Mouse Genome Informatics (MGI) Is the International Resource for Information on the Laboratory Mouse

JAK and STAT5B mediate olfactory response of migratory locusts to their own volatiles

Janus kinase (JAK) and signal transducer and activator of transcription (STAT) signaling affect social aggregation, mood and psychiatric disorders, nociceptive and depressive behaviors. Olfactory dysfunction is one of the distinct symptoms of these behaviors, but function and mechanism of JAK and STAT in modulating olfaction remain largely unknown. Migratory locusts show olfactory preference for their own volatiles. We thus use this animal model to explore functions and mechanisms of JAK and STAT5B in mediating olfaction response to their own volatiles. Tissue distribution study shows that JAK and STAT5B express in antennae and brains, especially in antennal lobes and mushroom bodies in locust brains, and knockdown of these two genes by RNA interference (RNAi) in antennae and brains results in the loss of olfactory preference for locust volatiles, including chemical odorants indole and β-ionone. RNA-seq analysis reveals that JAK and STAT5B RNAi knockdown downregulates a functional class of transcripts in nucleoprotein complex, including heterogeneous nuclear ribonucleoprotein C (hnRNPC) and small nuclear ribonucleoprotein polypeptide F (SNRPF). HnRNPC and SNRPF mRNAs and proteins are also expressed in antennae and brains, and RNAi knockdown of these two genes reduces the percentage of locusts preferring volatiles, including chemical odorants indole and β-ionone. Furthermore, RNAi knockdown of dopamine receptor 1 (DopR1) results in the decrease of JAK mRNA level in antennae, and JAK/STAT5B, hnRNPC and SNRPF are required for dopamine receptor 1 (DopR1) to modulate olfactory preference for their own volatiles. This study confirms that JAK/STAT5B signaling modulates olfaction by affecting expression levels of hnRNPC and SNRPF, and this pathway is also required for DopR1 to modulate olfactory preference for their own volatiles. These findings highlight novel roles of JAK and STAT5B in modulating olfactory preference. This study provides novel insights into functional links among JAK/STAT5B signaling, RNA binding proteins and DopR1 underlying the modulation of olfactory behaviors.

Tumor Necrosis Factor-Alpha Modulates Expression of Genes Involved in Cytokines and Chemokine Pathways in Proliferative Myoblast Cells

Skeletal muscle regeneration after injury is a complex process involving inflammatory signaling and myoblast activation. Pro-inflammatory cytokines like tumor necrosis factor-alpha (TNF-α) are key mediators, but their effects on gene expression in proliferating myoblasts are unclear. We performed the RNA sequencing of TNF-α treated C2C12 myoblasts to elucidate the signaling pathways and gene networks regulated by TNF-α during myoblast proliferation. The TNF-α (10 ng/mL) treatment of C2C12 cells led to 958 differentially expressed genes compared to the controls. Pathway analysis revealed significant regulation of TNF-α signaling, along with the chemokine and IL-17 pathways. Key upregulated genes included cytokines (e.g., IL-6), chemokines (e.g., CCL7), and matrix metalloproteinases (MMPs). TNF-α increased myogenic factor 5 (Myf5) but decreased MyoD protein levels and stimulated the release of MMP-9, MMP-10, and MMP-13. TNF-α also upregulates versican and myostatin mRNA. Overall, our study demonstrates the TNF-α modulation of distinct gene expression patterns and signaling pathways that likely contribute to enhanced myoblast proliferation while suppressing premature differentiation after muscle injury. Elucidating the mechanisms involved in skeletal muscle regeneration can aid in the development of regeneration-enhancing therapeutics.

Deciphering potential causative factors for undiagnosed Waardenburg syndrome through multi-data integration

BACKGROUND

Waardenburg syndrome (WS) is a rare genetic disorder mainly characterized by hearing loss and pigmentary abnormalities. Currently, seven causative genes have been identified for WS, but clinical genetic testing results show that 38.9% of WS patients remain molecularly unexplained. In this study, we performed multi-data integration analysis through protein-protein interaction and phenotype-similarity to comprehensively decipher the potential causative factors of undiagnosed WS. In addition, we explored the association between genotypes and phenotypes in WS with the manually collected 443 cases from published literature.

RESULTS

We predicted two possible WS pathogenic genes (KIT, CHD7) through multi-data integration analysis, which were further supported by gene expression profiles in single cells and phenotypes in gene knockout mouse. We also predicted twenty, seven, and five potential WS pathogenic variations in gene PAX3, MITF, and SOX10, respectively. Genotype-phenotype association analysis showed that white forelock and telecanthus were dominantly present in patients with PAX3 variants; skin freckles and premature graying of hair were more frequently observed in cases with MITF variants; while aganglionic megacolon and constipation occurred more often in those with SOX10 variants. Patients with variations of PAX3 and MITF were more likely to have synophrys and broad nasal root. Iris pigmentary abnormality was more common in patients with variations of PAX3 and SOX10. Moreover, we found that patients with variants of SOX10 had a higher risk of suffering from auditory system diseases and nervous system diseases, which were closely associated with the high expression abundance of SOX10 in ear tissues and brain tissues.

