Pervasive haplotypic variation in the spliceo-transcriptome of the human major histocompatibility complex

Exploring the HLA complex in autoimmunity: From the risk haplotypes to the modulation of expression

The genes mapping at the HLA region show high density, strong linkage disequilibrium and high polymorphism, which affect the association of HLA class I and class II genes with autoimmunity. We focused on the HLA haplotypes, genomic structures consisting of an array of specific alleles showing some degrees of genetic association with different autoimmune disorders. GWASs in many pathologies have identified variants in either the coding loci or the flanking regulatory regions, both in linkage disequilibrium in haplotypes, that are frequently associated with increased risk and may influence gene expression. We discuss the relevance of the HLA gene expression because the level of surface heterodimers determines the number of complexes presenting self-antigen and, thus, the strength of pathogenic autoreactive T cells immune response.

Template-specific optimization of NGS genotyping pipelines reveals allele-specific variation in MHC gene expression

Using high-throughput sequencing for precise genotyping of multi-locus gene families, such as the major histocompatibility complex (MHC), remains challenging, due to the complexity of the data and difficulties in distinguishing genuine from erroneous variants. Several dedicated genotyping pipelines for data from high-throughput sequencing, such as next-generation sequencing (NGS), have been developed to tackle the ensuing risk of artificially inflated diversity. Here, we thoroughly assess three such multi-locus genotyping pipelines for NGS data, the DOC method, AmpliSAS and ACACIA, using MHC class IIβ data sets of three-spined stickleback gDNA, cDNA and "artificial" plasmid samples with known allelic diversity. We show that genotyping of gDNA and plasmid samples at optimal pipeline parameters was highly accurate and reproducible across methods. However, for cDNA data, the gDNA-optimal parameter configuration yielded decreased overall genotyping precision and consistency between pipelines. Further adjustments of key clustering parameters were required tο account for higher error rates and larger variation in sequencing depth per allele, highlighting the importance of template-specific pipeline optimization for reliable genotyping of multi-locus gene families. Through accurate paired gDNA-cDNA typing and MHC-II haplotype inference, we show that MHC-II allele-specific expression levels correlate negatively with allele number across haplotypes. Lastly, sibship-assisted cDNA-typing of MHC-I revealed novel variants linked in haplotype blocks, and a higher-than-previously-reported individual MHC-I allelic diversity. In conclusion, we provide novel genotyping protocols for the three-spined stickleback MHC-I and -II genes, and evaluate the performance of popular NGS-genotyping pipelines. We also show that fine-tuned genotyping of paired gDNA-cDNA samples facilitates amplification bias-corrected MHC allele expression analysis.

Epigenome-wide methylation haplotype association analysis identified HLA-DRB1, HLA-DRB5 and HLA-DQB1 as risk factors for rheumatoid arthritis

The aim of this study was to compare nonrandom associations between physically adjacent single methylation polymorphism loci among rheumatoid arthritis (RA) and normal subjects for investigating RA-risk methylation haplotypes (meplotype). With 354 ACPA-positive RA patients and 335 normal controls selected from a case-control study based on Swedish population, we conducted the first RA epigenome-wide meplotype association study using our software EWAS2.0, mainly including (i) converted the β value to methylation genotype (menotype) data, (ii) identified methylation disequilibrium (MD) block, (iii) calculated frequent of each meplotypes in MD block and performed case-control association test and (iv) screened for RA-risk meplotypes by odd ratio (OR) and p-values. Ultimately, 545 meplotypes on 334 MD blocks were identified significantly associated with RA (p-value < .05). These meplotypes were mapped to 329 candidate genes related to RA. Subsequently, combined with gene optimization, eight RA-risk meplotypes were identified on three risk genes: HLA-DRB1, HLA-DRB5 and HLA-DQB1. Our results reported the relationship between DNA methylation pattern on HLA-DQB1 and the risk of RA for the first time, demonstrating the co-demethylation of 'cg22984282' and 'cg13423887' on HLA-DQB1 gene (meplotype UU, p-value = 2.90E - 6, OR = 1.68, 95% CI = [1.35, 2.10]) may increase the risk of RA. Our results demonstrates the potential of methylation haplotype analysis to identify RA-related genes from a new perspective and its applicability to the study of other disease.

Regulation of expression quantitative trait loci by SVA retrotransposons within the major histocompatibility complex

Genomic and transcriptomic studies of expression quantitative trait loci (eQTL) revealed that SINE-VNTR-Alu (SVA) retrotransposon insertion polymorphisms (RIPs) within human genomes markedly affect the co-expression of many coding and noncoding genes by coordinated regulatory processes. This study examined the polymorphic SVA modulation of gene co-expression within the major histocompatibility complex (MHC) genomic region where more than 160 coding genes are involved in innate and adaptive immunity. We characterized the modulation of SVA RIPs utilizing the genomic and transcriptomic sequencing data obtained from whole blood of 1266 individuals in the Parkinson's Progression Markers Initiative (PPMI) cohort that included an analysis of human leukocyte antigen (HLA)-A regulation in a subpopulation of the cohort. The regulatory properties of eight SVAs located within the class I and class II MHC regions were associated with differential co-expression of 71 different genes within and 75 genes outside the MHC region. Some of the same genes were affected by two or more different SVA. Five SVA are annotated in the human genomic reference sequence GRCh38.p14/hg38, whereas the other three were novel insertions within individuals. We also examined and found distinct structural effects (long and short variants and the CT internal variants) for one of the SVA (R_SVA_24) insertions on the differential expression of the HLA-A gene within a subpopulation (550 individuals) of the PPMI cohort. This is the first time that many HLA and non-HLA genes (multilocus expression units) and splicing mechanisms have been shown to be regulated by eight structurally polymorphic SVA within the MHC genomic region by applying precise statistical analysis of RNA data derived from the blood samples of a human cohort population. This study shows that SVA within the MHC region are important regulators or rheostats of gene co-expression that might have potential roles in diversity, health, and disease.

Alternative splicing and genetic variation of mhc-e: implications for rhesus cytomegalovirus-based vaccines

Rhesus cytomegalovirus (RhCMV)-based vaccination against Simian Immunodeficiency virus (SIV) elicits MHC-E-restricted CD8+ T cells that stringently control SIV infection in ~55% of vaccinated rhesus macaques (RM). However, it is unclear how accurately the RM model reflects HLA-E immunobiology in humans. Using long-read sequencing, we identified 16 Mamu-E isoforms and all Mamu-E splicing junctions were detected among HLA-E isoforms in humans. We also obtained the complete Mamu-E genomic sequences covering the full coding regions of 59 RM from a RhCMV/SIV vaccine study. The Mamu-E gene was duplicated in 32 (54%) of 59 RM. Among four groups of Mamu-E alleles: three ~5% divergent full-length allele groups (G1, G2, G2_LTR) and a fourth monomorphic group (G3) with a deletion encompassing the canonical Mamu-E exon 6, the presence of G2_LTR alleles was significantly (p = 0.02) associated with the lack of RhCMV/SIV vaccine protection. These genomic resources will facilitate additional MHC-E targeted translational research.

