The Mouse Genome Database: integration of and access to knowledge about the laboratory mouse

Modeling normal mouse uterine contraction and placental perfusion with non-invasive longitudinal dynamic contrast enhancement MRI

BACKGROUND

The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual's entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities.

OBJECTIVE

Our goal is to create a non-invasive preclinical imaging pipeline that can longitudinally probe murine placental health in vivo. We use advanced imaging processing schemes to establish functional biomarkers for non-invasive longitudinal evaluation of placental development.

METHODOLOGY

We implement dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and analysis pipeline to quantify uterine contraction and placental perfusion dynamics. We use optic flow and time-frequency analysis to quantify and characterize contraction-related placental motion. Our novel imaging and analysis pipeline uses subcutaneous administration of gadolinium for steepest slope-based perfusion evaluation, enabling non-invasive longitudinal monitoring.

RESULTS

We demonstrate that the placenta exhibits spatially asymmetric contractile motion that develops from E14.5 to E17.5. Additionally, we see that placental perfusion, perfusion delivery rate, and substrate delivery all increase from E14.5 to E17.5, with the High Perfusion Chamber (HPC) leading the placental changes that occur from E14.5 to E17.5.

DISCUSSION

We advance the placental perfusion chamber paradigm with a novel, physiologically based threshold model for chamber localization and demonstrate spatially varying placental chambers using multiple functional metrics that assess mouse placental development and remodeling throughout gestation.

CONCLUSION

Our pipeline enables the non-invasive, longitudinal assessment of multiple placenta functions from a single imaging session. Our pipeline serves as a key toolbox for advancing research in mouse models of placental disease and disorder.

Modeling Normal Mouse Uterine Contraction and Placental Perfusion with Non-invasive Longitudinal Dynamic Contrast Enhancement MRI

The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual's entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities. Non-invasive imaging that can longitudinally probe murine placental health in vivo are critical to understanding placental development throughout pregnancy. We developed advanced imaging processing schemes to establish functional biomarkers for non-invasive longitudinal evaluation of placental development. We developed a dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) pipeline combined with advanced image process methods to model uterine contraction and placental perfusion dynamics. Our novel imaging pipeline uses subcutaneous administration of gadolinium for steepest-slope based perfusion evaluation. This enables non-invasive longitudinal monitoring. Additionally, we advance the placental perfusion chamber paradigm with a novel physiologically-based threshold model for chamber localization and demonstrate spatially varying placental chambers using multiple functional metrics that assess mouse placental development and continuing remodeling throughout gestation. Lastly, using optic flow to quantify placental motions arisen from uterine contractions in conjunction with time-frequency analysis, we demonstrated that the placenta exhibited asymmetric contractile motion.

Clinical exome sequencing efficacy and phenotypic expansions involving anomalous pulmonary venous return

Anomalous pulmonary venous return (APVR) frequently occurs with other congenital heart defects (CHDs) or extra-cardiac anomalies. While some genetic causes have been identified, the optimal approach to genetic testing in individuals with APVR remains uncertain, and the etiology of most cases of APVR is unclear. Here, we analyzed molecular data from 49 individuals to determine the diagnostic yield of clinical exome sequencing (ES) for non-isolated APVR. A definitive or probable diagnosis was made for 8 of those individuals yielding a diagnostic efficacy rate of 16.3%. We then analyzed molecular data from 62 individuals with APVR accrued from three databases to identify novel APVR genes. Based on data from this analysis, published case reports, mouse models, and/or similarity to known APVR genes as revealed by a machine learning algorithm, we identified 3 genes-EFTUD2, NAA15, and NKX2-1-for which there is sufficient evidence to support phenotypic expansion to include APVR. We also provide evidence that 3 recurrent copy number variants contribute to the development of APVR: proximal 1q21.1 microdeletions involving RBM8A and PDZK1, recurrent BP1-BP2 15q11.2 deletions, and central 22q11.2 deletions involving CRKL. Our results suggest that ES and chromosomal microarray analysis (or genome sequencing) should be considered for individuals with non-isolated APVR for whom a genetic etiology has not been identified, and that genetic testing to identify an independent genetic etiology of APVR is not warranted in individuals with EFTUD2-, NAA15-, and NKX2-1-related disorders.

Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis

BACKGROUND AND HYPOTHESIS

Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes.

STUDY DESIGN

We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score.

STUDY RESULTS

After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores.

CONCLUSIONS

Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

Genome-wide association studies (GWASs) are a valuable tool for understanding the biology of complex human traits and diseases, but associated variants rarely point directly to causal genes. In the present study, we introduce a new method, polygenic priority score (PoPS), that learns trait-relevant gene features, such as cell-type-specific expression, to prioritize genes at GWAS loci. Using a large evaluation set of genes with fine-mapped coding variants, we show that PoPS and the closest gene individually outperform other gene prioritization methods, but observe the best overall performance by combining PoPS with orthogonal methods. Using this combined approach, we prioritize 10,642 unique gene-trait pairs across 113 complex traits and diseases with high precision, finding not only well-established gene-trait relationships but nominating new genes at unresolved loci, such as LGR4 for estimated glomerular filtration rate and CCR7 for deep vein thrombosis. Overall, we demonstrate that PoPS provides a powerful addition to the gene prioritization toolbox.

Evaluation of the Impact of BaP Exposure on the Gut Microbiota and Allergic Responses in an OVA-Sensitized Mouse Model

BACKGROUND

Exposure to environmental pollutants, including benzo[a]pyrene (BaP), has been implicated in allergic diseases and intestinal microbiota homeostasis, but the environment-microbiota-immunity triangular relationship and to what extent BaP-induced remodeling of the gut microbiota contributes to intestinal allergic inflammation remain to be established.

OBJECTIVES

We investigated the impact of BaP on intestinal allergic inflammation and examined the relationship between this effect and gut microbiota dysbiosis. We explored the potential ability of intestinal bacteria to degrade BaP and alleviate cytotoxicity as a detoxification strategy to counteract the effects of BaP exposure.

METHODS

We combined microbiome shotgun metagenomics with animal histological and intestinal allergic inflammatory responses to assess the effects of BaP (50μg/mouse per day) in a 23-d toxicity test in antigen-induced allergic female mice. In addition, genome annotation, quantitative analysis of BaP, and in vitro cytotoxicity-tests using CaCo-2 cells were conducted to infer the role of intestinal bacteria in BaP detoxification.

RESULTS

BaP exposure impacted the taxonomic composition and the functional potential of the gut microbiota and aggravated antigen-induced intestinal allergic inflammatory responses. The level of inflammatory cytokines correlated with the abundance of specific bacterial taxa, including Lachnospiraceae bacterium 28-4 and Alistipes inops. We identified 614 bacteria harboring genes implicated in the degradation of BaP, and 4 of these bacterial strains were shown to significantly reduce the cytotoxicity of BaP to CaCo-2 cells in vitro.

DISCUSSION

Using allergic female mice as a model, we investigated the relationship between BaP, microbiota, and host immune reactions, highlighting the role of gut bacteria in BaP-aggravated allergic reactions. Our findings offer novel insight toward establishing the causal relationship between BaP exposure and the occurrence of allergic disorders. Identifying gut bacteria that degrade BaP may provide new strategies for ameliorating BaP cytotoxicity. https://doi.org/10.1289/EHP11874.