CONCLUSIONS

Our study provides new insights into the potential causative factors of WS and an alternative way to explore clinically undiagnosed cases, which will promote clinical diagnosis and genetic counseling. However, the two potential disease-causing genes (KIT, CHD7) and 32 potential pathogenic variants (PAX3: 20, MITF: 7, SOX10: 5) predicted by multi-data integration in this study are all computational predictions and need to be further verified through experiments in follow-up research.

Intermittent fasting shifts the diurnal transcriptome atlas of transcription factors

Intermittent fasting remains a safe and effective strategy to ameliorate various age-related diseases, but its specific mechanisms are not fully understood. Considering that transcription factors (TFs) determine the response to environmental signals, here, we profiled the diurnal expression of 600 samples across four metabolic tissues sampled every 4 over 24 h from mice placed on five different feeding regimens to provide an atlas of TFs in biological space, time, and feeding regimen. Results showed that 1218 TFs exhibited tissue-specific and temporal expression profiles in ad libitum mice, of which 974 displayed significant oscillations at least in one tissue. Intermittent fasting triggered more than 90% (1161 in 1234) of TFs to oscillate somewhere in the body and repartitioned their tissue-specific expression. A single round of fasting generally promoted TF expression, especially in skeletal muscle and adipose tissues, while intermittent fasting mainly suppressed TF expression. Intermittent fasting down-regulated aging pathway and upregulated the pathway responsible for the inhibition of mammalian target of rapamycin (mTOR). Intermittent fasting shifts the diurnal transcriptome atlas of TFs, and mTOR inhibition may orchestrate intermittent fasting-induced health improvements. This atlas offers a reference and resource to understand how TFs and intermittent fasting may contribute to diurnal rhythm oscillation and bring about specific health benefits.

Brain transcriptomic, metabolic and mitohormesis properties associated with N-propargylglycine treatment: A prevention strategy against neurodegeneration

INTRODUCTION

There is an urgent need for new or repurposed therapeutics that protect against or significantly delay the clinical progression of neurodegenerative diseases, such as Huntington's disease (HD), Parkinson's disease and Alzheimer's disease. In particular, preclinical studies are needed for well tolerated and brain-penetrating small molecules capable of mitigating the proteotoxic mitochondrial processes that are hallmarks of these diseases. We identified a unique suicide inhibitor of mitochondrial proline dehydrogenase (Prodh), N-propargylglycine (N-PPG), which has anticancer and brain-enhancing mitohormesis properties, and we hypothesize that induction of mitohormesis by N-PPG protects against neurodegenerative diseases. We carried out a series of mouse studies designed to: i) compare brain and metabolic responses while on oral N-PPG treatment (50 mg/kg, 9-14 days) of B6CBA wildtype (WT) and short-lived transgenic R6/2 (HD) mice; and ii) evaluate potential brain and systemwide stress rebound responses in WT mice 2 months after cessation of extended mitohormesis induction by well-tolerated higher doses of N-PPG (100-200 mg/kg x 60 days). WT and HD mice showed comparable global evidence of N-PPG induced brain mitohormesis characterized by Prodh protein decay and increased mitochondrial expression of chaperone and Yme1l1 protease proteins. Interestingly, transcriptional analysis (RNAseq) showed partial normalization of HD whole brain transcriptomes toward those of WT mice. Comprehensive metabolomic profiles performed on control and N-PPG treated blood, brain, and kidney samples revealed expected N-PPG-induced tissue increases in proline levels in both WT and HD mice, accompanied by surprising parallel increases in hydroxyproline and sarcosine. Two months after cessation of the higher dose N-PPG stress treatments, WT mouse brains showed robust rebound increases in Prodh protein levels and mitochondrial transcriptome responses, as well as altered profiles of blood amino acid-related metabolites. Our HD and WT mouse preclinical findings point to the brain penetrating and mitohormesis-inducing potential of the drug candidate, N-PPG, and provide new rationale and application insights supporting its further preclinical testing in various models of neurodegenerative diseases characterized by loss of mitochondrial proteostasis.

A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data

BACKGROUND

Funding agencies, publishers, and other stakeholders are pushing environmental health science investigators to improve data sharing; to promote the findable, accessible, interoperable, and reusable (FAIR) principles; and to increase the rigor and reproducibility of the data collected. Accomplishing these goals will require significant cultural shifts surrounding data management and strategies to develop robust and reliable resources that bridge the technical challenges and gaps in expertise.

