This article addresses the genetic and genomic determinants that influence susceptibility or resistance to human infections, whether caused by bacteria, viruses, fungi, parasites or even prions. A large number of genes are involved in susceptibility or resistance, and this is because Homo sapiens sapiens evolutionarily acquired key DNA modifications adaptable to defence as a result of the interaction of infectious agents with their genetic properties, natural selection and mutations. This article provides a description of the methods used in the investigation of this evolution and mutual host-infectious agent adaptation. The genes involved in susceptibility and resistance are presented, as well as the polymorphic variants that provide greater or lesser reaction capacity. The high number of genes, which produce specific defence proteins, have intricate relationships among them. Relationships among these genes have been analysed. A list of variants, and even mutations of the 70 to 153 proteins/genes that are involved in the immune response to infectious diseases has been compiled. Additionally, we designed a network of physical interactions as predictable, with BioGrid data and enrichment data obtained by the g:Profiler platform, finding 57 of the 70 genes with protein-to-protein interactions. The network detected is composed of 1,049 interacting genes (in total 1,106 genes and 1,910 interactions). This analysis shows the importance of immunity genes in the defence against infectious agents, as well as the effects of the genes involved such as HLA, immunoglobulins, interleukins, immune cells, among others. Based on the functional analysis of genes involved in susceptibility and resistance to infections, we compiled a list of genetic disorders that increase an individual’s risk of developing infectious diseases. It is known that infectious diseases manifest general clinical characteristics, which are a good guide to suspect a disease. Furthermore, we describe general clinical signs that may suggest underlying genetic immunodeficiency and highlight specific infectious diseases—such as HIV/AIDS, amebiasis, malaria, Chagas disease, tuberculosis, and COVID-19—where genetic susceptibility factors have been well-characterised.

Extracellular vesicles (EVs) are a heterogeneous group of lipid-bound vesicles released by cells into the extracellular space. EVs are an important mediator of intercellular communications and carry a wide variety of molecules that exert a biological function, such as lipids, nucleic acids, proteins, ions, and adenosine triphosphate (ATP). Extracellular vesicles are classified into microvesicles, exosomes, and apoptotic bodies depending on their biogenesis and size. Exosomes are spherical lipid-bilayer vesicles with a diameter of about 40 to 100 nm. Exosomes originate from intracellular endosomal compartments, while microvesicles originated directly from a cell’s plasma membrane and apoptotic bodies originate from cells undergoing apoptosis and are released via outward blebbing and fragmentation of the plasma membrane. Specifically, exosomes have garnered great attention since they display great potential as both biomarkers and carriers of therapeutic molecules.

In this paper, we first summarise the 2020 International Conference of EMBnet (The Global Bioinformatics Network) on “Bioinformatics Approaches to Precision Research”, held on 23th-24th September 2020, and then briefly introduce the main topics and contributions presented at the Conference and published in this supplement issue. The Conference’s main aim was to share the knowledge and scientific achievements of EMBnet members to prompt the cross-fertilisation of ideas and collaborations. The title reflects the type of contributions presented (20 in total), covering a wide range of cutting-edge research topics for which advanced bioinformatics methods and precision approaches are essential, and training in Bioinformatics. As for many other organisations, 2020 was the first year that the EMBnet Annual General Meeting was not in presence but ran on a virtual meeting platform because of the pandemic’s travel restrictions to moves. If this situation represented a limitation to our social activities, it allowed us to offer the possibility to attend the Conference to a larger number of researchers (i.e., 190 from 38 different countries). Among all registered people, 148 were following the conference presentations on both days. Under the authors’ permission, presentations were recorded and are available at the EMBnet Conference 2020 playlist on YouTube (https://youtube.com/playlist?list=PLVP2771lOozCHAOgVXBdqPW3oclEmzNIA), whereas the programme is available at the EMBnet Conference 2020 Google Drive folder (https://drive.google.com/file/d/1wWqp_I5vf-1GUlKmbCUq45EDQ9LfbrpC/view)

Extracellular vesicles have been the focus of a large number of studies in the past five years. Exosomes, a subgroup of extracellular vesicles, are of particularly high interest because they partake in a wide number of biological pathways. Produced by a variety of cells, exosomes have an important role in both physiological and pathological conditions. Exosome cargo heavily defines the vesicles’ unique characteristics, and the cargo with the most intriguing prospects in its’ biomedical applications is the non-coding RNAs. Non-coding RNAs, and specifically microRNAs are implicated in the regulation of many biological processes and have been associated with numerous diseases. Exosomes containing such important cargo can be used as biomarkers, therapeutic biomaterials, or even drug carriers. The potential media use of exosomes seems promising. However, some obstacles should be overcome before their clinical application. Synthetic exosome-like biomolecules may be a solution, but their production is still in their beginning stages. This review provides concise information regarding the current trends in exosome studies.

Basic bioinformatics training workshop conducted at Armauer Hansen Research Institute (AHRI), Addis Ababa, Ethiopia. This report describes a bioinformatics training initiative started at AHRI aiming to support life science researchers and postgraduates in handling next-generation sequencing data.

CADASIL syndrome is a rare disease that belongs to a group of disorders called leukodystrophies. It is well established that NOTCH3 gene on chromosome 19 is primarily responsible for the development of the CADASIL syndrome. Herein, an attempt is made to shed light on the actual molecular mechanism underlying CADASIL syndrome, through insights extracted from comprehensive evolutionary studies and in silico modelling on Notch 3 protein. In particular, we suggest the use of optical coherence tomography angiography for the detection of early signs of small vessel diseases, which are the major precursors to a repertoire of neurodegenerative conditions, including CADASIL.

For its unprecedented level of spatial resolution, chromatin immunoprecipitation combined with λ exonuclease digestion followed by high-throughput sequencing (ChIP-exo) has the potential to replace ChIP-seq as the standard approach for genome-wide mapping of protein-DNA interactions. In this assay, the midpoint between the strand-specific paired peaks, formed in the forward and reverse strands, is typically delimited by the exonuclease stop-sites, within which the protein-binding events are located. Although numerous algorithms have been developed for peak-calling in ChIP-seq data, none of them is fully adjusted for the analysis of ChIP-exo. This is because those statistical models do not make use of ChIP-exo’s strand-specificity for the identification of protein-DNA binding sites. Here, we present the CexoR algorithm, which aims to ease the analysis of replicated ChIP-exo data in BAM alignment format. The detection algorithm relies on the Skellam distribution (cross-correlation of two Poisson distributions) to calculate probabilities of consecutive punctate-sources of read-enrichment located nearby at Watson-and-Crick strands. ChIP-exo peak-pairs are identified and ranked by their irreproducible discovery rate estimated across biological replicates, and finally reported in BED format files. CexoR can potentially be applied to other ChIP-exo-based protocols, such as ChIP-nexus. Availability and implementation: CexoR has been implemented in R, and is freely available at http://bioconductor.org.