an accurate pipeline for analysis of ngs data of small non coding rna

Motivations. The discovery of various families of small non-coding RNAs (sncRNAs) in recent years revealed the complexity of the regulation of gene expression at both transcriptional and post-transcriptional level. Of the numerous sncRNAs, microRNAs (miRNAs) constitute a large family of 19-23 nucleotides long RNAs that participate in a variety of processes, such as cell development and differentiation, apoptosis and stress responses to carcinogenesis. Computational analysis indicates that a unique miRNA can regulate hundreds of genes, underlining the potential influence of miRNAs in almost every cellular pathway. Deep sequencing technologies provides a powerful strategy to explore miRNA populations (miRNA-Seq) with high sensitivity and specificity. Different computational approaches have been developed to analyze miRNA-Seq data, allowing to identify known and novel miRNAs, perform differential expression analysis and predict putative miRNAs targets. We combined these algorithms into an analysis pipeline and tested it on data obtained from our experiments in cancer cell lines. Methods. The data obtained from the sequencer were filtered following several criteria. Since the sequence of the adapter is known, a Perl script was used to trim, from the raw data, the adaptors. The sequence reads were then filtered for quality and clustered to unique sequences to remove redundancy, retaining their individual read count information. Unique sequences 18 nucleotides or more in length were mapped, allowing up to one mismatch, on miRNA annotation according to miRBase version 18 using miRanalyzer. This detects the reads which correspond to known miRNAs, giving an estimation of expression level. miRBase repository is used because it offers information about mature (the mature sequence of known miRNAs), mature-star (the sequence which pairs with the mature miRNA in the miRNA secondary structure) and precursor miRNA sequences (sequence of the hairpin). miRNAs have been considered as expressed if they are detected at least 5 reads/sample. After detecting those that correspond to known miRNAs, the remaining reads were mapped to databases of transcribed sequences as mRNA and non-coding RNA (RFam). This step has two goals: (i) the number of matches can be viewed as a sample quality parameter (contamination of the RNA sample with degradation products and poly A tails) and (ii) it might be interesting to see which other known sncRNAs are in the sample. To predict novel miRNAs we used a probabilistic algorithm, miRDeep2, based on miRNA biogenesis model, to score compatibility of the position and frequency of sequenced RNA with the secondary structure of the miRNA precursor. This tool aligns sequencing reads to potential hairpin structures in a manner consistent with Dicer processing and assigns log-odds scores to measure the probability that hairpins are true miRNA precursors. To detect novel miRNAs by miRDeep2, a score cutoff corresponding to a prediction signal-to-noise ratio >10 was used. Identification of differentially expressed miRNAs was performed with the Bioconductor DESeq package. Starting from the expression values, the first step was to minimize the effect of the systematic technical variations, and then a negative binomial distribution model was used to test differential expression in deep sequencing datasets. Only miRNAs with a p-values less or equal to 0.05 and fold-change less or equal to -1.5 and greater or equal to 1.5 were considered as differentially expressed. Given the critical roles of miRNAs in regulating gene expression and cellular functions, we predicted their putative targets, intersecting results obtained from two resources, TargetScan and microRNA.org. TargetScan provide computationally predicted miRNA gene targets by searching for the presence of 8 and 7 mer sites that match the seed region of each miRNA, while microRNA.org target prediction incorporates current knowledge on target rules and on the use of a compendium of mammalian miRNAs. A further step of the analysis was to investigate nucleotide variations relative to the reference genome. To this purpose, preliminary steps were to reduce alignment artifacts and compute a more accurate quality estimation, removing biases due to sequencing cycle and preceding nucleotide. Further evidences were used to identify new miRNA variation sites: (i) Sequencing depth of variation sites should be equal to or larger than 5 reads per site, (ii) frequency of Single Nucleotide Variant occurrence >5% and (iii) variants not found in previous SNP annotation databases, like dbSNP. Results. We developed an accurate pipeline for integral analysis of next generation sequencing data of small RNA molecules. Based on solid statistical methods, this allows both detection of known miRNAs and prediction of new miRNAs, integrating steps for differential analysis, sequence analysis and target prediction. Acknowledgements Research support by: Fondazione con il Sud; Italian Association for Cancer Research; Italian Ministry for Education, University and Research; Regione Campania; University of Salerno; Fondazione Veronesi. Giorgio Giurato is a student of PhD School in Experimental and Clinic Medicine / Doctorate in Experimental Physiopathology and Neuroscience, Second University of Naples. Maria Ravo is supported by a 'Vladimir Ashkenazy' fellowship of Italian Association for Cancer Research. Concita Cantarella and Giovanni Nassa are fellows of Fondazione con il Sud