OBJECTIVE

In this commentary, we examine the current state of managing data and metadata-referred to collectively as (meta)data-in the experimental environmental health sciences. We introduce new tools and resources based on in vivo experiments to serve as examples for the broader field.

METHODS

We discuss previous and ongoing efforts to improve (meta)data collection and curation. These include global efforts by the Functional Genomics Data Society to develop metadata collection tools such as the Investigation, Study, Assay (ISA) framework, and the Center for Expanded Data Annotation and Retrieval. We also conduct a case study of in vivo data deposited in the Gene Expression Omnibus that demonstrates the current state of in vivo environmental health data and highlights the value of using the tools we propose to support data deposition.

DISCUSSION

The environmental health science community has played a key role in efforts to achieve the goals of the FAIR guiding principles and is well positioned to advance them further. We present a proposed framework to further promote these objectives and minimize the obstacles between data producers and data scientists to maximize the return on research investments. https://doi.org/10.1289/EHP11484.

PrismEXP: gene annotation prediction from stratified gene-gene co-expression matrices

Background

Gene-gene co-expression correlations measured by mRNA-sequencing (RNA-seq) can be used to predict gene annotations based on the co-variance structure within these data. In our prior work, we showed that uniformly aligned RNA-seq co-expression data from thousands of diverse studies is highly predictive of both gene annotations and protein-protein interactions. However, the performance of the predictions varies depending on whether the gene annotations and interactions are cell type and tissue specific or agnostic. Tissue and cell type-specific gene-gene co-expression data can be useful for making more accurate predictions because many genes perform their functions in unique ways in different cellular contexts. However, identifying the optimal tissues and cell types to partition the global gene-gene co-expression matrix is challenging.

Results

Here we introduce and validate an approach called PRediction of gene Insights from Stratified Mammalian gene co-EXPression (PrismEXP) for improved gene annotation predictions based on RNA-seq gene-gene co-expression data. Using uniformly aligned data from ARCHS4, we apply PrismEXP to predict a wide variety of gene annotations including pathway membership, Gene Ontology terms, as well as human and mouse phenotypes. Predictions made with PrismEXP outperform predictions made with the global cross-tissue co-expression correlation matrix approach on all tested domains, and training using one annotation domain can be used to predict annotations in other domains.

Conclusions

By demonstrating the utility of PrismEXP predictions in multiple use cases we show how PrismEXP can be used to enhance unsupervised machine learning methods to better understand the roles of understudied genes and proteins. To make PrismEXP accessible, it is provided via a user-friendly web interface, a Python package, and an Appyter. AVAILABILITY. The PrismEXP web-based application, with pre-computed PrismEXP predictions, is available from: https://maayanlab.cloud/prismexp; PrismEXP is also available as an Appyter: https://appyters.maayanlab.cloud/PrismEXP/; and as Python package: https://github.com/maayanlab/prismexp.

Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia

Introduction: Acute myeloid leukemia (AML) is the most common type of leukemia in adults. However, there is a gap in understanding the molecular basis of the disease, partly because key genes associated with AML have not been extensively explored. In the current study, we aimed to identify genes that have strong association with AML based on a cross-species integrative approach. Methods: We used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify co-expressed gene modules significantly correlated with human AML, and further selected the genes exhibiting a significant difference in expression between AML and healthy mouse. Protein-protein interactions, transcription factors, gene function, genetic regulation, and coding sequence variants were integrated to identify key hub genes in AML. Results: The cross-species approach identified a total of 412 genes associated with both human and mouse AML. Enrichment analysis confirmed an association of these genes with hematopoietic and immune-related functions, phenotypes, processes, and pathways. Further, the integrated analysis approach identified a set of important module genes including Nfe2, Trim27, Mef2c, Ets1, Tal1, Foxo1, and Gata1 in AML. Six of these genes (except ETS1) showed significant differential expression between human AML and healthy samples in an independent microarray dataset. All of these genes are known to be involved in immune/hematopoietic functions, and in transcriptional regulation. In addition, Nfe2, Trim27, Mef2c, and Ets1 harbor coding sequence variants, whereas Nfe2 and Trim27 are cis-regulated, making them attractive candidates for validation. Furthermore, subtype-specific analysis of the hub genes in human AML indicated high expression of NFE2 across all the subtypes (M0 through M7) and enriched expression of ETS1, LEF1, GATA1, and TAL1 in M6 and M7 subtypes. A significant correlation between methylation status and expression level was observed for most of these genes in AML patients. Conclusion: Findings from the current study highlight the importance of our cross-species approach in the identification of multiple key candidate genes in AML, which can be further studied to explore their detailed role in leukemia/AML.

Actionable secondary findings following exome sequencing of 836 non-obstructive azoospermia cases and their value in patient management

STUDY QUESTION

What is the load, distribution and added clinical value of secondary findings (SFs) identified in exome sequencing (ES) of patients with non-obstructive azoospermia (NOA)?

