Allele Frequency Net Database.

The allele frequency net database (AFND, http://www.allelefrequencies.net ) is an online web-based repository that contains information on the frequencies of immune-related genes and their corresponding alleles in worldwide human populations. At present, the website contains data from 1784 population samples in more than 14 million individuals from 129 countries on the frequency of genes from different polymorphic regions including data for the human leukocyte antigen (HLA) system. In addition, over the last four years, AFND has also incorporated genotype raw data from 85,000 individuals comprising 215 population samples from 39 countries. Moreover, more population data sets containing next generation sequencing data spanning >3 million individuals have been added. This resource has been widely used in a variety of contexts such as histocompatibility, immunology, epidemiology, pharmacogenetics, epitope prediction algorithms for population coverage in vaccine development, population genetics, among many others. In this chapter, we present an update of the most used searching mechanisms as described in a previous volume and some of the latest developments included in AFND.

A snapshot of human leukocyte antigen (HLA) diversity using data from the Allele Frequency Net Database.

The extensive allelic variability observed in several genes related to the immune response and its significance in different areas including transplantation, disease association studies, diversity in human populations, among many others, has led the scientific community to analyse these variants among individuals. Serving as an electronic data warehouse, the Allele Frequency Net Database (AFND, http://www.allelefrequencies.net) contains data on the frequency of immune related genes and their corresponding alleles from more than 1700 worldwide population samples covering more than ten million unrelated individuals. The collection of population data sets available in AFND encompasses different polymorphic regions including the highly-polymorphic human leukocyte antigen (HLA) system for which more than 1200 populations are available. In this article, we provide an insight of the high diversity found in the HLA region by examining population data sets stored in AFND, as well as a description of the available data sets for further analyses.

A Proteome-Wide Immunoinformatics Tool to Accelerate T-Cell Epitope Discovery and Vaccine Design in the Context of Emerging Infectious Diseases: An Ethnicity-Oriented Approach.

Emerging infectious diseases (EIDs) caused by viruses are increasing in frequency, causing a high disease burden and mortality world-wide. The COVID-19 pandemic caused by the novel SARS-like coronavirus (SARS-CoV-2) underscores the need to innovate and accelerate the development of effective vaccination strategies against EIDs. Human leukocyte antigen (HLA) molecules play a central role in the immune system by determining the peptide repertoire displayed to the T-cell compartment. Genetic polymorphisms of the HLA system thus confer a strong variability in vaccine-induced immune responses and may complicate the selection of vaccine candidates, because the distribution and frequencies of HLA alleles are highly variable among different ethnic groups. Herein, we build on the emerging paradigm of rational epitope-based vaccine design, by describing an immunoinformatics tool (Predivac-3.0) for proteome-wide T-cell epitope discovery that accounts for ethnic-level variations in immune responsiveness. Predivac-3.0 implements both CD8+ and CD4+ T-cell epitope predictions based on HLA allele frequencies retrieved from the Allele Frequency Net Database. The tool was thoroughly assessed, proving comparable performances (AUC ~0.9) against four state-of-the-art pan-specific immunoinformatics methods capable of population-level analysis (NetMHCPan-4.0, Pickpocket, PSSMHCPan and SMM), as well as a strong accuracy on proteome-wide T-cell epitope predictions for HIV-specific immune responses in the Japanese population. The utility of the method was investigated for the COVID-19 pandemic, by performing in silico T-cell epitope mapping of the SARS-CoV-2 spike glycoprotein according to the ethnic context of the countries where the ChAdOx1 vaccine is currently initiating phase III clinical trials. Potentially immunodominant CD8+ and CD4+ T-cell epitopes and population coverages were predicted for each population (the Epitope Discovery mode), along with optimized sets of broadly recognized (promiscuous) T-cell epitopes maximizing coverage in the target populations (the Epitope Optimization mode). Population-specific epitope-rich regions (T-cell epitope clusters) were further predicted in protein antigens based on combined criteria of epitope density and population coverage. Overall, we conclude that Predivac-3.0 holds potential to contribute in the understanding of ethnic-level variations of vaccine-induced immune responsiveness and to guide the development of epitope-based next-generation vaccines against emerging pathogens, whose geographic distributions and populations in need of vaccinations are often well-defined for regional epidemics.

lcmsWorld: High-Performance 3D Visualization Software for Mass Spectrometry.

Complex biological samples, in particular, in proteomics and metabolomics research, are often analyzed using mass spectrometry paired with liquid chromatography or gas chromatography. The chromatography stage adds a third dimension (retention time) to the usual 2D mass spectrometry output (mass/charge, detected ion counts). Experimental results are often discovered by complex computational analysis, but it is not always possible to know if the data has been correctly interpreted. To perform quality-control checks, it can often be helpful to verify the results by manually examining the raw data, and it is typically easier to understand the data in a graphical, rather than numerical, form. 3D graphics hardware is present in most modern computers but is rarely utilized by bioinformatics software, even when the data to be viewed are naturally 3D. lcmsWorld is new software that uses graphics hardware to quickly and smoothly examine and compare LC-MS data. A preprocessing step allows the software to subsequently access any area of the data instantly at multiple levels of detail. The data can then be freely navigated while the software automatically selects, loads, and displays the most appropriate detail. lcmsWorld is open source. Releases, source code, and example data files are available via https://github.com/PGB-LIV/lcmsWorld.

Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools.

