Comprehensive survey of conserved RNA secondary structures in full-genome alignment of Hepatitis C virus.

Hepatitis C virus (HCV) is a plus-stranded RNA virus that often chronically infects liver hepatocytes and causes liver cirrhosis and cancer. These viruses replicate their genomes employing error-prone replicases. Thereby, they routinely generate a large 'cloud' of RNA genomes (quasispecies) which-by trial and error-comprehensively explore the sequence space available for functional RNA genomes that maintain the ability for efficient replication and immune escape. In this context, it is important to identify which RNA secondary structures in the sequence space of the HCV genome are conserved, likely due to functional requirements. Here, we provide the first genome-wide multiple sequence alignment (MSA) with the prediction of RNA secondary structures throughout all representative full-length HCV genomes. We selected 57 representative genomes by clustering all complete HCV genomes from the BV-BRC database based on k-mer distributions and dimension reduction and adding RefSeq sequences. We include annotations of previously recognized features for easy comparison to other studies. Our results indicate that mainly the core coding region, the C-terminal NS5A region, and the NS5B region contain secondary structure elements that are conserved beyond coding sequence requirements, indicating functionality on the RNA level. In contrast, the genome regions in between contain less highly conserved structures. The results provide a complete description of all conserved RNA secondary structures and make clear that functionally important RNA secondary structures are present in certain HCV genome regions but are largely absent from other regions. Full-genome alignments of all branches of Hepacivirus C are provided in the supplement.

The genome and population genomics of allopolyploid Coffea arabica reveal the diversification history of modern coffee cultivars.

Coffea arabica, an allotetraploid hybrid of Coffea eugenioides and Coffea canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000-610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred ~30.5 thousand years ago, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica.

Defining the landscape of circular RNAs in neuroblastoma unveils a global suppressive function of MYCN.

Circular RNAs (circRNAs) are a regulatory RNA class. While cancer-driving functions have been identified for single circRNAs, how they modulate gene expression in cancer is not well understood. We investigate circRNA expression in the pediatric malignancy, neuroblastoma, through deep whole-transcriptome sequencing in 104 primary neuroblastomas covering all risk groups. We demonstrate that MYCN amplification, which defines a subset of high-risk cases, causes globally suppressed circRNA biogenesis directly dependent on the DHX9 RNA helicase. We detect similar mechanisms in shaping circRNA expression in the pediatric cancer medulloblastoma implying a general MYCN effect. Comparisons to other cancers identify 25 circRNAs that are specifically upregulated in neuroblastoma, including circARID1A. Transcribed from the ARID1A tumor suppressor gene, circARID1A promotes cell growth and survival, mediated by direct interaction with the KHSRP RNA-binding protein. Our study highlights the importance of MYCN regulating circRNAs in cancer and identifies molecular mechanisms, which explain their contribution to neuroblastoma pathogenesis.

Toward a Systematic Assessment of Sex Differences in Cystic Fibrosis.

(1) Background: Cystic fibrosis (CF) is a disease with well-documented clinical differences between female and male patients. However, this gender gap is very poorly studied at the molecular level. (2) Methods: Expression differences in whole blood transcriptomics between female and male CF patients are analyzed in order to determine the pathways related to sex-biased genes and assess their potential influence on sex-specific effects in CF patients. (3) Results: We identify sex-biased genes in female and male CF patients and provide explanations for some sex-specific differences at the molecular level. (4) Conclusion: Genes in key pathways associated with CF are differentially expressed between sexes, and thus may account for the gender gap in morbidity and mortality in CF.

Temperature-dependent resistance to starvation of three contrasting freshwater ciliates.

We investigated the temperature-dependent response to starvation of three contrasting freshwater ciliates (Ciliophora). The cyst-forming algivorous species Meseres corlissi and the bactivorous species Glaucomides bromelicola, which cannot form cysts, co-occur in the reservoirs (tanks) of tree bromeliads. The mixotrophic species Coleps spetai is common in many lakes. We hypothesized that the ciliates' different traits and life strategies would affect their survival rates and temperature sensitivity under food depleted conditions. We measured the decline of the ciliate populations in microcosm experiments at different temperatures for several days. We used an imaging flow cytometer to size the ciliates and documented their morphological and physiological changes in response to starvation. We found that the cyst-forming species had the highest mortality rates but may endure long-term starvation by encystment. The sympatric, non-encysting species suffered the lowest mortality rates and could survive for more than three weeks without food. The mixotrophic species had intermediate mortality rates but showed the highest phenotypic plasticity in response to starvation. A significant fraction of the C. spetai population appeared unaffected by starvation, suggesting that the endosymbionts provided some resources to the host cells. The mean mortality rate per day of all three species increased with temperature by 0.09 °C-1.

