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Genome partitioning and whole-genome analysis.

Standard DNA marker-based approaches to mapping genes that influence complex traits typically consider a limited number of hypotheses. Most of these hypotheses concentrate on the effect of a single individual locus (or relatively few loci) on the trait of interest. Although of tremendous importance scientifically, such hypotheses do not accommodate the full range of genetic phenomena that may contribute to phenotypic expression. We present novel approaches to complex trait analysis that make as complete use of marker information as is possible. The proposed methodologies can be used to entertain a wide variety of hypotheses, including those that engage, for example, the contribution of a particular chromosome, genome-wide heterozygosity, and multiple genomic regions, to phenotypic expression. We consider a number of possible extensions of the proposed methods as well as their limitations. Although we discuss many methodological details in the context of quantitative trait locus mapping involving sampling units such as human pedigrees and hybrids resulting from crosses between inbred strains of model organisms, our procedures can be easily adapted to standard sibpair and other sampling unit-based designs. Ultimately, the proposed approaches not only have the potential to increase power to identify individual loci that harbor trait-influencing genes, but also present a framework for testing a number of hypotheses about the nature of the genetic determinants of phenotypes in general.

Alleles↗

The impact of polymorphisms in the gene encoding aldosterone synthase (CYP11B2) on steroid synthesis and blood pressure regulation.

The terminal stages in the synthesis of aldosterone and cortisol are catalysed by the enzymes aldosterone synthase and 11beta-hydroxylase respectively. We have previously reported that polymorphic variation in the 5' promoter region (-344C/T) of the gene encoding aldosterone synthase (CYP11B2) is associated with increased aldosterone metabolite excretion and with hypertension associated with a raised aldosterone to renin ratio (ARR). Additionally, basal and ACTH-stimulated plasma levels of 11-deoxycortisol, the precursor of cortisol, are higher in subjects carrying the T-allelic variant. We have now identified in a family study (573 individuals from 105 extended families ascertained through a hypertensive proband) that excretion of the main metabolite of this steroid (tetrahydro-11-deoxycortisol, THS) is heritable (19.4%) and that the T-allele of CYP11B2 is more strongly associated with higher THS levels than the C-allele. Raised plasma and urinary levels of 11-deoxycortisol suggest that there is relative inefficiency of 11beta-hydroxylation in the zona fasciculata; the P450 enzyme responsible for this step is encoded by the gene CYP11B1, which is highly homologous with and adjacent to CYP11B2. The association of genetic variation in the promoter of CYP11B2 which, in the adrenal cortex, is only expressed in zona glomerulosa, and zona fasciculata 11beta-hydroxylation function is paradoxical. There may be linkage dys-equilibrium between this polymorphism and a quantitative trait locus (QTL) in CYP11B1. Chronic alteration of 11beta-hydroxylase activity may increase ACTH drive to the adrenal cortex, altering the regulation of aldosterone synthesis. This may explain, at least partly, the association between CYP11B2 polymorphisms and hypertension.

Adrenocorticotropic Hormone↗

Localization of non-Mhc collagen-induced arthritis susceptibility loci in DBA/1j mice.

One approach to understanding common human diseases is to determine the genetic defects responsible for similar diseases in animal models and place those defective genes in their corresponding biochemical pathways. Our laboratory is working with an animal model for human rheumatoid arthritis called collagen-induced arthritis (CIA). We are particularly interested in determining the location of disease-predisposing loci. To that end, we performed experiments to localize susceptibility loci for CIA in an F2 cross between the highly susceptible mouse strain DBA/1j and the highly resistant mouse strain SWR/j. Specifically, a quantitative trait locus analysis was performed to localize regions of the mouse genome responsible for susceptibility/severity to CIA. One susceptibility locus, Cia1 in the major histocompatibility locus, had been identified previously. Two additional loci were detected in our analysis that contribute to CIA severity (Cia2, Cia3) on chromosomes 2 and 6. A third locus was detected that contributes to the age of onset of the disease. This locus (Cia4) was located on chromosome 2 and was linked to the same region as Cia2. Determining the identity of these loci may provide insights into the etiology of human rheumatoid arthritis.

