IMGT/HLA Database--a sequence database for the human major histocompatibility complex

25 years of the IPD-IMGT/HLA Database

Twenty-five years ago, in 1998, the HLA Informatics Group of the Anthony Nolan Research Institute released the IMGT/HLA Database. Since this time, this online resource has acted as the repository for the numerous variant sequences of HLA alleles named by the WHO Nomenclature Committee for Factors of the HLA System. The IPD-IMGT/HLA Database has provided a stable, highly accessible, user-friendly repository for this work. During this time, the technology underlying HLA typing has undergone significant changes. Next generation sequencing (NGS) has superseded previous methodologies of HLA typing and can generate large amounts of high-resolution sequencing data. This has resulted in a drastic increase in the number and complexity of sequences submitted to the database. The challenge for the IPD-IMGT/HLA Database has been to maintain the highest standards of curation, while supporting the core set of tools and functionality to our users with increased numbers of submissions and sequences. Traditional methods of accessing and presenting data have been challenged and new methods utilising new computing technologies have had to be developed to keep pace and support a shifting user demographic.

Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules is crucial for rational development of immunotherapies and vaccines targeting CD4+ T cell activation. So far, most prediction methods for HLA class II antigen presentation have focused on HLA-DR because of limited availability of immunopeptidomics data for HLA-DQ and HLA-DP while not taking into account alternative peptide binding modes. We present an update to the NetMHCIIpan prediction method, which closes the performance gap between all three HLA class II loci. We accomplish this by first integrating large immunopeptidomics datasets describing the HLA class II specificity space across all loci using a refined machine learning framework that accommodates inverted peptide binders. Next, we apply targeted immunopeptidomics assays to generate data that covers additional HLA-DP specificities. The final method, NetMHCIIpan-4.3, achieves high accuracy and molecular coverage across all HLA class II allotypes.

Can we predict T cell specificity with digital biology and machine learning?

Recent advances in machine learning and experimental biology have offered breakthrough solutions to problems such as protein structure prediction that were long thought to be intractable. However, despite the pivotal role of the T cell receptor (TCR) in orchestrating cellular immunity in health and disease, computational reconstruction of a reliable map from a TCR to its cognate antigens remains a holy grail of systems immunology. Current data sets are limited to a negligible fraction of the universe of possible TCR-ligand pairs, and performance of state-of-the-art predictive models wanes when applied beyond these known binders. In this Perspective article, we make the case for renewed and coordinated interdisciplinary effort to tackle the problem of predicting TCR-antigen specificity. We set out the general requirements of predictive models of antigen binding, highlight critical challenges and discuss how recent advances in digital biology such as single-cell technology and machine learning may provide possible solutions. Finally, we describe how predicting TCR specificity might contribute to our understanding of the broader puzzle of antigen immunogenicity.

The IPD-IMGT/HLA Database

It is 24 years since the IPD-IMGT/HLA Database, http://www.ebi.ac.uk/ipd/imgt/hla/, was first released, providing the HLA community with a searchable repository of highly curated HLA sequences. The database now contains over 35 000 alleles of the human Major Histocompatibility Complex (MHC) named by the WHO Nomenclature Committee for Factors of the HLA System. This complex contains the most polymorphic genes in the human genome and is now considered hyperpolymorphic. The IPD-IMGT/HLA Database provides a stable and user-friendly repository for this information. Uptake of Next Generation Sequencing technology in recent years has driven an increase in the number of alleles and the length of sequences submitted. As the size of the database has grown the traditional methods of accessing and presenting this data have been challenged, in response, we have developed a suite of tools providing an enhanced user experience to our traditional web-based users while creating new programmatic access for our bioinformatics user base. This suite of tools is powered by the IPD-API, an Application Programming Interface (API), providing scalable and flexible access to the database. The IPD-API provides a stable platform for our future development allowing us to meet the future challenges of the HLA field and needs of the community.

MICA Polymorphism and Genetic Predisposition to T1D in Jordanian Patients: A Case-Control Study

Type 1 diabetes (T1D) is an autoimmune disorder whose etiology includes genetic and environmental factors. The non-classical Major Histocompatibility Complex (MHC) class I chain-related gene A (MICA) gene has been associated with increased susceptibility to T1D as the interaction of MICA to the Natural Killer Group 2D (NK2GD) receptors found on the cell surface of natural killer (NK) cells and T cells is responsible for inducing immune responses. MICA polymorphisms were reported in association with T1D among different ethnic groups. However, data from different populations revealed conflicting results, so the association of MICA polymorphisms with predisposition to T1D remains uncertain. The aim of this sequencing-based study was to identify, for the first time, the possible MICA alleles and/or genotypes that could be associated with T1D susceptibility in the Jordanian population. Polymorphisms in exons 2–4 and the short tandem repeats (STR) in exon 5 of the highly polymorphic MICA gene were analyzed. No evidence for association between T1D and MICA alleles/genotypes was found in this study, except for the MICA*011 allele which was found to be negatively associated with T1D (p = 0.023, OR = 0.125). In conclusion, MICA polymorphisms seem not to be associated with increasing T1D susceptibility in Jordanian patients.

