Genetic and phenotypic landscape of the major histocompatibilty complex region in the Japanese population

Hirata, Jun; Hosomichi, Kazuyoshi; Sakaue, Saori; Kanai, Masahiro; Nakaoka, Hirofumi; Ishigaki, Kazuyoshi; Suzuki, Ken; Akiyama, Masato; Kishikawa, Toshihiro; Ogawa, Kotaro; Masuda, Tatsuo; Yamamoto, Kenichi; Hirata, Makoto; Matsuda, Koichi; Momozawa, Yukihide; Inoue, Ituro; Kubo, Michiaki; Kamatani, Yoichiro; Okada, Yukinori

doi:10.1038/s41588-018-0336-0

Cited by 89 publications

(110 citation statements)

References 56 publications

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“…We first screened potential epitopes that are likely to be presented on certain HLA class I molecules, HLA-A, B, and C molecules, which are commonly observed (frequencies of more than 5%) in the Japanese population [9], using netMHC4.0 and netMHCpan4.0 algorithm [11,12]. We selected the top 0.5%-ranked (high affinity) peptides derived from the SARS-CoV-2 protein sequences and obtained a total of 2013 unique predicted epitopes ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…The predicted epitopes were significantly enriched in the M protein (P = 0.00062, odds ratio = 1.64), whereas less enriched in the N protein (P = 0.0074, odds ratio = 0.69). We then performed a screening of HLA-class II-candidate peptide epitopes that show the high affinity to HLA-DPA1, DPB1, DQA1, DQB1, and DRB1, which are common (frequencies of more than 5%) in the Japanese populations [9,10], using netMHCIIpan3.1 algorithm [13]. We found a total of 1399 possible HLA-class II epitopes after selecting top 2%ranked peptides ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Epitope prediction was carried out using the predicted proteins, including S, E, N, M, and ORFs (corresponding to accession numbers QHD43415-QHD43423, QHI42199) of the reference SARS-CoV-2_Wuhan-Hu-1 (accession number MN908947). To predict HLA-class I epitopes, we selected 7, 10, 8 of human leukocyte antigen-A (HLA-A), HLA-B, HLA-C alleles, respectively, which were reported to be present in more than 5% frequencies in the Japanese population ( Supplementary Table 1) [9]. For HLA-class II epitope prediction, we selected 5 and 6 haplotypes of HLA-DPA1-DPB1 and HLA-DQA1-DQB1, respectively, and 7 alleles of HLA-DRB1 that are frequently observed in the Japanese populations ( Supplementary Table 1) [9,10].…”

Section: T Cell Epitope Prediction For Sars-cov-2mentioning

confidence: 99%

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Bioinformatic prediction of potential T cell epitopes for SARS-Cov-2

et al. 2020

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To control and prevent the current COVID-19 pandemic, the development of novel vaccines is an emergent issue. In addition, we need to develop tools that can measure/monitor T-cell and B-cell responses to know how our immune system is responding to this deleterious virus. However, little information is currently available about the immune target epitopes of novel coronavirus (SARS-CoV-2) to induce host immune responses. Through a comprehensive bioinformatic screening of potential epitopes derived from the SARS-CoV-2 sequences for HLAs commonly present in the Japanese population, we identified 2013 and 1399 possible peptide epitopes that are likely to have the high affinity (<0.5%-and 2%-rank, respectively) to HLA class I and II molecules, respectively, that may induce CD8 + and CD4 + T-cell responses. These epitopes distributed across the structural (spike, envelope, membrane, and nucleocapsid proteins) and the nonstructural proteins (proteins corresponding to six open reading frames); however, we found several regions where high-affinity epitopes were significantly enriched. By comparing the sequences of these predicted T cell epitopes to the other coronaviruses, we identified 781 HLA-class I and 418 HLA-class II epitopes that have high homologies to SARS-CoV. To further select commonly-available epitopes that would be applicable to larger populations, we calculated population coverages based on the allele frequencies of HLA molecules, and found 2 HLA-class I epitopes covering 83.8% of the Japanese population. The findings in the current study provide us valuable information to design widely-available vaccine epitopes against SARS-CoV-2 and also provide the useful information for monitoring T-cell responses.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: T Cell Epitope Prediction For Sars-cov-2mentioning

confidence: 99%

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Bioinformatic prediction of potential T cell epitopes for SARS-Cov-2

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“…Institute of Medical Science, the University of Tokyo. The details of the characteristics of individuals were described in elsewhere 30,39,40 . This study was approved by the ethical committee of Osaka University Graduate School of Medicine.…”

Section: Methodsmentioning

confidence: 99%

Genetic and phenotypic landscape of the mitochondrial genome in the Japanese population

et al. 2020

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The genetic landscape of mitochondrial DNA (mtDNA) has been elusive. By analyzing mtDNA using the whole genome sequence (WGS) of Japanese individuals (n = 1928), we identified 2023 mtDNA variants and high-resolution haplogroups. Frequency spectra of the haplogroups were population-specific and were heterogeneous among geographic regions within Japan. Application of machine learning methods could finely classify the subjects corresponding to the high-digit mtDNA sub-haplogroups. mtDNA had distinct genetic structures from that of nuclear DNA (nDNA), characterized by no distance-dependent linkage disequilibrium decay, sparse tagging of common variants, and the existence of common haplotypes spanning the entire mtDNA. We did not detect any evidence of mtDNA-nDNA (or mtDNA copy number-nDNA) genotype associations. Together with WGS-based mtDNA variant imputation, we conducted a phenome-wide association study of 147,437 Japanese individuals with 99 clinical phenotypes. We observed pleiotropy of mtDNA genetic risk on the five late-onset human complex traits including creatine kinase (P = 1.7 × 10 −12).

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“…This linear transformation, however, was not sufficient to fully capture the fine and subtle genomic structure. Additional non-linear dimensionality reduction methods, t-distributed stochastic neighbor embedding (t-SNE) and its combination with PCA (PCA-t-SNE), were applied, and exhibited the ability to provide interpretations of complex population structures and disease biology [9][10][11] . Recently, uniform manifold approximation and projection (UMAP) was developed as a novel non-linear dimensionality reduction method capable of clearly distinguishing neighboring clusters while retaining the global structure.…”

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confidence: 99%

Dimensionality reduction reveals fine-scale structure in the Japanese population with consequences for polygenic risk prediction

et al. 2020

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The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on complex traits. Here we apply dimensionality reduction methods (PCA, t-SNE, PCA-t-SNE, UMAP, and PCA-UMAP) to biobank-derived genomic data of a Japanese population (n = 169,719). Dimensionality reduction reveals fine-scale population structure, conspicuously differentiating adjacent insular subpopulations. We further enluciate the demographic landscape of these Japanese subpopulations using population genetics analyses. Finally, we perform phenome-wide polygenic risk score (PRS) analyses on 67 complex traits. Differences in PRS between the deconvoluted subpopulations are not always concordant with those in the observed phenotypes, suggesting that the PRS differences might reflect biases from the uncorrected structure, in a trait-dependent manner. This study suggests that such an uncorrected structure can be a potential pitfall in the clinical application of PRS.

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Genetic and phenotypic landscape of the major histocompatibilty complex region in the Japanese population

Cited by 89 publications

References 56 publications

Bioinformatic prediction of potential T cell epitopes for SARS-Cov-2

Bioinformatic prediction of potential T cell epitopes for SARS-Cov-2

Genetic and phenotypic landscape of the mitochondrial genome in the Japanese population

Dimensionality reduction reveals fine-scale structure in the Japanese population with consequences for polygenic risk prediction

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