Mitochondrial Genomes in Perkinsus Decode Conserved Frameshifts in All Genes.

Mitochondrial genomes of apicomplexans, dinoflagellates, and chrompodellids that collectively make up the Myzozoa, encode only three proteins (Cytochrome b [COB], Cytochrome c oxidase subunit 1 [COX1], Cytochrome c oxidase subunit 3 [COX3]), contain fragmented ribosomal RNAs, and display extensive recombination, RNA trans-splicing, and RNA-editing. The early-diverging Perkinsozoa is the final major myzozoan lineage whose mitochondrial genomes remained poorly characterized. Previous reports of Perkinsus genes indicated independent acquisition of non-canonical features, namely the occurrence of multiple frameshifts. To determine both ancestral myzozoan and novel perkinsozoan mitochondrial genome features, we sequenced and assembled mitochondrial genomes of four Perkinsus species. These data show a simple ancestral genome with the common reduced coding capacity but disposition for rearrangement. We identified 75 frameshifts across the four species that occur as distinct types and that are highly conserved in gene location. A decoding mechanism apparently employs unused codons at the frameshift sites that advance translation either +1 or +2 frames to the next used codon. The locations of frameshifts are seemingly positioned to regulate protein folding of the nascent protein as it emerges from the ribosome. The cox3 gene is distinct in containing only one frameshift and showing strong selection against residues that are otherwise frequently encoded at the frameshift positions in cox1 and cob. All genes lack cysteine codons implying a reduction to 19 amino acids in these genomes. Furthermore, mitochondrion-encoded rRNA fragment complements are incomplete in Perkinsus spp. but some are found in the nuclear DNA suggesting import into the organelle. Perkinsus demonstrates further remarkable trajectories of organelle genome evolution including pervasive integration of frameshift translation into genome expression.

BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria.

Recent technological advances have led to an exponential expansion of biological sequence data and extraction of meaningful information through Machine Learning (ML) algorithms. This knowledge has improved the understanding of mechanisms related to several fatal diseases, e.g. Cancer and coronavirus disease 2019, helping to develop innovative solutions, such as CRISPR-based gene editing, coronavirus vaccine and precision medicine. These advances benefit our society and economy, directly impacting people's lives in various areas, such as health care, drug discovery, forensic analysis and food processing. Nevertheless, ML-based approaches to biological data require representative, quantitative and informative features. Many ML algorithms can handle only numerical data, and therefore sequences need to be translated into a numerical feature vector. This process, known as feature extraction, is a fundamental step for developing high-quality ML-based models in bioinformatics, by allowing the feature engineering stage, with design and selection of suitable features. Feature engineering, ML algorithm selection and hyperparameter tuning are often manual and time-consuming processes, requiring extensive domain knowledge. To deal with this problem, we present a new package: BioAutoML. BioAutoML automatically runs an end-to-end ML pipeline, extracting numerical and informative features from biological sequence databases, using the MathFeature package, and automating the feature selection, ML algorithm(s) recommendation and tuning of the selected algorithm(s) hyperparameters, using Automated ML (AutoML). BioAutoML has two components, divided into four modules: (1) automated feature engineering (feature extraction and selection modules) and (2) Metalearning (algorithm recommendation and hyper-parameter tuning modules). We experimentally evaluate BioAutoML in two different scenarios: (i) prediction of the three main classes of noncoding RNAs (ncRNAs) and (ii) prediction of the eight categories of ncRNAs in bacteria, including housekeeping and regulatory types. To assess BioAutoML predictive performance, it is experimentally compared with two other AutoML tools (RECIPE and TPOT). According to the experimental results, BioAutoML can accelerate new studies, reducing the cost of feature engineering processing and either keeping or improving predictive performance. BioAutoML is freely available at https://github.com/Bonidia/BioAutoML.

Small integral membrane protein 10 like 1 downregulation enhances differentiation of adipose progenitor cells.

