Identifying novel regulatory effects for clinically relevant genes through the study of the Greek population.

BACKGROUND: Expression quantitative trait loci (eQTL) studies provide insights into regulatory mechanisms underlying disease risk. Expanding studies of gene regulation to underexplored populations and to medically relevant tissues offers potential to reveal yet unknown regulatory variants and to better understand disease mechanisms. Here, we performed eQTL mapping in subcutaneous (S) and visceral (V) adipose tissue from 106 Greek individuals (Greek Metabolic study, GM) and compared our findings to those from the Genotype-Tissue Expression (GTEx) resource. RESULTS: We identified 1,930 and 1,515 eGenes in S and V respectively, over 13% of which are not observed in GTEx adipose tissue, and that do not arise due to different ancestry. We report additional context-specific regulatory effects in genes of clinical interest (e.g. oncogene ST7) and in genes regulating responses to environmental stimuli (e.g. MIR21, SNX33). We suggest that a fraction of the reported differences across populations is due to environmental effects on gene expression, driving context-specific eQTLs, and suggest that environmental effects can determine the penetrance of disease variants thus shaping disease risk. We report that over half of GM eQTLs colocalize with GWAS SNPs and of these colocalizations 41% are not detected in GTEx. We also highlight the clinical relevance of S adipose tissue by revealing that inflammatory processes are upregulated in individuals with obesity, not only in V, but also in S tissue. CONCLUSIONS: By focusing on an understudied population, our results provide further candidate genes for investigation regarding their role in adipose tissue biology and their contribution to disease risk and pathogenesis.

Robust Bioinformatics Approaches Result in the First Polygenic Risk Score for BMI in Greek Adults.

Quantifying the role of genetics via construction of polygenic risk scores (PRSs) is deemed a resourceful tool to enable and promote effective obesity prevention strategies. The present paper proposes a novel methodology for PRS extraction and presents the first PRS for body mass index (BMI) in a Greek population. A novel pipeline for PRS derivation was used to analyze genetic data from a unified database of three cohorts of Greek adults. The pipeline spans various steps of the process, from iterative dataset splitting to training and test partitions, calculation of summary statistics and PRS extraction, up to PRS aggregation and stabilization, achieving higher evaluation metrics. Using data from 2185 participants, implementation of the pipeline enabled consecutive repetitions in splitting training and testing samples and resulted in a 343-single nucleotide polymorphism PRS yielding an R2 = 0.3241 (beta = 1.011, p-value = 4 × 10-193) for BMI. PRS-included variants displayed a variety of associations with known traits (i.e., blood cell count, gut microbiome, lifestyle parameters). The proposed methodology led to creation of the first-ever PRS for BMI in Greek adults and aims at promoting a facilitating approach to reliable PRS development and integration in healthcare practice.

In Vitro Fermentation of Pleurotus eryngii Mushrooms by Human Fecal Microbiota: Metataxonomic Analysis and Metabolomic Profiling of Fermentation Products.

Edible mushrooms contain biologically active compounds with antioxidant, antimicrobial, immunomodulatory and anticancer properties. The link between their anticancer and immunomodulatory properties with their possible prebiotic activity on gut micro-organisms has been the subject of intense research over the last decade. Lyophilized Pleurotus eryngii (PE) mushrooms, selected due to their strong lactogenic effect and anti-genotoxic, immunomodulatory properties, underwent in vitro static batch fermentation for 24 h by fecal microbiota from eight elderly apparently healthy volunteers (>65 years old). The fermentation-induced changes in fecal microbiota communities were examined using Next Generation Sequencing of the hypervariable regions of the 16S rRNA gene. Primary processing and analysis were conducted using the Ion Reporter Suite. Changes in the global metabolic profile were assessed by 1H NMR spectroscopy, and metabolites were assigned by 2D NMR spectroscopy and the MetaboMiner platform. PLS-DA analysis of both metataxonomic and metabolomic data showed a significant cluster separation of PE fermented samples relative to controls. DEseq2 analysis showed that the abundance of families such as Lactobacillaceae and Bifidobacteriaceae were increased in PE samples. Accordingly, in metabolomics, more than twenty metabolites including SCFAs, essential amino acids, and neurotransmitters discriminate PE samples from the respective controls, further validating the metataxonomic findings.

