Evaluation of circulating tumor DNA by electropherogram analysis and methylome profiling in high-risk neuroblastomas.

Background: Liquid biopsy has emerged as a promising, non-invasive diagnostic approach in oncology because the analysis of circulating tumor DNA (ctDNA) reflects the precise status of the disease at diagnosis, progression, and response to treatment. DNA methylation profiling is also a potential solution for sensitive and specific detection of many cancers. The combination of both approaches, DNA methylation analysis from ctDNA, provides an extremely useful and minimally invasive tool with high relevance in patients with childhood cancer. Neuroblastoma is an extracranial solid tumor most common in children and responsible for up to 15% of cancer-related deaths. This high death rate has prompted the scientific community to search for new therapeutic targets. DNA methylation also offers a new source for identifying these molecules. However, the limited blood sample size which can be obtained from children with cancer and the fact that ctDNA content may occasionally be diluted by non-tumor cell-free DNA (cfDNA) complicate optimal quantities of material for high-throughput sequencing studies. Methods: In this article, we present an improved method for ctDNA methylome studies of blood-derived plasma from high-risk neuroblastoma patients. We assessed the electropherogram profiles of ctDNA-containing samples suitable for methylome studies, using 10 ng of plasma-derived ctDNA from 126 samples of 86 high-risk neuroblastoma patients, and evaluated several bioinformatic approaches to analyze DNA methylation sequencing data. Results: We demonstrated that enzymatic methyl-sequencing (EM-seq) outperformed bisulfite conversion-based method, based on the lower proportion of PCR duplicates and the higher percentage of unique mapping reads, mean coverage, and genome coverage. The analysis of the electropherogram profiles revealed the presence of nucleosomal multimers, and occasionally high molecular weight DNA. We established that 10% content of the mono-nucleosomal peak is sufficient ctDNA for successful detection of copy number variations and methylation profiles. Quantification of mono-nucleosomal peak also showed that samples at diagnosis contained a higher amount of ctDNA than relapse samples. Conclusions: Our results refine the use of electropherogram profiles to optimize sample selection for subsequent high-throughput analysis and support the use of liquid biopsy followed by enzymatic conversion of unmethylated cysteines to assess the methylomes of neuroblastoma patients.

cvlr: finding heterogeneously methylated genomic regions using ONT reads.

Summary: Nanopore reads encode information on the methylation status of cytosines in CpG dinucleotides. The length of the reads makes it comparatively easy to look at patterns consisting of multiple loci; here, we exploit this property to search for regions where one can define subpopulations of molecules based on methylation patterns. As an example, we run our clustering algorithm on known imprinted genes; we also scan chromosome 15 looking for windows corresponding to heterogeneous methylation. Our software can also compute the covariance of methylation across these regions while keeping into account the mixture of different types of reads. Availability and implementation: https://github.com/EmanueleRaineri/cvlr. Contact: simon.heath@cnag.crg.eu. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Liquidhope: methylome and genomic profiling from very limited quantities of plasma-derived DNA.

Analysis of the methylome of tumor cell-free deoxyribonucleic acid (DNA; cfDNA) has emerged as a powerful non-invasive technique for cancer subtyping and prognosis. However, its application is frequently hampered by the quality and total cfDNA yield. Here, we demonstrate the feasibility of very low-input cfDNA for whole-methylome and copy-number profiling studies using enzymatic conversion of unmethylated cysteines [enzymatic methyl-seq (EM-seq)] to better preserve DNA integrity. We created a model for predicting genomic subtyping and prognosis with high accuracy. We validated our tool by comparing whole-genome CpG sequencing with in situ cohorts generated with bisulfite conversion and array hybridization, demonstrating that, despite the different techniques and sample origins, information on cfDNA methylation is comparable with in situ cohorts. Our findings support use of liquid biopsy followed by EM-seq to assess methylome of cancer patients, enabling validation in external cohorts. This advance is particularly relevant for rare cancers like neuroblastomas where liquid-biopsy volume is restricted by ethical regulations in pediatric patients.