Small integral membrane protein 10 like 1 (SMIM10L1) was identified by RNA sequencing as the most significantly downregulated gene in Phosphatase and Tensin Homologue (PTEN) knockdown adipose progenitor cells (APCs). PTEN is a tumor suppressor that antagonizes the growth promoting Phosphoinositide 3-kinase (PI3K)/AKT/mechanistic Target of Rapamycin (mTOR) cascade. Diseases caused by germline pathogenic variants in PTEN are summarized as PTEN Hamartoma Tumor Syndrome (PHTS). This overgrowth syndrome is associated with lipoma formation, especially in pediatric patients. The mechanisms underlying this adipose tissue dysfunction remain elusive. We observed that SMIM10L1 downregulation in APCs led to an enhanced adipocyte differentiation in two- and three-dimensional cell culture and increased expression of adipogenesis markers. Furthermore, SMIM10L1 knockdown cells showed a decreased expression of PTEN, pointing to a mutual crosstalk between PTEN and SMIM10L1. In line with these observations, SMIM10L1 knockdown cells showed increased activation of PI3K/AKT/mTOR signaling and concomitantly increased expression of the adipogenic transcription factor SREBP1. We computationally predicted an α-helical structure and membrane association of SMIM10L1. These results support a specific role for SMIM10L1 in regulating adipogenesis, potentially by increasing PI3K/AKT/mTOR signaling, which might be conducive to lipoma formation in pediatric patients with PHTS.

Multiomics reveal unique signatures of human epiploic adipose tissue related to systemic insulin resistance.

OBJECTIVE: Human white adipose tissue (AT) is a metabolically active organ with distinct depot-specific functions. Despite their locations close to the gastrointestinal tract, mesenteric AT and epiploic AT (epiAT) have only scarcely been investigated. Here, we aim to characterise these ATs in-depth and estimate their contribution to alterations in whole-body metabolism. DESIGN: Mesenteric, epiploic, omental and abdominal subcutaneous ATs were collected from 70 patients with obesity undergoing Roux-en-Y gastric bypass surgery. The metabolically well-characterised cohort included nine subjects with insulin sensitive (IS) obesity, whose AT samples were analysed in a multiomics approach, including methylome, transcriptome and proteome along with samples from subjects with insulin resistance (IR) matched for age, sex and body mass index (n=9). Findings implying differences between AT depots in these subgroups were validated in the entire cohort (n=70) by quantitative real-time PCR. RESULTS: While mesenteric AT exhibited signatures similar to those found in the omental depot, epiAT was distinct from all other studied fat depots. Multiomics allowed clear discrimination between the IS and IR states in all tissues. The highest discriminatory power between IS and IR was seen in epiAT, where profound differences in the regulation of developmental, metabolic and inflammatory pathways were observed. Gene expression levels of key molecules involved in AT function, metabolic homeostasis and inflammation revealed significant depot-specific differences with epiAT showing the highest expression levels. CONCLUSION: Multi-omics epiAT signatures reflect systemic IR and obesity subphenotypes distinct from other fat depots. Our data suggest a previously unrecognised role of human epiploic fat in the context of obesity, impaired insulin sensitivity and related diseases.

PTEN regulates adipose progenitor cell growth, differentiation, and replicative aging.

The tumor suppressor phosphatase and tensin homolog (PTEN) negatively regulates the insulin signaling pathway. Germline PTEN pathogenic variants cause PTEN hamartoma tumor syndrome (PHTS), associated with lipoma development in children. Adipose progenitor cells (APCs) lose their capacity to differentiate into adipocytes during continuous culture, whereas APCs from lipomas of patients with PHTS retain their adipogenic potential over a prolonged period. It remains unclear which mechanisms trigger this aberrant adipose tissue growth. To investigate the role of PTEN in adipose tissue development, we performed functional assays and RNA-Seq of control and PTEN knockdown APCs. Reduction of PTEN levels using siRNA or CRISPR led to enhanced proliferation and differentiation of APCs. Forkhead box protein O1 (FOXO1) transcriptional activity is known to be regulated by insulin signaling, and FOXO1 was downregulated at the mRNA level while its inactivation through phosphorylation increased. FOXO1 phosphorylation initiates the expression of the lipogenesis-activating transcription factor sterol regulatory element-binding protein 1 (SREBP1). SREBP1 levels were higher after PTEN knockdown and may account for the observed enhanced adipogenesis. To validate this, we overexpressed constitutively active FOXO1 in PTEN CRISPR cells and found reduced adipogenesis, accompanied by SREBP1 downregulation. We observed that PTEN CRISPR cells showed less senescence compared with controls and the senescence marker CDKN1A (p21) was downregulated in PTEN knockdown cells. Cellular senescence was the most significantly enriched pathway found in RNA-Seq of PTEN knockdown versus control cells. These results provide evidence that PTEN is involved in the regulation of APC proliferation, differentiation, and senescence, thereby contributing to aberrant adipose tissue growth in patients with PHTS.

