Protein and Genetic Composition of Four Chromatin Types in Drosophila melanogaster Cell Lines.

BACKGROUND: Recently, we analyzed genome-wide protein binding data for the Drosophila cell lines S2, Kc, BG3 and Cl.8 (modENCODE Consortium) and identified a set of 12 proteins enriched in the regions corresponding to interbands of salivary gland polytene chromosomes. Using these data, we developed a bioinformatic pipeline that partitioned the Drosophila genome into four chromatin types that we hereby refer to as aquamarine, lazurite, malachite and ruby. RESULTS: Here, we describe the properties of these chromatin types across different cell lines. We show that aquamarine chromatin tends to harbor transcription start sites (TSSs) and 5' untranslated regions (5'UTRs) of the genes, is enriched in diverse "open" chromatin proteins, histone modifications, nucleosome remodeling complexes and transcription factors. It encompasses most of the tRNA genes and shows enrichment for non-coding RNAs and miRNA genes. Lazurite chromatin typically encompasses gene bodies. It is rich in proteins involved in transcription elongation. Frequency of both point mutations and natural deletion breakpoints is elevated within lazurite chromatin. Malachite chromatin shows higher frequency of insertions of natural transposons. Finally, ruby chromatin is enriched for proteins and histone modifications typical for the "closed" chromatin. Ruby chromatin has a relatively low frequency of point mutations and is essentially devoid of miRNA and tRNA genes. Aquamarine and ruby chromatin types are highly stable across cell lines and have contrasting properties. Lazurite and malachite chromatin types also display characteristic protein composition, as well as enrichment for specific genomic features. We found that two types of chromatin, aquamarine and ruby, retain their complementary protein patterns in four Drosophila cell lines.

ArrayExpress update--simplifying data submissions.

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is an international functional genomics database at the European Bioinformatics Institute (EMBL-EBI) recommended by most journals as a repository for data supporting peer-reviewed publications. It contains data from over 7000 public sequencing and 42,000 array-based studies comprising over 1.5 million assays in total. The proportion of sequencing-based submissions has grown significantly over the last few years and has doubled in the last 18 months, whilst the rate of microarray submissions is growing slightly. All data in ArrayExpress are available in the MAGE-TAB format, which allows robust linking to data analysis and visualization tools and standardized analysis. The main development over the last two years has been the release of a new data submission tool Annotare, which has reduced the average submission time almost 3-fold. In the near future, Annotare will become the only submission route into ArrayExpress, alongside MAGE-TAB format-based pipelines. ArrayExpress is a stable and highly accessed resource. Our future tasks include automation of data flows and further integration with other EMBL-EBI resources for the representation of multi-omics data.

Plasma exosomal miR-21 and miR-181a differentiates follicular from papillary thyroid cancer.

Thyroid cancer (TC) is the most common endocrine malignancy and its incidence has increased over the last few decades. As has been revealed by a number of studies, TC tissue's micro-RNA (miRNA) profile may reflect histological features and the clinical behavior of tumor. However, alteration of the miRNA profile of plasma exosomes associated with TC development has to date not been explored. We isolated exosomes from plasma and assayed their characteristics using laser diffraction particle size analysis, atomic force microscopy, and western blotting. Next, we profiled cancer-associated miRNAs in plasma exosomes obtained from papillary TC patients, before and after surgical removal of the tumor. The diagnostic value of selected miRNAs was evaluated in a large cohort of patients displaying different statuses of thyroid nodule disease. MiRNA assessment was performed by RT-qPCR. In total, 60 patients with different types of thyroid nodal pathology were included in the study. Our results revealed that the development of papillary TC is associated with specific changes in exosomal miRNA profiles; this phenomenon can be used for differential diagnostics. MiRNA-31 was found to be over-represented in the plasma exosomes of patients with papillary TC vs. benign tumors, while miRNA-21 helped to distinguish between benign tumors and follicular TC. MiRNA-21 and MiRNA-181a-5p were found to be expressed reciprocally in the exosomes of patients with papillary and follicular TC, and their comparative assessment may help to distinguish between these types of TC with 100 % sensitivity and 77 % specificity.

miRNA profiling, detection of BRAF V600E mutation and RET-PTC1 translocation in patients from Novosibirsk oblast (Russia) with different types of thyroid tumors.