Protocol for unbiased, consolidated variant calling from whole exome sequencing data.

Whole Exome Sequencing (WES) is used for querying DNA variants using the protein coding parts of genomes (exomes). However, WES analysis can be challenging because of the complexity of the data. Here, we describe a consolidated protocol for unbiased WES analysis. The protocol uses three variant callers (HaplotypeCaller, FreeBayes, and DeepVariant), which have different underlying models. We provide detailed execution steps, as well as basic variant filtering, annotation, visualization, and consolidation aspects.

Catchet-MS identifies IKZF1-targeting thalidomide analogues as novel HIV-1 latency reversal agents.

A major pharmacological strategy toward HIV cure aims to reverse latency in infected cells as a first step leading to their elimination. While the unbiased identification of molecular targets physically associated with the latent HIV-1 provirus would be highly valuable to unravel the molecular determinants of HIV-1 transcriptional repression and latency reversal, due to technical limitations, this has been challenging. Here we use a dCas9 targeted chromatin and histone enrichment strategy coupled to mass spectrometry (Catchet-MS) to probe the differential protein composition of the latent and activated HIV-1 5'LTR. Catchet-MS identified known and novel latent 5'LTR-associated host factors. Among these, IKZF1 is a novel HIV-1 transcriptional repressor, required for Polycomb Repressive Complex 2 recruitment to the LTR. We find the clinically advanced thalidomide analogue iberdomide, and the FDA approved analogues lenalidomide and pomalidomide, to be novel LRAs. We demonstrate that, by targeting IKZF1 for degradation, these compounds reverse HIV-1 latency in CD4+ T-cells isolated from virally suppressed people living with HIV-1 and that they are able to synergize with other known LRAs.

Interactive Analysis, Exploration, and Visualization of RNA-Seq Data with SeqCVIBE.

The rise of modern gene expression profiling techniques, such as RNA-Seq, has generated a wealth of high-quality datasets spanning all fields of current biological research. The large data sets and the continually expanding applications for which they can be mined, such as the investigation of alternative splicing and others, have created novel challenges for data management, exploration, analysis, and visualization. Although a large variety of RNA-Seq data analysis software packages has emerged, both open-source and commercial, most fail to simultaneously address the above challenges, while they lack obvious functionalities, such as estimating RNA abundance over non-annotated genomic regions of interest in real time. We have developed SeqCVIBE, an R Shiny web application for the interactive exploration, analysis, visualization, and genome browsing of large RNA-Seq datasets. SeqCVIBE allows for multiple on-the-fly visualizations and calculations, such as differential expression analysis, averaging genomic signals over specific regions of the genome, and calculating RNA abundances over custom, potentially non-annotated regions, such as novel long non-coding RNAs. In addition, SeqCVIBE comprises a database for pre-analyzed data, where users can navigate and explore results, as well as perform a variety of basic on-the-fly analyses and export the outcomes. Finally, we demonstrate the value of SeqCVIBE in the elucidation of the interplay of a novel lincRNA, WiNTRLINC1, and Wnt signaling in colon cancer.

The transcription factor Xrp1 orchestrates both reduced translation and cell competition upon defective ribosome assembly or function.

Ribosomal Protein (Rp) gene haploinsufficiency affects translation rate, can lead to protein aggregation, and causes cell elimination by competition with wild type cells in mosaic tissues. We find that the modest changes in ribosomal subunit levels observed were insufficient for these effects, which all depended on the AT-hook, bZip domain protein Xrp1. Xrp1 reduced global translation through PERK-dependent phosphorylation of eIF2α. eIF2α phosphorylation was itself sufficient to enable cell competition of otherwise wild type cells, but through Xrp1 expression, not as the downstream effector of Xrp1. Unexpectedly, many other defects reducing ribosome biogenesis or function (depletion of TAF1B, eIF2, eIF4G, eIF6, eEF2, eEF1α1, or eIF5A), also increased eIF2α phosphorylation and enabled cell competition. This was also through the Xrp1 expression that was induced in these depletions. In the absence of Xrp1, translation differences between cells were not themselves sufficient to trigger cell competition. Xrp1 is shown here to be a sequence-specific transcription factor that regulates transposable elements as well as single-copy genes. Thus, Xrp1 is the master regulator that triggers multiple consequences of ribosomal stresses and is the key instigator of cell competition.

