A statistical method for predicting classical HLA alleles from SNP data

Genetic variation at classical HLA alleles is a crucial determinant of transplant success and susceptibility to a large number of infectious and autoimmune diseases. However, large-scale studies involving classical type I and type II HLA alleles might be limited by the cost of allele-typing technologies. Although recent studies have shown that some common HLA alleles can be tagged with small numbers of markers, SNP-based tagging does not offer a complete solution to predicting HLA alleles. We have developed a new statistical methodology to use SNP variation within the region to predict alleles at key class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1, HLA-DQA1, and HLA-DQB1) loci. Our results indicate that a single panel of approximately 100 SNPs typed across the region is sufficient for predicting both rare and common HLA alleles with up to 95% accuracy in both African and non-African populations. Furthermore, we show that HLA alleles can be successfully predicted by using previously genotyped SNPs that are within the MHC and that had not been chosen for their ability to predict HLA alleles, such as those included on genome-wide products. These results indicate that our methodology, combined with an extended database of reference haplotypes, will facilitate large-scale experiments, including disease-association studies and vaccine trials, in which detailed information about HLA type is valuable.     

A population-based LD map of the human chromosome 6p

The recent publication of the complete sequence of human chromosome 6 provides a platform from which to investigate genomic sequence variation. We report here a detailed linkage disequilibrium (LD) pattern map across the entire human chromosome 6p by using a set of 1152 single nucleotide polymorphisms (SNPs) in a population of 198 Singaporean Chinese, with 326 SNPs focused in the major histocompatibility complex (MHC) region. Our analysis shows some unexpectedly high segments of strong LD in a 10-Mb region that includes the extremely polymorphic and gene-rich MHC loci and many non-MHC genes. These include the telomeric peri-MHC region that harbors olfactory receptors, histones and zinc finger clusters, and the centromeric peri-MHC region that contains several unknown open reading frames. The data also help refine a human–mouse synteny break in the region between 28.6 and 29.4 Mb. The population-based LD map presented here will provide an essential resource for understanding the genomic sequence variation of chromosome 6p and LD mapping of disease genes of complex genetic traits. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users. H. Yu and J.-M. Chia should be regarded as joint first authors.     

Unraveling Multiple MHC Gene Associations with Systemic Lupus Erythematosus: Model Choice Indicates a Role for HLA Alleles and Non-HLA Genes in Europeans

We have performed a meta-analysis of the major-histocompatibility-complex (MHC) region in systemic lupus erythematosus (SLE) to determine the association with both SNPs and classical human-leukocyte-antigen (HLA) alleles. More specifically, we combined results from six studies and well-known out-of-study control data sets, providing us with 3,701 independent SLE cases and 12,110 independent controls of European ancestry. This study used genotypes for 7,199 SNPs within the MHC region and for classical HLA alleles (typed and imputed). Our results from conditional analysis and model choice with the use of the Bayesian information criterion show that the best model for SLE association includes both classical loci (HLA-DRB1^∗03:01, HLA-DRB1^∗08:01, and HLA-DQA1^∗01:02) and two SNPs, rs8192591 (in class III and upstream of NOTCH4) and rs2246618 (MICB in class I). Our approach was to perform a stepwise search from multiple baseline models deduced from a priori evidence on HLA-DRB1 lupus-associated alleles, a stepwise regression on SNPs alone, and a stepwise regression on HLA alleles. With this approach, we were able to identify a model that was an overwhelmingly better fit to the data than one identified by simple stepwise regression either on SNPs alone (Bayes factor [BF] > 50) or on classical HLA alleles alone (BF > 1,000).     

