Biology subjects

Nakagawa, H.

Publications and source records attributed to Nakagawa, H..

35 records · Page 2Linked to original sources

bioRxiv2019

Endogenization and excision of human herpesvirus 6 in human genomes

The genome of human herpesvirus 6 (HHV-6) is integrated within the nuclear genome of about 1% of humans, but how this came about is not clear. HHV-6 integrates into telomeres, and this has recently been associated with polymorphisms affecting MOV10L1. MOV10L1 is located on the subtelomere of chromosome 22q (chr22q) and is required to make PIWI-interacting RNAs (piRNAs). piRNAs block integration of transposons in the germline, so piRNA-mediated repression of HHV-6 integration has been suspected. Whether integrated HHV-6 can reactive into an infectious virus is also uncertain. In vitro, recombination of the viral genome along its terminal direct repeats (DRs) leads to excision from the telomere and viral reactivation, but the expected single DR "scar" has not been described in vivo. We analyzed whole-genome sequencing (WGS) data from 13,040 subjects, including 7,485 from Japan. We found an association between integrated HHV-6 and polymorphisms on chr22q in Japanese subjects. However, association with the reported MOV10L1 polymorphism was driven by physical linkage to a single ancient endogenous HHV-6A variant integrated into the telomere of chr22q in East Asians. We resolved the junction of the human chromosome with this viral genome using long read sequencing. Unexpectedly, an HHV-6B variant has also endogenized in chr22q; two endogenous HHV-6 variants at this locus thus account for 72% of all integrated HHV-6 in Japan. We also report human genomes carrying only one portion of the HHV-6B genome, a single DR, supporting in vivo excision and viral reactivation. Using WGS data from North American families, we show that the incidence of HHV-6 integration into the germline is lower than its prevalence, and that integrated HHV-6 is not associated with the reported variant in MOV10L1. Together these results explain the recently reported association between integrated HHV-6 and MOV10L1/piRNAs, suggest exaptation of HHV-6 in its coevolution with human chr22q, and clarify the evolution and risk of reactivation of the only intact non-retroviral genome known to be present in human germlines. SIGNIFICANCE STATEMENT Human herpesvirus 6 (HHV-6) infects most people during childhood, usually only causing fever and rash. Reactivation of HHV-6 has been linked to a number of neurological diseases including encephalitis, Alzheimers disease and multiple sclerosis. However, about 1% of people are born with the HHV-6 genome present within their genome, included in the end "cap" of one of their 46 chromosomes. Little is known about how and when HHV-6 genomes entered human genomes, whether or not they still do, and whether or not this poses risk for virus reactivation. We looked for HHV-6 in genome sequences from over 13,000 people. Most HHV-6 variants present in human genomes have been co-evolving with human chromosomes for many generations, and new integration events are rare. Surprisingly, in almost three fourths of Japanese people with HHV-6 in their genome, HHV-6 integrated in the same end of the same chromosome - 22q. Persistence of the HHV-6 genome within the short "cap" that preserves the end of chromosome 22q suggests that the integrated viral sequence may have taken on a useful function for this chromosome. We also found that some human genomes harbor only one part of the HHV-6 genome. This part is the same part that remains after experimental viral reactivation, during which most of the virus is cut out of the genome. This warrants assessment of the risk that integration of HHV-6 into inherited human genomes is not irreversible, and possibly leads to production of infectious virus.

genetics↗

bioRxiv2019

A multifunctional R package for identification of tumor-specific neoantigens

It is known that some mutated peptides, such as those resulting from missense mutations and frameshift insertions, can bind to the major histocompatibility complex and be presented to antitumor T-cells on the surface of a tumor cell. These peptides are termed neoantigen and it is important to understand this process for cancer immunotherapy. Here, we introduce an R package that can predict a list of potential neoantigens from a variety of mutations, which include not only somatic point mutations but insertions, deletions, and structural variants. Beyond the existing applications, this package is capable of attaching and reflecting several additional information, e.g., wild-type binding capability, allele specific RNA expression levels, single nucleotide polymorphism information, and combinations of mutations to filter out infeasible peptides as neoantigen. AvailabilityThe R package is available at http://github/hase62/Neoantimon.