Animals↗

Toward integration of comparative genetic, physical, diversity, and cytomolecular maps for grasses and grains, using the sorghum genome as a foundation.

The small genome of sorghum (Sorghum bicolor L. Moench.) provides an important template for study of closely related large-genome crops such as maize (Zea mays) and sugarcane (Saccharum spp.), and is a logical complement to distantly related rice (Oryza sativa) as a "grass genome model." Using a high-density RFLP map as a framework, a robust physical map of sorghum is being assembled by integrating hybridization and fingerprint data with comparative data from related taxa such as rice and using new methods to resolve genomic duplications into locus-specific groups. By taking advantage of allelic variation revealed by heterologous probes, the positions of corresponding loci on the wheat (Triticum aestivum), rice, maize, sugarcane, and Arabidopsis genomes are being interpolated on the sorghum physical map. Bacterial artificial chromosomes for the small genome of rice are shown to close several gaps in the sorghum contigs; the emerging rice physical map and assembled sequence will further accelerate progress. An important motivation for developing genomic tools is to relate molecular level variation to phenotypic diversity. "Diversity maps," which depict the levels and patterns of variation in different gene pools, shed light on relationships of allelic diversity with chromosome organization, and suggest possible locations of genomic regions that are under selection due to major gene effects (some of which may be revealed by quantitative trait locus mapping). Both physical maps and diversity maps suggest interesting features that may be integrally related to the chromosomal context of DNA-progress in cytology promises to provide a means to elucidate such relationships. We seek to provide a detailed picture of the structure, function, and evolution of the genome of sorghum and its relatives, together with molecular tools such as locus-specific sequence-tagged site DNA markers and bacterial artificial chromosome contigs that will have enduring value for many aspects of genome analysis.

DNA Fingerprinting↗

Mapping of porcine genetic markers generated by representational difference analysis.

Representational difference analysis (RDA) was performed using pig genomic DNA from a Landrace non-selected control population and a Landrace population selected for increased loin muscle area (LMA) for five generations. Pigs used for the analysis differed phenotypically for various carcass traits and were divergent in genotype at the skeletal muscle ryanodine receptor 1 locus. Two RDA experiments were performed using BamHI and BglII. Fourteen BamHI and 37 BglII difference products were cloned and sequenced. Oligonucleotide primers were designed to amplify RDA difference products and sequence-tagged sites (STS) were developed for 16 RDA fragments (two BamHI and 14 BglII). These 16 STS were mapped using the INRA-Minnesota porcine Radiation Hybrid panel. Polymorphisms identified in nine of the STS were used to place these markers on the PiGMaP genetic linkage map. Sequence-tagged sites were localized to 11 different chromosomes including three markers on chromosome 11 and four markers on chromosome 14. Development of RDA markers increases the resolution of the pig genome maps and markers located within putative quantitative trait locus (QTL) regions can be used to refine QTL positions.

Animals↗

Accelerating effect of an MRL gene locus on the severity and onset of arthropathy in DBA/1 mice.

OBJECTIVE: To analyze the influence of the genetic background of an arthritis-prone strain of mice, MRL, on the spontaneous development of arthropathy in DBA/1 mice, which histopathologically resembles enthesopathy in humans, and to clarify the strain-specific gene loci and their interactions that confer susceptibility to arthropathy. METHODS: MRL, DBA/1, (MRL x DBA/1)F(1), and (MRL x DBA/1)F(2) intercross mice were prepared, and the severity and onset of arthropathy of the ankle joints in individual mice were quantified (0-3 and 0-5 scale, respectively). A genome-wide scan of 271 male F(2) intercross mice with polymorphic microsatellite markers was performed. RESULTS: Only male DBA/1, (MRL x DBA/1)F(1), and (MRL x DBA/1)F(2) mice developed arthropathy. The macroscopic and histopathologic findings of arthropathy in the F(2) mice were similar to those in the parental DBA/1 mice, but the onset was significantly earlier. In the quantitative trait locus analysis of male F(2) mice, 1 susceptibility locus for both the severity and early onset of the disease in the region of an MRL allele, Amd1, was located at marker D10Mit259 (map position 40.0 cM), which was common to 1 of the sialadenitis susceptibility loci in MRL mice, Asm1. Another susceptibility locus for the severity and early onset of arthropathy in the region of a DBA allele, Amd2, was located at D3Mit46 (29.5 cM). These loci manifested an additive effect on the development of arthropathy. CONCLUSION: Arthropathy in DBA/1 mice is under the control of an allelic combination of gene loci, one of which is common to the locus for sialadenitis in MRL/MpJ-lpr/lpr mice.

