Long-read sequencing technology enable better characterization of structural variants (SVs). To adapt the technology to population-scale analyses, one critical issue is to obtain sufficient amount of high-molecular-weight genomic DNA. Here, we propose utilizing activated T lymphocytes, which can be established efficiently in a biobank to stably supply high-grade genomic DNA sufficiently. We conducted nanopore sequencing of 333 individuals constituting 111 trios with high-coverage long-read sequencing data (depth 22.2x, N50 of 25.8 kb) and identified 74,201 SVs. Our trio-based analysis revealed that more than 95% of the SVs were concordant with Mendelian inheritance. We also identified SVs associated with clinical phenotypes, all of which appear to be stably transmitted from parents to offspring. Our data provide a catalog of SVs in the general Japanese population, and the applied approach using the activated T-lymphocyte resource will contribute to biobank-based human genetic studies focusing on SVs at the population scale.

Introduction: Pharmacogenomic (PGx) testing results provide valuable information on drug selection and appropriate dosing, maximization of efficacy, and minimization of adverse effects. Although the number of large-scale, next-generation-sequencing-based PGx studies has recently increased, little is known about the risks and benefits of returning PGx results to ostensibly healthy individuals in research settings. Methods: Single-nucleotide variants of three actionable PGx genes, namely, MT-RNR1, CYP2C19, and NUDT15, were returned to 161 participants in a population-based Tohoku Medical Megabank project. Informed consent was obtained from the participants after a seminar on the outline of this study. The results were sent by mail alongside sealed information letter intended for clinicians. As an exception, genetic counseling was performed for the MT-RNR1 m.1555A > G variant carriers by a medical geneticist, and consultation with an otolaryngologist was encouraged. Questionnaire surveys (QSs) were conducted five times to evaluate the participants' understanding of the topic, psychological impact, and attitude toward the study. Results: Whereas the majority of participants were unfamiliar with the term PGx, and none had undergone PGx testing before the study, more than 80% of the participants felt that they could acquire basic PGx knowledge sufficient to understand their genomic results and were satisfied with their potential benefit and use in future prescriptions. On the other hand, some felt that the PGx concepts or terminology was difficult to fully understand and suggested that in-person return of the results was desirable. Conclusions: These results collectively suggest possible benefits of returning preemptive PGx information to ostensibly healthy cohort participants in a research setting.

Dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene, is the rate-limiting enzyme in 5-fluorouracil (5-FU) degradation. In Caucasians, four DPYD risk variants are recognized to be responsible for interindividual variations in the development of 5-FU toxicity. However, these risk variants have not been identified in Asian populations. Recently, 41 DPYD allelic variants, including 15 novel single nucleotide variants, were identified in 3,554 Japanese individuals by analyzing their whole-genome sequences; however, the effects of these variants on DPD enzymatic activity remain unknown. In the present study, an in vitro analysis was performed on 41 DPD allelic variants and three DPD risk variants to elucidate the changes in enzymatic activity. Wild-type and 44 DPD-variant proteins were heterologously expressed in 293FT cells. DPD expression levels and dimerization of DPD were determined by immunoblotting after SDS-PAGE and blue native PAGE, respectively. The enzymatic activity of DPD was evaluated by quantification of dihydro-5-FU, a metabolite of 5-FU, using high-performance liquid chromatography-tandem mass spectrometry. Moreover, we used 3D simulation modeling to analyze the effect of amino acid substitutions on the conformation of DPD. Among the 41 DPD variants, seven exhibited drastically decreased intrinsic clearance (CL int ) compared to the wild-type protein. Moreover, R353C and G926V exhibited no enzymatic activity, and the band patterns observed in the immunoblots after blue native PAGE indicated that DPD dimerization is required for its enzymatic activity. Our data suggest that these variants may contribute to the significant inter-individual variability observed in the pharmacokinetics and pharmacodynamics of 5-FU. In our study, nine DPD variants exhibited drastically decreased or no enzymatic activity due to dimerization inhibition or conformational changes in each domain. Especially, the rare DPYD variants, although at very low frequencies, may serve as important pharmacogenomic markers associated with the severe 5-FU toxicity in Japanese population.