bioinformatics↗

bioRxiv2019

Seasonal and annual fluctuations of deer populations estimated by a Bayesian state-space model

Deer overabundance is a contributing factor in the degradation of plant communities and ecosystems worldwide. The management and conservation of the deer-affected ecosystems requires us to urgently grasp deer population trends and to identify the factors that affect them. In this study, we developed a Bayesian state-space model to estimate the population dynamics of sika deer (Cervus nippon) in a cool-temperate forest in Japan, where wolves (Canis lupus hodophilax) are extinct. The model was based on field data collected from block count surveys, road count surveys by vehicles, mortality surveys during the winter, and nuisance control for 12 years (2007-2018). We clarified the seasonal and annual fluctuation of the deer population. We found two peaks of deer abundance (2007 and 2010) over 12 years. In 2011 the estimated deer abundance decreased drastically and has remained at a low level then. The deer population increased from spring to autumn and decreased from autumn to winter in most years. The seasonal fluctuation we detected could reflect the seasonal migration pattern of deer and the population recruitment through fawn births in early summer. In our model, snowfall accumulation, which can be a lethal factor for deer, may have slightly affected their mortality during the winter. Although we could not detect a direct effect of snow on population dynamics, snowfall decrease due to global warming may decelerate the winter migration of deer; subsequently, deer staying on-site may intensively forage evergreen perennial plants during the winter season. The nuisance control affected population dynamics. Even in wildlife protection areas and national parks where hunting is regulated, nuisance control could be effective in buffering the effect of deer browsing on forest ecosystems.

ecology↗

bioRxiv2019

Choosing the optimal population for a genome-wide association study: a simulation using whole-genome sequences from rice

A genome-wide association study (GWAS) needs to have a suitable population. The factors that affect a GWAS, e.g. population structure, sample size, and sequence analysis and field testing costs, need to be considered. Mixture populations containing subpopulations of different genetic backgrounds may be suitable populations. We conducted simulation experiments to see if a population with high genetic diversity, e.g., a diversity panel, should be added to a target population, especially when the target population harbors small genetic diversity. The target population was 112 accessions of Oryza sativa subsp. japonica, mainly developed in Japan. We combined the target population with three populations that had higher genetic diversities. These were 100 indica accessions, 100 japonica accessions, and 100 accessions with various genetic backgrounds. The results showed that the GWAS power with a mixture population was generally higher than with a separate population. Also, the GWAS optimal population varied depending on the fixation index FST of the quantitative trait nucleotide (QTN) and its polymorphism of QTN in each population. When a QTN is polymorphic in a target population, a target population combined with a higher diversity population improves the QTN detection power. Investigating FST and the expected heterozygosity He as factors influencing the detection power, we showed that SNPs with high FST or low He are less likely to be detected by GWAS with mixture populations. Sequenced/genotyped germplasm collections can improve the GWAS detection power by using a subset of them with a target population.\n\nCore ideas (3-5 impact statements, 85 char max for each)\n\n- Genome-wide association studies with mixture populations are expected to improve the detection power of novel genes due to the increase of the sample size although the influence of population structure is a concern.\n- When a quantitative trait nucleotide (QTN) is polymorphic in a target population, a combination of the target population and a population with higher diversity than the target population improves the detection power of the QTN.\n- We found that the fixation index (FST) and the expected heterozygosity (He) were strongly related to the detection power of QTNs.\n- Germplasm collections which have been already sequenced/genotyped are useful for improving the detection power of GWAS without any addition of sequence costs by using a subset of them with a target population.

genomics↗

bioRxiv2019

Large scale genome-wide association study in a Japanese population identified 45 novel susceptibility loci for 22 diseases

