Genome Wide Identification of SARS-CoV Susceptibility Loci Using the Collaborative Cross

Lisa E Gralinski, Martin T Ferris, David L Aylor, Alan C Whitmore, Richard Green, Matthew B Frieman, Damon Deming, Vineet D Menachery, Darla R Miller, Ryan J Buus, Timothy A Bell, Gary A Churchill, David W Threadgill, Michael G Katze, Leonard McMillan, William Valdar, Mark T Heise, Fernando Pardo-Manuel de Villena, Ralph S Baric, Lisa E Gralinski, Martin T Ferris, David L Aylor, Alan C Whitmore, Richard Green, Matthew B Frieman, Damon Deming, Vineet D Menachery, Darla R Miller, Ryan J Buus, Timothy A Bell, Gary A Churchill, David W Threadgill, Michael G Katze, Leonard McMillan, William Valdar, Mark T Heise, Fernando Pardo-Manuel de Villena, Ralph S Baric

Abstract

New systems genetics approaches are needed to rapidly identify host genes and genetic networks that regulate complex disease outcomes. Using genetically diverse animals from incipient lines of the Collaborative Cross mouse panel, we demonstrate a greatly expanded range of phenotypes relative to classical mouse models of SARS-CoV infection including lung pathology, weight loss and viral titer. Genetic mapping revealed several loci contributing to differential disease responses, including an 8.5Mb locus associated with vascular cuffing on chromosome 3 that contained 23 genes and 13 noncoding RNAs. Integrating phenotypic and genetic data narrowed this region to a single gene, Trim55, an E3 ubiquitin ligase with a role in muscle fiber maintenance. Lung pathology and transcriptomic data from mice genetically deficient in Trim55 were used to validate its role in SARS-CoV-induced vascular cuffing and inflammation. These data establish the Collaborative Cross platform as a powerful genetic resource for uncovering genetic contributions of complex traits in microbial disease severity, inflammation and virus replication in models of outbred populations.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. PreCC and founder strain phenotypes.
Fig 1. PreCC and founder strain phenotypes.
(A) Weight loss is shown as percent of starting weight at day four post infection, individual preCC mice are shown in open diamonds and mean values for founders are shown in color. All CAST/EiJ mice died or were humanely euthanized before day four post infection. (B) Log transformed lung titer at day four post infection in individual preCC mice and founders, dashed line indicates the limit of detection at 100 PFU per lung. Individual preCC mice are shown in open diamonds, mean values for the founders are color coded by strain. (C) Lung titer vs. weight loss at day four post infection. Individual preCC mice are indicated in open diamonds, mean values for the founder strains are shown in color. The dashed line indicates the limit of detection at 100 PFU per lung.
Fig 2. Lung pathology in select preCC…
Fig 2. Lung pathology in select preCC mice.
(A). OR63f51—normal parenchyma. (B). OR181f61—airway debris and cuffing and edema surrounding the associated vasculature. (C) OR220f57—denuded airway blocked with debris. (D) OR380f64 –perivascular cuffing including eosinophilia. (E) OR941f69 –alveolitis including hyaline membrane formation, arrows point to hyaline membranes. (F) OR5030f128 –normal airway and associated vasculature.
Fig 3. Phenotypic relationships.
Fig 3. Phenotypic relationships.
Heat map of the relationships between lung pathology, titer and weight loss in the preCC. Yellow indicates positive correlation and blue indicates negative correlation.
Fig 4. SARS QTL.
Fig 4. SARS QTL.
Shown are LOD curves for each of three SARS-CoV associated phenotypes: (A) Eosinophilia, with HrS3 on chromosome 15 responsible for 26% of phenotypic variation; (B) Viral titer with HrS2 on chromosome 16 accounting for 22% of variation; and (C) Perivascular Cuffing, with HrS1 (black curve) accounting for 26% of phenotypic variation, and HrS4 (blue curve) accounting for 21% of phenotypic variation. In A and B, the upper horizontal dashed lines correspond to the genome-wide p = 0.05 significance threshold and the lower dashed lines correspond to a significance threshold of p = 0.1. In C the black dashed line corresponds to a genome-wide p = 0.05 significance threshold for HrS1 and the blue dashed line corresponds to the genome-wide significance threshold of p = 0.05 for Hrs4, when conditioned on HrS1.
Fig 5. Trim55 knockout phenotypes.
Fig 5. Trim55 knockout phenotypes.
(A) Trim55-/- and C57BL/6J control mice show similar weight loss over four days of infection. Trim55-/- are shown in gray, C57BL/6J controls are shown in black. (B) No differences were observed in lung titer at day four post infection. (C) Hematoxylin and eosin stained lung sections from Trim55-/- mice display less vascular cuffing than do those from C57BL/6J controls (p<0.05, t-test). (A-C). Three to ten Trim55-/- and C57BL/6J biological replicates were used, experiments were repeated at least three times. (D) SARS-CoV-infected Trim55-/- mice (n = 6) have lower percentages of monocytes (p<0.01, t-test), specifically Ly6C low staining monocytes (p = 0.001, t-test), in their lungs than do C57BL/6J controls (n = 6) as measured by flow cytometry. Mock infected mice have similar levels of monocytes and Ly6C low staining monocytes, respectively (p = 0.83 and p = 0.37, t-test). Experiment performed once. Data in A, B and D are means, error bars show standard error of the mean.
Fig 6. Transcriptional analysis.
Fig 6. Transcriptional analysis.
(A) A heat map showing a comparison of functionally enriched biological pathways between Trim55-/- and C57BL/6J mice at days two and four post infection based on RNA expression levels in the lung. Three mice used per condition, per timepoint. Experiment performed once. Relative expression of all DE genes (log2 FC of 1 or greater and FDR < .05, Trim55-/- vs C57BL/6J) involved in granulocyte adhesion and diapedesis at day two (B) or four (C) post infection.

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