Baseline Gene Expression Levels in Falkland-Malvinas Island Penguins: Towards a New Monitoring Paradigm

Health diagnostics of wildlife have historically relied on the evaluation of select serum biomarkers and the identification of a contaminant or pathogen burden within specific tissues as an indicator of a level of insult. However, these approaches fail to measure the physiological reaction of the individual to stressors, thus limiting the scope of interpretation. Gene-based health diagnostics provide an opportunity for an alternate, whole-system, or holistic assessment of health, not only in individuals or populations but potentially in ecosystems. Seabirds are among the most threatened marine taxonomic groups in the world, with ~25% of this species currently listed as threatened or considered of special concern; among seabirds, the penguins (Family Spheniscidae) are the most threatened seabird Family. We used gene expression to develop baseline physiological indices for wild penguins in the Falkland-Malvinas Islands, and captive zoo penguins. We identified the almost complete statistical separation of penguin groups (gentoo Detroit Zoo, gentoo Falkland-Malvinas Islands, rockhopper Detroit Zoo, and rockhopper Falkland-Malvinas Islands) based on gene expression profiles. Implementation of long-term longitudinal studies would allow for the assessment of temporal increases or decreases of select transcripts and would facilitate interpretation of the drivers of change.

Heterogeneity of Genetic Admixture Determines SLE Susceptibility in Mexican

Systemic Lupus Erythematosus (SLE) is an autoimmune inflammatory disorder for which Major Histocompatibility Complex (MHC) genes are well identified as risk factors. SLE patients present different clinical phenotypes, which are partly explained by admixture patterns variation among Mexicans. Population genetic has insight into the high genetic variability of Mexicans, mainly described through HLA gene studies with anthropological and biomedical importance. A prospective, case-control study was performed. In this study, we recruited 146 SLE patients, and 234 healthy individuals were included as a control group; both groups were admixed Mexicans from Mexico City. The HLA typing methods were based on Next Generation Sequencing and Sequence-Based Typing (SBT). The data analysis was performed with population genetic programs and statistical packages. The admixture estimations based on HLA-B and -DRB1 revealed that SLE patients have a higher Southwestern European ancestry proportion (48 ± 8%) than healthy individuals (30 ± 7%). In contrast, Mexican Native American components are diminished in SLE patients (44 ± 1%) and augmented in Healthy individuals (63 ± 4%). HLA alleles and haplotypes' frequency analysis found variants previously described in SLE patients from Mexico City. Moreover, a conserved extended haplotype that confers risk to develop SLE was found, the HLA-A^∗29:02∼C^∗16:01∼B^∗44:03∼DRB1^∗07:01∼DQB1^∗02:02, pC = 0.02, OR = 1.41. Consistent with the admixture estimations, the origin of all risk alleles and haplotypes found in this study are European, while the protection alleles are Mexican Native American. The analysis of genetic distances supported that the SLE patient group is closer to the Southwestern European parental populace and farthest from Mexican Native Americans than healthy individuals. Heterogeneity of genetic admixture determines SLE susceptibility and protection in Mexicans. HLA sequencing is helpful to determine susceptibility alleles and haplotypes restricted to some populations.

Immunoinformatics analysis of antigenic epitopes and designing of a multi-epitope peptide vaccine from putative nitro-reductases of Mycobacterium tuberculosis DosR

Mycobacterium tuberculosis (Mtb) resides in alveolar macrophages as a non-dividing and dormant state causing latent tuberculosis. Currently, no vaccine is available against the latent tuberculosis. Latent Mtb expresses ~48 genes under the control of DosR regulon. Among these, putative nitroreductases have significantly high expression levels, help Mtb to cope up with nitrogen stresses and possess antigenic properties. In the current study, immunoinformatics methodologies are applied to predict promiscuous antigenic T-cell epitopes from putative nitro-reductases of the DosR regulon. The promiscuous antigenic T-cell epitopes prediction was performed on the basis of their potential to induce an immune response and forming a stable interaction with the HLA alleles. The highest antigenic promiscuous epitopes were assembled for designing an in-silico vaccine construct. A TLR-2 agonist Phenol-soluble modulin alpha 4 was exploited as an adjuvant. Molecular docking and Molecular Dynamics Simulations were used to predict the stability of vaccine construct with the immune receptor. The predicted promiscuous epitopes may be helpful in the construction of a subunit vaccine against latent tuberculosis, which can also be administered along with the BCG to increase its efficacy. Experimental validation is a prerequisite for the in-silico designed vaccine construct against TB infection.

Anti-IFN-γ autoantibodies underlie disseminated Talaromyces marneffei infections

Talaromyces marneffei causes life-threatening opportunistic infections, mainly in Southeast Asia and South China. T. marneffei mainly infects patients with human immunodeficiency virus (HIV) but also infects individuals without known immunosuppression. Here we investigated the involvement of anti-IFN-γ autoantibodies in severe T. marneffei infections in HIV-negative patients. We enrolled 58 HIV-negative adults with severe T. marneffei infections who were otherwise healthy. We found a high prevalence of neutralizing anti-IFN-γ autoantibodies (94.8%) in this cohort. The presence of anti-IFN-γ autoantibodies was strongly associated with HLA-DRB1*16:02 and -DQB1*05:02 alleles in these patients. We demonstrated that adult-onset acquired immunodeficiency due to autoantibodies against IFN-γ is the major cause of severe T. marneffei infections in HIV-negative patients in regions where this fungus is endemic. The high prevalence of anti-IFN-γ autoantibody-associated HLA class II DRB1*16:02 and DQB1*05:02 alleles may account for severe T. marneffei infections in Southeast Asia. Our findings clarify the pathogenesis of T. marneffei infection and pave the way for developing novel treatments.

