Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse

Whole-exome sequencing reveals sex difference in the genetic architecture of high myopia

BACKGROUND

High myopia (HM) is one of the leading causes of visual impairment and blindness worldwide. To understand the sex difference in the genetic architecture of HM, which may contribute to understanding HM aetiology and help further the realisation of precision medicine for HM.

METHODS

We performed sex-stratified exome-wide association studies (ExWAS) with n (males)=7492 and n (females)=8090, along with gene- and pathway-based tests and genetic correlation analyses to clarify the variants, genes and molecular pathways that relate to HM in a sex-specific manner.

RESULTS

In our ExWAS, we identified that a male-specific gene, CHRNB1 (Zfemales=1.382, Pfemales=0.083; Zmales=4.029, Pmales=2.80×10-05; Pdifference=0.003), was associated with higher risk scores of HM in males than in females. Rare variant burden tests showed a significant excess of rare protein-truncating variants among HM males in CHRNB1-related pathways, including cell-cell signalling and muscle structure development. Sex-based differences in gene expression within CHRNB1-enriched ciliary body cells were observed; specifically, increased expression of mitochondrial metabolism-related genes in males and antioxidant genes in females. Functional differences in mitochondrial metabolism were confirmed in male-derived H1 and female-derived H9 human embryonic stem cell lines, with H1 cells specifically exhibiting significant dysregulation of mitochondrial organisation and mitochondrial respiratory chain complex assembly after CHRNB1 knockdown.

CONCLUSION

Together, our study provides insight into the sex differences in the genetic architecture of HM and highlights CHRNB1's role in HM pathogenesis in males.

Phenogenomic resources immortalized in a panel of wild-derived strains of five species of house mice

The house mouse, Mus musculus, is a widely used animal model in biomedical research, with classical laboratory strains (CLS) being the most frequently employed. However, the limited genetic variability in CLS hinders their applicability in evolutionary studies. Wild-derived strains (WDS), on the other hand, provide a suitable resource for such investigations. This study quantifies genetic and phenotypic data of 101 WDS representing 5 species, 3 subspecies, and 8 natural Y consomic strains and compares them with CLS. Genetic variability was estimated using whole mtDNA sequences, the Prdm9 gene, and copy number variation at two sex chromosome-linked genes. WDS exhibit a large natural variation with up to 2173 polymorphic sites in mitogenomes, whereas CLS display 92 sites. Moreover, while CLS have two Prdm9 alleles, WDS harbour 46 different alleles. Although CLS resemble M. m. domesticus and M. m. musculus WDS, they differ from them in 10 and 14 out of 16 phenotypic traits, respectively. The results suggest that WDS can be a useful tool in evolutionary and biomedical studies with great potential for medical applications.

Comprehensive prediction and analysis of human protein essentiality based on a pretrained large language model

Human essential proteins (HEPs) are indispensable for individual viability and development. However, experimental methods to identify HEPs are often costly, time consuming and labor intensive. In addition, existing computational methods predict HEPs only at the cell line level, but HEPs vary across living human, cell line and animal models. Here we develop a sequence-based deep learning model, Protein Importance Calculator (PIC), by fine-tuning a pretrained protein language model. PIC not only substantially outperforms existing methods for predicting HEPs but also provides comprehensive prediction results across three levels: human, cell line and mouse. Furthermore, we define the protein essential score, derived from PIC, to quantify human protein essentiality and validate its effectiveness by a series of biological analyses. We also demonstrate the biomedical value of the protein essential score by identifying potential prognostic biomarkers for breast cancer and quantifying the essentiality of 617,462 human microproteins.

Detection of chimeric alpha-defensin transcripts and peptides in mouse Paneth cells

Introduction

In mammals, Paneth cells, located in the crypts of the small intestine, produceantimicrobial peptides that serve to keep the intestinal microbiome under control. a-Defensins are the primary antimicrobial peptides produced by these cells.

Methods

We used 148 publicly available bulk RNA-seq samples on purified PCs, proteomics on enriched purified PC proteins and Defa peptide activity assays to detect all Defa transcrips, including potential chimeric transcrips.

Results

We identified 28 expressed Defa genes in mice, with up to 85% of Paneth cell RNA reads mapping to these genes. Chimeric mRNAs, involving sequences from two different Defa genes, were detected in most experiments. Despite their low abundance (less than 0.3%), mass spectrometry confirmed the presence of chimeric peptides. Synthetic versions of these peptides demonstrated antibacterial activity against multiple bacterial species.

Conclusion

We show the existence of chimeric Defa transcripts and peptides in mice that are biologically active. We propose a possible stochatic mechanism or that the activation of the UPR patway may play a role in their production.

Essential resources and best practices for laboratory mouse research

The laboratory mouse (Mus musculus) is the most widely used mammalian model organism in biomedical and life science research. This concise guide aims to provide essential information to assist researchers new to working with mice, covering topics such as mouse husbandry, maintenance, and available resources for obtaining mouse strains and associated data. Additionally, we discuss ethical considerations, emphasizing the 3Rs (replacement, reduction, and refinement) to ensure responsible and humane research practices.

The Role of de novo and Ultra-Rare Variants in Hirschsprung Disease (HSCR): Extended Gene Discovery for Risk Profiling of Patients

Background

Hirschsprung disease (HSCR) is a rare neurodevelopmental disorder caused by disrupted migration and proliferation of enteric neural crest cells during enteric nervous system development. Genetic studies suggest a complex etiology involving both rare and common variants, but the contribution of ultra-rare pathogenic variants (PAs) remains poorly understood.

Methods

We perform whole-exome sequencing (WES) on 301 HSCR probands and 109 family trios, employing advanced statistical methods and gene prioritization strategies to identify genes carrying de novo and ultra-rare coding pathogenic variants. Multiple study designs, including case-control, de novo mutation analysis and joint test, are used to detect associated genes. Candidate genes are further prioritized based on their biological and functional relevance to disease associated tissues and onset period (i.e., human embryonic colon).

Results

We identify 19 risk genes enriched with ultra-rare coding pathogenic variants in HSCR probands, including four known genes (RET, EDNRB, ZEB2, SOX10) and 15 novel candidates (e.g., COLQ, NES, FAT3) functioning in neural proliferation and neuromuscular synaptic development. These genes account for 17.5% of the population-attributable risk (PAR), with novel candidates contributing 6.5%. Notably, a positive correlation between pathogenic mutational burden and disease severity is observed. Female cases exhibit at least 42% higher ultra-rare pathogenic variant burden than males (P = 0.05).

Conclusions

This first-ever genome-wide screen of ultra-rare variants in a large, phenotypically diverse HSCR cohort highlights the substantial contribution of ultra-rare pathogenic variants to the disease risk and phenotypic variability. These findings enhance our understanding of the genetic architecture of HSCR and provide potential targets for genetic screening and personalized interventions.

Etrinabdione (VCE-004.8), a B55α activator, promotes angiogenesis and arteriogenesis in critical limb ischemia

BACKGROUND

Vasculogenic therapies explored for the treatment of peripheral artery disease (PAD) have encountered minimal success in clinical trials. Addressing this, B55α, an isoform of protein phosphatase 2A (PP2A), emerges as pivotal in vessel remodeling through activation of hypoxia-inducible factor 1α (HIF-1α). This study delves into the pharmacological profile of VCE-004.8 (Etrinabdione) and evaluates its efficacy in a preclinical model of critical limb ischemia, with a focus on its potential as a PP2A/B55α activator to induce angiogenesis and arteriogenesis.

