Characterization of human transcription factor function and patterns of gene regulation in HepG2 cells.

Transcription factors (TFs) are trans-acting proteins that bind cis-regulatory elements (CREs) in DNA to control gene expression. Here, we analyzed the genomic localization profiles of 529 sequence-specific TFs and 151 cofactors and chromatin regulators in the human cancer cell line HepG2, for a total of 680 broadly termed DNA-associated proteins (DAPs). We used this deep collection to model each TF's impact on gene expression, and identified a cohort of 26 candidate transcriptional repressors. We examine high occupancy target (HOT) sites in the context of three-dimensional genome organization and show biased motif placement in distal-promoter connections involving HOT sites. We also found a substantial number of closed chromatin regions with multiple DAPs bound, and explored their properties, finding that a MAFF/MAFK TF pair correlates with transcriptional repression. Altogether, these analyses provide novel insights into the regulatory logic of the human cell line HepG2 genome and show the usefulness of large genomic analyses for elucidation of individual TF functions.

CINmetrics: an R package for analyzing copy number aberrations as a measure of chromosomal instability.

Genomic instability is an important hallmark of cancer and more recently has been identified in others like neurodegenrative diseases. Chromosomal instability, as a measure of genomic instability, has been used to characterize clinical and biological phenotypes associated with these diseases by measuring structural and numerical chromosomal alterations. There have been multiple chromosomal instability scores developed across many studies in the literature; however, these scores have not been compared because of the lack of a single tool available to calculate and facilitate these various metrics. Here, we provide an R package CINmetrics, that calculates six different chromosomal instability scores and allows direct comparison between them. We also demonstrate how these scores differ by applying CINmetrics to breast cancer data from The Cancer Genome Atlas (TCGA). The package is available on CRAN at https://cran.rproject.org/package=CINmetrics and on GitHub at https://github.com/lasseignelab/CINmetrics.

Three dimensional modeling of biologically relevant fluid shear stress in human renal tubule cells mimics in vivo transcriptional profiles.

The kidney proximal tubule is the primary site for solute reabsorption, secretion and where kidney diseases can originate, including drug-induced toxicity. Two-dimensional cell culture systems of the human proximal tubule cells (hPTCs) are often used to study these processes. However, these systems fail to model the interplay between filtrate flow, fluid shear stress (FSS), and functionality essential for understanding renal diseases and drug toxicity. The impact of FSS exposure on gene expression and effects of FSS at differing rates on gene expression in hPTCs has not been thoroughly investigated. Here, we performed RNA-sequencing of human RPTEC/TERT1 cells in a microfluidic chip-based 3D model to determine transcriptomic changes. We measured transcriptional changes following treatment of cells in this device at three different fluidic shear stress. We observed that FSS changes the expression of PTC-specific genes and impacted genes previously associated with renal diseases in genome-wide association studies (GWAS). At a physiological FSS level, we observed cell morphology, enhanced polarization, presence of cilia, and transport functions using albumin reabsorption via endocytosis and efflux transport. Here, we present a dynamic view of hPTCs response to FSS with increasing fluidic shear stress conditions and provide insight into hPTCs cellular function under biologically relevant conditions.

Identification of Gene Variants Associated with Melanocyte Stem Cell Differentiation in Mice Predisposed for Hair Graying.

Age-related hair graying is caused by malfunction in the regenerative potential of the adult pigmentation system. The retention of hair color over the life of an organism is dependent on the ability of the melanocyte stem cells and their progeny to produce pigment each time a new hair grows. Age-related hair graying is variable in association with genetic background suggesting that quantitative trait loci influencing this trait can be identified. Identification of these quantitative trait loci may lead to the discovery of novel and interesting genes involved in stem cell biology and/or melanogenesis. With this in mind we developed previously a sensitized, mouse modifier screen and discovered that the DBA/1J background is particularly resistant to melanocyte stem cell differentiation in comparison to the C57BL/6J background. Melanocyte stem cell differentiation generally precedes hair graying and is observed in melanocyte stem cells with age. Using quantitative trait loci analysis, we have now identified three quantitative trait loci on mouse chromosomes 7, 13, and X that are associated with DBA/1J-mediated variability in melanocyte stem cell differentiation. Taking advantage of publicly-available mouse sequence and variant data, in silico protein prediction programs, and whole genome gene expression results we describe a short list of potential candidate genes that we anticipate to be involved in melanocyte stem cell biology in mice.