To reveal gene-environment interactions underlying common diseases and estimate the risk for common diseases, the Tohoku Medical Megabank (TMM) project has conducted prospective cohort studies and genomic and multiomics analyses. To establish an integrated biobank, we developed an integrated database called "dbTMM" that incorporates both the individual cohort/clinical data and the genome/multiomics data of 157,191 participants in the Tohoku Medical Megabank project. To our knowledge, dbTMM is the first database to store individual whole-genome data on a variant-by-variant basis as well as cohort/clinical data for over one hundred thousand participants in a prospective cohort study. dbTMM enables us to stratify our cohort by both genome-wide genetic factors and environmental factors, and it provides a research and development platform that enables prospective analysis of large-scale data from genome cohorts.

<title>Abstract</title>Lung function reflects the ability of the respiratory system and is utilized for the assessment of respiratory diseases. Because type 2 airway inflammation influences lung function, genome wide association studies (GWAS) for lung function would be improved by adjustment with an indicator of the inflammation. Here, we performed a GWAS for lung function with adjustment for exhaled nitric oxide (FeNO) levels in two independent Japanese populations. Our GWAS with genotype imputations revealed that the <italic>RNF5/AGER</italic> locus including <italic>AGER</italic> rs2070600 SNP, which introduces a G82S substitution of AGER, was the most significantly associated with FEV₁/FVC. Three other rare missense variants of AGER were further identified. We also found genetic loci with three candidate genes (<italic>NOS2, SPSB2</italic> and <italic>RIPOR2</italic>) associated with FeNO levels. Analyses with the BioBank-Japan GWAS resource revealed genetic links of FeNO and asthma-related traits, and existence of common genetic background for allergic diseases and their biomarkers. Our study identified the genetic locus most strongly associated with airway obstruction in the Japanese population and three genetic loci associated with FeNO, an indicator of type 2 airway inflammation in adults.

Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort.

Cytochrome P450 1A2 (CYP1A2), which accounts for approximately 13% of the total hepatic cytochrome content, catalyzes the metabolic reactions of approximately 9% of frequently used drugs, including theophylline and olanzapine. Substantial inter-individual differences in enzymatic activity have been observed among patients, which could be caused by genetic polymorphisms. Therefore, we functionally characterized 21 novel CYP1A2 variants identified in 4773 Japanese individuals by determining the kinetic parameters of phenacetin O-deethylation. Our results showed that most of the evaluated variants exhibited decreased or no enzymatic activity, which may be attributed to potential structural alterations. Notably, the Leu98Gln, Gly233Arg, Ser380del Gly454Asp, and Arg457Trp variants did not exhibit quantifiable enzymatic activity. Additionally, three-dimensional (3D) docking analyses were performed to further understand the underlying mechanisms behind variant pharmacokinetics. Our data further suggest that despite mutations occurring on the protein surface, accumulating interactions could result in the impairment of protein function through the destabilization of binding regions and changes in protein folding. Therefore, our findings provide additional information regarding rare CYP1A2 genetic variants and how their underlying effects could clarify discrepancies noted in previous phenotypical studies. This would allow the improvement of personalized therapeutics and highlight the importance of identifying and characterizing rare variants.

<title>Abstract</title> Ethnic-specific SNP arrays are becoming more important to increase the power of genome-wide association studies in diverse population. In the Tohoku Medical Megabank Project, we have been developing a series of Japonica Arrays (JPA) for genotyping participants based on reference panels constructed from whole-genome sequence data of the Japanese population. Here, we designed a novel version of the SNP array for the Japanese population, called Japonica Array NEO (JPA NEO), comprising a total of 666,883 markers. Among them, 654,246 tag SNPs of autosomes and X chromosome were selected from an expanded reference panel of 3,552 Japanese, 3.5KJPNv2, using pairwise r2 of linkage disequilibrium measures. Additionally, 28,298 markers were included for the evaluation of previously identified disease risk markers from the literature and databases, and those present in the Japanese population were extracted using the reference panel. Through genotyping 286 Japanese samples, we found that the imputation quality r2 and INFO score in the minor allele frequency bin &amp;gt;2.5–5% were &amp;gt;0.9 and &amp;gt;0.8, respectively, and &amp;gt;12 million markers were imputed with an INFO score &amp;gt;0.8. From these results, JPA NEO is a promising tool for genotyping the Japanese population with genome-wide coverage, contributing to the development of genetic risk scores.

