The mutant mouse resource and research center (MMRRC) consortium: the US-based public mouse repository system.

Now in its 25th year, the Mutant Mouse Resource and Research Center (MMRRC) consortium continues to serve the United States and international biomedical scientific community as a public repository and distribution archive of laboratory mouse models of human disease for research. Supported by the National Institutes of Health (NIH), the MMRRC consists of 4 regionally distributed and dedicated vivaria, offices, and specialized laboratory facilities and an Informatics Coordination and Service Center (ICSC). The overarching purpose of the MMRRC is to facilitate groundbreaking biomedical research by offering an extensive repertoire of mutant mice that are essential for advancing the understanding of human physiology and disease. The function of the MMRRC is to identify, acquire, evaluate, characterize, cryopreserve, and distribute mutant mouse strains to qualified biomedical investigators around the nation and the globe. Mouse strains accepted from the research community are held to the highest scientific standards to optimize reproducibility and enhance scientific rigor and transparency. All submitted strains are thoroughly reviewed, documented, and validated using extensive scientific quality control measures. In addition, the MMRRC conducts resource-related research on cryopreservation, mouse genetics, environmental conditions, and other topics that enhance operations of the MMRRC. Today, the MMRRC maintains an archive of mice, cryopreserved embryos and sperm, embryonic stem (ES) cell lines, and murine hybridomas for nearly 65,000 alleles. Since its inception, the MMRRC has fulfilled more than 20,000 orders from 13,651 scientists at 8441 institutions worldwide. The MMRRC also provides numerous services to assist researchers, including scientific consultation, technical assistance, genetic assays, microbiome analysis, analytical phenotyping, pathology, cryorecovery, husbandry, breeding and colony management, infectious disease surveillance, and disease modeling. The ICSC coordinates MMRRC operations, interacts with researchers, and manages the website (mmrrc.org) and online catalogue. Researchers benefit from an expansive list of well-defined mouse models of disease that meet the highest scientific standards while submitting investigators benefit by having their mouse strains cryopreserved, protected, and distributed in compliance with NIH policies.

Placental-brain axis in females detected within broadly impacted metabolic gene networks protects against prenatal PCB exposure.

Background: Neurodevelopmental disorders have a strong male bias that is poorly understood. Placenta is a rich source of molecular information about environmental interactions with genetics (including biological sex), that affect the developing brain. We investigated placental-brain transcriptional responses in an established mouse model of prenatal exposure to a human-relevant mixture of polychlorinated biphenyls (PCBs). Results: To understand sex, tissue, and dosage effects in embryonic (E18) brain and placenta by RNAseq, we used weighted gene correlation network analysis (WGCNA) to create correlated gene networks that could be compared across sex or tissue. WGCNA revealed that expression within most correlated gene networks was significantly and strongly associated with PCB exposures, but frequently in opposite directions between male-female and placenta-brain comparisons. In both WGCNA and differentially expressed gene analyses, male brain showed more PCB-induced transcriptional changes than male placenta, but the reverse pattern was seen in females. Furthermore, non-monotonic dose responses to PCBs were observed in most gene networks but were most prominent in male brain. The transcriptomic effects of low dose PCB exposure were significantly reversed by dietary folic acid supplementation across both sexes, but these effects were strongest in female placenta. PCB-dysregulated and folic acid-reversed gene networks were commonly enriched in functions in metabolic pathways involved in energy usage and translation, with female-specific protective effects enriched in PPAR, thermogenesis, glycerolipids, and O-glycan biosynthesis, as opposed to toxicant responses in male brain. Conclusions: The female protective effect in prenatal PCB exposures appears to be mediated by dose-dependent sex differences in transcriptional modulation of metabolism in placenta.

Improving rigor and reproducibility in chromatin immunoprecipitation assay data analysis workflows with Rocketchip.

