Orchestrated intron retention regulates normal granulocyte differentiation.

Intron retention (IR) is widely recognized as a consequence of mis-splicing that leads to failed excision of intronic sequences from pre-messenger RNAs. Our bioinformatic analyses of transcriptomic and proteomic data of normal white blood cell differentiation reveal IR as a physiological mechanism of gene expression control. IR regulates the expression of 86 functionally related genes, including those that determine the nuclear shape that is unique to granulocytes. Retention of introns in specific genes is associated with downregulation of splicing factors and higher GC content. IR, conserved between human and mouse, led to reduced mRNA and protein levels by triggering the nonsense-mediated decay (NMD) pathway. In contrast to the prevalent view that NMD is limited to mRNAs encoding aberrant proteins, our data establish that IR coupled with NMD is a conserved mechanism in normal granulopoiesis. Physiological IR may provide an energetically favorable level of dynamic gene expression control prior to sustained gene translation.

A Liver Capsular Network of Monocyte-Derived Macrophages Restricts Hepatic Dissemination of Intraperitoneal Bacteria by Neutrophil Recruitment.

The liver is positioned at the interface between two routes traversed by pathogens in disseminating infection. Whereas blood-borne pathogens are efficiently cleared in hepatic sinusoids by Kupffer cells (KCs), it is unknown how the liver prevents dissemination of peritoneal pathogens accessing its outer membrane. We report here that the hepatic capsule harbors a contiguous cellular network of liver-resident macrophages phenotypically distinct from KCs. These liver capsular macrophages (LCMs) were replenished in the steady state from blood monocytes, unlike KCs that are embryonically derived and self-renewing. LCM numbers increased after weaning in a microbiota-dependent process. LCMs sensed peritoneal bacteria and promoted neutrophil recruitment to the capsule, and their specific ablation resulted in decreased neutrophil recruitment and increased intrahepatic bacterial burden. Thus, the liver contains two separate and non-overlapping niches occupied by distinct resident macrophage populations mediating immunosurveillance at these two pathogen entry points to the liver.

NF90 modulates processing of a subset of human pri-miRNAs.

MicroRNAs (miRNAs) are predicted to regulate the expression of >60% of mammalian genes and play fundamental roles in most biological processes. Deregulation of miRNA expression is a hallmark of most cancers and further investigation of mechanisms controlling miRNA biogenesis is needed. The double stranded RNA-binding protein, NF90 has been shown to act as a competitor of Microprocessor for a limited number of primary miRNAs (pri-miRNAs). Here, we show that NF90 has a more widespread effect on pri-miRNA biogenesis than previously thought. Genome-wide approaches revealed that NF90 is associated with the stem region of 38 pri-miRNAs, in a manner that is largely exclusive of Microprocessor. Following loss of NF90, 22 NF90-bound pri-miRNAs showed increased abundance of mature miRNA products. NF90-targeted pri-miRNAs are highly stable, having a lower free energy and fewer mismatches compared to all pri-miRNAs. Mutations leading to less stable structures reduced NF90 binding while increasing pri-miRNA stability led to acquisition of NF90 association, as determined by RNA electrophoretic mobility shift assay (EMSA). NF90-bound and downregulated pri-miRNAs are embedded in introns of host genes and expression of several host genes is concomitantly reduced. These data suggest that NF90 controls the processing of a subset of highly stable, intronic miRNAs.

A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants.

BACKGROUND: Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been successfully used to classify breast tumours into 5 major types with different prognosis and sensitivity to specific treatments. Unfortunately, these profiles have failed to subclassify breast tumours into more subtypes to improve diagnostics and survival rate. Alternative splicing is emerging as a new source of highly specific biomarkers to classify tumours in different grades. Taking advantage of extensive public transcriptomics datasets in breast cancer cell lines (CCLE) and breast cancer tumours (TCGA), we have addressed the capacity of alternative splice variants to subclassify highly aggressive breast cancers. RESULTS: Transcriptomics analysis of alternative splicing events between luminal, basal A and basal B breast cancer cell lines identified a unique splicing signature for a subtype of tumours, the basal B, whose classification is not in use in the clinic yet. Basal B cell lines, in contrast with luminal and basal A, are highly metastatic and express epithelial-to-mesenchymal (EMT) markers, which are hallmarks of cell invasion and resistance to drugs. By developing a semi-supervised machine learning approach, we transferred the molecular knowledge gained from these cell lines into patients to subclassify basal-like triple negative tumours into basal A- and basal B-like categories. Changes in splicing of 25 alternative exons, intimately related to EMT and cell invasion such as ENAH, CD44 and CTNND1, were sufficient to identify the basal-like patients with the worst prognosis. Moreover, patients expressing this basal B-specific splicing signature also expressed newly identified biomarkers of metastasis-initiating cells, like CD36, supporting a more invasive phenotype for this basal B-like breast cancer subtype. CONCLUSIONS: Using a novel machine learning approach, we have identified an EMT-related splicing signature capable of subclassifying the most aggressive type of breast cancer, which are basal-like triple negative tumours. This proof-of-concept demonstrates that the biological knowledge acquired from cell lines can be transferred to patients data for further clinical investigation. More studies, particularly in 3D culture and organoids, will increase the accuracy of this transfer of knowledge, which will open new perspectives into the development of novel therapeutic strategies and the further identification of specific biomarkers for drug resistance and cancer relapse.

