seq analysis are presented in Table 6.

Animals
B6.129S4-PDGFRα tm11(EGFP)Sor /J mouse-line herein designated PDGFRα GFP [2], with PDGFRα promoter driving the expression of the H2B-eGFP fusion gene were used for immunohistochemical, differential plate-down, and flow cytometry analyses. Mice lacking the PDGFRα GFP tag were used for PDGFRα þ cell RNA-Seq analysis.

Confocal microscopy
Lung tissues were harvested, fixed with 4% PFA in PBS and frozen. Tissue was sectioned into 200 μm slices and stained with anti-αSMA (Sigma-Aldrich, St. Louis, MO), Pro-SPC and chicken polyclonal anti-GFP antibody (Abcam, Cambridge, MA). Data was analyzed by Imaris software, version 7.6.

Characterization of PDGFRα GFP Cells by flow cytometry in plate-adhered or suspension cells
Lung tissue from PDGFRα GFP mice was harvested, processed into single cell suspension as previously described [3]. Cells were incubated in Dulbecco's DMEM/F12 (10% FBS, 2% pen/strep) after 2 h of culture, the media containing the non-adherent cell fraction was collected, and the adherent Fig. 1. Spatial distribution of PDGFRα GFP cells during the saccular stage of development. Confocal microscopy of lung sections from E18.5 PDGFRα GFP mouse lungs co-stained with αSMA and pro-SPC to demonstrate the relationship of PDGFRα GFP cells to saccular epithelial cells and contribution to αSMA-containing developing conducting airways (A) and blood vessels (B). Images obtained with 40X objective. fraction was collected using Accutase (1 Â ACCUTASE enzymes in Dulbecco's PBS (0.2 g/L KCl, 0.2 g/L KH 2 PO 4 , 8 g/L NaCl, and 1.15 g/L Na 2 HPO 4 ) containing 0.5 mM EDTA Á 4Na and 3 mg/L Phenol Red).

Bioinformatics data analysis
RNA-Seq data was quantitated using TopHat and Cufflinks [4], genes were included with the expression level (FPKM) was more than 1 in all samples. Bayesian Analysis of Time Series (BATS) Fig. 2. Proportions and characteristics of PDGFRα GFP cells obtained by direct FACS compared to isolation by differential adherence. Flow cytometry profile of lung cell lineage proportions and PDGFRα GFP proportions of fresh whole cell suspension or after selection by differential adherence. Single cell suspensions were stained and subjected to FACS directly after isolation (whole prep) or following incubation for 2 h to obtain non-adherent cells (supernatant) and adherent stromal cells (adherent). (A) Relative proportion of hematopoietic (CD45 þ ), epithelial (CD326 þ ), endothelial (CD31 þ ), CD140a þ (PDGFRα þ ) stromal, and CD140a neg stromal cell populations analyzed by FACS in samples obtained from whole-lung suspension vs. non-adherent and adherent cells following differential adherence. (B) Distribution of PDGFRα-GFP bright and PDGFRα-GFP dim stromal cells contained in non-adherent and adherent cell fractions following differential adherence. (C) Proportion of PDGFRα-GFP bright (dark green) and PDGFRα-GFP dim (light green) fibroblasts contained in single cell suspensions by direct FACS or FACS following differential adherence. (D) The relative proportion CD29 þ , CD34 þ CD29 þ , CD34 þ or CD29 -CD34subpopulations in CD140a þ cells analyzed by direct FACS or FACS following differential adherence.
identified genes as differentially expressed at one or more timepoints, co-regulated genes were identified by using pattern recognition using STEM and grouped into Gene expression profiles. Gene expression profiles were subjected to gene set enrichment analysis with Toppgene and Toppcluster [5][6][7].