In biology, networks are used in different contexts as ways to represent relationships between entities, such as for instance interactions between genes, proteins or metabolites. Despite progress in the analysis of such networks and their potential to better understand the collective impact of genes on complex traits, one remaining challenge is to establish the biologic validity of gene co-expression networks and to determine what governs their organization. We used WGCNA to construct and analyze seven gene expression datasets from several tissues of mouse recombinant inbred strains (RIS). For six out of the 7 networks, we found that linkage to "module QTLs" (mQTLs) could be established for 29.3% of gene co-expression modules detected in the several mouse RIS. For about 74.6% of such genetically-linked modules, the mQTL was on the same chromosome as the one contributing most genes to the module, with genes originating from that chromosome showing higher connectivity than other genes in the modules. Such modules (that we considered as "genetically-driven") had network statistic properties (density and centralization) that set them apart from other modules in the network. Altogether, a sizeable portion of gene co-expression modules detected in mouse RIS panels had genetic determinants as their main organizing principle. In addition to providing a biologic interpretation validation for these modules, these genetic determinants imparted on them particular properties that set them apart from other modules in the network, to the point that they can be predicted to a large extent on the basis of their network statistics.

High-throughput methylation sequencing enables genome-wide detection of differentially methylated sites (DMS) or regions (DMR). Increasing evidence suggests that treatment-induced DMS can be transmitted across generations, but the analysis of induced methylation changes across multiple generations is complicated by the lack of sound statistical methods to evaluate significance levels. Due to software design, DMS detection was usually made on each generation separately, thus disregarding stochastic effects expected when a large number of DMS is detected in each generation. Here, we present a novel method based on Monte Carlo sampling, methylInheritance, to evaluate that the number of conserved DMS between several generations is associated to an effect inherited from a treatment and not randomness. Moreover, we developed an inheritance simulation package, methInheritSim, to demonstrate the performance of the methylInheritance method and to evaluate the power of different experimental designs. Finally, we applied methylInheritance to a DNA methylation dataset obtained from early-life persistent organic pollutants (POPs) exposed Sprague-Dawley female rats and their descendants through a paternal transmission. The results show that metylInheritance can efficiently identify treatment-induced inherited methylation changes. Specifically, we identified two intergenerationally conserved DMS at transcription start site (TSS); one of those persisted transgenerationally. Three transgenerationally conserved DMR were found at intra or integenic regions.

Weight loss success is dependent on the ability to refrain from regaining the lost weight in time. This feature was shown to be largely variable among individuals, and these differences, with their underlying molecular processes, are diverse and not completely elucidated. Altered plasma metabolites concentration could partly explain weight loss maintenance mechanisms. In the present work, a systems biology approach has been applied to investigate the potential mechanisms involved in weight loss maintenance within the Diogenes weight-loss intervention study.

During evolution, humans colonized different ecological niches and adopted a variety of subsistence strategies that gave rise to diverse selective pressures acting across the genome. Environmentally induced selection of vitamin, mineral, or other cofactor transporters could influence micronutrient-requiring molecular reactions and contribute to inter-individual variability in response to foods and nutritional interventions.

Growing evidence demonstrates that epithelial-mesenchymal transition (EMT) plays an important role in epithelial ovarian cancer (EOC) progression and spreading; however, its molecular mechanisms remain poorly defined. We have previously shown that the antigen receptor LY75 can modulate EOC cell phenotype and metastatic potential, as LY75 depletion directed mesenchymal-epithelial transition (MET) in EOC cell lines with mesenchymal phenotype. We used the LY75-mediated modulation of EMT as a model to investigate for DNA methylation changes during EMT in EOC cells, by applying the reduced representation bisulfite sequencing (RRBS) methodology. Numerous genes have displayed EMT-related DNA methylation patterns alterations in their promoter/exon regions. Ten selected genes, whose DNA methylation alterations were further confirmed by alternative methods, were further identified, some of which could represent new EOC biomarkers/therapeutic targets. Moreover, our methylation data were strongly indicative for the predominant implication of the Wnt/β-catenin pathway in the EMT-induced DNA methylation variations in EOC cells. Consecutive experiments, including alterations in the Wnt/β-catenin pathway activity in EOC cells with a specific inhibitor and the identification of LY75-interacting partners by a proteomic approach, were strongly indicative for the direct implication of the LY75 receptor in modulating the Wnt/β-catenin signaling in EOC cells.

