Genetic analysis of hyperoxic acute lung injury survival in reciprocal intercross mice

Daniel R. Prows, Amanda P. Hafertepen, Abby V. Winterberg, William J. Gibbons Jr., Chunyan Liu, Todd G. Nick


Acute lung injury (ALI) and its most severe presentation, acute respiratory distress syndrome, represent a full spectrum of a complex and devastating illness, with associated mortality that still hovers around 30–40%. Even supplemental O2, a routine and necessary therapy for such patients, paradoxically causes lung injury. The detrimental effects of O2 have established hyperoxic ALI (HALI) as a conventional model to study neonatal and adult forms of respiratory distress syndromes in experimental animals. To confront the high ALI mortality problem quite differently, we recently identified a mouse model (sensitive C57BL/6J and resistant 129X1/SvJ mice) to assess the genetic complexity of HALI and to identify genes affecting strain survival differences. Segregation analysis of 840 F2 mice generated from all four possible intercrosses between C57BL/6J and 129X1/SvJ mice demonstrated that survival time is a quantitative trait with decreased penetrance, and significant sex, cross, and parent-of-origin effects. Quantitative trait locus (QTL) analyses of the total F2 population identified three highly significant (named Shali1, Shali2 and Shali3, for Survival to hyperoxic acute lung injury) and one significant (Shali4) linkage. Analysis of F2 subpopulations further identified a male-specific QTL (Shali5). QTL allelic comparisons supported cross and sex effects and were consistent with imprinting. Genome-wide pairwise analysis predicted additive gene-gene interactions between the QTLs and also revealed a significant epistatic interaction with an otherwise unlinked region. QTL results confirmed that both parental strains contribute dominant resistance alleles to their offspring to determine individual HALI susceptibility.

  • acute respiratory distress syndrome
  • imprinting
  • quantitative trait locus analysis
  • sex effect

the course from early acute lung injury (ALI) to its most critical presentation, the acute respiratory distress syndrome (ARDS), represents a continuum of increasing lung injury severity, primarily distinguished by the degree of hypoxemia. Clinical studies for numerous promising therapeutic agents have been disappointing to date; indeed, no pharmacological agents have significantly improved survival rates (6, 14). As a result, conventional therapy primarily includes supportive measures aimed at maintaining cellular and physiological function (i.e., gas exchange, organ perfusion, and aerobic metabolism) while the lung injury resolves (5, 8, 17, 43). The remarkable improvements in supportive care have led to a significant decrease in mortality over the past decade (5), yet the lack of a concomitant pharmacological regimen has kept the mortality rate unacceptably high, with most studies reporting a death rate of 30–40% (2, 5, 8, 17, 30, 32, 34). Mortality associated with and attributable to ALI was estimated at 7.4 deaths per 100,000 in 1996 (22). A more recent estimate was at least four times the earlier finding, with an annual US mortality rate of 74,500/yr for ALI and 59,000/yr for ARDS (31), ranking ALI in the top 10 causes of adult deaths in the US.

A number of studies have identified advanced age as an independent predictor of hospital death in patients with ALI and ARDS (31, 33, 34, 49). Already one-half of all patient days in the intensive care unit (ICU) are incurred by patients older than 65 yr of age (1). Respiratory failure is a common indication for admittance to the ICU, and ALI and ARDS make up a significant proportion of those patients receiving mechanical ventilation. Therefore, ALI/ARDS will be an increasingly important cause of morbidity and mortality as our population continues to age and represents a significant public health issue. The potential impact of ALI on health care was highlighted by an estimate that in 25 yr the annual incidence of ALI will be 335,000 cases, leading to 147,000 deaths/yr in the US (31). Given this startling projection and the current rate of progress to advance our understanding of ALI pathobiology, additional research strategies are essential to improve management of this increasing health care burden.

One strategy to investigate the complex nature of ALI has involved candidate gene association studies, which test genes initially identified by their involvement in the disease pathogenesis. Results from association studies support the idea that genetic predisposition contributes to ALI susceptibility and severity (10, 18, 21, 28, 38). Nevertheless, the candidate gene approach is limited to assessing one gene at a time for a complex trait that clearly involves multiple genes and the environment, and it assumes that the major gene of importance is known and can be directly or indirectly assessed for its role in the trait. A more conventional genetic method to analyze complex traits such as ALI is to use genome-wide linkage mapping. However, phenotypic variance, genetic heterogeneity, incomplete gene penetrance, and gene-gene and gene-environmental interactions, combined with low incidence and a lack of affected families with ALI, make linkage mapping studies in human populations impractical.

To avoid many of these problems in human populations, inbred mice have been used in genetic studies of ALI (7, 12, 13, 15, 16, 23). ALI is an outcome of diverse causes, and many seemingly similar insults likely incite different mechanisms. We have established several mouse models of oxidant-induced ALI to delineate genes affecting survival (26, 27, 45). A mouse model of hyperoxic ALI (HALI) survival is identified in the companion paper to the present article (24). In this model, C57BL/6J (B) mice are sensitive to the lethal effects of continuous hyperoxia (>95% O2), surviving ∼4–5 days and all succumbing by 150 h. 129X1/SvJ (S) inbred mice are significantly more resistant; one-fourth of S mice survived longer than any B mouse, with some surviving >10 days. Segregation analysis of 840 F2 mice generated from all four intercrosses demonstrated that HALI survival time is a multigenic trait with a complex inheritance pattern, which includes decreased penetrance and significant sex, cross, and parent-of-origin effects. Additional genetic and quantitative trait locus (QTL) analyses were performed on the separate and combined F2 populations derived from the B and S strains. These analyses identified five genetic regions significantly linked to HALI survival. Pairwise analysis demonstrated several additive interactions among the QTLs and revealed a significant epistatic interaction between a major QTL on chromosome 1 and an otherwise undetected locus on chromosome 18. This mouse model will allow us to further resolve these QTLs and their interactions and to better assess the complex genetic and epigenetic factors contributing to HALI mortality.