Competing Endogenous RNA in Colorectal Cancer: An Analysis for Colon, Rectum, and Rectosigmoid Junction.

BACKGROUND: Colorectal cancer (CRC) is a heterogeneous cancer. Its treatment depends on its anatomical site and distinguishes between colon, rectum, and rectosigmoid junction cancer. This study aimed to identify diagnostic and prognostic biomarkers using networks of CRC-associated transcripts that can be built based on competing endogenous RNAs (ceRNA). METHODS: RNA expression and clinical information data of patients with colon, rectum, and rectosigmoid junction cancer were obtained from The Cancer Genome Atlas (TCGA). The RNA expression profiles were assessed through bioinformatics analysis, and a ceRNA was constructed for each CRC site. A functional enrichment analysis was performed to assess the functional roles of the ceRNA networks in the prognosis of colon, rectum, and rectosigmoid junction cancer. Finally, to verify the ceRNA impact on prognosis, an overall survival analysis was performed. RESULTS: The study identified various CRC site-specific prognosis biomarkers: hsa-miR-1271-5p, NRG1, hsa-miR-130a-3p, SNHG16, and hsa-miR-495-3p in the colon; E2F8 in the rectum and DMD and hsa-miR-130b-3p in the rectosigmoid junction. We also identified different biological pathways that highlight differences in CRC behavior at different anatomical sites, thus reinforcing the importance of correctly identifying the tumor site. CONCLUSIONS: Several potential prognostic markers for colon, rectum, and rectosigmoid junction cancer were found. CeRNA networks could provide better understanding of the differences between, and common factors in, prognosis of colon, rectum, and rectosigmoid junction cancer.

A workflow to identify novel proteins based on the direct mapping of peptide-spectrum-matches to genomic locations.

BACKGROUND: Small Proteins have received increasing attention in recent years. They have in particular been implicated as signals contributing to the coordination of bacterial communities. In genome annotations they are often missing or hidden among large numbers of hypothetical proteins because genome annotation pipelines often exclude short open reading frames or over-predict hypothetical proteins based on simple models. The validation of novel proteins, and in particular of small proteins (sProteins), therefore requires additional evidence. Proteogenomics is considered the gold standard for this purpose. It extends beyond established annotations and includes all possible open reading frames (ORFs) as potential sources of peptides, thus allowing the discovery of novel, unannotated proteins. Typically this results in large numbers of putative novel small proteins fraught with large fractions of false-positive predictions. RESULTS: We observe that number and quality of the peptide-spectrum matches (PSMs) that map to a candidate ORF can be highly informative for the purpose of distinguishing proteins from spurious ORF annotations. We report here on a workflow that aggregates PSM quality information and local context into simple descriptors and reliably separates likely proteins from the large pool of false-positive, i.e., most likely untranslated ORFs. We investigated the artificial gut microbiome model SIHUMIx, comprising eight different species, for which we validate 5114 proteins that have previously been annotated only as hypothetical ORFs. In addition, we identified 37 non-annotated protein candidates for which we found evidence at the proteomic and transcriptomic level. Half (19) of these candidates have close functional homologs in other species. Another 12 candidates have homologs designated as hypothetical proteins in other species. The remaining six candidates are short (< 100 AA) and are most likely bona fide novel proteins. CONCLUSIONS: The aggregation of PSM quality information for predicted ORFs provides a robust and efficient method to identify novel proteins in proteomics data. The workflow is in particular capable of identifying small proteins and frameshift variants. Since PSMs are explicitly mapped to genomic locations, it furthermore facilitates the integration of transcriptomics data and other sources of genome-level information.

Mutational mechanisms shaping the coding and noncoding genome of germinal center derived B-cell lymphomas.