Dysregulated systemic metabolism in a Down syndrome mouse model

OBJECTIVE

Trisomy 21 is one of the most complex genetic perturbations compatible with postnatal survival. Dosage imbalance arising from the triplication of genes on human chromosome 21 (Hsa21) affects multiple organ systems. Much of Down syndrome (DS) research, however, has focused on addressing how aneuploidy dysregulates CNS function leading to cognitive deficit. Although obesity, diabetes, and associated sequelae such as fatty liver and dyslipidemia are well documented in the DS population, only limited studies have been conducted to determine how gene dosage imbalance affects whole-body metabolism. Here, we conduct a comprehensive and systematic analysis of key metabolic parameters across different physiological states in the Ts65Dn trisomic mouse model of DS.

METHODS

Ts65Dn mice and euploid littermates were subjected to comprehensive metabolic phenotyping under basal (chow-fed) state and the pathophysiological state of obesity induced by a high-fat diet (HFD). RNA sequencing of liver, skeletal muscle, and two major fat depots were conducted to determine the impact of aneuploidy on tissue transcriptome. Pathway enrichments, gene-centrality, and key driver estimates were performed to provide insights into tissue autonomous and non-autonomous mechanisms contributing to the dysregulation of systemic metabolism.

RESULTS

Under the basal state, chow-fed Ts65Dn mice of both sexes had elevated locomotor activity and energy expenditure, reduced fasting serum cholesterol levels, and mild glucose intolerance. Sexually dimorphic deterioration in metabolic homeostasis became apparent when mice were challenged with a high-fat diet. While obese Ts65Dn mice of both sexes exhibited dyslipidemia, male mice also showed impaired systemic insulin sensitivity, reduced mitochondrial activity, and elevated fibrotic and inflammatory gene signatures in the liver and adipose tissue. Systems-level analysis highlighted conserved pathways and potential endocrine drivers of adipose-liver crosstalk that contribute to dysregulated glucose and lipid metabolism.

CONCLUSIONS

A combined alteration in the expression of trisomic and disomic genes in peripheral tissues contribute to metabolic dysregulations in Ts65Dn mice. These data lay the groundwork for understanding the impact of aneuploidy on in vivo metabolism.

Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes

Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ([Formula: see text]), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.

Genome Editing and Myocardial Development

Congenital heart disease (CHD) has a strong genetic etiology, making it a likely candidate for therapeutic intervention using genetic editing. Complex genetics involving an orchestrated series of genetic events and over 400 genes are responsible for myocardial development. Cooperation is required from a vast series of genetic networks, and mutations in such can lead to CHD and cardiovascular abnormalities, affecting up to 1% of all live births. Genome editing technologies are becoming better studied and with time and improved logistics, CHD could be a prime therapeutic target. Syndromic, nonsyndromic, and cases of familial inheritance all involve identifiable causative mutations and thus have the potential for genome editing therapy. Mouse models are well-suited to study and predict clinical outcome. This review summarizes the anatomical and genetic timeline of myocardial development in both mice and humans, the potential of gene editing in typical CHD categories, as well as the use of mice thus far in reproducing models of human CHD and correcting the mutations that create them.

Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder

Defining different genetic subtypes of autism spectrum disorder (ASD) can enable the prediction of developmental outcomes. Based on minor physical and major congenital anomalies, we categorize 325 Canadian children with ASD into dysmorphic and nondysmorphic subgroups. We develop a method for calculating a patient-level, genome-wide rare variant score (GRVS) from whole-genome sequencing (WGS) data. GRVS is a sum of the number of variants in morphology-associated coding and non-coding regions, weighted by their effect sizes. Probands with dysmorphic ASD have a significantly higher GRVS compared to those with nondysmorphic ASD (P = 0.03). Using the polygenic transmission disequilibrium test, we observe an over-transmission of ASD-associated common variants in nondysmorphic ASD probands (P = 2.9 × 10^-3). These findings replicate using WGS data from 442 ASD probands with accompanying morphology data from the Simons Simplex Collection. Our results provide support for an alternative genomic classification of ASD subgroups using morphology data, which may inform intervention protocols.

Identifying genes targeted by disease-associated non-coding SNPs with a protein knowledge graph

Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) that play important roles in the genetic heritability of traits and diseases. With most of these SNPs located on the non-coding part of the genome, it is currently assumed that these SNPs influence the expression of nearby genes on the genome. However, identifying which genes are targeted by these disease-associated SNPs remains challenging. In the past, protein knowledge graphs have often been used to identify genes that are associated with disease, also referred to as “disease genes”. Here, we explore whether protein knowledge graphs can be used to identify genes that are targeted by disease-associated non-coding SNPs by testing and comparing the performance of six existing methods for a protein knowledge graph, four of which were developed for disease gene identification. We compare our performance against two baselines: (1) an existing state-of-the-art method that is based on guilt-by-association, and (2) the leading assumption that SNPs target the nearest gene on the genome. We test these methods with four reference sets, three of which were obtained by different means. Furthermore, we combine methods to investigate whether their combination improves performance. We find that protein knowledge graphs that include predicate information perform comparable to the current state of the art, achieving an area under the receiver operating characteristic curve (AUC) of 79.6% on average across all four reference sets. Protein knowledge graphs that lack predicate information perform comparable to our other baseline (genetic distance) which achieved an AUC of 75.7% across all four reference sets. Combining multiple methods improved performance to 84.9% AUC. We conclude that methods for a protein knowledge graph can be used to identify which genes are targeted by disease-associated non-coding SNPs.

Enrichment of Newly Synthesized Proteins following treatment of C2C12 Myotubes with Endotoxin and Interferon-γ

Inflammation in muscle induces the synthesis of mediators that can impair protein synthesis and enhance proteolysis, and when sustained lead to muscle atrophy. Furthermore, muscle-derived mediators that are secreted may participate in disrupting the function of other peripheral organs. Selective identification of newly synthesized proteins can provide insight on biological processes that depend on the continued synthesis of specific proteins to maintain homeostasis as well as those proteins that are up- or down-regulated in response to inflammation. We used puromycin-associated nascent chain proteomics (PUNCH-P) to characterize new protein synthesis in C2C12 myotubes and changes resulting from their exposure to the inflammatory mediators lipopolysaccharide (LPS) and interferon (IFN)-γ for either a short (4 h) or prolonged (16 h) time period. We identified sequences of nascent polypeptide chains belonging to a total of 1523 proteins and report their detection from three independent samples of each condition at each time point. The identified nascent proteins correspond to approximately 15% of presently known proteins in C2C12 myotubes and are enriched in specific cellular components and pathways. A subset of these proteins was identified only in treated samples and has functional characteristics consistent with the synthesis of specific new proteins in response to LPS/IFNγ. Thus, the identification of proteins from their nascent polypeptide chains provides a resource to analyze the role of new synthesis of proteins in both protein homeostasis and in proteome responses to stimuli in C2C12 myotubes. Our results reveal a profile of actively translating proteins for specific cellular components and biological processes in normal C2C12 myotubes and a different enrichment of proteins in response to LPS/IFNγ. Collectively, our data disclose a highly interconnected network that integrates the regulation of cellular proteostasis and reveal a diverse immune response to inflammation in muscle which may underlie the concomitantly observed atrophy and be important in inter-organ communication.

