Reference
The Collaborative Cross (CC) is a large (~1,000 line) panel of recombinant inbred (RI) mouse strains being developed through a community effort (Churchill et al. 2004). The CC combines the genomes of eight genetically diverse founder strains A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HlLtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ to capture nearly 90% of the known variation present in laboratory mice. CC strains are derived using a unique funnel breeding scheme. Once inbred, the RI CC lines can be used to generate thousands of potential 'outbred' but completely reproducible genomes through the generation of recombinant inbred crosses (RIX). The designation 'PreCC' is used to describe a mapping population of CC mice that is still at incipient stages of inbreeding.
CTC (2004), Churchill, G. A., et al.. The Collaborative Cross, a community resource for the genetic analysis of complex traits. Nat Genet. 36, 1133-7.
Experiment
Severe Acute Respiratory Syndrome-Coronavirus (SARS-CoV) emerged in 20022003 as the first highly pathogenic zoonotic virus of the 21st century. Infected individuals experienced disease phenotypes ranging from mild respiratory symptoms to severe pulmonary disease including diffuse alveolar damage (DAD), acute respiratory distress syndrome (ARDS), and death (10% mortality rate).
Host genetic variation is known to contribute to differential pathogenesis following infection. Mouse models allow direct assessment of host genetic factors responsible for susceptibility to SARS-CoV. Based on an assessment of early stage lines from the Collaborative Cross (CC) mouse multi-parent population, the authors identified two lines showing highly divergent susceptibilities to SARS-CoV: the resistant CC003/Unc and the susceptible CC053/Unc.
The authors generated 264 (CC003/Unc x CC053/Unc) F2 mice and infected them with SARS-CoV. Weight loss, pulmonary hemorrhage, and viral load were all highly correlated disease phenotypes. Mice were genotyped using MUGA array (Neogen Inc., Lincoln, NE). The authors selected those SNP markers behaving in a biallelic manner between replicate samples of CC003/Unc and CC053/Unc), and, using the argyle package, used the thin.genotypes() function to arrive at a set of 304 biallelic markers evenly spaced across the genome for QTL mapping. They exported these data into the R/QTL package using argyles as.rqtl.genotypes() function, and mapped QTL for each of the measured phenotypic traits using the scanone() function in rqtl.
QTL analysis identified 8 novel QTL (genome coordinates relative to GRCm38/mm10):
Hrsq5 (host response to SARS QTL 5, D3% weight) maps to Chr 18: 27.108062 - 58.694005 Mb with a peak LOD score of 5.55 at 42.852536 Mb (backupUNC181069094). Hrsq5 explains 6.60 of the trait variation.
Hrsq6 (host response to SARS QTL 6, D3% weight) maps to Chr 9: 116.476207 - Telomere with a peak LOD score of 3.11 at 121.771517 Mb (backupJAX00708075). Hrsq6 explains 7% of the trait variation.
Hrsq7 (host response to SARS QTL 7, log titer) maps to Chr 7: 55.169841 - 117.22358 Mb with a peak LOD score of 8.12 at 96.668697 Mb (UNC070369595). Hrsq7 explains 12.30% of the trait variation.
Hrsq8 (host response to SARS QTL 8, log titer) maps to Chr 12: 81.649471 - 108.529109 Mb with a peak LOD score of 4.06 at 88.541688 Mb (UNC120199018). Hrsq8 explains 5.40% of the trait variation.
Hrsq9 (host response to SARS QTL 9, hemorrhage) maps to Chr 15: Centromere - 64.430001 Mb with a peak LOD score of 0.67 at 30.785867 Mb (UNC150077326). Hrsq9 explains 9.10% of the trait variation.
Hrsq10 (host response to SARS QTL 10, D4% weight) maps to Chr 18: 27.108062 - 58.694005 Mb with a peak LOD score of 7.27 at 51.250937 Mb (JAX00083358). Hrsq10 explains 8.50% of the trait variation.
Hrsq11 (host response to SARS QTL 11, log titer) maps to Chr 18: 27.108062 - 58.694005 Mb with a peak LOD score of 7.27 at 51.250937 Mb (JAX00083358). Hrsq11 explains 12.90% of the trait variation.
Hrsq12 (host response to SARS QTL 12, hemorrhage) maps to Chr 18: 24.762824 - 78.29634 Mb with a peak LOD score of 7.27 at 51.250937 Mb (JAX00083358). Hrsq12 explains 6% of the trait variation.
The authors found strong support for additive interactions between Hrs5 and Hrs6 for day 3 weight loss (LOD = 8.27, genome-wide P = 0.05 threshold = 6.25).
The authors found strong support for additive interactions between Hrs9 and Hrs12 for hemorrhage (LOD = 9.43, genome-wide P = 0.05 threshold = 6.4).
The authors found evidence for a full model of interaction (that is both additive and epistatic interactions) for viral titers between Hrs7 and Hrs8 (LOD = 13.3, genome-wide P = 0.05 threshold = 11.4).
The authors found evidence for a full model of interaction (that is both additive and epistatic interactions) for viral titers between as well as between Hrs7 and Hrs11 (LOD = 17.5, genome-wide P = 0.05 threshold = 11.4).
The shared PWK/PhJ haplotype at the proximal end of the Hrsq5, Hrsq10, Hrsq11, Hrsq12 loci functionally reduced the QTL regions to 31.2 - 58.6 Mb, and, at the most highly associated marker (JAX00083358, Chr18: 51.41 Mb), the authors found that the CC003/Unc PWK-derived allele was associated with enhanced disease relative to the CC053/Unc C57BL/6J-derived allele - a case of transgressive segregation.
Hrsq6 had the CC003/Unc haplotype (C57BL/6J) associated with reduced weight loss as compared to the CC053/Unc haplotype (WSB/EiJ).
Hrsq7 showed the CC003/UNC haplotype (PWK/PhJ 55.1 - 69 Mb; C57BL/6J 69 - 78 Mb; 129S1/SvImJ 78 - 90 Mb; C57BL/6J and 129S1/SvImJ/SvImJ 90 - 117.22 Mb) was associated with reduced viral titers as compared to the CC053/Unc haplotype (C57BL/6J and WSB/EiJ uncertainty 55.1 - 58 Mb; WSB/EiJ and PWK/PhJ uncertainty 58 - 81 Mb; WSB/EiJ 81 - 117.22 Mb).
Hrsq8 had the CC003/Unc haplotype (NOD/ShiLtJ) associated with lower viral titers than the CC053/UNC haplotype (WSB/EiJ 81.6 - 88.9 Mb; WSB/EiJ and CAST/EiJ uncertainty 88.9 - 108 Mb).
Hrsq9 had the CC003/Unc haplotype (PWK/PhJ centromere - 30 Mb, NZO/HlLtJ and PWK/PhJ uncertainty 30 - 36 Mb, PWK/PhJ 36 - 64.4 Mb) associated with lower pulmonary hemorrhage as compared to the CC053/Unc haplotype (NOD/ShiLtJ centromere - 22.3 Mb; 129S1/SvImJ 22.3 - 32.2 Mb; CAST/EiJ 32.2 - 64.4 Mb).
The authors identified Ticam2, an adaptor protein in the TLR signaling pathways, as a candidate driving differential disease at the Chr 18 loci. Ticam2-/- mice were highly susceptible to SARS-CoV infection, exhibiting increased weight loss and more pulmonary hemorrhage than control mice.
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