QTLViewer: an interactive webtool for genetic analysis in the Collaborative Cross and Diversity Outbred mouse populations

Vincent, Matthew; Gyuricza, Isabela Gerdes; Keele, Gregory R.; Gatti, Daniel M.; Keller, Mark P.; Broman, Karl W.; Churchill, Gary A.

doi:10.1093/g3journal/jkac146

Cited by 14 publications

(14 citation statements)

References 32 publications

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“…iPSCs also enable differentiation into other cell types, 3-dimensional cell models, organoids, or scaffolded arrays which can be screened across a variety of environmental conditions including other toxicants, drugs, or other culture conditions. It is important to note that while other studies mapping cmQTL were limited by lack of genetic diversity, poor adaptation of some cell types to culture, and the genetic architecture of the population being studied 2,97 , we also found that beyond large effect QTL, our study was underpowered despite previous examples showing sample sizes in this range for molecular phenotypes can detect strong QTL 12,54,98 . This is the result of experimental and residual sources of variance as described above, as well as the limited extensibility of standard dose-response models to diverse populations.…”

Section: Discussionmentioning

confidence: 56%

Cell morphology QTL reveal gene by environment interactions in a genetically diverse cell population

O’Connor,

Keele,

Martin

et al. 2023

Preprint

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Genetically heterogenous cell lines from laboratory mice are promising tools for population-based screening as they offer power for genetic mapping, and potentially, predictive value forin vivoexperimentation in genetically matched individuals. To explore this further, we derived a panel of fibroblast lines from a genetic reference population of laboratory mice (the Diversity Outbred, DO). We then used high-content imaging to capture hundreds of cell morphology traits in cells exposed to the oxidative stress-inducing arsenic metabolite monomethylarsonous acid (MMAIII). We employed dose-response modeling to capture latent parameters of response and we then used these parameters to identify several hundred cell morphology quantitative trait loci (cmQTL). Response cmQTL encompass genes with established associations with cellular responses to arsenic exposure, includingAbcc4andTxnrd1, as well as novel gene candidates likeXrcc2. Moreover, baseline trait cmQTL highlight the influence of natural variation on fundamental aspects of nuclear morphology. We show that the natural variants influencing response include both coding and non-coding variation, and that cmQTL haplotypes can be used to predict response in orthogonal cell lines. Our study sheds light on the major molecular initiating events of oxidative stress that are under genetic regulation, including the NRF2-mediated antioxidant response, cellular detoxification pathways, DNA damage repair response, and cell death trajectories.

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Section: Discussionmentioning

confidence: 56%

Cell morphology QTL reveal gene by environment interactions in a genetically diverse cell population

O’Connor,

Keele,

Martin

et al. 2023

Preprint

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“…We used a modified version of RQTL2 and qtl2qpi to identify chromosomal regions associated with survival after MRSA infection [53, 54]. We used the number of mice within a strain that survived at the end of each day as the phenotype.…”

Section: Resultsmentioning

confidence: 99%

“…We used RQTL2 software with CC genotypes imputed from qtl2qpi to identify genomic regions associated with survival after MRSA infection [59, 60]. Within the CC strains we infected, survival was a highly heritable trait with a broad sense heritability score of 0.38 (Table S4).…”

Section: Resultsmentioning

confidence: 99%

Collaborative Cross mice have diverse phenotypic responses to infection with Methicillin-resistantStaphylococcus aureusUSA300

