Characterization of basal and estrogen-regulated antisense transcription in breast cancer cells: Role in regulating sense transcription

Estrogen-responsive breast cancer cells exhibit both basal and estrogen-regulated transcriptional programs, which lead to the transcription of many different transcription units (i.e., genes), including those that produce coding and non-coding sense (e.g., mRNA, lncRNA) and antisense (i.e., asRNA) transcripts. We have previously characterized the global basal and estrogen-regulated transcriptomes in estrogen receptor alpha (ERα)-positive MCF-7 breast cancer cells. Herein, we have mined genomic data to define three classes of antisense transcription in MCF-7 cells based on where their antisense transcription termination sites reside relative to their cognate sense mRNA and lncRNA genes. These three classes differ in their response to estrogen treatment, the enrichment of a number of genomic features associated with active promoters (H3K4me3, RNA polymerase II, open chromatin architecture), and the biological functions of their cognate sense genes as analyzed by DAVID gene ontology. We further characterized two estrogen-regulated antisense transcripts arising from the MYC gene in MCF-7 cells, showing that these antisense transcripts are 5'-capped, 3'-polyadenylated, and localized to different compartments of the cell. Together, our analyses have revealed distinct classes of antisense transcription correlated to different biological processes and response to estrogen stimulation, uncovering another layer of hormone-regulated gene regulation.

Distinct Roles for BET Family Members in Estrogen Receptor α Enhancer Function and Gene Regulation in Breast Cancer Cells

The bromodomain family member proteins (BRD; BET proteins) are key coregulators for estrogen receptor alpha (ERα)-mediated transcriptional enhancers. The use of BRD-selective inhibitors has gained much attention as a potential treatment for various solid tumors, including ER-positive breast cancers. However, the roles of individual BET family members have largely remained unexplored. Here, we describe the role of BRDs in estrogen (E2)-dependent gene expression in ERα-positive breast cancer cells. We observed that chemical inhibition of BET family proteins with JQ1 impairs E2-regulated gene expression and growth in breast cancer cells. In addition, RNAi-mediated depletion of each BET family member (BRDs 2, 3, and 4) revealed partially redundant roles at ERα enhancers and for target gene transcription. Furthermore, we found a unique role of BRD3 as a molecular sensor of total BET family protein levels and activity through compensatory control of its own protein levels. Finally, we observed that BRD3 is recruited to a subset of ERα-binding sites (ERBS) that are enriched for active enhancer features, located in clusters of ERBSs likely functioning as "super enhancers," and associated with highly E2-responsive genes. Collectively, our results illustrate a critical and specific role for BET family members in ERα-dependent gene transcription. IMPLICATIONS: BRD3 is recruited to and controls the activity of a subset ERα transcriptional enhancers, providing a therapeutic opportunity to target BRD3 with BET inhibitors in ERα-positive breast cancers.

Family CHAOS is associated with glycaemic control in children and adolescents with type 1 diabetes mellitus

BACKGROUND

Despite advances in the medical management of type 1 diabetes mellitus (T1DM), for many, glycaemic control remains substandard. Other factors are clearly important in determining success, or lack thereof, with diabetes management. With this in mind, we have investigated whether family CHAOS may provide a novel tool to identify when environmental confusion could impact on diabetes management and subsequent glycaemic control.

METHODS

A case-control study of children and adolescents with established T1DM and age-/sex-matched controls was conducted. Demographic information, both maternal and paternal CHAOS scores, and HbA1c were collected. Statistical analysis was undertaken to explore associations between T1DM and CHAOS and between CHAOS and HbA1c.

RESULTS

Data on 65 children with T1DM and 60 age-/sex-matched controls were obtained. There was no evidence of group differences for maternal CHAOS (p = 0.227), but paternal CHAOS scores were higher for the T1DM group (p = 0.041). Greater maternal and paternal CHAOS scores were both associated with higher HbA1c (p ≤ 0.027). The maternal association remained after controlling for diabetes duration, SMBG frequency, and insulin therapy.

CONCLUSION

In children with T1DM, there appears to be a negative association between increased environmental confusion, as rated by CHAOS, and glycaemic control. In addition, when compared to controls, fathers of children and adolescents with T1DM appear to experience CHAOS differently to mothers. These findings contribute to the growing body of literature exploring psychosocial factors in T1DM. Continuing efforts are required to fully understand how the family and psychosocial environment interact with diabetes to impact on long-term health outcomes.

Intuitive eating is associated with glycaemic control in adolescents with type I diabetes mellitus

BACKGROUND

While there have been considerable advances in the medical management of type 1 diabetes mellitus (T1DM), for many, glycaemic control remains substandard. Nutrition and eating behaviour are important additional factors to consider with regards to T1DM management and outcomes. Intuitive eating is one such factor, and has not previously been investigated in T1DM. With this in mind, we undertook a study examining the relationship between intuitive eating and glycaemic control in adolescents with T1DM.

