The 36th International Mammalian Genome Conference: A scientific gathering under the cherry blossoms in Tsukuba.

The 36th International Mammalian Genome Conference (IMGC) was held in a hybrid format at the Tsukuba International Congress Center in Tsukuba, Ibaraki, Japan, for 4 days from March 28 to 31, 2023. This international conference on functional genomics of mouse, human, and other mammalian species attracted 246 participants in total, of which 129 were from outside Japan, including Europe, the United States and Asia, and 117 participants were from Japan. The conference included three technical workshops, keynote lectures by domestic researchers, commemorative lectures for the conference awards, 57 oral presentations, and 97 poster presentations. The event was a great success. Topics included the establishment and analysis of disease models using genetically engineered or spontaneous mutant mice, systems genetic analysis using mouse strains such as wild-derived mice and recombinant inbred mouse strains, infectious diseases, immunology, and epigenetics. In addition, as a joint program, a two-day RIKEN Symposium was held, and active discussions continued over the four-day period. Also, there was a trainee symposium, in which young researchers were encouraged to participate, and excellent papers were selected as oral presentations in the main session.

Prototyping an Ontological Framework for Cellular Senescence Mechanisms: A Homeostasis Imbalance Perspective.

Although cellular senescence is a key factor in organismal aging, with both positive and negative effects on individuals, its mechanisms remain largely unknown. Thus, integrating knowledge is essential to explain how cellular senescence manifests in tissue damage and age-related diseases. Here, we propose an ontological model that organizes knowledge of cellular senescence in a computer-readable form. We manually annotated and defined cellular senescence processes, molecules, anatomical structures, phenotypes, and other entities based on the Homeostasis Imbalance Process ontology (HOIP). We described the mechanisms as causal relationships of processes and modelled a homeostatic imbalance between stress and stress response in cellular senescence for a unified framework. HOIP was assessed formally, and the relationships between cellular senescence and diseases were inferred for higher-order knowledge processing. We visualized cellular senescence processes to support knowledge utilization. Our study provides a knowledge base to help elucidate mechanisms linking cellular and organismal aging.

Homeostasis imbalance process ontology: a study on COVID-19 infectious processes.

BACKGROUND: One significant challenge in addressing the coronavirus disease 2019 (COVID-19) pandemic is to grasp a comprehensive picture of its infectious mechanisms. We urgently need a consistent framework to capture the intricacies of its complicated viral infectious processes and diverse symptoms. RESULTS: We systematized COVID-19 infectious processes through an ontological approach and provided a unified description framework of causal relationships from the early infectious stage to severe clinical manifestations based on the homeostasis imbalance process ontology (HoIP). HoIP covers a broad range of processes in the body, ranging from normal to abnormal. Moreover, our imbalance model enabled us to distinguish viral functional demands from immune defense processes, thereby supporting the development of new drugs, and our research demonstrates how ontological reasoning contributes to the identification of patients at severe risk. CONCLUSIONS: The HoIP organises knowledge of COVID-19 infectious processes and related entities, such as molecules, drugs, and symptoms, with a consistent descriptive framework. HoIP is expected to harmonise the description of various heterogeneous processes and improve the interoperability of COVID-19 knowledge through the COVID-19 ontology harmonisation working group.

Estimation of silent phenotypes of calf antibiotic dysbiosis.

Reducing antibiotic usage among livestock animals to prevent antimicrobial resistance has become an urgent issue worldwide. This study evaluated the effects of administering chlortetracycline (CTC), a versatile antibacterial agent, on the performance, blood components, fecal microbiota, and organic acid concentrations of calves. Japanese Black calves were fed with milk replacers containing CTC at 10 g/kg (CON group) or 0 g/kg (EXP group). Growth performance was not affected by CTC administration. However, CTC administration altered the correlation between fecal organic acids and bacterial genera. Machine learning (ML) methods such as association analysis, linear discriminant analysis, and energy landscape analysis revealed that CTC administration affected populations of various types of fecal bacteria. Interestingly, the abundance of several methane-producing bacteria at 60 days of age was high in the CON group, and the abundance of Lachnospiraceae, a butyrate-producing bacterium, was high in the EXP group. Furthermore, statistical causal inference based on ML data estimated that CTC treatment affected the entire intestinal environment, potentially suppressing butyrate production, which may be attributed to methanogens in feces. Thus, these observations highlight the multiple harmful impacts of antibiotics on the intestinal health of calves and the potential production of greenhouse gases by calves.