Obesity Reshapes the Microbial Population Structure along the Gut-Liver-Lung Axis in Mice.

The microbiome is emerging as a major player in tissue homeostasis in health and disease. Gut microbiome dysbiosis correlates with several autoimmune and metabolic diseases, while high-fat diets and ensuing obesity are known to affect the complexity and diversity of the microbiome, thus modulating pathophysiology. Moreover, the existence of a gut-liver microbial axis has been proposed, which may extend to the lung. In this context, we systematically compared the microbiomes of the gut, liver, and lung of mice fed a high-fat diet to those of littermates fed a matched control diet. We carried out deep sequencing of seven hypervariable regions of the 16S rRNA microbial gene to examine microbial diversity in the tissues of interest. Comparison of the local microbiomes indicated that lung tissue has the least diverse microbiome under healthy conditions, while microbial diversity in the healthy liver clustered closer to the gut. Obesity increased microbial complexity in all three tissues, with lung microbial diversity being the most modified. Obesity promoted the expansion of Firmicutes along the gut-liver-lung axis, highlighting staphylococcus as a possible pathologic link between obesity and systemic pathophysiology, especially in the lungs.

A Two-Color Haploid Genetic Screen Identifies Novel Host Factors Involved in HIV-1 Latency.

To identify novel host factors as putative targets to reverse HIV-1 latency, we performed an insertional mutagenesis genetic screen in a latent HIV-1 infected pseudohaploid KBM7 cell line (Hap-Lat). Following mutagenesis, insertions were mapped to the genome, and bioinformatic analysis resulted in the identification of 69 candidate host genes involved in maintaining HIV-1 latency. A select set of candidate genes was functionally validated using short hairpin RNA (shRNA)-mediated depletion in latent HIV-1 infected J-Lat A2 and 11.1 T cell lines. We confirmed ADK, CHD9, CMSS1, EVI2B, EXOSC8, FAM19A, GRIK5, IRF2BP2, NF1, and USP15 as novel host factors involved in the maintenance of HIV-1 latency. Chromatin immunoprecipitation assays indicated that CHD9, a chromodomain helicase DNA-binding protein, maintains HIV-1 latency via direct association with the HIV-1 5' long terminal repeat (LTR), and its depletion results in increased histone acetylation at the HIV-1 promoter, concomitant with HIV-1 latency reversal. FDA-approved inhibitors 5-iodotubercidin, trametinib, and topiramate, targeting ADK, NF1, and GRIK5, respectively, were characterized for their latency reversal potential. While 5-iodotubercidin exhibited significant cytotoxicity in both J-Lat and primary CD4+ T cells, trametinib reversed latency in J-Lat cells but not in latent HIV-1 infected primary CD4+ T cells. Importantly, topiramate reversed latency in cell line models, in latently infected primary CD4+ T cells, and crucially in CD4+ T cells from three people living with HIV-1 (PLWH) under suppressive antiretroviral therapy, without inducing T cell activation or significant toxicity. Thus, using an adaptation of a haploid forward genetic screen, we identified novel and druggable host factors contributing to HIV-1 latency. IMPORTANCE A reservoir of latent HIV-1 infected cells persists in the presence of combination antiretroviral therapy (cART), representing a major obstacle for viral eradication. Reactivation of the latent HIV-1 provirus is part of curative strategies which aim to promote clearance of the infected cells. Using a two-color haploid screen, we identified 69 candidate genes as latency-maintaining host factors and functionally validated a subset of 10 of those in additional T-cell-based cell line models of HIV-1 latency. We further demonstrated that CHD9 is associated with HIV-1's promoter, the 5' LTR, while this association is lost upon reactivation. Additionally, we characterized the latency reversal potential of FDA compounds targeting ADK, NF1, and GRIK5 and identify the GRIK5 inhibitor topiramate as a viable latency reversal agent with clinical potential.

