Riu Yamashita

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.

mTORC1 and muscle regeneration are regulated by the LINC00961-encoded SPAR polypeptide

Although long non-coding RNAs (lncRNAs) are non-protein-coding transcripts by definition, recent studies have shown that a fraction of putative small open reading frames within lncRNAs are translated. However, the biological significance of these hidden polypeptides is still unclear. Here we identify and functionally characterize a novel polypeptide encoded by the lncRNA LINC00961. This polypeptide is conserved between human and mouse, is localized to the late endosome/lysosome and interacts with the lysosomal v-ATPase to negatively regulate mTORC1 activation. This regulation of mTORC1 is specific to activation of mTORC1 by amino acid stimulation, rather than by growth factors. Hence, we termed this polypeptide ‘small regulatory polypeptide of amino acid response’ (SPAR). We show that the SPAR-encoding lncRNA is highly expressed in a subset of tissues and use CRISPR/Cas9 engineering to develop a SPAR-polypeptide-specific knockout mouse while maintaining expression of the host lncRNA. We find that the SPAR-encoding lncRNA is downregulated in skeletal muscle upon acute injury, and using this in vivo model we establish that SPAR downregulation enables efficient activation of mTORC1 and promotes muscle regeneration. Our data provide a mechanism by which mTORC1 activation may be finely regulated in a tissue-specific manner in response to injury, and a paradigm by which lncRNAs encoding small polypeptides can modulate general biological pathways and processes to facilitate tissue-specific requirements, consistent with their restricted and highly regulated expression profile.

DBTSS as an integrative platform for transcriptome, epigenome and genome sequence variation data

DBTSS (http://dbtss.hgc.jp/) was originally constructed as a collection of uniquely determined transcriptional start sites (TSSs) in humans and some other species in 2002. Since then, it has been regularly updated and in recent updates epigenetic information has also been incorporated because such information is useful for characterizing the biological relevance of these TSSs/downstream genes. In the newest release, Release 9, we further integrated public and original single nucleotide variation (SNV) data into our database. For our original data, we generated SNV data from genomic analyses of various cancer types, including 97 lung adenocarcinomas and 57 lung small cell carcinomas from Japanese patients as well as 26 cell lines of lung cancer origin. In addition, we obtained publically available SNV data from other cancer types and germline variations in total of 11,322 individuals. With these updates, users can examine the association between sequence variation pattern in clinical lung cancers with its corresponding TSS-seq, RNA-seq, ChIP-seq and BS-seq data. Consequently, DBTSS is no longer a mere storage site for TSS information but has evolved into an integrative platform of a variety of genome activity data.

BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains

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.

Genome-Wide Analysis of DNA Methylation and Expression of MicroRNAs in Breast Cancer Cells

DNA methylation of promoters is linked to transcriptional silencing of protein-coding genes, and its alteration plays important roles in cancer formation. For example, hypermethylation of tumor suppressor genes has been seen in some cancers. Alteration of methylation in the promoters of microRNAs (miRNAs) has also been linked to transcriptional changes in cancers; however, no systematic studies of methylation and transcription of miRNAs have been reported. In the present study, to clarify the relation between DNA methylation and transcription of miRNAs, next-generation sequencing and microarrays were used to analyze the methylation and expression of miRNAs, protein-coding genes, other non-coding RNAs (ncRNAs), and pseudogenes in the human breast cancer cell lines MCF7 and the adriamycin (ADR) resistant cell line MCF7/ADR. DNA methylation in the proximal promoter of miRNAs is tightly linked to transcriptional silencing, as it is with protein-coding genes. In protein-coding genes, highly expressed genes have CpG-rich proximal promoters whereas weakly expressed genes do not. This is only rarely observed in other gene categories, including miRNAs. The present study highlights the epigenetic similarities and differences between miRNA and protein-coding genes.