Comparative systeomics to elucidate physiological differences between CHO and SP2/0 cell lines

Omics-based tools were coupled with bioinformatics for a systeomics analysis of two biopharma cell types: Chinese hamster ovary (M-CHO and CHO-K1) and SP2/0. Exponential and stationary phase samples revealed more than 10,000 transcripts and 6000 proteins across these two manufacturing cell lines. A statistical comparison of transcriptomics and proteomics data identified downregulated genes involved in protein folding, protein synthesis and protein metabolism, including PPIA-cyclophilin A, HSPD1, and EIF3K, in M-CHO compared to SP2/0 while cell cycle and actin cytoskeleton genes were reduced in SP2/0. KEGG pathway comparisons revealed glycerolipids, glycosphingolipids, ABC transporters, calcium signaling, cell adhesion, and secretion pathways depleted in M-CHO while retinol metabolism was upregulated. KEGG and IPA also indicated apoptosis, RNA degradation, and proteosomes enriched in CHO stationary phase. Alternatively, gene ontology analysis revealed an underrepresentation in ion and potassium channel activities, membrane proteins, and secretory granules including Stxbpt2, Syt1, Syt9, and Cma1 proteins in M-CHO. Additional enrichment strategies involving ultracentrifugation, biotinylation, and hydrazide chemistry identified over 4000 potential CHO membrane and secretory proteins, yet many secretory and membrane proteins were still depleted. This systeomics pipeline has revealed bottlenecks and potential opportunities for cell line engineering in CHO and SP2/0 to improve their production capabilities.

The ERM protein moesin regulates natural killer cell homeostasis in vivo

Moesin is a member of the ezrin-radixin-moesin (ERM) family of proteins that link plasma membrane proteins with actin filaments in the cell cortex. Hemizygous mutations in the X-linked moesin gene are associated with primary immunodeficiency with T and B cell lymphopenia, which also affects natural killer (NK) cells in most cases. We previously showed that moesin deficiency in mice substantially affects lymphocyte homeostasis, but its impact on NK cells remains unexplored. Here, we found that in moesin-deficient mice, NK cells were decreased in the peripheral blood and bone marrow but increased in the spleen. Analysis of female heterozygous mice showed a selective advantage for moesin-expressing NK cells in the blood. Moesin-deficient NK cells exhibited increased cell death and impaired signaling in response to IL-15, suggesting that moesin regulates NK cell survival through IL-15-mediated signaling. Our findings thus identify moesin as an NK cell homeostasis regulator in vivo.

NREM delta power and AD-relevant tauopathy are associated with shared cortical gene networks

Reduced NREM sleep in humans is associated with AD neuropathology. Recent work has demonstrated a reduction in NREM sleep in preclinical AD, pointing to its potential utility as an early marker of dementia. We test the hypothesis that reduced NREM delta power and increased tauopathy are associated with shared underlying cortical molecular networks in preclinical AD. We integrate multi-omics data from two extensive public resources, a human Alzheimer's disease cohort from the Mount Sinai Brain Bank (N = 125) reflecting AD progression and a (C57BL/6J × 129S1/SvImJ) F2 mouse population in which NREM delta power was measured (N = 98). Two cortical gene networks, including a CLOCK-dependent circadian network, are associated with NREM delta power and AD tauopathy progression. These networks were validated in independent mouse and human cohorts. Identifying gene networks related to preclinical AD elucidate possible mechanisms associated with the early disease phase and potential targets to alter the disease course.

Transcriptome-wide association study reveals two genes that influence mismatch negativity

Mismatch negativity (MMN) is a differential electrophysiological response measuring cortical adaptability to unpredictable stimuli. MMN is consistently attenuated in patients with psychosis. However, the genetics of MMN are uncharted, limiting the validation of MMN as a psychosis endophenotype. Here, we perform a transcriptome-wide association study of 728 individuals, which reveals 2 genes (FAM89A and ENGASE) whose expression in cortical tissues is associated with MMN. Enrichment analyses of neurodevelopmental expression signatures show that genes associated with MMN tend to be overexpressed in the frontal cortex during prenatal development but are significantly downregulated in adulthood. Endophenotype ranking value calculations comparing MMN and three other candidate psychosis endophenotypes (lateral ventricular volume and two auditory-verbal learning measures) find MMN to be considerably superior. These results yield promising insights into sensory processing in the cortex and endorse the notion of MMN as a psychosis endophenotype.

Integrative Analysis Identified Key Schizophrenia Risk Factors from an Abnormal Behavior Mouse Gene Set

Schizophrenia (SCZ) is a severe chronic psychiatric illness with heterogeneous symptoms. However, the pathogenesis of SCZ is unclear, and the number of well-defined SCZ risk factors is limited. We hypothesized that an abnormal behavior (AB) gene set verified by mouse model experiments can be used to better understand SCZ risks. In this work, we carried out an integrative bioinformatics analysis to study two types of risk genes that are either differentially expressed (DEGs) in the case-control study data or carry reported SCZ genetic variants (MUTs). Next, we used RNA-Seq expression data from the hippocampus (HIPPO) and dorsolateral prefrontal cortex (DLPFC) to define the key genes affected by different types (DEGs and MUTs) in different brain regions (DLPFC and HIPPO): DLPFC-kDEG, DLPFC-kMUT, HIPPO-kDEG, and HIPPO-kMUT. The four hub genes (SHANK1, SHANK2, DLG4, and NLGN3) of the biological functionally enriched terms were strongly linked to SCZ via gene co-expression network analysis. Then, we observed that specific spatial expressions of DLPFC-kMUT and HIPPO-kMUT were convergent in the early stages and divergent in the later stages of development. In addition, all four types of key genes showed significantly larger average protein-protein interaction degrees than the background. Comparing the different cell types, the expression of four types of key genes showed specificity in different dimensions. Together, our results offer new insights into potential risk factors and help us understand the complexity and regional heterogeneity of SCZ.

A transcriptome-wide association study implicates specific pre- and post-synaptic abnormalities in schizophrenia

Schizophrenia is a complex highly heritable disorder. Genome-wide association studies (GWAS) have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. We identify a significant correlation between schizophrenia risk and expression at 89 genes in the dorsolateral prefrontal cortex (P ≤ 9.43 × 10-6), including 20 novel genes. Genes whose expression correlate with schizophrenia were enriched for those involved in abnormal CNS synaptic transmission (PFDR = 0.02) and antigen processing and presentation of peptide antigen via MHC class I (PFDR = 0.02). Within the CNS synaptic transmission set, we identify individual significant candidate genes to which we assign direction of expression changes in schizophrenia. The findings provide strong candidates for experimentally probing the molecular basis of synaptic pathology in schizophrenia.