Fibromine is a multi-omics database and mining tool for target discovery in pulmonary fibrosis.

Idiopathic pulmonary fibrosis is a lethal lung fibroproliferative disease with limited therapeutic options. Differential expression profiling of affected sites has been instrumental for involved pathogenetic mechanisms dissection and therapeutic targets discovery. However, there have been limited efforts to comparatively analyse/mine the numerous related publicly available datasets, to fully exploit their potential on the validation/creation of novel research hypotheses. In this context and towards that goal, we present Fibromine, an integrated database and exploration environment comprising of consistently re-analysed, manually curated transcriptomic and proteomic pulmonary fibrosis datasets covering a wide range of experimental designs in both patients and animal models. Fibromine can be accessed via an R Shiny application ( http://www.fibromine.com/Fibromine ) which offers dynamic data exploration and real-time integration functionalities. Moreover, we introduce a novel benchmarking system based on transcriptomic datasets underlying characteristics, resulting to dataset accreditation aiming to aid the user on dataset selection. Cell specificity of gene expression can be visualised and/or explored in several scRNA-seq datasets, in an effort to link legacy data with this cutting-edge methodology and paving the way to their integration. Several use case examples are presented, that, importantly, can be reproduced on-the-fly by a non-specialist user, the primary target and potential user of this endeavour.

Blood Transcriptomes of Anti-SARS-CoV-2 Antibody-Positive Healthy Individuals Who Experienced Asymptomatic Versus Clinical Infection.

The reasons behind the clinical variability of SARS-CoV-2 infection, ranging from asymptomatic infection to lethal disease, are still unclear. We performed genome-wide transcriptional whole-blood RNA sequencing, bioinformatics analysis and PCR validation to test the hypothesis that immune response-related gene signatures reflecting baseline may differ between healthy individuals, with an equally robust antibody response, who experienced an entirely asymptomatic (n=17) versus clinical SARS-CoV-2 infection (n=15) in the past months (mean of 14 weeks). Among 12.789 protein-coding genes analysed, we identified six and nine genes with significantly decreased or increased expression, respectively, in those with prior asymptomatic infection relatively to those with clinical infection. All six genes with decreased expression (IFIT3, IFI44L, RSAD2, FOLR3, PI3, ALOX15), are involved in innate immune response while the first two are interferon-induced proteins. Among genes with increased expression six are involved in immune response (GZMH, CLEC1B, CLEC12A), viral mRNA translation (GCAT), energy metabolism (CACNA2D2) and oxidative stress response (ENC1). Notably, 8/15 differentially expressed genes are regulated by interferons. Our results suggest that subtle differences at baseline expression of innate immunity-related genes may be associated with an asymptomatic disease course in SARS-CoV-2 infection. Whether a certain gene signature predicts, or not, those who will develop a more efficient immune response upon exposure to SARS-CoV-2, with implications for prioritization for vaccination, warrant further study.

Combining Multiple RNA-Seq Data Analysis Algorithms Using Machine Learning Improves Differential Isoform Expression Analysis.

RNA sequencing has become the standard technique for high resolution genome-wide monitoring of gene expression. As such, it often comprises the first step towards understanding complex molecular mechanisms driving various phenotypes, spanning organ development to disease genesis, monitoring and progression. An advantage of RNA sequencing is its ability to capture complex transcriptomic events such as alternative splicing which results in alternate isoform abundance. At the same time, this advantage remains algorithmically and computationally challenging, especially with the emergence of even higher resolution technologies such as single-cell RNA sequencing. Although several algorithms have been proposed for the effective detection of differential isoform expression from RNA-Seq data, no widely accepted golden standards have been established. This fact is further compounded by the significant differences in the output of different algorithms when applied on the same data. In addition, many of the proposed algorithms remain scarce and poorly maintained. Driven by these challenges, we developed a novel integrative approach that effectively combines the most widely used algorithms for differential transcript and isoform analysis using state-of-the-art machine learning techniques. We demonstrate its usability by applying it on simulated data based on several organisms, and using several performance metrics; we conclude that our strategy outperforms the application of the individual algorithms. Finally, our approach is implemented as an R Shiny application, with the underlying data analysis pipelines also available as docker containers.