Detection, imputation, and association analysis of small deletions and null alleles on oligonucleotide arrays

Copy-number variation (CNV) is a major contributor to human genetic variation. Recently, CNV associations with human disease have been reported. Many genome-wide association (GWA) studies in complex diseases have been performed with sets of biallelic single-nucleotide polymorphisms (SNPs), but the available CNV methods are still limited. We present a new method (TriTyper) that can infer genotypes in case-control data sets for deletion CNVs, or SNPs with an extra, untyped allele at a high-resolution single SNP level. By accounting for linkage disequilibrium (LD), as well as intensity data, calling accuracy is improved. Analysis of 3102 unrelated individuals with European descent, genotyped with Illumina Infinium BeadChips, resulted in the identification of 1880 SNPs with a common untyped allele, and these SNPs are in strong LD with neighboring biallelic SNPs. Simulations indicate our method has superior power to detect associations compared to biallelic SNPs that are in LD with these SNPs, yet without increasing type I errors, as shown in a GWA analysis in celiac disease. Genotypes for 1204 triallelic SNPs could be fully imputed, with only biallelic-genotype calls, permitting association analysis of these SNPs in many published data sets. We estimate that 682 of the 1655 unique loci reflect deletions; this is on average 99 deletions per individual, four times greater than those detected by other methods. Whereas the identified loci are strongly enriched for known deletions, 61% have not been reported before. Genes overlapping with these loci more often have paralogs (p = 0.006) and biologically interact with fewer genes than expected (p = 0.004).     

HLA DNA sequence variation among human populations: molecular signatures of demographic and selective events

Molecular differences between HLA alleles vary up to 57 nucleotides within the peptide binding coding region of human Major Histocompatibility Complex (MHC) genes, but it is still unclear whether this variation results from a stochastic process or from selective constraints related to functional differences among HLA molecules. Although HLA alleles are generally treated as equidistant molecular units in population genetic studies, DNA sequence diversity among populations is also crucial to interpret the observed HLA polymorphism. In this study, we used a large dataset of 2,062 DNA sequences defined for the different HLA alleles to analyze nucleotide diversity of seven HLA genes in 23,500 individuals of about 200 populations spread worldwide. We first analyzed the HLA molecular structure and diversity of these populations in relation to geographic variation and we further investigated possible departures from selective neutrality through Tajima's tests and mismatch distributions. All results were compared to those obtained by classical approaches applied to HLA allele frequencies.Our study shows that the global patterns of HLA nucleotide diversity among populations are significantly correlated to geography, although in some specific cases the molecular information reveals unexpected genetic relationships. At all loci except HLA-DPB1, populations have accumulated a high proportion of very divergent alleles, suggesting an advantage of heterozygotes expressing molecularly distant HLA molecules (asymmetric overdominant selection model). However, both different intensities of selection and unequal levels of gene conversion may explain the heterogeneous mismatch distributions observed among the loci. Also, distinctive patterns of sequence divergence observed at the HLA-DPB1 locus suggest current neutrality but old selective pressures on this gene. We conclude that HLA DNA sequences advantageously complement HLA allele frequencies as a source of data used to explore the genetic history of human populations, and that their analysis allows a more thorough investigation of human MHC molecular evolution.     

Biological implication for loss of function at major histocompatibility complex loci

Despite relatively frequent gene or segment duplications, the number of functional loci in the major histocompatibility complex (MHC) is relatively small. The dual function of MHC molecules (triggering the immune system and limiting T-cell receptor repertoires) is likely to balance the number of functional loci. The effect of this dual function on the number of functional MHC loci has been argued mainly in the theoretical and computer simulation studies, but the evidence from empirical data has not been fully examined. Here, we attempt to evaluate this effect based on the analysis of nucleotide sequence data. We hypothesized that due to the dual function, even becoming a pseudogene (pseudogenization) of MHC is advantageous for the organisms. To evaluate this hypothesis, we compared the distribution of the waiting time (T (W)) till pseudogenization for HLA (human MHC) with that of the human olfactory receptor (OR) and bitter taste receptor (T2R) genes. The result shows that T (W) in HLA has a tendency to be relatively shorter as the emergence time (T) of the gene becomes older, while in OR T (W) becomes proportionally longer as T becomes older and in T2R it is almost null irrespective of T. Furthermore, T (W) in HLA is strongly influenced by the extent of functional differentiation in the peptide-binding region. Taken together, these results show that MHC molecules have optimal numbers of functional loci, and these numbers are regulated by the advantageous pseudogenization of duplicated copies.     