Heparan Sulfate Biosynthesis in Zebrafish

The biosynthesis of heparan sulfate (HS) proteoglycans occurs in the Golgi compartment of cells and will determine the sulfation pattern of HS chains, which in turn will have a large impact on the biological activity of the proteoglycans. Earlier studies in mice have demonstrated the importance of HS for embryonic development. In this review, the enzymes participating in zebrafish HS biosynthesis, along with a description of enzyme mutants available for functional studies, are presented. The consequences of the zebrafish genome duplication and maternal transcript contribution are briefly discussed as are the possibilities of CRISPR/Cas9 methodologies to use the zebrafish model system for studies of biosynthesis as well as proteoglycan biology.

Bio-activating ultrafine grain titanium: RNA sequencing reveals enhanced mechano-activation of osteoconduction on nanostructured substrates

Titanium is essentially absent from biological systems yet reliably integrates into bone. To achieve osseointegration, titanium must activate biological processes without entering cells, defining it as a bio-activating material. Nanostructuring bulk titanium reduces grain size, increases strength, and improves other quantifiable physical properties, including cytocompatibility. The biological processes activated by increasing grain boundary availability were detected with total RNA-sequencing in mouse pre-osteoblasts grown for 72 hours on nanometrically smooth substrates of either coarse grain or nanostructured ultrafine grain titanium. The average grain boundary length under cells on the conventional coarse grain substrates is 273.0 μm, compared to 70,881.5 μm for cells adhered to the nanostructured ultrafine grain substrates; a 260-fold difference. Cells on both substrates exhibit similar expression profiles for genes whose products are critical for mechanosensation and transduction of cues that trigger osteoconduction. Biological process Gene Ontology term enrichment analysis of differentially expressed genes reveals that cell cycle, chromatin modification, telomere maintenance, and RNA metabolism processes are upregulated on ultrafine grain titanium. Processes related to immune response, including apoptosis, are downregulated. Tumor-suppressor genes are upregulated while tumor-promoting genes are downregulated. Upregulation of genes involved in chromatin remodeling and downregulation of genes under the control of the peripheral circadian clock implicate both processes in the transduction of mechanosensory information. Non-coding RNAs may also play a role in the response. Merging transcriptomics with well-established mechanobiology principles generates a unified model to explain the bio-activating properties of titanium. The modulation of processes is accomplished through chromatin remodeling in which the nucleus responds like a rheostat to grain boundary concentration. This convergence of biological and materials science reveals a pathway toward understanding the biotic-abiotic interface and will inform the development of effective bio-activating and bio-inactivating materials.

Polygenic risk for schizophrenia and subcortical brain anatomy in the UK Biobank cohort

Research has shown differences in subcortical brain volumes between participants with schizophrenia and healthy controls. However, none of these differences have been found to associate with schizophrenia polygenic risk. Here, in a large sample (n = 14,701) of unaffected participants from the UK Biobank, we test whether schizophrenia polygenic risk scores (PRS) limited to specific gene-sets predict subcortical brain volumes. We compare associations with schizophrenia PRS at the whole genome level ('genomic', including all SNPs associated with the disorder at a p-value threshold < 0.05) with 'genic' PRS (based on SNPs in the vicinity of known genes), 'intergenic' PRS (based on the remaining SNPs), and genic PRS limited to SNPs within 7 gene-sets previously found to be enriched for genetic association with schizophrenia ('abnormal behaviour,' 'abnormal long-term potentiation,' 'abnormal nervous system electrophysiology,' 'FMRP targets,' '5HT2C channels,' 'CaV2 channels' and 'loss-of-function intolerant genes'). We observe a negative association between the 'abnormal behaviour' gene-set PRS and volume of the right thalamus that survived correction for multiple testing (ß = -0.031, pFDR = 0.005) and was robust to different schizophrenia PRS p-value thresholds. In contrast, the only association with genomic PRS surviving correction for multiple testing was for right pallidum, which was observed using a schizophrenia PRS p-value threshold < 0.01 (ß = -0.032, p = 0.0003, pFDR = 0.02), but not when using other PRS P-value thresholds. We conclude that schizophrenia PRS limited to functional gene sets may provide a better means of capturing differences in subcortical brain volume than whole genome PRS approaches.

The role of copy-number variation in the reinforcement of sexual isolation between the two European subspecies of the house mouse

Reinforcement has the potential to generate strong reproductive isolation through the evolution of barrier traits as a response to selection against maladaptive hybridization, but the genetic changes associated with this process remain largely unexplored. Building upon the increasing evidence for a role of structural variants in adaptation and speciation, we addressed the role of copy-number variation in the reinforcement of sexual isolation evidenced between the two European subspecies of the house mouse. We characterized copy-number divergence between populations of Mus musculus musculus that display assortative mate choice, and those that do not, using whole-genome resequencing data. Updating methods to detect deletions and tandem duplications (collectively: copy-number variants, CNVs) in Pool-Seq data, we developed an analytical pipeline dedicated to identifying genomic regions showing the expected pattern of copy-number displacement under a reinforcement scenario. This strategy allowed us to detect 1824 deletions and seven tandem duplications that showed extreme differences in frequency between behavioural classes across replicate comparisons. A subset of 480 deletions and four tandem duplications were specifically associated with the derived trait of assortative mate choice. These 'Choosiness-associated' CNVs occur in hundreds of genes. Consistent with our hypothesis, such genes included olfactory receptors potentially involved in the olfactory-based assortative mate choice in this system as well as one gene, Sp110, that is known to show patterns of differential expression between behavioural classes in an organ used in mate choice-the vomeronasal organ. These results demonstrate that fine-scale structural changes are common and highly variable within species, despite being under-studied, and may be important targets of reinforcing selection in this system and others. This article is part of the theme issue 'Towards the completion of speciation: the evolution of reproductive isolation beyond the first barriers'.

Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects

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Combining CHD phenotype–driven gene set enrichment and CRISPR knockdown screening in zebrafish is an effective approach to identifying novel CHD genes.

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Mutations affecting genes coding for the WAVE2 protein complex and small GTPase-mediated signaling are associated with LVOTO lesions.

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WAVE2 complex genes brk1, nckap1, and wasf2 and regulators of small GTPase signaling cul3a and racgap1 are critical to zebrafish heart development.

Genetic variants are the primary driver of congenital heart disease (CHD) pathogenesis. However, our ability to identify causative variants is limited. To identify causal CHD genes that are associated with specific molecular functions, the study used prior knowledge to filter de novo variants from 2,881 probands with sporadic severe CHD. This approach enabled the authors to identify an association between left ventricular outflow tract obstruction lesions and genes associated with the WAVE2 complex and regulation of small GTPase-mediated signal transduction. Using CRISPR zebrafish knockdowns, the study confirmed that WAVE2 complex proteins brk1, nckap1, and wasf2 and the regulators of small GTPase signaling cul3a and racgap1 are critical to cardiac development.

Novel Approaches for Identifying the Molecular Background of Schizophrenia

Recent advances in psychiatric genetics have led to the discovery of dozens of genomic loci associated with schizophrenia. However, a gap exists between the detection of genetic associations and understanding the underlying molecular mechanisms. This review describes the basic approaches used in the so-called post-GWAS studies to generate biological interpretation of the existing population genetic data, including both molecular (creation and analysis of knockout animals, exploration of the transcriptional effects of common variants in human brain cells) and computational (fine-mapping of causal variability, gene set enrichment analysis, partitioned heritability analysis) methods. The results of the crucial studies, in which these approaches were used to uncover the molecular and neurobiological basis of the disease, are also reported.