HLA allele-specific expression: Methods, disease associations, and relevance in hematopoietic stem cell transplantation

Varying HLA allele-specific expression levels are associated with human diseases, such as graft versus host disease (GvHD) in hematopoietic stem cell transplantation (HSCT), cytotoxic T cell response and viral load in HIV infection, and the risk of Crohn’s disease. Only recently, RNA-based next generation sequencing (NGS) methodologies with accompanying bioinformatics tools have emerged to quantify HLA allele-specific expression replacing the quantitative PCR (qPCR) -based methods. These novel NGS approaches enable the systematic analysis of the HLA allele-specific expression changes between individuals and between normal and disease phenotypes. Additionally, analyzing HLA allele-specific expression and allele-specific expression loss provide important information for predicting efficacies of novel immune cell therapies. Here, we review available RNA sequencing-based approaches and computational tools for NGS to quantify HLA allele-specific expression. Moreover, we explore recent studies reporting disease associations with differential HLA expression. Finally, we discuss the role of allele-specific expression in HSCT and how considering the expression quantification in recipient-donor matching could improve the outcome of HSCT.

Aspectos técnicos y clínicos de la prueba cruzada de histocompatibilidad en el trasplante de órganos sólidos

La presencia de anticuerpos dirigidos contra los antígenos leucocitarios humanos (Human Leukocyte Antigens, HLA) que se expresan en las células del donante, es uno de los factores de riesgo más importantes asociados con las complicaciones clínicas después del trasplante. La prueba cruzada es una de las pruebas de histocompatibilidad más eficaces para la detección de anticuerpos específicos contra el donante en los receptores de injertos. En los primeros métodos de la prueba cruzada, se utilizaba la citotoxicidad dependiente del complemento, que es útil para detectar dichos anticuerpos responsables del rechazo hiperagudo del injerto, pero carece de la sensibilidad adecuada. Por ello, se desarrollaron métodos de pruebas cruzadas más sensibles, entre ellas, la prueba cruzada por citometría de flujo que hoy se considera el método preferido.

En este artículo se revisa la evolución de la prueba cruzada y los factores más importantes que deben tenerse en cuenta al realizarla y al interpretar los resultados de esta prueba fundamental para la supervivencia a largo plazo del injerto.

Regulation of HLA class I expression by non-coding gene variations

The Human Leukocyte Antigen (HLA) is a critical genetic system for different outcomes after solid organ and hematopoietic cell transplantation. Its polymorphism is usually determined by molecular technologies at the DNA level. A potential role of HLA allelic expression remains under investigation in the context of the allogenic immune response between donors and recipients. In this study, we quantified the allelic expression of all three HLA class I loci (HLA-A, B and C) by RNA sequencing and conducted an analysis of expression quantitative traits loci (eQTL) to investigate whether HLA expression regulation could be associated with non-coding gene variations. HLA-B alleles exhibited the highest expression levels followed by HLA-C and HLA-A alleles. The max fold expression variation was observed for HLA-C alleles. The expression of HLA class I loci of distinct individuals demonstrated a coordinated and paired expression of both alleles of the same locus. Expression of conserved HLA-A~B~C haplotypes differed in distinct PBMC's suggesting an individual regulated expression of both HLA class I alleles and haplotypes. Cytokines TNFα /IFNβ, which induced a very similar upregulation of HLA class I RNA and cell surface expression across alleles did not modify the individually coordinated expression at the three HLA class I loci. By identifying cis eQTLs for the HLA class I genes, we show that the non-coding eQTLs explain 29%, 13%, and 31% of the respective HLA-A, B, C expression variance in unstimulated cells, and 9%, 23%, and 50% of the variance in cytokine-stimulated cells. The eQTLs have significantly higher effect sizes in stimulated cells compared to unstimulated cells for HLA-B and HLA-C genes expression. Our data also suggest that the identified eQTLs are independent from the coding variation which defines HLA alleles and thus may be influential on intra-allele expression variability although they might not represent the causal eQTLs.

Association of HLA-DRB1, DQA1 and DQB1 alleles and haplotype in Parkinson's disease from South India

Parkinson's disease (PD) is a chronic, neurodegenerative motor disease exhibiting familial and sporadic forms. The present study was aimed to elucidate the association of HLA-DRB1*, DQA1* and DQB1* alleles with PD. A total of 105 PD patients and 100 healthy controls were typed by PCR-SSP method. We further carried out high-resolution genotyping for DQB1 and DQA1. Results revealed the increased frequencies of alleles DRB1*04 (OR = 2.36), DRB1* 13 (OR = 4.04), DQA1* 01:04:01 (OR = 4.51), DQB1*02:01 (OR = 2.66) and DQB1*06:03 (OR = 2.65) in PD patients suggesting susceptible associations. Further, decreased frequencies observed for alleles DRB1*10 (OR = 0.34), DRB1*15 (OR = 0.44), DQA1*04:01 (OR = 0.28), DQA1*06:01 (OR = 0.11) and HLA-DQB1*05:01 (OR = 0.37) among patients have suggested protective associations. Significant disease associations were observed for two-locus haplotype such as DRB1*13-DQB1*06:03 (OR = 11.52), DQA1*01:041-DQB1*06:03 (OR = 16.50), DQA1*01:041-DQB1*05:02 (OR = 5.38) and DQA1*04:01-DQB1*06:03 (OR = 3.027). Protective associations were observed for haplotypes DRB1*10-DQB1*05:01 (OR = 0.21), DRB1*15-DQB1*06 (OR = 0.006), DQA1*04:01-DQB1*05:01 (OR = 0.400) and DQA1*04:01-DQB1*05:03 (OR = 0.196). The critical amino acid residue analyses have revealed strong susceptible association for the residues of DQB1 alleles such as: L²⁶, S²⁸, K⁷¹, T⁷¹ and A⁷⁴, Y⁹, S³⁰, D³⁷, I³⁷, A³⁸, A⁵⁷ and S⁵⁷; and for the residues of DQA1 alleles such as: C¹¹, F⁶¹, I⁷⁴, and M⁷⁶. Similarly, amino acid residues such as A¹³, G²⁶, Y²⁶, A⁷¹, S⁷⁴, L⁹ and V³⁸ of HLA-DQB1 alleles and residues such as Y¹¹, G⁶¹, S⁷⁴ and L⁷⁶ of DQA1 alleles showed protective associations. Thus, our study documented the susceptible and protective associations of DRB1*, DQB1 and DQA1 alleles and haplotypes in developing the disease and their influence on longevity of PD patients in south India.