INTRODUCTORY PARAGRAPHThe overwhelming majority of participants in current genetic studies are of European ancestry1-3, limiting our genetic understanding of complex disease in non-European populations. To address this, we aimed to elucidate polygenic disease biology in the East Asian population by conducting a genome-wide association study (GWAS) with 212,453 Japanese individuals across 42 diseases. We detected 383 independent signals in 331 loci for 30 diseases, among which 45 loci were novel (P < 5 x 10-8). Compared with known variants, novel variants have lower frequency in European populations but comparable frequency in East Asian populations, suggesting the advantage of this study in discovering these novel variants. Three novel signals were in linkage disequilibrium (r2 > 0.6) with missense variants which are monomorphic in European populations (1000 Genomes Project) including rs11235604(p.R220W of ATG16L2, a autophagy-related gene) associated with coronary artery disease. We further investigated enrichment of heritability within 2,868 annotations of genome-wide transcription factor occupancy, andidentified 378 significant enrichments across nine diseases (FDR < 0.05) (e.g. NF-{kappa}B for immune-related diseases). This large-scale GWAS in a Japanese population provides insights into the etiology of common complex diseases and highlights the importance of performing GWAS in non-European populations.

genetics↗

bioRxiv2019

Coupling Day Length Data and Genomic Prediction tools for Predicting Time-Related Traits under Complex Scenarios

Genomic selection (GS) has proven to be an efficient tool for predicting crop-rank performance of untested genotypes; however, when the traits have intermediate optima (phenology stages) this implementation might not be the most convenient. GS might deliver high rank correlations but incurring in serious bias. Days to heading (DTH) is a crucial development stage in rice for regional adaptability with significant impact in yield potential. The objectives of this research consisted in the development of a method that accurately predicts time related traits like DTH in unobserved environments. For this, we developed an implementation that incorporate day length information (DL) in the prediction process for two relevant scenarios: CV0, predicting tested genotypes in unobserved environments (C method); and CV00, predicting untested genotypes in unobserved environments (CB method). The use of DL has advantages over weather data since it can be determined in advance just by knowing the location and planting date. The proposed methods showed that DL information significantly helps to improve the predictive ability of DTH in unobserved environments. Under CV0, the C method returned an root-mean-square-error (RMSE) of 3.9 days, a Pearson Correlation (PC) of 0.98 and the differences between the predicted and observed environmental means (EMD) ranged between -4.95 and 4.67 days. For CV00, the CB method returned an RMSE of 7.3 days, a PC of 0.93 and the EMD ranged between -6.4 and 4.1 days while the conventional GS implementation produced an RMSE of 18.1 days, a PC of 0.41 and the EMD ranged between -31.5 and 28.7 days.

genomics↗

bioRxiv2019

Identifying predictors of HPV-related head and neck squamous cell carcinoma progression and survival through patient-derived models

Therapeutic innovation for human papilloma virus-related (HPV+) head and neck squamous cell carcinomas (HNSCCs) is impaired by inadequate biomarkers and preclinical models. This study addressed both limitations using the largest panel of HPV+ HNSCC patient-derived xenografts (PDXs) and organoids described to date. Whole exome profiles of the PDXs were compared to those of HPV+ human tumors and cell lines, and genetic features of the models were analyzed relative to their growth properties and outcomes of their patients of origin. PDX engraftment enriched for negatively prognostic NOTCH1 mutations while preserving multiple features lost in existing cell lines, including PIK3CA mutations, TRAF3 deletion, and absence of EGFR amplification. Observation of more mutations in faster-growing models facilitated identification of an association between mutational burden and local progression in both HPV+ and HPV-HNSCCs. Reduced E7 and p16INK4A levels found in a PDX from a lethal case led to detection of a similar profile among recurrent HPV+ HNSCCs in two patient cohorts, where low E2F target gene expression downstream of E7 predicted recurrence and mortality. Our findings bridge a critical gap in preclinical models for HPV+ HNSCCs and simultaneously reveal novel applications for mutational burden and E2F target dysregulation in biomarker development.