SUMMARY ANSWER

One in 28 NOA cases carried an identifiable, medically actionable SF.

WHAT IS KNOWN ALREADY

In addition to molecular diagnostics, ES allows assessment of clinically actionable disease-related gene variants that are not connected to the patient's primary diagnosis, but the knowledge of which may allow the prevention, delay or amelioration of late-onset monogenic conditions. Data on SFs in specific clinical patient groups, including reproductive failure, are currently limited.

STUDY DESIGN, SIZE, DURATION

The study group was a retrospective cohort of patients with NOA recruited in 10 clinics across six countries and formed in the framework of the international GEMINI (The GEnetics of Male INfertility Initiative) study.

PARTICIPANTS/MATERIALS, SETTING, METHODS

ES data of 836 patients with NOA were exploited to analyze SFs in 85 genes recommended by the American College of Medical Genetics and Genomics (ACMG), Geisinger's MyCode, and Clinical Genome Resource. The identified 6374 exonic variants were annotated with ANNOVAR and filtered for allele frequency, retaining 1381 rare or novel missense and loss-of-function variants. After automatic assessment of pathogenicity with ClinVar and InterVar, 87 variants were manually curated. The final list of confident disease-causing SFs was communicated to the corresponding GEMINI centers. When patient consent had been given, available family health history and non-andrological medical data were retrospectively assessed.

MAIN RESULTS AND THE ROLE OF CHANCE

We found a 3.6% total frequency of SFs, 3.3% from the 59 ACMG SF v2.0 genes. One in 70 patients carried SFs in genes linked to familial cancer syndromes, whereas 1 in 60 cases was predisposed to congenital heart disease or other cardiovascular conditions. Retrospective assessment confirmed clinico-molecular diagnoses in several cases. Notably, 37% (11/30) of patients with SFs carried variants in genes linked to male infertility in mice, suggesting that some SFs may have a co-contributing role in spermatogenic impairment. Further studies are needed to determine whether these observations represent chance findings or the profile of SFs in NOA patients is indeed different from the general population.

LIMITATIONS, REASONS FOR CAUTION

One limitation of our cohort was the low proportion of non-Caucasian ethnicities (9%). Additionally, as comprehensive clinical data were not available retrospectively for all men with SFs, we were not able to confirm a clinico-molecular diagnosis and assess the penetrance of the specific variants.

WIDER IMPLICATIONS OF THE FINDINGS

For the first time, this study analyzed medically actionable SFs in men with spermatogenic failure. With the evolving process to incorporate ES into routine andrology practice for molecular diagnostic purposes, additional assessment of SFs can inform about future significant health concerns for infertility patients. Timely detection of SFs and respective genetic counseling will broaden options for disease prevention and early treatment, as well as inform choices and opportunities regarding family planning. A notable fraction of SFs was detected in genes implicated in maintaining genome integrity, essential in both mitosis and meiosis. Thus, potential genetic pleiotropy may exist between certain adult-onset monogenic diseases and NOA.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the Estonian Research Council grants IUT34-12 and PRG1021 (M.L. and M.P.); National Institutes of Health of the United States of America grant R01HD078641 (D.F.C., K.I.A. and P.N.S.); National Institutes of Health of the United States of America grant P50HD096723 (D.F.C. and P.N.S.); National Health and Medical Research Council of Australia grant APP1120356 (M.K.O'B., D.F.C. and K.I.A.); Fundação para a Ciência e a Tecnologia (FCT)/Ministério da Ciência, Tecnologia e Inovação grant POCI-01-0145-FEDER-007274 (A.M.L., F.C. and J.G.) and FCT: IF/01262/2014 (A.M.L.). J.G. was partially funded by FCT/Ministério da Ciência, Tecnologia e Ensino Superior (MCTES), through the Centre for Toxicogenomics and Human Health-ToxOmics (grants UID/BIM/00009/2016 and UIDB/00009/2020). M.L.E. is a consultant for, and holds stock in, Roman, Sandstone, Dadi, Hannah, Underdog and has received funding from NIH/NICHD. Co-authors L.K., K.L., L.N., K.I.A., P.N.S., J.G., F.C., D.M.-M., K.A., K.A.J., M.K.O'B., A.M.L., D.F.C., M.P. and M.L. declare no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

Revisiting the Transcriptome Landscape of Pig Embryo Implantation Site at Single-Cell Resolution