The mice used in these genetic analyses (n = 840 F2) are described in the companion paper (24), but are briefly summarized here. From a screen of 18 inbred mouse strains, C57BL/6J (B) mice were identified as sensitive, whereas 129X1/SvJ (S) mice were significantly more resistant to HALI mortality. Crosses of these strains (the B-S model) were used to generate mice for initial genetic and segregation analyses and subsequent QTL analysis. First, reciprocal F1 lines were generated by breeding B females to S males (B.S) and S females to B males (S.B). A mean survival time (MST) difference between these reciprocal F1 mice suggested a parent-of-origin effect, so reciprocal F1 offspring were systematically bred to generate ∼200 mice for each of the four possible F2 crosses (i.e., BS × BS, BS × SB, SB × BS, and SB × SB; female F1 listed first) for genetic studies. Total males and females were nearly equal for all F2 populations, and included 106 males and 107 females for BS.BS, 105 males and 116 females for BS.SB, 97 males and 98 females for SB.BS, and 107 males and 102 females for SB.SB.

Hyperoxia Exposure

Mice were exposed in their original shoe box cages (up to 4 mice/cage) with food and water ad libitum. Shoe box cages were placed in a 0.13-m3 Plexiglas inhalation chamber (constructed per specifications by Stellar Plastics, Detroit, MI) and exposed to >95% O2 until death. The O2 concentration in the chamber was continuously monitored and self-regulated with a ProOx 110 (Biospherix, Redfield, NY) portable O2 monitor, which was calibrated as needed before each exposure with a two-point method of room air and 100% O2. The exposure was monitored at routine intervals, such that half the time difference between checks was within 5% error of the overall exposure time. Accordingly, the survival time for each mouse was recorded as the median exposure time between the current and previous check. For mice obtained from the Jackson Laboratory, exposures were initiated at least 1 wk after receipt and by 12 wk of age. Mice bred in-house were exposed between 6 and 12 wk of age. Exposures were continued until all mice within the chamber were dead. Breeding and exposures of mice included in these studies occurred over a period of ∼4 yr. Mice were handled in accordance with protocols approved by the Institutional Animal Care and Use Committee of Cincinnati Children's Hospital Medical Center.

DNA Preparation

After death of all mice within the chamber, a tail sample was retrieved from each mouse and stored at −80°C for subsequent genotype studies. Genomic DNA was isolated with a commercial DNA extraction kit (Wizard Genomic DNA, Promega, Madison, WI). Samples were analyzed for purity [absorbance at 260 and 280 nm (A260/A280)] and DNA content (A260) with a 96-well quartz plate and a SpectraMAX 190 spectrophotometer (Molecular Devices, Sunnyvale, CA). DNA was diluted either to 20 ng/μl for PCR products separated by agarose gel electrophoresis or to 5 ng/μl for PCR using fluorescent genotyping (ABI, Applied Biosystems, Foster City, CA).

Genotype Analysis

We performed routine PCR to genotype F2 progeny for microsatellite markers dispersed nearly evenly throughout the mouse genome (details on numbers of markers and resolution of coverage are given in QTL Mapping and Linkage Analyses). Primer pairs, chosen based on known polymorphisms between the B and S strains, were purchased from Research Genetics/Invitrogen (Frederick, MD) or IDT (Coralville, IA). PCR was performed in 15-μl volumes in 96-well plates (Bio-Rad) with a 4-block thermocycler (Bio-Rad, model PTC-225 or PTC-240). The final concentration for each reaction was 10 mM Tris·HCl (pH 8.3), 50 mM KCl, 1.5 mM MgCl2, each dNTP at 0.2 mM (Promega), 1× RediLoad (Invitrogen), and each microsatellite primer at 0.132 μM. This reaction mixture was added to ∼100 ng (5 μl of 20 ng/μl) genomic DNA and 0.6125 U of Taq DNA polymerase (New England Biolabs, Beverly, MA). The final mixtures were initially denatured at 94°C for 3 min, followed by 36–38 cycles of 94°C for 30 s, 55°C for 45 s, and 72°C for 30 s. A final elongation step at 72°C for 7 min was followed by refrigeration at 4°C until gel analysis. PCR products were differentiated on 2.5–4% agarose (ISC BioExpress, Kaysville, UT) gels and visualized by ethidium bromide staining. A resolution of ∼5% difference in allele size was possible with agarose. For markers <5% different in allele sizes between strains, PCR was performed with fluorescent primers synthesized by ABI and the protocols provided. Separation of PCR products was performed at the Cincinnati Children's Hospital DNA Core Facility with an ABI-3730xL sequencer, and fluorescent genotypes were ascertained with GeneMapper software (V3.5, ABI).