A method for multiplexed full-length single-molecule sequencing of the human mitochondrial genome.

Methods to reconstruct the mitochondrial DNA (mtDNA) sequence using short-read sequencing come with an inherent bias due to amplification and mapping. They can fail to determine the phase of variants, to capture multiple deletions and to cover the mitochondrial genome evenly. Here we describe a method to target, multiplex and sequence at high coverage full-length human mitochondrial genomes as native single-molecules, utilizing the RNA-guided DNA endonuclease Cas9. Combining Cas9 induced breaks, that define the mtDNA beginning and end of the sequencing reads, as barcodes, we achieve high demultiplexing specificity and delineation of the full-length of the mtDNA, regardless of the structural variant pattern. The long-read sequencing data is analysed with a pipeline where our custom-developed software, baldur, efficiently detects single nucleotide heteroplasmy to below 1%, physically determines phase and can accurately disentangle complex deletions. Our workflow is a tool for studying mtDNA variation and will accelerate mitochondrial research.

COVID-19 Vaccination-Induced Cholangiopathy and Autoimmune Hepatitis: A Series of Two Cases.

The coronavirus disease 2019 (COVID-19) pandemic has been associated with significant morbidity and mortality. Following the introduction of vaccines, various side effects have been reported. Whilst those reported may be attributed to the vaccine itself, at times, it may simply incite an immunological phenomenon. We present a case series of two patients who presented with symptoms of yellowing of the eyes and the skin along with fatigue, and tiredness, following vaccination for COVID-19. The diagnosis of post COVID-19-vaccination related hepatitis is one of the fewer, less understood, yet reported side effects associated with significant morbidity. The diagnosis of COVID-19 vaccination-related cholangitis is an outcome reported here for the first time to the best of our knowledge. It was alarming that both patients did not have any significant past history of medical ailments. A prompt assessment followed by investigations including liver biopsy assisted in a timely understanding of the phenomenon with complete resolution of the symptoms.

DeepMP: a deep learning tool to detect DNA base modifications on Nanopore sequencing data.

MOTIVATION: DNA methylation plays a key role in a variety of biological processes. Recently, Nanopore long-read sequencing has enabled direct detection of these modifications. As a consequence, a range of computational methods have been developed to exploit Nanopore data for methylation detection. However, current approaches rely on a human-defined threshold to detect the methylation status of a genomic position and are not optimized to detect sites methylated at low frequency. Furthermore, most methods use either the Nanopore signals or the basecalling errors as the model input and do not take advantage of their combination. RESULTS: Here, we present DeepMP, a convolutional neural network-based model that takes information from Nanopore signals and basecalling errors to detect whether a given motif in a read is methylated or not. Besides, DeepMP introduces a threshold-free position modification calling model sensitive to sites methylated at low frequency across cells. We comprehensively benchmarked DeepMP against state-of-the-art methods on Escherichia coli, human and pUC19 datasets. DeepMP outperforms current approaches at read-based and position-based methylation detection across sites methylated at different frequencies in the three datasets. AVAILABILITY AND IMPLEMENTATION: DeepMP is implemented and freely available under MIT license at https://github.com/pepebonet/DeepMP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gender specific airway gene expression in COPD sub-phenotypes supports a role of mitochondria and of different types of leukocytes.