Computational estimation of sediment symbiotic bacterial structures of seagrasses overgrowing downstream of onshore aquaculture.

Coastal seagrass meadows are essential in blue carbon and aquatic ecosystem services. However, this ecosystem has suffered severe eutrophication and destruction due to the expansion of aquaculture. Therefore, methods for the flourishing of seagrass are still being explored. Here, data from 49 public coastal surveys on the distribution of seagrass and seaweed around the onshore aquaculture facilities are revalidated, and an exceptional area where the seagrass Zostera marina thrives was found near the shore downstream of the onshore aquaculture facility. To evaluate the characteristics of the sediment for growing seagrass, physicochemical properties and bacterial ecological evaluations of the sediment were conducted. Evaluation of chemical properties in seagrass sediments confirmed a significant increase in total carbon and a decrease in zinc content. Association analysis and linear discriminant analysis refined bacterial candidates specified in seagrass overgrown- and nonovergrown-sediment. Energy landscape analysis indicated that the symbiotic bacterial groups of seagrass sediment were strongly affected by the distance close to the seagrass-growing aquaculture facility despite their bacterial population appearing to fluctuate seasonally. The bacterial population there showed an apparent decrease in the pathogen candidates belonging to the order Flavobacteriales. Moreover, structure equation modeling and a linear non-Gaussian acyclic model based on the machine learning data estimated an optimal sediment symbiotic bacterial group candidate for seagrass growth as follows: the Lachnospiraceae and Ruminococcaceae families as gut-inhabitant bacteria, Rhodobacteraceae as photosynthetic bacteria, and Desulfobulbaceae as cable bacteria modulating oxygen or nitrate reduction and oxidation of sulfide. These observations confer a novel perspective on the sediment symbiotic bacterial structures critical for blue carbon and low-pathogenic marine ecosystems in aquaculture.

Decomposing predictability to identify dominant causal drivers in complex ecosystems.

Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of different levels of stochasticity and nonlinearity, handling these data is a challenge for existing methods of time series-based causal inferences. Here, we show that, by harnessing contemporary machine learning approaches, the concept of Granger causality can be effectively extended to the analysis of complex ecosystem time series and bridge the gap between dynamical and statistical approaches. The central idea is to use an ensemble of fast and highly predictive artificial neural networks to select a minimal set of variables that maximizes the prediction of a given variable. It enables decomposition of the relationship among variables through quantifying the contribution of an individual variable to the overall predictive performance. We show how our approach, EcohNet, can improve interaction network inference for a mesocosm experiment and simulated ecosystems. The application of the method to a long-term lake monitoring dataset yielded interpretable results on the drivers causing cyanobacteria blooms, which is a serious threat to ecological integrity and ecosystem services. Since performance of EcohNet is enhanced by its predictive capabilities, it also provides an optimized forecasting of overall components in ecosystems. EcohNet could be used to analyze complex and hybrid multivariate time series in many scientific areas not limited to ecosystems.

Chemical-Mediated Microbial Interactions Can Reduce the Effectiveness of Time-Series-Based Inference of Ecological Interaction Networks.

