Explore the types of human genomic variation and the diseases known to be caused by structural variants.
Explore how long-read sequencing enables solving of rare and mendelian diseases.
Access full spectrum of polymorphisms in HLA class I & II genes, without imputation for disease association and evolutionary research.
MHC class I and II genes are critically monitored by high-resolution sequencing for organ transplant decisions due to their role in GVHD. Their direct or linkage-based causal association, have increased their prominence as targets for drug sensitivity, autoimmune, cancer and infectious disease research. Monitoring HLA genes can however be tricky due to their highly polymorphic nature. Allele-level resolution is thus strongly preferred. However, most studies were historically focused on peptide binding domains of the HLA genes, due to technological challenges. As a result knowledge about the functional role of polymorphisms outside of exons 2 and 3 of HLA genes was rather limited. There are also relatively few full-length gene references currently available in the IMGT HLA database. This made it difficult to quickly adopt high-throughput reference-reliant methods for allele-level HLA sequencing. Increasing awareness regarding role of regulatory region polymorphisms of HLA genes in disease association1, nonetheless have brought about a revolution in full-length HLA gene sequencing. Researchers are now exploring ways to obtain complete information for HLA genes and integrate it with the current HLA database so it can be interpreted used by clinical researchers. We have explored advantages of SMRT Sequencing to obtain fully phased, allele-specific sequences of HLA class I and II genes for 96 samples using completely De novo consensus generation approach for imputation-free 4-field typing. With long read lengths (average >10 kb) and consensus accuracy exceeding 99.999% (Q50), a comprehensive snapshot of variants in exons, introns and UTRs could be obtained for spectrum of polymorphisms in phase across SNP-poor regions. Such information can provide invaluable insights in future causality association and population diversity research.
Human MHC class I genes HLA-A, -B, -C, and class II genes HLA -DR, -DQ, and -DP play a critical role in the immune system as primary factors responsible for…
The discovery of mutations associated with human genetic dis- ease is an exercise in comparative genomics (see Glossary). Although there are many different strategies and approaches, the central premise is that affected persons harbor a significant excess of pathogenic DNA variants as com- pared with a group of unaffected persons (controls) that is either clinically defined1 or established by surveying large swaths of the general population.2 The more exclu- sive the variant is to the disease, the greater its penetrance, the larger its effect size, and the more relevant it becomes to both disease diagnosis and future therapeutic investigation. The most popular approach used by researchers in human genetics is the case–control design, but there are others that can be used to track variants and disease in a family context or that consider the probability of different classes of mutations based on evolutionary patterns of divergence or de novo mutational change.3,4 Although the approaches may be straightforward, the discovery of patho- genic variation and its mechanism of action often is less trivial, and decades of research can be required in order to identify the variants underlying both mendelian and complex genetic traits.
The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50?bp) and 27,622 SVs (=50?bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.
Long expansions of short tandem repeats (STRs), i.e. DNA repeats of 2-6 nt, are associated with some genetic diseases. Cost-efficient high-throughput sequencing can quickly produce billions of short reads that would be useful for uncovering disease-associated STRs. However, enumerating STRs in short reads remains largely unexplored because of the difficulty in elucidating STRs much longer than 100 bp, the typical length of short reads.We propose ab initio procedures for sensing and locating long STRs promptly by using the frequency distribution of all STRs and paired-end read information. We validated the reproducibility of this method using biological replicates and used it to locate an STR associated with a brain disease (SCA31). Subsequently, we sequenced this STR site in 11 SCA31 samples using SMRT(TM) sequencing (Pacific Biosciences), determined 2.3-3.1 kb sequences at nucleotide resolution and revealed that (TGGAA)- and (TAAAATAGAA)-repeat expansions determined the instability of the repeat expansions associated with SCA31. Our method could also identify common STRs, (AAAG)- and (AAAAG)-repeat expansions, which are remarkably expanded at four positions in an SCA31 sample. This is the first proposed method for rapidly finding disease-associated long STRs in personal genomes using hybrid sequencing of short and long reads.Our TRhist software is available at http://firstname.lastname@example.orgSupplementary data are available at Bioinformatics online.
In the past decade, the development of next-generation sequencing (NGS) has paved the way for whole-genome analysis in individuals. Research on the human leukocyte antigen (HLA), an extensively studied molecule involved in immunity, has benefitted from NGS technologies. The HLA region, a 3.6-Mb segment of the human genome at 6p21, has been associated with more than 100 different diseases, primarily autoimmune diseases. Recently, the HLA region has received much attention because severe adverse effects of various drugs are associated with particular HLA alleles. Owing to the complex nature of the HLA genes, classical direct sequencing methods cannot comprehensively elucidate the genomic makeup of HLA genes. Thus far, several high-throughput HLA-typing methods using NGS have been developed. In HLA research, NGS facilitates complete HLA sequencing and is expected to improve our understanding of the mechanisms through which HLA genes are modulated, including transcription, regulation of gene expression and epigenetics. Most importantly, NGS may also permit the analysis of HLA-omics. In this review, we summarize the impact of NGS on HLA research, with a focus on the potential for clinical applications.
TCR sequencing of single cells reactive to DQ2.5-glia-a2 and DQ2.5-glia-?2 reveals clonal expansion and epitope-specific V-gene usage.
CD4+ T cells recognizing dietary gluten epitopes in the context of disease-associated human leukocyte antigen (HLA)-DQ2 or HLA-DQ8 molecules are the key players in celiac disease pathogenesis. Here, we conducted a large-scale single-cell paired T-cell receptor (TCR) sequencing study to characterize the TCR repertoire for two homologous immunodominant gluten epitopes, DQ2.5-glia-a2 and DQ2.5-glia-?2, in blood of celiac disease patients after oral gluten challenge. Despite sequence similarity of the epitopes, the TCR repertoires are unique but shared several overall features. We demonstrate that clonally expanded T cells dominate the T-cell responses to both epitopes. Moreover, we find V-gene bias of TRAV26, TRAV4, and TRBV7 in DQ2.5-glia-a2 reactive TCRs, while DQ2.5-glia-?2 TCRs displayed significant bias toward TRAV4 and TRBV4. The knowledge that antigen-specific TCR repertoire in chronic inflammatory diseases tends to be dominated by a few expanded clones that use the same TCR V-gene segments across patients is important information for HLA-associated diseases where the antigen is unknown.