Native American ancestry significantly contributes to neuromyelitis optica susceptibility in the admixed Mexican population

Neuromyelitis Optica (NMO) is an autoimmune disease with a higher prevalence in non-European populations. Because the Mexican population resulted from the admixture between mainly Native American and European populations, we used genome-wide microarray, HLA high-resolution typing and AQP4 gene sequencing data to analyze genetic ancestry and to seek genetic variants conferring NMO susceptibility in admixed Mexican patients. A total of 164 Mexican NMO patients and 1,208 controls were included. On average, NMO patients had a higher proportion of Native American ancestry than controls (68.1% vs 58.6%; p = 5 × 10^-6). GWAS identified a HLA region associated with NMO, led by rs9272219 (OR = 2.48, P = 8 × 10^-10). Class II HLA alleles HLA-DQB1*03:01, -DRB1*08:02, -DRB1*16:02, -DRB1*14:06 and -DQB1*04:02 showed the most significant associations with NMO risk. Local ancestry estimates suggest that all the NMO-associated alleles within the HLA region are of Native American origin. No novel or missense variants in the AQP4 gene were found in Mexican patients with NMO or multiple sclerosis. To our knowledge, this is the first study supporting the notion that Native American ancestry significantly contributes to NMO susceptibility in an admixed population, and is consistent with differences in NMO epidemiology in Mexico and Latin America.

Aspartic acid70 in the HLA-DRB1 chain and shared epitope alleles partially explain the high prevalence of autoimmunity in Mexicans

INTRODUCTION

Autoimmune thyroid disease (AITD) is the most common autoimmune disorder worldwide. Remarkably, it is commonly accompanied by other autoimmune diseases, such as rheumatoid arthritis (RA). The immunopathogenic mechanisms behind the coexistence of these disorders are still not completely understood. Immunogenetics influences the physiopathology of these diseases since ethnicity plays an essential role in the inheritance of susceptibility markers.

METHODS

High-resolution HLA class II typing was performed using a sequence-based method.

RESULTS

The allele frequency of HLA-DRB1∗04:04 and -DRB1∗03:01 were significantly increased in patients with AITD and RA compared to healthy individuals, pC ​= ​0.021, OR ​= ​2.4, 95%CI ​= ​1.19-4.75 and pC ​= ​0.009, OR ​= ​3.4, 95%CI ​= ​1.42-7.93, respectively. Remarkably, these patients have a combined risk given by susceptibility HLA-DRB1 alleles that contain the shared epitope, pC ​= ​0.03, OR ​= ​1.7, IC95% ​= ​1.07-2.76, and a lack of protective alleles carrying aspartic acid70, pC ​= ​0.009, OR ​= ​0.5, IC95% ​= ​0.32-0.84.

DISCUSSION

The results suggest that patients with AITD and RA have an immunogenetic mechanism that combines the susceptibility alleles associated with both diseases. Importantly, it seems to be linked mainly to the lack of protective alleles with aspartic acid in the position 70, along with the presence of susceptibility alleles that have the sequences QRRAA, QKRAA, and RRRAA at positions 70-74.

CONCLUSION

Patients with AITD and RA have a characteristic immunogenetic signature, which could be useful for determining multiple autoimmunities and assessing their relatives' risk of developing it.

Study of the Binding Pattern of HLA Class I Alleles of Indian Frequency and cTAP Binding Peptide for Chikungunya Vaccine Development

Chikungunya is a mosquito-borne disease, caused by the member of the Togaviridae family belongs to the genus alphavirus, making it a major threat in all developing countries as well as some developed countries. The mosquito acts as a vector for the disease and carries the CHIK-Virus. To date there is no direct treatment available and that demands the development of more effective vaccines. In this study author employed Immune Epitope Database and Analysis Resource, a machine learning-based algorithm principally working on the Artificial Neural Network (ANN) algorithm, also known as (IEDB-ANN) for the prediction and analysis of Epitopes. A total of 173 epitopes were identified on the basis of IC50 values, among them 40 epitopes were found, sharing part with the linear B-cell epitopes and exposed to the cTAP1protein, and out of 40, 6 epitopes were noticed to show interactions with the cTAP with their binding energy ranging from - 3.61 to - 1.22 kcal/mol. The six epitopes identified were exposed to the HLA class I alleles and from this all revealed interaction with the HLA alleles and minimum binding energy that ranges from - 4.12 to - 5.88 kcal/mol. Besides, two T cell epitopes i.e. 145KVFTGVYPE153 and 395STVPVAPPR403 were found most promiscuous candidates. These promiscuous epitopes-HLA complexes were further analyzed by the molecular dynamics simulation to check the stability of the complex. Results obtained from this study suggest that the identified epitopes i.e. and 395 STVPVAPPR 403 , are likely to be capable of passing through the lumen of ER to bind withthe HLA class I allele and provide new insights and potential application in the designing and development of peptide-based vaccine candidate for the treatment of chikungunya.