Network-based assessments are important for disentangling complex microbial and microbial-host interactions and can provide the basis for microbial engineering. There is a growing recognition that chemical-mediated interactions are important for the coexistence of microbial species. However, so far, the methods used to infer microbial interactions have been validated with models assuming direct species-species interactions, such as generalized Lotka-Volterra models. Therefore, it is unclear how effective existing approaches are in detecting chemical-mediated interactions. In this paper, we used time series of simulated microbial dynamics to benchmark five major/state-of-the-art methods. We found that only two methods (CCM and LIMITS) were capable of detecting interactions. While LIMITS performed better than CCM, it was less robust to the presence of chemical-mediated interactions, and the presence of trophic competition was essential for the interactions to be detectable. We show that the existence of chemical-mediated interactions among microbial species poses a new challenge to overcome for the development of a network-based understanding of microbiomes and their interactions with hosts and the environment.

Characterization of single nucleotide polymorphisms for a forward genetics approach using genetic crosses in C57BL/6 and BALB/c substrains of mice.

Forward genetics is a powerful approach based on chromosomal mapping of phenotypes and has successfully led to the discovery of many mouse mutations in genes responsible for various phenotypes. Although crossing between genetically remote strains can produce F2 and backcross mice for chromosomal mapping, the phenotypes are often affected by background effects from the partner strains in genetic crosses. Genetic crosses between substrains might be useful in genetic mapping to avoid genetic background effects. In this study, we investigated single nucleotide polymorphisms (SNPs) available for genetic mapping using substrains of C57BL/6 and BALB/c mice. In C57BL/6 mice, 114 SNP markers were developed and assigned to locations on all chromosomes for full utilization for genetic mapping using genetic crosses between the C57BL/6J and C57BL/6N substrains. Moreover, genetic differences were identified in the 114 SNP markers among the seven C57BL/6 substrains from five production breeders. In addition, 106 SNPs were detected on all chromosomes of BALB/cAJcl and BALB/cByJJcl substrains. These SNPs could be used for genotyping in BALB/cJ, BALB/cAJcl, BALB/cAnNCrlCrlj, and BALB/cCrSlc mice, and they are particularly useful for genetic mapping using crosses between BALB/cByJJcl and other BALB/c substrains. The SNPs characterized in this study can be utilized for genetic mapping to identify the causative mutations of the phenotypes induced by N-ethyl-N-nitrosourea mutagenesis and the SNPs responsible for phenotypic differences between the substrains of C57BL/6 and BALB/c mice.

A community effort for COVID-19 Ontology Harmonization.

Ontologies have emerged to become critical to support data and knowledge representation, standardization, integration, and analysis. The SARS-CoV-2 pandemic led to the rapid proliferation of COVID-19 data, as well as the development of many COVID-19 ontologies. In the interest of supporting data interoperability, we initiated a community-based effort to harmonize COVID-19 ontologies. Our effort involves the collaborative discussion among developers of seven COVID-19 related ontologies, and the merging of four ontologies. This effort demonstrates the feasibility of harmonizing these ontologies in an interoperable framework to support integrative representation and analysis of COVID-19 related data and knowledge.

Mouse resources at the RIKEN BioResource Research Center and the National BioResource Project core facility in Japan.

The RIKEN BioResource Research Center (BRC) was established in 2001 as a comprehensive biological resource center in Japan. The Experimental Animal Division, one of the BRC infrastructure divisions, has been designated as the core facility for mouse resources within the National BioResource Project (NBRP) by the Japanese government since FY2002. Our activities regarding the collection, preservation, quality control, and distribution of mouse resources have been supported by the research community, including evaluations and guidance on advancing social and research needs, as well as the operations and future direction of the BRC. Expenditure for collection, preservation, and quality-control operations of the BRC, as a national core facility, has been funded by the government, while distribution has been separately funded by users' reimbursement fees. We have collected over 9000 strains created mainly by Japanese scientists including Nobel laureates and researchers in cutting-edge fields and distributed mice to 7000 scientists with 1500 organizations in Japan and globally. Our users have published 1000 outstanding papers and a few dozen patents. The collected mouse resources are accessible via the RIKEN BRC website, with a revised version of the searchable online catalog. In addition, to enhance the visibility of useful strains, we have launched web corners designated as the "Mouse of the Month" and "Today's Tool and Model." Only high-demand strains are maintained in live colonies, while other strains are cryopreserved as embryos or sperm to achieve cost-effective management. Since 2007, the RIKEN BRC has built up a back-up facility in the RIKEN Harima branch to protect the deposited strains from disasters. Our mice have been distributed with high quality through the application of strict microbial and genetic quality control programs that cover a globally accepted pathogens list and mutated alleles generated by various methods. Added value features, such as information about users' publications, standardized phenotyping data, and genome sequences of the collected strains, are important to facilitate the use of our resources. We have added and disseminated such information in collaboration with the NBRP Information Center and the NBRP Genome Information Upgrading Program. The RIKEN BRC has participated in international mouse resource networks such as the International Mouse Strain Resource, International Mouse Phenotyping Consortium, and Asian Mouse Mutagenesis and Resource Association to facilitate the worldwide use of high-quality mouse resources, and as a consequence it contributes to reproducible life science studies and innovation around the globe.