As genome sequencing technologies advance, the accumulation of sequencing data in public databases necessitates more robust and adaptable data analysis workflows. Here, we present Rocketchip, which aims to offer a solution to this problem by allowing researchers to easily compare and swap out different components of ChIP-seq, CUT&RUN, and CUT&Tag data analysis, thereby facilitating the identification of reliable analysis methodologies. Rocketchip enables researchers to efficiently process large datasets while ensuring reproducibility and allowing for the reanalysis of existing data. By supporting comparative analyses across different datasets and methodologies, Rocketchip contributes to the rigor and reproducibility of scientific findings. Furthermore, Rocketchip serves as a platform for benchmarking algorithms, allowing researchers to identify the most accurate and efficient analytical approaches to be applied to their data. In emphasizing reproducibility and adaptability, Rocketchip represents a significant step towards fostering robust scientific research practices.

Sex-specific single cell-level transcriptomic signatures of Rett syndrome disease progression.

Dominant X-linked diseases are uncommon due to female X chromosome inactivation (XCI). While random XCI usually protects females against X-linked mutations, Rett syndrome (RTT) is a female neurodevelopmental disorder caused by heterozygous MECP2 mutation. After 6-18 months of typical neurodevelopment, RTT girls undergo poorly understood regression. We performed longitudinal snRNA-seq on cerebral cortex in a construct-relevant Mecp2e1 mutant mouse model of RTT, revealing transcriptional effects of cell type, mosaicism, and sex on progressive disease phenotypes. Across cell types, we observed sex differences in the number of differentially expressed genes (DEGs) with 6x more DEGs in mutant females than males. Unlike males, female DEGs emerged prior to symptoms, were enriched for homeostatic gene pathways in distinct cell types over time, and correlated with disease phenotypes and human RTT cortical cell transcriptomes. Non-cell-autonomous effects were prominent and dynamic across disease progression of Mecp2e1 mutant females, indicating wild-type-expressing cells normalizing transcriptional homeostasis. These results improve understanding of RTT progression and treatment.

Do organisms need an impact factor? Citations of key biological resources including model organisms reveal usage patterns and impact.

Research resources like transgenic animals and antibodies are the workhorses of biomedicine, enabling investigators to relatively easily study specific disease conditions. As key biological resources, transgenic animals and antibodies are often validated, maintained, and distributed from university based stock centers. As these centers heavily rely largely on grant funding, it is critical that they are cited by investigators so that usage can be tracked. However, unlike systems for tracking the impact of papers, the conventions and systems for tracking key resource usage and impact lag behind. Previous studies have shown that about 50% of the resources are not findable, making the studies they are supporting irreproducible, but also makes tracking resources difficult. The RRID project is filling this gap by working with journals and resource providers to improve citation practices and to track the usage of these key resources. Here, we reviewed 10 years of citation practices for five university based stock centers, characterizing each reference into two broad categories: findable (authors could use the RRID, stock number, or full name) and not findable (authors could use a nickname or a common name that is not unique to the resource). The data revealed that when stock centers asked their communities to cite resources by RRID, in addition to helping stock centers more easily track resource usage by increasing the number of RRID papers, authors shifted from citing resources predominantly by nickname (~50% of the time) to citing them by one of the findable categories (~85%) in a matter of several years. In the case of one stock center, the MMRRC, the improvement in findability is also associated with improvements in the adherence to NIH rigor criteria, as determined by a significant increase in the Rigor and Transparency Index for studies using MMRRC mice. From this data, it was not possible to determine whether outreach to authors or changes to stock center websites drove better citation practices, but findability of research resources and rigor adherence was improved.

SpecDB: A relational database for archiving biomolecular NMR spectral data.