Litter size is one of the most economically important traits in commercial pig farming. It has been estimated that approximately 30% of porcine embryos are lost during the peri-implantation period. Despite rapid advances over recent years, the molecular mechanism underlying embryo implantation in pigs remains poorly understood. In this study, the conceptus together with a small amount of its surrounding endometrial tissues at the implantation site was collected and subjected to single-cell RNA-seq using the 10x platform. Because embryo and maternal endometrium were genetically different, we successfully dissected embryonic cells from maternal endometrial cells in the data according to single nucleotide polymorphism information captured by single-cell RNA-seq. Undoubtedly, the interaction between trophoblast cells and uterine epithelial cells represents the key mechanism of embryo implantation. Using the CellChat tool, we revealed cell-cell communications between these 2 cell types in terms of secreted signaling, ECM-receptor interaction and cell-cell contact. Additionally, by analyzing the non-pregnant endometrium as control, we were able to identify global gene expression changes associated with embryo implantation in each cell type. Our data provide a valuable resource for deciphering the molecular mechanism of embryo implantation in pigs.

Single-cell analysis of mouse uterus at the invasion phase of embryo implantation

Background

Embryo implantation into the uterus is a crucial step for human reproduction. A hypothesis has been proposed that the molecular circuit invented by trophoblasts for invasive embryo implantation during evolution might be misused by cancer cells to promote malignancy. Unfortunately, our current understanding of the molecular mechanism underlying embryo implantation is far from complete.

Results

Here we used the mouse as an animal model and generated a single-cell transcriptomic atlas of the embryo implantation site of mouse uterus at the invasion phase of embryo implantation on gestational day 6. We revealed 23 distinct cell clusters, including 5 stromal cell clusters, 2 epithelial cell clusters, 1 smooth muscle cell cluster, 2 pericyte clusters, 4 endothelial cell clusters, and 9 immune cell clusters. Through data analysis, we identified differentially expression changes in all uterine cell types upon embryo implantation. By integrated with single-cell RNA-seq data from E5.5 embryos, we predicted cell–cell crosstalk between trophoblasts and uterine cell types.

Conclusions

Our study provides a valuable resource for understanding of the molecular mechanism of embryo implantation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00749-y.

Adipocyte-Specific Ablation of PU.1 Promotes Energy Expenditure and Ameliorates Metabolic Syndrome in Aging Mice

Objective: Although PU.1/Spi1 is known as a master regulator for macrophage development and function, we have reported previously that it is also expressed in adipocytes and is transcriptionally induced in obesity. Here, we investigated the role of adipocyte PU.1 in the development of the age-associated metabolic syndrome.

Methods: We generated mice with adipocyte-specific PU.1 knockout, assessed metabolic changes in young and older adult PU.1^fl/fl (control) and AdipoqCre PU.1^fl/fl (aPU.1KO) mice, including body weight, body composition, energy expenditure, and glucose homeostasis. We also performed transcriptional analyses using RNA-Sequencing of adipocytes from these mice.

Results: aPU.1KO mice have elevated energy expenditure at a young age and decreased adiposity and increased insulin sensitivity in later life. Corroborating these observations, transcriptional network analysis indicated the existence of validated, adipocyte PU.1-modulated regulatory hubs that direct inflammatory and thermogenic gene expression programs.

Conclusion: Our data provide evidence for a previously uncharacterized role of PU.1 in the development of age-associated obesity and insulin resistance.

TcoFBase: a comprehensive database for decoding the regulatory transcription co-factors in human and mouse

Transcription co-factors (TcoFs) play crucial roles in gene expression regulation by communicating regulatory cues from enhancers to promoters. With the rapid accumulation of TcoF associated chromatin immunoprecipitation sequencing (ChIP-seq) data, the comprehensive collection and integrative analyses of these data are urgently required. Here, we developed the TcoFBase database (http://tcof.liclab.net/TcoFbase), which aimed to document a large number of available resources for mammalian TcoFs and provided annotations and enrichment analyses of TcoFs. TcoFBase curated 2322 TcoFs and 6759 TcoFs associated ChIP-seq data from over 500 tissues/cell types in human and mouse. Importantly, TcoFBase provided detailed and abundant (epi) genetic annotations of ChIP-seq based TcoF binding regions. Furthermore, TcoFBase supported regulatory annotation information and various functional annotations for TcoFs. Meanwhile, TcoFBase embedded five types of TcoF regulatory analyses for users, including TcoF gene set enrichment, TcoF binding genomic region annotation, TcoF regulatory network analysis, TcoF-TF co-occupancy analysis and TcoF regulatory axis analysis. TcoFBase was designed to be a useful resource that will help reveal the potential biological effects of TcoFs and elucidate TcoF-related regulatory mechanisms.