METHODS

Vascular endothelial cells were used for in vitro experiments. Aorta ring assay was performed to explore sprouting activity. Matrigel plug-in assay was used to assess the angiogenic potential. Critical limb ischemia (CLI) in mice was induced by double ligation in the femoral arteria. Endothelial vascular and fibrotic biomarkers were studied by immunohistochemistry and qPCR. Arteriogenesis was investigated by microvascular casting and micro-CT. Proteomic analysis in vascular tissues was analyzed by LC-MS/MS. Ex-vivo expression of B55α and biomarkers were investigated in artery samples from PAD patients.

RESULTS

VCE-004.8 exhibited the ability to induce B55α expression and activate the intersecting pathways B55α/AMPK/Sirtuin 1/eNOS and B55α/PHD2/HIF-1α. VCE-004.8 prevented OxLDL and H2O2-induced cytotoxicity, senescence, and inflammation in endothelial cells. Oral VCE-004.8 increased aorta sprouting in vitro and angiogenesis in vivo. In CLI mice VCE-004.8 improved collateral vessel formation and induced endothelial cells proliferation, angiogenic gene expression and prevented fibrosis. The expression of B55α, Caveolin 1 and Sirtuin-1 is reduced in arteries from CLI mice and PAD patient, and the expression of these markers was restored in mice treated with VCE-004.8.

CONCLUSIONS

The findings presented in this study indicate that Etrinabdione holds promise in mitigating endothelial cell damage and senescence, while concurrently fostering arteriogenesis and angiogenesis. These observations position Etrinabdione as a compelling candidate for the treatment of PAD, and potentially other cardiovascular disorders.

RummaGEO: Automatic mining of human and mouse gene sets from GEO

The Gene Expression Omnibus (GEO) has millions of samples from thousands of studies. While users of GEO can search the metadata describing studies, there is a need for methods to search GEO at the data level. RummaGEO is a gene expression signature search engine for human and mouse RNA sequencing perturbation studies extracted from GEO. To develop RummaGEO, we automatically identified groups of samples and computed differential expressions to extract gene sets from each study. The contents of RummaGEO are served for gene set, PubMed, and metadata search. Next, we analyzed the contents of RummaGEO to identify patterns and perform global analyses. Overall, RummaGEO provides a resource that is enabling users to identify relevant GEO studies based on their own gene expression results. Users of RummaGEO can incorporate RummaGEO into their analysis workflows for integrative analyses and hypothesis generation.

Associating transcription factors to single-cell trajectories with DREAMIT

Inferring gene regulatory networks from single-cell RNA-sequencing trajectories has been an active area of research yet methods are still needed to identify regulators governing cell transitions. We developed DREAMIT (Dynamic Regulation of Expression Across Modules in Inferred Trajectories) to annotate transcription-factor activity along single-cell trajectory branches, using ensembles of relations to target genes. Using a benchmark representing several different tissues, as well as external validation with ATAC-Seq and Perturb-Seq data on hematopoietic cells, the method was found to have higher tissue-specific sensitivity and specificity over competing approaches.

CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data

Transcriptomic analysis across species is increasingly used to reveal conserved gene regulations which implicate crucial regulators. Cross-species analysis of single-cell RNA sequencing (scRNA-seq) data provides new opportunities to identify the cellular and molecular conservations, especially for cell types and cell type-specific gene regulations. However, few methods have been developed to analyze cross-species scRNA-seq data to uncover both molecular and cellular conservations. Here, we built a tool called CACIMAR, which can perform cross-species analysis of cell identities, markers, regulations, and interactions using scRNA-seq profiles. Based on the weighted sum models of the conserved features, we developed different conservation scores to measure the conservation of cell types, regulatory networks, and intercellular interactions. Using publicly available scRNA-seq data on retinal regeneration in mice, zebrafish, and chick, we demonstrated four main functions of CACIMAR. First, CACIMAR allows to identify conserved cell types even in evolutionarily distant species. Second, the tool facilitates the identification of evolutionarily conserved or species-specific marker genes. Third, CACIMAR enables the identification of conserved intracellular regulations, including cell type-specific regulatory subnetworks and regulators. Lastly, CACIMAR provides a unique feature for identifying conserved intercellular interactions. Overall, CACIMAR facilitates the identification of evolutionarily conserved cell types, marker genes, intracellular regulations, and intercellular interactions, providing insights into the cellular and molecular mechanisms of species evolution.

Phenome-wide identification of therapeutic genetic targets, leveraging knowledge graphs, graph neural networks, and UK Biobank data

The ongoing expansion of human genomic datasets propels therapeutic target identification; however, extracting gene-disease associations from gene annotations remains challenging. Here, we introduce Mantis-ML 2.0, a framework integrating AstraZeneca's Biological Insights Knowledge Graph and numerous tabular datasets, to assess gene-disease probabilities throughout the phenome. We use graph neural networks, capturing the graph's holistic structure, and train them on hundreds of balanced datasets via a robust semi-supervised learning framework to provide gene-disease probabilities across the human exome. Mantis-ML 2.0 incorporates natural language processing to automate disease-relevant feature selection for thousands of diseases. The enhanced models demonstrate a 6.9% average classification power boost, achieving a median receiver operating characteristic (ROC) area under curve (AUC) score of 0.90 across 5220 diseases from Human Phenotype Ontology, OpenTargets, and Genomics England. Notably, Mantis-ML 2.0 prioritizes associations from an independent UK Biobank phenome-wide association study (PheWAS), providing a stronger form of triaging and mitigating against underpowered PheWAS associations. Results are exposed through an interactive web resource.

A review of animal models utilized in preclinical studies of approved gene therapy products: trends and insights

Scientific progress heavily relies on rigorous research, adherence to scientific standards, and transparent reporting. Animal models play a crucial role in advancing biomedical research, especially in the field of gene therapy. Animal models are vital tools in preclinical research, allowing scientists to predict outcomes and understand complex biological processes. The selection of appropriate animal models is critical, considering factors such as physiological and pathophysiological similarities, availability, and ethical considerations. Animal models continue to be indispensable tools in preclinical gene therapy research. Advancements in genetic engineering and model selection have improved the fidelity and relevance of these models. As gene therapy research progresses, careful consideration of animal models and transparent reporting will contribute to the development of effective therapies for various genetic disorders and diseases. This comprehensive review explores the use of animal models in preclinical gene therapy studies for approved products up to September 2023. The study encompasses 47 approved gene therapy products, with a focus on preclinical trials. This comprehensive analysis serves as a valuable reference for researchers in the gene therapy field, aiding in the selection of suitable animal models for their preclinical investigations.

BioKA: a curated and integrated biomarker knowledgebase for animals

Biomarkers play an important role in various area such as personalized medicine, drug development, clinical care, and molecule breeding. However, existing animals' biomarker resources predominantly focus on human diseases, leaving a significant gap in non-human animal disease understanding and breeding research. To address this limitation, we present BioKA (Biomarker Knowledgebase for Animals, https://ngdc.cncb.ac.cn/bioka), a curated and integrated knowledgebase encompassing multiple animal species, diseases/traits, and annotated resources. Currently, BioKA houses 16 296 biomarkers associated with 951 mapped diseases/traits across 31 species from 4747 references, including 11 925 gene/protein biomarkers, 1784 miRNA biomarkers, 1043 mutation biomarkers, 773 metabolic biomarkers, 357 circRNA biomarkers and 127 lncRNA biomarkers. Furthermore, BioKA integrates various annotations such as GOs, protein structures, protein-protein interaction networks, miRNA targets and so on, and constructs an interactive knowledge network of biomarkers including circRNA-miRNA-mRNA associations, lncRNA-miRNA associations and protein-protein associations, which is convenient for efficient data exploration. Moreover, BioKA provides detailed information on 308 breeds/strains of 13 species, and homologous annotations for 8784 biomarkers across 16 species, and offers three online application tools. The comprehensive knowledge provided by BioKA not only advances human disease research but also contributes to a deeper understanding of animal diseases and supports livestock breeding.