Following their production in the testis, spermatozoa enter the epididymis where they gain their motility and fertilizing abilities. This post-testicular maturation coincides with sperm epigenetic profile changes that influence progeny outcome. While recent studies highlighted the dynamics of small non-coding RNAs in maturing spermatozoa, little is known regarding sperm methylation changes and their impact at the post-fertilization level. Fluorescence-activated cell sorting (FACS) was used to purify spermatozoa from the testis and different epididymal segments (i.e., caput, corpus and cauda) of CAG/su9-DsRed2; Acr3-EGFP transgenic mice in order to map out sperm methylome dynamics. Reduced representation bisulfite sequencing (RRBS-Seq) performed on DNA from these respective sperm populations indicated that high methylation changes were observed between spermatozoa from the caput vs. testis with 5,546 entries meeting our threshold values (q value <0.01, methylation difference above 25%). Most of these changes were transitory during epididymal sperm maturation according to the low number of entries identified between spermatozoa from cauda vs. testis. According to enzymatic and sperm/epididymal fluid co-incubation assays, (de)methylases were not found responsible for these sperm methylation changes. Instead, we identified that a subpopulation of caput spermatozoa displayed distinct methylation marks that were susceptible to sperm DNAse treatment and accounted for the DNA methylation profile changes observed in the proximal epididymis. Our results support the paradigm that a fraction of caput spermatozoa has a higher propensity to bind extracellular DNA, a phenomenon responsible for the sperm methylome variations observed at the post-testicular level. Further investigating the degree of conservation of this sperm heterogeneity in human will eventually provide new considerations regarding sperm selection procedures used in fertility clinics.

Characterizing the complex composition of solid tumors is fundamental for understanding tumor initiation, progression and metastasis. While patient-derived samples provide valuable insight, they are heterogeneous on multiple molecular levels, and often originate from advanced tumor stages. Here, we use single-cell transcriptome and epitope profiling together with pathway and lineage analyses to study tumorigenesis from a developmental perspective in a mouse model of salivary gland squamous cell carcinoma. We provide a comprehensive cell atlas and characterize tumor-specific cells. We find that these cells are connected along a reproducible developmental trajectory: initiated in basal cells exhibiting an epithelial-to-mesenchymal transition signature, tumorigenesis proceeds through Wnt-differential cancer stem cell-like subpopulations before differentiating into luminal-like cells. Our work provides unbiased insights into tumor-specific cellular identities in a whole tissue environment, and emphasizes the power of using defined genetic model systems.

Vaccines play a critical role in combating the COVID-19 pandemic. Future control of the pandemic requires improved vaccines with high efficacy against newly emerging SARS-CoV-2 variants and the ability to reduce virus transmission. Here we compare immune responses and preclinical efficacy of the mRNA vaccine BNT162b2, the adenovirus-vectored spike vaccine Ad2-spike and the live-attenuated virus vaccine candidate sCPD9 in Syrian hamsters, using both homogeneous and heterologous vaccination regimens. Comparative vaccine efficacy was assessed by employing readouts from virus titrations to single-cell RNA sequencing. Our results show that sCPD9 vaccination elicited the most robust immunity, including rapid viral clearance, reduced tissue damage, fast differentiation of pre-plasmablasts, strong systemic and mucosal humoral responses, and rapid recall of memory T cells from lung tissue after challenge with heterologous SARS-CoV-2. Overall, our results demonstrate that live-attenuated vaccines offer advantages over currently available COVID-19 vaccines.