B cells have the unique property to somatically alter their immunoglobulin (IG) genes by V(D)J recombination, somatic hypermutation (SHM) and class-switch recombination (CSR). Aberrant targeting of these mechanisms is implicated in lymphomagenesis, but the mutational processes are poorly understood. By performing whole genome and transcriptome sequencing of 181 germinal center derived B-cell lymphomas (gcBCL) we identified distinct mutational signatures linked to SHM and CSR. We show that not only SHM, but presumably also CSR causes off-target mutations in non-IG genes. Kataegis clusters with high mutational density mainly affected early replicating regions and were enriched for SHM- and CSR-mediated off-target mutations. Moreover, they often co-occurred in loci physically interacting in the nucleus, suggesting that mutation hotspots promote increased mutation targeting of spatially co-localized loci (termed hypermutation by proxy). Only around 1% of somatic small variants were in protein coding sequences, but in about half of the driver genes, a contribution of B-cell specific mutational processes to their mutations was found. The B-cell-specific mutational processes contribute to both lymphoma initiation and intratumoral heterogeneity. Overall, we demonstrate that mutational processes involved in the development of gcBCL are more complex than previously appreciated, and that B cell-specific mutational processes contribute via diverse mechanisms to lymphomagenesis.

MCPIP1 ribonuclease can bind and cleave AURKA mRNA in MYCN-amplified neuroblastoma cells.

The role of the inflammation-silencing ribonuclease, MCPIP1 (monocyte chemoattractant protein-induced protein 1), in neoplasia continuous to emerge. The ribonuclease can cleave not only inflammation-related transcripts but also some microRNAs (miRNAs) and viral RNAs. The suppressive effect of the protein has been hitherto suggested in breast cancer, clear cell renal cell carcinoma, osteosarcoma, and neuroblastoma. Our previous results have demonstrated a reduced levels of several oncogenes, as well as inhibited growth of neuroblastoma cells upon MCPIP1 overexpression. Here, we investigate the mechanisms underlying the suppression of MYCN proto-oncogene, bHLH transcription factor (MYCN)-amplified neuroblastoma cells overexpressing the MCPIP1 protein. We showed that the levels of several transcripts involved in cell cycle progression decreased in BE(2)-C and KELLY cells overexpressing MCPIP1 in a ribonucleolytic activity-dependent manner. However, RNA immunoprecipitation indicated that only AURKA mRNA (encoding for Aurora A kinase) interacts with the ribonuclease. Furthermore, the application of a luciferase assay suggested MCPIP1-dependent destabilization of the transcript. Further analyses demonstrated that the entire conserved region of AURKA seems to be indispensable for the interaction with the MCPIP1 protein. Additionally, we examined the effect of the ribonuclease overexpression on the miRNA expression profile in MYCN-amplified neuroblastoma cells. However, no significant alterations were observed. Our data indicate a key role of the binding and cleavage of the AURKA transcript in an MCPIP1-dependent suppressive effect on neuroblastoma cells.

HumanMetagenomeDB: a public repository of curated and standardized metadata for human metagenomes.

Metagenomics became a standard strategy to comprehend the functional potential of microbial communities, including the human microbiome. Currently, the number of metagenomes in public repositories is increasing exponentially. The Sequence Read Archive (SRA) and the MG-RAST are the two main repositories for metagenomic data. These databases allow scientists to reanalyze samples and explore new hypotheses. However, mining samples from them can be a limiting factor, since the metadata available in these repositories is often misannotated, misleading, and decentralized, creating an overly complex environment for sample reanalysis. The main goal of the HumanMetagenomeDB is to simplify the identification and use of public human metagenomes of interest. HumanMetagenomeDB version 1.0 contains metadata of 69 822 metagenomes. We standardized 203 attributes, based on standardized ontologies, describing host characteristics (e.g. sex, age and body mass index), diagnosis information (e.g. cancer, Crohn's disease and Parkinson), location (e.g. country, longitude and latitude), sampling site (e.g. gut, lung and skin) and sequencing attributes (e.g. sequencing platform, average length and sequence quality). Further, HumanMetagenomeDB version 1.0 metagenomes encompass 58 countries, 9 main sample sites (i.e. body parts), 58 diagnoses and multiple ages, ranging from just born to 91 years old. The HumanMetagenomeDB is publicly available at https://webapp.ufz.de/hmgdb/.

DNA methylation signature in blood mirrors successful weight-loss during lifestyle interventions: the CENTRAL trial.