METHODS

A case-control study of adolescents with established T1DM, and age/sex matched controls was conducted. Demographic information, the Intuitive Eating Scale (IES), and HbA1c were collected. Statistical analysis was undertaken to explore associations between the IES and HbA1c as a marker of glycaemic control.

RESULTS

Data on 38 adolescents with T1DM, and 39 age/sex matched controls were obtained. Those with T1DM had significantly lower (by 0.5 SD) IES scores compared to controls (p = 0.009). Higher values of both total IES and the Eating for physical rather than emotional reasons subscale were associated with lower HbA1c: HbA1c 22% lower/whole unit increase in total IES mean score, HbA1c 11% lower/whole unit increase in Eating for physical rather than emotional reasons mean score, p = 0.017 and p = 0.009 respectively.

CONCLUSION

In adolescents with T1DM, there appears to be a strong association between intuitive eating, in particular the effect of emotion on eating, and glycaemic control. In addition, those with T1DM have lower scores for their intuitive eating behaviour compared to controls. Emotional eating could be a future target for screening and potentially intervening in those with T1DM, as part of a wider treatment package to improve glycaemic control. Continuing efforts are needed to fully understand the important dynamics of diabetes, adolescence, diet, emotion, and how these factors affect long term outcomes in those with T1DM.

groHMM: a computational tool for identifying unannotated and cell type-specific transcription units from global run-on sequencing data

Background

Global run-on coupled with deep sequencing (GRO-seq) provides extensive information on the location and function of coding and non-coding transcripts, including primary microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and enhancer RNAs (eRNAs), as well as yet undiscovered classes of transcripts. However, few computational tools tailored toward this new type of sequencing data are available, limiting the applicability of GRO-seq data for identifying novel transcription units.

Results

Here, we present groHMM, a computational tool in R, which defines the boundaries of transcription units de novo using a two state hidden-Markov model (HMM). A systematic comparison of the performance between groHMM and two existing peak-calling methods tuned to identify broad regions (SICER and HOMER) favorably supports our approach on existing GRO-seq data from MCF-7 breast cancer cells. To demonstrate the broader utility of our approach, we have used groHMM to annotate a diverse array of transcription units (i.e., primary transcripts) from four GRO-seq data sets derived from cells representing a variety of different human tissue types, including non-transformed cells (cardiomyocytes and lung fibroblasts) and transformed cells (LNCaP and MCF-7 cancer cells), as well as non-mammalian cells (from flies and worms). As an example of the utility of groHMM and its application to questions about the transcriptome, we show how groHMM can be used to analyze cell type-specific enhancers as defined by newly annotated enhancer transcripts.

Conclusions

Our results show that groHMM can reveal new insights into cell type-specific transcription by identifying novel transcription units, and serve as a complete and useful tool for evaluating functional genomic elements in cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0656-3) contains supplementary material, which is available to authorized users.

Linking the aryl hydrocarbon receptor with altered DNA methylation patterns and developmentally induced aberrant antiviral CD8+ T cell responses

Successfully fighting infection requires a properly tuned immune system. Recent epidemiological studies link exposure to pollutants that bind the aryl hydrocarbon receptor (AHR) during development with poorer immune responses later in life. Yet, how developmental triggering of AHR durably alters immune cell function remains unknown. Using a mouse model, we show that developmental activation of AHR leads to long-lasting reduction in the response of CD8(+) T cells during influenza virus infection, cells critical for resolving primary infection. Combining genome-wide approaches, we demonstrate that developmental activation alters DNA methylation and gene expression patterns in isolated CD8(+) T cells prior to and during infection. Altered transcriptional profiles in CD8(+) T cells from developmentally exposed mice reflect changes in pathways involved in proliferation and immunoregulation, with an overall pattern that bears hallmarks of T cell exhaustion. Developmental exposure also changed DNA methylation across the genome, but differences were most pronounced following infection, where we observed inverse correlation between promoter methylation and gene expression. This points to altered regulation of DNA methylation as one mechanism by which AHR causes durable changes in T cell function. Discovering that distinct gene sets and pathways were differentially changed in developmentally exposed mice prior to and after infection further reveals that the process of CD8(+) T cell activation is rendered fundamentally different by early life AHR signaling. These findings reveal a novel role for AHR in the developing immune system: regulating DNA methylation and gene expression as T cells respond to infection later in life.

Dynamic reorganization of the AC16 cardiomyocyte transcriptome in response to TNFα signaling revealed by integrated genomic analyses

BACKGROUND

Defining cell type-specific transcriptomes in mammals can be challenging, especially for unannotated regions of the genome. We have developed an analytical pipeline called groHMM for annotating primary transcripts using global nuclear run-on sequencing (GRO-seq) data. Herein, we use this pipeline to characterize the transcriptome of an immortalized adult human ventricular cardiomyocyte cell line (AC16) in response to signaling by tumor necrosis factor alpha (TNFα), which is controlled in part by NF-κB, a key transcriptional regulator of inflammation. A unique aspect of this work is the use of the RNA polymerase II (Pol II) inhibitor α-amanitin, which we used to define a set of RNA polymerase I and III (Pol I and Pol III) transcripts.

