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Alzheimer's disease (AD) is a progressive neurodegenerative disorder with typical neuropathological hallmarks, such as neuritic plaques and neurofibrillary tangles, preferentially found at layers III and V. The distribution of both hallmarks provides the basis for the staging of AD, following a hierarchical pattern throughout the cerebral cortex. To unravel the background of this layer-specific vulnerability, we evaluated differential gene expression of supragranular and infragranular layers and subcortical white matter in both healthy controls and AD patients. We identified AD-associated layer-specific differences involving protein-coding and non-coding sequences, most of those present in the subcortical white matter, thus indicating a critical role for long axons and oligodendrocytes in AD pathomechanism. In addition, GO analysis identified networks containing synaptic vesicle transport, vesicle exocytosis and regulation of neurotransmitter levels. Numerous AD-associated layer-specifically expressed genes were previously reported to undergo layer-specific switches in recent hominid brain evolution between layers V and III, i.e., those layers that are most vulnerable to AD pathology. Against the background of our previous finding of accelerated evolution of AD-specific gene expression, here we suggest a critical role in AD pathomechanism for this phylogenetic layer-specific adaptation of gene expression, which is most prominently seen in the white matter compartment.

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/. The work was funded by a grant from the European Commission 7th Framework Program (FP7/2007–2013, grant 282510, BLUEPRINT) to XE, PF, JHAM, MY, HGS and WHO. WHO is an NIHR senior investigator and receives funding from Bristol-Myers Squibb, the British Heart Foundation, the Medical Research Council and the NIHR. OGI, FJM, AF, JMM, LC and PF are funded by the Wellcome Trust (WT108749/Z/15/Z) with additional funding for specific project components such as GENCODE from the National Human Genome Research Institute of the National Institutes of Health (2U41HG007234). FP is supported by the Fundação Carlos Chagas Filho de Amparo à Pesquisado Estado do Rio de Janeiro (FAPERJ; E-26/203.229/2016). NANJ is a recipient of a scholarship from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES; Finance Code 001). MF is supported by the British Heart Foundation (FS/18/53/33863)

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.

Riboswitches are RNA sensors that affect post-transcriptional processes through their ability to bind to small molecules. Thiamine pyrophosphate (TPP) riboswitch class is the most widespread riboswitch occurring in all three domains of life. Even though it controls different genes involved in the synthesis or transport of thiamine and its phosphorylated derivatives in bacteria, archaea, fungi, and plants, the TPP aptamer has a conserved structure. In this study, we aimed at understanding differences in the structural dynamics of TPP riboswitches from Escherichia coli and Arabidopsis thaliana, based on their crystallographic structures (TPPswec and TPPswat, respectively) and dynamics in aqueous solution, both in apo and holo states. A combination of Molecular Dynamics Simulations and Network Analysis empowered to find out slight differences in the dynamical behavior of TPP riboswitches, although relevant for their dynamics in bacteria and plants species. Our results suggest that distinct interactions in the microenvironment surrounding nucleotide U36 of TPPswec (and U35 in TPPswat) are related to different responses to TPP. The network analysis showed that minor structural differences in the aptamer enable enhanced intramolecular communication in the presence of TPP in TPPswec, but not in TPPswat. TPP riboswitches of plants present subtler and slower regulation mechanisms than bacteria do.

Spliced leader dependent trans-splicing (SLTS) has been described as an important RNA regulatory process that occurs in different organisms, including the trematode Schistosoma mansoni. We identified more than seven thousand putative SLTS sites in the parasite, comprising genes with a wide spectrum of functional classes, which underlines the SLTS as a ubiquitous mechanism in the parasite. Also, SLTS gene expression levels span several orders of magnitude, showing that SLTS frequency is not determined by the expression level of the target gene, but by the presence of particular gene features facilitating or hindering the trans-splicing mechanism. Our in-depth investigation of SLTS events demonstrates widespread alternative trans-splicing (ATS) acceptor sites occurring in different regions along the entire gene body, highlighting another important role of SLTS generating alternative RNA isoforms in the parasite, besides the polycistron resolution. Particularly for introns where SLTS directly competes for the same acceptor substrate with cis-splicing, we identified for the first time additional and important features that might determine the type of splicing. Our study substantially extends the current knowledge of RNA processing by SLTS in S. mansoni, and provide basis for future studies on the trans-splicing mechanism in other eukaryotes.

Lung cancer is one of the most frequent types of cancer worldwide. Most patients are diagnosed at advanced stage and thus have poor prognosis. Smoking is a risk factor for lung cancer, however most smokers do not develop lung cancer while 20% of women with lung adenocarcinoma are non-smokers. Therefore, it is possible that these two groups present differences besides the smoking status, including differences in their gene expression signature. The altered expression patterns of non-coding RNAs in complex diseases make them potential biomarkers for diagnosis and treatment. We analyzed data from differentially and constitutively expressed PIWI-interacting RNAs and small nucleolar RNAs from publicly available small RNA high-throughput sequencing data in search of an expression pattern of non-coding RNA that could differentiate these two groups. Here, we report two sets of differentially expressed small non-coding RNAs identified in normal and tumoral tissues of women with lung adenocarcinoma, that discriminate between smokers and non-smokers. Our findings may offer new insights on metabolic alterations caused by tobacco and may be used for early diagnosis of lung cancer.

The numerous genome sequencing projects produced unprecedented amount of data providing significant information to the discovery of novel non-coding RNA (ncRNA). Several ncRNAs have been described to control gene expression and display important role during cell differentiation and homeostasis. In the last decade, high throughput methods in conjunction with approaches in bioinformatics have been used to identify, classify, and evaluate the expression of hundreds of ncRNA in normal and pathological states, such as cancer. Patient outcomes have been already associated with differential expression of ncRNAs in normal and tumoral tissues, providing new insights in the development of innovative therapeutic strategies in oncology. In this review, we present and discuss bioinformatics advances in the development of computational approaches to analyze and discover ncRNA data in oncology using high throughput sequencing technologies.