BACKGROUND: One of the major challenges in obesity treatment is to explain the high variability in the individual's response to specific dietary and physical activity interventions. With this study, we tested the hypothesis that specific DNA methylation changes reflect individual responsiveness to lifestyle intervention and may serve as epigenetic predictors for a successful weight-loss. METHODS: We conducted an explorative genome-wide DNA methylation analysis in blood samples from 120 subjects (90% men, mean ± SD age = 49 ± 9 years, body mass-index (BMI) = 30.2 ± 3.3 kg/m2) from the 18-month CENTRAL randomized controlled trial who underwent either Mediterranean/low-carbohydrate or low-fat diet with or without physical activity. RESULTS: Analyses comparing male subjects with the most prominent body weight-loss (responders, mean weight change - 16%) vs. non-responders (+ 2.4%) (N = 10 each) revealed significant variation in DNA methylation of several genes including LRRC27, CRISP2, and SLFN12 (all adj. P < 1 × 10-5). Gene ontology analysis indicated that biological processes such as cell adhesion and molecular functions such as calcium ion binding could have an important role in determining the success of interventional therapies in obesity. Epigenome-wide association for relative weight-loss (%) identified 15 CpGs being negatively correlated with weight change after intervention (all combined P < 1 × 10- 4) including new and also known obesity candidates such as NUDT3 and NCOR2. A baseline DNA methylation score better predicted successful weight-loss [area under the curve (AUC) receiver operating characteristic (ROC) = 0.95-1.0] than predictors such as age and BMI (AUC ROC = 0.56). CONCLUSIONS: Body weight-loss following 18-month lifestyle intervention is associated with specific methylation signatures. Moreover, methylation differences in the identified genes could serve as prognostic biomarkers to predict a successful weight-loss therapy and thus contribute to advances in patient-tailored obesity treatment.

Master and servant: LINC00152 - a STAT3-induced long noncoding RNA regulates STAT3 in a positive feedback in human multiple myeloma.

BACKGROUND: The survival of INA-6 human multiple myeloma cells is strictly dependent upon the Interleukin-6-activated transcription factor STAT3. Although transcriptional analyses have revealed many genes regulated by STAT3, to date no protein-coding STAT3 target gene is known to mediate survival in INA-6 cells. Therefore, the aim here was to identify and analyze non-protein-coding STAT3 target genes. In addition to the oncogenic microRNA-21, we previously described five long noncoding RNAs (lncRNAs) induced by STAT3, named STAiRs. Here, we focus on STAT3-induced RNA 18 (STAiR18), an mRNA-like, long ncRNA that is duplicated in the human lineage. One STAiR18 locus is annotated as the already well described LINC00152/CYTOR, however, the other harbors the MIR4435-2HG gene and is, up to now, barely described. METHODS: CAPTURE-RNA-sequencing was used to analyze STAiR18 transcript architecture. To identify the STAiR18 and STAT3 phenotype, siRNA-based knockdowns were performed and microarrays were applied to identify their target genes. RNA-binding partners of STAiR18 were determined by Chromatin-Isolation-by-RNA-Purification (ChIRP) and subsequent sequencing. STAT3 expression in dependence of STAiR18 was investigated by immunoblots, chromatin- and RNA-immunoprecipitations. RESULTS: As identified by CAPTURE-RNA sequencing, a complex splice pattern originates from both STAiR18 loci, generating different transcripts. Knockdown of the most abundant STAiR18 isoforms dramatically decreased INA-6 cell vitality, suggesting a functional role in myeloma cells. Additionally, STAiR18 and STAT3 knockdowns yielded overlapping changes of transcription patterns in INA-6 cells, suggesting a close functional interplay between the two factors. Moreover, Chromatin isolation by RNA purification (ChIRP), followed by genome-wide RNA sequencing showed that STAiR18 associates specifically with the STAT3 primary transcript. Furthermore, the knockdown of STAiR18 reduced STAT3 levels on both the RNA and protein levels, suggesting a positive feedback between both molecules. Furthermore, STAiR18 knockdown changes the histone methylation status of the STAT3 locus, which explains the positive feedback and indicates that STAiR18 is an epigenetic modulator. CONCLUSION: Hence, STAiR18 is an important regulator of myeloma cell survival and is strongly associated with the oncogenic function of STAT3. The close functional interplay between STAT3 and STAiR18 suggests a novel principle of regulatory interactions between long ncRNAs and signaling pathways.

