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

The Impact of Patterns in Linkage Disequilibrium and Sequencing Quality on the Imprint of Balancing Selection

Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima's D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions.

The importance of establishing genetic phase in clinical medicine

Haplotyping or determination of genetic phase has always played a pivotal role in MHC (HLA studies) both in helping to understand inheritance patterns in diseases such as type 1 diabetes (T1D) and in ensuring better matching in transplantation scenarios such as haematopoietic stem cell transplantation (HSCT), using donors genetically related to the patient. In recent years the need to establish genetic phase in a number of clinical scenarios has become apparent. These include: Genetic phasing for hematopoietic stem cell transplants using unrelated donors, where the HLA haplotypes are not known but where haplotype-matched recipients fare better clinically than allele matched, but haplotype mismatched patients. The use of checkpoint inhibitors is one of the most innovative and exciting developments in cancer treatment in years. An example is the use of the monoclonal ipilimumab to block the CTLA-4 receptor which is known to contain polymorphic sites. Until the phase of these polymorphisms is known it will not be possible to determine how effectively this monoclonal will perform in individual patients. The role of miRNA single strand molecules and their effect on gene expression. Thousands of non-coding genes have been identified and have been shown to be polymorphic, as have their target genes. Genetic phasing of polymorphism both in the miRNA source genes and their targets is clearly a fertile area of research In areas such a drug metabolism where the polymorphic family of CYP genes is responsible for the metabolism of the majority of prescription drugs, determining phase of SNPs is critical to understanding drug metabolism and efficacy. In multigenic disease studies combinations of single nucleotide polymorphisms (SNPs) in participating genes require accurate phasing in order to fully appreciate their role in the disease process. In addition, the level of expression of genes (point 3) is also important in understanding disease processes at the functional level. This review outlines the techniques that are currently available for approximating phase and discusses the clinical relevance of establishing genetic phase in areas of clinical medicine outlined in points 1-3.

Regulatory noncoding RNAs and the major histocompatibility complex

The Major Histocompatibility Complex (MHC) is a 4 Mbp genomic region located on the short arm of chromosome 6. The MHC region contains many key immune-related genes such as Human Leukocyte Antigens (HLAs). There has been a growing realization that, apart from MHC encoded proteins, RNAs derived from noncoding regions of the MHC-specifically microRNAs (miRNAs) and long noncoding RNAs (lncRNAs)-play a significant role in cellular regulation. Furthermore, regulatory noncoding RNAs (ncRNAs) derived from other parts of the genome fine-tune the expression of many immune-related MHC proteins. Although the field of ncRNAs of the MHC is a research area that is still in its infancy, ncRNA regulation of MHC genes has already been shown to be vital for immune function, healthy pregnancy and cellular homeostasis. Dysregulation of this intricate network of ncRNAs can lead to serious perturbations in homeostasis and subsequent disease.

Clinical utility of next generation sequencing based HLA typing for disease association and pharmacogenetic testing

HLA associations have been linked to many diseases and are important for risk assessment of drug hypersensitivity reactions. The increasing number of HLA alleles discovered generated a list of ambiguities that cannot be resolved with the current clinical assays, which commonly include sequence-specific oligonucleotide probe (SSOP) genotyping, and real-time PCR with melting curve analysis. HLA typing by next-generation sequencing (NGS) has recently been adopted by clinical laboratories for transplantation testing, as it provides unambiguous and cost-effective HLA typing. The goal of this study was to evaluate the feasibility of using NGS-based HLA-B and DQ genotyping for clinical HLA disease association testing, and provide direct comparison with the currently used clinical tests, including SSOP genotyping, and real-time PCR with melting curve analysis. While the real-time PCR method is easy and inexpensive to perform, ambiguities are rapidly increasing as more and more HLA alleles are discovered. SSOP genotyping identifies the alleles present but limitations include ambiguities and underreporting less common alleles. Our data show that HLA typing by NGS is superior to the existing clinical methods for identifying HLA alleles associated with disease or drug hypersensitivity, and offers a viable approach for high volume clinical diagnostic laboratories.

Novel and Haplotype Specific MicroRNAs Encoded by the Major Histocompatibility Complex

The MHC is recognized for its importance in human health and disease. However, many disease-associated variants throughout the region remain of unknown significance, residing predominantly within non-coding regions of the MHC. The characterization of non-coding RNA transcripts throughout the MHC is thus central to understanding the genetic contribution of these variants. Therefore, we characterize novel miRNA transcripts throughout the MHC by performing deep RNA sequencing of two B lymphoblastoid cell lines with completely characterized MHC haplotypes. Our analysis identifies 89 novel miRNA transcripts, 48 of which undergo Dicer-dependent biogenesis and are loaded onto the Argonaute silencing complex. Several of the identified mature miRNA and pre-miRNA transcripts are unique to specific MHC haplotypes and overlap common SNPs. Furthermore, 43 of the 89 identified novel miRNA transcripts lie within linkage disequilibrium blocks that contain a disease-associated SNP. These disease associated SNPs are associated with 65 unique disease phenotypes, suggesting that these transcripts may play a role in the etiology of numerous diseases associated with the MHC. Additional in silico analysis reveals the potential for thousands of putative pre-miRNA encoding loci within the MHC that may be expressed by different cell types and at different developmental stages.