IPD-IMGT/HLA Database

The IPD-IMGT/HLA Database, http://www.ebi.ac.uk/ipd/imgt/hla/, currently contains over 25 000 allele sequence for 45 genes, which are located within the Major Histocompatibility Complex (MHC) of the human genome. This region is the most polymorphic region of the human genome, and the levels of polymorphism seen exceed most other genes. Some of the genes have several thousand variants and are now termed hyperpolymorphic, rather than just simply polymorphic. The IPD-IMGT/HLA Database has provided a stable, highly accessible, user-friendly repository for this information, providing the scientific and medical community access to the many variant sequences of this gene system, that are critical for the successful outcome of transplantation. The number of currently known variants, and dramatic increase in the number of new variants being identified has necessitated a dedicated resource with custom tools for curation and publication. The challenge for the database is to continue to provide a highly curated database of sequence variants, while supporting the increased number of submissions and complexity of sequences. In order to do this, traditional methods of accessing and presenting data will be challenged, and new methods will need to be utilized to keep pace with new discoveries.

Computational approaches for characterizing the tumor immune microenvironment

Recent advances in high-throughput molecular profiling technologies and multiplexed imaging platforms have revolutionized our ability to characterize the tumor immune microenvironment. As a result, studies of tumor-associated immune cells increasingly involve complex data sets that require sophisticated methods of computational analysis. In this review, we present an overview of key assays and related bioinformatics tools for analyzing the tumor-associated immune system in bulk tissues and at the single-cell level. In parallel, we describe how data science strategies and novel technologies have advanced tumor immunology and opened the door for new opportunities to exploit host immunity to improve cancer clinical outcomes.

An original Eurasian haplotype, HLA-DRB1*14:54-DQB1*05:03, influences the susceptibility to idiopathic achalasia

Idiopathic achalasia is a relatively infrequent esophageal motor disorder for which major histocompatibility complex (MHC) genes are well-identified risk factors. However, no information about HLA-achalasia susceptibility in Mexicans has previously been reported. We studied a group of 91 patients diagnosed with achalasia and 234 healthy controls with Mexican admixed ancestry. HLA alleles and conserved extended haplotypes were analyzed using high-resolution HLA typing based on Sanger and next-generation sequencing technologies. Admixture estimates were determined using HLA-B and short tandem repeats. Results were analyzed by non-parametric statistical analysis and Bonferroni correction. P-values < 0.05 were considered significant. Patients with achalasia had 56.7% Native American genes, 24.7% European genes, 16.5% African genes and 2.0% Asian genes, which was comparable with the estimates in the controls. Significant increases in the frequencies of alleles DRB1*14:54 and DQB1*05:03 and the extended haplotypes DRB1*14:54-DQB1*05:03 and DRB1*11:01-DQB1*03:01, even after Bonferroni correction (pC<0.05), were found in the achalasia group compared to those in the controls. Concluding, the HLA class II alleles HLA-DRB1*14:54:01 and DQB1*05:03:01 and the extended haplotype are risk factors for achalasia in mixed-ancestry Mexican individuals. These results also suggest that the HLA-DRB1*14:54-DQB1*05:03 haplotype was introduced by admixture with European and/or Asian populations.

Using Gene Transcription to Assess Ecological and Anthropological Stressors in Brown Bears

Increasingly, population- and ecosystem-level health assessments are performed using sophisticated molecular tools. Advances in molecular technology enable the identification of synergistic effects of multiple stressors on the individual physiology of different species. Brown bears (Ursus arctos) are an apex predator; thus, they are ideal candidates for detecting potentially ecosystem-level systemic perturbations using molecular-based tools. We used gene transcription to analyze 130 brown bear samples from three National Parks and Preserves in Alaska. Although the populations we studied are apparently stable in abundance and exist within protected and intact environments, differences in transcript profiles were noted. The most prevalent differences were among locations. The transcript patterns among groups reflect the influence of environmental factors, such as nutritional status, disease, and xenobiotic exposure. However, these profiles also likely represent baselines for each unique environment by which future measures can be made to identify early indication of population-level changes due to, for example, increasing Arctic temperatures. Some of those environmental changes are predicted to be potentially positive for brown bears, but other effects such as the manifestation of disease or indirect effects of oceanic acidification may produce negative impacts.

HLA-G in Amerindians: Epidemiology and Worldwide Population Comparison

Background:

HLA-G molecules are immunosuppressive and avoid fetal rejection by giving negative signals to maternal immune system from fetal trophoblast cell surface. HLA-G genes have been associated to different pathologies: Spontaneous abortions, autoimmunity, tumor progression, transplant rejection and infection. In addition, different World populations show remarkable different HLA-G allele frequencies in the allele that does not produce a full HLA-G molecule (HLA-G*05N); this allele is almost absent in studied Amerindians.

Objectives:

The aim is to study HLA-A.-B,-DRB1 and –G alleles and extended haplotypes in Amerindians for the first time. This may be useful to asses HLA-G epidemiology, association to disease and Preventive Medicine in Amerindians.

Methods:

HLA-A,-B and -DRB1 have been typed by using standard automatic protocols. HLA-G alleles have been detected by direct HLA-G exon 2, exon 3 and exon 4 DNA sequencing. Computer calculations have been done by specific standard methods.

Results:

HLA-A,-B,-DRB1 and –G extended haplotypes have been calculated in Amerindians for the first time. Also, their HLA-G frequencies have been compared with worldwide populations.

Conclusion:

Low frequencies of null HLA-G*01:05N allele are found in Amerindians. The extended haplotypes with this allele bear other typical Amerindian HLA-DRB1 alleles and its origin is discussed. HLA-G allele frequency profile is closer to that of Europeans than to that of Far East Asians. Our findings are useful to Preventive Medicine and Epidemiology associated to Fertility and HLA-G associated pathology and transplantation.

Anti-NKG2D mAb: A New Treatment for Crohn's Disease?