A comprehensive review of the data and knowledge graphs approaches in bioinformatics

The scientific community is currently showing strong interest in constructing knowledge graphs from heterogeneous domains (genomic, pharmaceutical, clinical etc.). The main goal here is to support researchers in gaining an immediate overview of the biomedical and clinical data that can be utilized to construct and extend KGs. A in-depth overview of the available biomedical data and the latest applications of knowledge graphs, from the biological to the clinical context, is provided showing the most recent methods of representing biomedical knowledge with embeddings (KGEs). Furthermore, this review, differentiates biomedical databases based on their construction process (whether manually curated by experts or not), aiming to offer a detailed overview and guide researchers in selecting the appropriate database for their research considering to the specific project needs, available resources, and data complexity. In conclusion, the review highlights current challenges: integration of different knowledge graphs and the interpretability of predictions of new relations.

D2H2: diabetes data and hypothesis hub

Motivation

There is a rapid growth in the production of omics datasets collected by the diabetes research community. However, such published data are underutilized for knowledge discovery. To make bioinformatics tools and published omics datasets from the diabetes field more accessible to biomedical researchers, we developed the Diabetes Data and Hypothesis Hub (D2H2).

Results

D2H2 contains hundreds of high-quality curated transcriptomics datasets relevant to diabetes, accessible via a user-friendly web-based portal. The collected and processed datasets are curated from the Gene Expression Omnibus (GEO). Each curated study has a dedicated page that provides data visualization, differential gene expression analysis, and single-gene queries. To enable the investigation of these curated datasets and to provide easy access to bioinformatics tools that serve gene and gene set-related knowledge, we developed the D2H2 chatbot. Utilizing GPT, we prompt users to enter free text about their data analysis needs. Parsing the user prompt, together with specifying information about all D2H2 available tools and workflows, we answer user queries by invoking the most relevant tools via the tools' API. D2H2 also has a hypotheses generation module where gene sets are randomly selected from the bulk RNA-seq precomputed signatures. We then find highly overlapping gene sets extracted from publications listed in PubMed Central with abstract dissimilarity. With the help of GPT, we speculate about a possible explanation of the high overlap between the gene sets. Overall, D2H2 is a platform that provides a suite of bioinformatics tools and curated transcriptomics datasets for hypothesis generation.

Availability and implementation

D2H2 is available at: https://d2h2.maayanlab.cloud/ and the source code is available from GitHub at https://github.com/MaayanLab/D2H2-site under the CC BY-NC 4.0 license.

Differential Correlation of Transcriptome Data Reveals Gene Pairs and Pathways Involved in Treatment of Citrobacter rodentium Infection with Bioactive Punicalagin

This study is part of the work investigating bioactive fruit enzymes as sustainable alternatives to parasite anthelmintics that can help reverse the trend of lost efficacy. The study looked to define biological and molecular interactions that demonstrate the ability of the pomegranate extract punicalagin against intracellular parasites. The study compared transcriptomic reads of two distinct conditions. Condition A was treated with punicalagin (PA) and challenged with Citrobacter rodentium, while condition B (CM) consisted of a group that was challenged and given mock treatment of PBS. To understand the effect of punicalagin on transcriptomic changes between conditions, a differential correlation analysis was conducted. The analysis examined the regulatory connections of genes expressed between different treatment conditions by statistically querying the relationship between correlated gene pairs and modules in differing conditions. The results indicated that punicalagin treatment had strong positive correlations with the over-enriched gene ontology (GO) terms related to oxidoreductase activity and lipid metabolism. However, the GO terms for immune and cytokine responses were strongly correlated with no punicalagin treatment. The results matched previous studies that showed punicalagin to have potent antioxidant and antiparasitic effects when used to treat parasitic infections in mice and livestock. Overall, the results indicated that punicalagin enhanced the effect of tissue-resident genes.

A physiologically based model of bile acid metabolism in mice

Bile acid (BA) metabolism is a complex system that includes a wide variety of primary and secondary, as well as conjugated and unconjugated BAs that undergo continuous enterohepatic circulation (EHC). Alterations in both composition and dynamics of BAs have been associated with various diseases. However, a mechanistic understanding of the relationship between altered BA metabolism and related diseases is lacking. Computational modeling may support functional analyses of the physiological processes involved in the EHC of BAs along the gut-liver axis. In this study, we developed a physiologically based model of murine BA metabolism describing synthesis, hepatic and microbial transformations, systemic distribution, excretion, and EHC of BAs at the whole-body level. For model development, BA metabolism of specific pathogen-free (SPF) mice was characterized in vivo by measuring BA levels and composition in various organs, expression of transporters along the gut, and cecal microbiota composition. We found significantly different BA levels between male and female mice that could only be explained by adjusted expression of the hepatic enzymes and transporters in the model. Of note, this finding was in agreement with experimental observations. The model for SPF mice could also describe equivalent experimental data in germ-free mice by specifically switching off microbial activity in the intestine. The here presented model can therefore facilitate and guide functional analyses of BA metabolism in mice, e.g., the effect of pathophysiological alterations on BA metabolism and translation of results from mouse studies to a clinically relevant context through cross-species extrapolation.

Capturing heart valve development with Gene Ontology

Introduction: The normal development of all heart valves requires highly coordinated signaling pathways and downstream mediators. While genomic variants can be responsible for congenital valve disease, environmental factors can also play a role. Later in life valve calcification is a leading cause of aortic valve stenosis, a progressive disease that may lead to heart failure. Current research into the causes of both congenital valve diseases and valve calcification is using a variety of high-throughput methodologies, including transcriptomics, proteomics and genomics. High quality genetic data from biological knowledge bases are essential to facilitate analyses and interpretation of these high-throughput datasets. The Gene Ontology (GO, http://geneontology.org/) is a major bioinformatics resource used to interpret these datasets, as it provides structured, computable knowledge describing the role of gene products across all organisms. The UCL Functional Gene Annotation team focuses on GO annotation of human gene products. Having identified that the GO annotations included in transcriptomic, proteomic and genomic data did not provide sufficient descriptive information about heart valve development, we initiated a focused project to address this issue. Methods: This project prioritized 138 proteins for GO annotation, which led to the curation of 100 peer-reviewed articles and the creation of 400 heart valve development-relevant GO annotations. Results: While the focus of this project was heart valve development, around 600 of the 1000 annotations created described the broader cellular role of these proteins, including those describing aortic valve morphogenesis, BMP signaling and endocardial cushion development. Our functional enrichment analysis of the 28 proteins known to have a role in bicuspid aortic valve disease confirmed that this annotation project has led to an improved interpretation of a heart valve genetic dataset. Discussion: To address the needs of the heart valve research community this project has provided GO annotations to describe the specific roles of key proteins involved in heart valve development. The breadth of GO annotations created by this project will benefit many of those seeking to interpret a wide range of cardiovascular genomic, transcriptomic, proteomic and metabolomic datasets.