Increased Autotaxin Levels in Severe COVID-19, Correlating with IL-6 Levels, Endothelial Dysfunction Biomarkers, and Impaired Functions of Dendritic Cells.

Autotaxin (ATX; ENPP2) is a secreted lysophospholipase D catalyzing the extracellular production of lysophosphatidic acid (LPA), a pleiotropic signaling phospholipid. Genetic and pharmacologic studies have previously established a pathologic role for ATX and LPA signaling in pulmonary injury, inflammation, and fibrosis. Here, increased ENPP2 mRNA levels were detected in immune cells from nasopharyngeal swab samples of COVID-19 patients, and increased ATX serum levels were found in severe COVID-19 patients. ATX serum levels correlated with the corresponding increased serum levels of IL-6 and endothelial damage biomarkers, suggesting an interplay of the ATX/LPA axis with hyperinflammation and the associated vascular dysfunction in COVID-19. Accordingly, dexamethasone (Dex) treatment of mechanically ventilated patients reduced ATX levels, as shown in two independent cohorts, indicating that the therapeutic benefits of Dex include the suppression of ATX. Moreover, large scale analysis of multiple single cell RNA sequencing datasets revealed the expression landscape of ENPP2 in COVID-19 and further suggested a role for ATX in the homeostasis of dendritic cells, which exhibit both numerical and functional deficits in COVID-19. Therefore, ATX has likely a multifunctional role in COVID-19 pathogenesis, suggesting that its pharmacological targeting might represent an additional therapeutic option, both during and after hospitalization.

Application of human liver organoids as a patient-derived primary model for HBV infection and related hepatocellular carcinoma.

The molecular events that drive hepatitis B virus (HBV)-mediated transformation and tumorigenesis have remained largely unclear, due to the absence of a relevant primary model system. Here we propose the use of human liver organoids as a platform for modeling HBV infection and related tumorigenesis. We first describe a primary ex vivo HBV-infection model derived from healthy donor liver organoids after challenge with recombinant virus or HBV-infected patient serum. HBV-infected organoids produced covalently closed circular DNA (cccDNA) and HBV early antigen (HBeAg), expressed intracellular HBV RNA and proteins, and produced infectious HBV. This ex vivo HBV-infected primary differentiated hepatocyte organoid platform was amenable to drug screening for both anti-HBV activity and drug-induced toxicity. We also studied HBV replication in transgenically modified organoids; liver organoids exogenously overexpressing the HBV receptor sodium taurocholate co-transporting polypeptide (NTCP) after lentiviral transduction were not more susceptible to HBV, suggesting the necessity for additional host factors for efficient infection. We also generated transgenic organoids harboring integrated HBV, representing a long-term culture system also suitable for viral production and the study of HBV transcription. Finally, we generated HBV-infected patient-derived liver organoids from non-tumor cirrhotic tissue of explants from liver transplant patients. Interestingly, transcriptomic analysis of patient-derived liver organoids indicated the presence of an aberrant early cancer gene signature, which clustered with the hepatocellular carcinoma (HCC) cohort on The Cancer Genome Atlas Liver Hepatocellular Carcinoma dataset and away from healthy liver tissue, and may provide invaluable novel biomarkers for the development of HCC and surveillance in HBV-infected patients.