Allele-specific expression changes dynamically during T cell activation in HLA and other autoimmune loci

Genetic studies have revealed that autoimmune susceptibility variants are over-represented in memory CD4+ T cell regulatory elements1-3. Understanding how genetic variation affects gene expression in different T cell physiological states is essential for deciphering genetic mechanisms of autoimmunity4,5. Here, we characterized the dynamics of genetic regulatory effects at eight time points during memory CD4+ T cell activation with high-depth RNA-seq in healthy individuals. We discovered widespread, dynamic allele-specific expression across the genome, where the balance of alleles changes over time. These genes were enriched fourfold within autoimmune loci. We found pervasive dynamic regulatory effects within six HLA genes. HLA-DQB1 alleles had one of three distinct transcriptional regulatory programs. Using CRISPR-Cas9 genomic editing we demonstrated that a promoter variant is causal for T cell-specific control of HLA-DQB1 expression. Our study shows that genetic variation in cis-regulatory elements affects gene expression in a manner dependent on lymphocyte activation status, contributing to the interindividual complexity of immune responses.

Genetic association of molecular traits: A help to identify causative variants in complex diseases

In the past 15 years, major progresses have been made in the understanding of the genetic basis of regulation of gene expression. These new insights have revolutionized our approach to resolve the genetic variation underlying complex diseases. Gene transcript levels were the first expression phenotypes that were studied. They are heritable and therefore amenable to genome-wide association studies. The genetic variants that modulate them are called expression quantitative trait loci. Their study has been extended to other molecular quantitative trait loci (molQTLs) that regulate gene expression at the various levels, from chromatin state to cellular responses. Altogether, these studies have generated a wealth of basic information on the genome-wide patterns of gene expression and their inter-individual variation. Most importantly, molQTLs have become an invaluable asset in the genetic study of complex diseases. Although the identification of the disease-causing variants on the basis of their overlap with molQTLs requires caution, molQTLs can help to prioritize the relevant candidate gene(s) in the disease-associated regions and bring a functional interpretation of the associated variants, therefore, bridging the gap between genotypes and clinical phenotypes.

AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes

Motivation

Reliance on mapping to a single reference haplotype currently limits accurate estimation of allele or haplotype-specific expression using RNA-sequencing, notably in highly polymorphic regions such as the major histocompatibility complex.

Results

We present AltHapAlignR, a method incorporating alternate reference haplotypes to generate gene- and haplotype-level estimates of transcript abundance for any genomic region where such information is available. We validate using simulated and experimental data to quantify input allelic ratios for major histocompatibility complex haplotypes, demonstrating significantly improved correlation with ground truth estimates of gene counts compared to standard single reference mapping. We apply AltHapAlignR to RNA-seq data from 462 individuals, showing how significant underestimation of expression of the majority of classical human leukocyte antigen genes using conventional mapping can be corrected using AltHapAlignR to allow more accurate quantification of gene expression for individual alleles and haplotypes.

Availability and implementation

Source code freely available at https://github.com/jknightlab/AltHapAlignR.

Supplementary information

Supplementary data are available at Bioinformatics online.

Aberrant expression of alternative splicing variants in multiple sclerosis - A systematic review

OBJECTIVE

Alternative splicing is an important form of RNA processing that affects nearly all human genes. The differential expression of specific transcript and protein isoforms holds the potential of novel biomarkers for complex diseases. In this systematic review, we compiled the existing literature on aberrant alternative splicing events in multiple sclerosis (MS).

METHODS

A systematic literature search in the PubMed database was carried out and supplemented by screening the reference lists of the identified articles. We selected only MS-related original research studies which compared the levels of different isoforms of human protein-coding genes. A narrative synthesis of the research findings was conducted. Additionally, we performed a case-control analysis using high-density transcriptome microarray data to reevaluate the genes that were examined in the reviewed studies.

RESULTS

A total of 160 records were screened. Of those, 36 studies from the last two decades were included. Most commonly, peripheral blood samples were analyzed (32 studies), and PCR-based techniques were usually employed (27 studies) for measuring the expression of selected genes. Two studies used an exploratory genome-wide approach. Overall, 27 alternatively spliced genes were investigated. Nine of these genes appeared in at least two studies (CD40, CFLAR, FOXP3, IFNAR2, IL7R, MOG, PTPRC, SP140 and TNFRSF1A). The microarray data analysis confirmed differential alternative pre-mRNA splicing for 19 genes.

CONCLUSIONS

An altered RNA processing of genes mediating immune signaling pathways has been repeatedly implicated in MS. The analysis of individual exon-level expression patterns is stimulated by the advancement of transcriptome profiling technologies. In particular, the examination of genes encoded in MS-associated genetic regions may provide important insights into the pathogenesis of the disease and help to identify new biomarkers.

Expression estimation and eQTL mapping for HLA genes with a personalized pipeline

The HLA (Human Leukocyte Antigens) genes are well-documented targets of balancing selection, and variation at these loci is associated with many disease phenotypes. Variation in expression levels also influences disease susceptibility and resistance, but little information exists about the regulation and population-level patterns of expression. This results from the difficulty in mapping short reads originated from these highly polymorphic loci, and in accounting for the existence of several paralogues. We developed a computational pipeline to accurately estimate expression for HLA genes based on RNA-seq, improving both locus-level and allele-level estimates. First, reads are aligned to all known HLA sequences in order to infer HLA genotypes, then quantification of expression is carried out using a personalized index. We use simulations to show that expression estimates obtained in this way are not biased due to divergence from the reference genome. We applied our pipeline to the GEUVADIS dataset, and compared the quantifications to those obtained with reference transcriptome. Although the personalized pipeline recovers more reads, we found that using the reference transcriptome produces estimates similar to the personalized pipeline (r ≥ 0.87) with the exception of HLA-DQA1. We describe the impact of the HLA-personalized approach on downstream analyses for nine classical HLA loci (HLA-A, HLA-C, HLA-B, HLA-DRA, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, HLA-DPB1). Although the influence of the HLA-personalized approach is modest for eQTL mapping, the p-values and the causality of the eQTLs obtained are better than when the reference transcriptome is used. We investigate how the eQTLs we identified explain variation in expression among lineages of HLA alleles. Finally, we discuss possible causes underlying differences between expression estimates obtained using RNA-seq, antibody-based approaches and qPCR.

The MHC in the era of next-generation sequencing: Implications for bridging structure with function

The MHC continues to have the most disease-associations compared to other regions of the human genome, even in the genome-wide association study (GWAS) and single nucleotide polymorphism (SNP) era. Analysis of non-coding variation and their impact on the level of expression of HLA allotypes has shed new light on the potential mechanisms underlying HLA disease associations and alloreactivity in transplantation. Next-generation sequencing (NGS) technology has the capability of delineating the phase of variants in the HLA antigen-recognition site (ARS) with non-coding regulatory polymorphisms. These relationships are critical for understanding the qualitative and quantitative implications of HLA gene diversity. This article summarizes current understanding of non-coding region variation of HLA loci, the consequences of regulatory variation on HLA expression, the role for evolution in shaping lineage-specific expression, and the impact of HLA expression on disease susceptibility and transplantation outcomes. A role for phased sequencing methods for the MHC, and perspectives for future directions in basic and applied immunogenetic studies of the MHC are presented.