Chronic obstructive pulmonary disease (COPD) is a destructive inflammatory disease and the genes expressed within the lung are crucial to its pathophysiology. We have determined the RNAseq transcriptome of bronchial brush cells from 312 stringently defined ex-smoker patients. Compared to healthy controls there were for males 40 differentially expressed genes (DEGs) and 73 DEGs for females with only 26 genes shared. The gene ontology (GO) term "response to bacterium" was shared, with several different DEGs contributing in males and females. Strongly upregulated genes TCN1 and CYP1B1 were unique to males and females, respectively. For male emphysema (E)-dominant and airway disease (A)-dominant COPD (defined by computed tomography) the term "response to stress" was found for both sub-phenotypes, but this included distinct up-regulated genes for the E-sub-phenotype (neutrophil-related CSF3R, CXCL1, MNDA) and for the A-sub-phenotype (macrophage-related KLF4, F3, CD36). In E-dominant disease, a cluster of mitochondria-encoded (MT) genes forms a signature, able to identify patients with emphysema features in a confirmation cohort. The MT-CO2 gene is upregulated transcriptionally in bronchial epithelial cells with the copy number essentially unchanged. Both MT-CO2 and the neutrophil chemoattractant CXCL1 are induced by reactive oxygen in bronchial epithelial cells. Of the female DEGs unique for E- and A-dominant COPD, 88% were detected in females only. In E-dominant disease we found a pronounced expression of mast cell-associated DEGs TPSB2, TPSAB1 and CPA3. The differential genes discovered in this study point towards involvement of different types of leukocytes in the E- and A-dominant COPD sub-phenotypes in males and females.

Impact of DNA methylation on 3D genome structure.

Determining the effect of DNA methylation on chromatin structure and function in higher organisms is challenging due to the extreme complexity of epigenetic regulation. We studied a simpler model system, budding yeast, that lacks DNA methylation machinery making it a perfect model system to study the intrinsic role of DNA methylation in chromatin structure and function. We expressed the murine DNA methyltransferases in Saccharomyces cerevisiae and analyzed the correlation between DNA methylation, nucleosome positioning, gene expression and 3D genome organization. Despite lacking the machinery for positioning and reading methylation marks, induced DNA methylation follows a conserved pattern with low methylation levels at the 5' end of the gene increasing gradually toward the 3' end, with concentration of methylated DNA in linkers and nucleosome free regions, and with actively expressed genes showing low and high levels of methylation at transcription start and terminating sites respectively, mimicking the patterns seen in mammals. We also see that DNA methylation increases chromatin condensation in peri-centromeric regions, decreases overall DNA flexibility, and favors the heterochromatin state. Taken together, these results demonstrate that methylation intrinsically modulates chromatin structure and function even in the absence of cellular machinery evolved to recognize and process the methylation signal.

Lung microbiome composition and bronchial epithelial gene expression in patients with COPD versus healthy individuals: a bacterial 16S rRNA gene sequencing and host transcriptomic analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is associated with airway inflammation and bacterial dysbiosis. The relationship between the airway microbiome and bronchial gene expression in COPD is poorly understood. We aimed to identify differences in the airway microbiome from bronchial brushings in patients with COPD and healthy individuals and to investigate whether any distinguishing bacteria are related to bronchial gene expression. METHODS: For this 16S rRNA gene sequencing and host transcriptomic analysis, individuals aged 45-75 years with mild-to-moderate COPD either receiving or not receiving inhaled corticosteroids and healthy individuals in the same age group were recruited as part of the Emphysema versus Airways Disease (EvA) consortium from nine centres in the UK, Germany, Italy, Poland, and Hungary. Individuals underwent clinical characterisation, spirometry, CT scans, and bronchoscopy. From bronchoscopic bronchial brush samples, we obtained the microbial profiles using 16S rRNA gene sequencing and gene expression using the RNA-Seq technique. We analysed bacterial genera relative abundance and the associations between genus abundance and clinical characteristics or between genus abundance and host lung transcriptional signals in patients with COPD versus healthy individuals, and in patients with COPD with versus without inhaled corticosteroids treatment. FINDINGS: Between February, 2009, and March, 2012, we obtained brush samples from 574 individuals. We used 546 of 574 samples for analysis, including 207 from healthy individuals and 339 from patients with COPD (192 with inhaled corticosteroids and 147 without). The bacterial genera that most strongly distinguished patients with COPD from healthy individuals were Prevotella (median relative abundance 33·5%, IQR 14·5-49·4, in patients with COPD vs 47·7%, 31·1-60·7, in healthy individuals; p<0·0001), Streptococcus (8·6%, 3·8-15·8, vs 5·3%, 3·0-10·1; p<0·0001), and Moraxella (0·05%, 0·02-0·14, vs 0·02%, 0-0·07; p<0·0001). Prevotella abundance was inversely related to COPD severity in terms of symptoms and positively related to lung function and exercise capacity. 446 samples had assessable RNA-seq data, 257 from patients with COPD (136 with inhaled corticosteroids and 121 without) and 189 from healthy individuals. No significant associations were observed between lung transcriptional signals from bronchial brushings and abundance of bacterial genera in patients with COPD without inhaled corticosteroids treatment and in healthy individuals. In patients with COPD treated with inhaled corticosteroids, Prevotella abundance was positively associated with expression of epithelial genes involved in tight junction promotion and Moraxella abundance was associated with expression of the IL-17 and TNF inflammatory pathways. INTERPRETATION: With increasing severity of COPD, the airway microbiome is associated with decreased abundance of Prevotella and increased abundance of Moraxella in concert with downregulation of genes promoting epithelial defence and upregulation of pro-inflammatory genes associated with inhaled corticosteroids use. Our work provides further insight in understanding the relationship between microbiome alteration and host inflammatory response, which might lead to novel therapeutic strategies for COPD. FUNDING: EU Seventh Framework Programme, National Institute for Health Research.