We have previously reported Lvm1 as a quantitative trait locus (QTL) on chromosome 13 that links to cardiac left ventricular mass (LVM) in a panel of AxB/BxA mouse recombinant inbred strains (RIS). When performing a gene expression QTL (eQTL) analysis, we detected 33 cis-eQTLs that correlated with LVM. Among the latter, a group of eight cis-eQTLs clustered in a genomic region smaller than 6 Mb and surrounding the Lvm1 peak on chr13. Co-variant analysis indicated that all eight genes correlated with the phenotype in a causal rather than a reactive fashion, a finding that (despite its functional interest) did not provide grounds to prioritize any of these candidate genes. As a complementary approach, we performed weighted gene co-expression network analysis, which allowed us to detect 49 modules of highly connected genes. The module that correlated best with LVM: (1) showed linkage to a module QTL whose boundaries matched closely those of the phenotypic Lvm1 QTL on chr13; (2) harbored a disproportionately high proportion of genes originating from a small genomic region on chromosome 13 (including the 8 previously detected cis-eQTL genes); (3) contained genes that, beyond their individual level of expression, correlated with LVM as a function of their inter-connectivity; and (4) showed increased abundance of polymorphic insertion-deletion elements in the same region. Taken together, these data suggest that a domain on chromosome 13 constitutes the biologic principle responsible for the organization and linkage of the gene co-expression module, and indicate a mechanism whereby genetic variants within chromosome domains may associate to phenotypic changes via coordinate changes in the expression of several genes. One other possible implication of these findings is that candidate genes to consider as contributors to a particular phenotype should extend further than those that are closest to the QTL peak.

Little is known about the functions of chromosome Y (chrY) genes beyond their effects on sex and reproduction. In hearts, postpubertal testosterone affects the size of cells and the expression of genes differently in male C57BL/6J than in their C57.Y(A) counterparts, where the original chrY has been substituted with that from A/J mice. We further compared the 2 strains to better understand how chrY polymorphisms may affect cardiac properties, the latter being sexually dimorphic but unrelated to sex and reproduction. Genomic regions showing occupancy with androgen receptors (ARs) were identified in adult male hearts from both strains by chromatin immunoprecipitation. AR chromatin immunoprecipitation peaks (showing significant enrichment for consensus AR binding sites) were mostly strain specific. Measurements of anogenital distances in male pups showed that the biologic effects of perinatal androgens were greater in C57BL/6J than in C57.Y(A). Although perinatal endocrine manipulations showed that these differences contributed to the strain-specific differences in the response of adult cardiac cells to testosterone, the amounts of androgens produced by fetal testes were not different in each strain. Nonetheless, chrY polymorphisms associated in newborn pups' hearts with strain-specific differences in genomic regions showing either AR occupancy, accessible chromatin sites, or trimethylation of histone H3 Lysine 4 marks, as well as with differential expression of 2 chrY-encoded histone demethylases. In conclusion, the effects of chrY on adult cardiac phenotypes appeared to result from an interaction of this chromosome with the organizational programming effects exerted by the neonatal testosterone surge and show several characteristics of being mediated by an epigenetic remodeling of chromatin.

Although gene coexpression domains have been reported in most eukaryotic organisms, data available to date suggest that coexpression rarely concerns more than doublets or triplets of adjacent genes in mammals. Using expression data from hearts of mice from the panel of AxB/BxA recombinant inbred mice, we detected (according to window sizes) 42-53 loci linked to the expression levels of clusters of three or more neighboring genes. These loci thus formed "cis-expression quantitative trait loci (eQTL) clusters" because their position matched that of the genes whose expression was linked to the loci. Compared with matching control regions, genes contained within cis-eQTL clusters showed much greater levels of coexpression. Corresponding regions showed: (1) a greater abundance of polymorphic elements (mostly short interspersed element retrotransposons), and (2) significant enrichment for the motifs of binding sites for various transcription factors, with binding sites for the chromatin-organizing CCCTC-binding factor showing the greatest levels of enrichment in polymorphic short interspersed elements. Similar cis-eQTL clusters also were detected when we used data obtained with several tissues from BxD recombinant inbred mice. In addition to strengthening the evidence for gene expression domains in mammalian genomes, our data suggest a possible mechanism whereby noncoding polymorphisms could affect the coordinate expression of several neighboring genes.

