Cell type-specific novel long non-coding RNA and circular RNA in the BLUEPRINT hematopoietic transcriptomes atlas.

Transcriptional profiling of hematopoietic cell subpopulations has helped to characterize the developmental stages of the hematopoietic system and the molecular bases of malignant and non-malignant blood diseases. Previously, only the genes targeted by expression microarrays could be profiled genome-wide. High-throughput RNA sequencing, however, encompasses a broader repertoire of RNA molecules, without restriction to previously annotated genes. We analyzed the BLUEPRINT consortium RNA-sequencing data for mature hematopoietic cell types. The data comprised 90 total RNA-sequencing samples, each composed of one of 27 cell types, and 32 small RNA-sequencing samples, each composed of one of 11 cell types. We estimated gene and isoform expression levels for each cell type using existing annotations from Ensembl. We then used guided transcriptome assembly to discover unannotated transcripts. We identified hundreds of novel non-coding RNA genes and showed that the majority have cell type-dependent expression. We also characterized the expression of circular RNA and found that these are also cell type-specific. These analyses refine the active transcriptional landscape of mature hematopoietic cells, highlight abundant genes and transcriptional isoforms for each blood cell type, and provide a valuable resource for researchers of hematologic development and diseases. Finally, we made the data accessible via a web-based interface: https://blueprint.haem.cam.ac.uk/bloodatlas/.

Downregulation of IGF2 expression in third trimester placental tissues from Zika virus infected women in Brazil.

OBJECTIVES: Screening for genes differentially expressed in placental tissues, aiming to identify transcriptional signatures that may be involved in ZIKV congenital pathogenesis. METHODS: Transcriptome data from placental tissues of pregnant women naturally infected with Zika virus during the third trimester were compared to those from women who tested negative for Zika infection. The findings were validated using both a cell culture model and an immunohistochemistry/morphological analysis of naturally infected placental tissues. RESULTS: Transcriptome analysis revealed that Zika virus infection induces downregulation of insulin-like growth factor II (IGF2) gene, an essential factor for fetal development. The Caco-2 cell culture model that constitutively expresses IGF2 was used for the transcriptome validation. Asiatic and African Zika virus strains infection caused downregulated IGF2 gene expression in Caco-2 cells, whereas other flaviviruses, such as dengue serotype 1, West Nile and wild-type yellow fever viruses, had no effect on this gene expression. Immunohistochemical assays on decidual tissues corroborated our transcriptome analysis, showing that IGF2 is reduced in the decidua of Zika virus-infected women. CONCLUSIONS: Our results draw attention to IGF2 modulation in uterine tissues, and this finding is expected to support future studies on strategies to ameliorate the harmful effects of Zika virus infection during pregnancy.

Poor clinical outcome in metastatic melanoma is associated with a microRNA-modulated immunosuppressive tumor microenvironment.

BACKGROUND: Interaction between malignant cells and immune cells that reside within the tumor microenvironment (TME) modulate different aspects of tumor development and progression. Recent works showed the importance of miRNA-containing extracellular vesicles in this crosstalk. METHODS: Interested in understanding the interplay between melanoma and immune-related TME cells, we characterized the TCGA's metastatic melanoma samples according to their tumor microenvironment profiles, HLA-I neoepitopes, transcriptome profile and classified them into three groups. Moreover, we combined our results with melanoma single-cell gene expression and public miRNA data to better characterize the regulatory network of circulating miRNAs and their targets related to immune evasion and microenvironment response. RESULTS: The group associated with a worse prognosis showed phenotypic characteristics that favor immune evasion, including a strong signature of suppressor cells and less stable neoantigen:HLA-I complexes. Conversely, the group with better prognosis was marked by enrichment in lymphocyte and MHC signatures. By analyzing publicly available melanoma single-cell RNA and microvesicle microRNAs sequencing data we identified circulating microRNAs potentially involved in the crosstalk between tumor and TME cells. Candidate miRNA/target gene pairs with previously reported roles in tumor progression and immune escape mechanisms were further investigated and demonstrated to impact patient's overall survival not only in melanoma but across different tumor types. CONCLUSION: Our results underscore the impact of tumor-microenvironment interactions on disease outcomes and reveal potential non-invasive biomarkers of prognosis and treatment response.

Using RNA Sequence and Structure for the Prediction of Riboswitch Aptamer: A Comprehensive Review of Available Software and Tools.

RNA molecules are essential players in many fundamental biological processes. Prokaryotes and eukaryotes have distinct RNA classes with specific structural features and functional roles. Computational prediction of protein structures is a research field in which high confidence three-dimensional protein models can be proposed based on the sequence alignment between target and templates. However, to date, only a few approaches have been developed for the computational prediction of RNA structures. Similar to proteins, RNA structures may be altered due to the interaction with various ligands, including proteins, other RNAs, and metabolites. A riboswitch is a molecular mechanism, found in the three kingdoms of life, in which the RNA structure is modified by the binding of a metabolite. It can regulate multiple gene expression mechanisms, such as transcription, translation initiation, and mRNA splicing and processing. Due to their nature, these entities also act on the regulation of gene expression and detection of small metabolites and have the potential to helping in the discovery of new classes of antimicrobial agents. In this review, we describe software and web servers currently available for riboswitch aptamer identification and secondary and tertiary structure prediction, including applications.