Blood eosinophil count and airway epithelial transcriptome relationships in COPD versus asthma.

BACKGROUND: Whether the clinical or pathophysiologic significance of the "treatable trait" high blood eosinophil count in COPD is the same as for asthma remains controversial. We sought to determine the relationship between the blood eosinophil count, clinical characteristics and gene expression from bronchial brushings in COPD and asthma. METHODS: Subjects were recruited into a COPD (emphysema versus airway disease [EvA]) or asthma cohort (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes, U-BIOPRED). We determined gene expression using RNAseq in EvA (n = 283) and Affymetrix microarrays in U-BIOPRED (n = 85). We ran linear regression analysis of the bronchial brushings transcriptional signal versus blood eosinophil counts as well as differential expression using a blood eosinophil > 200 cells/µL as a cut-off. The false discovery rate was controlled at 1% (with continuous values) and 5% (with dichotomized values). RESULTS: There were no differences in age, gender, lung function, exercise capacity and quantitative computed tomography between eosinophilic versus noneosinophilic COPD cases. Total serum IgE was increased in eosinophilic asthma and COPD. In EvA, there were 12 genes with a statistically significant positive association with the linear blood eosinophil count, whereas in U-BIOPRED, 1197 genes showed significant associations (266 positive and 931 negative). The transcriptome showed little overlap between genes and pathways associated with blood eosinophil counts in asthma versus COPD. Only CST1 was common to eosinophilic asthma and COPD and was replicated in independent cohorts. CONCLUSION: Despite shared "treatable traits" between asthma and COPD, the molecular mechanisms underlying these clinical entities are predominately different.

Nucleosome Dynamics: a new tool for the dynamic analysis of nucleosome positioning.

We present Nucleosome Dynamics, a suite of programs integrated into a virtual research environment and created to define nucleosome architecture and dynamics from noisy experimental data. The package allows both the definition of nucleosome architectures and the detection of changes in nucleosomal organization due to changes in cellular conditions. Results are displayed in the context of genomic information thanks to different visualizers and browsers, allowing the user a holistic, multidimensional view of the genome/transcriptome. The package shows good performance for both locating equilibrium nucleosome architecture and nucleosome dynamics and provides abundant useful information in several test cases, where experimental data on nucleosome position (and for some cases expression level) have been collected for cells under different external conditions (cell cycle phase, yeast metabolic cycle progression, changes in nutrients or difference in MNase digestion level). Nucleosome Dynamics is a free software and is provided under several distribution models.

Whole-genome DNA hyper-methylation in iPSC-derived dopaminergic neurons from Parkinson's disease patients.