BACKGROUND: The postoperative typing of thyroid lesions, which is instrumental in adequate patient treatment, is currently based on histologic examination. However, it depends on pathologist's qualification and can be difficult in some cases. Numerous studies have shown that molecular markers such as microRNAs and somatic mutations may be useful to assist in these cases, but no consensus exists on the set of markers that is optimal for that purpose. The aim of the study was to discriminate between different thyroid neoplasms by RT-PCR, using a limited set of microRNAs selected from literature. METHODS: By RT-PCR we evaluated the relative levels of 15 microRNAs (miR-221, -222, -146b, -181b, -21, -187, -199b, -144, -192, -200a, -200b, -205, -141, -31, -375) and the presence of BRAF(V600E) mutation and RET-PTC1 translocation in surgically resected lesions from 208 patients from Novosibirsk oblast (Russia) with different types of thyroid neoplasms. Expression of each microRNA was normalized to adjacent non-tumor tissue. Three pieces of lesion tissue from each patient (39 goiters, 41 follicular adenomas, 16 follicular thyroid cancers, 108 papillary thyroid cancers, 4 medullary thyroid cancers) were analyzed independently to take into account method variation. RESULTS: The diagnostic classifier based on profiling of 13 microRNAs was proposed, with total estimated accuracy varying from 82.7 to 99% for different nodule types. Relative expression of six microRNAs (miR-146b, -21, -221, -222, 375, -199b) appeared significantly different in BRAF(V600E)-positive samples (all classified as papillary thyroid carcinomas) compared to BRAF(V600E)-negative papillary carcinoma samples. CONCLUSIONS: The results confirm practical feasibility of using molecular markers for typing of thyroid neoplasms and clarification of controversial cases.

ArrayExpress update--trends in database growth and links to data analysis tools.

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is one of three international functional genomics public data repositories, alongside the Gene Expression Omnibus at NCBI and the DDBJ Omics Archive, supporting peer-reviewed publications. It accepts data generated by sequencing or array-based technologies and currently contains data from almost a million assays, from over 30 000 experiments. The proportion of sequencing-based submissions has grown significantly over the last 2 years and has reached, in 2012, 15% of all new data. All data are available from ArrayExpress in MAGE-TAB format, which allows robust linking to data analysis and visualization tools, including Bioconductor and GenomeSpace. Additionally, R objects, for microarray data, and binary alignment format files, for sequencing data, have been generated for a significant proportion of ArrayExpress data.

ArrayExpress update--an archive of microarray and high-throughput sequencing-based functional genomics experiments.

The ArrayExpress Archive (http://www.ebi.ac.uk/arrayexpress) is one of the three international public repositories of functional genomics data supporting publications. It includes data generated by sequencing or array-based technologies. Data are submitted by users and imported directly from the NCBI Gene Expression Omnibus. The ArrayExpress Archive is closely integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Advanced queries provided via ontology enabled interfaces include queries based on technology and sample attributes such as disease, cell types and anatomy.

Modeling sample variables with an Experimental Factor Ontology.

MOTIVATION: Describing biological sample variables with ontologies is complex due to the cross-domain nature of experiments. Ontologies provide annotation solutions; however, for cross-domain investigations, multiple ontologies are needed to represent the data. These are subject to rapid change, are often not interoperable and present complexities that are a barrier to biological resource users. RESULTS: We present the Experimental Factor Ontology, designed to meet cross-domain, application focused use cases for gene expression data. We describe our methodology and open source tools used to create the ontology. These include tools for creating ontology mappings, ontology views, detecting ontology changes and using ontologies in interfaces to enhance querying. The application of reference ontologies to data is a key problem, and this work presents guidelines on how community ontologies can be presented in an application ontology in a data-driven way. AVAILABILITY: http://www.ebi.ac.uk/efo.

ArrayExpress update--from an archive of functional genomics experiments to the atlas of gene expression.

ArrayExpress http://www.ebi.ac.uk/arrayexpress consists of three components: the ArrayExpress Repository--a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse--a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas--a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200,000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently-ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.

Detection of high-grade neoplasia in air-dried cervical PAP smears by a microRNA-based classifier.

Recent studies have shown that changes in the expression levels of certain microRNAs correlate with the degree of severity of cervical lesions. The aim of the present study was to develop a microRNA-based classifier for the detection of high-grade cervical intraepithelial neoplasia (CIN ≥2) in cytological samples from patients with different high-risk human papillomavirus (HR-HPV) viral loads. For this purpose, raw RT-qPCR data for 25 candidate microRNAs, U6 snRNA and human DNA in air-dried PAP smears from 174 women with different cervical cytological diagnoses, 144 of which were HR-HPV-positive [40 negative for intraepithelial lesion or malignancy (NILM), 34 low-grade squamous intraepithelial lesions (L-SIL), 57 high-grade squamous intraepithelial lesions (H-SIL), 43 invasive cancers], were statistically processed. The expression level changes of various individual microRNAs were found to be significantly correlated with the cytological diagnosis but the statistical significance of this correlation was critically dependent on the normalization strategy. We developed a linear classifier based on the paired ratios of 8 microRNA concentrations and cellular DNA content. The classifier determines the dimensionless coefficient (DF value), which increases with the severity of cervical lesion. The high- and low-grade CINs were better distinguished by the microRNA classifier than by the measurement of individual microRNA levels with the use of traditional normalization methods. The diagnostic sensitivity of detecting high-grade lesions (CIN ≥2) with the developed microRNA classifier was 83.4%, diagnostic specificity 81.2%, ROC AUC=0.913. The analysis can be performed with the same nucleic acid preparation as used for HPV testing. No statistically significant correlation of the DF value and HR-HPV DNA load was found. The DF value and the HR HPV presence and viral DNA load may be regarded as independent criteria that can complement each other in molecular screening for high-grade cervical intraepithelial neoplasia. Although it has several limitations, the present study showed that the small-scale analysis of microRNA signatures performed by simple PCR-based methods may be useful for improving the diagnostic/prognostic value of cervical screening.