QTL Mapping and Linkage Analyses

To analyze individual and collective F2 groups, and to screen for gene-gene interactions within and between F2 populations, all 840 F2 mice were initially typed for 65 polymorphic microsatellite markers distributed at 20–25 cM intervals across the entire genome, including the X chromosome. All phenotype (i.e., survival times) and genotype data were then analyzed for main-effect QTLs with the freely available R/qtl (4) and MapManager QTX (20) computer packages. QTL analysis was performed on raw and natural log-transformed data, with no significant differences in results; therefore, results of raw data are reported. Regions on chromosomes 1, 2, 4, 9, 15, and 17 had logarithm of the odds (LOD) scores of ∼2.0 or more, so additional microsatellite markers around the peaks of these intervals were genotyped. A total of 97 markers were genotyped for all 840 F2 mice (Supplemental Table 1; supplemental data for this article are available online at the Physiological Genomics website). Chromosomes 1 and 4 were more densely typed as an attempt to further define these QTL interval(s); eight additional markers were typed on chromosome 1 (for a total of 13 markers) and chromosome 4 (for a total of 12 markers). After additional markers were typed LOD scores for chromosomes 1, 4, 9, and 15 improved, whereas those for chromosomes 2 and 17 did not change significantly. As was seen in the reciprocal F1 mice, MSTs and phenotype ratios (resistant-to-sensitive mice) for the separate F2 mating groups suggested that a parent-of-origin effect was involved in the overall HALI survival (24). Therefore, offspring from all four F2 mating schemes were analyzed separately and in groups derived from a common F1 dam or F1 sire (i.e., B.S dam = BS.BS and BS.SB; B.S sire = BS.BS and SB.BS; S.B dam = SB.SB and SB.BS; and S.B sire = SB.SB and BS.SB), hereafter referred to as the four combined F2 groups.

To assess gene-gene interactions, including additivity and epistasis, genome-wide scans for all marker pairs were carried out on the total F2 population with R/qtl (i.e., scantwo function) and MapManager QTX (interaction function). Empirical threshold significance values for pairwise interactions were determined in the respective programs with 10,000 permutations of the data set. Pairwise analysis in R/qtl was performed in parallel, using a Perl script and MPI libraries to spread the computations over several processors in a Linux cluster. Results from these multiprocessors were then concatenated to yield the overall empirical threshold values.

QTL Genotype Analysis for Allelic Effects

To gain insight into the contribution of each QTL and combination of QTLs to the overall survival time difference in the F2 populations, QTL genotype analysis was performed, as previously described (25, 44). This procedure directly assessed the difference in survival time (in hours) associated with each particular QTL genotype (i.e., allelic effects). In this analysis, each QTL was assumed to be located at a microsatellite marker near the peak LOD score (i.e., the representative QTL marker) for the identified highly significant and significant QTLs (i.e., D1Mit303, D1Mit34, D4Mit308, D9Mit137, and D15Mit175), as determined by initial marker regression analysis with MapManager QTX. MSTs for groups of mice with the same genotype at each QTL or combination of QTL peak markers were calculated and then compared with the MSTs of mice with the other possible genotypes to determine the contributions of these QTLs to the overall survival time. Other than specific genotypes at the desired loci, the remainder of the genome differs for each mouse within these groups. A significant difference between groups suggests that the QTL(s) has a role in the overall phenotype.

Statistical Analyses

MSTs and SE are presented for all groups. Multiway ANOVA was used to compare MSTs (dependent variable) in each locus subset (D1Mit303 and D4Mit308) with cross, sex, genotype, and two-way interactions of cross with genotype and sex with genotype as independent variables. One-way ANOVA was used to compare MSTs (dependent variable) of one (D1Mit303 or D4Mit308)- or two (D1Mit303 + D4Mit308)-QTL genotypes (independent variables). QTL genotype comparisons within D1Mit303 and D4Mit308 were also done by one-way ANOVA with MST as the dependent variable and sex or cross (or combined cross) as the independent variable. Tukey-Kramer post hoc adjustments for multiple comparisons were used to maintain the overall family-wise type I error rate at 0.05.


QTL Analysis

No differences in results were found after natural log transformation, so individual survival times were used directly. The total F2 population (n = 840) was analyzed for linkage with R/qtl (4) and MapManager QTX (20) computer packages; only slight, nonsignificant differences in peak LOD scores were noted between these programs; R/qtl results are presented. Results from the genome-wide QTL analysis of the total F2 population are displayed in Fig. 1A. Empirical threshold significance values were established from the results of 10,000 permutations of the total F2 data. Threshold LOD scores of 4.0, 3.3, and 3.0 were set as highly significant, significant, and suggestive for linkage to HALI survival time, respectively, for the total F2 data set. Given these threshold values, the total F2 data set identified three highly significant QTLs, one each on chromosome 1 (near D1Mit303, LOD = 9.4), chromosome 4 (near D4Mit308, LOD = 6.4), and chromosome 15 (between D15Mit175 and D15Mit5, LOD = 4.8) (Fig. 1, BD). In addition, one significant linkage (Fig. 1E) was identified on chromosome 9 (at D9Mit137, LOD = 3.7). The highly significant QTLs on chromosomes 1, 4, and 15 were named Shali13, for Survival to hyperoxic acute lung injury 1, 2, and 3, respectively, and the significant QTL on chromosome 9 was named Shali4.