NMR is a valuable experimental tool in the structural biologist's toolkit to elucidate the structures, functions, and motions of biomolecules. The progress of machine learning, particularly in structural biology, reveals the critical importance of large, diverse, and reliable datasets in developing new methods and understanding in structural biology and science more broadly. Biomolecular NMR research groups produce large amounts of data, and there is renewed interest in organizing these data to train new, sophisticated machine learning architectures and to improve biomolecular NMR analysis pipelines. The foundational data type in NMR is the free-induction decay (FID). There are opportunities to build sophisticated machine learning methods to tackle long-standing problems in NMR data processing, resonance assignment, dynamics analysis, and structure determination using NMR FIDs. Our goal in this study is to provide a lightweight, broadly available tool for archiving FID data as it is generated at the spectrometer, and grow a new resource of FID data and associated metadata. This study presents a relational schema for storing and organizing the metadata items that describe an NMR sample and FID data, which we call Spectral Database (SpecDB). SpecDB is implemented in SQLite and includes a Python software library providing a command-line application to create, organize, query, backup, share, and maintain the database. This set of software tools and database schema allow users to store, organize, share, and learn from NMR time domain data. SpecDB is freely available under an open source license at https://github.rpi.edu/RPIBioinformatics/SpecDB.

Association of Diet and Antimicrobial Resistance in Healthy U.S. Adults.

Antimicrobial resistance (AMR) represents a significant source of morbidity and mortality worldwide, with expectations that AMR-associated consequences will continue to worsen throughout the coming decades. Since resistance to antibiotics is encoded in the microbiome, interventions aimed at altering the taxonomic composition of the gut might allow us to prophylactically engineer microbiomes that harbor fewer antibiotic resistant genes (ARGs). Diet is one method of intervention, and yet little is known about the association between diet and antimicrobial resistance. To address this knowledge gap, we examined diet using the food frequency questionnaire (FFQ; habitual diet) and 24-h dietary recalls (Automated Self-Administered 24-h [ASA24®] tool) coupled with an analysis of the microbiome using shotgun metagenome sequencing in 290 healthy adult participants of the United States Department of Agriculture (USDA) Nutritional Phenotyping Study. We found that aminoglycosides were the most abundant and prevalent mechanism of AMR in these healthy adults and that aminoglycoside-O-phosphotransferases (aph3-dprime) correlated negatively with total calories and soluble fiber intake. Individuals in the lowest quartile of ARGs (low-ARG) consumed significantly more fiber in their diets than medium- and high-ARG individuals, which was concomitant with increased abundances of obligate anaerobes, especially from the family Clostridiaceae, in their gut microbiota. Finally, we applied machine learning to examine 387 dietary, physiological, and lifestyle features for associations with antimicrobial resistance, finding that increased phylogenetic diversity of diet was associated with low-ARG individuals. These data suggest diet may be a potential method for reducing the burden of AMR. IMPORTANCE Antimicrobial resistance (AMR) represents a considerable burden to health care systems, with the public health community largely in consensus that AMR will be a major cause of death worldwide in the coming decades. Humans carry antibiotic resistance in the microbes that live in and on us, collectively known as the human microbiome. Diet is a powerful method for shaping the human gut microbiome and may be a tractable method for lessening antibiotic resistance, and yet little is known about the relationship between diet and AMR. We examined this relationship in healthy individuals who contained various abundances of antibiotic resistance genes and found that individuals who consumed diverse diets that were high in fiber and low in animal protein had fewer antibiotic resistance genes. Dietary interventions may be useful for lessening the burden of antimicrobial resistance and might ultimately motivate dietary guidelines which will consider how nutrition can reduce the impact of infectious disease.

The Mutant Mouse Resource and Research Center (MMRRC): the NIH-supported National Public Repository and Distribution Archive of Mutant Mouse Models in the USA.