Alternatively spliced variants in Atlantic cod (Gadus morhua) support response to variable salinity environment

Analysis of gill transcriptome of the Atlantic cod from the Baltic Sea demonstrated that alternatively spliced (AS) variants may be actively involved in the process of adaptation to altered salinity. Some AS variants of different genes, like phospholipase A2 group IVC (PLA2G4C), appeared only in fish exposed to altered salinity, while other isoforms of the same genes were present in all experimental groups. Novel sequence arrangements represent 89% of all AS in the Baltic cod compared to the Atlantic population. Profiles of modified pathways suggest that regulation by AS can afford specific changes of genes expressed in response to the environment. The AS variants appear to be involved in the response to stress by modifications of signalling in apoptosis pathways, an innate immunological response and pro-inflammatory process. Present results support the hypothesis that developing new AS variants could support genome complexity and reinforce the ability to fast adapt to local environments.

What has GWAS done for HLA and disease associations?

The major histocompatibility complex (MHC) is located in chromosome 6p21 and contains crucial regulators of immune response, including human leucocyte antigen (HLA) genes, alongside other genes with nonimmunological roles. More recently, a repertoire of noncoding RNA genes, including expressed pseudogenes, has also been identified. The MHC is the most gene dense and most polymorphic part of the human genome. The region exhibits haplotype-specific linkage disequilibrium patterns, contains the strongest cis- and trans-eQTLs/meQTLs in the genome and is known as a hot spot for disease associations. Another layer of complexity is provided to the region by the extreme structural variation and copy number variations. While the HLA-B gene has the highest number of alleles, the HLA-DR/DQ subregion is structurally most variable and shows the highest number of disease associations. Reliance on a single reference sequence has complicated the design, execution and analysis of GWAS for the MHC region and not infrequently, the MHC region has even been excluded from the analysis of GWAS data. Here, we contrast features of the MHC region with the rest of the genome and highlight its complexities, including its functional polymorphisms beyond those determined by single nucleotide polymorphisms or single amino acid residues. One of the several issues with customary GWAS analysis is that it does not address this additional layer of polymorphisms unique to the MHC region. We highlight alternative approaches that may assist with the analysis of GWAS data from the MHC region and unravel associations with all functional polymorphisms beyond single SNPs. We suggest that despite already showing the highest number of disease associations, the true extent of the involvement of the MHC region in disease genetics may not have been uncovered.

Expression level of risk genes of MHC class II is a susceptibility factor for autoimmunity: New insights

To date, the study of the impact of major hystocompatibility complex on autoimmunity has been prevalently focused on structural diversity of MHC molecules in binding and presentation of (auto)antigens to cognate T cells. Recently, a number of experimental evidences suggested new points of view to investigate the complex relationships between MHC gene expression and the individual predisposition to autoimmune diseases. Irrespective of the nature of the antigen, a threshold of MHC-peptide complexes needs to be reached, as well as a threshold of T cell receptors engaged is required, for the activation and proliferation of autoantigen-reactive T cells. Moreover, it is well known that increased expression of MHC class II molecules may alter the T cell receptor repertoire during thymic development, and affect the survival and expansion of mature T cells. Many evidences confirmed that the level of both transcriptional and post-transcriptional regulation are involved in the modulation of the expression of MHC class II genes and that both contribute to the predisposition to autoimmune diseases. Here, we aim to focus some of these regulative aspects to better clarify the role of MHC class II genes in predisposition and development of autoimmunity.

Novel Transcriptional Activity and Extensive Allelic Imbalance in the Human MHC Region

The MHC region encodes HLA genes and is the most complex region in the human genome. The extensively polymorphic nature of the HLA hinders accurate localization and functional assessment of disease risk loci within this region. Using targeted capture sequencing and constructing individualized genomes for transcriptome alignment, we identified 908 novel transcripts within the human MHC region. These include 593 novel isoforms of known genes, 137 antisense strand RNAs, 119 novel long intergenic noncoding RNAs, and 5 transcripts of 3 novel putative protein-coding human endogenous retrovirus genes. We revealed allele-dependent expression imbalance involving 88% of all heterozygous transcribed single nucleotide polymorphisms throughout the MHC transcriptome. Among these variants, the genetic variant associated with Behçet's disease in the HLA-B/MICA region, which tags HLA-B*51, is within novel long intergenic noncoding RNA transcripts that are exclusively expressed from the haplotype with the protective but not the disease risk allele. Further, the transcriptome within the MHC region can be defined by 14 distinct coexpression clusters, with evidence of coregulation by unique transcription factors in at least 9 of these clusters. Our data suggest a very complex regulatory map of the human MHC, and can help uncover functional consequences of disease risk loci in this region.

A genomic perspective on HLA evolution

Several decades of research have convincingly shown that classical human leukocyte antigen (HLA) loci bear signatures of natural selection. Despite this conclusion, many questions remain regarding the type of selective regime acting on these loci, the time frame at which selection acts, and the functional connections between genetic variability and natural selection. In this review, we argue that genomic datasets, in particular those generated by next-generation sequencing (NGS) at the population scale, are transforming our understanding of HLA evolution. We show that genomewide data can be used to perform robust and powerful tests for selection, capable of identifying both positive and balancing selection at HLA genes. Importantly, these tests have shown that natural selection can be identified at both recent and ancient timescales. We discuss how findings from genomewide association studies impact the evolutionary study of HLA genes, and how genomic data can be used to survey adaptive change involving interaction at multiple loci. We discuss the methodological developments which are necessary to correctly interpret genomic analyses involving the HLA region. These developments include adapting the NGS analysis framework so as to deal with the highly polymorphic HLA data, as well as developing tools and theory to search for signatures of selection, quantify differentiation, and measure admixture within the HLA region. Finally, we show that high throughput analysis of molecular phenotypes for HLA genes-namely transcription levels-is now a feasible approach and can add another dimension to the study of genetic variation.

Quantification of classical HLA class I mRNA by allele-specific, real-time polymerase chain reaction for most Han individuals

Recent studies have shown that expression levels of different alleles at the same HLA class I locus can vary dramatically, which might have a broad influence on human disease. However, precise quantification of the relative expression level of each HLA allele is challenging, because distinguishing different alleles on the same locus is difficult. Here, we developed a series of allele-specific, real-time polymerase chain reaction assays for quantifying HLA class I allele mRNA in most Han individuals. The alleles of almost all heterozygous genotypes with a frequency higher than 0.5% in our population (78 alleles on HLA-A locus, 124 alleles on HLA-B locus, and 74 alleles on HLA-C locus) were specifically amplified. The specificity of the amplification was strictly validated by setting the corresponding negative control for each allele of each genotype. The amplification efficiency of each reaction was determined, and the slopes of the reactions were compared. This study provides a tool for detecting the comprehensive expression profile of HLA class I alleles and will be useful not only for the investigation of the molecular mechanism underlying HLA allele expression regulation but also for exploration of immunological mechanisms involving HLA expression in the fields of tumour immune evasion, viral infection, auto-immune disorders, and graft vs host disease after haematopoietic stem cell transplantation.

