Nonlinear DNA methylation trajectories in aging male mice.

Although DNA methylation data yields highly accurate age predictors, little is known about the dynamics of this quintessential epigenomic biomarker during lifespan. To narrow the gap, we investigate the methylation trajectories of male mouse colon at five different time points of aging. Our study indicates the existence of sudden hypermethylation events at specific stages of life. Precisely, we identify two epigenomic switches during early-to-midlife (3-9 months) and mid-to-late-life (15-24 months) transitions, separating the rodents' life into three stages. These nonlinear methylation dynamics predominantly affect genes associated with the nervous system and enrich in bivalently marked chromatin regions. Based on groups of nonlinearly modified loci, we construct a clock-like classifier STageR (STage of aging estimatoR) that accurately predicts murine epigenetic stage. We demonstrate the universality of our clock in an independent mouse cohort and with publicly available datasets.

Systematic computational hunting for small RNAs derived from ncRNAs during dengue virus infection in endothelial HMEC-1 cells.

In recent years, a population of small RNA fragments derived from non-coding RNAs (sfd-RNAs) has gained significant interest due to its functional and structural resemblance to miRNAs, adding another level of complexity to our comprehension of small-RNA-mediated gene regulation. Despite this, scientists need more tools to test the differential expression of sfd-RNAs since the current methods to detect miRNAs may not be directly applied to them. The primary reasons are the lack of accurate small RNA and ncRNA annotation, the multi-mapping read (MMR) placement, and the multicopy nature of ncRNAs in the human genome. To solve these issues, a methodology that allows the detection of differentially expressed sfd-RNAs, including canonical miRNAs, by using an integrated copy-number-corrected ncRNA annotation was implemented. This approach was coupled with sixteen different computational strategies composed of combinations of four aligners and four normalization methods to provide a rank-order of prediction for each differentially expressed sfd-RNA. By systematically addressing the three main problems, we could detect differentially expressed miRNAs and sfd-RNAs in dengue virus-infected human dermal microvascular endothelial cells. Although more biological evaluations are required, two molecular targets of the hsa-mir-103a and hsa-mir-494 (CDK5 and PI3/AKT) appear relevant for dengue virus (DENV) infections. Here, we performed a comprehensive annotation and differential expression analysis, which can be applied in other studies addressing the role of small fragment RNA populations derived from ncRNAs in virus infection.

Bashing irreproducibility with shournal.

Arguably, the most important tool for many computational scientists is the Linux shell. Processing steps carried out there are critical for a large number of analyses. While the manual documentation of the work is time-consuming and error-prone, existing tools do not integrate well into the shell or suffer from a large overhead. Here, we present shournal, which integrates tightly into the shell and automatically records all shell commands along with their associated file events. Thus, for all files, it can later be told how they were generated and processed. Additionally, it allows the creation of detailed reports for whole project folders. shournal retrieves its data directly from the Linux kernel and allows the monitoring of whole process trees with low overhead.

Age-Associated Changes in Endothelial Transcriptome and Epigenetic Landscapes Correlate With Elevated Risk of Cerebral Microbleeds.

Background Stroke is a leading global cause of human death and disability, with advanced aging associated with elevated incidences of stroke. Despite high mortality and morbidity of stroke, the mechanisms leading to blood-brain barrier dysfunction and development of stroke with age are poorly understood. In the vasculature of brain, endothelial cells (ECs) constitute the core component of the blood-brain barrier and provide a physical barrier composed of tight junctions, adherens junctions, and basement membrane. Methods and Results We show, in mice, the incidents of intracerebral bleeding increases with age. After isolating an enriched population of cerebral ECs from murine brains at 2, 6, 12, 18, and 24 months, we studied age-associated changes in gene expression. The study reveals age-dependent dysregulation of 1388 genes, including many involved in the maintenance of the blood-brain barrier and vascular integrity. We also investigated age-dependent changes on the levels of CpG methylation and accessible chromatin in cerebral ECs. Our study reveals correlations between age-dependent changes in chromatin structure and gene expression, whereas the dynamics of DNA methylation changes are different. Conclusions We find significant age-dependent downregulation of the Aplnr gene along with age-dependent reduction in chromatin accessibility of promoter region of the Aplnr gene in cerebral ECs. Aplnr is associated with positive regulation of vasodilation and is implicated in vascular health. Altogether, our data suggest a potential role of the apelinergic axis involving the ligand apelin and its receptor to be critical in maintenance of the blood-brain barrier and vascular integrity.

Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision.