DapBCH: a disease association prediction model Based on Cross-species and Heterogeneous graph embedding

The study of comorbidity can provide new insights into the pathogenesis of the disease and has important economic significance in the clinical evaluation of treatment difficulty, medical expenses, length of stay, and prognosis of the disease. In this paper, we propose a disease association prediction model DapBCH, which constructs a cross-species biological network and applies heterogeneous graph embedding to predict disease association. First, we combine the human disease-gene network, mouse gene-phenotype network, human-mouse homologous gene network, and human protein-protein interaction network to reconstruct a heterogeneous biological network. Second, we apply heterogeneous graph embedding based on meta-path aggregation to generate the feature vector of disease nodes. Finally, we employ link prediction to obtain the similarity of disease pairs. The experimental results indicate that our model is highly competitive in predicting the disease association and is promising for finding potential disease associations.

Meta-Analysis of Heat-Stressed Transcriptomes Using the Public Gene Expression Database from Human and Mouse Samples

Climate change has significantly increased the frequency of our exposure to heat, adversely affecting human health and industries. Heat stress is an environmental stress defined as the exposure of organisms and cells to abnormally high temperatures. To comprehensively explain the mechanisms underlying an organism's response to heat stress, it is essential to investigate and analyze genes that have been under-represented or less well-known in previous studies. In this study, we analyzed heat stress-responsive genes using a meta-analysis of numerous gene expression datasets from the public database. We obtained 322 human and 242 mouse pairs as the heat exposure and control data. The meta-analysis of these data identified 76 upregulated and 37 downregulated genes common to both humans and mice. We performed enrichment, protein-protein interaction network, and transcription factor target gene analyses for these genes. Furthermore, we conducted an integrated analysis of these genes using publicly available chromatin immunoprecipitation sequencing (ChIP-seq) data for HSF1, HSF2, and PPARGC1A (PGC-1α) as well as gene2pubmed data from the existing literature. The results identified previously overlooked genes, such as ABHD3, ZFAND2A, and USPL1, as commonly upregulated genes. Further functional analysis of these genes can contribute to coping with climate change and potentially lead to technological advancements.

Sequencing of 19,219 exomes identifies a low-frequency variant in FKBP5 promoter predisposing to high myopia in a Han Chinese population

High myopia (HM) is one of the leading causes of visual impairment and blindness worldwide. Here, we report a whole-exome sequencing (WES) study in 9,613 HM cases and 9,606 controls of Han Chinese ancestry to pinpoint HM-associated risk variants. Single-variant association analysis identified three newly identified -genetic loci associated with HM, including an East Asian ancestry-specific low-frequency variant (rs533280354) in FKBP5. Multi-ancestry meta-analysis with WES data of 2,696 HM cases and 7,186 controls of European ancestry from the UK Biobank discerned a newly identified European ancestry-specific rare variant in FOLH1. Functional experiments revealed a mechanism whereby a single G-to-A transition at rs533280354 disrupted the binding of transcription activator KLF15 to the promoter of FKBP5, resulting in decreased transcription of FKBP5. Furthermore, burden tests showed a significant excess of rare protein-truncating variants among HM cases involved in retinal blood vessel morphogenesis and neurotransmitter transport.

The rearing environment persistently modulates mouse phenotypes from the molecular to the behavioural level

The phenotype of an organism results from its genotype and the influence of the environment throughout development. Even when using animals of the same genotype, independent studies may test animals of different phenotypes, resulting in poor replicability due to genotype-by-environment interactions. Thus, genetically defined strains of mice may respond differently to experimental treatments depending on their rearing environment. However, the extent of such phenotypic plasticity and its implications for the replicability of research findings have remained unknown. Here, we examined the extent to which common environmental differences between animal facilities modulate the phenotype of genetically homogeneous (inbred) mice. We conducted a comprehensive multicentre study, whereby inbred C57BL/6J mice from a single breeding cohort were allocated to and reared in 5 different animal facilities throughout early life and adolescence, before being transported to a single test laboratory. We found persistent effects of the rearing facility on the composition and heterogeneity of the gut microbial community. These effects were paralleled by persistent differences in body weight and in the behavioural phenotype of the mice. Furthermore, we show that environmental variation among animal facilities is strong enough to influence epigenetic patterns in neurons at the level of chromatin organisation. We detected changes in chromatin organisation in the regulatory regions of genes involved in nucleosome assembly, neuronal differentiation, synaptic plasticity, and regulation of behaviour. Our findings demonstrate that common environmental differences between animal facilities may produce facility-specific phenotypes, from the molecular to the behavioural level. Furthermore, they highlight an important limitation of inferences from single-laboratory studies and thus argue that study designs should take environmental background into account to increase the robustness and replicability of findings.

The phenotype of an organism results not only from its genotype but also the influence of its environment throughout development. This study shows that common environmental differences between animal facilities can induce substantial variation in the phenotype of mice, thereby highlighting an important limitation of inferences from single-laboratory studies in animal research.

Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes

To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance (P < 2.5 × 10-6), including five new risk genes (NAV3, ITSN1, MARK2, SCAF1 and HNRNPUL2). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes (NAV3, ITSN1, SCAF1 and HNRNPUL2; n = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes (CHD8, SCN2A, ADNP, FOXP1 and SHANK3) (59% vs 88%, P = 1.9 × 10-6). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes.

Rap1 controls epiblast morphogenesis in sync with the pluripotency states transition

The complex architecture of the murine fetus originates from a simple ball of pluripotent epiblast cells, which initiate morphogenesis upon implantation. In turn, this establishes an intermediate state of tissue-scale organization of the embryonic lineage in the form of an epithelial monolayer, where patterning signals delineate the body plan. However, how this major morphogenetic process is orchestrated on a cellular level and synchronized with the developmental progression of the epiblast is still obscure. Here, we identified that the small GTPase Rap1 plays a critical role in reshaping the pluripotent lineage. We found that Rap1 activity is controlled via Oct4/Esrrb input and is required for the transmission of polarization cues, which enables the de novo epithelialization and formation of tricellular junctions in the epiblast. Thus, Rap1 acts as a molecular switch that coordinates the morphogenetic program in the embryonic lineage, in sync with the cellular states of pluripotency.

GlioMarker: An integrated database for knowledge exploration of diagnostic biomarkers in gliomas

Gliomas are the most frequent malignant and aggressive tumors in the central nervous system. Early and effective diagnosis of glioma using diagnostic biomarkers can prolong patients' lives and aid in the development of new personalized treatments. Therefore, a thorough and comprehensive understanding of the diagnostic biomarkers in gliomas is of great significance. To this end, we developed the integrated and web-based database GlioMarker (http://gliomarker.prophetdb.org/), the first comprehensive database for knowledge exploration of glioma diagnostic biomarkers. In GlioMarker, accurate information on 406 glioma diagnostic biomarkers from 1559 publications was manually extracted, including biomarker descriptions, clinical information, associated literature, experimental records, associated diseases, statistical indicators, etc. Importantly, we integrated many external resources to provide clinicians and researchers with the capability to further explore knowledge on these diagnostic biomarkers based on three aspects. (1) Obtain more ontology annotations of the biomarker. (2) Identify the relationship between any two or more components of diseases, drugs, genes, and variants to explore the knowledge related to precision medicine. (3) Explore the clinical application value of a specific diagnostic biomarker through online analysis of genomic and expression data from glioma cohort studies. GlioMarker provides a powerful, practical, and user-friendly web-based tool that may serve as a specialized platform for clinicians and researchers by providing rapid and comprehensive knowledge of glioma diagnostic biomarkers to subsequently facilitates high-quality research and applications.