Inter-Individual Differences in the Oral Bacteriome Are Greater than Intra-Day Fluctuations in Individuals

Given the advent of massively parallel DNA sequencing, human microbiome is analyzed comprehensively by metagenomic approaches. However, the inter- and intra-individual variability and stability of the human microbiome remain poorly characterized, particularly at the intra-day level. This issue is of crucial importance for studies examining the effects of microbiome on human health. Here, we focused on bacteriome of oral plaques, for which repeated, time-controlled sampling is feasible. Eighty-one supragingival plaque subjects were collected from healthy individuals, examining multiple sites within the mouth at three time points (forenoon, evening, and night) over the course of 3 days. Bacterial composition was estimated by 16S rRNA sequencing and species-level profiling, resulting in identification of a total of 162 known bacterial species. We found that species compositions and their relative abundances were similar within individuals, and not between sampling time or tooth type. This suggests that species-level oral bacterial composition differs significantly between individuals, although the number of subjects is limited and the intra-individual variation also occurs. The majority of detected bacterial species (98.2%; 159/162), however, did not fluctuate over the course of the day, implying a largely stable oral microbiome on an intra-day time scale. In fact, the stability of this data set enabled us to estimate potential interactions between rare bacteria, with 40 co-occurrences supported by the existing literature. In summary, the present study provides a valuable basis for studies of the human microbiome, with significant implications in terms of biological and clinical outcomes.

The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications

BackgroundThe interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009.ResultsDevelopers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs.ConclusionsBeyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service space; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework.

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 Babesia bovis gene and promoter model: an update from full-length EST analysis

BackgroundBabesia bovis is an apicomplexan parasite that causes babesiosis in infected cattle. Genomes of pathogens contain promising information that can facilitate the development of methods for controlling infections. Although the genome of B. bovis is publically available, annotated gene models are not highly reliable prior to experimental validation. Therefore, we validated a preproposed gene model of B. bovis and extended the associated annotations on the basis of experimentally obtained full-length expressed sequence tags (ESTs).ResultsFrom in vitro cultured merozoites, 12,286 clones harboring full-length cDNAs were sequenced from both ends using the Sanger method, and 6,787 full-length cDNAs were assembled. These were then clustered, and a nonredundant referential data set of 2,115 full-length cDNA sequences was constructed. The comparison of the preproposed gene model with our data set identified 310 identical genes, 342 almost identical genes, 1,054 genes with potential structural inconsistencies, and 409 novel genes. The median length of 5 untranslated regions (UTRs) was 152xa0nt. Subsequently, we identified 4,086 transcription start sites (TSSs) and 2,023 transcriptionally active regions (TARs) by examining 5 ESTs. We identified ATGGGG and CCCCAT sites as consensus motifs in TARs that were distributed around -50xa0bp from TSSs. In addition, we found ACACA, TGTGT, and TATAT sites, which were distributed periodically around TSSs in cycles of approximately 150xa0bp. Moreover, related periodical distributions were not observed in mammalian promoter regions.ConclusionsThe observations in this study indicate the utility of integrated bioinformatics and experimental data for improving genome annotations. In particular, full-length cDNAs with one-base resolution for TSSs enabled the identification of consensus motifs in promoter sequences and demonstrated clear distributions of identified motifs. These observations allowed the illustration of a model promoter composition, which supports the differences in transcriptional regulation frameworks between apicomplexan parasites and mammals.

Comparison of Boiling and Robotics Automation Method in DNA Extraction for Metagenomic Sequencing of Human Oral Microbes.

The rapid improvement of next-generation sequencing performance now enables us to analyze huge sample sets with more than ten thousand specimens. However, DNA extraction can still be a limiting step in such metagenomic approaches. In this study, we analyzed human oral microbes to compare the performance of three DNA extraction methods: PowerSoil (a method widely used in this field), QIAsymphony (a robotics method), and a simple boiling method. Dental plaque was initially collected from three volunteers in the pilot study and then expanded to 12 volunteers in the follow-up study. Bacterial flora was estimated by sequencing the V4 region of 16S rRNA following species-level profiling. Our results indicate that the efficiency of PowerSoil and QIAsymphony was comparable to the boiling method. Therefore, the boiling method may be a promising alternative because of its simplicity, cost effectiveness, and short handling time. Moreover, this method was reliable for estimating bacterial species and could be used in the future to examine the correlation between oral flora and health status. Despite this, differences in the efficiency of DNA extraction for various bacterial species were observed among the three methods. Based on these findings, there is no “gold standard” for DNA extraction. In future, we suggest that the DNA extraction method should be selected on a case-by-case basis considering the aims and specimens of the study.