Age of Onset↗

Genetic analysis of ozone-induced acute lung injury in sensitive and resistant strains of mice.

Epidemiological studies have found air pollution to be associated with excessive mortality, particularly death from respiratory and cardiovascular causes. Interpretation of these findings is controversial, however, because toxicological mechanisms controlling mortality are uncertain. Susceptibility to many air pollutants entails an oxidative stress response. Accordingly, the best-characterized oxidant air pollutant is ozone, which causes direct oxidative damage of lung biomolecules. An underlying characteristic derived from clinical and epidemiological studies of healthy and asthmatic individuals of all ages is marked variability in the respiratory effects of ozone. This susceptibility difference among humans suggests that genetic determinants may control predisposition to the harmful effects of ozone. Mice also vary considerably in their response to ozone. Moreover, ozone-induced differences in strain responses indicate that susceptibility in mice can be genetically determined. Therefore, we used inbred mice to investigate the genetic determinants of acute lung injury. Recombinant inbred (RI) strains derived from A/J (A) mice (sensitive) and C57BL/6J (B) mice (resistant) showed a continuous phenotypic pattern, suggesting a multigenic trait. Quantitative trait locus and RI analyses suggested three major loci linked to ozone susceptibility. Differences in phenotype ratios among the reciprocal back-crosses were consistent with parental imprinting. These findings implicate various genetic and epigenetic factors in individual susceptibility to air pollution.

Animals↗

Genetic dissection of "OLETF", a rat model for non-insulin-dependent diabetes mellitus.

To elucidate the genetic factors underlying non-insulin-dependent diabetes mellitus (NIDDM), we performed genome-wide quantitative trait locus (QTL) analysis, using the Otsuka Long-Evans Tokushima Fatty (OLETF) rat. The OLETF rat is an excellent animal model of NIDDM because the features of the disease closely resemble human NIDDM. Genetic dissection with two kinds of F2 intercross progeny, from matings between the OLETF rat and non-diabetic control rats F344 or BN, allowed us to identify on Chromosome (Chr) 1 a major QTL associated with features of NIDDM that was common to both crosses. We also mapped two additional significant loci, on Chrs 7 and 14, in the (OLETF x F344)F2 cross alone, and designated these three loci as Diabetes mellitus, OLETF type Dmo 1, Dmo2 and Dmo3 respectively. With regard to suggestive QTLs, we found loci on Chrs 10, 11, and 16 that were common to both crosses, as well as loci on Chrs 5 and 12 in the (OLETF x F344)F2 cross and on Chrs 4 and 13 in the (OLETF x BN)F2 cross. Our results showed that NIDDM in the OLETF rat is polygenic and demonstrated that different genetic backgrounds could affect "fitness" for QTLs and produce different phenotypic effects from the same locus.

Animals↗

Haplotype association analysis of discrete and continuous traits using mixture of regression models.

We present a regression-based method of haplotype association analysis for quantitative and dichotomous traits in samples consisting of unrelated individuals. The method takes account of uncertain phase by initially estimating haplotype frequencies and obtaining the posterior probabilities of all possible haplotype combinations in each individual, then using these as weights in a finite mixture of regression models. Using this method, different combinations of marker loci can be modeled, to find a parsimonious set of marker loci that are most predictive and therefore most likely to be closely associated with the a quantitative trait locus. The method has the additional advantage of being able to use individuals with some missing genotype data, by considering all possible genotypes at the missing markers. We have implemented this method using the SNPHAP and Mx programs and illustrated its use on published data on idiopathic generalized epilepsy.