TALC: Transcript-level Aware Long-read Correction.

MOTIVATION: Long-read sequencing technologies are invaluable for determining complex RNA transcript architectures but are error-prone. Numerous 'hybrid correction' algorithms have been developed for genomic data that correct long reads by exploiting the accuracy and depth of short reads sequenced from the same sample. These algorithms are not suited for correcting more complex transcriptome sequencing data. RESULTS: We have created a novel reference-free algorithm called Transcript-level Aware Long-Read Correction (TALC) which models changes in RNA expression and isoform representation in a weighted De Bruijn graph to correct long reads from transcriptome studies. We show that transcript-level aware correction by TALC improves the accuracy of the whole spectrum of downstream RNA-seq applications and is thus necessary for transcriptome analyses that use long read technology. AVAILABILITY AND IMPLEMENTATION: TALC is implemented in C++ and available at https://github.com/lbroseus/TALC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genome-wide characterization of the routes to pluripotency.

Somatic cell reprogramming to a pluripotent state continues to challenge many of our assumptions about cellular specification, and despite major efforts, we lack a complete molecular characterization of the reprograming process. To address this gap in knowledge, we generated extensive transcriptomic, epigenomic and proteomic data sets describing the reprogramming routes leading from mouse embryonic fibroblasts to induced pluripotency. Through integrative analysis, we reveal that cells transition through distinct gene expression and epigenetic signatures and bifurcate towards reprogramming transgene-dependent and -independent stable pluripotent states. Early transcriptional events, driven by high levels of reprogramming transcription factor expression, are associated with widespread loss of histone H3 lysine 27 (H3K27me3) trimethylation, representing a general opening of the chromatin state. Maintenance of high transgene levels leads to re-acquisition of H3K27me3 and a stable pluripotent state that is alternative to the embryonic stem cell (ESC)-like fate. Lowering transgene levels at an intermediate phase, however, guides the process to the acquisition of ESC-like chromatin and DNA methylation signature. Our data provide a comprehensive molecular description of the reprogramming routes and is accessible through the Project Grandiose portal at http://www.stemformatics.org.

A dynamic intron retention program in the mammalian megakaryocyte and erythrocyte lineages.

Intron retention (IR) is a form of alternative splicing that can impact mRNA levels through nonsense-mediated decay or by nuclear mRNA detention. A complex, dynamic IR pattern has been described in maturing mammalian granulocytes, but it is unknown whether IR occurs broadly in other hematopoietic lineages. We globally assessed IR in primary maturing mammalian erythroid and megakaryocyte (MK) lineages as well as their common progenitor cells (MEPs). Both lineages exhibit an extensive differential IR program involving hundreds of introns and genes with an overwhelming loss of IR in erythroid cells and MKs compared to MEPs. Moreover, complex IR patterns were seen throughout murine erythroid maturation. Similarly complex patterns were observed in human erythroid differentiation, but not involving the murine orthologous introns or genes. Despite the common origin of erythroid cells and MKs, and overlapping gene expression patterns, the MK IR program is entirely distinct from that of the erythroid lineage with regards to introns, genes, and affected gene ontologies. Importantly, our results suggest that IR serves to broadly regulate mRNA levels. These findings highlight the importance of this understudied form of alternative splicing in gene regulation and provide a useful resource for studies on gene expression in the MK and erythroid lineages.

Intron retention in mRNA: No longer nonsense: Known and putative roles of intron retention in normal and disease biology.