OUP accepted manuscript

Conflicts between transcription and replication machinery are a potent source of replication stress and genome instability; however, no technique currently exists to identify endogenous genomic locations prone to transcription–replication interactions. Here, we report a novel method to identify genomic loci prone to transcription–replication interactions termed transcription–replication immunoprecipitation on nascent DNA sequencing, TRIPn-Seq. TRIPn-Seq employs the sequential immunoprecipitation of RNA polymerase 2 phosphorylated at serine 5 (RNAP2s5) followed by enrichment of nascent DNA previously labeled with bromodeoxyuridine. Using TRIPn-Seq, we mapped 1009 unique transcription–replication interactions (TRIs) in mouse primary B cells characterized by a bimodal pattern of RNAP2s5, bidirectional transcription, an enrichment of RNA:DNA hybrids, and a high probability of forming G-quadruplexes. TRIs are highly enriched at transcription start sites and map to early replicating regions. TRIs exhibit enhanced Replication Protein A association and TRI-associated genes exhibit higher replication fork termination than control transcription start sites, two marks of replication stress. TRIs colocalize with double-strand DNA breaks, are enriched for deletions, and accumulate mutations in tumors. We propose that replication stress at TRIs induces mutations potentially contributing to age-related disease, as well as tumor formation and development.

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.

N-Propargylglycine: a unique suicide inhibitor of proline dehydrogenase with anticancer activity and brain-enhancing mitohormesis properties

Proline dehydrogenase (PRODH) is a mitochondrial inner membrane flavoprotein critical for cancer cell survival under stress conditions and newly recognized as a potential target for cancer drug development. Reversible (competitive) and irreversible (suicide) inhibitors of PRODH have been shown in vivo to inhibit cancer cell growth with excellent host tolerance. Surprisingly, the PRODH suicide inhibitor N-propargylglycine (N-PPG) also induces rapid decay of PRODH with concordant upregulation of mitochondrial chaperones (HSP-60, GRP-75) and the inner membrane protease YME1L1, signifying activation of the mitochondrial unfolded protein response (UPRmt) independent of anticancer activity. The present study was undertaken to address two aims: (i) use PRODH overexpressing human cancer cells (ZR-75-1) to confirm the UPRmt inducing properties of N-PPG relative to another equipotent irreversible PRODH inhibitor, thiazolidine-2-carboxylate (T2C); and (ii) employ biochemical and transcriptomic approaches to determine if orally administered N-PPG can penetrate the blood-brain barrier, essential for its future use as a brain cancer therapeutic, and also potentially protect normal brain tissue by inducing mitohormesis. Oral daily treatments of N-PPG produced a dose-dependent decline in brain mitochondrial PRODH protein without detectable impairment in mouse health; furthermore, mice repeatedly dosed with 50 mg/kg N-PPG showed increased brain expression of the mitohormesis associated protease, YME1L1. Whole brain transcriptome (RNAseq) analyses of these mice revealed significant gene set enrichment in N-PPG stimulated neural processes (FDR p < 0.05). Given this in vivo evidence of brain bioavailability and neural mitohormesis induction, N-PPG appears to be unique among anticancer agents and should be evaluated for repurposing as a pharmaceutical capable of mitigating the proteotoxic mechanisms driving neurodegenerative disorders.

ReMap 2022: a database of Human, Mouse, Drosophila and Arabidopsis regulatory regions from an integrative analysis of DNA-binding sequencing experiments

ReMap (https://remap.univ-amu.fr) aims to provide manually curated, high-quality catalogs of regulatory regions resulting from a large-scale integrative analysis of DNA-binding experiments in Human, Mouse, Fly and Arabidopsis thaliana for hundreds of transcription factors and regulators. In this 2022 update, we have uniformly processed >11 000 DNA-binding sequencing datasets from public sources across four species. The updated Human regulatory atlas includes 8103 datasets covering a total of 1210 transcriptional regulators (TRs) with a catalog of 182 million (M) peaks, while the updated Arabidopsis atlas reaches 4.8M peaks, 423 TRs across 694 datasets. Also, this ReMap release is enriched by two new regulatory catalogs for Mus musculus and Drosophila melanogaster. First, the Mouse regulatory catalog consists of 123M peaks across 648 TRs as a result of the integration and validation of 5503 ChIP-seq datasets. Second, the Drosophila melanogaster catalog contains 16.6M peaks across 550 TRs from the integration of 1205 datasets. The four regulatory catalogs are browsable through track hubs at UCSC, Ensembl and NCBI genome browsers. Finally, ReMap 2022 comes with a new Cis Regulatory Module identification method, improved quality controls, faster search results, and better user experience with an interactive tour and video tutorials on browsing and filtering ReMap catalogs.

Deciphering mouse uterine receptivity for embryo implantation at single-cell resolution

Objectives

Mice are widely used as an animal model for studying human uterine receptivity for embryo implantation. Although transcriptional changes related to mouse uterine receptivity have been determined by using bulk RNA‐seq, the data are of limited value because the uterus is a complex organ consisting of many cell types. Here, we aimed to decipher mouse uterine receptivity for embryo implantation at single‐cell resolution.