MoG+: a database of genomic variations across three mouse subspecies for biomedical research.

Laboratory mouse strains have mosaic genomes derived from at least three major subspecies that are distributed in Eurasia. Here, we describe genomic variations in ten inbred strains: Mus musculus musculus-derived BLG2/Ms, NJL/Ms, CHD/Ms, SWN/Ms, and KJR/Ms; M. m. domesticus-derived PGN2/Ms and BFM/Ms; M. m. castaneus-derived HMI/Ms; and JF1/Ms and MSM/Ms, which were derived from a hybrid between M. m. musculus and M. m. castaneus. These strains were established by Prof. Moriwaki in the 1980s and are collectively named the "Mishima Battery". These strains show large phenotypic variations in body size and in many physiological traits. We resequenced the genomes of the Mishima Battery strains and performed a comparative genomic analysis with dbSNP data. More than 81 million nucleotide coordinates were identified as variant sites due to the large genetic distances among the mouse subspecies; 8,062,070 new SNP sites were detected in this study, and these may underlie the large phenotypic diversity observed in the Mishima Battery. The new information was collected in a reconstructed genome database, termed MoG+ that includes new application software and viewers. MoG+ intuitively visualizes nucleotide variants in genes and intergenic regions, and amino acid substitutions across the three mouse subspecies. We report statistical data from the resequencing and comparative genomic analyses and newly collected phenotype data of the Mishima Battery, and provide a brief description of the functions of MoG+, which provides a searchable and unique data resource of the numerous genomic variations across the three mouse subspecies. The data in MoG+ will be invaluable for research into phenotype-genotype links in diverse mouse strains.

Integrated Collection of Stem Cell Bank Data, a Data Portal for Standardized Stem Cell Information.

The past decade has witnessed an extremely rapid increase in the number of newly established stem cell lines. However, due to the lack of a standardized format, data exchange among stem cell line resources has been challenging, and no system can search all stem cell lines across resources worldwide. To solve this problem, we have developed the Integrated Collection of Stem Cell Bank data (ICSCB) (http://icscb.stemcellinformatics.org/), the largest database search portal for stem cell line information, based on the standardized data items and terms of the MIACARM framework. Currently, ICSCB can retrieve >16,000 cell lines from four major data resources in Europe, Japan, and the United States. ICSCB is automatically updated to provide the latest cell line information, and its integrative search helps users collect cell line information for over 1,000 diseases, including many rare diseases worldwide, which has been a formidable task, thereby distinguishing itself from other database search portals.

Establishment and application of information resource of mutant mice in RIKEN BioResource Research Center.