Crohn’s disease (CD) and ulcerative colitis (UC) are immunologically-mediated, debilitating conditions resulting from destructive inflammation of the gastrointestinal tract. The pathogenesis of IBD is incompletely understood, but is considered to be the result of an abnormal immune response with a wide range of cell types and proteins involved. Natural Killer Group 2D (NKG2D) is an activating receptor constitutively expressed on human Natural Killer (NK), γδ T, mucosal-associated invariant T (MAIT), CD56⁺ T, and CD8⁺ T cells. Activation of NKG2D triggers cellular proliferation, cytokine production, and target cell killing. Research into the NKG2D mechanism of action has primarily been focused on cancer and viral infections where cytotoxicity evasion is a concern. In human inflammatory bowel disease (IBD) this system is less characterized, but the ligands have been shown to be highly expressed during intestinal inflammation and the following receptor activation may contribute to tissue degeneration. A recent phase II clinical trial showed that an antibody against NKG2D induced clinical remission of CD in some patients, suggesting NKG2D and its ligands to be of importance in the pathogenesis of CD. This review will describe the receptor and its ligands in intestinal tissues and the clinical potential of blocking NKG2D in Crohn’s disease.

Applications of Immunogenomics to Cancer

Cancer immunogenomics originally was framed by research supporting the hypothesis that cancer mutations generated novel peptides seen as "non-self" by the immune system. The search for these "neoantigens" has been facilitated by the combination of new sequencing technologies, specialized computational analyses, and HLA binding predictions that evaluate somatic alterations in a cancer genome and interpret their ability to produce an immune-stimulatory peptide. The resulting information can characterize a tumor's neoantigen load, its cadre of infiltrating immune cell types, the T or B cell receptor repertoire, and direct the design of a personalized therapeutic.

Characterization of the novel HLA-A*02:431 allele identified in a Chinese Han individual

HLA-A*02:431 differs from the closest allele HLA-A*02:03:01 by a nonsynonymous mutation at nucleotide 317 in exon 2.

Association analysis of HLA-DRA in Chinese patients with sporadic Parkinson's disease

Our aim is to explore the linkage between single nucleotide polymorphisms (SNPs) in human leukocyte antigen (HLA)-DRA and Parkinson's disease (PD). 542 sporadic PD patients and 674 healthy controls were recruited to investigate this association in the Chinese population by the screening of 15 SNPs in HLA-DRA, and the association of rs3129882 was further re-evaluated by performing meta-analysis and meta-regression analysis. No SNPs in HLA-DRA were significantly associated with PD in the Chinese patients. Although the rs3129882 allele-G frequency in the Caucasian population was lower than that in Chinese population, meta-analysis showed no association of rs3129882 allele-G with PD in the Chinese or Caucasian population. In consideration of the heterogeneity (I(2)=78.6%, Q=66.33, p<0.000), subgroup analysis was performed, revealing a significant association between rs3129882 and PD in the Caucasian patients from the genome-wide association studies (OR=1.22, 95% CI: 1.16, 1.27); however, this association was not consistently observed in the studies performed using other DNA sequencing techniques. Meta-regression analysis, which accounted for 58.3% of the heterogeneity, revealed that the impact of the sequencing technique used was significant (p=0.027) compared with ethnicity. Regression analysis of the Caucasian population further showed that the sequencing technique used contributed to 71.2% of the heterogeneity (p=0.033). Our data support the absence of a linkage between the risk loci in HLA-DRA and PD in Chinese patients. The different DNA sequencing techniques used in PD studies may largely account for the controversial conclusions concerning rs3129882.

Design of a predicted MHC restricted short peptide immunodiagnostic and vaccine candidate for Fowl adenovirus C in chicken infection

Fowl adenoviruses (FAdVs) are the ethiologic agents of multiple pathologies in chicken. There are five different species of FAdVs grouped as FAdV-A, FAdV-B, FAdV-C, FAdV-D, and FAdV-E. It is of interest to develop immunodiagnostics and vaccine candidate for Peruvian FAdV-C in chicken infection using MHC restricted short peptide candidates. We sequenced the complete genome of one FAdV strain isolated from a chicken of a local farm. A total of 44 protein coding genes were identified in each genome. We sequenced twelve Cobb chicken MHC alleles from animals of different farms in the central coast of Peru, and subsequently determined three optimal human MHC-I and four optimal human MHC-II substitute alleles for MHC-peptide prediction. The potential MHC restricted short peptide epitope-like candidates were predicted using human specific (with determined suitable chicken substitutes) NetMHC MHC-peptide prediction model with web server features from all the FAdV genomes available. FAdV specific peptides with calculated binding values to known substituted chicken MHC-I and MHC-II were further filtered for diagnostics and potential vaccine epitopes. Promiscuity to the 3/4 optimal human MHC-I/II alleles and conservation among the available FAdV genomes was considered in this analysis. The localization on the surface of the protein was considered for class II predicted peptides. Thus, a set of class I and class II specific peptides from FAdV were reported in this study. Hence, a multiepitopic protein was built with these peptides, and subsequently tested to confirm the production of specific antibodies in chicken.