Materials and methods

Single‐cell RNA sequencing was performed for the pre‐receptive and the receptive mouse uterus. Gene expression profiles in luminal epithelium and glandular epithelium were validated by comparing against a published laser capture microdissection (LCM)‐coupled microarray dataset.

Results

We revealed 19 distinct cell clusters, including 3 stromal cell clusters, 2 epithelial cell clusters, 1 smooth muscle cell cluster, 4 endothelial cell clusters and 8 immune cell clusters. We identified global gene expression changes associated with uterine receptivity in each cell type. Additionally, we predicted signalling interactions for distinct cell types to understand the crosstalk between the blastocyst and the receptive uterus.

Conclusion

Our data provide a valuable resource for deciphering the molecular mechanism underlying uterine receptivity in mice.

Identification of Intercellular Crosstalk between Decidual Cells and Niche Cells in Mice

Decidualization is a crucial step for human reproduction, which is a prerequisite for embryo implantation, placentation and pregnancy maintenance. Despite rapid advances over recent years, the molecular mechanism underlying decidualization remains poorly understood. Here, we used the mouse as an animal model and generated a single-cell transcriptomic atlas of a mouse uterus during decidualization. By analyzing the undecidualized inter-implantation site of the uterus as a control, we were able to identify global gene expression changes associated with decidualization in each cell type. Additionally, we identified intercellular crosstalk between decidual cells and niche cells, including immune cells, endothelial cells and trophoblast cells. Our data provide a valuable resource for deciphering the molecular mechanism underlying decidualization.

Single-cell analysis of mouse and human prostate reveals novel fibroblasts with specialized distribution and microenvironment interactions

Stromal-epithelial interactions are critical to the morphogenesis, differentiation, and homeostasis of the prostate, but the molecular identity and anatomy of discrete stromal cell types is poorly understood. Using single-cell RNA sequencing, we identified and validated the in situ localization of three smooth muscle subtypes (prostate smooth muscle, pericytes, and vascular smooth muscle) and two novel fibroblast subtypes in human prostate. Peri-epithelial fibroblasts (APOD+) wrap around epithelial structures, whereas interstitial fibroblasts (C7+) are interspersed in extracellular matrix. In contrast, the mouse displayed three fibroblast subtypes with distinct proximal-distal and lobe-specific distribution patterns. Statistical analysis of mouse and human fibroblasts showed transcriptional correlation between mouse prostate (C3+) and urethral (Lgr5+) fibroblasts and the human interstitial fibroblast subtype. Both urethral fibroblasts (Lgr5+) and ductal fibroblasts (Wnt2+) in the mouse contribute to a proximal Wnt/Tgfb signaling niche that is absent in human prostate. Instead, human peri-epithelial fibroblasts express secreted WNT inhibitors SFRPs and DKK1, which could serve as a buffer against stromal WNT ligands by creating a localized signaling niche around individual prostate glands. We also identified proximal-distal fibroblast density differences in human prostate that could amplify stromal signaling around proximal prostate ducts. In human benign prostatic hyperplasia, fibroblast subtypes upregulate critical immunoregulatory pathways and show distinct distributions in stromal and glandular phenotypes. A detailed taxonomy of leukocytes in benign prostatic hyperplasia reveals an influx of myeloid dendritic cells, T cells and B cells, resembling a mucosal inflammatory disorder. A receptor-ligand interaction analysis of all cell types revealed a central role for fibroblasts in growth factor, morphogen, and chemokine signaling to endothelia, epithelia, and leukocytes. These data are foundational to the development of new therapeutic targets in benign prostatic hyperplasia. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Cell-Cell Communication at the Embryo Implantation Site of Mouse Uterus Revealed by Single-Cell Analysis

As a crucial step for human reproduction, embryo implantation is a low-efficiency process. Despite rapid advances in recent years, the molecular mechanism underlying embryo implantation remains poorly understood. Here, we used the mouse as an animal model and generated a single-cell transcriptomic atlas of embryo implantation sites. By analyzing inter-implantation sites of the uterus as control, we were able to identify global gene expression changes associated with embryo implantation in each cell type. Additionally, we predicted signaling interactions between uterine luminal epithelial cells and mural trophectoderm of blastocysts, which represent the key mechanism of embryo implantation. We also predicted signaling interactions between uterine epithelial-stromal crosstalk at implantation sites, which are crucial for post-implantation development. Our data provide a valuable resource for deciphering the molecular mechanism underlying embryo implantation.

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.

A most formidable arsenal: genetic technologies for building a better mouse

The mouse is one of the most widely used model organisms for genetic study. The tools available to alter the mouse genome have developed over the preceding decades from forward screens to gene targeting in stem cells to the recent influx of CRISPR approaches. In this review, we first consider the history of mice in genetic study, the development of classic approaches to genome modification, and how such approaches have been used and improved in recent years. We then turn to the recent surge of nuclease-mediated techniques and how they are changing the field of mouse genetics. Finally, we survey common classes of alleles used in mice and discuss how they might be engineered using different methods.

