GOWDL: gene ontology-driven wide and deep learning model for cell typing of scRNA-seq data

Single-cell RNA-sequencing (scRNA-seq) allows for obtaining genomic and transcriptomic profiles of individual cells. That data make it possible to characterize tissues at the cell level. In this context, one of the main analyses exploiting scRNA-seq data is identifying the cell types within tissue to estimate the quantitative composition of cell populations. Due to the massive amount of available scRNA-seq data, automatic classification approaches for cell typing, based on the most recent deep learning technology, are needed. Here, we present the gene ontology-driven wide and deep learning (GOWDL) model for classifying cell types in several tissues. GOWDL implements a hybrid architecture that considers the functional annotations found in Gene Ontology and the marker genes typical of specific cell types. We performed cross-validation and independent external testing, comparing our algorithm with 12 other state-of-the-art predictors. Classification scores demonstrated that GOWDL reached the best results over five different tissues, except for recall, where we got about 92% versus 97% of the best tool. Finally, we presented a case study on classifying immune cell populations in breast cancer using a hierarchical approach based on GOWDL

Bioactive Molecules from the Innate Immunity of Ascidians and Innovative Methods of Drug Discovery: A Computational Approach Based on Artificial Intelligence

The study of bioactive molecules of marine origin has created an important bridge between biological knowledge and its applications in biotechnology and biomedicine. Current studies in different research fields, such as biomedicine, aim to discover marine molecules characterized by biological activities that can be used to produce potential drugs for human use. In recent decades, increasing attention has been paid to a particular group of marine invertebrates, the Ascidians, as they are a source of bioactive products. We describe omics data and computational methods relevant to identifying the mechanisms and processes of innate immunity underlying the biosynthesis of bioactive molecules, focusing on innovative computational approaches based on Artificial Intelligence. Since there is increasing attention on finding new solutions for a sustainable supply of bioactive compounds, we propose that a possible improvement in the biodiscovery pipeline might also come from the study and utilization of marine invertebrates’ innate immunity

The Clinical Significance of Unknown Sequence Variants in BRCA Genes

Abstract: Germline mutations in BRCA1/2 genes are responsible for a large proportion of hereditary breast and/or ovarian cancers. Many highly penetrant predisposition alleles have been identified and include frameshift or nonsense mutations that lead to the translation of a truncated protein. Other alleles contain missense mutations, which result in amino acid substitution and intronic variants with splicing effect. The discovery of variants of uncertain/unclassified significance (VUS) is a result that can complicate rather than improve the risk assessment process. VUSs are mainly missense mutations, but also include a number of intronic variants and in-frame deletions and insertions. Over 2,000 unique BRCA1 and BRCA2 missense variants have been identified, located throughout the whole gene (Breast Cancer Information Core Database (BIC database)). Up to 10–20% of the BRCA tests report the identification of a variant of uncertain significance. There are many methods to discriminate deleterious/high-risk from neutral/low-risk unclassified variants (i.e., analysis of the cosegregation in families of the VUS, measure of the influence of the VUSs on the wild-type protein activity, comparison of sequence conservation across multiple species), but only an integrated analysis of these methods can contribute to a real interpretation of the functional and clinical role of the discussed variants. The aim of our manuscript is to review the studies on BRCA VUS in order to clarify their clinical relevance

Transcriptomic Analyses Reveal 2 and 4 Family Members of Cytochromes P450 (CYP) Involved in LPS Inflammatory Response in Pharynx of Ciona robusta

Cytochromes P450 (CYP) are enzymes responsible for the biotransformation of most en- dogenous and exogenous agents. The expression of each CYP is influenced by a unique combination of mechanisms and factors including genetic polymorphisms, induction by xenobiotics, and regula- tion by cytokines and hormones. In recent years, Ciona robusta, one of the closest living relatives of vertebrates, has become a model in various fields of biology, in particular for studying inflammatory response. Using an in vivo LPS exposure strategy, next-generation sequencing (NGS) and qRT-PCR combined with bioinformatics and in silico analyses, compared whole pharynx transcripts from naïve and LPS-exposed C. robusta, and we provide the first view of cytochrome genes expression and miRNA regulation in the inflammatory response induced by LPS in a hematopoietic organ. In C. robusta, cytochromes belonging to 2B,2C, 2J, 2U, 4B and 4F subfamilies were deregulated and miRNA network interactions suggest that different conserved and species-specific miRNAs are involved in post-transcriptional regulation of cytochrome genes and that there could be an interplay between specific miRNAs regulating both inflammation and cytochrome molecules in the inflammatory response in C. robusta

germline mutations in women with familial breast cancer and a relative with haematological malignancy