Calpains as mechanistic drivers and therapeutic targets for ocular disease

Ophthalmic neurodegenerative diseases encompass a wide array of molecular pathologies unified by calpain dysregulation. Calpains are calcium-dependent proteases that perpetuate cellular death and inflammation when hyperactivated. Calpain inhibition trials in other organs have faced pharmacological challenges, but the eye offers many advantages for the development and testing of targeted molecular therapeutics, including small molecules, peptides, engineered proteins, drug implants, and gene-based therapies. This review highlights structural mechanisms underlying calpain activation, distinct cellular expression patterns, and in vivo models that link calpain hyperactivity to human retinal and developmental disease. Optimizing therapeutic approaches for calpain-mediated eye diseases can help accelerate clinically feasible strategies for treating calpain dysregulation in other diseased tissues.

New Insights on Gene by Environmental Effects of Drugs of Abuse in Animal Models Using GeneNetwork

Gene-by-environment interactions are important for all facets of biology, especially behaviour. Families of isogenic strains of mice, such as the BXD strains, are excellently placed to study these interactions, as the same genome can be tested in multiple environments. BXD strains are recombinant inbred mouse strains derived from crossing two inbred strains—C57BL/6J and DBA/2J mice. Many reproducible genometypes can be leveraged, and old data can be reanalysed with new tools to produce novel insights. We obtained drug and behavioural phenotypes from Philip et al. Genes, Brain and Behaviour 2010, and reanalysed their data with new genotypes from sequencing, as well as new models (Genome-wide Efficient Mixed Model Association (GEMMA) and R/qtl2). We discovered QTLs on chromosomes 3, 5, 9, 11, and 14, not found in the original study. We reduced the candidate genes based on their ability to alter gene expression or protein function. Candidate genes included Slitrk6 and Cdk14. Slitrk6, in a Chromosome14 QTL for locomotion, was found to be part of a co-expression network involved in voluntary movement and associated with neuropsychiatric phenotypes. Cdk14, one of only three genes in a Chromosome5 QTL, is associated with handling induced convulsions after ethanol treatment, that is regulated by the anticonvulsant drug valproic acid. By using families of isogenic strains, we can reanalyse data to discover novel candidate genes involved in response to drugs of abuse.

Increased risk of internal tumors in DNA repair-deficient xeroderma pigmentosum patients: analysis of four international cohorts

Background

Xeroderma pigmentosum (XP) is a rare, autosomal, recessive DNA repair-deficiency disorder with a frequency of 1–3 per million livebirths in Europe and USA but with higher frequencies in isolated islands or in countries with a high level of consanguinity. XP is characterized by high incidence of skin cancers on sun-exposed sites. Recent improvement in life expectancy of XP patients suggests an increased risk of frequently aggressive and lethal internal tumors. Our purpose was to quantify relative risks of internal tumor development for XP patients by tumor type, XP-subtype, patients’ ages and ethnicity through comparison with the US general population.

Methods

We analyzed four independent international well-characterized XP cohorts (from USA, UK, France and Brazil) with a total of 434 patients, where 11.3% developed internal tumors and compared them to the American general population. We also compiled, through PubMed/Medline, a dataset of 89 internal tumors in XP patients published between 1958 and 2020.

Results

In the combined 4-XP cohort, relative risk of internal tumors was 34 (95% confidence interval (CI) 25–47) times higher than in the general population (p-value = 1.0E−47) and tumor arose 50 years earlier. The XP-C group was at the highest risk for the 0–20 years old-patients (OR = 665; 95% CI 368–1200; p-value = 4.3E−30). The highest risks were observed for tumors of central nervous system (OR = 331; 95% CI 171–641; p-value = 2.4E−20), hematological malignancies (OR = 120; 95% CI 77–186; p-value = 3.7E−36), thyroid (OR = 74; 95% CI 31–179; p-value = 1.2E−8) and gynecological tumors (OR = 91; 95% CI 42–193; p-value = 3.5E−12). The type of mutation on the XPC gene is associated with different classes of internal tumors. The majority of French XP-C patients (80%) are originated from North Africa and carried the XPC delTG founder mutation specific from the South Mediterranean area. The OR is extremely high for young (0–20 years) patients with more than 1300-fold increase for the French XPs carrying the founder mutation.

Conclusion

Because the age of XP population is increasing due to better sun-protection and knowledge of the disease, these results are of particular importance for the physicians to help in early prevention and detection of internal tumors in their XP patients. Few preventive blood analyses or simple medical imaging may help to better detect early cancer appearance in this population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02203-1.

scREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model

Cell reprogramming offers a potential treatment to many diseases, by regenerating specialized somatic cells. Despite decades of research, discovering the transcription factors that promote cell reprogramming has largely been accomplished through trial and error, a time-consuming and costly method. A computational model for cell reprogramming, however, could guide the hypothesis formulation and experimental validation, to efficiently utilize time and resources. Current methods often cannot account for the heterogeneity observed in cell reprogramming, or they only make short-term predictions, without modelling the entire reprogramming process. Here, we present scREMOTE, a novel computational model for cell reprogramming that leverages single cell multiomics data, enabling a more holistic view of the regulatory mechanisms at cellular resolution. This is achieved by first identifying the regulatory potential of each transcription factor and gene to uncover regulatory relationships, then a regression model is built to estimate the effect of transcription factor perturbations. We show that scREMOTE successfully predicts the long-term effect of overexpressing two key transcription factors in hair follicle development by capturing higher-order gene regulations. Together, this demonstrates that integrating the multimodal processes governing gene regulation creates a more accurate model for cell reprogramming with significant potential to accelerate research in regenerative medicine.

Mapping the gene network landscape of Alzheimer's disease through integrating genomics and transcriptomics

Integration of multi-omics data with molecular interaction networks enables elucidation of the pathophysiology of Alzheimer's disease (AD). Using the latest genome-wide association studies (GWAS) including proxy cases and the STRING interactome, we identified an AD network of 142 risk genes and 646 network-proximal genes, many of which were linked to synaptic functions annotated by mouse knockout data. The proximal genes were confirmed to be enriched in a replication GWAS of autopsy-documented cases. By integrating the AD gene network with transcriptomic data of AD and healthy temporal cortices, we identified 17 gene clusters of pathways, such as up-regulated complement activation and lipid metabolism, down-regulated cholinergic activity, and dysregulated RNA metabolism and proteostasis. The relationships among these pathways were further organized by a hierarchy of the AD network pinpointing major parent nodes in graph structure including endocytosis and immune reaction. Control analyses were performed using transcriptomics from cerebellum and a brain-specific interactome. Further integration with cell-specific RNA sequencing data demonstrated genes in our clusters of immunoregulation and complement activation were highly expressed in microglia.

Circadian control of heparan sulfate levels times phagocytosis of amyloid beta aggregates

Alzheimer's Disease (AD) is a neuroinflammatory disease characterized partly by the inability to clear, and subsequent build-up, of amyloid-beta (Aβ). AD has a bi-directional relationship with circadian disruption (CD) with sleep disturbances starting years before disease onset. However, the molecular mechanism underlying the relationship of CD and AD has not been elucidated. Myeloid-based phagocytosis, a key component in the metabolism of Aβ, is circadianly-regulated, presenting a potential link between CD and AD. In this work, we revealed that the phagocytosis of Aβ42 undergoes a daily circadian oscillation. We found the circadian timing of global heparan sulfate proteoglycan (HSPG) biosynthesis was the molecular timer for the clock-controlled phagocytosis of Aβ and that both HSPG binding and aggregation may play a role in this oscillation. These data highlight that circadian regulation in immune cells may play a role in the intricate relationship between the circadian clock and AD.