An Expanded Role for HLA Genes: HLA-B Encodes a microRNA that Regulates IgA and Other Immune Response Transcripts

We describe a novel functional role for the HLA-B locus mediated by its intron-encoded microRNA (miRNA), miR-6891-5p. We show that in vitro inhibition of miR-6891-5p impacts the expression of nearly 200 transcripts within the B-lymphoblastoid cell line (B-LCL) COX, affecting a large number of metabolic pathways, including various immune response networks. The top affected transcripts following miR-6891-5p inhibition are those encoding the heavy chain of IgA. We identified a conserved miR-6891-5p target site on the 3′UTR of both immunoglobulin heavy chain alpha 1 and 2 (IGHA1 and IGHA2) transcripts and demonstrated that this miRNA modulates the expression of IGHA1 and IGHA2. B-LCLs from IgA-deficient patients expressed significantly elevated levels of miR-6891-5p when compared with unaffected family members. Upon inhibition of miR-6891-5p, IgA mRNA expression levels were increased, and IgA secretion was restored in the B-LCL of an IgA-deficient patient. These findings indicate that miR-6891-5p regulates IGHA1 and IGHA2 gene expression at the posttranscriptional level and suggest that increase in miR-6891-5p levels may contribute to the etiology of selective IgA deficiency.

Targeted Next-Generation Sequencing for Human Leukocyte Antigen Typing in a Clinical Laboratory: Metrics of Relevance and Considerations for Its Successful Implementation

CONTEXT

- Numerous feasibility studies to type human leukocyte antigens (HLAs) by next-generation sequencing (NGS) have led to the development of vendor-supported kits for HLA typing by NGS. Some clinical laboratories have introduced HLA-NGS, and many are investigating the introduction. Standards from accrediting agencies form the regulatory framework for introducing this test into clinical laboratories.

OBJECTIVES

- To provide an assessment of metrics and considerations relevant to the successful implementation of clinical HLA-NGS typing, and to provide as a reference a validated HLA-NGS protocol used clinically since December 2013 at the Children's Hospital of Philadelphia (Philadelphia, Pennsylvania).

DATA SOURCES

- The HLA-NGS has been performed on 2532 samples. The initial 1046 and all homozygous samples were also typed by an alternate method. The HLA-NGS demonstrated 99.7% concordance with the alternate method. Ambiguous results were most common at the DPB1 locus because of a lack of phasing between exons 2 and 3 or the unsequenced exon 1 (533 of 2954 alleles; 18.04%) and the DRB1 locus because of not sequencing exon 1 (75 of 3972 alleles; 1.89%). No ambiguities were detected among the other loci. Except for 2 false homozygous samples, all homozygous samples (1891) demonstrated concordance with the alternate method. The article is organized to address the critical elements in the preanalytic, analytic, and postanalytic phases of introducing this assay into the clinical laboratory.

CONCLUSIONS

- The results demonstrate that HLA typing by NGS is a highly accurate, reproducible, efficient method that provides more-complete sequencing information for the length of the HLA gene and can be the single methodology for HLA typing in clinical immunogenetics laboratories.

Evaluation of shared genetic susceptibility loci between autoimmune diseases and schizophrenia based on genome-wide association studies

BACKGROUND

Epidemiological studies have documented higher than expected comorbidity (or, in some cases, inverse comorbidity) between schizophrenia and several autoimmune disorders. It remains unknown whether this comorbidity reflects shared genetic susceptibility loci.

AIMS

The present study aimed to investigate whether verified genome wide significant variants of autoimmune disorders confer risk of schizophrenia, which could suggest a common genetic basis.

METHODS

Seven hundred and fourteen genome wide significant risk variants of 25 autoimmune disorders were extracted from the NHGRI GWAS catalogue and examined for association to schizophrenia in the Psychiatric Genomics Consortium schizophrenia GWAS samples (36,989 cases and 113,075 controls).

RESULTS

Two independent loci at 4q24 and 6p21.32-33 originally identified from GWAS of autoimmune diseases were found genome wide associated with schizophrenia (1.7 × 10^-8≥p ≥ 4.0 × 10^-21). While these observations confirm the existence of shared genetic susceptibility loci between schizophrenia and autoimmune diseases, the findings did not show a significant enrichment.