cancer biology↗

bioRxiv2019

Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer

BackgroundPrimary liver tissue cancers display consistent increase in global disease burden and mortality. Identification of cell-of-origins for primary liver cancers would be a necessity to expand options for designing relevant therapeutics and preventive medicine for these cancer types. Previous reports on cell-of-origin for primary liver cancers was mainly from animal studies, and integrative research utilizing human specimen data was poorly established.\n\nMethodsWe analyzed a whole-genome sequencing data set for a total of 363 tumor and progenitor tissues along with 423 normal tissue epigenomic marks to predict the cell-of-origin for primary liver cancer subtypes.\n\nResultsDespite the mixed histological features, the predicted cell-of-origin for mixed hepatocellular carcinoma / intrahepatic cholangiocarcinoma were uniformly predicted as a hepatocytic origin. Individual sample-level prediction revealed differential level of cell-of-origin heterogeneity depending on the primary liver cancer types, with more heterogeneity observed in intrahepatic cholangiocarcinomas. Additional analyses on the whole genome sequencing data of hepatic progenitor cells suggest these progenitor cells might not a direct cell-of-origin for liver cancers.\n\nConclusionsThese results provide novel insights on the heterogeneous nature and potential contributors of cell-of-origin predictions for primary liver cancers.

genomics↗

bioRxiv2018

Comprehensive Analysis of Indels in Whole-genome Microsatellite Regions and Microsatellite Instability across 21 Cancer Types

Microsatellites are repeats of 1-6bp units and [~]10 million microsatellites have been identified across the human genome. Microsatellites are vulnerable to DNA mismatch errors, and have thus been used to detect cancers with mismatch repair deficiency. To reveal the mutational landscape of the microsatellite repeat regions at the genome level, we analyzed approximately 20.1 billion microsatellites in 2,717 whole genomes of pan-cancer samples across 21 tissue types. Firstly, we developed a new insertion and deletion caller (MIMcall) that takes into consideration the error patterns of different types of microsatellites. Among the 2,717 pan-cancer samples, our analysis identified 31 samples, including colorectal, uterus, and stomach cancers, with higher microsatellite mutation rate ([≥] 0.03), which we defined as microsatellite instability (MSI) cancers in genome-wide level. Next, we found 20 highly-mutated microsatellites that can be used to detect MSI cancers with high sensitivity. Third, we found that replication timing and DNA shape were significantly associated with mutation rates of the microsatellites. Analysis of germline variation of the microsatellites suggested that the amount of germline variations and somatic mutation rates were correlated. Lastly, analysis of mutations in mismatch repair genes showed that somatic SNVs and short indels had larger functional impact than germline mutations and structural variations. Our analysis provides a comprehensive picture of mutations in the microsatellite regions, and reveals possible causes of mutations, as well as provides a useful marker set for MSI detection.

cancer biology↗

bioRxiv2018

ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data

Although human leukocyte antigen (HLA) genotyping based on amplicon, whole exome sequence (WES), and RNA sequence data has been achieved in recent years, accurate genotyping from whole genome sequence (WGS) data remains a challenge due to the low depth. Furthermore, there is no method to identify the sequences of unknown HLA types not registered in HLA databases. We developed a Bayesian model, called ALPHLARD, that collects reads potentially generated from HLA genes and accurately determines a pair of HLA types for each of HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, and -DRB1 genes at 6-digit resolution. Furthermore, ALPHLARD can detect rare germline variants not stored in HLA databases and call somatic mutations from paired normal and tumor sequence data. We illustrate the capability of ALPHLARD using 253 WES data and 25 WGS data from Illumina platforms. By comparing the results of HLA genotyping from SBT and amplicon sequencing methods, ALPHLARD achieved 98.8% for WES data and 98.5% for WGS data at 4-digit resolution. We also detected three somatic point mutations and one case of loss of heterozygosity in the HLA genes from the WGS data. ALPHLARD showed good performance for HLA genotyping even from low-coverage data. It also has a potential to detect rare germline variants and somatic mutations in HLA genes. It would help to fill in the current gaps in HLA reference databases and unveil the immunological significance of somatic mutations identified in HLA genes.

bioinformatics↗

bioRxiv2018

Immuno-genomic PanCancer Landscape Reveals Diverse Immune Escape Mechanisms and Immuno-Editing Histories

Immune reactions in the tumor micro-environment are one of the cancer hallmarks and emerging immune therapies have been proven effective in many types of cancer. To investigate cancer genome-immune interactions and the role of immuno-editing or immune escape mechanisms in cancer development, we analyzed 2,834 whole genomes and RNA-seq datasets across 31 distinct tumor types from the PanCancer Analysis of Whole Genomes (PCAWG) project with respect to key immuno-genomic aspects. We show that selective copy number changes in immune-related genes could contribute to immune escape. Furthermore, we developed an index of the immuno-editing history of each tumor sample based on the information of mutations in exonic regions and pseudogenes. Our immuno-genomic analyses of pan-cancer analyses have the potential to identify a subset of tumors with immunogenicity and diverse background or intrinsic pathways associated with their immune status and immuno-editing history.

