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Genetic changes occurring in different stages of pre-cancer lesions reflect causal events initiating and promoting the progression to cancer. Coexisting pre-cancerous lesions including low- and high-grade squamous intraepithelial lesion (LGSIL and HGSIL), and adjacent normal cervical epithelium from six formalin-fixed paraffin-embedded (FFPE) samples were selected. Tissues from these 18 samples were isolated using laser capture microdissection, RNA was extracted and sequenced. RNA-sequencing (RNA-seq) generated 2.4 billion raw reads in 18 samples, of which approximately 50.1% mapped to known and annotated genes in the human genome. There were 40 genes up-regulated and 3 down-regulated (normal to LGSIL) in at least one third of the sample pairs (same direction and FDR p

Genome-wide association (GWA) studies have become a standard approach for discovering and validating genomic polymorphisms putatively associated with phenotypes of interest. Accounting for population structure in GWA studies is critical to attain unbiased parameter measurements and control Type I error. One common approach to accounting for population structure is to include several principal components derived from the entire autosomal dataset, which reflects population structure signal. However, knowing which components to include is subjective and generally not conclusive. We examined how phylogenetic signal from mitochondrial DNA (mtDNA) and chromosome Y (chr:Y) markers is concordant with principal component data based on autosomal markers to determine whether mtDNA and chr:Y phylogenetic data can help guide principal component selection. Using HAPMAP and other original data from individuals of multiple ancestries, we examined the relationships of mtDNA and chr:Y phylogenetic signal with the autosomal PCA using best subset logistic regression. We show that while the two approaches agree at times, this is independent of the component order and not completely represented in the Eigen values. Additionally, we use simulations to demonstrate that our approach leads to a slightly reduced Type I error rate compared to the standard approach. This approach provides preliminary evidence to support the theoretical concept that mtDNA and chr:Y data can be informative in locating the PCs that are most associated with evolutionary history of populations that are being studied, although the utility of such information will depend on the specific situation.