Direct regulation of microRNA biogenesis and expression by estrogen receptor beta in hormone-responsive breast cancer.

Estrogen effects on mammary epithelial and breast cancer (BC) cells are mediated by the nuclear receptors ERα and ERβ, transcription factors that display functional antagonism with each other, with ERβ acting as oncosuppressor and interfering with the effects of ERα on cell proliferation, tumor promotion and progression. Indeed, hormone-responsive, ERα+ BC cells often lack ERβ, which when present associates with a less aggressive clinical phenotype of the disease. Recent evidences point to a significant role of microRNAs (miRNAs) in BC, where specific miRNA expression profiles associate with distinct clinical and biological phenotypes of the lesion. Considering the possibility that ERβ might influence BC cell behavior via miRNAs, we compared miRNome expression in ERβ+ vs ERβ- hormone-responsive BC cells and found a widespread effect of this ER subtype on the expression pattern of these non-coding RNAs. More importantly, the expression pattern of 67 miRNAs, including 10 regulated by ERβ in BC cells, clearly distinguishes ERβ+, node-negative, from ERβ-, metastatic, mammary tumors. Molecular dissection of miRNA biogenesis revealed multiple mechanisms for direct regulation of this process by ERβ+ in BC cell nuclei. In particular, ERβ downregulates miR-30a by binding to two specific sites proximal to the gene and thereby inhibiting pri-miR synthesis. On the other hand, the receptor promotes miR-23b, -27b and 24-1 accumulation in the cell by binding in close proximity of the corresponding gene cluster and preventing in situ the inhibitory effects of ERα on pri-miR maturation by the p68/DDX5-Drosha microprocessor complex. These results indicate that cell autonomous regulation of miRNA expression is part of the mechanism of action of ERβ in BC cells and could contribute to establishment or maintenance of a less aggressive tumor phenotype mediated by this nuclear receptor

Effects of Oestrogen on MicroRNA Expression in Hormone-Responsive Breast Cancer Cells

Oestrogen receptor alpha (ERα) is a ligand-dependent transcription factor that mediates oestrogen effects in hormone-responsive cells. Following oestrogenic activation, ERα directly regulates the transcription of target genes via DNA binding. MicroRNAs (miRNAs) represent a class of small noncoding RNAs that function as negative regulators of protein-coding gene expression. They are found aberrantly expressed or mutated in cancer, suggesting their crucial role as either oncogenes or tumour suppressor genes. Here, we analysed changes in miRNA expression in response to oestrogen in hormone-responsive breast cancer MCF-7 and ZR-75.1 cells by microarray-mediated expression profiling. This led to the identification of 172 miRNAs up- or down-regulated by ERα in response to 17β-oestradiol, of which 52 are similarly regulated by the hormone in the two cell models investigated. To identify mechanisms by which ERα exerts its effects on oestrogen-responsive miRNA genes, the oestrogen-dependent miRNA expression profiles were integrated with global in vivo ERα binding site mapping in the genome by ChIP-Seq. In addition, data from miRNA and messenger RNA (mRNA) expression profiles obtained under identical experimental conditions were compared to identify relevant miRNA target transcripts. Results show that miRNAs modulated by ERα represent a novel genomic pathway to impact oestrogen-dependent processes that affect hormone-responsive breast cancer cell behaviour. MiRNome analysis in tumour tissues from breast cancer patients confirmed a strong association between expression of these small RNAs and clinical outcome of the disease, although this appears to involve only marginally the oestrogen-regulated miRNAs identified in this study