Chromosome Mapping↗

Power and sample sizes for linkage with extreme sampling under an oligogenic model for quantitative traits.

Extreme sampling of sibling pairs has been shown to be efficient in terms of statistical power and sample sizes (in number of sibling pairs needed to genotype) to detect a quantitative trait locus (QTL) when the residual distribution is normal. In the present study, the efficiency of extreme sampling strategies to detect each locus under an oligogenic model is analytically explored with a test statistic based on identical-by-descent (IBD) statuses of independent sibling pairs. In the oligogenic model, the joint effect of oligogenes is the sum of the effects of each locus. Under this model, detecting each single locus will depend, in part, on the allele frequencies and magnitudes of effect of the other loci. Effects of two QTLs with different magnitudes of displacement and acting nonepistatically are considered. Three types of extreme sampling-that is, extreme concordant high (ECH), extreme concordant low (ECL), and extreme discordant (ED)-are primarily considered herein. Among these, ED sampling under the oligogenic model is shown to be most efficient in most situations considered here in terms of allele frequency and mode of inheritance. Differences in results between ECH and ECL sampling are purely arbitrary, brought up mostly by the directions of displacement effects. However, power to detect a locus with the lesser (in magnitude) displacement effect does not necessarily increase with extremity of sampling. Combinations of extreme discordant and extreme concordant sibling pairs are briefly discussed.

Alleles↗

High-resolution comparative mapping of pig Chromosome 4, emphasizing the FAT1 region.

The first quantitative trait locus (QTL) in pigs, FAT1, was found on Chromosome 4 (SSC4) using a Wild Boar intercross. Further mapping has refined the FAT1 QTL to a region with conserved synteny to both human Chromosomes 1 and 8. To both improve the comparative map of the entire SSC4 and to define the specific human chromosome region with conserved synteny to FAT1, we have now mapped 103 loci to pig Chromosome 4 using a combination of radiation hybrid and linkage mapping. The physical data and linkage analysis results are in very good agreement. Comparative analysis revealed that gene order is very well conserved across SSC4 compared to both HSA1 and HSA8. The breakpoint in conserved synteny was refined to an area of about 23 cR on the q arm of SSC4 corresponding to a genetic distance of less than 0.5 cM. Localizations of the centromeres do not seem to have been conserved between the two species. No remnants of the HSA1 centromere were detected on the corresponding region on SSC4 and traces from the centromeric region of SSC4 cannot clearly be revealed on the homologous region on HSA8. This refined SSC4 map and the comparative analysis will be a great aid in the search for the genes underlying the FAT1 locus.

Animals↗

Genetic analyses of ethanol-induced hyperglycemia.

BACKGROUND: Genetic sensitivity to ethanol-induced hyperglycemia was hypothesized to be related to sensitivity to ethanol-induced hypothermia and conditioned taste aversion. These hypotheses were explored by characterizing blood glucose changes after ethanol exposure in BXD recombinant inbred mice. METHODS: Adult male and female BXD recombinant inbred mice were acutely exposed to 4 g/kg of ethanol or saline with the order of exposure counterbalanced, and separated by a 1-week interval. Tail blood samples and rectal temperatures were determined immediately before ethanol/saline exposure and 2 hr after exposure. RESULTS: Substantial strain differences in ethanol-induced hyperglycemia and hypothermia were noted. In addition, sex also determined sensitivity to ethanol-induced hyperglycemia and interacted with strain. Correlational analyses using strain means indicated that ethanol-induced hyperglycemia was genetically independent from ethanol-induced hypothermia or conditioned taste aversion. Quantitative trait locus (QTL) analyses indicated provisional QTL for ethanol-induced hyperglycemia on chromosomes 1, 3, 4, 6, 7, 9, 12, 14, and 18, which, in part, were sex specific. CONCLUSIONS: These findings indicate important sex differences in the glycemic response to ethanol. In addition, multiple genes likely control this response, independent from genes that are important for the thermic or aversive effects of ethanol.

Animals↗

A major gene mapped on chromosome XII is the main factor of a quantitatively inherited resistance to Meloidogyne fallax in Solanum sparsipilum.