The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed using computational tools. Numerous such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools detected more than 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were validated using three orthogonal methods. Generally, tool-specific precision is high and similar (median of 98.8%, 96.3% and 95.5% for qPCR, RNase R and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant differentiators. Of note, precision values are lower when evaluating low-abundance circRNAs. We also show that the tools can be used complementarily to increase detection sensitivity. Finally, we offer recommendations for future circRNA detection and validation.

Multi-omics analysis identifies RFX7 targets involved in tumor suppression and neuronal processes.

Recurrently mutated in lymphoid neoplasms, the transcription factor RFX7 is emerging as a tumor suppressor. Previous reports suggested that RFX7 may also have a role in neurological and metabolic disorders. We recently reported that RFX7 responds to p53 signaling and cellular stress. Furthermore, we found RFX7 target genes to be dysregulated in numerous cancer types also beyond the hematological system. However, our understanding of RFX7's target gene network and its role in health and disease remains limited. Here, we generated RFX7 knock-out cells and employed a multi-omics approach integrating transcriptome, cistrome, and proteome data to obtain a more comprehensive picture of RFX7 targets. We identify novel target genes linked to RFX7's tumor suppressor function and underscoring its potential role in neurological disorders. Importantly, our data reveal RFX7 as a mechanistic link that enables the activation of these genes in response to p53 signaling.

Leveraging quantum computing for dynamic analyses of logical networks in systems biology.

The dynamics of cellular mechanisms can be investigated through the analysis of networks. One of the simplest but most popular modeling strategies involves logic-based models. However, these models still face exponential growth in simulation complexity compared with a linear increase in nodes. We transfer this modeling approach to quantum computing and use the upcoming technique in the field to simulate the resulting networks. Leveraging logic modeling in quantum computing has many benefits, including complexity reduction and quantum algorithms for systems biology tasks. To showcase the applicability of our approach to systems biology tasks, we implemented a model of mammalian cortical development. Here, we applied a quantum algorithm to estimate the tendency of the model to reach particular stable conditions and further revert dynamics. Results from two actual quantum processing units and a noisy simulator are presented, and current technical challenges are discussed.

The landscape of human p53-regulated long non-coding RNAs reveals critical host gene co-regulation.

The role of long non-coding RNAs (lncRNAs) in p53-mediated tumor suppression has become increasingly appreciated in the past decade. Thus, the identification of p53-regulated lncRNAs can be a promising starting point to select and prioritize lncRNAs for functional analyses. By integrating transcriptome and transcription factor-binding data, we identified 379 lncRNAs that are recurrently differentially regulated by p53. Dissecting the mechanisms by which p53 regulates many of them, we identified sets of lncRNAs regulated either directly by p53 or indirectly through the p53-RFX7 and p53-p21-DREAM/RB:E2F pathways. Importantly, we identified multiple p53-responsive lncRNAs that are co-regulated with their protein-coding host genes, revealing an important mechanism by which p53 may regulate lncRNAs. Further analysis of transcriptome data and clinical data from cancer patients showed that recurrently p53-regulated lncRNAs are associated with patient survival. Together, the integrative analysis of the landscape of p53-regulated lncRNAs provides a powerful resource facilitating the identification of lncRNA function and displays the mechanisms of p53-dependent regulation that could be exploited for developing anticancer approaches.

Focal structural variants revealed by whole genome sequencing disrupt the histone demethylase KDM4C in B-cell lymphomas.

Histone methylation-modifiers, such as EZH2 and KMT2D, are recurrently altered in B-cell lymphomas. To comprehensively describe the landscape of alterations affecting genes encoding histone methylation-modifiers in lymphomagenesis we investigated whole genome and transcriptome data of 186 mature B-cell lymphomas sequenced in the ICGC MMML-Seq project. Besides confirming common alterations of KMT2D (47% of cases), EZH2 (17%), SETD1B (5%), PRDM9 (4%), KMT2C (4%), and SETD2 (4%), also identified by prior exome or RNA-sequencing studies, we here found recurrent alterations to KDM4C in chromosome 9p24, encoding a histone demethylase. Focal structural variation was the main mechanism of KDM4C alterations, and was independent from 9p24 amplification. We also identified KDM4C alterations in lymphoma cell lines including a focal homozygous deletion in a classical Hodgkin lymphoma cell line. By integrating RNA-sequencing and genome sequencing data we predict that KDM4C structural variants result in loss-offunction. By functional reconstitution studies in cell lines, we provide evidence that KDM4C can act as a tumor suppressor. Thus, we show that identification of structural variants in whole genome sequencing data adds to the comprehensive description of the mutational landscape of lymphomas and, moreover, establish KDM4C as a putative tumor suppressive gene recurrently altered in subsets of B-cell derived lymphomas.