Online databases are crucial infrastructures to facilitate the wide effective and efficient use of mouse mutant resources in life sciences. The number and types of mouse resources have been rapidly growing due to the development of genetic modification technology with associated information of genomic sequence and phenotypes. Therefore, data integration technologies to improve the findability, accessibility, interoperability, and reusability of mouse strain data becomes essential for mouse strain repositories. In 2020, the RIKEN BioResource Research Center released an integrated database of bioresources including, experimental mouse strains, Arabidopsis thaliana as a laboratory plant, cell lines, microorganisms, and genetic materials using Resource Description Framework-related technologies. The integrated database shows multiple advanced features for the dissemination of bioresource information. The current version of our online catalog of mouse strains which functions as a part of the integrated database of bioresources is available from search bars on the page of the Center ( https://brc.riken.jp ) and the Experimental Animal Division ( https://mus.brc.riken.jp/ ) websites. The BioResource Research Center also released a genomic variation database of mouse strains established in Japan and Western Europe, MoG+ ( https://molossinus.brc.riken.jp/mogplus/ ), and a database for phenotype-phenotype associations across the mouse phenome using data from the International Mouse Phenotyping Platform. In this review, we describe features of current version of databases related to mouse strain resources in RIKEN BioResource Research Center and discuss future views.

An atlas of evidence-based phenotypic associations across the mouse phenome.

To date, reliable relationships between mammalian phenotypes, based on diagnostic test measurements, have not been reported on a large scale. The purpose of this study was to present a large mouse phenotype-phenotype relationships dataset as a reference resource, alongside detailed evaluation of the resource. We used bias-minimized comprehensive mouse phenotype data and applied association rule mining to a dataset consisting of only binary (normal and abnormal phenotypes) data to determine relationships among phenotypes. We present 3,686 evidence-based significant associations, comprising 345 phenotypes covering 60 biological systems (functions), and evaluate their characteristics in detail. To evaluate the relationships, we defined a set of phenotype-phenotype association pairs (PPAPs) as a module of phenotypic expression for each of the 345 phenotypes. By analyzing each PPAP, we identified phenotype sub-networks consisting of the largest numbers of phenotypes and distinct biological systems. Furthermore, using hierarchical clustering based on phenotype similarities among the 345 PPAPs, we identified seven community types within a putative phenome-wide association network. Moreover, to promote leverage of these data, we developed and published web-application tools. These mouse phenome-wide phenotype-phenotype association data reveal general principles of relationships among mammalian phenotypes and provide a reference resource for biomedical analyses.

A new mouse model of GLUT1 deficiency syndrome exhibits abnormal sleep-wake patterns and alterations of glucose kinetics in the brain.

Dysfunction of glucose transporter 1 (GLUT1) proteins causes infantile epilepsy, which is designated as a GLUT1 deficiency syndrome (GLUT1DS; OMIM #606777). Patients with GLUT1DS display varied clinical phenotypes, such as infantile seizures, ataxia, severe mental retardation with learning disabilities, delayed development, hypoglycorrhachia, and other varied symptoms. Glut1Rgsc200 mutant mice mutagenized with N-ethyl-N-nitrosourea (ENU) carry a missense mutation in the Glut1 gene that results in amino acid substitution at the 324th residue of the GLUT1 protein. In this study, these mutants exhibited various phenotypes, including embryonic lethality of homozygotes, a decreased cerebrospinal-fluid glucose value, deficits in contextual learning, a reduction in body size, seizure-like behavior and abnormal electroencephalogram (EEG) patterns. During EEG recording, the abnormality occurred spontaneously, whereas the seizure-like phenotypes were not observed at the same time. In sleep-wake analysis using EEG recording, heterozygotes exhibited a longer duration of wake times and shorter duration of non-rapid eye movement (NREM) sleep time. The shortened period of NREM sleep and prolonged duration of the wake period may resemble the sleep disturbances commonly observed in patients with GLUT1DS and other epilepsy disorders. Interestingly, an in vivo kinetic analysis of glucose utilization by positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-D-glucose imaging revealed that glucose transportation was reduced, whereas hexokinase activity and glucose metabolism were enhanced. These results indicate that a Glut1Rgsc200 mutant is a useful tool for elucidating the molecular mechanisms of GLUT1DS.This article has an associated First Person interview with the joint first authors of the paper.