Bitter taste receptors protect against skin aging by inhibiting cellular senescence and enhancing wound healing

BACKGROUND/OBJECTIVES

Bitter taste receptors are taste signaling pathway mediators, and are also expressed and function in extra-gustatory organs. Skin aging affects the quality of life and may lead to medical issues. The purpose of this study was to better understand the anti-skin aging effects of bitter taste receptors in D-galactose (D-gal)-induced aged human keratinocytes, HaCaT cells.

MATERIALS/METHODS

Expressions of bitter taste receptors in HaCaT cells and mouse skin tissues were examined by polymerase chain reaction assay. Bitter taste receptor was overexpressed in HaCaT cells, and D-gal was treated to induce aging. We examined the effects of bitter taste receptors on aging by using β-galactosidase assay, wound healing assay, and Western blot assay.

RESULTS

TAS2R16 and TAS2R10 were expressed in HaCaT cells and were upregulated by D-gal treatment. TAS2R16 exerted protective effects against skin aging by regulating p53 and p21, antioxidant enzymes, the SIRT1/mechanistic target of rapamycin pathway, cell migration, and epithelial-mesenchymal transition markers. TAS2R10 was further examined to confirm a role of TAS2R16 in cellular senescence and wound healing in D-gal-induced aged HaCaT cells.

CONCLUSIONS

Our results suggest a novel potential preventive role of these receptors on skin aging by regulating cellular senescence and wound healing in human keratinocyte, HaCaT.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

1-deoxysphingolipids bind to COUP-TF to modulate lymphatic and cardiac cell development

Identification of physiological modulators of nuclear hormone receptor (NHR) activity is paramount for understanding the link between metabolism and transcriptional networks that orchestrate development and cellular physiology. Using libraries of metabolic enzymes alongside their substrates and products, we identify 1-deoxysphingosines as modulators of the activity of NR2F1 and 2 (COUP-TFs), which are orphan NHRs that are critical for development of the nervous system, heart, veins, and lymphatic vessels. We show that these non-canonical alanine-based sphingolipids bind to the NR2F1/2 ligand-binding domains (LBDs) and modulate their transcriptional activity in cell-based assays at physiological concentrations. Furthermore, inhibition of sphingolipid biosynthesis phenocopies NR2F1/2 deficiency in endothelium and cardiomyocytes, and increases in 1-deoxysphingosine levels activate NR2F1/2-dependent differentiation programs. Our findings suggest that 1-deoxysphingosines are physiological regulators of NR2F1/2-mediated transcription.

Biallelic AOPEP Loss-of-Function Variants Cause Progressive Dystonia with Prominent Limb Involvement

BACKGROUND

Monogenic causes of isolated dystonia are heterogeneous. Assembling cohorts of affected individuals sufficiently large to establish new gene-disease relationships can be challenging.

OBJECTIVE

We sought to expand the catalogue of monogenic etiologies for isolated dystonia.

METHODS

After the discovery of a candidate variant in a multicenter exome-sequenced cohort of affected individuals with dystonia, we queried online platforms and genomic data repositories worldwide to identify subjects with matching genotypic profiles.

RESULTS

Seven different biallelic loss-of-function variants in AOPEP were detected in five probands from four unrelated families with strongly overlapping phenotypes. In one proband, we observed a homozygous nonsense variant (c.1477C>T [p.Arg493*]). A second proband harbored compound heterozygous nonsense variants (c.763C>T [p.Arg255*]; c.777G>A [p.Trp259*]), whereas a third proband possessed a frameshift variant (c.696_697delAG [p.Ala234Serfs*5]) in trans with a splice-disrupting alteration (c.2041-1G>A). Two probands (siblings) from a fourth family shared compound heterozygous frameshift alleles (c.1215delT [p.Val406Cysfs*14]; c.1744delA [p.Met582Cysfs*6]). All variants were rare and expected to result in truncated proteins devoid of functionally important amino acid sequence. AOPEP, widely expressed in developing and adult human brain, encodes a zinc-dependent aminopeptidase, a member of a class of proteolytic enzymes implicated in synaptogenesis and neural maintenance. The probands presented with disabling progressive dystonia predominantly affecting upper and lower extremities, with variable involvement of craniocervical muscles. Dystonia was unaccompanied by any additional symptoms in three families, whereas the fourth family presented co-occurring late-onset parkinsonism.

CONCLUSIONS

Our findings suggest a likely causative role of predicted inactivating biallelic AOPEP variants in cases of autosomal recessive dystonia. Additional studies are warranted to understand the pathophysiology associated with loss-of-function variation in AOPEP. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Importing genetically altered animals: ensuring quality

The reproducibility of research using laboratory animals requires reliable management of their quality, in particular of their genetics, health and environment, all of which contribute to their phenotypes. The point at which these biological materials are transferred between researchers is particularly sensitive, as it may result in a loss of integrity of the animals and/or their documentation. Here, we describe the various aspects of laboratory animal quality that should be confirmed when sharing rodent research models. We also discuss how repositories of biological materials support the scientific community to ensure the continuity of the quality of laboratory animals. Both the concept of quality and the role of repositories themselves extend to all exchanges of biological materials and all networks that support the sharing of these reagents.

DES-Tcell is a knowledgebase for exploring immunology-related literature

T-cells are a subtype of white blood cells circulating throughout the body, searching for infected and abnormal cells. They have multifaceted functions that include scanning for and directly killing cells infected with intracellular pathogens, eradicating abnormal cells, orchestrating immune response by activating and helping other immune cells, memorizing encountered pathogens, and providing long-lasting protection upon recurrent infections. However, T-cells are also involved in immune responses that result in organ transplant rejection, autoimmune diseases, and some allergic diseases. To support T-cell research, we developed the DES-Tcell knowledgebase (KB). This KB incorporates text- and data-mined information that can expedite retrieval and exploration of T-cell relevant information from the large volume of published T-cell-related research. This KB enables exploration of data through concepts from 15 topic-specific dictionaries, including immunology-related genes, mutations, pathogens, and pathways. We developed three case studies using DES-Tcell, one of which validates effective retrieval of known associations by DES-Tcell. The second and third case studies focuses on concepts that are common to Grave’s disease (GD) and Hashimoto’s thyroiditis (HT). Several reports have shown that up to 20% of GD patients treated with antithyroid medication develop HT, thus suggesting a possible conversion or shift from GD to HT disease. DES-Tcell found miR-4442 links to both GD and HT, and that miR-4442 possibly targets the autoimmune disease risk factor CD6, which provides potential new knowledge derived through the use of DES-Tcell. According to our understanding, DES-Tcell is the first KB dedicated to exploring T-cell-relevant information via literature-mining, data-mining, and topic-specific dictionaries.

Metabolic Syndrome Impairs 3D Mitochondrial Structure, Dynamics, and Function in Swine Mesenchymal Stem Cells

Transplantation of autologous mesenchymal stem cells (MSCs) is an effective therapy for several diseases. Mitochondria modulate several important aspects of MSC function, but might be damaged by comorbidities and cardiovascular risk factors. We hypothesized that metabolic syndrome (MetS) compromises 3D mitochondrial structure, dynamics, and function in swine adipose tissue-derived MSCs. Domestic pigs were fed a Lean or MetS diet (n = 6 each) for 16 weeks. MSCs were collected from subcutaneous abdominal fat and their mitochondria analyzed using state-of-the-art Serial Block Face Electron Microscopy and 3D reconstruction. Mitochondrial dynamics (fusion/fission) were assessed by mRNA sequencing and Western blotting, and bioenergetics by membrane potential (TMRE), cytochrome-c oxidase (COX)-IV activity, and Seahorse Analyzer. Expression of mitochondria-associated microRNAs (mitomiRs) was measured by quantitative polymerase chain reaction (qPCR). MetS pigs developed obesity, hypertension, insulin resistance, and hyperlipidemia. Mitochondrial density was similar between the groups, but 3D mitochondrial and matrix volumes were lower in MetS-MSCs versus Lean-MSCs. Mitochondrial fission was higher, but fusion lower in MetS-MSCs versus Lean-MSCs, as were membrane potential, COX-IV activity, and ATP production. Contrarily, expression of the mitomiRs miR15a, miR-137, and miR-181c, which target mitochondrial genes that support mitochondrial structure, energy pathways, and dynamics, was higher in MetS-MSCs compared to Lean-MSCs, suggesting a potential to modulate their expression. MetS damages MSC 3D mitochondrial structure, dynamics, and function, and may modulate genes encoding for mitochondrial proteins. These observations support development of mitoprotective strategies to preserve the regenerative potency of MSCs and their suitability for autologous transplantation in patients with MetS.