BACKGROUND: Parkinson's disease (PD) is characterized by the loss of midbrain dopaminergic neurons (DAn). Previously, we described the presence of DNA hyper- and hypo-methylation alterations in induced pluripotent stem cells (iPSC)-derived DAn from PD patients using the Illumina 450K array which prominently covers gene regulatory regions. METHODS: To expand and contextualize previous findings, we performed the first whole-genome DNA bisulfite sequencing (WGBS) using iPSC-derived DAn from representative PD subjects: one sporadic PD (sPD) patient, one monogenic LRRK2-associated PD patient (L2PD), and one control. RESULTS: At the whole-genome level, we detected global DNA hyper-methylation in the PD which was similarly spread across the genome in both sPD and L2PD and mostly affected intergenic regions. CONCLUSION: This study implements previous epigenetic knowledge in PD at a whole genome level providing the first comprehensive and unbiased CpG DNA methylation data using iPSC-derived DAn from PD patients. Our results indicate that DAn from monogenic or sporadic PD exhibit global DNA hyper-methylation changes. Findings from this exploratory study are to be validated in further studies analyzing other PD cell models and patient tissues.

PD-1 signaling affects cristae morphology and leads to mitochondrial dysfunction in human CD8+ T lymphocytes.

BACKGROUND: Binding of the programmed death-1 (PD-1) receptor to its ligands (PD-L1/2) transduces inhibitory signals that promote exhaustion of activated T cells. Blockade of the PD-1 pathway is widely used for cancer treatment, yet the inhibitory signals transduced by PD-1 in T cells remain elusive. METHODS: Expression profiles of human CD8+ T cells in resting, activated (CD3 + CD28) and PD-1-stimulated cells (CD3 + CD28 + PD-L1-Fc) conditions were evaluated by RNA-seq. Bioinformatic analyses were used to identify signaling pathways differentially regulated in PD-1-stimulated cells. Metabolic analyses were performed with SeaHorse technology, and mitochondrial ultrastructure was determined by transmission electron microscopy. PD-1-regulated mitochondrial genes were silenced using short-hairpin RNA in primary cells. Blue native gel electrophoresis was used to determine respiratory supercomplex assembly. RESULTS: PD-1 engagement in human CD8+ T cells triggers a specific, progressive genetic program different from that found in resting cells. Gene ontology identified metabolic processes, including glycolysis and oxidative phosphorylation (OXPHOS), as the main pathways targeted by PD-1. We observed severe functional and structural alterations in the mitochondria of PD-1-stimulated cells, including a reduction in the number and length of mitochondrial cristae. These cristae alterations were associated with reduced expression of CHCHD3 and CHCHD10, two proteins that form part of the mitochondrial contact site and cristae organizing system (MICOS). Although PD-1-stimulated cells showed severe cristae alterations, assembly of respiratory supercomplexes was unexpectedly greater in these cells than in activated T cells. CHCHD3 silencing in primary CD8+ T cells recapitulated some effects induced by PD-1 stimulation, including reduced mitochondrial polarization and interferon-γ production following T cell activation with anti-CD3 and -CD28 activating antibodies. CONCLUSIONS: Our results suggest that mitochondria are the main targets of PD-1 inhibitory activity. PD-1 reprograms CD8+ T cell metabolism for efficient use of fatty acid oxidation; this mitochondrial phenotype might explain the long-lived phenotype of PD-1-engaged T cells.

Systems analysis reveals complex biological processes during virus infection fate decisions.

The processes and mechanisms of virus infection fate decisions that are the result of a dynamic virus-immune system interaction with either an efficient effector response and virus elimination or an alleviated immune response and chronic infection are poorly understood. Here, we characterized the host response to acute and chronic lymphocytic choriomeningitis virus (LCMV) infections by gene coexpression network analysis of time-resolved splenic transcriptomes. First, we found an early attenuation of inflammatory monocyte/macrophage prior to the onset of T cell exhaustion, and second, a critical role of the XCL1-XCR1 communication axis during the functional adaptation of the T cell response to the chronic infection state. These findings not only reveal an important feedback mechanism that couples T cell exhaustion with the maintenance of a lower level of effector T cell response but also suggest therapy options to better control virus levels during the chronic infection phase.