Cytochrome P450 2C9 (CYP2C9) is an important drug-metabolizing enzyme that contributes to the metabolism of approximately 15% of clinically used drugs, including warfarin, which is known for its narrow therapeutic window. Interindividual differences in CYP2C9 enzymatic activity caused by CYP2C9 genetic polymorphisms lead to inconsistent treatment responses in patients. Thus, in this study, we characterized the functional differences in CYP2C9 wild-type (CYP2C9.1), CYP2C9.2, CYP2C9.3, and 12 rare novel variants identified in 4773 Japanese individuals. These CYP2C9 variants were heterologously expressed in 293FT cells, and the kinetic parameters (Km, kcat, Vmax, catalytic efficiency, and CLint) of (S)-warfarin 7-hydroxylation and tolbutamide 4-hydroxylation were estimated. From this analysis, almost all novel CYP2C9 variants showed significantly reduced or null enzymatic activity compared with that of the CYP2C9 wild-type. A strong correlation was found in catalytic efficiencies between (S)-warfarin 7-hydroxylation and tolbutamide 4-hydroxylation among all studied CYP2C9 variants. The causes of the observed perturbation in enzyme activity were evaluated by three-dimensional structural modeling. Our findings could clarify a part of discrepancies among genotype-phenotype associations based on the novel CYP2C9 rare allelic variants and could, therefore, improve personalized medicine, including the selection of the appropriate warfarin dose.

Bone dysplasias are a group of rare hereditary diseases, with up to 436 disease types. Perinatal diagnosis is clinically important for adequate personalized management and counseling. There are no reports focused on pathogenic variants of bone dysplasias in the general population. In this study, we focused on autosomal recessive bone dysplasias. We identified pathogenic variants using whole-genome reference panel data from 3552 Japanese individuals. For the first time, we were able to estimate the carrier frequencies and the proportions of potential patients. For autosomal recessive bone dysplasias, we detected 198 pathogenic variants of 54 causative genes. We estimated the variant carrier frequencies and the proportions of potential patients with variants associated with four clinically important bone dysplasias: osteogenesis imperfecta (OI), hypophosphatasia (HPP), asphyxiating thoracic dysplasia (ATD), and Ellis-van Creveld syndrome (EvC). The proportions of potential patients with OI, ATD, and EvC based on pathogenic variants classified as "pathogenic" and "likely pathogenic" by InterVar were closer to the reported incidence rates in Japanese subjects. Furthermore, the proportions of potential patients with HPP variants classified as "pathogenic" and "likely pathogenic" in InterVar and "pathogenic" in ClinVar were closer to the reported incidence rates. For bone dysplasia, the findings of this study will provide a better understanding of the variant types and frequencies in the Japanese general population, and should be useful for clinical diagnosis, genetic counseling, and personalized medicine.

In the Tohoku Medical Megabank project, genome and omics analyses of participants in two cohort studies were performed. A part of the data is available at the Japanese Multi Omics Reference Panel (jMorp; https://jmorp.megabank.tohoku.ac.jp) as a web-based database, as reported in our previous manuscript published in Nucleic Acid Research in 2018. At that time, jMorp mainly consisted of metabolome data; however, now genome, methylome, and transcriptome data have been integrated in addition to the enhancement of the number of samples for the metabolome data. For genomic data, jMorp provides a Japanese reference sequence obtained using de novo assembly of sequences from three Japanese individuals and allele frequencies obtained using whole-genome sequencing of 8,380 Japanese individuals. In addition, the omics data include methylome and transcriptome data from ∼300 samples and distribution of concentrations of more than 755 metabolites obtained using high-throughput nuclear magnetic resonance and high-sensitivity mass spectrometry. In summary, jMorp now provides four different kinds of omics data (genome, methylome, transcriptome, and metabolome), with a user-friendly web interface. This will be a useful scientific data resource on the general population for the discovery of disease biomarkers and personalized disease prevention and early diagnosis.