LOTTE-seq (Long hairpin oligonucleotide based tRNA high-throughput sequencing): specific selection of tRNAs with 3'-CCA end for high-throughput sequencing.

Transfer RNAs belong to the most abundant type of ribonucleic acid in the cell, and detailed investigations revealed correlations between alterations in the tRNA pool composition and certain diseases like breast cancer. However, currently available methods do not sample the entire tRNA pool or lack specificity for tRNAs. A specific disadvantage of such methods is that only full-length tRNAs are analysed, while tRNA fragments or incomplete cDNAs due to RT stops at modified nucleosides are lost. Another drawback in certain approaches is that the tRNA fraction has to be isolated and separated from high molecular weight RNA, resulting in considerable labour costs and loss of material. Based on a hairpin-shaped adapter oligonucleotide selective for tRNA transcripts, we developed a highly specific protocol for efficient and comprehensive high-throughput analysis of tRNAs that combines the benefits of existing methods and eliminates their disadvantages. Due to a 3'-TGG overhang, the adapter is specifically ligated to the tRNA 3'-CCA end. Reverse transcription prior to the ligation of a second adapter allows to include prematurely terminated cDNA products, increasing the number of tRNA reads. This strategy renders this approach a powerful and universal tool to analyse the tRNA pool of cells and organisms under different conditions in health and disease.

DREAM and RB cooperate to induce gene repression and cell-cycle arrest in response to p53 activation.

Most human cancers acquire mutations causing defects in the p53 signaling pathway. The tumor suppressor p53 becomes activated in response to genotoxic stress and is essential for arresting the cell cycle to facilitate DNA repair or to initiate apoptosis. p53-induced cell cycle-arrest is mediated by expression of the CDK inhibitor p21WAF1/Cip1, which prevents phosphorylation and inactivation of the pocket proteins RB, p130, and p107. In a hypophosphorylated state, pocket proteins bind to E2F factors forming RB-E2F and DREAM transcriptional repressor complexes. Here, we analyze the influence of RB and DREAM on p53-induced gene repression and cell-cycle arrest. We show that abrogation of DREAM function by knockout of the DREAM component LIN37 results in a reduced repression of cell-cycle genes. We identify the genes repressed by the p53-DREAM pathway and describe a set of genes that is downregulated by p53 independent of LIN37/DREAM. Most strikingly, p53-dependent repression of cell-cycle genes is completely abrogated in LIN37-/-;RB-/- cells leading to a loss of the G1/S checkpoint. Taken together, we show that DREAM and RB are key factors in the p53 signaling pathway to downregulate a large number of cell-cycle genes and to arrest the cell cycle at the G1/S transition.

Gene expression profile of human T cells following a single stimulation of peripheral blood mononuclear cells with anti-CD3 antibodies.

BACKGROUND: Anti-CD3 immunotherapy was initially approved for clinical use for renal transplantation rejection prevention. Subsequently, new generations of anti-CD3 antibodies have entered clinical trials for a broader spectrum of therapeutic applications, including cancer and autoimmune diseases. Despite their extensive use, little is known about the exact mechanism of these molecules, except that they are able to activate T cells, inducing an overall immunoregulatory and tolerogenic behavior. To better understand the effects of anti-CD3 antibodies on human T cells, PBMCs were stimulated, and then, we performed RNA-seq assays of enriched T cells to assess changes in their gene expression profiles. In this study, three different anti-CD3 antibodies were used for the stimulation: two recombinant antibody fragments, namely, a humanized and a chimeric FvFc molecule, and the prototype mouse mAb OKT3. RESULTS: Gene Ontology categories and individual immunoregulatory markers were compared, suggesting a similarity in modulated gene sets, mainly those for immunoregulatory and inflammatory terms. Upregulation of interleukin receptors, such as IL2RA, IL1R, IL12RB2, IL18R1, IL21R and IL23R, and of inhibitory molecules, such as FOXP3, CTLA4, TNFRSF18, LAG3 and PDCD1, were also observed, suggesting an inhibitory and exhausted phenotype. CONCLUSIONS: We used a deep transcriptome sequencing method for comparing three anti-CD3 antibodies in terms of Gene Ontology enrichment and immunological marker expression. The present data showed that both recombinant antibodies induced a compatible expression profile, suggesting that they might be candidates for a closer evaluation with respect to their therapeutic value. Moreover, the proposed methodology is amenable to be more generally applied for molecular comparison of cell receptor dependent antibody therapy.