Linking Cell Dynamics With Gene Coexpression Networks to Characterize Key Events in Chronic Virus Infections.

The host immune response against infection requires the coordinated action of many diverse cell subsets that dynamically adapt to a pathogen threat. Due to the complexity of such a response, most immunological studies have focused on a few genes, proteins, or cell types. With the development of "omic"-technologies and computational analysis methods, attempts to analyze and understand complex system dynamics are now feasible. However, the decomposition of transcriptomic data sets generated from complete organs remains a major challenge. Here, we combined Weighted Gene Coexpression Network Analysis (WGCNA) and Digital Cell Quantifier (DCQ) to analyze time-resolved mouse splenic transcriptomes in acute and chronic Lymphocytic Choriomeningitis Virus (LCMV) infections. This enabled us to generate hypotheses about complex immune functioning after a virus-induced perturbation. This strategy was validated by successfully predicting several known immune phenomena, such as effector cytotoxic T lymphocyte (CTL) expansion and exhaustion. Furthermore, we predicted and subsequently verified experimentally macrophage-CD8 T cell cooperativity and the participation of virus-specific CD8+ T cells with an early effector transcriptome profile in the host adaptation to chronic infection. Thus, the linking of gene expression changes with immune cell kinetics provides novel insights into the complex immune processes within infected tissues.

Chromatin-Based Classification of Genetically Heterogeneous AMLs into Two Distinct Subtypes with Diverse Stemness Phenotypes.

Global investigation of histone marks in acute myeloid leukemia (AML) remains limited. Analyses of 38 AML samples through integrated transcriptional and chromatin mark analysis exposes 2 major subtypes. One subtype is dominated by patients with NPM1 mutations or MLL-fusion genes, shows activation of the regulatory pathways involving HOX-family genes as targets, and displays high self-renewal capacity and stemness. The second subtype is enriched for RUNX1 or spliceosome mutations, suggesting potential interplay between the 2 aberrations, and mainly depends on IRF family regulators. Cellular consequences in prognosis predict a relatively worse outcome for the first subtype. Our integrated profiling establishes a rich resource to probe AML subtypes on the basis of expression and chromatin data.

A FBN1 3'UTR mutation variant is associated with endoplasmic reticulum stress in aortic aneurysm in Marfan syndrome.

Marfan syndrome (MFS) is caused by mutations in the protein fibrillin-1 (FBN1) which affects the integrity of connective tissue elastic fibres. The most severe clinical outcome is the formation of ascending aortic aneurysms. FBN1 mutations are extremely variable and the prediction of disease phenotype and aortic risk is challenging under the prevailing mutation type classification. Finding a better correlation between mutation type and disease development is crucial for patient treatment. By mRNA sequencing of cultured vascular smooth muscle cells derived from control subjects and from the dilated and non-dilated aortic tunica media of MFS patients, we found a scarcely described FBN1 3'UTR mutation. This mutation was accompanied by a clear gene ontological endoplasmic reticulum (ER) stress response in the non-dilated aortic zone, which was confirmed by the increased transcriptional expression of MANF, HSPA5, SEL1L, DDIT3/CHOP and CRELD2 as well as protein expression levels of BiP/GRP78, CHOP and sXBP1. Moreover, the ER stress response was accompanied by a decrease in the phosphorylation levels of the protein translation regulator elF2α. In conclusion, we here identify a 3'UTR mutation of FBN1 in MFS patients, whose molecular mechanism suggest the involvement of the ER stress response in the formation of the aortic aneurysm. Our results emphasise the importance of mutations in non-coding regions and their resulting molecular mechanisms in the development of connective tissue diseases with impact on the cardiovascular system.

gemBS: high throughput processing for DNA methylation data from bisulfite sequencing.