Although the genetic basis of Duchenne muscular dystrophy has been known for almost thirty years, the cellular and molecular mechanisms characterizing the disease are not completely understood and an efficacious treatment remains to be developed. In this study we analyzed proteomics data obtained with the SomaLogic technology from blood serum of a cohort of patients and matched healthy subjects. We developed a workflow based on biomarker identification and network-based pathway analysis that allowed us to describe different deregulated pathways. In addition to muscle-related functions, we identified other biological processes such as apoptosis, signaling in the immune system and neurotrophin signaling as significantly modulated in patients compared with controls. Moreover, our network-based analysis identified the involvement of FoxO transcription factors as putative regulators of different pathways. On the whole, this study provided a global view of the molecular processes involved in Duchenne muscular dystrophy that are decipherable from serum proteome.

Due to the grasshopper effect, the Arctic food chain in Canada is contaminated with persistent organic pollutants (POPs) of industrial origin, including polychlorinated biphenyls and organochlorine pesticides. Exposure to POPs may be a contributor to the greater incidence of poor fetal growth, placental abnormalities, stillbirths, congenital defects and shortened lifespan in the Inuit population compared to non-Aboriginal Canadians. Although maternal exposure to POPs is well established to harm pregnancy outcomes, paternal transmission of the effects of POPs is a possibility that has not been well investigated. We used a rat model to test the hypothesis that exposure to POPs during gestation and suckling leads to developmental defects that are transmitted to subsequent generations via the male lineage. Indeed, developmental exposure to an environmentally relevant Arctic POPs mixture impaired sperm quality and pregnancy outcomes across two subsequent, unexposed generations and altered sperm DNA methylation, some of which are also observed for two additional generations. Genes corresponding to the altered sperm methylome correspond to health problems encountered in the Inuit population. These findings demonstrate that the paternal methylome is sensitive to the environment and that some perturbations persist for at least two subsequent generations. In conclusion, although many factors influence health, paternal exposure to contaminants plays a heretofore-underappreciated role with sperm DNA methylation contributing to the molecular underpinnings involved.

The C57BL/6J.YA/J mouse strain is a chromosome-substituted line where the original male-specific portion of chromosome Y (MSY) from C57BL/6J mice was substituted for that from A/J mice. In hearts from male C57BL/6J.YA/J and C57BL/6J mice, orchidectomy (ORX) affected in a strictly strain-specific fashion the expression a subset of genes showing enrichment for functional categories, including that of circadian rhythms and cardiac contractility. We further tested whether: (1) there were strain-specific differences in cardiac circadian rhythms; (2) strain-dependent differences in the effects of ORX on contractility genes translated into differences in cardiac functions; and (3) differential contractility responses occurred preferentially at times when circadian rhythms also showed strain-specific differences.

The domesticated dog, Canis lupus familiaris, has been selectively bred to produce extreme diversity in phenotype and genotype. Dogs have an immense diversity in weight and height. Specific differences in metabolism have not been characterized in small dogs as compared to larger dogs.

Genetic reference panels are widely used to map complex, quantitative traits in model organisms. We have generated new high-resolution genetic maps of 259 mouse inbred strains from recombinant inbred strain panels (C57BL/6J × DBA/2J, ILS/IbgTejJ × ISS/IbgTejJ, and C57BL/6J × A/J) and chromosome substitution strain panels (C57BL/6J-Chr#, C57BL/6J-Chr#, and C57BL/6J-Chr#). We genotyped all samples using the Affymetrix Mouse Diversity Array with an average intermarker spacing of 4.3 kb. The new genetic maps provide increased precision in the localization of recombination breakpoints compared to the previous maps. Although the strains were presumed to be fully inbred, we found residual heterozygosity in 40% of individual mice from five of the six panels. We also identified de novo deletions and duplications, in homozygous or heterozygous state, ranging in size from 21 kb to 8.4 Mb. Almost two-thirds (46 out of 76) of these deletions overlap exons of protein coding genes and may have phenotypic consequences. Twenty-nine putative gene conversions were identified in the chromosome substitution strains. We find that gene conversions are more likely to occur in regions where the homologous chromosomes are more similar. The raw genotyping data and genetic maps of these strain panels are available at http://churchill-lab.jax.org/website/MDA.