Fig. 1.

Linkage analysis results. A: genome-wide logarithm of the odds (LOD) plot of hyperoxic acute lung injury (HALI) survival time in the total B-S-derived F2 population (n = 840) from R/qtl (4). Highly significant (LOD score >4.0; solid line) and significant (LOD score >3.3; dashed line) thresholds were established by performing 10,000 permutations of the total F2 data set. B–E: individual LOD plots of the chromosomes with highly significant (chromosomes 1, 4, and 15; B–D, respectively) and significant (chromosomes 9; E) linkages for HALI survival time. Symbols represent MIT microsatellite marker positions (MGI map locations) along the chromosome. The support interval (SI) is displayed along the x-axis, and it represents the approximate megabase pair span encompassing a bidirectional 1.5 LOD score drop from the quantitative trait locus (QTL) peak.

The large F2 population of mice generated as part of the original study design also allowed us to run separate genome-wide QTL analyses on males, females, the four individual F2 crosses, and the four combined F2 crosses. The genome-wide plots of these analyses are presented in Supplemental Fig. 1, and a summary of the results is given in Table 1, relative to the QTLs identified in the total F2 analysis. Males and females showed similar LOD scores for the QTLs on chromosomes 9 and 15, but did not reach significance. However, males and females differed for the QTLs on chromosomes 1 and 4 (Fig. 2). Shali1 was highly significant in females (LOD = 6.6) and significant in males (LOD = 3.9). Interestingly, males also showed significant linkage on chromosome 1 at 32 Mbp (LOD = 4.0) and at 174 Mbp (LOD = 3.5), whereas females did not (Fig. 2A). Both these peaks coincided with peaks in the total F2 data set, although the peak at 32 Mbp may not be distinct from the peak at 63 Mbp (i.e., D1Mit303). The peak at 174 Mbp was significant in males (LOD = 3.5) but was nonexistent in females (LOD = 0.3). Although the total F2 data set did not reach significance (LOD = 3.0), the 174-Mbp peak certainly represents a second male-specific significant QTL on chromosome 1; this male-specific QTL was named Shali5. On chromosome 4, Shali2 was highly significant in males (LOD = 4.9) but only suggestive for linkage in females (LOD = 3.2). Two other regions on chromosome 4 differed between males and females—the peak at 63 Mbp was significant in males (LOD = 3.8) but not in females (LOD = 2.5); a peak at 140 Mbp had suggestive linkage in females (LOD = 3.2) but not in males (LOD = 2.6; Fig. 2B). These three regions correspond to the three peaks on chromosome 4 in the total F2 analysis (Fig. 1C) and suggest that Shali2 represents at least two distinct genes.

Fig. 2.

LOD score differences in males and females for chromosomes 1 (A) and 4 (B). Chromosome-wide LOD plots of males and females for the 2 chromosomes housing the major HALI survival time QTLs. Total males (n = 417; dashed line, ○) and total females (n = 423; solid line, •) show differences in linkage thresholds for each QTL. Females had a single QTL peak (at D1Mit303) on chromosome 1 with a highly significant linkage (LOD score = 6.6). Besides this peak (which reached a LOD score = 4.0), males had 2 other significant linkages on chromosome 1, at 32 and 174 Mbp (Shali5, male specific). Females did not reach significance anywhere on chromosome 4, but males had a highly significant and a significant linkage (total region named Shali2). QTL SIs are similar to the total F2 population.

View this table:
Table 1.

QTL analysis results of separate and combined F2 populations

LOD score significance also differed for the separate F2 crosses (Table 1 and Supplemental Fig. 1, B and C). The BS.BS and BS.SB F2 groups had suggestive LOD scores (3.1 and 3.3, respectively). The chromosome 1 QTL was highly significant in SB.BS mice (LOD = 5.0) but was absent in SB.SB mice (LOD = 0.8). The chromosome 4 QTL was highly significant (LOD = 4.5) in the SB.SB F2, but none of the other three crosses even reached suggestive linkage (LOD scores 1.8–2.9). To further assess these cross effects, QTL analysis was also performed on the four combined F2 groups (Table 1 and Supplemental Fig. 1, D and E). Only the group generated from an S.B sire did not reach significance for Shali1 on chromosome 1, and only the group generated from a B.S dam did not reach significance for Shali2 on chromosome 4. Shali3 on chromosome 15 was significant or suggestive for all groups except the group from an S.B dam. The S.B dam group was suggestive for linkage to Shali4, but no other combined F2 group reached any level of significance for Shali4 (Table 1).

We next looked for evidence of additive and/or epistatic interactions in the total F2 data set with R/qtl; the associated heat maps generated from R/qtl are presented in Fig. 3, with the genome-wide results in Fig. 3A. Epistatic LOD scores for all pairwise marker comparisons are displayed above the diagonal line, and joint LOD scores (additive + epistatic LOD scores) are plotted below the diagonal line. A closer view of the pairwise results for the QTL-containing chromosomes 1, 4, 9, and 15 is presented in Fig. 3B. Joint LOD scores were highly significant for Shali1 with Shali2 (LOD = 17.5), Shali3 (LOD = 15.9), or Shali4 (LOD = 13.4). In addition, Shali1 was highly significant for additive effects with Shali5 at the distal end of chromosome 1 (LOD = 17.3). Although additive, no significant epistatic interactions were identified between the five significant QTLs. However, a significant epistatic interaction was uncovered between D18Mit152 on chromosome 18 and the chromosome 1 QTL. By itself, D18Mit152 had a LOD score of 0.1; but when it was combined with D1Mit236 (near the peak of the QTL on chromosome 1; LOD score of 7.2), the two markers gave the highest interaction LOD score (5.8), with a significant two-locus joint LOD score of 13.8 (Fig. 3C).