Selection and validation of miRNAs as normalizers for profiling expression of microRNAs isolated from thyroid fine needle aspiration smears.

Fine needle aspiration cytology (FNAC) is currently the method of choice for malignancy prediction in thyroid nodules. Nevertheless, in some cases the interpretation of FNAC results may be problematic due to limitations of the method. The expression level of some microRNAs changes with the development of thyroid tumors, and its quantitation can be used to refine the FNAC results. For this quantitation to be reliable, the obtained data must be adequately normalized. Currently, no reference genes are universally recognized for quantitative assessments of microRNAs in thyroid nodules. The aim of the present study was the selection and validation of such reference genes. Expression of 800 microRNAs in 5 paired samples of thyroid surgical material corresponding to different histotypes of tumors was analyzed using Nanostring technology and four of these (hsa-miR-151a-3p, -197-3p, -99a-5p and -214-3p) with the relatively low variation coefficient were selected. The possibility of use of the selected microRNAs and their combination as references was estimated by RT-qPCR on a sampling of cytological smears: benign (n=226), atypia of undetermined significance (n=9), suspicious for follicular neoplasm (n=61), suspicious for malignancy (n=19), medullary thyroid carcinoma (MTC) (n=32), papillary thyroid carcinoma (PTC) (n=54) and non-diagnostic material (ND) (n=34). In order to assess the expression stability of the references, geNorm algorithm was used. The maximum stability was observed for the normalization factor obtained by the combination of all 4 microRNAs. Further validation of the complex normalizer and individual selected microRNAs was performed using 5 different classification methods on 3 groups of FNAC smears from the analyzed batch: benign neoplasms, MTC and PTC. In all cases, the use of the complex classifier resulted in the reduced number of errors. On using the complex microRNA normalizer, the decision-tree method C4.5 makes it possible to distinguish between malignant and benign thyroid neoplasms in cytological smears with high overall accuracy (>91%).

Data storage and analysis in ArrayExpress and Expression Profiler.

ArrayExpress at the European Bioinformatics Institute is a public database for MIAME-compliant microarray and transcriptomics data. It consists of two parts: the ArrayExpress Repository, which is a public archive of microarray data, and the ArrayExpress Warehouse of Gene Expression Profiles, which contains additionally curated subsets of data from the Repository. Archived experiments can be queried by experimental attributes, such as keywords, species, array platform, publication details, or accession numbers. Gene expression profiles can be queried by gene names and properties, such as Gene Ontology terms, allowing expression profiles visualization. The data can be exported and analyzed using the online data analysis tool named Expression Profiler. Data analysis components, such as data preprocessing, filtering, differentially expressed gene finding, clustering methods, and ordination-based techniques, as well as other statistical tools are all available in Expression Profiler, via integration with the statistical package R.

A dual origin of the Xist gene from a protein-coding gene and a set of transposable elements.

X-chromosome inactivation, which occurs in female eutherian mammals is controlled by a complex X-linked locus termed the X-inactivation center (XIC). Previously it was proposed that genes of the XIC evolved, at least in part, as a result of pseudogenization of protein-coding genes. In this study we show that the key XIC gene Xist, which displays fragmentary homology to a protein-coding gene Lnx3, emerged de novo in early eutherians by integration of mobile elements which gave rise to simple tandem repeats. The Xist gene promoter region and four out of ten exons found in eutherians retain homology to exons of the Lnx3 gene. The remaining six Xist exons including those with simple tandem repeats detectable in their structure have similarity to different transposable elements. Integration of mobile elements into Xist accompanies the overall evolution of the gene and presumably continues in contemporary eutherian species. Additionally we showed that the combination of remnants of protein-coding sequences and mobile elements is not unique to the Xist gene and is found in other XIC genes producing non-coding nuclear RNA.