<p>【目的】薬物代謝酵素CYP2B6遺伝子の多型性は、抗HIV薬をはじめ多くの薬物代謝反応の個人差を引き起こすと考えられている。CYP遺伝子多型の位置や頻度には民族集団差が存在するため、塩基多型に由来するアミノ酸置換等の酵素活性に及ぼす影響の解析は、日本人集団で同定されたバリアントに関して行うことが重要である。そこで本研究では、東北メディカル・メガバンクの全ゲノム情報を活用して、39種類のCYP2B6遺伝子多型バリアントの機能変化を解析し、薬物代謝活性に及ぼす影響を検討した。【方法】野生型CYP2B6のcDNA配列中に遺伝子多型を導入したバリアント発現ベクターを作製し、ヒト胎児腎臓由来293FT細胞中に各バリアント酵素を発現させた。次に、還元型一酸化炭素吸収差スペクトル測定法によりCYP2B6のホロP450含量および抗CYP2B6抗体を用いたウェスタンブロット法によりホロとアポP450の総量を定量した。酵素機能変化に関しては、抗HIV薬エファビレンツ (EFZ) を基質として一定時間反応させ、代謝物である8-水酸化体をLC-MS/MSを用いて定量し、酵素反応速度論的パラメータを算出した。さらに、3次元ドッキングシミュレーションモデル解析により酵素活性変化の分子メカニズム解明も試みた。【結果・考察】EFZ代謝活性測定において、39種のバリアントのうち15種で酵素活性の消失を認めた。また、酵素反応速度論的パラメータが算出できた24種のバリアントのうち、野生型CYP2B6と比較して、6種で酵素活性が有意に低下し、6種で有意に上昇することが明らかとなった。酵素活性が消失したバリアントのほとんどで、ホロP450含量が定量限界以下であった。また、酵素活性が大きく変化したバリアントでは、ホロP450含量の低下やアミノ酸置換部位周辺のループ構造およびヘリックス構造の変化が認められた。【結論】本研究により、野生型を含めた40種のCYP2B6バリアントについて、それらの酵素活性変化を明らかにした。EFZ服用患者において、酵素活性の消失あるいは低下が生じるCYP2B6遺伝子多型を有する場合、中枢神経障害等の副作用発現リスクの増大や治療中断に繋がる可能性が考えられる。今回の知見がCYP2B6遺伝子多型を考慮した個別化薬物療法を実施する上での情報基盤となり、さらなる臨床応用が期待される。</p>

Identification of the population frequencies of definitely pathogenic germline variants in two major hereditary breast and ovarian cancer syndrome (HBOC) genes, BRCA1/2, is essential to estimate the number of HBOC patients. In addition, the identification of moderately penetrant HBOC gene variants that contribute to increasing the risk of breast and ovarian cancers in a population is critical to establish personalized health care. A prospective cohort subjected to genome analysis can provide both sets of information. Computational scoring and prospective cohort studies may help to identify such likely pathogenic variants in the general population. We annotated the variants in the BRCA1 and BRCA2 genes from a dataset of 3,552 whole-genome sequences obtained from members of a prospective cohorts with genome data in the Tohoku Medical Megabank Project (TMM) with InterVar software. Computational impact scores (CADD_phred and Eigen_raw) and minor allele frequencies (MAFs) of pathogenic (P) and likely pathogenic (LP) variants in ClinVar were used for filtration criteria. Familial predispositions to cancers among the 35,000 TMM genome cohort participants were analyzed to verify the identified pathogenicity. Seven potentially pathogenic variants were newly identified. The sisters of carriers of these moderately deleterious variants and definite P and LP variants among members of the TMM prospective cohort showed a statistically significant preponderance for cancer onset, from the self-reported cancer history. Filtering by computational scoring and MAF is useful to identify potentially pathogenic variants in BRCA genes in the Japanese population. These results should help to follow up the carriers of variants of uncertain significance in the HBOC genes in the longitudinal prospective cohort study.

<title>Abstract</title> We performed a metabolome genome-wide association study for the Japanese population in the prospective cohort study of Tohoku Medical Megabank. By combining whole-genome sequencing and nontarget metabolome analyses, we identified a large number of novel associations between genetic variants and plasma metabolites. Of the identified metabolite-associated genes, approximately half have already been shown to be involved in various diseases. We identified metabolite-associated genes involved in the metabolism of xenobiotics, some of which are from intestinal microorganisms, indicating that the identified genetic variants also markedly influence the interaction between the host and symbiotic bacteria. We also identified five associations that appeared to be female-specific. A number of rare variants that influence metabolite levels were also found, and combinations of common and rare variants influenced the metabolite levels more profoundly. These results support our contention that metabolic phenotyping provides important insights into how genetic and environmental factors provoke human diseases.