Natural sequence variation within mitochondrial DNA (mtDNA) contributes to human phenotypes and may serve as natural genetic markers in human cells for clonal and lineage tracing. We recently developed a single-cell multi-omic approach, called 'mitochondrial single-cell assay for transposase-accessible chromatin with sequencing' (mtscATAC-seq), enabling concomitant high-throughput mtDNA genotyping and accessible chromatin profiling. Specifically, our technique allows the mitochondrial genome-wide inference of mtDNA variant heteroplasmy along with information on cell state and accessible chromatin variation in individual cells. Leveraging somatic mtDNA mutations, our method further enables inference of clonal relationships among native ex vivo-derived human cells not amenable to genetic engineering-based clonal tracing approaches. Here, we provide a step-by-step protocol for the use of mtscATAC-seq, including various cell-processing and flow cytometry workflows, by using primary hematopoietic cells, subsequent single-cell genomic library preparation and sequencing that collectively take ~3-4 days to complete. We discuss experimental and computational data quality control metrics and considerations for the extension to other mammalian tissues. Overall, mtscATAC-seq provides a broadly applicable platform to map clonal relationships between cells in human tissues, investigate fundamental aspects of mitochondrial genetics and enable additional modes of multi-omic discovery.

Polyphenol-rich foods are part of many nutritional interventions aimed at improving health and preventing cardiometabolic diseases (CMDs). Polyphenols have oxidative, inflammatory, and/or metabolic effects. Research into the chemistry and biology of polyphenol bioactives is prolific but knowledge of their molecular interactions with proteins is limited. We mined public data to (i) identify proteins that interact with or metabolize polyphenols, (ii) mapped these proteins to pathways and networks, and (iii) annotated functions enriched within the resulting polyphenol-protein interactome. A total of 1,395 polyphenols and their metabolites were retrieved (using Phenol-Explorer and Dictionary of Natural Products) of which 369 polyphenols interacted with 5,699 unique proteins in 11,987 interactions as annotated in STITCH, Pathway Commons, and BindingDB. Pathway enrichment analysis using the KEGG repository identified a broad coverage of significant pathways of low specificity to particular polyphenol (sub)classes. When compared to drugs or micronutrients, polyphenols have pleiotropic effects across many biological processes related to metabolism and CMDs. These systems-wide effects were also found in the protein interactome of the polyphenol-rich citrus fruits, used as a case study. In sum, these findings provide a knowledgebase for identifying polyphenol classes (and polyphenol-rich foods) that individually or in combination influence metabolism.

Recent developments in droplet-based microfluidics allow the transcriptional profiling of thousands of individual cells in a quantitative, highly parallel and cost-effective way. A critical, often limiting step is the preparation of cells in an unperturbed state, not altered by stress or ageing. Other challenges are rare cells that need to be collected over several days or samples prepared at different times or locations.

Multi-omics integration is key to fully understand complex biological processes in an holistic manner. Furthermore, multi-omics combined with new longitudinal experimental design can unreveal dynamic relationships between omics layers and identify key players or interactions in system development or complex phenotypes. However, integration methods have to address various experimental designs and do not guarantee interpretable biological results. The new challenge of multi-omics integration is to solve interpretation and unlock the hidden knowledge within the multi-omics data. In this paper, we go beyond integration and propose a generic approach to face the interpretation problem. From multi-omics longitudinal data, this approach builds and explores hybrid multi-omics networks composed of both inferred and known relationships within and between omics layers. With smart node labelling and propagation analysis, this approach predicts regulation mechanisms and multi-omics functional modules. We applied the method on 3 case studies with various multi-omics designs and identified new multi-layer interactions involved in key biological functions that could not be revealed with single omics analysis. Moreover, we highlighted interplay in the kinetics that could help identify novel biological mechanisms. This method is available as an R package netOmics to readily suit any application.