MOTIVATION: DNA methylation is essential for normal embryogenesis and development in mammals and can be captured at single base pair resolution by whole genome bisulfite sequencing (WGBS). Current available analysis tools are becoming rapidly outdated as they lack sensible functionality and efficiency to handle large amounts of data now commonly created. RESULTS: We developed gemBS, a fast high-throughput bioinformatics pipeline specifically designed for large scale BS-Seq analysis that combines a high performance BS-mapper (GEM3) and a variant caller specifically for BS-Seq data (BScall). gemBS provides genotype information and methylation estimates for all genomic cytosines in different contexts (CpG and non-CpG) and a set of quality reports for comprehensive and reproducible analysis. gemBS is highly modular and can be easily automated, while producing robust and accurate results. AVAILABILITY AND IMPLEMENTATION: gemBS is released under the GNU GPLv3+ license. Source code and documentation are freely available from www.statgen.cat/gemBS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Epigenetic regulation of gene expression in Chinese Hamster Ovary cells in response to the changing environment of a batch culture.

The existence of dynamic cellular phenotypes in changing environmental conditions is of major interest for cell biologists who aim to understand the mechanism and sequence of regulation of gene expression. In the context of therapeutic protein production by Chinese Hamster Ovary (CHO) cells, a detailed temporal understanding of cell-line behavior and control is necessary to achieve a more predictable and reliable process performance. Of particular interest are data on dynamic, temporally resolved transcriptional regulation of genes in response to altered substrate availability and culture conditions. In this study, the gene transcription dynamics throughout a 9-day batch culture of CHO cells was examined by analyzing histone modifications and gene expression profiles in regular 12- and 24-hr intervals, respectively. Three levels of regulation were observed: (a) the presence or absence of DNA methylation in the promoter region provides an ON/OFF switch; (b) a temporally resolved correlation is observed between the presence of active transcription- and promoter-specific histone marks and the expression level of the respective genes; and (c) a major mechanism of gene regulation is identified by interaction of coding genes with long non-coding RNA (lncRNA), as observed in the regulation of the expression level of both neighboring coding/lnc gene pairs and of gene pairs where the lncRNA is able to form RNA-DNA-DNA triplexes. Such triplex-forming regions were predominantly found in the promoter or enhancer region of the targeted coding gene. Significantly, the coding genes with the highest degree of variation in expression during the batch culture are characterized by a larger number of possible triplex-forming interactions with differentially expressed lncRNAs. This indicates a specific role of lncRNA-triplexes in enabling rapid and large changes in transcription. A more comprehensive understanding of these regulatory mechanisms will provide an opportunity for new tools to control cellular behavior and to engineer enhanced phenotypes.

Differential expression of long non-coding RNAs are related to proliferation and histological diversity in follicular lymphomas.

Long non-coding RNAs (lncRNAs) comprise a family of non-coding transcripts that are emerging as relevant gene expression regulators of different processes, including tumour development. To determine the possible contribution of lncRNA to the pathogenesis of follicular lymphoma (FL) we performed RNA-sequencing at high depth sequencing in primary FL samples ranging from grade 1-3A to aggressive grade 3B variants using unpurified (n = 16) and purified (n = 12) tumour cell suspensions from nodal samples. FL grade 3B had a significantly higher number of differentially expressed lncRNAs (dif-lncRNAs) with potential target coding genes related to cell cycle regulation. Nine out of the 18 selected dif-lncRNAs were validated by quantitative real time polymerase chain reaction in an independent series (n = 43) of FL. RP4-694A7.2 was identified as the top deregulated lncRNA potentially involved in cell proliferation. RP4-694A7.2 silencing in the WSU-FSCCL FL cell line reduced cell proliferation due to a block in the G1/S phase. The relationship between RP4-694A7.2 and proliferation was confirmed in primary samples as its expression levels positively related to the Ki-67 proliferation index. In summary, lncRNAs are differentially expressed across the clinico-biological spectrum of FL and a subset of them, related to cell cycle, may participate in cell proliferation regulation in these tumours.