Transcriptional dysregulation, which can be caused by genetic and epigenetic alterations, is a fundamental feature of many cancers. A key cytoprotective transcriptional activator, NRF2, is often aberrantly activated in non-small cell lung cancers (NSCLCs) and supports both aggressive tumorigenesis and therapeutic resistance. Herein, we find that persistently activated NRF2 in NSCLCs generates enhancers at gene loci that are not normally regulated by transiently activated NRF2 under physiological conditions. Elevated accumulation of CEBPB in NRF2-activated NSCLCs is found to be one of the prerequisites for establishment of the unique NRF2-dependent enhancers, among which the NOTCH3 enhancer is shown to be critical for promotion of tumor-initiating activity. Enhancer remodeling mediated by NRF2-CEBPB cooperativity promotes tumor-initiating activity and drives malignancy of NRF2-activated NSCLCs via establishment of the NRF2-NOTCH3 regulatory axis.

<title>Abstract</title>Identification of pathogenic germline variants yet no clinical evidence in <italic>BRCA</italic> genes has become important in patient care of hereditary breast and ovarian cancer syndrome (HBOC). Computational scoring and prospective cohort studies may help to identify such pathogenic variants. We annotated the variants in the <italic>BRCA1</italic> and <italic>BRCA2</italic> genes from a dataset of 3,552 whole-genome sequences obtained from members of the genome cohorts by Tohoku Medical Megabank Project (TMM) with the InterVar software. Computational impact scores (CADD_phred and Eigen_raw) and minor allele frequencies (MAF) of pathogenic (P) and likely pathogenic (LP) variants in ClinVar are used for filtration criteria. Familial predispositions in cancers among the 35,000 TMM genome cohort participants are analyzed to verify the pathogenicity. Seven potentially pathogenic variants were newly identified. Carriers of these potential pathogenic variants and definite P and LP variants among participants of the TMM prospective cohort show a statistically significant preponderance in cancer onset in sisters in the self-reported cancer history. Filtering by computational scoring and MAF is useful to identify potential pathogenic variants in <italic>BRCA</italic> genes for Japanese population. These results will be helpful to follow up the carriers of variants of uncertain significance in the HBOC genes.

<title>ABSTRACT</title>The complete sequence of the human genome is used as a reference for next-generation sequencing analyses. However, some ethnic ancestries are under-represented in the international human reference genome (e.g., GRCh37), especially Asian populations, due to a strong bias toward European and African ancestries in a single mosaic haploid genome consisting chiefly of a single donor. Here, we performed <italic>de novo</italic> assembly of the genomes from three Japanese male individuals using &gt;100× PacBio long reads and Bionano optical maps per sample. We integrated the genomes using the major allele for consensus, and anchored the scaffolds using sequence-tagged site markers from conventional genetic and radiation hybrid maps to reconstruct each chromosome sequence. The resulting genome sequence, designated JG1, is highly contiguous, accurate, and carries the major allele in the majority of single nucleotide variant sites for a Japanese population. We adopted JG1 as the reference for confirmatory exome re-analyses of seven Japanese families with rare diseases and found that re-analysis using JG1 reduced false-positive variant calls versus GRCh37 while retaining disease-causing variants. These results suggest that integrating multiple genome assemblies from a single ethnic population can aid next-generation sequencing analyses of individuals originated from the population.

Fanconi anemia is a rare recessive disease characterized by multiple congenital abnormalities, progressive bone marrow failure, and a predisposition to malignancies. It results from mutations in one of the 22 known FANC genes. The number of Japanese Fanconi anemia patients with a defined genetic diagnosis was relatively limited. In this study, we reveal the genetic subtyping and the characteristics of mutated FANC genes in Japan and clarify the genotype-phenotype correlations. We studied 117 Japanese patients and successfully subtyped 97% of the cases. FANCA and FANCG pathogenic variants accounted for the disease in 58% and 25% of Fanconi anemia patients, respectively. We identified one FANCA and two FANCG hot spot mutations, which are found at low percentages (0.04-0.1%) in the whole-genome reference panel of 3,554 Japanese individuals (Tohoku Medical Megabank). FANCB was the third most common complementation group and only one FANCC case was identified in our series. Based on the data from the Tohoku Medical Megabank, we estimate that approximately 2.6% of Japanese are carriers of disease-causing FANC gene variants, excluding missense mutations. This is the largest series of subtyped Japanese Fanconi anemia patients to date and the results will be useful for future clinical management.