Association analysis of the extended MHC region in celiac disease implicates multiple independent susceptibility loci

Celiac disease is a common autoimmune disease caused by sensitivity to the dietary protein gluten. Forty loci have been implicated in the disease. All disease loci have been characterized as low-penetrance, with the exception of the high-risk genotypes in the HLA-DQA1 and HLA-DQB1 genes, which are necessary but not sufficient to cause the disease. The very strong effects from the known HLA loci and the genetically complex nature of the major histocompatibility complex (MHC) have precluded a thorough investigation of the region. The purpose of this study was to test the hypothesis that additional celiac disease loci exist within the extended MHC (xMHC). A set of 1898 SNPs was analyzed for association across the 7.6 Mb xMHC region in 1668 confirmed celiac disease cases and 517 unaffected controls. Conditional recursive partitioning was used to create an informative indicator of the known HLA-DQA1 and HLA-DQB1 high-risk genotypes that was included in the association analysis to account for their effects. A linkage disequilibrium-based grouping procedure was utilized to estimate the number of independent celiac disease loci present in the xMHC after accounting for the known effects. There was significant statistical evidence for four new independent celiac disease loci within the classic MHC region. This study is the first comprehensive association analysis of the xMHC in celiac disease that specifically accounts for the known HLA disease genotypes and the genetic complexity of the region.     

Distinct Genetic Loci Control Plasma HIV-RNA and Cellular HIV-DNA Levels in HIV-1 Infection: The ANRS Genome Wide Association 01 Study

Previous studies of the HIV-1 disease have shown that HLA and Chemokine receptor genetic variants influence disease progression and early viral load. We performed a Genome Wide Association study in a cohort of 605 HIV-1-infected seroconverters for detection of novel genetic factors that influence plasma HIV-RNA and cellular HIV-DNA levels. Most of the SNPs strongly associated with HIV-RNA levels were localised in the 6p21 major histocompatibility complex (MHC) region and were in the vicinity of class I and III genes. Moreover, protective alleles for four disease-associated SNPs in the MHC locus (rs2395029, rs13199524, rs12198173 and rs3093662) were strikingly over-represented among forty-five Long Term HIV controllers. Furthermore, we show that the HIV-DNA levels (reflecting the HIV reservoir) are associated with the same four SNPs, but also with two additional SNPs on chromosome 17 (rs6503919; intergenic region flanked by the DDX40 and YPEL2 genes) and chromosome 8 (rs2575735; within the Syndecan 2 gene). Our data provide evidence that the MHC controls both HIV replication and HIV reservoir. They also indicate that two additional genomic loci may influence the HIV reservoir.     

Genetic drift outweighs balancing selection in shaping post-bottleneck major histocompatibility complex variation in New Zealand robins (Petroicidae)

The Chatham Island black robin, Petroica traversi, is a highly inbred, endangered passerine with extremely low levels of variation at hypervariable neutral DNA markers. In this study we investigated variation in major histocompatibility complex (MHC) class II genes in both the black robin and its nonendangered relative, the South Island robin Petroica australis australis. Previous studies have shown that Petroica have at least four expressed class II B MHC genes. In this study, the sequences of introns flanking exon 2 of these loci were characterized to design primers for peptide-binding region (PBR) sequence analysis. Intron sequences were comprised of varying numbers of repeated units, with highly conserved regions immediately flanking exon 2. Polymerase chain reaction primers designed to this region amplified three or four sequences per black robin individual, and eight to 14 sequences per South Island robin individual. MHC genes are fitness-related genes thought to be under balancing selection, so they may be more likely to retain variation in bottlenecked populations. To test this, we compared MHC variation in the black robin with artificially bottlenecked populations of South Island robin, and with their respective source populations, using restriction fragment length polymorphism analyses and DNA sequencing of the PBR. Our results indicate that the black robin is monomorphic at class II B MHC loci, while both source and bottlenecked populations of South Island robin have retained moderate levels of variation. Comparison of MHC variation with minisatellite DNA variation indicates that genetic drift outweighs balancing selection in determining MHC diversity in the bottlenecked populations. However, balancing selection appears to influence MHC diversity over evolutionary timescales, and the effects of gene conversion are evident.     