Identification of genetic elements in metabolism by high-throughput mouse phenotyping.

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome.

Prevalence of sexual dimorphism in mammalian phenotypic traits.

The role of sex in biomedical studies has often been overlooked, despite evidence of sexually dimorphic effects in some biological studies. Here, we used high-throughput phenotype data from 14,250 wildtype and 40,192 mutant mice (representing 2,186 knockout lines), analysed for up to 234 traits, and found a large proportion of mammalian traits both in wildtype and mutants are influenced by sex. This result has implications for interpreting disease phenotypes in animal models and humans.

Endoplasmic reticulum stress-mediated apoptosis contributes to a skeletal dysplasia resembling platyspondylic lethal skeletal dysplasia, Torrance type, in a novel Col2a1 mutant mouse line.

In humans, mutations in the COL2A1 gene encoding the α1(II) chain of type II collagen, create many clinical phenotypes collectively termed type II collagenopathies. However, the mechanisms generating this diversity remain to be determined. Here we identified a novel Col2a1 mutant mouse line by screening a large-scale N-ethyl-N-nitrosourea mutant mouse library. This mutant possessed a p.Tyr1391Ser missense mutation in the C-propeptide coding region, and this mutation was located in positions corresponding to the human COL2A1 mutation responsible for platyspondylic lethal skeletal dysplasia, Torrance type (PLSD-T). As expected, p.Tyr1391Ser homozygotes exhibited lethal skeletal dysplasias resembling PLSD-T, including extremely short limbs and severe dysplasia of the spine and pelvis. The secretion of the mutant proteins into the extracellular space was disrupted, accompanied by an abnormally expanded endoplasmic reticulum (ER) and the up-regulation of ER stress-related genes in chondrocytes. Chondrocyte apoptosis was severely induced in the growth plate of the homozygotes. These findings strongly suggest that ER stress-mediated apoptosis caused by the accumulated mutant proteins in ER contributes to skeletal dysplasia in Co12a1 mutant mice and PLSD-T patients.

Principles and application of LIMS in mouse clinics.

Large-scale systemic mouse phenotyping, as performed by mouse clinics for more than a decade, requires thousands of mice from a multitude of different mutant lines to be bred, individually tracked and subjected to phenotyping procedures according to a standardised schedule. All these efforts are typically organised in overlapping projects, running in parallel. In terms of logistics, data capture, data analysis, result visualisation and reporting, new challenges have emerged from such projects. These challenges could hardly be met with traditional methods such as pen & paper colony management, spreadsheet-based data management and manual data analysis. Hence, different Laboratory Information Management Systems (LIMS) have been developed in mouse clinics to facilitate or even enable mouse and data management in the described order of magnitude. This review shows that general principles of LIMS can be empirically deduced from LIMS used by different mouse clinics, although these have evolved differently. Supported by LIMS descriptions and lessons learned from seven mouse clinics, this review also shows that the unique LIMS environment in a particular facility strongly influences strategic LIMS decisions and LIMS development. As a major conclusion, this review states that there is no universal LIMS for the mouse research domain that fits all requirements. Still, empirically deduced general LIMS principles can serve as a master decision support template, which is provided as a hands-on tool for mouse research facilities looking for a LIMS.

Applying the ARRIVE Guidelines to an In Vivo Database.

The Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines were developed to address the lack of reproducibility in biomedical animal studies and improve the communication of research findings. While intended to guide the preparation of peer-reviewed manuscripts, the principles of transparent reporting are also fundamental for in vivo databases. Here, we describe the benefits and challenges of applying the guidelines for the International Mouse Phenotyping Consortium (IMPC), whose goal is to produce and phenotype 20,000 knockout mouse strains in a reproducible manner across ten research centres. In addition to ensuring the transparency and reproducibility of the IMPC, the solutions to the challenges of applying the ARRIVE guidelines in the context of IMPC will provide a resource to help guide similar initiatives in the future.