Incidence rates of Mendelian diseases vary among ethnic groups, and frequencies of variant types of causative genes also vary among human populations. In this study, we examined to what extent we can predict population frequencies of recessive disorders from genomic data, and explored better strategies for variant interpretation and classification. We used a whole-genome reference panel from 3552 general Japanese individuals constructed by the Tohoku Medical Megabank Organization (ToMMo). Focusing on 32 genes for 17 congenital metabolic disorders included in newborn screening (NBS) in Japan, we identified reported and predicted pathogenic variants through variant annotation, interpretation, and multiple ways of classifications. The estimated carrier frequencies were compared with those from the Japanese NBS data based on 1,949,987 newborns from a previous study. The estimated carrier frequency based on genomic data with a recent guideline of variant interpretation for the PAH gene, in which defects cause hyperphenylalaninemia (HPA) and phenylketonuria (PKU), provided a closer estimate to that by the observed incidence than the other methods. In contrast, the estimated carrier frequencies for SLC25A13, which causes citrin deficiency, were much higher compared with the incidence rate. The results varied greatly among the 11 NBS diseases with single responsible genes; the possible reasons for departures from the carrier frequencies by reported incidence rates were discussed. Of note, (1) the number of pathogenic variants increases by including additional lines of evidence, (2) common variants with mild effects also contribute to the actual frequency of patients, and (3) penetrance of each variant remains unclear.

Personalized healthcare (PHC) based on an individual's genetic make-up is one of the most advanced, yet feasible, forms of medical care. The Tohoku Medical Megabank (TMM) Project aims to combine population genomics, medical genetics and prospective cohort studies to develop a critical infrastructure for the establishment of PHC. To date, a TMM CommCohort (adult general population) and a TMM BirThree Cohort (birth+three-generation families) have conducted recruitments and baseline surveys. Genome analyses as part of the TMM Project will aid in the development of a high-fidelity whole-genome Japanese reference panel, in designing custom single-nucleotide polymorphism (SNP) arrays specific to Japanese, and in estimation of the biological significance of genetic variations through linked investigations of the cohorts. Whole-genome sequencing from >3,500 unrelated Japanese and establishment of a Japanese reference genome sequence from long-read data have been done. We next aim to obtain genotype data for all TMM cohort participants (>150,000) using our custom SNP arrays. These data will help identify disease-associated genomic signatures in the Japanese population, while genomic data from TMM BirThree Cohort participants will be used to improve the reference genome panel. Follow-up of the cohort participants will allow us to test the genetic markers and, consequently, contribute to the realization of PHC.

The first step towards realizing personalized healthcare is to catalog the genetic variations in a population. Since the dissemination of individual-level genomic information is strictly controlled, it will be useful to construct population-level allele frequency panels with easy-to-use interfaces. In the Tohoku Medical Megabank Project, we sequenced nearly 4000 individuals from a Japanese population and constructed an allele frequency panel of 3552 individuals after removing related samples. The panel is called the 3.5KJPNv2. It was constructed by using a standard pipeline including the 1KGP and gnomAD algorithms to reduce technical biases and to allow comparisons to other populations. Our database is the first large-scale panel providing the frequencies of variants present on the X chromosome and on the mitochondria in the Japanese population. All the data are available on our original database at https://jmorp.megabank.tohoku.ac.jp.

The first step towards realizing personalized healthcare is to catalog the genetic variations in a population. Since the dissemination of individual-level genomic information is strictly controlled, it will be useful to construct population-level allele frequency panels with easy-to-use interfaces. In the Tohoku Medical Megabank Project, we sequenced nearly 4000 individuals from a Japanese population and constructed an allele frequency panel of 3552 individuals after removing related samples. The panel is called the 3.5KJPNv2. It was constructed by using a standard pipeline including the 1KGP and gnomAD algorithms to reduce technical biases and to allow comparisons to other populations. Our database is the first large-scale panel providing the frequencies of variants present on the X chromosome and on the mitochondria in the Japanese population. All the data are available on our original database at https://jmorp.megabank.tohoku.ac.jp.