Taz protects hematopoietic stem cells from an aging-dependent decrease in PU.1 activity.

Specific functions of the immune system are essential to protect us from infections caused by pathogens such as viruses and bacteria. However, as we age, the immune system shows a functional decline that can be attributed in large part to age-associated defects in hematopoietic stem cells (HSCs)-the cells at the apex of the immune cell hierarchy. Here, we find that the Hippo pathway coactivator TAZ is potently induced in old HSCs and protects these cells from functional decline. We identify Clca3a1 as a TAZ-induced gene that allows us to trace TAZ activity in vivo. Using CLCA3A1 as a marker, we can isolate "young-like" HSCs from old mice. Mechanistically, Taz acts as coactivator of PU.1 and to some extent counteracts the gradual loss of PU.1 expression during HSC aging. Our work thus uncovers an essential role for Taz in a previously undescribed fail-safe mechanism in aging HSCs.

Synthesizing genome regulation data with vote-counting.

The increasing availability of high-throughput datasets allows amalgamating research information across a large body of genome regulation studies. Given the recent success of meta-analyses on transcriptional regulators, epigenetic marks, and enhancer:gene associations, we expect that such surveys will continue to provide novel and reproducible insights. However, meta-analyses are severely hampered by the diversity of available data, concurring protocols, an eclectic amount of bioinformatics tools, and myriads of conceivable parameter combinations. Such factors can easily bar life scientists from synthesizing omics data and substantially curb their interpretability. Despite statistical challenges of the method, we would like to emphasize the advantages of joining data from different sources through vote-counting and showcase examples that achieve a simple but highly intuitive data integration.

LINC00892 Is an lncRNA Induced by T Cell Activation and Expressed by Follicular Lymphoma-Resident T Helper Cells.

Successful immunotherapy in both solid tumors and in hematological malignancies relies on the ability of T lymphocytes to infiltrate the cancer tissue and mount an immune response against the tumor. Biomarkers able to discern the amount and the types of T lymphocytes infiltrating a given tumor therefore have high diagnostic and prognostic value. Given that lncRNAs are known to have a highly cell-type-specific expression pattern, we searched for lncRNAs specifically expressed by activated T cells and at the same time in a kind of lymphoma, follicular lymphoma, where the microenvironment is known to play a critical role in the regulation of antitumor immunity. We focused on a non-coding transcript, annotated as LINC00892, which reaches extremely high expression levels following cell activation in Jurkat cells. Interestingly LINC00892 has an expression pattern resembling that of genes involved in T cell memory. Accordingly, LINC00892 is mostly expressed by the effector memory and helper CD4+ T cell sub-types but not by naïve T cells. In situ analyses of LINC00892 expression in normal lymph nodes and in follicular lymphoma biopsies show that its expression is limited to CD4+ PD1hi T cells, with a subcellular localization within the germinal center matching that of follicular helper T cells. Our analysis therefore suggests that the previously uncharacterized lncRNA LINC00892 could be a useful biomarker for the detection of CD4+ memory T cells in both normal and tumor tissues.

TargetGeneReg 2.0: a comprehensive web-atlas for p53, p63, and cell cycle-dependent gene regulation.

In recent years, our web-atlas at www.TargetGeneReg.org has enabled many researchers to uncover new biological insights and to identify novel regulatory mechanisms that affect p53 and the cell cycle - signaling pathways that are frequently dysregulated in diseases like cancer. Here, we provide a substantial upgrade of the database that comprises an extension to include non-coding genes and the transcription factors ΔNp63 and RFX7. TargetGeneReg 2.0 combines gene expression profiling and transcription factor DNA binding data to determine, for each gene, the response to p53, ΔNp63, and cell cycle signaling. It can be used to dissect common, cell type and treatment-specific effects, identify the most promising candidates, and validate findings. We demonstrate the increased power and more intuitive layout of the resource using realistic examples.