TarGo: network based target gene selection system for human disease related mouse models

Genetically engineered mouse models are used in high-throughput phenotyping screens to understand genotype-phenotype associations and their relevance to human diseases. However, not all mutant mouse lines with detectable phenotypes are associated with human diseases. Here, we propose the “Target gene selection system for Genetically engineered mouse models” (TarGo). Using a combination of human disease descriptions, network topology, and genotype-phenotype correlations, novel genes that are potentially related to human diseases are suggested. We constructed a gene interaction network using protein-protein interactions, molecular pathways, and co-expression data. Several repositories for human disease signatures were used to obtain information on human disease-related genes. We calculated disease- or phenotype-specific gene ranks using network topology and disease signatures. In conclusion, TarGo provides many novel features for gene function prediction.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

Motivation

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease’s (or patient’s) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse.

Results

We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprised of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

Availability and implementation

https://github.com/bio-ontology-research-group/SmuDGE

Reproducibility of CRISPR-Cas9 methods for generation of conditional mouse alleles: a multi-center evaluation

BACKGROUND

CRISPR-Cas9 gene-editing technology has facilitated the generation of knockout mice, providing an alternative to cumbersome and time-consuming traditional embryonic stem cell-based methods. An earlier study reported up to 16% efficiency in generating conditional knockout (cKO or floxed) alleles by microinjection of 2 single guide RNAs (sgRNA) and 2 single-stranded oligonucleotides as donors (referred herein as "two-donor floxing" method).

RESULTS

We re-evaluate the two-donor method from a consortium of 20 laboratories across the world. The dataset constitutes 56 genetic loci, 17,887 zygotes, and 1718 live-born mice, of which only 15 (0.87%) mice contain cKO alleles. We subject the dataset to statistical analyses and a machine learning algorithm, which reveals that none of the factors analyzed was predictive for the success of this method. We test some of the newer methods that use one-donor DNA on 18 loci for which the two-donor approach failed to produce cKO alleles. We find that the one-donor methods are 10- to 20-fold more efficient than the two-donor approach.

CONCLUSION

We propose that the two-donor method lacks efficiency because it relies on two simultaneous recombination events in cis, an outcome that is dwarfed by pervasive accompanying undesired editing events. The methods that use one-donor DNA are fairly efficient as they rely on only one recombination event, and the probability of correct insertion of the donor cassette without unanticipated mutational events is much higher. Therefore, one-donor methods offer higher efficiencies for the routine generation of cKO animal models.

Gene ORGANizer: linking genes to the organs they affect

One of the biggest challenges in studying how genes work is understanding their effect on the physiology and anatomy of the body. Existing tools try to address this using indirect features, such as expression levels and biochemical pathways. Here, we present Gene ORGANizer (geneorganizer.huji.ac.il), a phenotype-based tool that directly links human genes to the body parts they affect. It is built upon an exhaustive curated database that links >7000 genes to ∼150 anatomical parts using >150 000 gene-organ associations. The tool offers user-friendly platforms to analyze the anatomical effects of individual genes, and identify trends within groups of genes. We demonstrate how Gene ORGANizer can be used to make new discoveries, showing that chromosome X is enriched with genes affecting facial features, that positive selection targets genes with more constrained phenotypic effects, and more. We expect Gene ORGANizer to be useful in a variety of evolutionary, medical and molecular studies aimed at understanding the phenotypic effects of genes.

Identification of an early cell fate regulator by detecting dynamics in transcriptional heterogeneity and co-regulation during astrocyte differentiation

There are an increasing number of reports that characterize the temporal behavior of gene expression at the single-cell level during cell differentiation. Despite accumulation of data describing the heterogeneity of biological responses, the dynamics of gene expression heterogeneity and its regulation during the differentiation process have not been studied systematically. To understand transcriptional heterogeneity during astrocyte differentiation, we analyzed single-cell transcriptional data from cells representing the different stages of astrocyte differentiation. When we compared the transcriptional variability of co-expressed genes between the undifferentiated and differentiated states, we found that there was significant increase in transcriptional variability in the undifferentiated state. The genes showing large changes in both "variability" and "correlation" between neural stem cells (NSCs) and astrocytes were found to be functionally involved in astrocyte differentiation. We determined that these genes are potentially regulated by Ascl1, a previously known oscillatory gene in NSCs. Pharmacological blockade of Ntsr2, which is transcriptionally co-regulated with Ascl1, showed that Ntsr2 may play an important role in the differentiation from NSCs to astrocytes. This study shows the importance of characterizing transcriptional heterogeneity and rearrangement of the co-regulation network between different cell states. It also highlights the potential for identifying novel regulators of cell differentiation that will further increase our understanding of the molecular mechanisms underlying the differentiation process.

Expanding the neurodevelopmental phenotypes of individuals with de novo KMT2A variants

De novo loss-of-function (LoF) variants in the KMT2A gene are associated with Wiedemann-Steiner Syndrome (WSS). Recently, de novo KMT2A variants have been identified in sequencing studies of cohorts of individuals with neurodevelopmental disorders (NDDs). However, most of these studies lack the detailed clinical information required to determine whether those individuals have isolated NDDs or WSS (i.e. syndromic NDDs). We performed thorough clinical and neurodevelopmental phenotyping on six individuals with de novo KMT2A variants. From these data, we found that all six patients met clinical criteria for WSS and we further define the neurodevelopmental phenotypes associated with KMT2A variants and WSS. In particular, we identified a subtype of Autism Spectrum Disorder (ASD) in five individuals, characterized by marked rigid, repetitive and inflexible behaviours, emotional dysregulation, externalizing behaviours, but relative social motivation. To further explore the clinical spectrum associated with KMT2A variants, we also conducted a meta-analysis of individuals with KMT2A variants reported in the published literature. We found that de novo LoF or missense variants in KMT2A were significantly more prevalent than predicted by a previously established statistical model of de novo mutation rate for KMT2A. Our genotype-phenotype findings better define the clinical spectrum associated with KMT2A variants and suggest that individuals with de novo LoF and missense variants likely have a clinically unrecognized diagnosis of WSS, rather than isolated NDD or ASD alone. This highlights the importance of a clinical genetic and neurodevelopmental assessment for individuals with such variants in KMT2A.

Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids

The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.

Genetic variants differentially associated with rheumatoid arthritis and systemic lupus erythematosus reveal the disease-specific biology

Two rheumatic autoimmune diseases, rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), have distinct clinical features despite their genetic similarities. We hypothesized that disease-specific variants exclusively associated with only one disease could contribute to disease-specific phenotypes. We calculated the strength of disease specificity for each variant in each disease against the other disease using summary association statistics reported in the largest genome-wide association studies of RA and SLE. Most of highly disease-specific associations were explained by non-coding variants that were significantly enriched within regulatory regions (enhancers or H3K4me3 histone modification marks) in specific cell or organ types. (e.g., In RA, regulatory T primary cells, CD4+ memory T primary cells, thymus and lung; In SLE, CD19+ B primary cells, mobilized CD34+ primary cells, regulatory T primary cells and monocytes). Consistently, genes in the disease-specific loci were significantly involved in T cell- and B cell-related gene sets in RA and SLE. In summary, this study identified disease-specific variants between RA and SLE, and provided statistical evidence for disease-specific cell types, organ and gene sets that may drive the disease-specific phenotypes.