BACKGROUND: Genotype imputation from single-nucleotide polymorphism (SNP) genotype data using a haplotype reference panel consisting of thousands of unrelated individuals from populations of interest can help to identify strongly associated variants in genome-wide association studies. The Tohoku Medical Megabank (TMM) project was established to support the development of precision medicine, together with the whole-genome sequencing of 1070 human genomes from individuals in the Miyagi region (Northeast Japan) and the construction of the 1070 Japanese genome reference panel (1KJPN). Here, we investigated the performance of 1KJPN for genotype imputation of Japanese samples not included in the TMM project and compared it with other population reference panels. RESULTS: We found that the 1KJPN population was more similar to other Japanese populations, Nagahama (south-central Japan) and Aki (Shikoku Island), than to East Asian populations in the 1000 Genomes Project other than JPT, suggesting that the large-scale collection (more than 1000) of Japanese genomes from the Miyagi region covered many of the genetic variations of Japanese in mainland Japan. Moreover, 1KJPN outperformed the phase 3 reference panel of the 1000 Genomes Project (1KGPp3) for Japanese samples, and IKJPN showed similar imputation rates for the TMM and other Japanese samples for SNPs with minor allele frequencies (MAFs) higher than 1%. CONCLUSIONS: 1KJPN covered most of the variants found in the samples from areas of the Japanese mainland outside the Miyagi region, implying 1KJPN is representative of the Japanese population's genomes. 1KJPN and successive reference panels are useful genome reference panels for the mainland Japanese population. Importantly, the addition of whole genome sequences not included in the 1KJPN panel improved imputation efficiencies for SNPs with MAFs under 1% for samples from most regions of the Japanese archipelago.

We developed jMorp, a new database containing metabolome and proteome data for plasma obtained from >5000 healthy Japanese volunteers from the Tohoku Medical Megabank Cohort Study, which is available at https://jmorp.megabank.tohoku.ac.jp. Metabolome data were measured by proton nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC-MS), while proteome data were obtained by nanoLC-MS. We released the concentration distributions of 37 metabolites identified by NMR, distributions of peak intensities of 257 characterized metabolites by LC-MS, and observed frequencies of 256 abundant proteins. Additionally, correlation networks for the metabolites can be observed using an interactive network viewer. Compared with some existing databases, jMorp has some unique features: (i) Metabolome data were obtained using a single protocol in a single institute, ensuring that measurement biases were significantly minimized; (ii) The database contains large-scale data for healthy volunteers with various health records and genome data and (iii) Correlations between metabolites can be easily observed using the graphical viewer. Metabolites data are becoming important intermediate markers for evaluating the health states of humans, and thus jMorp is an outstanding resource for a wide range of researchers, particularly those in the fields of medical science, applied molecular biology, and biochemistry.

Motivation: The identification of functional modules from protein-protein interaction (PPI) networks is an important step toward understanding the biological features of PPI networks. The detection of functional modules in PPI networks is often performed by identifying internally densely connected subnetworks, and often produces modules with "core" and "peripheral" proteins. The core proteins are the ones having dense connections to each other in a module. The difference between core and peripheral proteins is important to understand the functional roles of proteins in modules, but there are few methods to explicitly elucidate the internal structure of functional modules at gene level. Results: We propose NCMine, which is a novel network clustering method and visualization tool for the core-peripheral structure of functional modules. It extracts near-complete subgraphs from networks based on a node-weighting scheme using degree centrality, and reports subgroups as functional modules. We implemented this method as a plugin of Cytoscape, which is widely used to visualize and analyze biological networks. The plugin allows users to extract functional modules from PPI networks and interactively filter modules of interest. We applied the method to human PPI networks, and found several examples with the core-peripheral structure of modules that may be related to cancer development.

ATTED-II (http://atted. jp) is a coexpression database for plant species with parallel views of multiple coexpression data sets and network analysis tools. The user can efficiently find functional gene relationships and design experiments to identify gene functions by reverse genetics and general molecular biology techniques. Here, we report updates to ATTED-II (version 8.0), including new and updated coexpression data and analysis tools. ATTED-II now includes eight microarray-and six RNA sequencing-based coexpression data sets for seven dicot species (Arabidopsis, field mustard, soybean, barrel medick, poplar, tomato and grape) and two monocot species (rice and maize). Stand-alone coexpression analyses tend to have low reliability. Therefore, examining evolutionarily conserved coexpression is a more effective approach from the viewpoints of reliability and evolutionary importance. In contrast, the reliability of species- specific coexpression data remains poor. Our assessment scores for individual coexpression data sets indicated that the quality of the new coexpression data sets in ATTEDII is higher than for any previous coexpression data set. In addition, five species (Arabidopsis, soybean, tomato, rice and maize) in ATTED-II are now supported by both microarray- and RNA sequencing-based coexpression data, which has increased the reliability. Consequently, ATTED-II can now provide lineage-specific coexpression information. As an example of the use of ATTED-II to explore lineage-specific coexpression, we demonstrate monocot- and dicot-specific coexpression of cell wall genes. With the expanded coexpression data for multilevel evaluation, ATTED-II provides new opportunities to investigate lineage-specific evolution in plants.