HLA genotyping by next-generation sequencing of complementary DNA

Background

Genotyping of the human leucocyte antigen (HLA) is indispensable for various medical treatments. However, unambiguous genotyping is technically challenging due to high polymorphism of the corresponding genomic region. Next-generation sequencing is changing the landscape of genotyping. In addition to high throughput of data, its additional advantage is that DNA templates are derived from single molecules, which is a strong merit for the phasing problem. Although most currently developed technologies use genomic DNA, use of cDNA could enable genotyping with reduced costs in data production and analysis. We thus developed an HLA genotyping system based on next-generation sequencing of cDNA.

Methods

Each HLA gene was divided into 3 or 4 target regions subjected to PCR amplification and subsequent sequencing with Ion Torrent PGM. The sequence data were then subjected to an automated analysis. The principle of the analysis was to construct candidate sequences generated from all possible combinations of variable bases and arrange them in decreasing order of the number of reads. Upon collecting candidate sequences from all target regions, 2 haplotypes were usually assigned. Cases not assigned 2 haplotypes were forwarded to 4 additional processes: selection of candidate sequences applying more stringent criteria, removal of artificial haplotypes, selection of candidate sequences with a relaxed threshold for sequence matching, and countermeasure for incomplete sequences in the HLA database.

Results

The genotyping system was evaluated using 30 samples; the overall accuracy was 97.0% at the field 3 level and 98.3% at the G group level. With one sample, genotyping of DPB1 was not completed due to short read size. We then developed a method for complete sequencing of individual molecules of the DPB1 gene, using the molecular barcode technology.

Conclusion

The performance of the automatic genotyping system was comparable to that of systems developed in previous studies. Thus, next-generation sequencing of cDNA is a viable option for HLA genotyping.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4300-7) contains supplementary material, which is available to authorized users.

Unique Allelic eQTL Clusters in Human MHC Haplotypes

The control of gene regulation within the major histocompatibility complex (MHC) remains poorly understood, despite several expression quantitative trait loci (eQTL) studies revealing an association of MHC gene expression with independent tag-single nucleotide polymorphisms (SNPs). MHC haplotype variation may exert a greater effect on gene expression phenotype than specific single variants. To explore the effect of MHC haplotype sequence diversity on gene expression phenotypes across the MHC, we examined the MHC transcriptomic landscape at haplotype-specific resolution for three prominent MHC haplotypes (A2-B46-DR9, A33-B58-DR3, and A1-B8-DR3) derived from MHC-homozygous B-lymphoblastoid cell lines (B-LCLs). We demonstrate that MHC-wide gene expression patterns are dictated by underlying haplotypes, and identify 36 differentially expressed genes. By mapping these haplotype sequence variations to known eQTL, we provide evidence that unique allelic combinations of eQTL, embedded within haplotypes, are correlated with the level of expression of 17 genes. Interestingly, the influence of haplotype sequence on gene expression is not homogenous across the MHC. We show that haplotype sequence polymorphisms within or proximate to HLA-A, HLA-C, C4A, and HLA-DRB regions exert haplotype-specific gene regulatory effects, whereas the expression of genes in other parts of the MHC region are not affected by the haplotype sequence. Overall, we demonstrate that MHC haplotype sequence diversity can impact phenotypic outcome via the alteration of transcriptional variability, indicating that a haplotype-based approach is fundamental for the assessment of trait associations in the MHC.

Abnormalities in alternative splicing in diabetes: therapeutic targets

Diabetes mellitus (DM) is a non-communicable, metabolic disorder that affects 416 million individuals worldwide. Type 2 diabetes contributes to a vast 85-90% of the diabetes incidences while 10-15% of patients suffer from type 1 diabetes. These two predominant forms of DM cause a significant loss of functional pancreatic β-cell mass causing different degrees of insulin deficiency, most likely, due to increased β-cell apoptosis. Treatment options involve the use of insulin sensitisers, α-glucosidase inhibitors, and β-cell secretagogues which are often expensive, limited in efficacy and carry detrimental adverse effects. Cost-effective options for treatment exists in the form of herbal drugs, however, scientific validations of these widely used medicinal plants are still underway. Alternative splicing (AS) is a co-ordinated post-transcriptional process in which a single gene generates multiple mRNA transcripts which results in increased amounts of functionally different protein isoforms and in some cases aberrant splicing leads to metabolic disease. In this review, we explore the association of AS with metabolic alterations in DM and the biological significance of the abnormal splicing of some pathogenic diabetes-related genes. An understanding of the molecular mechanism behind abnormally spliced transcripts will aid in the development of new diagnostic, prognostic and therapeutic tools.

Conserved 33-kb haplotype in the MHC class III region regulates chronic arthritis

Genome-wide association studies have revealed many genetic loci associated with complex autoimmune diseases. In rheumatoid arthritis (RA), the MHC gene HLA-DRB1 is the strongest candidate predicting disease development. It has been suggested that other immune-regulating genes in the MHC contribute to the disease risk, but this contribution has been difficult to show because of the strong linkage disequilibrium within the MHC. We isolated genomic regions in the form of congenic fragments in rats to test whether there are additional susceptibility loci in the MHC. By both congenic mapping in inbred strains and SNP typing in wild rats, we identified a conserved, 33-kb large haplotype Ltab-Ncr3 in the MHC-III region, which regulates the onset, severity, and chronicity of arthritis. The Ltab-Ncr3 haplotype consists of five polymorphic immunoregulatory genes: Lta (lymphotoxin-α), Tnf, Ltb (lymphotoxin-β), Lst1 (leukocyte-specific transcript 1), and Ncr3 (natural cytotoxicity-triggering receptor 3). Significant correlation in the expression of the Ltab-Ncr3 genes suggests that interaction of these genes may be important in keeping these genes clustered together as a conserved haplotype. We studied the arthritis association and the spliceo-transcriptome of four different Ltab-Ncr3 haplotypes and showed that higher Ltb and Ncr3 expression, lower Lst1 expression, and the expression of a shorter splice variant of Lst1 correlate with reduced arthritis severity in rats. Interestingly, patients with mild RA also showed higher NCR3 expression and lower LST1 expression than patients with severe RA. These data demonstrate the importance of a conserved haplotype in the regulation of complex diseases such as arthritis.