The Mutant Mouse Resource and Research Center (MMRRC) Program is the pre-eminent public national mutant mouse repository and distribution archive in the USA, serving as a national resource of mutant mice available to the global scientific community for biomedical research. Established more than two decades ago with grants from the National Institutes of Health (NIH), the MMRRC Program supports a Consortium of regionally distributed and dedicated vivaria, laboratories, and offices (Centers) and an Informatics Coordination and Service Center (ICSC) at three academic teaching and research universities and one non-profit genetic research institution. The MMRRC Program accepts the submission of unique, scientifically rigorous, and experimentally valuable genetically altered and other mouse models donated by academic and commercial scientists and organizations for deposition, maintenance, preservation, and dissemination to scientists upon request. The four Centers maintain an archive of nearly 60,000 mutant alleles as live mice, frozen germplasm, and/or embryonic stem (ES) cells. Since its inception, the Centers have fulfilled 13,184 orders for mutant mouse models from 9591 scientists at 6626 institutions around the globe. Centers also provide numerous services that facilitate using mutant mouse models obtained from the MMRRC, including genetic assays, microbiome analysis, analytical phenotyping and pathology, cryorecovery, mouse husbandry, infectious disease surveillance and diagnosis, and disease modeling. The ICSC coordinates activities between the Centers, manages the website (mmrrc.org) and online catalog, and conducts communication, outreach, and education to the research community. Centers preserve, secure, and protect mutant mouse lines in perpetuity, promote rigor and reproducibility in scientific experiments using mice, provide experiential training and consultation in the responsible use of mice in research, and pursue cutting edge technologies to advance biomedical studies using mice to improve human health. Researchers benefit from an expansive list of well-defined mouse models of disease that meet the highest standards of rigor and reproducibility, while donating investigators benefit by having their mouse lines preserved, protected, and distributed in compliance with NIH policies.

Functional annotations of three domestic animal genomes provide vital resources for comparative and agricultural research.

Gene regulatory elements are central drivers of phenotypic variation and thus of critical importance towards understanding the genetics of complex traits. The Functional Annotation of Animal Genomes consortium was formed to collaboratively annotate the functional elements in animal genomes, starting with domesticated animals. Here we present an expansive collection of datasets from eight diverse tissues in three important agricultural species: chicken (Gallus gallus), pig (Sus scrofa), and cattle (Bos taurus). Comparative analysis of these datasets and those from the human and mouse Encyclopedia of DNA Elements projects reveal that a core set of regulatory elements are functionally conserved independent of divergence between species, and that tissue-specific transcription factor occupancy at regulatory elements and their predicted target genes are also conserved. These datasets represent a unique opportunity for the emerging field of comparative epigenomics, as well as the agricultural research community, including species that are globally important food resources.

Low-pass whole genome bisulfite sequencing of neonatal dried blood spots identifies a role for RUNX1 in Down syndrome DNA methylation profiles.

Neonatal dried blood spots (NDBS) are a widely banked sample source that enables retrospective investigation into early life molecular events. Here, we performed low-pass whole genome bisulfite sequencing (WGBS) of 86 NDBS DNA to examine early life Down syndrome (DS) DNA methylation profiles. DS represents an example of genetics shaping epigenetics, as multiple array-based studies have demonstrated that trisomy 21 is characterized by genome-wide alterations to DNA methylation. By assaying over 24 million CpG sites, thousands of genome-wide significant (q < 0.05) differentially methylated regions (DMRs) that distinguished DS from typical development and idiopathic developmental delay were identified. Machine learning feature selection refined these DMRs to 22 loci. The DS DMRs mapped to genes involved in neurodevelopment, metabolism, and transcriptional regulation. Based on comparisons with previous DS methylation studies and reference epigenomes, the hypermethylated DS DMRs were significantly (q < 0.05) enriched across tissues while the hypomethylated DS DMRs were significantly (q < 0.05) enriched for blood-specific chromatin states. A ~28 kb block of hypermethylation was observed on chromosome 21 in the RUNX1 locus, which encodes a hematopoietic transcription factor whose binding motif was the most significantly enriched (q < 0.05) overall and specifically within the hypomethylated DMRs. Finally, we also identified DMRs that distinguished DS NDBS based on the presence or absence of congenital heart disease (CHD). Together, these results not only demonstrate the utility of low-pass WGBS on NDBS samples for epigenome-wide association studies, but also provide new insights into the early life mechanisms of epigenomic dysregulation resulting from trisomy 21.