Fig. 3.

Gene-gene interactions: additive effects and epistasis. The total F2 data set was analyzed for pairwise interactions with R/qtl (4). A: genome-wide LOD plot of the total F2 data set. Top left: pairwise LOD score for epistatic interactions (“twoscan”). Bottom right: joint (additive + epistasis) LOD scores. B: a closer look at the 4 QTL-containing chromosomes; additive effects, but no epistatic interactions, are evident. C: a closer look at the significant epistatic interaction between markers on chromosomes 1 and 18 (hardly noticeable on the genome-wide plot in A). Color intensity scales for each plot are displayed on right: left scale represents “epistatic LOD score,” and right scale represents the “joint LOD score.”

QTL Genotype Analysis

To estimate the contribution of each QTL and combination of QTLs to overall survival time, QTL genotype analysis was performed. For this analysis, the separate (Figs. 4 and 5) and combined (Fig. 6) allelic effects (i.e., the genotype effect on the overall survival time) of the peak markers for Shali1 and Shali2 on chromosomes 1 and 4, respectively, were determined for all F2 populations. As predicted by QTL analysis of the total F2 population, mice that were homozygous S at the peak marker for Shali1 (D1Mit303) were more resistant (MST = 144.2 h) than mice that were homozygous B (MST = 120.0 h) for this marker (Fig. 4A). Mice heterozygous at D1Mit303 were intermediate in phenotype (MST = 128.7 h). In fact, the groups of mice that were homozygous S at D1Mit303 were always the most resistant of the three genotypes for all F2 populations (Fig. 4, BD). Unexpectedly, F2 mice that were homozygous B for the Shali2 peak marker (D4Mit308) demonstrated resistance (B-B = 139.9 h), compared with heterozygous (131.2 h) or homozygous S (119.8 h) mice (Fig. 5A). Again, in all F2 populations, the groups of mice that were B-B for D4Mit308 were always the most resistant genotype at this marker (Fig. 5, BD). As can be seen when comparing Figs. 4 and 5, D1Mit303 and D4Mit308 nearly mirrored each other, with equal and opposite effects on survival time.

Fig. 4.

Allelic effects of the Shali1 peak marker in all F2 populations. Survival times (±SE) were determined for mice with the same genotype (i.e., S-S or B-B) for the peak marker representing the major QTL on chromosome 1 (D1Mit303). A: total F2. B: males and females, C: the 4 separate F2 crosses. D: the 4 combined F2 crosses. y-Axis is the same in all plots for direct comparisons of survival times. Within each plot, bars labeled with the same letters are significantly different from each other (P < 0.05). B-B vs. S-S genotypes differed from each other in all F2 groups (unlabeled, except in A).

Fig. 5.

Allelic effects of the Shali2 peak marker in all F2 populations. Survival times (±SE) were determined for mice with the same genotype (i.e., S-S or B-B) for the peak marker representing the major QTL on chromosome 4 (D4Mit308). A: total F2. B: males and females. C: the 4 separate F2 crosses. D: the 4 combined F2 crosses. y-Axis is the same in all plots for direct comparisons of survival times. Within each plot, bars labeled with the same letters are significantly different from each other (P < 0.05). B-B vs. S-S genotypes differed from each other in all F2 groups (unlabeled, except in A).

Fig. 6.

Combined allelic effects for the highly significant QTLs on chromosomes 1 and 4 in the total F2 population, males, females, and the separate F2 crosses. Survival times were determined for mice with each of the 9 possible genotypes for the peak markers representing the 2 major QTLs in total (A), males (B), females (C), and separate F2 crosses (D–G). D1Mit303 and D4Mit308 are MIT microsatellite markers that map near the QTL peaks for the two highly significant linkages. SS = homozygous for 129X1/SvJ at marker; BB = homozygous for C57BL/6J at marker; SB = heterozygous at marker. y-Axis is the same in all plots for direct comparisons of survival times.

This unexpected result strongly suggested that the sensitive B strain contains one or more resistance genes near the chromosome 4 QTL peak marker. If this is the case, one would predict that mice homozygous S for D1Mit303 and homozygous B for D4Mit308 (i.e., SS-BB) would be the most resistant for a 2-QTL model. This was exactly the case: mice SS-BB for these two loci showed a 54.6-h higher MST in the total F2 population compared with mice with the reciprocal genotype, i.e., BB-SS at the same two markers (Fig. 6A). Mice with any of the other seven genotypes at these two loci showed intermediate survival times compared with mice with reciprocal SS-BB and BB-SS genotypes. The allelic differences found in the total F2 population for the chromosome 1 and chromosome 4 QTL markers were also seen in all other F2 subpopulations (Fig. 6, BG). For example, the specific MST differences between males and females and between the various F2 cohorts at these two loci (i.e., SS-BB vs. BB-SS) differed dramatically: 53.0 h for males and 50.6 h for females; 36.1 h for BS.BS, 41.3 h for BS.SB, 53.9 h for SB.SB, and 67.1 h for SB.BS mice (Fig. 6). Similar results were determined for the four combined F2 groups (Supplemental Fig. 2).

