Inaho Danjoh

Rare variant discovery by deep whole-genome sequencing of 1,070 Japanese individuals

The Tohoku Medical Megabank Organization reports the whole-genome sequences of 1,070 healthy Japanese individuals and construction of a Japanese population reference panel (1KJPN). Here we identify through this high-coverage sequencing (32.4 × on average), 21.2 million, including 12 million novel, single-nucleotide variants (SNVs) at an estimated false discovery rate of <1.0%. This detailed analysis detected signatures for purifying selection on regulatory elements as well as coding regions. We also catalogue structural variants, including 3.4 million insertions and deletions, and 25,923 genic copy-number variants. The 1KJPN was effective for imputing genotypes of the Japanese population genome wide. These data demonstrate the value of high-coverage sequencing for constructing population-specific variant panels, which covers 99.0% SNVs of minor allele frequency ≥0.1%, and its value for identifying causal rare variants of complex human disease phenotypes in genetic association studies.

Genome-wide association study of clinically defined gout identifies multiple risk loci and its association with clinical subtypes

Objective Gout, caused by hyperuricaemia, is a multifactorial disease. Although genome-wide association studies (GWASs) of gout have been reported, they included self-reported gout cases in which clinical information was insufficient. Therefore, the relationship between genetic variation and clinical subtypes of gout remains unclear. Here, we first performed a GWAS of clinically defined gout cases only. Methods A GWAS was conducted with 945 patients with clinically defined gout and 1213 controls in a Japanese male population, followed by replication study of 1048 clinically defined cases and 1334 controls. Results Five gout susceptibility loci were identified at the genome-wide significance level (p<5.0×10−8), which contained well-known urate transporter genes (ABCG2 and SLC2A9) and additional genes: rs1260326 (p=1.9×10−12; OR=1.36) of GCKR (a gene for glucose and lipid metabolism), rs2188380 (p=1.6×10−23; OR=1.75) of MYL2-CUX2 (genes associated with cholesterol and diabetes mellitus) and rs4073582 (p=6.4×10−9; OR=1.66) of CNIH-2 (a gene for regulation of glutamate signalling). The latter two are identified as novel gout loci. Furthermore, among the identified single-nucleotide polymorphisms (SNPs), we demonstrated that the SNPs of ABCG2 and SLC2A9 were differentially associated with types of gout and clinical parameters underlying specific subtypes (renal underexcretion type and renal overload type). The effect of the risk allele of each SNP on clinical parameters showed significant linear relationships with the ratio of the case–control ORs for two distinct types of gout (r=0.96 [p=4.8×10−4] for urate clearance and r=0.96 [p=5.0×10−4] for urinary urate excretion). Conclusions Our findings provide clues to better understand the pathogenesis of gout and will be useful for development of companion diagnostics.

Japonica array: improved genotype imputation by designing a population-specific SNP array with 1070 Japanese individuals

The Tohoku Medical Megabank Organization constructed the reference panel (referred to as the 1KJPN panel), which contains >20 million single nucleotide polymorphisms (SNPs), from whole-genome sequence data from 1070 Japanese individuals. The 1KJPN panel contains the largest number of haplotypes of Japanese ancestry to date. Here, from the 1KJPN panel, we designed a novel custom-made SNP array, named the Japonica array, which is suitable for whole-genome imputation of Japanese individuals. The array contains 659 253 SNPs, including tag SNPs for imputation, SNPs of Y chromosome and mitochondria, and SNPs related to previously reported genome-wide association studies and pharmacogenomics. The Japonica array provides better imputation performance for Japanese individuals than the existing commercially available SNP arrays with both the 1KJPN panel and the International 1000 genomes project panel. For common SNPs (minor allele frequency (MAF)>5%), the genomic coverage of the Japonica array (r2>0.8) was 96.9%, that is, almost all common SNPs were covered by this array. Nonetheless, the coverage of low-frequency SNPs (0.5%<MAF⩽5%) of the Japonica array reached 67.2%, which is higher than those of the existing arrays. In addition, we confirmed the high quality genotyping performance of the Japonica array using the 288 samples in 1KJPN; the average call rate 99.7% and the average concordance rate 99.7% to the genotypes obtained from high-throughput sequencer. As demonstrated in this study, the creation of custom-made SNP arrays based on a population-specific reference panel is a practical way to facilitate further association studies through genome-wide genotype imputations.