Genotype-Phenotype Association Analysis Reveals New Pathogenic Factors for Osteogenesis Imperfecta Disease

Osteogenesis imperfecta (OI), mainly caused by structural abnormalities of type I collagen, is a hereditary rare disease characterized by increased bone fragility and reduced bone mass. Clinical manifestations of OI mostly include multiple repeated bone fractures, thin skin, blue sclera, hearing loss, cardiovascular and pulmonary system abnormalities, triangular face, dentinogenesis imperfecta (DI), and walking with assistance. Currently, 20 causative genes with 18 subtypes have been identified for OI, of them, variations in COL1A1 and COL1A2 have been demonstrated to be major causative factors to OI. However, the complexity of the bone formation process indicates that there are potential new pathogenic genes associated with OI. To comprehensively explore the underlying mechanism of OI, we conducted association analysis between genotypes and phenotypes of OI diseases and found that mutations in COL1A1 and COL1A2 contributed to a large proportion of the disease phenotypes. We categorized the clinical phenotypes and the genotypes based on the variation types for those 155 OI patients collected from literature, and association study revealed that three phenotypes (bone deformity, DI, walking with assistance) were enriched in two variation types (the Gly-substitution missense and groups of frameshift, nonsense, and splicing variations). We also identified four novel variations (c.G3290A (p.G1097D), c.G3289C (p.G1097R), c.G3289A (p.G1097S), c.G3281A (p.G1094D)) in gene COL1A1 and two novel variations (c.G2332T (p.G778C), c.G2341T (p.G781C)) in gene COL1A2, which could potentially contribute to the disease. In addition, we identified several new potential pathogenic genes (ADAMTS2, COL5A2, COL8A1) based on the integration of protein–protein interaction and pathway enrichment analysis. Our study provides new insights into the association between genotypes and phenotypes of OI and novel information for dissecting the underlying mechanism of the disease.

Using MARRVEL v1.2 for Bioinformatics Analysis of Human Genes and Variant Pathogenicity

One of the greatest challenges in the bioinformatic analysis of human sequencing data is identifying which variants are pathogenic. Numerous databases and tools have been generated to address this difficulty. However, these many useful data and tools are broadly dispersed, requiring users to search for their variants of interest through human genetic databases, variant function prediction tools, and model organism databases. To solve this problem, we collected data and observed workflows of human geneticists, clinicians, and model organism researchers to carefully select and display valuable information that facilitates the evaluation of whether a variant is likely to be pathogenic. This program, Model organism Aggregated Resources for Rare Variant ExpLoration (MARRVEL) v1.2, allows users to collect relevant data from 27 public sources for further efficient bioinformatic analysis of the pathogenicity of human variants. © 2019 by John Wiley & Sons, Inc.

Target Genes of Autism Risk Loci in Brain Frontal Cortex

Autism spectrum disorder (ASD) is a complex neuropsychiatric disorder. A number of genetic risk loci have been identified for ASD from genome-wide association studies (GWAS); however, their target genes in relevant tissues and cell types remain to be investigated. The frontal cortex is a key region in the human brain for communication and cognitive function. To identify risk genes contributing to potential dysfunction in the frontal cortex of ASD patients, we took an in silico approach integrating multi-omics data. We first found genes with expression in frontal cortex tissue that correlates with ASD risk loci by leveraging expression quantitative trait loci (eQTLs) information. Among these genes, we then identified 76 genes showing significant differential expression in the frontal cortex between ASD cases and controls in microarray datasets and further replicated four genes with RNA-seq data. Among the ASD GWAS single nucleotide polymorphisms (SNPs) correlating with the 76 genes, 20 overlap with histone marks and 40 are associated with gene methylation level. Thus, through multi-omics data analyses, we identified genes that may work as target genes of ASD risk loci in the brain frontal cortex.

Mouse Models and Online Resources for Functional Analysis of Osteoporosis Genome-Wide Association Studies

Osteoporosis is a complex genetic disease in which the number of loci associated with the bone mineral density, a clinical risk factor for fracture, has increased at an exponential rate in the last decade. The identification of the causative variants and candidate genes underlying these loci has not been able to keep pace with the rate of locus discovery. A large number of tools and data resources have been built around the use of the mouse as model of human genetic disease. Herein, we describe resources available for functional validation of human Genome Wide Association Study (GWAS) loci using mouse models. We specifically focus on large-scale phenotyping efforts focused on bone relevant phenotypes and repositories of genotype-phenotype data that exist for transgenic and mutant mice, which can be readily mined as a first step toward more targeted efforts designed to deeply characterize the role of a gene in bone biology.