A gene expression signature in developing Purkinje cells predicts autism and intellectual disability co-morbidity status

Autism spectrum disorder (ASD) is a complex neurodevelopmental disease whose underpinning molecular mechanisms and neural substrates are subject to intense scrutiny. Interestingly, the cerebellum has emerged as one of the key brain regions affected in ASD. However, the genetic and molecular mechanisms that link the cerebellum to ASD, particularly during development, remain poorly understood. To gain insight into the genetic and molecular mechanisms that might link the cerebellum to ASD, we analysed the transcriptome dynamics of a developing cell population highly enriched for Purkinje cells of the mouse cerebellum across multiple timepoints. We identified a single cluster of genes whose expression is positively correlated with development and which is enriched for genes associated with ASD. This ASD-associated gene cluster was specific to developing Purkinje cells and not detected in the mouse neocortex during the same developmental period, in which we identified a distinct temporally regulated ASD gene module. Furthermore, the composition of ASD risk genes within the two distinct clusters was significantly different in their association with intellectual disability (ID), consistent with the existence of genetically and spatiotemporally distinct endophenotypes of ASD. Together, our findings define a specific cluster of ASD genes that is enriched in developing PCs and predicts co-morbidity status.

Transcriptional Heterogeneity of Cryptococcus gattii VGII Compared with Non-VGII Lineages Underpins Key Pathogenicity Pathways

The transcriptional profiles of related pathogens and their responses to host-induced stresses underpin their pathogenicity. Expression differences between related pathogens during host interaction can indicate when and how these genes contribute to virulence, ultimately informing new and improved treatment strategies for those diseases. In this paper, we compare the transcriptional profiles of five isolates representing four lineages of C. gattii in rich media. Our analyses identified key processes, including those involving cell capsule, ergosterol production, and melanin, that are differentially expressed between lineages, and we found that VGII has the most distinct profile in terms of numbers of differentially expressed genes. All lineages have also undergone subfunctionalization for several paralogs, including capsule biosynthesis and attachment genes. Most genes appeared downregulated during coincubation with macrophages, with the largest decrease observed for capsule attachment genes, which appeared to be coordinated with a stress response, as all lineages also upregulated oxidative stress response genes. Furthermore, VGII upregulated many genes that are linked to ergosterol biosynthesis and switched from expression of the laccase LAC1 to expression of LAC2 ex vivo. Finally, we saw a pronounced increase in the FosB/Jun/Egr1 regulatory proteins at early time points in bone marrow-derived macrophages, marking a role in the host response to C. gattii. This work highlights the dynamic roles of key C. gattii virulence genes in response to macrophages.

Cryptococcus gattii is a pathogenic yeast of humans and other animals which causes disease predominantly in immunocompetent hosts. Infection begins when aerosolized yeast or spores enter the body, triggering an immune response, including engulfment by macrophages. To understand the early transcriptional signals in both the yeast and its mammalian host, we performed a time-course dual-transcriptome sequencing (RNA-seq) experiment for four lineages of C. gattii (lineages VGI to IV) interacting with mouse macrophages at 1, 3, and 6 h postinfection. Comparisons of in vitro to ex vivo gene expression levels indicated that lineage VGII is transcriptionally divergent from non-VGII lineages, including differential expression of genes involved in capsule synthesis, capsule attachment, and ergosterol production. Several paralogous genes demonstrated subfunctionalization between lineages, including upregulation of capsule biosynthesis-related gene CAP2 and downregulation of CAP1 in VGIII. Isolates also compensate for lineage-specific gene losses by overexpression of genetically similar paralogs, including overexpression of capsule gene CAS3 in VGIV, which have lost the CAS31 gene. Differential expression of one in five C. gattii genes was detected following coincubation with mouse macrophages; all isolates showed high induction of oxidative-reduction functions and downregulation of capsule attachment genes. We also found that VGII switches expression of two laccase paralogs (from LAC1 to LAC2) during coincubation of macrophages. Finally, we found that mouse macrophages respond to all four lineages of C. gattii by upregulating FosB/Jun/Egr1 regulatory proteins at early time points. This report highlights the evolutionary breadth of expression profiles among the lineages of C. gattii and the diversity of transcriptional responses at this host-pathogen interface.

IMPORTANCE The transcriptional profiles of related pathogens and their responses to host-induced stresses underpin their pathogenicity. Expression differences between related pathogens during host interaction can indicate when and how these genes contribute to virulence, ultimately informing new and improved treatment strategies for those diseases. In this paper, we compare the transcriptional profiles of five isolates representing four lineages of C. gattii in rich media. Our analyses identified key processes, including those involving cell capsule, ergosterol production, and melanin, that are differentially expressed between lineages, and we found that VGII has the most distinct profile in terms of numbers of differentially expressed genes. All lineages have also undergone subfunctionalization for several paralogs, including capsule biosynthesis and attachment genes. Most genes appeared downregulated during coincubation with macrophages, with the largest decrease observed for capsule attachment genes, which appeared to be coordinated with a stress response, as all lineages also upregulated oxidative stress response genes. Furthermore, VGII upregulated many genes that are linked to ergosterol biosynthesis and switched from expression of the laccase LAC1 to expression of LAC2 ex vivo. Finally, we saw a pronounced increase in the FosB/Jun/Egr1 regulatory proteins at early time points in bone marrow-derived macrophages, marking a role in the host response to C. gattii. This work highlights the dynamic roles of key C. gattii virulence genes in response to macrophages.

IDGenetics: a comprehensive database for genes and mutations of intellectual disability related disorders

Intellectual disability (ID) is one of the most prevalent chronic developmental brain disorders or phenotype of syndromic ID, affecting nearly 1-2% of the general population worldwide. Over recent decades, tremendous effort and high-throughput platforms have been devised to explore the complex heterogeneity, numerous genes and variants have been associated with the ID, especially de novo mutations and copy number variants. An organized resource containing the increasing genetic data is imperative to assist ID research. In this study, the integrative and annotated intellectual disability database has been developed, named 'IDGenetics', which contains known information about ID, including 815 genes and 17102 variants associated with 918 clinical diseases (3001 clinical phenotype) collected from 3822 publications and ID-related databases. Furthermore, in-depth data mining was performed to obtain an understanding of each entry, including functional annotation, gene/disease/phenotype network establishment and overlap analysis focusing on comorbidity. 1478 candidate genes (483 high-confidence and 995 low-confidence) were collected and prioritized by adopting the annotations of 12 functional prediction tools and algorithm. In addition, IDGenetics database provides concise search methods, convenient browsing functions, intuitive graphical displays and constantly updated features. IDGenetics will be a valuable and integrative resource for deciphering the genetic and functional architecture of ID and the improvement of clinical diagnosis, intervention and treatment.

Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection

Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population.

Mechanisms of action of Coxiella burnetii effectors inferred from host-pathogen protein interactions

Coxiella burnetii is an obligate Gram-negative intracellular pathogen and the etiological agent of Q fever. Successful infection requires a functional Type IV secretion system, which translocates more than 100 effector proteins into the host cytosol to establish the infection, restructure the intracellular host environment, and create a parasitophorous vacuole where the replicating bacteria reside. We used yeast two-hybrid (Y2H) screening of 33 selected C. burnetii effectors against whole genome human and murine proteome libraries to generate a map of potential host-pathogen protein-protein interactions (PPIs). We detected 273 unique interactions between 20 pathogen and 247 human proteins, and 157 between 17 pathogen and 137 murine proteins. We used orthology to combine the data and create a single host-pathogen interaction network containing 415 unique interactions between 25 C. burnetii and 363 human proteins. We further performed complementary pairwise Y2H testing of 43 out of 91 C. burnetii-human interactions involving five pathogen proteins. We used the combined data to 1) perform enrichment analyses of target host cellular processes and pathways, 2) examine effectors with known infection phenotypes, and 3) infer potential mechanisms of action for four effectors with uncharacterized functions. The host-pathogen interaction profiles supported known Coxiella phenotypes, such as adapting cell morphology through cytoskeletal re-arrangements, protein processing and trafficking, organelle generation, cholesterol processing, innate immune modulation, and interactions with the ubiquitin and proteasome pathways. The generated dataset of PPIs-the largest collection of unbiased Coxiella host-pathogen interactions to date-represents a rich source of information with respect to secreted pathogen effector proteins and their interactions with human host proteins.

The Mouse Tumor Biology Database: A Comprehensive Resource for Mouse Models of Human Cancer

Research using laboratory mice has led to fundamental insights into the molecular genetic processes that govern cancer initiation, progression, and treatment response. Although thousands of scientific articles have been published about mouse models of human cancer, collating information and data for a specific model is hampered by the fact that many authors do not adhere to existing annotation standards when describing models. The interpretation of experimental results in mouse models can also be confounded when researchers do not factor in the effect of genetic background on tumor biology. The Mouse Tumor Biology (MTB) database is an expertly curated, comprehensive compendium of mouse models of human cancer. Through the enforcement of nomenclature and related annotation standards, MTB supports aggregation of data about a cancer model from diverse sources and assessment of how genetic background of a mouse strain influences the biological properties of a specific tumor type and model utility. Cancer Res; 77(21); e67-70. ©2017 AACR.

Transcriptional memory of cells of origin overrides β-catenin requirement of MLL cancer stem cells

While β-catenin has been demonstrated as an essential molecule and therapeutic target for various cancer stem cells (CSCs) including those driven by MLL fusions, here we show that transcriptional memory from cells of origin predicts AML patient survival and allows β-catenin-independent transformation in MLL-CSCs derived from hematopoietic stem cell (HSC)-enriched LSK population but not myeloid-granulocyte progenitors. Mechanistically, β-catenin regulates expression of downstream targets of a key transcriptional memory gene, Hoxa9 that is highly enriched in LSK-derived MLL-CSCs and helps sustain leukemic self-renewal. Suppression of Hoxa9 sensitizes LSK-derived MLL-CSCs to β-catenin inhibition resulting in abolishment of CSC transcriptional program and transformation ability. In addition, further molecular and functional analyses identified Prmt1 as a key common downstream mediator for β-catenin/Hoxa9 functions in LSK-derived MLL-CSCs. Together, these findings not only uncover an unexpectedly important role of cells of origin transcriptional memory in regulating CSC self-renewal, but also reveal a novel molecular network mediated by β-catenin/Hoxa9/Prmt1 in governing leukemic self-renewal.

Whole exome sequencing in 342 congenital cardiac left sided lesion cases reveals extensive genetic heterogeneity and complex inheritance patterns

BACKGROUND

Left-sided lesions (LSLs) account for an important fraction of severe congenital cardiovascular malformations (CVMs). The genetic contributions to LSLs are complex, and the mutations that cause these malformations span several diverse biological signaling pathways: TGFB, NOTCH, SHH, and more. Here, we use whole exome sequence data generated in 342 LSL cases to identify likely damaging variants in putative candidate CVM genes.

METHODS

Using a series of bioinformatics filters, we focused on genes harboring population-rare, putative loss-of-function (LOF), and predicted damaging variants in 1760 CVM candidate genes constructed a priori from the literature and model organism databases. Gene variants that were not observed in a comparably sequenced control dataset of 5492 samples without severe CVM were then subjected to targeted validation in cases and parents. Whole exome sequencing data from 4593 individuals referred for clinical sequencing were used to bolster evidence for the role of candidate genes in CVMs and LSLs.

RESULTS

Our analyses revealed 28 candidate variants in 27 genes, including 17 genes not previously associated with a human CVM disorder, and revealed diverse patterns of inheritance among LOF carriers, including 9 confirmed de novo variants in both novel and newly described human CVM candidate genes (ACVR1, JARID2, NR2F2, PLRG1, SMURF1) as well as established syndromic CVM genes (KMT2D, NF1, TBX20, ZEB2). We also identified two genes (DNAH5, OFD1) with evidence of recessive and hemizygous inheritance patterns, respectively. Within our clinical cohort, we also observed heterozygous LOF variants in JARID2 and SMAD1 in individuals with cardiac phenotypes, and collectively, carriers of LOF variants in our candidate genes had a four times higher odds of having CVM (odds ratio = 4.0, 95% confidence interval 2.5-6.5).

CONCLUSIONS

Our analytical strategy highlights the utility of bioinformatic resources, including human disease records and model organism phenotyping, in novel gene discovery for rare human disease. The results underscore the extensive genetic heterogeneity underlying non-syndromic LSLs, and posit potential novel candidate genes and complex modes of inheritance in this important group of birth defects.

Diverse type 2 diabetes genetic risk factors functionally converge in a phenotype-focused gene network

Type 2 Diabetes (T2D) constitutes a global health burden. Efforts to uncover predisposing genetic variation have been considerable, yet detailed knowledge of the underlying pathogenesis remains poor. Here, we constructed a T2D phenotypic-linkage network (T2D-PLN), by integrating diverse gene functional information that highlight genes, which when disrupted in mice, elicit similar T2D-relevant phenotypes. Sensitising the network to T2D-relevant phenotypes enabled significant functional convergence to be detected between genes implicated in monogenic or syndromic diabetes and genes lying within genomic regions associated with T2D common risk. We extended these analyses to a recent multiethnic T2D case-control exome of 12,940 individuals that found no evidence of T2D risk association for rare frequency variants outside of previously known T2D risk loci. Examining associations involving protein-truncating variants (PTV), most at low population frequencies, the T2D-PLN was able to identify a convergent set of biological pathways that were perturbed within four of five independent T2D case/control ethnic sets of 2000 to 5000 exomes each. These same pathways were found to be over-represented among both known monogenic or syndromic diabetes genes and genes within T2D-associated common risk loci. Our study demonstrates convergent biology amongst variants representing different classes of T2D genetic risk. Although convergence was observed at the pathway level, few of the contributing genes were found in common between different cohorts or variant classes, most notably between the exome variant sets which suggests that future rare variant studies may be better focusing their power onto a single population of recent common ancestry.