Integrating Gene Transcription-Based Biomarkers to Understand Desert Tortoise and Ecosystem Health

Tortoises are susceptible to a wide variety of environmental stressors, and the influence of human disturbances on health and survival of tortoises is difficult to detect. As an addition to current diagnostic methods for desert tortoises, we have developed the first leukocyte gene transcription biomarker panel for the desert tortoise (Gopherus agassizii), enhancing the ability to identify specific environmental conditions potentially linked to declining animal health. Blood leukocyte transcript profiles have the potential to identify physiologically stressed animals in lieu of clinical signs. For desert tortoises, the gene transcript profile included a combination of immune or detoxification response genes with the potential to be modified by biological or physical injury and consequently provide information on the type and magnitude of stressors present in the animal's habitat. Blood from 64 wild adult tortoises at three sites in Clark County, NV, and San Bernardino, CA, and from 19 captive tortoises in Clark County, NV, was collected and evaluated for genes indicative of physiological status. Statistical analysis using a priori groupings indicated significant differences among groups for several genes, while multidimensional scaling and cluster analyses of transcription C T values indicated strong differentiation of a large cluster and multiple outlying individual tortoises or small clusters in multidimensional space. These analyses highlight the effectiveness of the gene panel at detecting environmental perturbations as well as providing guidance in determining the health of the desert tortoise.

Origin and prevalence of human T-lymphotropic virus type 1 (HTLV-1) and type 2 (HTLV-2) among indigenous populations in the Americas

Human T-lymphotropic virus type 1 (HTLV-1) is found in indigenous peoples of the Pacific Islands and the Americas, whereas type 2 (HTLV-2) is widely distributed among the indigenous peoples of the Americas, where it appears to be more prevalent than HTLV-1, and in some tribes of Central Africa. HTLV-2 is considered ancestral in the Americas and is transmitted to the general population and injection drug users from the indigenous population. In the Americas, HTLV-1 has more than one origin, being brought by immigrants in the Paleolithic period through the Bering Strait, through slave trade during the colonial period, and through Japanese immigration from the early 20^th century, whereas HTLV-2 was only brought by immigrants through the Bering Strait. The endemicity of HTLV-2 among the indigenous people of Brazil makes the Brazilian Amazon the largest endemic area in the world for its occurrence. A review of HTLV-1 in all Brazilian tribes supports the African origin of HTLV-1 in Brazil. The risk of hyperendemicity in these epidemiologically closed populations and transmission to other populations reinforces the importance of public health interventions for HTLV control, including the recognition of the infection among reportable diseases and events.

HLA Typing for the Next Generation

Allele-level resolution data at primary HLA typing is the ideal for most histocompatibility testing laboratories. Many high-throughput molecular HLA typing approaches are unable to determine the phase of observed DNA sequence polymorphisms, leading to ambiguous results. The use of higher resolution methods is often restricted due to cost and time limitations. Here we report on the feasibility of using Pacific Biosciences’ Single Molecule Real-Time (SMRT) DNA sequencing technology for high-resolution and high-throughput HLA typing. Seven DNA samples were typed for HLA-A, -B and -C. The results showed that SMRT DNA sequencing technology was able to generate sequences that spanned entire HLA Class I genes that allowed for accurate allele calling. Eight novel genomic HLA class I sequences were identified, four were novel alleles, three were confirmed as genomic sequence extensions and one corrected an existing genomic reference sequence. This method has the potential to revolutionize the field of HLA typing. The clinical impact of achieving this level of resolution HLA typing data is likely to considerable, particularly in applications such as organ and blood stem cell transplantation where matching donors and recipients for their HLA is of utmost importance.

HLA Class I and II Blocks Are Associated to Susceptibility, Clinical Subtypes and Autoantibodies in Mexican Systemic Sclerosis (SSc) Patients

INTRODUCTION

Human leukocyte antigen (HLA) polymorphism studies in Systemic Sclerosis (SSc) have yielded variable results. These studies need to consider the genetic admixture of the studied population. Here we used our previously reported definition of genetic admixture of Mexicans using HLA class I and II DNA blocks to map genetic susceptibility to develop SSc and its complications.

METHODS

We included 159 patients from a cohort of Mexican Mestizo SSc patients. We performed clinical evaluation, obtained SSc-associated antibodies, and determined HLA class I and class II alleles using sequence-based, high-resolution techniques to evaluate the contribution of these genes to SSc susceptibility, their correlation with the clinical and autoantibody profile and the prevalence of Amerindian, Caucasian and African alleles, blocks and haplotypes in this population.

RESULTS

Our study revealed that class I block HLA-C*12:03-B*18:01 was important to map susceptibility to diffuse cutaneous (dc) SSc, HLA-C*07:01-B*08:01 block to map the susceptibility role of HLA-B*08:01 to develop SSc, and the C*07:02-B*39:05 and C*07:02-B*39:06 blocks to map the protective role of C*07:02 in SSc. We also confirmed previous associations of HLA-DRB1*11:04 and -DRB1*01 to susceptibility to develop SSc. Importantly, we mapped the protective role of DQB1*03:01 using three Amerindian blocks. We also found a significant association for the presence of anti-Topoisomerase I antibody with HLA-DQB1*04:02, present in an Amerindian block (DRB1*08:02-DQB1*04:02), and we found several alleles associated to internal organ damage. The admixture estimations revealed a lower proportion of the Amerindian genetic component among SSc patients.

CONCLUSION

This is the first report of the diversity of HLA class I and II alleles and haplotypes Mexican patients with SSc. Our findings suggest that HLA class I and class II genes contribute to the protection and susceptibility to develop SSc and its different clinical presentations as well as different autoantibody profiles in Mexicans.