genomics↗

bioRxiv2017

Genetic structure and sex-biased gene flow in the history of southern African populations

ObjectivesWe investigated the genetic history of southern African populations with a special focus on their paternal history. We reexamined previous claims that the Y-chromosome haplogroup E1b1b was brought to southern Africa by pastoralists from eastern Africa, and investigated patterns of sex-biased gene flow in southern Africa.\n\nMaterial and MethodsWe analyzed previously published complete mtDNA genome sequences and ~900 kb of NRY sequences from 23 populations from Namibia, Botswana and Zambia, as well as haplogroup frequencies from a large sample of southern African populations and 23 newly genotyped Y-linked STR loci for samples assigned to haplogroup E1b1b.\n\nResultsOur results support an eastern African origin for Y-chromosome haplogroup E1b1b; however, its current distribution in southern Africa is not strongly associated with pastoralism, suggesting a more complex origin for pastoralism in this region. We confirm that the Bantu expansion had a notable genetic impact in southern Africa, and that in this region it was probably a rapid, male-dominated expansion. Furthermore, we find a significant increase in the intensity of sex-biased gene flow from north to south, which may reflect changes in the social dynamics between Khoisan and Bantu groups over time.\n\nConclusionsOur study shows that the population history of southern Africa has been very complex, with different immigrating groups mixing to different degrees with the autochthonous populations. The Bantu expansion led to heavily sex-biased admixture as a result of interactions between Khoisan females and Bantu males, with a geographic gradient which may reflect changes in the social dynamics between Khoisan and Bantu groups over time.

genetics↗

bioRxiv2017

Quantifying Immune-Based Counterselection of Somatic Mutations

It is now well established that somatic mutations in protein-coding regions can generate neoantigens, and that these can be recognized by the immune system and contribute to clearance of developing cancers. However, there is currently no model that can quantitatively predict the neoantigenic effect of any given somatic mutation. Here, we examined signatures of immune selection pressure on the distribution of somatic mutations. We quantified the extent to which somatic mutations are significantly depleted in peptides that are predicted to be displayed by major histocompatibility complex (MHC) class I proteins. We characterized the dependence of this depletion on expression level. We then examined whether immune selection pressure on somatic mutations changes depending on whether the patient had either one or two MHC-encoding alleles that can display the peptide. Our results indicate that MHC-encoding alleles are, in general, incompletely dominant, i.e., that having two copies of the display-enabling allele is more effective in displaying that peptide than having just one copy. More generally, a quantitative understanding of counter-selection of identifiable subclasses of neoantigenic somatic variation could guide immunotherapy or aid in developing personalized cancer vaccines.

genetics↗

bioRxiv2017

Germline determinants of the somatic mutation landscape in 2,642 cancer genomes

Cancers develop through somatic mutagenesis, however germline genetic variation can markedly contribute to tumorigenesis via diverse mechanisms. We discovered and phased 88 million germline single nucleotide variants, short insertions/deletions, and large structural variants in whole genomes from 2,642 cancer patients, and employed this genomic resource to study genetic determinants of somatic mutagenesis across 39 cancer types. Our analyses implicate damaging germline variants in a variety of cancer predisposition and DNA damage response genes with specific somatic mutation patterns. Mutations in the MBD4 DNA glycosylase gene showed association with elevated C>T mutagenesis at CpG dinucleotides, a ubiquitous mutational process acting across tissues. Analysis of somatic structural variation exposed complex rearrangement patterns, involving cycles of templated insertions and tandem duplications, in BRCA1-deficient tumours. Genome-wide association analysis implicated common genetic variation at the APOBEC3 gene cluster with reduced basal levels of somatic mutagenesis attributable to APOBEC cytidine deaminases across cancer types. We further inferred over a hundred polymorphic L1/LINE elements with somatic retrotransposition activity in cancer. Our study highlights the major impact of rare and common germline variants on mutational landscapes in cancer.