CONCLUSION

The findings do not support a genetic overlap in common SNPs between autoimmune diseases and schizophrenia that in part could explain the observed comorbidity from epidemiological studies.

Generation of Full-Length Class I Human Leukocyte Antigen Gene Consensus Sequences for Novel Allele Characterization

BACKGROUND

Routine, high-resolution human leukocyte antigen (HLA) genotyping by next generation sequencing within clinical immunogenetics laboratories can now provide the full-length gene sequence characterization of fully phased HLA alleles. This powerful technique provides insights into HLA variation beyond the traditionally characterized antigen recognition domain, providing sequence annotation across the entire gene including untranslated and intronic regions and may be used to characterize novel alleles from massively parallel sequencing runs.

METHODS

We evaluated the utility of the Omixon Holotype HLA assay to generate credible, fully phased full-length gene consensus sequences for 50 individuals at major histocompatibility complex, class I, A (HLA-A), HLA-B, and HLA-C loci (300 genotyped alleles in total) to identify and characterize novel class I HLA alleles using our downstream analytical pipeline.

RESULTS

Our analysis revealed that 7.7% (23/300) of genotyped class I HLA alleles contain novel polymorphisms. Interestingly, all of the novel alleles identified by our analysis were found to harbor sequence variations within intronic regions of the respective locus. In total our analysis identified 17 unique novel class I HLA alleles from 23 of the 300 genotyped alleles and generated full-length gene sequence annotations for 9 previously incompletely annotated HLA class I allele sequences derived from 14 of the 300 genotyped alleles.

CONCLUSIONS

The demonstrated utility of the Omixon Holotype HLA assay in combination with our downstream analytical framework to generate fully phased, full-length gene consensus sequences for the identification and characterization of novel HLA alleles, facilitates the study of HLA polymorphism beyond the antigen recognition domain in human health and disease.

The next generation of target capture technologies - large DNA fragment enrichment and sequencing determines regional genomic variation of high complexity

BACKGROUND

The ability to capture and sequence large contiguous DNA fragments represents a significant advancement towards the comprehensive characterization of complex genomic regions. While emerging sequencing platforms are capable of producing several kilobases-long reads, the fragment sizes generated by current DNA target enrichment technologies remain a limiting factor, producing DNA fragments generally shorter than 1 kbp. The DNA enrichment methodology described herein, Region-Specific Extraction (RSE), produces DNA segments in excess of 20 kbp in length. Coupling this enrichment method to appropriate sequencing platforms will significantly enhance the ability to generate complete and accurate sequence characterization of any genomic region without the need for reference-based assembly.

RESULTS

RSE is a long-range DNA target capture methodology that relies on the specific hybridization of short (20-25 base) oligonucleotide primers to selected sequence motifs within the DNA target region. These capture primers are then enzymatically extended on the 3'-end, incorporating biotinylated nucleotides into the DNA. Streptavidin-coated beads are subsequently used to pull-down the original, long DNA template molecules via the newly synthesized, biotinylated DNA that is bound to them. We demonstrate the accuracy, simplicity and utility of the RSE method by capturing and sequencing a 4 Mbp stretch of the major histocompatibility complex (MHC). Our results show an average depth of coverage of 164X for the entire MHC. This depth of coverage contributes significantly to a 99.94 % total coverage of the targeted region and to an accuracy that is over 99.99 %.

CONCLUSIONS

RSE represents a cost-effective target enrichment method capable of producing sequencing templates in excess of 20 kbp in length. The utility of our method has been proven to generate superior coverage across the MHC as compared to other commercially available methodologies, with the added advantage of producing longer sequencing templates amenable to DNA sequencing on recently developed platforms. Although our demonstration of the method does not utilize these DNA sequencing platforms directly, our results indicate that the capture of long DNA fragments produce superior coverage of the targeted region.

Predicting regulatory variants with composite statistic

MOTIVATION

Prediction and prioritization of human non-coding regulatory variants is critical for understanding the regulatory mechanisms of disease pathogenesis and promoting personalized medicine. Existing tools utilize functional genomics data and evolutionary information to evaluate the pathogenicity or regulatory functions of non-coding variants. However, different algorithms lead to inconsistent and even conflicting predictions. Combining multiple methods may increase accuracy in regulatory variant prediction.

RESULTS

Here, we compiled an integrative resource for predictions from eight different tools on functional annotation of non-coding variants. We further developed a composite strategy to integrate multiple predictions and computed the composite likelihood of a given variant being regulatory variant. Benchmarked by multiple independent causal variants datasets, we demonstrated that our composite model significantly improves the prediction performance.

AVAILABILITY AND IMPLEMENTATION

We implemented our model and scoring procedure as a tool, named PRVCS, which is freely available to academic and non-profit usage at http://jjwanglab.org/PRVCS CONTACT: wang.junwen@mayo.edu, jliu@stat.harvard.edu, or limx54@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.