Nagarajan

Scoggin

Gupta

et al. 2023

Preprint

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Staphylococcus aureus (S. aureus) is an opportunistic pathogen causing diseases ranging from mild skin infections to life-threatening conditions, including endocarditis, pneumonia, and sepsis. To identify host genes modulating this host-pathogen interaction, we infected 25 Collaborative Cross (CC) mouse strains with methicillin-resistant S. aureus (MRSA USA300) and monitored disease progression for seven days. We identified eight ‘susceptible’ CC strains with high bacterial load, tissue damage, and reduced survival. Among the surviving strains, six with minimal colonization were classified as ‘resistant’, while the remaining six tolerated higher organ colonization (‘tolerant’). The kidney was the most heavily colonized organ, but liver colonization was better correlated with reduced survival. We identified four CC strains with sex differences: females survived the study period while males met our euthanasia criteria earlier. In these CC strains, males had more baseline circulating monocytes and red blood cells. We identified several CC strains that may be useful as new models for endocarditis, myocarditis, pneumonia, and resistance to MRSA infection. Resistant strains had higher pre-infection circulating neutrophils than susceptible and tolerant strains. GM-CSF, IL-1-alpha, IL-15, IL-28, and IL-31 levels increased significantly in tolerant strains after infection. Using RNA seq, we identified two pathways, IL-1 and ERK1/ERK2, as potentially involved in the mechanism of tolerance. QTL analysis identified two significant loci, on Chromosomes 18 and 3, involved in early and late survival after infection. We prioritized Npc1 and Ifi44l genes as the strongest candidates influencing survival using variant analysis and mRNA expression data within these intervals.

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“…All analyses were performed using the R package qtl2 101 . Processed data and results are uploaded to the QTLViewer webtool (https://churchilllab.jax.org/qtlviewer/Zimring/RBC; 103 ) for interactive analyses and download. All data and code for the analysis pipeline are available at figshare (https://doi.org/10.6084/m9.figshare.24456619).…”

Section: Star Methodsmentioning

confidence: 99%

Biological and Genetic Determinants of Glycolysis: Phosphofructokinase Isoforms Boost Energy Status of Stored Red Blood Cells and Transfusion Outcomes

Nemkov,

Stephenson,

Earley

et al. 2023

Preprint

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Glycolysis is a central metabolic pathway in health and disease,1an essential one in mature red blood cells (RBCs), which rely on the Embden-Meyerhof-Parnas pathway, i.e., glycolysis, as the sole source of energy generation.2During aging in vivo and in vitro under blood bank conditions,3the adenosine triphosphate (ATP) generated via glycolysis in mitochondria-devoid mature RBCs is essential for the modulation of oxygen kinetics,4deformability2and, ultimately, intra- and extra-vascular hemolysis.3Here we draw upon a cohort of 13,029 volunteers from the Recipient Epidemiology and Donor Evaluation Study (REDS) to identify biological and genetic traits associated with heterogeneity in glycolytic phenotypes. Age, sex and ethnicity influenced glycolysis, with additional effects due to genetic polymorphisms in regions coding for rate-limiting enzymes of glycolysis,1phosphofructokinase 1 (PFKP) and hexokinase 1 (HK1), and for the ADP-ribosyl cyclase CD38. The gene-metabolite associations were validated by testing glycolysis in fresh and stored RBCs from 350 Diversity Outbred mice.5These findings were further corroborated via multi-omics analyses of 1,929 samples at storage day 10, 23 and 42 in 643 RBC units from donors who were selected amongst the index cohort based on their extreme hemolytic propensity. Finally, we show that glycolysis, ATP levels, breakdown and deamination into hypoxanthine are associated with increased hemolytic propensity and vesiculationex vivo, as well as with extravascular hemolysis in vivo, both in healthy autologous transfusion recipients from the Donor Iron Deficiency Study and in 4,700 heterologous critically ill patients receiving blood products from the REDS donors. This work advances our understanding of genetic and non-genetic factors that regulate glycolysis in mature RBCs, a simplified model of mammalian cell metabolism,6a cell type where dysregulated glycolysis holds broader implications in hemolytic disorders, offering potential avenues for novel therapeutic interventions and transfusion strategies.Graphical abstract

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QTLViewer: an interactive webtool for genetic analysis in the Collaborative Cross and Diversity Outbred mouse populations

Cited by 14 publications

References 32 publications

Cell morphology QTL reveal gene by environment interactions in a genetically diverse cell population

Cell morphology QTL reveal gene by environment interactions in a genetically diverse cell population

Collaborative Cross mice have diverse phenotypic responses to infection with Methicillin-resistantStaphylococcus aureusUSA300

Biological and Genetic Determinants of Glycolysis: Phosphofructokinase Isoforms Boost Energy Status of Stored Red Blood Cells and Transfusion Outcomes

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