We next assessed the 3-QTL effects in the total F2 population for the five significant loci on chromosomes 1, 4, 9, and 15. Six combinations were tested, keeping Shali1 in all three-QTL models (Table 2). Four of these 3-QTL combinations yielded increases in MSTs over the respective 2-QTL models, with differences between the most resistant and most sensitive genotypes of at least 62 h; three of the best four combinations included the two QTLs on chromosome 1. The best 3-QTL combinations were Shali1, Shali5, and Shali2 (represented as 1-1′-4, for their respective chromosome locations), Shali1, Shali5, and Shali3 (1-1′-15), Shali1, Shali2, and Shali4 (1-4-9), and Shali1, Shali2, and Shali3 (1-4-15). Shali1 was always S-S for the most resistance and B-B or S-B for the most sensitivity, whereas the Shali2-5 loci were primarily B-B or B-S for the most resistance and S-S for the most sensitivity. The results support that the Shali loci are all dominant, with the S allele dominant for Shali1 and the B allele dominant for Shali2, Shali4, and Shali5 loci. Shali3 on chromosome 15 was equivocal. The results also clearly demonstrate that different combinations of resistance QTL alleles can give increased resistance well above the MST of the S strain. Four-QTL models yielded too few mice for each of the 81 genotype combinations to be helpful. In total, these results provide strong evidence that increased survival in F2 offspring is due to dominant resistance alleles contributed by both parental strains.

View this table:
Table 2.

Allelic effects with 3-QTL models

Results of Statistical Comparisons of Shali1 and Shali2 Peak Markers

Multiway ANOVA.

A significant interaction between cross and genotype was identified for D1Mit303 (P = 0.02) and a significant interaction between sex and genotype for D4Mit308 (P = 0.03). Pairwise comparisons for the combinations of cross and genotype demonstrated that the MST of the S-S genotype in SB.BS was significantly higher than any other genotype and cross combinations (10 of 11 comparisons with P < 0.001 and 1 with P = 0.0015). The MSTs of B-B and S-B did not differ between the four F2 crosses, and S-S was not different among the three crosses other than SB.BS. For D1Mit303, no interaction was found between sex and genotype. However, the main effect of sex was significant; males had a significantly higher MST than females (P < 0.0001). For D4Mit308, no interaction occurred between cross and genotype, but the main effect of cross was significant. The MST of SB.BS mice was significantly higher than mice from all other crosses (P < 0.007 for all 3 comparisons). In addition, a significant interaction exists between genotype and sex for D4Mit308. The MST of the B-B genotype in males was significantly higher than other genotype and sex combinations (P ≤ 0.0031 for all 5 comparisons). Thus it is possible that a sex-specific locus exists on chromosome 4 as well. For combined loci, the MST of mice with SS-BB at D1Mit303-D4Mit308 was significantly higher than mice with any other two-point genotype (P ≤ 0.032 for all 8 comparisons). Mice BB-SS at D1Mit303-D4Mit308 had the lowest MST of all nine genotypes.

One-way ANOVA.

Significance values for genotype comparisons within each F2 population for D1Mit303 and D4Mit308 are presented in Supplemental Table 2. Among all 11 F2 populations, only SB.SB mice were not significant for differences between the three genotypes at D1Mit303. All 11 F2 populations were significant for the genotype differences for D4Mit308 and the combined D1Mit303 and D4Mit308 loci.

Results for pairwise comparisons of MST for B-B or S-S genotypes at D1Mit303 and D4Mit308 between the F2 populations are listed in Supplemental Table 3 and displayed in Figs. 4 and 5. The MSTs of BS.BS or BS.SB mice are consistently different from those of SB.BS mice, but no MST differences were found for B-B or S-S between BS.BS and BS.SB or for BS.BS and SB.SB. The MST for B-B differs significantly at both loci for BS.BS vs. SB.BS, BS.SB vs. SB.BS, and BS.SB vs. SB.SB. For the S-S genotype, the MSTs of BS.BS, BS.SB, and SB.SB do not differ from each other, but all differ from SB.BS. The S-S and B-B genotypes at both loci differed between S.B dam and B.S dam combined groups; only the B-B genotype at D1Mit303 did not differ between S.B dam and S.B sire combined groups.


Although improvements in supportive measures have significantly decreased mortality and morbidity associated with ALI/ARDS over the past decade, the death rate remains unacceptably high. As a different approach to confront the enduring mortality rate of ALI, we previously initiated genetic studies in mice (25, 27, 45). Many methods and agents have been used to directly or indirectly induce ALI, but it is intriguing that supplemental O2—a common supportive therapy in patients with ALI and other critical illnesses—is itself limited by its extremely detrimental effects on the lung at higher levels. For this reason, HALI is routinely used to model respiratory distress in experimental animal studies. Continuous >95% O2 was used in these studies to induce ALI, and survival time was adopted as the end phenotype. Thus, going into this long-term project, we saw that an established genetic mouse model had the potential to identify genes directly contributing to HALI mortality and that the results may be applicable to other oxidative causes of ALI mortality. Such knowledge could also lead to insights into the mechanisms of HALI and be used to optimize supplemental O2 therapy in critically ill patients.