Molecular Epidemiology of SARS-CoV-2 in Greece Reveals Low Rates of Onward Virus Transmission after Lifting of Travel Restrictions Based on Risk Assessment during Summer 2020.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly during the first months of 2020 and continues to expand in multiple areas across the globe. Molecular epidemiology has provided an added value to traditional public health tools by identifying SARS-CoV-2 clusters or providing evidence that clusters based on virus sequences and contact tracing are highly concordant. Our aim was to infer the levels of virus importation and to estimate the impact of public health measures related to travel restrictions to local transmission in Greece. Our phylogenetic and phylogeographic analyses included 389 full-genome SARS-CoV-2 sequences collected during the first 7 months of the pandemic in Greece and a random collection in five replicates of 3,000 sequences sampled globally, as well as the best hits to our data set identified by BLAST. Phylogenetic trees were reconstructed by the maximum likelihood method, and the putative source of SARS-CoV-2 infections was inferred by phylogeographic analysis. Phylogenetic analyses revealed the presence of 89 genetically distinct viruses identified as independent introductions into Greece. The proportion of imported strains was 41%, 11.5%, and 8.8% during the three periods of sampling, namely, March (no travel restrictions), April to June (strict travel restrictions), and July to September (lifting of travel restrictions based on thorough risk assessment), respectively. The results of phylogeographic analysis were confirmed by a Bayesian approach. Our findings reveal low levels of onward transmission from imported cases during summer and underscore the importance of targeted public health measures that can increase the safety of international travel during a pandemic. IMPORTANCE Our study based on current state-of-the-art molecular epidemiology methods suggests that virus screening and public health measures after the lifting of travel restrictions prevented SARS-CoV-2 onward transmission from imported cases during summer 2020 in Greece. These findings provide important data on the efficacy of targeted public health measures and have important implications regarding the safety of international travel during a pandemic. Our results can provide a roadmap about prevention policy in the future regarding the reopening of borders in the presence of differences in vaccination coverage, the circulation of the virus, and the presence of newly emergent variants across the globe.

Distinct transcriptional profile of blood mononuclear cells in Behçet's disease: insights into the central role of neutrophil chemotaxis.

OBJECTIVES: Both innate and adaptive immune responses are reportedly increased in Behçet's disease (BD), a chronic, relapsing systemic vasculitis lying at the intersection between autoinflammation and autoimmunity. To further study pathophysiologic molecular mechanisms operating in BD, we searched for transcriptome-wide changes in blood mononuclear cells from these patients. METHODS: We performed 3' mRNA next-generation sequencing-based genome-wide transcriptional profiling followed by analysis of differential expression signatures, Kyoto Encyclopedia of Genes and Genomes pathways, GO biological processes and transcription factor signatures. RESULTS: Differential expression analysis clustered the transcriptomes of 13 patients and one healthy subject separately from those of 10 healthy age/gender-matched controls and one patient. Among the total of 17 591 expressed protein-coding genes, 209 and 31 genes were significantly upregulated and downregulated, respectively, in BD vs controls by at least 2-fold. The most upregulated genes comprised an abundance of CC- and CXC-chemokines. Remarkably, the 5 out of top 10 upregulated biological processes involved leucocyte recruitment to peripheral tissues, especially for neutrophils. Moreover, NF-kB, TNF and IL-1 signalling pathways were prominently enhanced in BD, while transcription factor activity analysis suggested that the NF-kB p65/RELA subunit action underlies the observed differences in the BD transcriptome. CONCLUSION: This RNA-sequencing analysis in peripheral blood mononuclear cells derived from patients with BD does not support a major pathogenetic role for adaptive immunity-driven mechanisms, but clearly points to the action of aberrant innate immune responses with a central role played by upregulated neutrophil chemotaxis.

recoup: flexible and versatile signal visualization from next generation sequencing.