Signatures of demographic history and natural selection in the human major histocompatibility complex Loci

Many lines of evidence show that several HLA loci have experienced balancing selection. However, distinguishing among demographic and selective explanations for patterns of variation observed with HLA genes remains a challenge. In this study we address this issue using data from a diverse set of human populations at six classical HLA loci and, employing a comparative genomics approach, contrast results for HLA loci to those for non-HLA markers. Using a variety of analytic methods, we confirm and extend evidence for selection acting on several HLA loci. We find that allele frequency distributions for four of the six HLA loci deviate from neutral expectations and show that this is unlikely to be explained solely by demographic factors. Other features of HLA variation are explained in part by demographic history, including decreased heterozygosity and increased LD for populations at greater distances from Africa and a similar apportionment of genetic variation for HLA loci compared to putatively neutral non-HLA loci. On the basis of contrasts among different HLA loci and between HLA and non-HLA loci, we conclude that HLA loci bear detectable signatures of both natural selection and demographic history.     

Analysis of MHC class I genes across horse MHC haplotypes

The genomic sequences of 15 horse major histocompatibility complex (MHC) class I genes and a collection of MHC class I homozygous horses of five different haplotypes were used to investigate the genomic structure and polymorphism of the equine MHC. A combination of conserved and locus-specific primers was used to amplify horse MHC class I genes with classical and nonclassical characteristics. Multiple clones from each haplotype identified three to five classical sequences per homozygous animal and two to three nonclassical sequences. Phylogenetic analysis was applied to these sequences, and groups were identified which appear to be allelic series, but some sequences were left ungrouped. Sequences determined from MHC class I heterozygous horses and previously described MHC class I sequences were then added, representing a total of ten horse MHC haplotypes. These results were consistent with those obtained from the MHC homozygous horses alone, and 30 classical sequences were assigned to four previously confirmed loci and three new provisional loci. The nonclassical genes had few alleles and the classical genes had higher levels of allelic polymorphism. Alleles for two classical loci with the expected pattern of polymorphism were found in the majority of haplotypes tested, but alleles at two other commonly detected loci had more variation outside of the hypervariable region than within. Our data indicate that the equine major histocompatibility complex is characterized by variation in the complement of class I genes expressed in different haplotypes in addition to the expected allelic polymorphism within loci.     

Imputing Amino Acid Polymorphisms in Human Leukocyte Antigens

DNA sequence variation within human leukocyte antigen (HLA) genes mediate susceptibility to a wide range of human diseases. The complex genetic structure of the major histocompatibility complex (MHC) makes it difficult, however, to collect genotyping data in large cohorts. Long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC) region offers an alternative approach through imputation to interrogate HLA variation in existing GWAS data sets. Here we describe a computational strategy, SNP2HLA, to impute classical alleles and amino acid polymorphisms at class I (HLA-A, -B, -C) and class II (-DPA1, -DPB1, -DQA1, -DQB1, and -DRB1) loci. To characterize performance of SNP2HLA, we constructed two European ancestry reference panels, one based on data collected in HapMap-CEPH pedigrees (90 individuals) and another based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals). We imputed HLA alleles in an independent data set from the British 1958 Birth Cohort (N = 918) with gold standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500 K and Illumina Immunochip microarrays. We demonstrate that the sample size of the reference panel, rather than SNP density of the genotyping platform, is critical to achieve high imputation accuracy. Using the larger T1DGC reference panel, the average accuracy at four-digit resolution is 94.7% using the low-density Affymetrix GeneChip 500 K, and 96.7% using the high-density Illumina Immunochip. For amino acid polymorphisms within HLA genes, we achieve 98.6% and 99.3% accuracy using the Affymetrix GeneChip 500 K and Illumina Immunochip, respectively. Finally, we demonstrate how imputation and association testing at amino acid resolution can facilitate fine-mapping of primary MHC association signals, giving a specific example from type 1 diabetes.     