GWAS of clinically defined gout and subtypes identifies multiple susceptibility loci that include urate transporter genes

Objective A genome-wide association study (GWAS) of gout and its subtypes was performed to identify novel gout loci, including those that are subtype-specific. Methods Putative causal association signals from a GWAS of 945 clinically defined gout cases and 1213 controls from Japanese males were replicated with 1396 cases and 1268 controls using a custom chip of 1961 single nucleotide polymorphisms (SNPs). We also first conducted GWASs of gout subtypes. Replication with Caucasian and New Zealand Polynesian samples was done to further validate the loci identified in this study. Results In addition to the five loci we reported previously, further susceptibility loci were identified at a genome-wide significance level (p<5.0×10−8): urate transporter genes (SLC22A12 and SLC17A1) and HIST1H2BF-HIST1H4E for all gout cases, and NIPAL1 and FAM35A for the renal underexcretion gout subtype. While NIPAL1 encodes a magnesium transporter, functional analysis did not detect urate transport via NIPAL1, suggesting an indirect association with urate handling. Localisation analysis in the human kidney revealed expression of NIPAL1 and FAM35A mainly in the distal tubules, which suggests the involvement of the distal nephron in urate handling in humans. Clinically ascertained male patients with gout and controls of Caucasian and Polynesian ancestries were also genotyped, and FAM35A was associated with gout in all cases. A meta-analysis of the three populations revealed FAM35A to be associated with gout at a genome-wide level of significance (pmeta=3.58×10−8). Conclusions Our findings including novel gout risk loci provide further understanding of the molecular pathogenesis of gout and lead to a novel concept for the therapeutic target of gout/hyperuricaemia.

Validation of multiple single nucleotide variation calls by additional exome analysis with a semiconductor sequencer to supplement data of whole-genome sequencing of a human population

BackgroundValidation of single nucleotide variations in whole-genome sequencing is critical for studying disease-related variations in large populations. A combination of different types of next-generation sequencers for analyzing individual genomes may be an efficient means of validating multiple single nucleotide variations calls simultaneously.ResultsHere, we analyzed 12 independent Japanese genomes using two next-generation sequencing platforms: the Illumina HiSeq 2500 platform for whole-genome sequencing (average depth 32.4×), and the Ion Proton semiconductor sequencer for whole exome sequencing (average depth 109×). Single nucleotide polymorphism (SNP) calls based on the Illumina Human Omni 2.5-8 SNP chip data were used as the reference. We compared the variant calls for the 12 samples, and found that the concordance between the two next-generation sequencing platforms varied between 83% and 97%.ConclusionsOur results show the versatility and usefulness of the combination of exome sequencing with whole-genome sequencing in studies of human population genetics and demonstrate that combining data from multiple sequencing platforms is an efficient approach to validate and supplement SNP calls.

The Sonoda-Tajima Cell Collection, a human genetics research resource with emphasis on South American indigenous populations

The Sonoda–Tajima Cell Collection includes cell samples obtained from a range of ethnic minority groups across the world but in particular from South America. The collection is made all the more valuable by the fact that some of these ethnic populations have since died out, and thus it will be impossible to prepare a similar cell collection again. The collection was donated to our institute, a public cell bank in Japan, by Drs Sonoda and Tajima to make it available to researchers throughout the world. The original cell collection was composed of cryopreserved peripheral blood samples that would obviously have been rapidly exhausted if used directly. We, therefore, immortalized some samples with the Epstein–Barr virus and established B-lymphoblastoid cell lines (B-LCLs). As there is continuing controversy over whether the B-LCL genome is stably maintained, we performed an array comparative genomic hybridization (CGH) analysis to confirm the genomic stability of the cell lines. The array CGH analysis of the B-LCL lines and their parental B cells demonstrated that genomic stability was maintained in the long-term cell cultures. The B-LCLs of the Sonoda–Tajima Collection will therefore be made available to interested scientists around the world. At present, 512 B-LCLs have been developed, and we are willing to increase the number if there is sufficient demand.