To begin to identify genes controlling survival time to continuous hyperoxia, the B-S mouse model of HALI was established for genetic analyses. Reciprocal F1 mice from these strains suggested a parent-of-origin effect. To pursue this, a total of 840 F2 mice, including 197 mice or more from each of the four possible F2 crosses, were produced and tested for HALI survival. Segregation analysis demonstrated that important genes controlling HALI survival time were segregating in the F2 generation. Estimates for the number of genes involved were well below one, suggesting that the high variances of the recombinant offspring and the violation of assumptions inherent in the calculations invalidated the results. Regardless, QTL analyses identified five QTLs that were highly significant (Shali1, 2, and 3) or significant (Shali4 and 5) for linkage to HALI survival time.

Overall survival of the B-S-derived F2 mice ranged from 53 to 302 h, which expands beyond the ranges of the parental strains and suggested early on that the sensitive B strain contains one or more resistance alleles and the resistant S strain may harbor susceptibility alleles contributing to the overall survival time. Segregation analyses and sensitive-to-resistant ratios among the F2 groups also supported resistance genes in the sensitive B strain (24). The QTL analysis results of the present studies provide strong evidence that the QTLs on chromosomes 1, 4, and most probably 9 (i.e., Shali5, 2, and 4, respectively) contain dominant resistance genes in the sensitive B strain. First, F2 mice with a B-B genotype at D4Mit308 (Shali2) were significantly more resistant than mice S-S or S-B at that marker. Similar findings were obtained with D1Mit34 (Shali5) and D9Mit137 (Shali4). Second, 2-QTL genotype analysis demonstrated that mice containing S-S for D1Mit303 and B-B for D4Mit308 had the longest MSTs in all F2 populations and those mice with the opposite genotype (i.e., BB-SS) were the most sensitive of the nine 2-QTL genotypes (Supplemental Table 3). Third, four different 3-QTL combinations (Table 2) demonstrated a 60-h or more (and as much as 88 h) difference in survival time between mice that were SS-BB-BB at the three markers vs. those that were BB-SS-SS (Shali1 listed first). Thus, although genotype analysis only considers the markers at the QTL peaks and the remaining genome is not controlled in these groups of mice, 1-, 2-, and 3-QTL genotypes provide convincing evidence that the Shali QTLs confer additive resistance to mice carrying the corresponding resistance alleles from the S and B strains.

A search for gene-gene interactions was performed with pairwise analysis. Significant increases in single LOD scores were seen when D1Mit303 (Shali1) was combined with representative markers for any of the four other significant QTLs. However, these interactions were additive only; none of the interaction LOD scores for the QTLs approached significance. Interestingly, a significant interaction (interaction LOD score = 5.8) was revealed between a marker near the peak of Shali1 (D1Mit214) and D18Mit184 on chromosome 18, which by itself had no LOD score (0.1). This significant interaction LOD score led to a significant joint LOD score for the two markers. Although it is much too early to speculate on the genes involved in this interaction, we looked at the 2-QTL genotypes of these markers to gain insight as to whether the effect of the interaction could be quantified and which genotype combination supports the interaction effect. The change in survival time for the 2-QTL model was not significant (∼6 h), although there was a trend toward increased resistance when D18Mit184 was S-S or S-B, supporting a dominant modifier gene for resistance in the S strain.

As part of the original design to explore sex and parent-of-origin effects, QTL analysis was also performed on subpopulations of the total F2 data set, including males and females, the four individual F2 crosses, and the four combined F2 crosses. Females had highly significant linkage only to Shali1, whereas males had significant linkage to Shali1, Shali2, and Shali5. In fact, Shali5 on the distal portion of chromosome 1 was a male-specific QTL, with no LOD score in females and not reaching significance in any other F2 population. Shali2 on chromosome 4 showed a much larger survival effect in males, but the effect was also significant in females. Interestingly, a potential second more proximal QTL within the Shali2 interval was significant for males but not females; however, the distinction of separate peaks within the Shali2 support interval will await further studies. Thus the differential sex effects of Shali5 and Shali2 could explain why males demonstrated higher MSTs in all F2 populations.

In the analysis of separate crosses, neither the BS.BS nor the BS.SB F2 crosses demonstrated significant linkage to any QTL. However, the SB.BS F2 mice showed highly significant linkage to Shali1 and the SB.SB F2 mice were highly significantly linked to Shali2. This pattern is consistent with grandpaternal inheritance or maternal imprinting, assuming the imprint turns off allelic expression. The S allele is resistant and dominant for Shali1, so F2 progeny from S.B dams are more resistant than those from B.S dams. When the second Shali1 S allele is inherited from the B.S father, the offspring have increased resistance compared with inheritance from an S.B father (MST = 168.3 h vs. 139.3 h). Similarly, the B allele is resistant and dominant for Shali2, which, when inherited from a B.S father, shows more resistance than when inherited from an S.B father (MST = 158.5 h vs. 149.8 h). On the basis of MSTs and QTL analysis results, S.B dams seemed to confer increased survival to their offspring through Shali1 when bred to B.S sires and through Shali2 when bred to S.B sires. Combined F2 crosses supported all but Shali4 on chromosome 9, which only reached significance in the total F2 population, and the male-specific QTL Shali5, which would not be expected to reach significance when females are included in the analysis.