RESULTS

Using groHMM, we identified ~30,000 coding and non-coding transcribed regions in AC16 cells, which includes a set of unique Pol I and Pol III primary transcripts. Many of these transcripts have not been annotated previously, including enhancer RNAs originating from NF-κB binding sites. In addition, we observed that AC16 cells rapidly and dynamically reorganize their transcriptomes in response to TNFα stimulation in an NF-κB-dependent manner, switching from a basal state to a proinflammatory state affecting a spectrum of cardiac-associated protein-coding and non-coding genes. Moreover, we observed distinct Pol II dynamics for up- and downregulated genes, with a rapid release of Pol II into productive elongation for TNFα-stimulated genes. As expected, the TNFα-induced changes in the AC16 transcriptome resulted in corresponding changes in cognate mRNA and protein levels in a similar manner, but with delayed kinetics.

CONCLUSIONS

Our studies illustrate how computational genomics can be used to characterize the signal-regulated transcriptome in biologically relevant cell types, providing new information about how the human genome is organized, transcribed and regulated. In addition, they show how α-amanitin can be used to reveal the Pol I and Pol III transcriptome. Furthermore, they shed new light on the regulation of the cardiomyocyte transcriptome in response to a proinflammatory signal and help to clarify the link between inflammation and cardiomyocyte function at the transcriptional level.

Reordering hierarchical tree based on bilateral symmetric distance

BACKGROUND

In microarray data analysis, hierarchical clustering (HC) is often used to group samples or genes according to their gene expression profiles to study their associations. In a typical HC, nested clustering structures can be quickly identified in a tree. The relationship between objects is lost, however, because clusters rather than individual objects are compared. This results in a tree that is hard to interpret.

METHODOLOGY/PRINCIPAL FINDINGS

This study proposes an ordering method, HC-SYM, which minimizes bilateral symmetric distance of two adjacent clusters in a tree so that similar objects in the clusters are located in the cluster boundaries. The performance of HC-SYM was evaluated by both supervised and unsupervised approaches and compared favourably with other ordering methods.

CONCLUSIONS/SIGNIFICANCE

The intuitive relationship between objects and flexibility of the HC-SYM method can be very helpful in the exploratory analysis of not only microarray data but also similar high-dimensional data.

Modulation of lipid biosynthesis contributes to stress resistance and longevity of C. elegans mutants

Many lifespan-modulating genes are involved in either generation of oxidative substrates and end-products, or their detoxification and removal. Among such metabolites, only lipoperoxides have the ability to produce free-radical chain reactions. For this study, fatty-acid profiles were compared across a panel of C. elegans mutants that span a tenfold range of longevities in a uniform genetic background. Two lipid structural properties correlated extremely well with lifespan in these worms: fatty-acid chain length and susceptibility to oxidation both decreased sharply in the longest-lived mutants (affecting the insulinlike-signaling pathway). This suggested a functional model in which longevity benefits from a reduction in lipid peroxidation substrates, offset by a coordinate decline in fatty-acid chain length to maintain membrane fluidity. This model was tested by disrupting the underlying steps in lipid biosynthesis, using RNAi knockdown to deplete transcripts of genes involved in fatty-acid metabolism. These interventions produced effects on longevity that were fully consistent with the functions and abundances of their products. Most knockdowns also produced concordant effects on survival of hydrogen peroxide stress, which can trigger lipoperoxide chain reactions.

An iterative block-shifting approach to retention time alignment that preserves the shape and area of gas chromatography-mass spectrometry peaks

Background

Metabolomics, petroleum and biodiesel chemistry, biomarker discovery, and other fields which rely on high-resolution profiling of complex chemical mixtures generate datasets which contain millions of detector intensity readings, each uniquely addressed along dimensions of time (e.g., retention time of chemicals on a chromatographic column), a spectral value (e.g., mass-to-charge ratio of ions derived from chemicals), and the analytical run number. They also must rely on data preprocessing techniques. In particular, inter-run variance in the retention time of chemical species poses a significant hurdle that must be cleared before feature extraction, data reduction, and knowledge discovery can ensue. Alignment methods, for calibrating retention reportedly (and in our experience) can misalign matching chemicals, falsely align distinct ones, be unduly sensitive to chosen values of input parameters, and result in distortions of peak shape and area.

Results

We present an iterative block-shifting approach for retention-time calibration that detects chromatographic features and qualifies them by retention time, spectrum, and the effect of their inclusion on the quality of alignment itself. Mass chromatograms are aligned pairwise to one selected as a reference. In tests using a 45-run GC-MS experiment, block-shifting reduced the absolute deviation of retention by greater than 30-fold. It compared favourably to COW and XCMS with respect to alignment, and was markedly superior in preservation of peak area.

Conclusion

Iterative block-shifting is an attractive method to align GC-MS mass chromatograms that is also generalizable to other two-dimensional techniques such as HPLC-MS.