Evaluation of reported pathogenic variants and their frequencies in a Japanese population based on a whole-genome reference panel of 2049 individuals

Clarifying allele frequencies of disease-related genetic variants in a population is important in genomic medicine; however, such data is not yet available for the Japanese population. To estimate frequencies of actionable pathogenic variants in the Japanese population, we examined the reported pathological variants in genes recommended by the American College of Medical Genetics and Genomics (ACMG) in our reference panel of genomic variations, 2KJPN, which was created by whole-genome sequencing of 2049 individuals of the resident cohort of the Tohoku Medical Megabank Project. We searched for pathogenic variants in 2KJPN for 57 autosomal ACMG-recommended genes responsible for 26 diseases and then examined their frequencies. By referring to public databases of pathogenic variations, we identified 143 reported pathogenic variants in 2KJPN for the 57 ACMG recommended genes based on a classification system. At the individual level, 21% of the individuals were found to have at least one reported pathogenic allele. We then conducted a literature survey to review the variants and to check for evidence of pathogenicity. Our results suggest that a substantial number of people have reported pathogenic alleles for the ACMG genes, and reviewing variants is indispensable for constructing the information infrastructure of genomic medicine for the Japanese population.

The structural origin of metabolic quantitative diversity

Relationship between structural variants of enzymes and metabolic phenotypes in human population was investigated based on the association study of metabolite quantitative traits with whole genome sequence data for 512 individuals from a population cohort. We identified five significant associations between metabolites and non-synonymous variants. Four of these non-synonymous variants are located in enzymes involved in metabolic disorders, and structural analyses of these moderate non-synonymous variants demonstrate that they are located in peripheral regions of the catalytic sites or related regulatory domains. In contrast, two individuals with larger changes of metabolite levels were also identified, and these individuals retained rare variants, which caused non-synonymous variants located near the catalytic site. These results are the first demonstrations that variant frequency, structural location, and effect for phenotype correlate with each other in human population, and imply that metabolic individuality and susceptibility for diseases may be elicited from the moderate variants and much more deleterious but rare variants.

Monitoring of minimal residual disease in early T-cell precursor acute lymphoblastic leukaemia by next-generation sequencing.

Early T-cell precursor acute lymphoblastic leukaemia (ETPALL) is a recently identified stem-progenitor-originated malignancy with a high risk of treatment failure (Coustan-Smith et al, 2009). Diversified genetic alterations have been observed at the onset of ETP-ALL, whereas common disease-specific mutations have not been defined. Mutations with myeloid features such as FLT3 and NRAS are more often found in ETPALL than in other T-ALLs, whereas prototypical T-ALL lesions, such as CDKN2A/B deletions and NOTCH1 mutations, are less frequent (Haydu & Ferrando, 2013). Thus, identification of clonal and sub-clonal mutations in each case and subsequent monitoring of minimal residual disease (MRD) by utilizing Next-Generation Sequencing (NGS) are expected to improve the diagnosis and survival of ETP-ALL patients. Monitoring of MRD, crucial for planning therapeutic strategy and preventing relapse of leukaemia, focuses on particular regions of the genome in which leukaemia-specific gene mutations are localized, and prior identification of disease-related mutations is necessary for this. Therefore, NGS is a powerful means for MRD detection.

Omics research project on prospective cohort studies from the Tohoku Medical Megabank Project.

Population‐based prospective cohort studies are indispensable for modern medical research as they provide important knowledge on the influences of many kinds of genetic and environmental factors on the cause of disease. Although traditional cohort studies are mainly conducted using questionnaires and physical examinations, modern cohort studies incorporate omics and genomic approaches to obtain comprehensive physical information, including genetic information. Here, we report the design and midterm results of multi‐omics analysis on population‐based prospective cohort studies from the Tohoku Medical Megabank (TMM) Project. We have incorporated genomic and metabolomic studies in the TMM cohort study as both metabolome and genome analyses are suitable for high‐throughput analysis of large‐scale cohort samples. Moreover, an association study between the metabolome and genome show that metabolites are an important intermediate phenotype connecting genetic and lifestyle factors to physical and pathologic phenotypes. We apply our metabolome and genome analyses to large‐scale cohort samples in the following studies.