Multivariable Modeling of Biomarker Data From the Phase I Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

OBJECTIVE: To determine the optimal combination of imaging and biochemical biomarkers for use in the prediction of knee osteoarthritis (OA) progression. METHODS: The present study was a nested case-control trial from the Foundation of the National Institutes of Health OA Biomarkers Consortium that assessed study participants with a Kellgren/Lawrence grade of 1-3 who had complete biomarker data available (n = 539 to 550). Cases were participants' knees that had radiographic and pain progression between 24 and 48 months compared to baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) that had a P value of <0.10 in univariate analysis were selected, including quantitative cartilage thickness and volume on magnetic resonance imaging (MRI), semiquantitative MRI markers, bone shape and area, quantitative meniscal volume, radiographic progression (trabecular bone texture [TBT]), and serum and/or urine biochemical markers. Multivariable logistic regression models were built using 3 different stepwise selection methods (complex models versus parsimonious models). RESULTS: Among baseline biomarkers, the number of locations affected by osteophytes (semiquantitative), quantitative central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and semiquantitative Hoffa-synovitis predicted OA progression in most models (C statistic 0.641-0.671). In most models, 24-month changes in semiquantitative MRI markers (effusion-synovitis, meniscal morphologic changes, and cartilage damage), quantitative central medial femoral cartilage thickness, quantitative medial tibial cartilage volume, quantitative lateral patellofemoral bone area, horizontal TBT (intercept term), and urine N-telopeptide of type I collagen predicted OA progression (C statistic 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, which had a higher C statistic of 0.716-0.832. CONCLUSION: The present study highlights the combination of biomarkers with potential prognostic utility in OA disease-modifying trials. Properly qualified, these biomarkers could be used to enrich future trials with participants likely to experience progression of knee OA.

p53-mediated AKT and mTOR inhibition requires RFX7 and DDIT4 and depends on nutrient abundance.

In recent years the tumor suppressor p53 has been increasingly recognized as a potent regulator of the cell metabolism and for its ability to inhibit the critical pro-survival kinases AKT and mTOR. The mechanisms through which p53 controls AKT and mTOR, however, are largely unclear. Here, we demonstrate that p53 activates the metabolic regulator DDIT4 indirectly through the regulatory factor X 7 (RFX7). We provide evidence that DDIT4 is required for p53 to inhibit mTOR complex 2 (mTORC2)-dependent AKT activation. Most strikingly, we also find that the DDIT4 regulator RFX7 is required for p53-mediated inhibition of mTORC1 and AKT. Our results suggest that AMPK activation plays no role and p53-mediated AKT inhibition is not critical for p53-mediated mTORC1 inhibition. Moreover, using recently developed physiological cell culture media we uncover that basal p53 and RFX7 activity can play a critical role in restricting mTORC1 activity under physiological nutrient conditions, and we propose a nutrient-dependent model for p53-RFX7-mediated mTORC1 inhibition. These results establish RFX7 and its downstream target DDIT4 as essential effectors in metabolic control elicited by p53.

Locus-specific expression analysis of transposable elements.

Transposable elements (TEs) have been associated with many, frequently detrimental, biological roles. Consequently, the regulations of TEs, e.g. via DNA-methylation and histone modifications, are considered critical for maintaining genomic integrity and other functions. Still, the high-throughput study of TEs is usually limited to the family or consensus-sequence level because of alignment problems prompted by high-sequence similarities and short read lengths. To entirely comprehend the effects and reasons of TE expression, however, it is necessary to assess the TE expression at the level of individual instances. Our simulation study demonstrates that sequence similarities and short read lengths do not rule out the accurate assessment of (differential) expression of TEs at the instance-level. With only slight modifications to existing methods, TE expression analysis works surprisingly well for conventional paired-end sequencing data. We find that SalmonTE and Telescope can accurately tally a considerable amount of TE instances, allowing for differential expression recovery in model and non-model organisms.

Transcription factor RFX7 governs a tumor suppressor network in response to p53 and stress.

Despite its prominence, the mechanisms through which the tumor suppressor p53 regulates most genes remain unclear. Recently, the regulatory factor X 7 (RFX7) emerged as a suppressor of lymphoid neoplasms, but its regulation and target genes mediating tumor suppression remain unknown. Here, we identify a novel p53-RFX7 signaling axis. Integrative analysis of the RFX7 DNA binding landscape and the RFX7-regulated transcriptome in three distinct cell systems reveals that RFX7 directly controls multiple established tumor suppressors, including PDCD4, PIK3IP1, MXD4, and PNRC1, across cell types and is the missing link for their activation in response to p53 and stress. RFX7 target gene expression correlates with cell differentiation and better prognosis in numerous cancer types. Interestingly, we find that RFX7 sensitizes cells to Doxorubicin by promoting apoptosis. Together, our work establishes RFX7's role as a ubiquitous regulator of cell growth and fate determination and a key node in the p53 transcriptional program.