MECHANISMS IN ENDOCRINOLOGY: Alternative splicing: the new frontier in diabetes research

Type 1 diabetes (T1D) is a chronic autoimmune disease in which pancreatic β cells are killed by infiltrating immune cells and by cytokines released by these cells. This takes place in the context of a dysregulated dialogue between invading immune cells and target β cells, but the intracellular signals that decide β cell fate remain to be clarified. Alternative splicing (AS) is a complex post-transcriptional regulatory mechanism affecting gene expression. It regulates the inclusion/exclusion of exons into mature mRNAs, allowing individual genes to produce multiple protein isoforms that expand the proteome diversity. Functionally related transcript populations are co-ordinately spliced by master splicing factors, defining regulatory networks that allow cells to rapidly adapt their transcriptome in response to intra and extracellular cues. There is a growing interest in the role of AS in autoimmune diseases, but little is known regarding its role in T1D. In this review, we discuss recent findings suggesting that splicing events occurring in both immune and pancreatic β cells contribute to the pathogenesis of T1D. Splicing switches in T cells and in lymph node stromal cells are involved in the modulation of the immune response against β cells, while β cells exposed to pro-inflammatory cytokines activate complex splicing networks that modulate β cell viability, expression of neoantigens and susceptibility to immune-induced stress. Unveiling the role of AS in β cell functional loss and death will increase our understanding of T1D pathogenesis and may open new avenues for disease prevention and therapy.

The role of gene polymorphism in HLA class I splicing

Among the large number of human leucocyte antigen (HLA) alleles, only a few have been identified with a nucleotide polymorphism impairing correct splicing. Those alleles show aberrant expression levels, due to either a direct effect of the polymorphism on the normal splice site or to the creation of an alternative splice site. Furthermore, in several studies, the presence of alternatively spliced HLA transcripts co-expressed with the mature spliced transcripts was reported. We evaluated the splice site sequences of all known HLA class I alleles and found that, beside the consensus GT and AG sequences at the intron borders, there were some other highly conserved nucleotides for the different class I genes. In this review, we summarize the splicing mechanism and evaluate what is known today about alternative splicing of HLA class I genes.

Expression and alternative splicing of classical and nonclassical MHCI genes in the hippocampus and neuromuscular junction

The major histocompatibility complex class I (MHCI) is a large gene family, with over 20 members in mouse. Some MHCIs are well-known for their critical roles in the immune response. Studies in mice which lack stable cell-surface expression of many MHCI proteins suggest that one or more MHCIs also play unexpected, essential roles in the establishment, function, and modification of neuronal synapses. However, there is little information about which genes mediate MHCI's effects in neurons. In this study, RT-PCR was used to simultaneously assess transcription of many MHCI genes in regions of the central and peripheral nervous system where MHCI has a known or suspected role. In the hippocampus, a part of the CNS where MHCI regulates synapse density, synaptic transmission, and plasticity, we found that more than a dozen MHCI genes are transcribed. Single-cell RT-PCR revealed that individual hippocampal neurons can express more than one MHCI gene, and that the MHCI gene expression profile of CA1 pyramidal neurons differs significantly from that of CA3 pyramidal neurons or granule cells of the dentate gyrus. MHCI gene expression was also assessed at the neuromuscular junction (NMJ), a part of the peripheral nervous system (PNS) where MHCI plays a role in developmental synapse elimination, aging-related synapse loss, and neuronal regeneration. Four MHCI genes are expressed at the NMJ at an age when synapse elimination is occurring in three different muscles. Several MHCI mRNA splice variants were detected in hippocampus, but not at the NMJ. Together, these results establish the first profile of MHCI gene expression at the developing NMJ, and demonstrate that MHCI gene expression is under tight spatial and temporal regulation in the nervous system. They also identify more than a dozen MHCIs that could play important roles in regulating synaptic transmission and plasticity in the central and peripheral nervous systems.

Intrahaplotypic Variants Differentiate Complex Linkage Disequilibrium within Human MHC Haplotypes

Distinct regions of long-range genetic fixation in the human MHC region, known as conserved extended haplotypes (CEHs), possess unique genomic characteristics and are strongly associated with numerous diseases. While CEHs appear to be homogeneous by SNP analysis, the nature of fine variations within their genomic structure is unknown. Using multiple, MHC-homozygous cell lines, we demonstrate extensive sequence conservation in two common Asian MHC haplotypes: A33-B58-DR3 and A2-B46-DR9. However, characterization of phase-resolved MHC haplotypes revealed unique intra-CEH patterns of variation and uncovered 127 single nucleotide variants (SNVs) which are missing from public databases. We further show that the strong linkage disequilibrium structure within the human MHC that typically confounds precise identification of genetic features can be resolved using intra-CEH variants, as evidenced by rs3129063 and rs448489, which affect expression of ZFP57, a gene important in methylation and epigenetic regulation. This study demonstrates an improved strategy that can be used towards genetic dissection of diseases.

The dichotomy between disease phenotype databases and the implications for understanding complex diseases involving the major histocompatibility complex

Many genes related to innate and adaptive immunity reside within the major histocompatibility complex (MHC) and have been associated with a multitude of complex, immune-related disorders. Despite years of genetic study, this region has seen few causative determinants discovered for immune-mediated diseases. Reported associations have been curated in various databases including the Genetic Association Database, NCBI database of clinically relevant variants (ClinVar) and the Human Gene Mutation Database and together capture genetic associations and annotated pathogenic loci within the MHC and across the genome for a variety of complex, immune-mediated diseases. A review of these three distinct databases reveals disparate annotations between associated genes and pathogenic loci, alluding to the polygenic, multifactorial nature of immune-mediated diseases and the pleiotropic character of genes within the MHC. The technical limitations and inherent biases imposed by current approaches and technologies in studying the MHC create a strong case for the need to perform targeted deep sequencing of the MHC and other immunologically relevant loci in order to fully elucidate and study the causative elements of complex immune-mediated diseases.

Genome-wide peripheral blood transcriptome analysis of Arab female lupus and lupus nephritis

Systemic lupus erythematosus (lupus) is a genetically heterogeneous autoimmune disorder with an obscure etiology. With 92-94% of human genes exhibiting alternative splicing, gaining insights to such events may lead to better diagnostics. Herein, we explored the genome-wide peripheral blood transcriptome of lupus and its severe form lupus-nephritis (LN) compared to healthy controls (HC). Age/gender/ethnically-matched Arab females were tested using high-density arrays and statistical analysis was carried out using appropriate software. Analysis revealed 15 splice variants that are differentially expressed between lupus/HC and 99 variants between LN/HC (p ≤ 0.05, SI> or ≤ 0.5, Benjamin Hochberg-False discovery rate correction). Comparison between LN/lupus revealed 7 variants that significantly differed in expression. Pathway analysis of differentially spliced-genes postulated 11 significant pathways in lupus and 12 in LN (p<0.05). Analysis of peripheral blood transcriptome possibly revealed signature causative genes that are alternatively spliced, signifying their clinical relevance. Present study is the first to reveal the significance of alternative variants in lupus and LN.

Genome-wide association study of footrot in Texel sheep

Background

This is the first study based on a genome-wide association approach that investigates the links between ovine footrot scores and molecular polymorphisms in Texel sheep using the ovine 50 K SNP array (42 883 SNPs (single nucleotide polymorphisms) after quality control). Our aim was to identify molecular predictors of footrot resistance.