The Allele Frequency Net Database (AFND, www.allelefrequencies.net) provides the scientific community with a freely available repository for the storage of frequency data (alleles, genes, haplotypes and genotypes) related to human leukocyte antigens (HLA), killer-cell immunoglobulin-like receptors (KIR), major histocompatibility complex Class I chain related genes (MIC) and a number of cytokine gene polymorphisms in worldwide populations. In the last five years, AFND has become more popular in terms of clinical and scientific usage, with a recent increase in genotyping data as a necessary component of Short Population Report article submissions to another scientific journal. In addition, we have developed a user-friendly desktop application for HLA and KIR genotype/population data submissions. We have also focused on classification of existing and new data into 'gold-silver-bronze' criteria, allowing users to filter and query depending on their needs. Moreover, we have also continued to expand other features, for example focussed on HLA associations with adverse drug reactions. At present, AFND contains >1600 populations from >10 million healthy individuals, making AFND a valuable resource for the analysis of some of the most polymorphic regions in the human genome.

Allele Frequency Net Database.

The allele frequency net database (AFND, http://www.allelefrequencies.net ) is an online web-based repository that contains information on the frequencies of immune-related genes and their corresponding alleles in worldwide human populations. At present, the system contains data from 1505 populations in more than ten million individuals on the frequency of genes from different polymorphic regions including data for the human leukocyte antigens (HLA) system. This resource has been widely used in a variety of contexts such as histocompatibility, immunology, epidemiology, pharmacogenetics, and population genetics, among many others. In this chapter, we present some of the more commonly used searching mechanisms and some of the most recent developments included in AFND.

Neopeptide Analyser: A software tool for neopeptide discovery in proteomics data.

Experiments involving mass spectrometry (MS)-based proteomics are widely used for analyses of connective tissues. Common examples include the use of relative quantification to identify differentially expressed peptides and proteins in cartilage and tendon. We are working on characterising so-called 'neopeptides', i.e. peptides formed due to native cleavage of proteins, for example under pathological conditions. Unlike peptides typically quantified in MS workflows due to the in vitro use of an enzyme such as trypsin, a neopeptide has at least one terminus that was not due to the use of trypsin in the workflow. The identification of neopeptides within these datasets is important in understanding disease pathology, and the development of antibodies that could be utilised as diagnostic biomarkers for diseases, such as osteoarthritis, and targets for novel treatments. Our previously described neopeptide data analysis workflow was laborious and was not amenable to robust statistical analysis, which reduced confidence in the neopeptides identified. To overcome this, we developed 'Neopeptide Analyser', a user friendly neopeptide analysis tool used in conjunction with label-free MS quantification tool Progenesis QIP for proteomics. Neopeptide Analyser filters data sourced from Progenesis QIP output to identify neopeptide sequences, as well as give the residues that are adjacent to the peptide in its corresponding protein sequence. It also produces normalised values for the neopeptide quantification values and uses these to perform statistical tests, which are also included in the output. Neopeptide Analyser is available as a Java application for Mac, Windows and Linux. The analysis features and ease of use encourages data exploration, which could aid the discovery of novel pathways in extracellular matrix degradation, the identification of potential biomarkers and as a tool to investigate matrix turnover. Neopeptide Analyser is available from https://github.com/PGB-LIV/neo-pep-tool/releases/.

A web resource for mining HLA associations with adverse drug reactions: HLA-ADR.

Human leukocyte antigens (HLA) are an important family of genes involved in the immune system. Their primary function is to allow the host immune system to be able to distinguish between self and non-self peptides-e.g. derived from invading pathogens. However, these genes have also been implicated in immune-mediated adverse drug reactions (ADRs), presenting a problem to patients, clinicians and pharmaceutical companies. We have previously developed the Allele Frequency Net Database (AFND) that captures the allelic and haplotype frequencies for these HLA genes across many healthy populations from around the world. Here, we report the development and release of the HLA-ADR database that captures data from publications where HLA alleles and haplotypes have been associated with ADRs (e.g. Stevens-Johnson Syndrome/toxic epidermal necrolysis and drug-induced liver injury). HLA-ADR was created by using data obtained through systematic review of the literature and semi-automated literature mining. The database also draws on data already present in AFND allowing users to compare and analyze allele frequencies in both ADR patients and healthy populations. The HLA-ADR database provides clinicians and researchers with a centralized resource from which to investigate immune-mediated ADRs.Database URL: http://www.allelefrequencies.net/hla-adr/.

Allele Frequencies Net Database: Improvements for storage of individual genotypes and analysis of existing data.

The Allele Frequencies Net Database (AFND) is a freely accessible database which stores population frequencies for alleles or genes of the immune system in worldwide populations. Herein we introduce two new tools. We have defined new classifications of data (gold, silver and bronze) to assist users in identifying the most suitable populations for their tasks. The gold standard datasets are defined by allele frequencies summing to 1, sample sizes >50 and high resolution genotyping, while silver standard datasets do not meet gold standard genotyping resolution and/or sample size criteria. The bronze standard datasets are those that could not be classified under the silver or gold standards. The gold standard includes >500 datasets covering over 3 million individuals from >100 countries at one or more of the following loci: HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1 and -DRB1 - with all loci except DPA1 present in more than 220 datasets. Three out of 12 geographic regions have low representation (the majority of their countries having less than five datasets) and the Central Asia region has no representation. There are 18 countries that are not represented by any gold standard datasets but are represented by at least one dataset that is either silver or bronze standard. We also briefly summarize the data held by AFND for KIR genes, alleles and their ligands. Our second new component is a data submission tool to assist users in the collection of the genotypes of the individuals (raw data), facilitating submission of short population reports to Human Immunology, as well as simplifying the submission of population demographics and frequency data.