Until recently, retention of introns in mature mRNAs has been regarded as a consequence of mis-splicing. Intron-retaining transcripts are thought to be non-functional because they are readily degraded by nonsense-mediated decay. However, recent advances in next-generation sequencing technologies have enabled the detection of numerous transcripts that retain introns. As we review herein, intron-retaining mRNAs play an essential conserved role in normal physiology and an emergent role in diverse diseases. Intron retention should no longer be overlooked as a key mechanism that independently reduces gene expression in normal biology. Exploring its contribution to the development and/or maintenance of diseases is of increasing importance.

RBM3 regulates temperature sensitive miR-142-5p and miR-143 (thermomiRs), which target immune genes and control fever.

Fever is commonly used to diagnose disease and is consistently associated with increased mortality in critically ill patients. However, the molecular controls of elevated body temperature are poorly understood. We discovered that the expression of RNA-binding motif protein 3 (RBM3), known to respond to cold stress and to modulate microRNA (miRNA) expression, was reduced in 30 patients with fever, and in THP-1-derived macrophages maintained at a fever-like temperature (40 °C). Notably, RBM3 expression is reduced during fever whether or not infection is demonstrable. Reduced RBM3 expression resulted in increased expression of RBM3-targeted temperature-sensitive miRNAs, we termed thermomiRs. ThermomiRs such as miR-142-5p and miR-143 in turn target endogenous pyrogens including IL-6, IL6ST, TLR2, PGE2 and TNF to complete a negative feedback mechanism, which may be crucial to prevent pathological hyperthermia. Using normal PBMCs that were exogenously exposed to fever-like temperature (40 °C), we further demonstrate the trend by which decreased levels of RBM3 were associated with increased levels of miR-142-5p and miR-143 and vice versa over a 24 h time course. Collectively, our results indicate the existence of a negative feedback loop that regulates fever via reduced RBM3 levels and increased expression of miR-142-5p and miR-143.

Exploring the Roles of CREBRF and TRIM2 in the Regulation of Angiogenesis by High-Density Lipoproteins.

Angiogenesis, the process of forming new blood vessels, is crucial in the physiological response to ischemia, though it can be detrimental as part of inflammation and tumorigenesis. We have previously shown that high-density lipoproteins (HDL) modulate angiogenesis in a context-specific manner via distinct classical signalling pathways, enhancing hypoxia-induced angiogenesis while suppressing inflammatory-driven angiogenesis. Whether additional novel targets exist to account for these effects are unknown. A microarray approach identified two novel genes, cyclic-adenosine-monophosphate-response-element-binding protein 3 regulatory factor (CREBRF) and tripartite motif-containing protein 2 (TRIM2) that were upregulated by reconstituted HDL (rHDL). We measured CREBRF and TRIM2 expression in human coronary artery endothelial cells following incubation with rHDL and exposure to either hypoxia or an inflammatory stimulus. We found that CREBRF and TRIM2 mRNA were significantly upregulated by rHDL, particularly in response to its phospholipid component 1-palmitoyl-2-linoleoyl-phosphatidylcholine, however, protein expression was not significantly altered. Knockdown of TRIM2 impaired endothelial cell tubulogenesis in vitro in both hypoxia and inflammation, implying a necessary role in angiogenesis. Furthermore, TRIM2 knockdown attenuated rHDL-induced tubule formation in hypoxia, suggesting that it is important in mediating the pro-angiogenic action of rHDL. Our study has implications for understanding the regulation of angiogenesis in both of these pathophysiological contexts by HDL.

Targeting ASCT2-mediated glutamine uptake blocks prostate cancer growth and tumour development.

Glutamine is conditionally essential in cancer cells, being utilized as a carbon and nitrogen source for macromolecule production, as well as for anaplerotic reactions fuelling the tricarboxylic acid (TCA) cycle. In this study, we demonstrated that the glutamine transporter ASCT2 (SLC1A5) is highly expressed in prostate cancer patient samples. Using LNCaP and PC-3 prostate cancer cell lines, we showed that chemical or shRNA-mediated inhibition of ASCT2 function in vitro decreases glutamine uptake, cell cycle progression through E2F transcription factors, mTORC1 pathway activation and cell growth. Chemical inhibition also reduces basal oxygen consumption and fatty acid synthesis, showing that downstream metabolic function is reliant on ASCT2-mediated glutamine uptake. Furthermore, shRNA knockdown of ASCT2 in PC-3 cell xenografts significantly inhibits tumour growth and metastasis in vivo, associated with the down-regulation of E2F cell cycle pathway proteins. In conclusion, ASCT2-mediated glutamine uptake is essential for multiple pathways regulating the cell cycle and cell growth, and is therefore a putative therapeutic target in prostate cancer.

