Clustering gene expression time series data using an infinite Gaussian process mixture model.

Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP), which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.

Incomplete MyoD-induced transdifferentiation is associated with chromatin remodeling deficiencies.

Our current understanding of cellular transdifferentiation systems is limited. It is oftentimes unknown, at a genome-wide scale, how much transdifferentiated cells differ quantitatively from both the starting cells and the target cells. Focusing on transdifferentiation of primary human skin fibroblasts by forced expression of myogenic transcription factor MyoD, we performed quantitative analyses of gene expression and chromatin accessibility profiles of transdifferentiated cells compared to fibroblasts and myoblasts. In this system, we find that while many of the early muscle marker genes are reprogrammed, global gene expression and accessibility changes are still incomplete when compared to myoblasts. In addition, we find evidence of epigenetic memory in the transdifferentiated cells, with reminiscent features of fibroblasts being visible both in chromatin accessibility and gene expression. Quantitative analyses revealed a continuum of changes in chromatin accessibility induced by MyoD, and a strong correlation between chromatin-remodeling deficiencies and incomplete gene expression reprogramming. Classification analyses identified genetic and epigenetic features that distinguish reprogrammed from non-reprogrammed sites, and suggested ways to potentially improve transdifferentiation efficiency. Our approach for combining gene expression, DNA accessibility, and protein-DNA binding data to quantify and characterize the efficiency of cellular transdifferentiation on a genome-wide scale can be applied to any transdifferentiation system.

Expression level is a key determinant of E2F1-mediated cell fate.

The Rb/E2F network has a critical role in regulating cell cycle progression and cell fate decisions. It is dysfunctional in virtually all human cancers, because of genetic lesions that cause overexpression of activators, inactivation of repressors, or both. Paradoxically, the downstream target of this network, E2F1, is rarely strongly overexpressed in cancer. E2F1 can induce both proliferation and apoptosis but the factors governing these critical cell fate decisions remain unclear. Previous studies have focused on qualitative mechanisms such as differential cofactors, posttranslational modification or state of other signaling pathways as modifiers of the cell fate decisions downstream of E2F1 activation. In contrast, the importance of the expression levels of E2F1 itself in dictating the downstream phenotypes has not been rigorously studied, partly due to the limited resolution of traditional population-level measurements. Here, through single-cell quantitative analysis, we demonstrate that E2F1 expression levels have a critical role in determining the fate of individual cells. Low levels of exogenous E2F1 promote proliferation, moderate levels induce G1, G2 and mitotic cell cycle arrest, and very high levels promote apoptosis. These multiple anti-proliferative mechanisms result in a strong selection pressure leading to rapid elimination of E2F1-overexpressing cells from the population. RNA-sequencing and RT-PCR revealed that low levels of E2F1 are sufficient to induce numerous cell cycle-promoting genes, intermediate levels induce growth arrest genes (i.e., p18, p19 and p27), whereas higher levels are necessary to induce key apoptotic E2F1 targets APAF1, PUMA, HRK and BIM. Finally, treatment of a lung cancer cell line with a proteasome inhibitor, MLN2238, resulted in an E2F1-dependent mitotic arrest and apoptosis, confirming the role of endogenous E2F1 levels in these phenotypes. The strong anti-proliferative activity of moderately overexpressed E2F1 in multiple cancer types suggests that targeting E2F1 for upregulation may represent an attractive therapeutic strategy in cancer.

HDAC inhibitors cause site-specific chromatin remodeling at PU.1-bound enhancers in K562 cells.

BACKGROUND: Small molecule inhibitors of histone deacetylases (HDACi) hold promise as anticancer agents for particular malignancies. However, clinical use is often confounded by toxicity, perhaps due to indiscriminate hyperacetylation of cellular proteins. Therefore, elucidating the mechanisms by which HDACi trigger differentiation, cell cycle arrest, or apoptosis of cancer cells could inform development of more targeted therapies. We used the myelogenous leukemia line K562 as a model of HDACi-induced differentiation to investigate chromatin accessibility (DNase-seq) and expression (RNA-seq) changes associated with this process. RESULTS: We identified several thousand specific regulatory elements [~10 % of total DNase I-hypersensitive (DHS) sites] that become significantly more or less accessible with sodium butyrate or suberanilohydroxamic acid treatment. Most of the differential DHS sites display hallmarks of enhancers, including being enriched for non-promoter regions, associating with nearby gene expression changes, and increasing luciferase reporter expression in K562 cells. Differential DHS sites were enriched for key hematopoietic lineage transcription factor motifs, including SPI1 (PU.1), a known pioneer factor. We found PU.1 increases binding at opened DHS sites with HDACi treatment by ChIP-seq, but PU.1 knockdown by shRNA fails to block the chromatin accessibility and expression changes. A machine-learning approach indicates H3K27me3 initially marks PU.1-bound sites that open with HDACi treatment, suggesting these sites are epigenetically poised. CONCLUSIONS: We find HDACi treatment of K562 cells results in site-specific chromatin remodeling at epigenetically poised regulatory elements. PU.1 shows evidence of a pioneer role in this process by marking poised enhancers but is not required for transcriptional activation.