The COXPRESdb (http://coxpresdb.jp) provides gene coexpression relationships for animal species. Here, we report the updates of the database, mainly focusing on the following two points. For the first point, we added RNAseq-based gene coexpression data for three species (human, mouse and fly), and largely increased the number of microarray experiments to nine species. The increase of the number of expression data with multiple platforms could enhance the reliability of coexpression data. For the second point, we refined the data assessment procedures, for each coexpressed gene list and for the total performance of a platform. The assessment of coexpressed gene list now uses more reasonable Pvalues derived from platform-specific null distribution. These developments greatly reduced pseudopredictions for directly associated genes, thus expanding the reliability of coexpression data to design new experiments and to discuss experimental results.

The COXPRESdb (http://coxpresdb.jp) provides gene coexpression relationships for animal species. Here, we report the updates of the database, mainly focusing on the following two points. For the first point, we added RNAseq-based gene coexpression data for three species (human, mouse and fly), and largely increased the number of microarray experiments to nine species. The increase of the number of expression data with multiple platforms could enhance the reliability of coexpression data. For the second point, we refined the data assessment procedures, for each coexpressed gene list and for the total performance of a platform. The assessment of coexpressed gene list now uses more reasonable P-values derived from platform-specific null distribution. These developments greatly reduced pseudopredictions for directly associated genes, thus expanding the reliability of coexpression data to design new experiments and to discuss experimental results.

The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed.

ATTED-II (http://atted.jp) is a database of coexpressed genes that was originally developed to identify functionally related genes in Arabidopsis and rice. Herein, we describe an updated version of ATTED-II, which expands this resource to include additional agriculturally important plants. To improve the quality of the coexpression data for Arabidopsis and rice, we included more gene expression data from microarray and RNA sequencing studies. The RNA sequencing-based coexpression data now cover 94% of the Arabidopsis protein-encoding genes, representing a substantial increase from previously available microarray-based coexpression data (76% coverage). We also generated coexpression data for four dicots (soybean, poplar, grape and alfalfa) and one monocot (maize). As both the quantity and quality of expression data for the non-model species are generally poorer than for the model species, we verified coexpression data associated with these new species using multiple methods. First, the overall performance of the coexpression data was evaluated using gene ontology annotations and the coincidence of a genomic feature. Secondly, the reliability of each guide gene was determined by comparing coexpressed gene lists between platforms. With the expanded and newly evaluated coexpression data, ATTED-II represents an important resource for identifying functionally related genes in agriculturally important plants. © 2013 The Author.

Coexpressed gene databases are valuable resources for identifying new gene functions or functional modules in metabolic pathways and signaling pathways. Although coexpressed gene databases are a fundamental platform in the field of plant biology, their use in animal studies is relatively limited. The COXPRESdb ( ext-link-type="uri" xlink:href="http://coxpresdb.jp" xmlns:xlink="http://www.w3.org/1999/xlink"&gt;http://coxpresdb.jp) provides coexpression relationships for multiple animal species, as comparisons of coexpressed gene lists can enhance the reliability of gene coexpression determinations. Here, we report the updates of the database, mainly focusing on the following two points. First, we updated our coexpression data by including recent microarray data for the previous seven species (human, mouse, rat, chicken, fly, zebrafish and nematode) and adding four new species (monkey, dog, budding yeast and fission yeast), along with a new human microarray platform. A reliability scoring function was also implemented, based on coexpression conservation to filter out coexpression with low reliability. Second, the network drawing function was updated, to implement automatic cluster analyses with enrichment analyses in Gene Ontology and in cis elements, along with interactive network analyses with Cytoscape Web. With these updates, COXPRESdb will become a more powerful tool for analyses of functional and regulatory networks of genes in a variety of animal species.