HLA Class II Antigens and Their Interactive Effect on Perinatal Mother-To-Child HIV-1 Transmission

HLA class II antigens are central in initiating antigen-specific CD4+ T cell responses to HIV-1. Specific alleles have been associated with differential responses to HIV-1 infection and disease among adults. This study aims to determine the influence of HLA class II genes and their interactive effect on mother-child perinatal transmission in a drug naïve, Mother-Child HIV transmission cohort established in Kenya, Africa in 1986. Our study showed that DRB concordance between mother and child increased risk of perinatal HIV transmission by three fold (P = 0.00035/Pc = 0.0014, OR: 3.09, 95%CI, 1.64-5.83). Whereas, DPA1, DPB1 and DQB1 concordance between mother and child had no significant influence on perinatal HIV transmission. In addition, stratified analysis showed that DRB1*15:03+ phenotype (mother or child) significantly increases the risk of perinatal HIV-1 transmission. Without DRB1*15:03, DRB1 discordance between mother and child provided 5 fold protection (P = 0.00008, OR: 0.186, 95%CI: 0.081-0.427). However, the protective effect of DRB discordance was diminished if either the mother or the child was DRB1*15:03+ phenotype (P = 0.49-0.98, OR: 0.7-0.99, 95%CI: 0.246-2.956). DRB3+ children were less likely to be infected perinatally (P = 0.0006, Pc = 0.014; OR:0.343, 95%CI:0.183-0.642). However, there is a 4 fold increase in risk of being infected at birth if DRB3+ children were born to DRB1*15:03+ mother compared to those with DRB1*15:03- mother. Our study showed that DRB concordance/discordance, DRB1*15:03, children’s DRB3 phenotype and their interactions play an important role in perinatal HIV transmission. Identification of genetic factors associated with protection or increased risk in perinatal transmission will help develop alternative prevention and treatment methods in the event of increases in drug resistance of ARV.

Characterisation of a new HLA-DRB1 allele: DRB1*03:85

HLA-DRB1*03:85 differs from HLA-DRB1*03:06 by two nucleotides, position 257 A>T and position 258T>C, resulting in Valine at codon 57.

Clustering HLA class I superfamilies using structural interaction patterns

Human leukocyte antigen (HLA) class I molecules are critical components of the cell-mediated immune system that bind and present intracellular antigenic peptides to CD8(+) T cell receptors. To understand the interaction mechanism underlying human leukocyte antigen (HLA) class I specificity in detail, we studied the structural interaction characteristics of 16,393 nonameric peptides binding to 58 HLA-A and -B molecules. Our analysis showed for the first time that HLA-peptide intermolecular bonding patterns vary among different alleles and may be grouped in a superfamily dependent manner. Through the use of these HLA class I 'fingerprints', a high resolution HLA class I superfamily classification schema was developed. This classification is capable of separating HLA alleles into well resolved, non-overlapping clusters, which is consistent with known HLA superfamily definitions. Such structural interaction approach serves as an excellent alternative to the traditional methods of HLA superfamily definitions that use peptide binding motifs or receptor information, and will help identify appropriate antigens suitable for broad-based subunit vaccine design.

HLA class I and class II conserved extended haplotypes and their fragments or blocks in Mexicans: implications for the study of genetic diversity in admixed populations

Major histocompatibility complex (MHC) genes are highly polymorphic and informative in disease association, transplantation, and population genetics studies with particular importance in the understanding of human population diversity and evolution. The aim of this study was to describe the HLA diversity in Mexican admixed individuals. We studied the polymorphism of MHC class I (HLA-A, -B, -C), and class II (HLA-DRB1, -DQB1) genes using high-resolution sequence based typing (SBT) method and we structured the blocks and conserved extended haplotypes (CEHs) in 234 non-related admixed Mexican individuals (468 haplotypes) by a maximum likelihood method. We found that HLA blocks and CEHs are primarily from Amerindian and Caucasian origin, with smaller participation of African and recent Asian ancestry, demonstrating a great diversity of HLA blocks and CEHs in Mexicans from the central area of Mexico. We also analyzed the degree of admixture in this group using short tandem repeats (STRs) and HLA-B that correlated with the frequency of most probable ancestral HLA-C/−B and -DRB1/−DQB1 blocks and CEHs. Our results contribute to the analysis of the diversity and ancestral contribution of HLA class I and HLA class II alleles and haplotypes of Mexican admixed individuals from Mexico City. This work will help as a reference to improve future studies in Mexicans regarding allotransplantation, immune responses and disease associations.

Pairomics, the omics way to mate choice

The core aspects of the biology and evolution of sexual reproduction are reviewed with a focus on the diploid, sexually reproducing, outbreeding, polymorphic, unspecialized, altricial and cultural human species. Human mate choice and pair bonding are viewed as central to individuals' lives and to the evolution of the species, and genetic assistance in reproduction is viewed as a universal human right. Pairomics is defined as an emerging branch of the omics science devoted to the study of mate choice at the genomic level and its consequences for present and future generations. In pairomics, comprehensive genetic information of individual genomes is stored in a database. Computational tools are employed to analyze the mating schemes and rules that govern mating among the members of the database. Mating models and algorithms simulate the outcomes of mating any given genome with each of a number of genomes represented in the database. The analyses and simulations may help to understand mating schemes and their outcomes, and also contribute a new cue to the multicued schemes of mate choice. The scientific, medical, evolutionary, ethical, legal and social implications of pairomics are far reaching. The use of genetic information as a search tool in mate choice may influence our health, lifestyle, behavior and culture. As knowledge on genomics, population genetics and gene-environment interactions, as well as the size of genomic databases expand, so does the ability of pairomics to investigate and predict the consequences of mate choice for the present and future generations.

NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ

Major histocompatibility complex class II (MHCII) molecules play an important role in cell-mediated immunity. They present specific peptides derived from endosomal proteins for recognition by T helper cells. The identification of peptides that bind to MHCII molecules is therefore of great importance for understanding the nature of immune responses and identifying T cell epitopes for the design of new vaccines and immunotherapies. Given the large number of MHC variants, and the costly experimental procedures needed to evaluate individual peptide-MHC interactions, computational predictions have become particularly attractive as first-line methods in epitope discovery. However, only a few so-called pan-specific prediction methods capable of predicting binding to any MHC molecule with known protein sequence are currently available, and all of them are limited to HLA-DR. Here, we present the first pan-specific method capable of predicting peptide binding to any HLA class II molecule with a defined protein sequence. The method employs a strategy common for HLA-DR, HLA-DP and HLA-DQ molecules to define the peptide-binding MHC environment in terms of a pseudo sequence. This strategy allows the inclusion of new molecules even from other species. The method was evaluated in several benchmarks and demonstrates a significant improvement over molecule-specific methods as well as the ability to predict peptide binding of previously uncharacterised MHCII molecules. To the best of our knowledge, the NetMHCIIpan-3.0 method is the first pan-specific predictor covering all HLA class II molecules with known sequences including HLA-DR, HLA-DP, and HLA-DQ. The NetMHCpan-3.0 method is available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.0 .

A community standard for immunogenomic data reporting and analysis: proposal for a STrengthening the REporting of Immunogenomic Studies statement

Modern high-throughput HLA and KIR typing technologies are generating a wealth of immunogenomic data with the potential to revolutionize the fields of histocompatibility and immune-related disease association and population genetic research, much as SNP-based approaches have revolutionized association research. The STrengthening the REporting of Genetic Association studies (STREGA) statement provides community-based data reporting and analysis standards for genomic disease-association studies, identifying specific areas in which adoption of reporting guidelines can improve the consistent interpretation of genetic studies. While aspects of STREGA can be applied to immunogenomic studies, HLA and KIR research requires additional consideration, as the high levels of polymorphism associated with immunogenomic data pose unique methodological and computational challenges to the synthesis of information across datasets. Here, we outline the principle challenges to consistency in immunogenomic studies, and propose that an immunogenomic-specific analog to the STREGA statement, a STrengthening the REporting of Immunogenomic Studies (STREIS) statement, be developed as part of the 16th International HLA and Immunogenetics Workshop. We propose that STREIS extends at least four of the 22 elements of the STREGA statement to specifically address issues pertinent to immunogenomic data: HLA and KIR nomenclature, data-validation, ambiguity resolution, and the analysis of highly polymorphic genetic systems. As with the STREGA guidelines, the intent behind STREIS is not to dictate the design of immunogenomic studies, but to ensure consistent and transparent reporting of research, facilitating the synthesis of HLA and KIR data across studies.

NetMHCcons: a consensus method for the major histocompatibility complex class I predictions

A key role in cell-mediated immunity is dedicated to the major histocompatibility complex (MHC) molecules that bind peptides for presentation on the cell surface. Several in silico methods capable of predicting peptide binding to MHC class I have been developed. The accuracy of these methods depends on the data available characterizing the binding specificity of the MHC molecules. It has, moreover, been demonstrated that consensus methods defined as combinations of two or more different methods led to improved prediction accuracy. This plethora of methods makes it very difficult for the non-expert user to choose the most suitable method for predicting binding to a given MHC molecule. In this study, we have therefore made an in-depth analysis of combinations of three state-of-the-art MHC-peptide binding prediction methods (NetMHC, NetMHCpan and PickPocket). We demonstrate that a simple combination of NetMHC and NetMHCpan gives the highest performance when the allele in question is included in the training and is characterized by at least 50 data points with at least ten binders. Otherwise, NetMHCpan is the best predictor. When an allele has not been characterized, the performance depends on the distance to the training data. NetMHCpan has the highest performance when close neighbours are present in the training set, while the combination of NetMHCpan and PickPocket outperforms either of the two methods for alleles with more remote neighbours. The final method, NetMHCcons, is publicly available at www.cbs.dtu.dk/services/NetMHCcons , and allows the user in an automatic manner to obtain the most accurate predictions for any given MHC molecule.

Resolution of HLA class I sequence-based typing ambiguities by group-specific sequencing primers

The increasing demand for allele-level human leukocyte antigen (HLA) typing has led the sequence-based typing (SBT) to become the preferred method. In turn, the steady increase in the number of HLA alleles driven by the adoption of SBT as the ultimate typing method leads to the ever increasing number of cis/trans ambiguities. Over the last few years, additional sequencing with the commercially available group-specific sequencing primers (GSSPs) has replaced sequence-specific primer-polymerase chain reaction and group-specific amplification as the means of resolving cis/trans ambiguities in many laboratories. Here we summarize our 3-year experience in designing and utilizing GSSPs for resolution of HLA class I ambiguities. The panel of GSSPs used in our laboratory includes 14 primers for HLA-A, 18 for HLA-B, and 13 primers for HLA-C. The panel resolves 99.9% of all ambiguities.