Sequence analysis of chromosome 1 revealed different selection patterns between Chinese wild mice and laboratory strains

Both natural and artificial selection play a critical role in animals' adaptation to the environment. Detection of the signature of selection in genomic regions can provide insights for understanding the function of specific phenotypes. It is generally assumed that laboratory mice may experience intense artificial selection while wild mice more natural selection. However, the differences of selection signature in the mouse genome and underlying genes between wild and laboratory mice remain unclear. In this study, we used two mouse populations: chromosome 1 (Chr 1) substitution lines (C1SLs) derived from Chinese wild mice and mouse genome project (MGP) sequenced inbred strains and two selection detection statistics: Fst and Tajima's D to identify the signature of selection footprint on Chr 1. For the differentiation between the C1SLs and MGP, 110 candidate selection regions containing 47 protein coding genes were detected. A total of 149 selection regions which encompass 7.215 Mb were identified in the C1SLs by Tajima's D approach. While for the MGP, we identified nearly twice selection regions (243) compared with the C1SLs which accounted for 13.27 Mb Chr 1 sequence. Through functional annotation, we identified several biological processes with significant enrichment including seven genes in the olfactory transduction pathway. In addition, we searched the phenotypes associated with the 47 candidate selection genes identified by Fst. These genes were involved in behavior, growth or body weight, mortality or aging, and immune systems which align well with the phenotypic differences between wild and laboratory mice. Therefore, the findings would be helpful for our understanding of the phenotypic differences between wild and laboratory mice and applications for using this new mouse resource (C1SLs) for further genetics studies.

Muscle-relevant genes marked by stable H3K4me2/3 profiles and enriched MyoD binding during myogenic differentiation

Post-translational modifications of histones play a key role in the regulation of gene expression during development and differentiation. Numerous studies have shown the dynamics of combinatorial regulation by transcription factors and histone modifications, in the sense that different combinations lead to distinct expression outcomes. Here, we investigated gene regulation by stable enrichment patterns of histone marks H3K4me2 and H3K4me3 in combination with the chromatin binding of the muscle tissue-specific transcription factor MyoD during myogenic differentiation of C2C12 cells. Using k-means clustering, we found that specific combinations of H3K4me2/3 profiles over and towards the gene body impact on gene expression and marks a subset of genes important for muscle development and differentiation. By further analysis, we found that the muscle key regulator MyoD was significantly enriched on this subset of genes and played a repressive role during myogenic differentiation. Among these genes, we identified the pluripotency gene Patz1, which is repressed during myogenic differentiation through direct binding of MyoD to promoter elements. These results point to the importance of integrating histone modifications and MyoD chromatin binding for coordinated gene activation and repression during myogenic differentiation.

Genetic association study of exfoliation syndrome identifies a protective rare variant at LOXL1 and five new susceptibility loci

Exfoliation syndrome (XFS) is the most common known risk factor for secondary glaucoma and a major cause of blindness worldwide. Variants in two genes, LOXL1 and CACNA1A, have previously been associated with XFS. To further elucidate the genetic basis of XFS, we collected a global sample of XFS cases to refine the association at LOXL1, which previously showed inconsistent results across populations, and to identify new variants associated with XFS. We identified a rare protective allele at LOXL1 (p.Phe407, odds ratio (OR) = 25, P = 2.9 × 10^-14) through deep resequencing of XFS cases and controls from nine countries. A genome-wide association study (GWAS) of XFS cases and controls from 24 countries followed by replication in 18 countries identified seven genome-wide significant loci (P < 5 × 10^-8). We identified association signals at 13q12 (POMP), 11q23.3 (TMEM136), 6p21 (AGPAT1), 3p24 (RBMS3) and 5q23 (near SEMA6A). These findings provide biological insights into the pathology of XFS and highlight a potential role for naturally occurring rare LOXL1 variants in disease biology.

Diverse application of MRI for mouse phenotyping

Small animal models, particularly mouse models, of human diseases are becoming an indispensable tool for biomedical research. Studies in animal models have provided important insights into the etiology of diseases and accelerated the development of therapeutic strategies. Detailed phenotypic characterization is essential, both for the development of such animal models and mechanistic studies into disease pathogenesis and testing the efficacy of experimental therapeutics. MRI is a versatile and noninvasive imaging modality with excellent penetration depth, tissue coverage, and soft tissue contrast. MRI, being a multi-modal imaging modality, together with proven imaging protocols and availability of good contrast agents, is ideally suited for phenotyping mutant mouse models. Here we describe the applications of MRI for phenotyping structural birth defects involving the brain, heart, and kidney in mice. The versatility of MRI and its ease of use are well suited to meet the rapidly increasing demands for mouse phenotyping in the coming age of functional genomics. Birth Defects Research 109:758-770, 2017. © 2017 Wiley Periodicals, Inc.

1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10^-8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples.

MYC-driven inhibition of the glutamate-cysteine ligase promotes glutathione depletion in liver cancer

How MYC reprograms metabolism in primary tumors remains poorly understood. Using integrated gene expression and metabolite profiling, we identify six pathways that are coordinately deregulated in primary MYC-driven liver tumors: glutathione metabolism; glycine, serine, and threonine metabolism; aminoacyl-tRNA biosynthesis; cysteine and methionine metabolism; ABC transporters; and mineral absorption. We then focus our attention on glutathione (GSH) and glutathione disulfide (GSSG), as they are markedly decreased in MYC-driven tumors. We find that fewer glutamine-derived carbons are incorporated into GSH in tumor tissue relative to non-tumor tissue. Expression of GCLC, the rate-limiting enzyme of GSH synthesis, is attenuated by the MYC-induced microRNA miR-18a. Inhibition of miR-18a in vivo leads to increased GCLC protein expression and GSH abundance in tumor tissue. Finally, MYC-driven liver tumors exhibit increased sensitivity to acute oxidative stress. In summary, MYC-dependent attenuation of GCLC by miR-18a contributes to GSH depletion in vivo, and low GSH corresponds with increased sensitivity to oxidative stress in tumors. Our results identify new metabolic pathways deregulated in primary MYC tumors and implicate a role for MYC in regulating a major antioxidant pathway downstream of glutamine.

Mouse Genome Informatics (MGI): Resources for Mining Mouse Genetic, Genomic, and Biological Data in Support of Primary and Translational Research

The Mouse Genome Informatics (MGI), resource ( www.informatics.jax.org ) has existed for over 25 years, and over this time its data content, informatics infrastructure, and user interfaces and tools have undergone dramatic changes (Eppig et al., Mamm Genome 26:272-284, 2015). Change has been driven by scientific methodological advances, rapid improvements in computational software, growth in computer hardware capacity, and the ongoing collaborative nature of the mouse genomics community in building resources and sharing data. Here we present an overview of the current data content of MGI, describe its general organization, and provide examples using simple and complex searches, and tools for mining and retrieving sets of data.