BACKGROUND: The relentless continuing emergence of new genomic sequencing protocols and the resulting generation of ever larger datasets continue to challenge the meaningful summarization and visualization of the underlying signal generated to answer important qualitative and quantitative biological questions. As a result, the need for novel software able to reliably produce quick, comprehensive, and easily repeatable genomic signal visualizations in a user-friendly manner is rapidly re-emerging. RESULTS: recoup is a Bioconductor package for quick, flexible, versatile, and accurate visualization of genomic coverage profiles generated from Next Generation Sequencing data. Coupled with a database of precalculated genomic regions for multiple organisms, recoup offers processing mechanisms for quick, efficient, and multi-level data interrogation with minimal effort, while at the same time creating publication-quality visualizations. Special focus is given on plot reusability, reproducibility, and real-time exploration and formatting options, operations rarely supported in similar visualization tools in a profound way. recoup was assessed using several qualitative user metrics and found to balance the tradeoff between important package features, including speed, visualization quality, overall friendliness, and the reusability of the results with minimal additional calculations. CONCLUSION: While some existing solutions for the comprehensive visualization of NGS data signal offer satisfying results, they are often compromised regarding issues such as effortless tracking of processing and preparation steps under a common computational environment, visualization quality and user friendliness. recoup is a unique package presenting a balanced tradeoff for a combination of assessment criteria while remaining fast and friendly.

Integrative, normalization-insusceptible statistical analysis of RNA-Seq data, with improved differential expression and unbiased downstream functional analysis.

The study of differential gene expression patterns through RNA-Seq comprises a routine task in the daily lives of molecular bioscientists, who produce vast amounts of data requiring proper management and analysis. Despite widespread use, there are still no widely accepted golden standards for the normalization and statistical analysis of RNA-Seq data, and critical biases, such as gene lengths and problems in the detection of certain types of molecules, remain largely unaddressed. Stimulated by these unmet needs and the lack of in-depth research into the potential of combinatorial methods to enhance the analysis of differential gene expression, we had previously introduced the PANDORA P-value combination algorithm while presenting evidence for PANDORA's superior performance in optimizing the tradeoff between precision and sensitivity. In this article, we present the next generation of the algorithm along with a more in-depth investigation of its capabilities to effectively analyze RNA-Seq data. In particular, we show that PANDORA-reported lists of differentially expressed genes are unaffected by biases introduced by different normalization methods, while, at the same time, they comprise a reliable input option for downstream pathway analysis. Additionally, PANDORA outperforms other methods in detecting differential expression patterns in certain transcript types, including long non-coding RNAs.

The transcription factor BCL-6 controls early development of innate-like T cells.

Innate T cells, including invariant natural killer T (iNKT) and mucosal-associated innate T (MAIT) cells, are a heterogeneous T lymphocyte population with effector properties preprogrammed during their thymic differentiation. How this program is initiated is currently unclear. Here, we show that the transcription factor BCL-6 was transiently expressed in iNKT cells upon exit from positive selection and was required for their proper development beyond stage 0. Notably, development of MAIT cells was also impaired in the absence of Bcl6. BCL-6-deficient iNKT cells had reduced expression of genes that were associated with the innate T cell lineage, including Zbtb16, which encodes PLZF, and PLZF-targeted genes. BCL-6 contributed to a chromatin accessibility landscape that was permissive for the expression of development-related genes and inhibitory for genes associated with naive T cell programs. Our results revealed new functions for BCL-6 and illuminated how this transcription factor controls early iNKT cell development.

Bookmarking by Non-pioneer Transcription Factors during Liver Development Establishes Competence for Future Gene Activation.

Transcription factor binding to enhancer and promoter regions critical for homeostatic adult gene activation is established during development. To understand how cell-specific gene expression patterns are generated, we study the developmental timing of association of two prominent hepatic transcription factors with gene regulatory regions. Most individual binding events display extraordinarily high temporal variations during liver development. Early and persistent binding is necessary, but not sufficient, for gene activation. Stable gene expression patterns are the result of combinatorial activity of multiple transcription factors, which mark regulatory regions long before activation and promote progressive broadening of active chromatin domains. Both temporally stable and dynamic, short-lived binding events contribute to the developmental maturation of active promoter configurations. The results reveal a developmental bookmarking function of master regulators and illuminate remarkable parallels between the principles employed for gene activation during development, during evolution, and upon mitotic exit.