The predisposition to type 1 diabetes linked to the human leukocyte antigen complex includes at least one non-class II gene

The human leukocyte antigen (HLA) complex, encompassing 3.5 Mb of DNA from the centromeric HLA-DPB2 locus to the telomeric HLA-F locus on chromosome 6p21, encodes a major part of the genetic predisposition to develop type 1 diabetes, designated "IDDM1." A primary role for allelic variation of the class II HLA-DRB1, HLA-DQA1, and HLA-DQB1 loci has been established. However, studies of animals and humans have indicated that other, unmapped, major histocompatibility complex (MHC)-linked genes are participating in IDDM1. The strong linkage disequilibrium between genes in this complex makes mapping a difficult task. In the present paper, we report on the approach we have devised to circumvent the confounding effects of disequilibrium between class II alleles and alleles at other MHC loci. We have scanned 12 Mb of the MHC and flanking chromosome regions with microsatellite polymorphisms and analyzed the transmission of these marker alleles to diabetic probands from parents who were homozygous for the alleles of the HLA-DRB1, HLA-DQA1, and HLA-DQB1 genes. Our analysis, using three independent family sets, suggests the presence of an additional type I diabetes gene (or genes). This approach is useful for the analysis of other loci linked to common diseases, to verify if a candidate polymorphism can explain all of the association of a region or if the association is due to two or more loci in linkage disequilibrium with each other.     

Genomic Organization Around the Centromeric End of the HLA Class I Region: Large-Scale Sequence Analysis

We previously sequenced two regions around the centromeric end of HLA class I and the boundary between class I and class III. In this paper we analyze the two regions of about 385 kb and confirm, giving a new line of evidence, that the following two pairs of the genomic segments were duplicated in evolution: (i) a 43-kb genomic segment including the HLA-B gene showing the highest polymorphism among the classical HLA class I loci (class Ia) and a 40-kb segment including the HLA-C locus showing the lowest polymorphism and (ii) a 52-kb segment including the MIC (MHC class I chain related gene) B and a 35-kb segment including MICA. We also found that repetitive elements such as SINEs, LINEs, and LTRs occupy as much as 47% of nucleotides in this 385-kb region. This unusually high content of repetitive elements indicates that repeat-mediated rearrangements have frequently occurred in the evolutionary history of the HLA class Ia region. Analysis of LINE compositions within the two pairs of duplicated segments revealed that (i) LINEs in these regions had been dispersed prior to both the duplication of the HLA-B and -C loci and the duplication of the MICB and MICA loci, and (ii) the divergence of the HLA-B and -C loci occurred prior to the duplication of the MICA and MICB loci. To find novel genes responsible for HLA class I-associated or other diseases, we performed computer analysis applying GenScan and GRAIL to GenBank's dbEST. As a result, at least five as yet uncharacterized genes were newly mapped on the HLA class I centromeric region studied. These novel genes should be analyzed further to determine their relationships to diseases associated with this region. Received: 16 June 1998 / Accepted: 18 August 1998     

Construction and Application of a Korean Reference Panel for Imputing Classical Alleles and Amino Acids of Human Leukocyte Antigen Genes