Refining microRNA target predictions: sorting the wheat from the chaff.

microRNAs are short RNAs that reduce gene expression by binding to their targets. The accurate prediction of microRNA targets is essential to understanding the function of microRNAs. Computational predictions indicate that all human genes may be regulated by microRNAs, with each microRNA possibly targeting thousands of genes. Here we discuss computational methods for identifying mammalian microRNA targets and refining them for further experimental validation. We describe microRNA target prediction resources and procedures and how they integrate with various types of experimental techniques that aim to validate them or further explore their function. We also provide a list of target prediction databases and explain how these are curated.

miREval 2.0: a web tool for simple microRNA prediction in genome sequences.

RESULT: We have developed miREval 2.0, an online tool that can simultaneously search up to 100 sequences for novel microRNAs (miRNAs) in multiple organisms. miREval 2.0 uses multiple published in silico approaches to detect miRNAs in sequences of interest. This tool can be used to discover miRNAs from DNA sequences or to validate candidates from sequencing data. AVAILABILITY: http://mimirna.centenary.org.au/mireval/.

Defining and providing robust controls for microRNA prediction.

MOTIVATION: microRNAs are short non-coding RNAs that regulate gene expression by inhibiting target mRNA genes. Next-generation sequencing combined with bioinformatics analyses provide an opportunity to predict numerous novel miRNAs. The efficiency of these predictions relies on the set of positive and negative controls used. We demonstrate that commonly used positive and negative controls may be unreliable and provide a rational methodology with which to replace them.

MicroRNA target prediction and validation.

The accurate prediction and validation of microRNA targets is essential to understanding the function of microRNAs. Computational predictions indicate that all human genes may be regulated by microRNAs, with each microRNA possibly targeting thousands of genes. Here we discuss computational and experimental methods for identifying mammalian microRNA targets. We describe microRNA target prediction resources and procedures that are suitable for experiments where more accurate prediction of microRNA targets is more important than detecting all putative targets. We then discuss experimental methods for identifying and validating microRNA target genes, with an emphasis on the target reporter assay as the method of choice for specifically testing functional microRNA target sites.

mimiRNA: a microRNA expression profiler and classification resource designed to identify functional correlations between microRNAs and their targets.

MOTIVATION: microRNAs (miRNAs) are short non-coding RNAs that regulate gene expression by inhibiting target mRNA genes. Their tissue- and disease-specific expression patterns have immense therapeutic and diagnostic potential. To understand these patterns, a reliable compilation of miRNA and mRNA expression data is required to compare multiple tissue types. Moreover, with the appropriate statistical tools, such a resource could be interrogated to discover functionally related miRNA-mRNA pairs. RESULTS: We have developed mimiRNA, an online resource that integrates expression data from 1483 samples and permits visualization of the expression of 635 human miRNAs across 188 different tissues or cell types. mimiRNA incorporates a novel sample classification algorithm, ExParser, that groups identical miRNA or mRNA experiments from separate sources. This enables mimiRNA to provide reliable expression profiles and to discover functional relations between miRNAs and mRNAs such as miRNA targets. Additionally, mimiRNA incorporates a decision tree algorithm to discover distinguishing miRNA features between two tissue or cell types. We validate the efficacy of our resource on independent experimental data and through biologically relevant analyses. AVAILABILITY: http://mimirna.centenary.org.au. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

IRFinder-S: a comprehensive suite to discover and explore intron retention.

Accurate quantification and detection of intron retention levels require specialized software. Building on our previous software, we create a suite of tools called IRFinder-S, to analyze and explore intron retention events in multiple samples. Specifically, IRFinder-S allows a better identification of true intron retention events using a convolutional neural network, allows the sharing of intron retention results between labs, integrates a dynamic database to explore and contrast available samples, and provides a tested method to detect differential levels of intron retention.

Intron retention and its impact on gene expression and protein diversity: A review and a practical guide.

Intron retention (IR) occurs when a complete and unspliced intron remains in mature mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions, including several that impact human health and disease. Although experimental technologies used to study other forms of mRNA splicing can also be used to investigate IR, a specialized downstream computational analysis is optimal for IR discovery and analysis. Here we provide a review of IR and its biological implications, as well as a practical guide for how to detect and analyze it. Several methods, including long read third generation direct RNA sequencing, are described. We have developed an R package, FakIR, to facilitate the execution of the bioinformatic tasks recommended in this review and a tutorial on how to fit them to users aims. Additionally, we provide guidelines and experimental protocols to validate IR discovery and to evaluate the potential impact of IR on gene expression and protein output. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Regulation/Alternative Splicing RNA Methods > RNA Analyses in vitro and In Silico.