Identification of potential positional candidate genes for these QTLs at this early stage initiates the screening processes for the next phases. A list of positional candidates for all the Shali QTLs was generated, based on their potential roles in ALI and/or oxidative stress (Table 3). In addition, because the S strain (129X1/SvJ) is known to have a defect in inflammatory cell migration (46), potential differences in macrophage or neutrophil activities were also considered in candidate gene selection. Shali1 presented the best-defined interval and the strongest linkage, reaching a LOD score of 9.4 in the total F2 population very near D1Mit303 at 62.84 Mbp. A number of genes mapping to the 1.5 LOD support interval for Shali1 (49-73 Mbp) have been associated with ALI, including Caspase 8 (Casp8) (40), Caspase 8 and FADD-like apoptosis regulator (Cflar) (40), and interleukin-8 receptor-b (IL8rb) (35). Casp8 and Cflar have no reported single nucleotide polymorphisms (SNPs), but Il8rb has an upstream SNP in the resistant strains S, A/J, and DBA/2J, but not in the sensitive strains B and 129S1/SvImJ. For Shali2, toll-like receptor 4 (Tlr4) and thioredoxin-1 (Txn1) map near the first peak on chromosome 4, and caspase 9 (Casp9) and platelet activating factor acetylhydrolase 2 (Pafah2) map near the distal peak of chromosome 4. Both Tlr4 (29, 48) and Txn1 (47) have been directly implicated in hyperoxia-induced ALI, and Tlr4 is a strong candidate for the known defect in macrophage migration in the S strain (16). Casp9, part of the apoptotic pathway induced by hyperoxia, is also linked to HALI (40). Platelet-activating factor is a potent vasoconstrictor and bronchoconstrictor and can induce pulmonary edema and ARDS (9, 37); Pafah is elevated in ARDS patients (11).

View this table:
Table 3.

Select Shali positional candidate genes from QTL analysis

Two strong positional candidate genes map to Shali3 on chromosome 15. Angiopoietin-1 (Angpt1) plays an essential role in embryonic vasculature development, has anti-inflammatory properties, and protects the adult peripheral vasculature from leakage. When combined with VEGF, angiopoietin-1 prevented alveolar damage from HALI (36). Of interest, compared with the B strain, the S strain has an exonic SNP in Angpt1 that changes an amino acid in exon 4 from isoleucine to valine (I/V). Oxidation resistance-1 (Oxr1) is a member of a conserved family of genes found in eukaryotes, but not in prokaryotes. It was originally discovered in a search for human genes that function in protection against oxidative damage (39). Oxr1 in the mouse has two nonsynonymous SNPs (T/P and S/L) between the B and S strains, as well as two SNPs located at exon splicing sites. Two positional candidate genes for Shali4 on chromosome 9 include the antioxidant glutathione peroxidase 1 (Gpx1) and macrophage stimulating receptor 1 (Mst1r). Of note, a recent report demonstrated an increased susceptibility of Mst1r (also called the RON receptor)-knockout mice in nickel-induced ALI survival (19). Mst1r has a nonsynonymous SNP (H/R) between the S and B strains. Shali5 at the distal portion of chromosome 1 is a male-specific QTL. Although a male-specific role is not known, peroxiredoxin-6 (Prdx6) is an excellent candidate gene for HALI. Knockout mice show a susceptibility to oxidative stress, with increased lung injury and mortality from hyperoxia (41), and transgenic Prdx6 mice demonstrated increased resistance to HALI (42). However, no coding SNPs are known between the B and S strains, although seven 3′ SNPs are listed.

In summary, we have identified five QTLs significantly linked to HALI survival time. At least two of these QTLs have resistance alleles in the sensitive B strain. Shali5 appears to be a male-specific QTL on chromosome 1. Results of segregation and QTL analyses clearly demonstrate that these QTLs are additive and can confer significant differences between allelic combinations. Several interesting candidate genes for these QTLs have been directly associated with HALI or other oxidant-induced ALI. This mouse model provides the basic foundation for linking these QTLs to their associated quantitative trait genes and establishing which combination(s) of genes can provide the necessary protection from HALI, and potentially other forms of ALI.


This study was funded by National Heart, Lung, and Blood Institute Grant HL-75562 (D. R. Prows) and the Division and Program in Human Genetics at Cincinnati Children's Hospital Research Foundation.


The authors thank Dusti Folger, Erin Full, Andrea Hogan, Michelle Horner, David Mann, Matt Monfils, and Shannon Speelman for technical support. R scripts for running pairwise permutation analyses were written by Prakash Velayutham and Dr. Michael Wagner, in the Division of Bioinformatics at Cincinnati Children's Hospital Medical Center. R/qtl support was received from Dr. Karl Broman, Department of Biostatistics, Johns Hopkins University.


  • Address for reprint requests and other correspondence: D. R. Prows, Children's Hospital Medical Center, 3333 Burnet Ave., Div. of Human Genetics, Bldg. R, MLC 7016, Rm. 1464, Cincinnati, OH 45229-3039 (e-mail: daniel.prows{at}

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