International audienceBiallelic inactivation of the gene causes ataxia–telangiectasia (A–T), a complex neurological disease associated with a high risk of leukaemias and lymphomas. Mothers of A–T children, obligate heterozygote mutation carriers, have a breast cancer (BC) relative risk of about 3. The frequency of carriers in BC women with a BC family history has been estimated to be 2.70%. To further our clinical understanding of familial BC and examine whether haematological malignancies are predictive of germline mutation, we estimated the frequency of heterozygote mutation carriers in a series of 122 BC women with a family history of both BC and haematological malignancy and without mutation. The gene screening was performed with a new high throughput method, EMMA (enhanced mismatch mutation analysis). Amongst 28 different variants, eight mutations have been identified in eight patients: two mutations leading to a putative truncated protein and six being likely deleterious mutations. One of the truncating mutations was initially interpreted as a missense mutation, p.Asp2597Tyr, but is actually a splice mutation (c.7789G>T/p.Asp2597_Lys2643>LysfsX3). The estimated frequency of heterozygote mutation carriers in our series is 6.56% (95% CI: 2.16–10.95), a significantly higher figure than that observed in the general population, estimated to be between 0.3 and 0.6%. Although a trend towards an increased frequency of carriers was observed, it was not different from that observed in a population of familial BC women not selected for haematological malignancy as the frequency of carriers was 2.70%, a value situated in the confidence interval of our study

Testing for SARS-CoV-2 (COVID-19): a systematic review and clinical guide to molecular and serological in-vitro diagnostic assays

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its associated Coronavirus disease 2019 (COVID-19) pandemic has demanded rapid upscaling of in-vitro diagnostic assays to enable mass screening and testing of high-risk groups, and simultaneous ascertainment of robust data on past SARS-CoV-2 exposure at an individual and population level. To meet the exponential demand in testing, there has been an accelerated development of both molecular and serological assays across a plethora of platforms. In the present review, we discuss the current literature on these modalities including the nucleic acid amplification tests, direct viral antigen tests and the rapidly expanding laboratory based and point of care serological tests. This suite of complementary tests will inform crucial decisions by healthcare providers and policy makers and understanding their strengths and limitations will be critical to their judicious application for the development of algorithmic approaches to treatment and public health strategies

miRTissue: a web application for the analysis of miRNA-target interactions in human tissues

Abstract Background microRNAs act as regulators of gene expression interacting with their gene targets. Current bioinformatics services, such as databases of validated miRNA-target interactions and prediction tools, usually provide interactions without any information about what tissue that interaction is more likely to appear nor information about the type of interactions, causing mRNA degradation or translation inhibition respectively. Results In this work, we introduce miRTissue, a web application that combines validated miRNA-target interactions with statistical correlation among expression profiles of miRNAs, genes and proteins in 15 different human tissues. Validated interactions are taken from the miRTarBase database, while expression profiles are downloaded from The Cancer Genome Atlas repository. As a result, the service provides a tissue-specific characterisation of each couple of miRNA and gene together with its statistical significance (p-value). The inclusion of protein data also allows providing the type of interaction. Moreover, miRTissue offers several views for analysing interactions, focusing for example on the comparison between different cancer types or different tissue conditions. All the results are freely downloadable in the most common formats. Conclusions miRTissue fills a gap concerning current bioinformatics services related to miRNA-target interactions because it provides a tissue-specific context to each validated interaction and the type of interaction itself. miRTissue is easily browsable allowing the user to select miRNAs, genes, cancer types and tissue conditions. The results can be sorted according to p-values to immediately identify those interactions that are more likely to occur in a given tissue. miRTissue is available at http://tblab.pa.icar.cnr.it/mirtissue.html