Methods

This study used data from animals selected from a footrot-phenotyped Texel sheep population of 2229 sheep with an average of 1.60 scoring records per animal. From these, a subset of 336 animals with extreme trait values for footrot was selected for genotyping based on their phenotypic records. De-regressed estimated breeding values (EBV) for footrot were used as pseudo-phenotypes in the genome-wide association analysis.

Results

Seven SNPs were significant on a chromosome-wise level but the association analysis did not reveal any genome-wise significant SNPs associated with footrot. Based on the current state of knowledge of the ovine genome, it is difficult to clearly link the function of the genes that contain these significant SNPs with a potential role in resistance/susceptibility to footrot. Linkage disequilibrium (LD) was analysed as one of the factors that influence the power of detecting QTL (quantitative trait loci). A mean LD of 0.20 (r² at a distance of 50 kb between two SNPs) in the population analysed was estimated. LD declined from 0.15 to 0.07 and to 0.04 at distances between two SNPs of 100, 1000 and 2000 kb, respectively.

Conclusions

Based on a relatively small number of genotyped animals, this study is a first step to search for genomic regions that are involved in resistance to footrot using the ovine 50 K SNP array. Seven SNPs were found to be significant on a chromosome-wise level. No major genome-wise significant QTL were identified.

The relevance of HLA sequencing in population genetics studies

Next generation sequencing (NGS) is currently being adapted by different biotechnological platforms to the standard typing method for HLA polymorphism, the huge diversity of which makes this initiative particularly challenging. Boosting the molecular characterization of the HLA genes through efficient, rapid, and low-cost technologies is expected to amplify the success of tissue transplantation by enabling us to find donor-recipient matching for rare phenotypes. But the application of NGS technologies to the molecular mapping of the MHC region also anticipates essential changes in population genetic studies. Huge amounts of HLA sequence data will be available in the next years for different populations, with the potential to change our understanding of HLA variation in humans. In this review, we first explain how HLA sequencing allows a better assessment of the HLA diversity in human populations, taking also into account the methodological difficulties it introduces at the statistical level; secondly, we show how analyzing HLA sequence variation may improve our comprehension of population genetic relationships by facilitating the identification of demographic events that marked human evolution; finally, we discuss the interest of both HLA and genome-wide sequencing and genotyping in detecting functionally significant SNPs in the MHC region, the latter having also contributed to the makeup of the HLA molecular diversity observed today.

Multiple sclerosis: autoimmunity and viruses

PURPOSE OF REVIEW

This review will explore two new aspects of the involvement of viruses in multiple sclerosis pathogenesis. The first aspect is the complex interactions between viruses. The second aspect is the proposal of a mechanism by which autoreactive T cells are able to escape thymic selection and potentially recognize self and a pathogen.

RECENT FINDINGS

With regard to viruses, recent work has demonstrated that one virus may enhance the replication of another virus, potentially leading to an increase in inflammation and disease progression. Also, interactions between human endogenous retroviruses, which likely do not replicate, and certain herpes viruses, may also play a role in disease pathogenesis. Mechanistically, T cells expressing dual T-cell receptors would be able to recognize self and a foreign antigen specifically. Therefore, human endogenous retroviruses potentially play a role in multiple sclerosis pathogenesis, and both interactions between multiple viruses and autoreactive CD8(+) T cells with dual T-cell receptors may play a role in the pathogenesis of the disease.

SUMMARY

The complex interactions between multiple viral infections, either within the central nervous system or in the periphery, and the host immune response to viral infection may be such that a variety of viral specificities result in the activation of T cells that recognize self and induce multiple sclerosis. Therefore, it is unlikely that any one microbe will be determined to be the causative agent of multiple sclerosis as reflected by the number of potential triggering mechanisms of the disease.

A joint analysis to identify loci underlying variation in nematode resistance in three European sheep populations

Gastrointestinal nematode infections are one of the main health/economic issues in sheep industries, worldwide. Indicator traits for resistance such as faecal egg count (FEC) are commonly used in genomic studies; however, published results are inconsistent among breeds. Meta (or joint)-analysis is a tool for aggregating information from multiple independent studies. The aim of this study was to identify loci underlying variation in FEC, as an indicator of nematode resistance, in a joint analysis using data from three populations (Scottish Blackface, Sarda × Lacaune and Martinik Black-Belly × Romane), genotyped with the ovine 50k SNP chip. The trait analysed was the average animal effect for Strongyles and Nematodirus FEC data. Analyses were performed with regional heritability mapping (RHM), fitting polygenic effects with either the whole genomic relationship matrix or matrices excluding the chromosome being interrogated. Across-population genomic covariances were set to zero. After quality control, 4123 animals and 38 991 SNPs were available for the analysis. RHM identified genome-wide significant regions on OAR4, 12, 14, 19 and 20, with the latter being the most significant. The OAR20 region is close to the major histocompatibility complex, which has often been proposed as a functional candidate for nematode resistance. This region was significant only in the Sarda × Lacaune population. Several other regions, on OAR1, 3, 4, 5, 7, 12, 19, 20 and 24, were significant at the suggestive level.

Genomics of alternative splicing: evolution, development and pathophysiology

Alternative splicing is a major cellular mechanism in metazoans for generating proteomic diversity. A large proportion of protein-coding genes in multicellular organisms undergo alternative splicing, and in humans, it has been estimated that nearly 90 % of protein-coding genes-much larger than expected-are subject to alternative splicing. Genomic analyses of alternative splicing have illuminated its universal role in shaping the evolution of genomes, in the control of developmental processes, and in the dynamic regulation of the transcriptome to influence phenotype. Disruption of the splicing machinery has been found to drive pathophysiology, and indeed reprogramming of aberrant splicing can provide novel approaches to the development of molecular therapy. This review focuses on the recent progress in our understanding of alternative splicing brought about by the unprecedented explosive growth of genomic data and highlights the relevance of human splicing variation on disease and therapy.

Fine mapping genetic determinants of the highly variably expressed MHC gene ZFP57

ZFP57 is an important transcriptional regulator involved in DNA methylation and genomic imprinting during development. Here we demonstrate that gene expression also occurs at a low level in adult peripheral blood cells and other tissues including the kidney and thymus, but is critically dependent on underlying local genetic variation within the MHC. We resolve a highly significant expression quantitative trait locus for ZFP57 involving single-nucleotide polymorphisms (SNPs) in the first intron of the gene co-localizing with a DNase I hypersensitive site and evidence of CTCF recruitment. These data identify ZFP57 as a candidate gene underlying reported MHC disease associations, notably for putative regulatory variants associated with cancer and HIV-1. The work highlights the role that ZFP57 may play in DNA methylation and epigenetic regulation beyond early development into adult life dependent on genetic background, with important potential implications for disease.