genomics↗

bioRxiv2017

In-depth characterization of the cisplatin mutational signature in a human cell line and in esophageal and liver tumors

Background and aimsCisplatin reacts with DNA, and thereby likely generates a characteristic pattern of somatic mutations, called a mutational signature. Despite widespread use of cisplatin in cancer treatment and its role in contributing to secondary malignancies, its mutational signature has not been delineated. We hypothesize that cisplatins mutational signature can serve as a biomarker to identify cisplatin mutagenesis in suspected secondary malignancies. Knowledge of which tissues are at risk of developing cisplatin-induced secondary malignancies could lead to guidelines for non-invasive monitoring for secondary malignancies after cisplatin chemotherapy.\n\nMethodsWe performed whole genome sequencing of 10 independent clones of cisplatin-exposed MCF-10A and HepG2 cells, and delineated the patterns of single- and dinucleotide mutations in terms of flanking sequence, transcription strand bias, and other characteristics. We used the mSigAct signature presence test and non-negative matrix factorization to search for cisplatin mutagenesis in hepatocellular carcinomas and esophageal adenocarcinomas.\n\nResultsAll clones showed highly consistent patterns of single- and dinucleotide substitutions. The proportion of dinucleotide substitutions was high: 8.1% of single nucleotide substitutions were part of dinucleotide substitutions, presumably due to cisplatins propensity to form intra-and inter-strand crosslinks between purine bases in DNA. We identified likely cisplatin exposure in 9 hepatocellular carcinomas and 3 esophageal adenocarcinomas. All hepatocellular carcinomas for which clinical data were available and all esophageal cancers indeed had histories of cisplatin treatment.\n\nConclusionsWe experimentally delineated the single- and dinucleotide mutational signature of cisplatin. This signature enabled us to detect previous cisplatin exposure in human hepatocellular carcinomas and esophageal adenocarcinomas with high confidence.

cancer biology↗

bioRxiv2017

Large-Scale Uniform Analysis of Cancer Whole Genomes in Multiple Computing Environments

The International Cancer Genome Consortium (ICGC)s Pan-Cancer Analysis of Whole Genomes (PCAWG) project aimed to categorize somatic and germline variations in both coding and non-coding regions in over 2,800 cancer patients. To provide this dataset to the research working groups for downstream analysis, the PCAWG Technical Working Group marshalled ~800TB of sequencing data from distributed geographical locations; developed portable software for uniform alignment, variant calling, artifact filtering and variant merging; performed the analysis in a geographically and technologically disparate collection of compute environments; and disseminated high-quality validated consensus variants to the working groups. The PCAWG dataset has been mirrored to multiple repositories and can be located using the ICGC Data Portal. The PCAWG workflows are also available as Docker images through Dockstore enabling researchers to replicate our analysis on their own data.

genomics↗

bioRxiv2017

Comprehensive Molecular Characterization of Mitochondrial Genomes in Human Cancers

Mitochondria are essential cellular organelles that play critical roles in cancer development. Through International Cancer Genome Consortium, we performed a multidimensional characterization of mitochondrial genomes using the whole-genome sequencing data of ~2,700 patients across 37 cancer types and related RNA-sequencing data. Our analysis presents the most definitive mutational landscape of mitochondrial genomes including a novel hypermutated case. We observe similar mutational signatures across cancer types, suggesting powerful endogenous mutational processes in mitochondria. Truncating mutations are remarkably enriched in kidney, colorectal and thyroid cancers and associated with the activation of critical signaling pathways. We find frequent somatic nuclear transfers of mitochondrial DNA (especially in skin and lung cancers), some of which disrupt therapeutic target genes (e.g., ERBB2). The mitochondrial DNA copy number shows great variations within and across cancers and correlates with clinical variables. Co-expression analysis highlights the function of mitochondrial genes in oxidative phosphorylation, DNA repair, and cell cycle; and reveals their connections with clinically actionable genes. Our study, including an open-access data portal, lays a foundation for understanding the interplays between the cancer mitochondrial and nuclear genomes and translating mitochondrial biology into clinical applications.

genomics↗