Loss of ISWI Function in Drosophila Nuclear Bodies Drives Cytoplasmic Redistribution of Drosophila TDP-43

Over the past decade, evidence has identified a link between protein aggregation, RNA biology, and a subset of degenerative diseases. An important feature of these disorders is the cytoplasmic or nuclear aggregation of RNA-binding proteins (RBPs). Redistribution of RBPs, such as the human TAR DNA-binding 43 protein (TDP-43) from the nucleus to cytoplasmic inclusions is a pathological feature of several diseases. Indeed, sporadic and familial forms of amyotrophic lateral sclerosis (ALS) and fronto-temporal lobar degeneration share as hallmarks ubiquitin-positive inclusions. Recently, the wide spectrum of neurodegenerative diseases characterized by RBPs functions' alteration and loss was collectively named proteinopathies. Here, we show that TBPH (TAR DNA-binding protein-43 homolog), the Drosophila ortholog of human TDP-43 TAR DNA-binding protein-43, interacts with the arcRNA hsr omega and with hsr omega-associated hnRNPs. Additionally, we found that the loss of the omega speckles remodeler ISWI (Imitation SWI) changes the TBPH sub-cellular localization to drive a TBPH cytoplasmic accumulation. Our results, hence, identify TBPH as a new component of omega speckles and highlight a role of chromatin remodelers in hnRNPs nuclear compartmentalization

Treatment of peripheral arterial disease in diabetes: a consensus of the Italian Societies of Diabetes (SID, AMD), Radiology (SIRM) and Vascular Endovascular Surgery (SICVE).

AbstractDiabetic foot (DF) is a chronic and highly disabling complication of diabetes. The prevalence of peripheral arterial disease (PAD) is high in diabetic patients and, associated or not with peripheral neuropathy (PN), can be found in 50% of cases of DF. It is worth pointing out that the number of major amputations in diabetic patients is still very high. Many PAD diabetic patients are not revascularised due to lack of technical expertise or, even worse, negative beliefs because of poor experience. This despite the progress obtained in the techniques of distal revascularisation that nowadays allow to reopen distal arteries of the leg and foot. Italy has one of the lowest prevalence rates of major amputations in Europe, and has a long tradition in the field of limb salvage by means of an aggressive approach in debridement, antibiotic therapy and distal revascularisation. Therefore, we believe it is appropriate to produce a consensus document concerning the treatment of PAD and limb salvage in diabetic patients, based on the Italian experience in this field, to share with the scientific community

Proinflammatory Modulation of the Surface and Cytokine Phenotype of Monocytes in Patients With Acute Charcot Foot

Despite increased information on the importance of an inappropriate inflammatory response in the acute Charcot process, there has been no previous attempt to define the specific pathways that mediate its pathogenesis. Here, the role played by monocytes was analyzed

Inhibition of histone methyltransferase DOT1L silences ER alpha gene and blocks proliferation of antiestrogen-resistant breast cancer cells

Breast cancer (BC) resistance to endocrine therapy results from constitutively active or aberrant estrogen receptor alpha (ER alpha) signaling, and ways to block ERa pathway in these tumors are sought after. We identified the H3K79 methyltransferase DOT1L as a novel cofactor of ER alpha in BC cell chromatin, where the two proteins colocalize to regulate estrogen target gene transcription. DOT1L blockade reduces proliferation of hormone-responsive BC cells in vivo and in vitro, consequent to cell cycle arrest and apoptotic cell death, with widespread effects on ER-dependent gene transcription, including ER alpha and FOXA1 gene silencing. Antiestrogen-resistant BC cells respond to DOT1L inhibition also in mouse xenografts, with reduction in ER alpha levels, H3K79 methylation, and tumor growth. These results indicate that DOT1L is an exploitable epigenetic target for treatment of endocrine therapy-resistant ER alpha-positive BCs