The major histocompatibility complex: a model for understanding graft-versus-host disease

Acute graft-versus-host disease (GVHD) afflicts as much as 80% of all patients who receive an unrelated donor hematopoietic cell transplant (HCT) for the treatment of blood disorders, even with optimal donor HLA matching and use of prophylactic immunosuppressive agents. Of patients who develop acute GVHD, many are at risk for chronic GVHD and bear the burden of considerable morbidity and lowered quality of life years after transplantation. The immunogenetic basis of GVHD has been the subject of intensive investigation, with the classic HLA genetic loci being the best-characterized determinants. Recent information on the major histocompatibility complex (MHC) region of chromosome 6 as an important source of untyped genetic variation has shed light on novel GVHD determinants. These data open new paradigms for understanding the genetic basis of GVHD.

Major histocompatibility complex genomics and human disease

Over several decades, various forms of genomic analysis of the human major histocompatibility complex (MHC) have been extremely successful in picking up many disease associations. This is to be expected, as the MHC region is one of the most gene-dense and polymorphic stretches of human DNA. It also encodes proteins critical to immunity, including several controlling antigen processing and presentation. Single-nucleotide polymorphism genotyping and human leukocyte antigen (HLA) imputation now permit the screening of large sample sets, a technique further facilitated by high-throughput sequencing. These methods promise to yield more precise contributions of MHC variants to disease. However, interpretation of MHC-disease associations in terms of the functions of variants has been problematic. Most studies confirm the paramount importance of class I and class II molecules, which are key to resistance to infection. Infection is likely driving the extreme variation of these genes across the human population, but this has been difficult to demonstrate. In contrast, many associations with autoimmune conditions have been shown to be specific to certain class I and class II alleles. Interestingly, conditions other than infections and autoimmunity are also associated with the MHC, including some cancers and neuropathies. These associations could be indirect, owing, for example, to the infectious history of a particular individual and selective pressures operating at the population level.

A genome-wide association study identifies 6p21 as novel risk locus for dilated cardiomyopathy

AIMS

Dilated cardiomyopathy (DCM) is one of the leading causes for cardiac transplantations and accounts for up to one-third of all heart failure cases. Since extrinsic and monogenic causes explain only a fraction of all cases, common genetic variants are suspected to contribute to the pathogenesis of DCM, its age of onset, and clinical progression. By a large-scale case-control genome-wide association study we aimed here to identify novel genetic risk loci for DCM.

METHODS AND RESULTS

Applying a three-staged study design, we analysed more than 4100 DCM cases and 7600 controls. We identified and successfully replicated multiple single nucleotide polymorphism on chromosome 6p21. In the combined analysis, the most significant association signal was obtained for rs9262636 (P = 4.90 × 10(-9)) located in HCG22, which could again be replicated in an independent cohort. Taking advantage of expression quantitative trait loci (eQTL) as molecular phenotypes, we identified rs9262636 as an eQTL for several closely located genes encoding class I and class II major histocompatibility complex heavy chain receptors.

CONCLUSION

The present study reveals a novel genetic susceptibility locus that clearly underlines the role of genetically driven, inflammatory processes in the pathogenesis of idiopathic DCM.

Genetic variants contribute to gene expression variability in humans

Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and gene expression. Most of these studies focused on the mean of gene expression level, but not the variance of gene expression level (i.e., gene expression variability). In the present study, we systematically explore genome-wide association between genetic variants and gene expression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of gene expression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of gene expression and the genotypes are termed expression variability QTL (evQTL). Using a data set of gene expression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of gene expression variability is discussed.

Genomic modulators of the immune response

Our understanding of immunity has historically been informed by studying heritable mutations in both the adaptive and innate immune responses, including primary immunodeficiency and autoimmune diseases. Recent advances achieved through the application of genomic and epigenomic approaches are reshaping the study of immune dysfunction and opening up new avenues for therapeutic interventions. Moreover, applying genomic techniques to resolve functionally important genetic variation between individuals is providing new insights into immune function in health. This review describes progress in the study of rare variants and primary immunodeficiency diseases arising from whole-exome sequencing (WES), and discusses the application, success, and challenges of applying genome-wide association studies (GWAS) to disorders of immune function and how they may inform more rational use of therapeutics. In addition, the application of expression quantitative-trait mapping to immune phenotypes, progress in understanding MHC disease associations, and insights into epigenetic mechanisms at the interface of immunity and the environment are reviewed.

Health 2050: The Realization of Personalized Medicine through Crowdsourcing, the Quantified Self, and the Participatory Biocitizen

The concepts of health and health care are moving towards the notion of personalized preventive health maintenance and away from an exclusive focus on the cure of disease. This is against the backdrop of contemporary public health challenges that include increasing costs, worsening outcomes, ‘diabesity’ epidemics, and anticipated physician shortages. Personalized preventive medicine could be critical to solving public health challenges at their causal root. This paper sets forth a vision and plan for the realization of preventive medicine by 2050 and examines efforts already underway such as participatory health initiatives, the era of big health data, and qualitative shifts in mindset.

Identification and characterization of a novel splice variant of rhesus macaque MHC IA

Major histocompatibility complex class I (MHC I) molecules play a pivotal role in the immune recognition to intracellular pathogens. A number of important splice variants have already been characterized for these molecules in different species, suggesting their important roles in modulation of immune responses. In this study, we have identified and characterized a novel alternatively spliced form of rhesus macaque MHC IA (designated MHC IA-sv2) that lacks exons coding for the α2 and α3 domains. Despite lacking the α2 and α3 domains, MHC IA-sv2 is targeted to the cell surface, as a 23-kDa glycoprotein that is totally susceptible to endoglycosidase-H digestion and is reduced to 18kDa after deglycosylation with PNGase F. In contrast, the full-length MHC IA reaches the cell surface as a 43-kDa protein of form with complex-type N-glycosylation (endoglycosidase-H resistant). Moreover, we provide evidence here that MHC IA-sv2 can self-associate, forming homodimers, or associate with the fully mature MHC IA molecule, forming a heterodimeric structure in mammalian cells. These data demonstrate that the formation of heterodimers may have some functional implications in the fine tuning of MHC IA-mediated innate and adaptive immune responses.

Insights into type 1 diabetes provided by genetic analyses

PURPOSE OF REVIEW

Recent identification of over 60 loci contributing to the susceptibility of developing type 1 diabetes (T1D) provides a timely opportunity to assess what is currently known of the genetics of T1D, and what these discoveries may tell us about the disease itself.

RECENT FINDINGS

The major findings will be discussed under five main themes: T1D risk gene identification, molecular mechanisms of susceptibility, shared genetic cause with other diseases, development of novel analytical methods, and understanding disease heterogeneity.

SUMMARY

The plethora of T1D risk genes that have been identified risk overwhelming clinicians with lists of gene names and symbols that have little bearing on management, and provide a challenge for researchers to place the genetics of T1D in a more amenable clinical context.