Genetic variations of human leukocyte antigen (HLA) genes within the major histocompatibility complex (MHC) locus are strongly associated with disease susceptibility and prognosis for many diseases, including many autoimmune diseases. In this study, we developed a Korean HLA reference panel for imputing classical alleles and amino acid residues of several HLA genes. An HLA reference panel has potential for use in identifying and fine-mapping disease associations with the MHC locus in East Asian populations, including Koreans. A total of 413 unrelated Korean subjects were analyzed for single nucleotide polymorphisms (SNPs) at the MHC locus and six HLA genes, including HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1. The HLA reference panel was constructed by phasing the 5,858 MHC SNPs, 233 classical HLA alleles, and 1,387 amino acid residue markers from 1,025 amino acid positions as binary variables. The imputation accuracy of the HLA reference panel was assessed by measuring concordance rates between imputed and genotyped alleles of the HLA genes from a subset of the study subjects and East Asian HapMap individuals. Average concordance rates were 95.6% and 91.1% at 2-digit and 4-digit allele resolutions, respectively. The imputation accuracy was minimally affected by SNP density of a test dataset for imputation. In conclusion, the Korean HLA reference panel we developed was highly suitable for imputing HLA alleles and amino acids from MHC SNPs in East Asians, including Koreans.     

Conserved haplotype blocks within the sheep MHC and low SNP heterozygosity in the Class IIa subregion

This report describes single-nucleotide polymorphisms (SNPs) in the sheep major histocompatibility complex (MHC) class II and class III regions and provides insights into the internal structure of this important genomic complex. MHC haplotypes were deduced from sheep family trios based on genotypes from 20 novel SNPs representative of the class II region and 10 previously described SNPs spanning the class III region. All 30 SNPs exhibited Hardy-Weinberg proportions in the sheep population studied. Recombination within an extended sire haplotype was observed within the class II region for 4 of 20 sheep chromosomes, thereby supporting the presence of separated IIa and IIb subregions similar to those present in cattle. SNP heterozygosity varied across the class II and III regions. One segment of the class IIa subregion manifested very low heterozygosity for several SNPs spanning approximately 120 Kbp. This feature corresponds to a subregion within the human MHC class II region previously described as a 'SNP desert' because of its paucity of SNPs. Linkage disequilibrium (LD) was reduced at the junction separating the putative class IIb and IIa subregions and also between the class IIa and the class III subregions. The latter observation is consistent with either an unmapped physical separation at this location or more likely a boundary characterized by more frequent recombination between two conserved subregions, each manifesting high within-block LD. These results identify internal blocks of loci in the sheep MHC, within which recombination is relatively rare.     

Power to detect risk alleles using genome-wide tag SNP panels

Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (λ ~ 1.8–2.0). Relative risks as low as λ ~ 1.1–1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%–35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data.     

Single-nucleotide polymorphisms and haplotype LD analysis of the 29-kb IGF2 region on chromosome 11p15.5 in the Korean population

OBJECTIVE: We investigated sequence variations of the 29-kb insulin-like growth factor 2 (IGF2) region in human chromosome region 11p15.5 in the Korean population. This region consists of IGF2, insulin-like growth factor 2 antisense (IGF2AS), and the insulin gene, all important candidate genes for various diseases, including cancer, obesity, diabetes, and coronary disease. While single nucleotide polymorphisms (SNPs) have been identified for this region and used in association studies, ethnic differences in genetic variation at this site have not been addressed. To date, SNPs for the entire 29-kb region in the Korean population have not been reported. METHODS: We surveyed a population of 108 Koreans for SNPs in the 29-kb IGF2 region. RESULTS: We identified 62 SNPs, consisting of 6 SNPs in the promoter region, 17 in the untranslated region, 19 in introns, and 20 in the intergenic region. We also analyzed linkage disequilibrium (LD) patterns and haplotypes using 36 high-frequency (> 5%)SNPs and found a well-defined LD block spanning about 13 kb that includes 8 kb of the IGF2AS gene, with two hot-spot regions flanking the LD block. CONCLUSION: These SNPs may be useful as genetic markers in disease association studies in the Korean population.