2.4. RNA-Seq, Ingenuity Pathway Analyses and Statistical Analyses

RNA libraries were prepared from the purified RNA samples for RNA-Sequencing using commercially available kits (Illumina, TruSeq® RNA Sample Prep Kit, San Diego, CA, USA). Samples (n = 6 offspring per treatment group/sex for a total of 36 samples; only one pup per litter was used for theses studies) were sequenced on the Illumina HiSeq2500 (San Diego, CA, USA) using HiSeq single read 50-cycle flow cells (Genome Technology Center (GTC), NYU Langone Medical Center). Male and female samples were sequenced with Illumina Hiseq 2500 platform in two separated runs and Illimuna bcl2fastq Conversion Software(version 1.8.4) was used to demultiplex the samples. Before processing data analysis, Fastqc (version 0.10.1, Basespace Labs Apps, Illumina, San Diego, CA, USA) was used to check the reads quality and PCR duplication. Reads were mapped to mm9 mouse transcriptome using Bowtie1 (version 0.12.9, maintained by John Hopkins University, Baltimore, MD, USA) with two mismatches allowed. The PCR duplicates were removed using Samtools (version 0.1.19, distributed under the Massachusetts Institute of Technology, Cambridge, MA, USA). Htseq (version 0.6.1.p.1,Python Software Foundation, Wilmington, DE, USA) was used to find the read counts for annotated genomic features. Principal Component Analysis was performed to detect variations among samples, in which one sample per sex group was detected as outlier and excluded from subsequent analysis. For the differential gene statistical analysis, DESeq2 R/Bioconductor package in the R statistical programming environment was used. Since male and female samples are prepared and sequenced in two different batches and batched effect is detected, we used one-way ANOVA to analyze the data separately instead of combining male and female data for two-way ANOVA analysis. In the analysis, the low counts were filtered with the Deseq2 algorithm if combined reads counts of retained samples for each gene was less than 5 per million. The Benjamini-Hochberg procedure (used R function p adjust) for multiple testing, which controls false discovery rate (FDR), was used to determine adjusted p-values. For each treatment group/sex dataset, which included (1) female offspring exposed to e-cigarettes with nicotine; (2) female offspring exposed to e-cigarettes without nicotine; (3) male offspring exposed to e-cigarettes with nicotine; and (4) male offspring exposed to e-cigarettes without nicotine, fold changes of genes with an adjusted p-value of <0.01 (when compared to air control values) were imported into IPA software to examine biological effects and disease pathway outcomes associated with the gene expression data. The RNA-Seq data have been deposited in the Gene Expression Omnibus, and are accessible through series accession number ({"type":"entrez-geo","attrs":{"text":"GSE75858","term_id":"75858"}}GSE75858).