Advances in bulk and single-cell multi-omics approaches for systems biology and precision medicine

Multi-omics allows the systematic understanding of the information flow across different omics layers, while single omics can mainly reflect one aspect of the biological system. The advancement of bulk and single-cell sequencing technologies and related computational methods for multi-omics largely facilitated the development of system biology and precision medicine. Single-cell approaches have the advantage of dissecting cellular dynamics and heterogeneity, whereas traditional bulk technologies are limited to individual/population-level investigation. In this review, we first summarize the technologies for producing bulk and single-cell multi-omics data. Then, we survey the computational approaches for integrative analysis of bulk and single-cell multimodal data, respectively. Moreover, the databases and data storage for multi-omics, as well as the tools for visualizing multimodal data are summarized. We also outline the integration between bulk and single-cell data, and discuss the applications of multi-omics in precision medicine. Finally, we present the challenges and perspectives for multi-omics development.

Cell-autonomous immune gene expression is repressed in pulmonary neuroendocrine cells and small cell lung cancer

Small cell lung cancer (SCLC) is classified as a high-grade neuroendocrine (NE) tumor, but a subset of SCLC has been termed “variant” due to the loss of NE characteristics. In this study, we computed NE scores for patient-derived SCLC cell lines and xenografts, as well as human tumors. We aligned NE properties with transcription factor-defined molecular subtypes. Then we investigated the different immune phenotypes associated with high and low NE scores. We found repression of immune response genes as a shared feature between classic SCLC and pulmonary neuroendocrine cells of the healthy lung. With loss of NE fate, variant SCLC tumors regain cell-autonomous immune gene expression and exhibit higher tumor-immune interactions. Pan-cancer analysis revealed this NE lineage-specific immune phenotype in other cancers. Additionally, we observed MHC I re-expression in SCLC upon development of chemoresistance. These findings may help guide the design of treatment regimens in SCLC.

Ling Cai et al. used transcriptomic profiling data of healthy lung, patient-derived small cell lung cancer cell lines, xenografts, and primary tumors to examine a link between neuroendocrine (NE) signatures and immune gene expression. Their findings suggest that cell-autonomous immune gene repression is a shared feature between healthy and tumor cells of NE lineage and may influence tumor-immune cell interaction and response to immunotherapy.

A novel cryo-embedding method for in-depth analysis of craniofacial mini pig bone specimens

The disconnect between preclinical and clinical results underscores the imperative for establishing good animal models, then gleaning all available data on efficacy, safety, and potential toxicities associated with a device or drug. Mini pigs are a commonly used animal model for testing orthopedic and dental devices because their skeletons are large enough to accommodate human-sized implants. The challenge comes with the analyses of their hard tissues: current methods are time-consuming, destructive, and largely limited to histological observations made from the analysis of very few tissue sections. We developed and employed cryo-based methods that preserved the microarchitecture and the cellular/molecular integrity of mini pig hard tissues, then demonstrated that the results of these histological, histochemical, immunohistochemical, and dynamic histomorphometric analyses e.g., mineral apposition rates were comparable with similar data from preclinical rodent models. Thus, the ability to assess static and dynamic bone states increases the translational value of mini pig and other large animal model studies. In sum, this method represents logical means to minimize the number of animals in a study while simultaneously maximizing the amount of information collected from each specimen.

RUNX2 co-operates with EGR1 to regulate osteogenic differentiation through Htra1 enhancers

Runt-related transcription factor 2 (Runx2) has been shown to regulate osteoblast differentiation by directly or indirectly regulating numerous osteoblast-related genes. However, our understanding of the transcriptional mechanisms of RUNX2 is mainly restricted to its transactivation, while the mechanism underlying its inhibitory effect during osteoblast differentiation remains largely unknown. Here, we incorporated the anti-RUNX2 chromatin immunoprecipitation (ChIP) sequencing in MC3T3-E1 cells and RNA-sequencing of parietal bone from Runx2 heterozygous mutant mice, to identify the putative genes negatively regulated by RUNX2. We identified HtrA serine peptidase 1 (Htra1) as a target gene and found ten candidate Htra1 enhancers potentially regulated by RUNX2, among which seven were verified by dual-luciferase assays. Furthermore, we investigated the motifs in the vicinity of RUNX2-binding sites and identified early growth response 1 (EGR1) as a potential partner transcription factor (TF) potentially regulating Htra1 expression, which was subsequently confirmed by Re-ChIP assays. RUNX2 and EGR1 co-repressed Htra1 and increased the expression levels of other osteoblast marker genes, such as osterix, osteocalcin, and osteoprotegerin at the messenger RNA and protein level. Moreover, Alizarin red staining combined with alkaline phosphatase (ALP) staining showed decreased calcified nodules and ALP activity in the siRUNX2+siEGR1 group compared with siRUNX2 group. Our findings revealed the detailed mechanism of the inhibitory function of RUNX2 towards its downstream genes, along with its partner TFs, to promote osteoblast differentiation.

Spontaneous and Induced Animal Models for Cancer Research

Considering the complexity of the current framework in oncology, the relevance of animal models in biomedical research is critical in light of the capacity to produce valuable data with clinical translation. The laboratory mouse is the most common animal model used in cancer research due to its high adaptation to different environments, genetic variability, and physiological similarities with humans. Beginning with spontaneous mutations arising in mice colonies that allow for pursuing studies of specific pathological conditions, this area of in vivo research has significantly evolved, now capable of generating humanized mice models encompassing the human immune system in biological correlation with human tumor xenografts. Moreover, the era of genetic engineering, especially of the hijacking CRISPR/Cas9 technique, offers powerful tools in designing and developing various mouse strains. Within this article, we will cover the principal mouse models used in oncology research, beginning with behavioral science of animals vs. humans, and continuing on with genetically engineered mice, microsurgical-induced cancer models, and avatar mouse models for personalized cancer therapy. Moreover, the area of spontaneous large animal models for cancer research will be briefly presented.

Simplified Method to Measure Mouse Fertility

Estimating breeding performance from mouse mating trials has focused on lifetime mating trials, which are too slow and costly for characterizing the many novel genetic mouse lines produced in fertility research, an underpinning of reproductive pathophysiology research. This study introduces the fertility index, defined as the slope of the regression of cumulative number of pups produced by a female over elapsed time in a monogamous mating trial. By using a robust resampling technique, the Theil-Sen estimator (widely available in free or niche statistical software), to estimate the fertility index, the present study of 410 mating trials of mice from 7 genotypes lasting a median of 10 litters shows that it is possible to estimate the fertility index reliably over as few as 4 litters.

Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer

Although much progress has been made to improve treatment, colon cancer remains a leading cause of cancer death worldwide. Metabolic reprogramming is a significant ability of cancer cells to ensure the necessary energy supply in uncontrolled proliferation. Since reprogramming energy metabolism has emerged as a new hallmark of cancer cells, accumulating evidences have suggested that metabolism-related genes may serve as key regulators of tumorigenesis and potential biomarkers. In this study, we analyzed a set of reprogramming energy metabolism-related genes by transcriptome analysis in colon cancer and revealed a five-gene signature that could significantly predict the overall survival. The reprogramming energy metabolism-related signature could distinguish patients into high-risk and low-risk groups with significantly different survival times (P = 0.0011; HR = 1.92; 95% CI [1.29–2.87]). Its prognostic value was confirmed in another two independent colon cancer cohorts (P = 5.2e–04; HR = 2.09, 95%; CI [1.37–3.2] for GSE17538 and P = 3.8e−04; HR = 2.08, 95% CI [1.37–3.16] for GSE41258). By multivariable analysis, we found that the signature was independent of clinicopathological features. Its power in promoting risk stratification of the current clinical stage was then evaluated by stratified analysis. Moreover, the signature could improve the power of the TNM stage for the prediction of overall survival and could be used in patients who received adjuvant chemotherapy. Overall, our results demonstrated the important role of the reprogramming energy metabolism-related signature in promoting stratification of high-risk patients, which could be diagnostic of adjuvant therapy benefit.

Human Disease Ontology 2018 update: classification, content and workflow expansion

The Human Disease Ontology (DO) (http://www.disease-ontology.org), database has undergone significant expansion in the past three years. The DO disease classification includes specific formal semantic rules to express meaningful disease models and has expanded from a single asserted classification to include multiple-inferred mechanistic disease classifications, thus providing novel perspectives on related diseases. Expansion of disease terms, alternative anatomy, cell type and genetic disease classifications and workflow automation highlight the updates for the DO since 2015. The enhanced breadth and depth of the DO’s knowledgebase has expanded the DO’s utility for exploring the multi-etiology of human disease, thus improving the capture and communication of health-related data across biomedical databases, bioinformatics tools, genomic and cancer resources and demonstrated by a 6.6× growth in DO’s user community since 2015. The DO’s continual integration of human disease knowledge, evidenced by the more than 200 SVN/GitHub releases/revisions, since previously reported in our DO 2015 NAR paper, includes the addition of 2650 new disease terms, a 30% increase of textual definitions, and an expanding suite of disease classification hierarchies constructed through defined logical axioms.

The UCSF Mouse Inventory Database Application, an Open Source Web App for Sharing Mutant Mice Within a Research Community

The UCSF Mouse Inventory Database Application is an open-source Web App that provides information about the mutant alleles, transgenes, and inbred strains maintained by investigators at the university and facilitates sharing of these resources within the university community. The Application is designed to promote collaboration, decrease the costs associated with obtaining genetically-modified mice, and increase access to mouse lines that are difficult to obtain. An inventory of the genetically-modified mice on campus and the investigators who maintain them is compiled from records of purchases from external sources, transfers from researchers within and outside the university, and from data provided by users. These data are verified and augmented with relevant information harvested from public databases, and stored in a succinct, searchable database secured on the university network. Here we describe this resource and provide information about how to implement and maintain such a mouse inventory database application at other institutions.

A unified nomenclature for vertebrate olfactory receptors

BACKGROUND

Olfactory receptors (ORs) are G protein-coupled receptors with a crucial role in odor detection. A typical mammalian genome harbors ~ 1000 OR genes and pseudogenes; however, different gene duplication/deletion events have occurred in each species, resulting in complex orthology relationships. While the human OR nomenclature is widely accepted and based on phylogenetic classification into 18 families and further into subfamilies, for other mammals different and multiple nomenclature systems are currently in use, thus concealing important evolutionary and functional insights.

RESULTS

Here, we describe the Mutual Maximum Similarity (MMS) algorithm, a systematic classifier for assigning a human-centric nomenclature to any OR gene based on inter-species hierarchical pairwise similarities. MMS was applied to the OR repertoires of seven mammals and zebrafish. Altogether, we assigned symbols to 10,249 ORs. This nomenclature is supported by both phylogenetic and synteny analyses. The availability of a unified nomenclature provides a framework for diverse studies, where textual symbol comparison allows immediate identification of potential ortholog groups as well as species-specific expansions/deletions; for example, Or52e5 and Or52e5b represent a rat-specific duplication of OR52E5. Another example is the complete absence of OR subfamily OR6Z among primate OR symbols. In other mammals, OR6Z members are located in one genomic cluster, suggesting a large deletion in the great ape lineage. An additional 14 mammalian OR subfamilies are missing from the primate genomes. While in chimpanzee 87% of the symbols were identical to human symbols, this number decreased to ~ 50% in dog and cow and to ~ 30% in rodents, reflecting the adaptive changes of the OR gene superfamily across diverse ecological niches. Application of the proposed nomenclature to zebrafish revealed similarity to mammalian ORs that could not be detected from the current zebrafish olfactory receptor gene nomenclature.

CONCLUSIONS

We have consolidated a unified standard nomenclature system for the vertebrate OR superfamily. The new nomenclature system will be applied to cow, horse, dog and chimpanzee by the Vertebrate Gene Nomenclature Committee and its implementation is currently under consideration by other relevant species-specific nomenclature committees.

PATHBIO: an international training program for precision mouse phenotyping

Design and production of genetically engineered mouse strains by individual research laboratories, research teams, large-scale consortia, and the biopharmaceutical industry have magnified the need for qualified personnel to identify, annotate, and validate (phenotype) these potentially new mouse models of human disease. The PATHBIO project has been recently established and funded by the European Union's ERASMUS+ Knowledge Alliance program to address the current shortfall in formally trained personnel. A series of teaching workshops will be given by experts on anatomy, histology, embryology, imaging, and comparative pathology to increase the availability of individuals with formal training to contribute to this important niche of Europe's biomedical research enterprise. These didactic and hands-on workshops are organized into three modules: (1) embryology, anatomy, histology, and the anatomical basis of imaging, (2) image-based phenotyping, and (3) pathology. The workshops are open to all levels of participants from recent graduates to Ph.D., M.D., and veterinary scientists. Participation is available on a competitive basis at no cost for attending. The first series of Workshop Modules was held in 2019 and these will continue for the next 2 years.

Discordant gene responses to radiation in humans and mice and the role of hematopoietically humanized mice in the search for radiation biomarkers

The mouse (Mus musculus) is an extensively used model of human disease and responses to stresses such as ionizing radiation. As part of our work developing gene expression biomarkers of radiation exposure, dose, and injury, we have found many genes are either up-regulated (e.g. CDKN1A, MDM2, BBC3, and CCNG1) or down-regulated (e.g. TCF4 and MYC) in both species after irradiation at ~4 and 8 Gy. However, we have also found genes that are consistently up-regulated in humans and down-regulated in mice (e.g. DDB2, PCNA, GADD45A, SESN1, RRM2B, KCNN4, IFI30, and PTPRO). Here we test a hematopoietically humanized mouse as a potential in vivo model for biodosimetry studies, measuring the response of these 14 genes one day after irradiation at 2 and 4 Gy, and comparing it with that of human blood irradiated ex vivo, and blood from whole body irradiated mice. We found that human blood cells in the hematopoietically humanized mouse in vivo environment recapitulated the gene expression pattern expected from human cells, not the pattern seen from in vivo irradiated normal mice. The results of this study support the use of hematopoietically humanized mice as an in vivo model for screening of radiation response genes relevant to humans.