Meloidogyne fallax is an emerging pest in Europe and represents a threat for potato production. We report the mapping of genetic factors controlling a quantitative resistance against M. fallax identified in the Solanum sparsipilum genotype 88S.329.15. When infected, this genotype develops a necrotic reaction at the feeding site of the juveniles and totally prevents their development to the female stage. A "F1" diploid progeny consisting of 128 individuals was obtained using the potato (S. tuberosum) dihaploid genotype BF15 H1 as female progenitor. Sixty-eight hybrid genotypes displayed necrosis at the feeding site of the juveniles and 60 other genotypes showed no defence reaction. This suggested a monogenic control of the resistance. However, when considering the number of nematode females developed in their roots, a continuous distribution was observed for both "necrotic" and "non-necrotic" hybrid genotypes, indicating a polygenic control of the resistance. A linkage map of each parental genotype was constructed using AFLP markers. The necrotic reaction (NR) was mapped as a qualitative trait on chromosome XII of the resistant genotype 88S.329.15. Quantitative trait locus (QTL) analysis for the number of nematode females developed per "F1" plant genotype was performed using the QTL cartographer software. No QTL was detected on the linkage map of the susceptible parent. A QTL explaining 94.5% of the phenotypic variation was mapped on chromosome XII of the resistant progenitor. This QTL, named MfaXIIspl, was mapped in a genomic region collinear to the map position of the Mi-3 gene conferring resistance to Meloidogyne incognita in tomato. It corresponds to the NR locus.

Animals↗

Suggestive linkages between markers on human 1p32-p22 and body fat and insulin levels in the Quebec Family Study.

A single-gene rodent mutation (diabetes) and a quantitative trait locus (dietary obese 1) mapped to the mid portion of mouse chromosome 4 have been related to obesity and/or insulin levels. Synteny relationships place their putative human homologs on 1p31 and 1p35-p31, respectively. In 137 sibships of adult brothers and sisters from the Québec Family Study, genetic linkages between seven microsatellite markers from 1p32-p22 and various obesity- and diabetes-related quantitative phenotypes were examined using single locus sibpair linkage analysis. Suggestive linkages were observed between markers D1S476 and body mass index (p = 0.05), fat mass (p = 0.02), the sum of six skinfolds (p = 0.02), the insulin area after an oral glucose tolerance test (p = 0.02), and between the neighboring marker D1S200 and body mass index (p = 0.03), and fat mass (p = 0.009). Suggestive linkages were also observed between the more telomeric markers D1S193 and body mass index (p = 0.03), and between the neighboring marker D1S197 and fasting insulin level (p = 0.05). No linkage was observed with the trunk to extremity skinfolds ratio. These linkages suggest that human homologs of the mouse diabetes or dietary obese 1 and/or other genes in this interval on chromosome 1 play a role in the regulation of body mass, body composition, and insulin levels, but not of subcutaneous fat distribution.

Adolescent↗

Interval mapping and congenic strains for a blood pressure QTL on rat chromosome 13.

The renin locus (Ren) on rat Chromosome (Chr) 13 had previously been shown to cosegregate with blood pressure in crosses involving Dahl salt-sensitive (S) and Dahl salt-resistant (R) rats. In the present work, interval mapping of blood pressure on Chr 13 with a large F2 (S x R), n = 233, population yielded a maximum LOD = 4.2 for linkage to blood pressure, but the quantitative trait locus (QTL) was only poorly localized to a large 35-centiMorgan (cM) segment of Chr 13. In the linkage analysis, the S-rat QTL allele (S) was associated with higher, and the R-rat QTL allele (R) with lower blood pressure, the difference between homozygotes being about 20 mm Hg. A congenic strain was made by introgressing the R-rat Ren allele into the recipient S strain. This congenic strain showed a 24 mm Hg reduction (P = 0.004) in blood pressure compared with S rats for rats fed 2% NaCl diet for 24 days; this difference was confirmed by two other independent tests. Two congenic substrains were derived from the first congenic strain with shorter R Chr 13 segments on the S background. Comparisons among these congenic strains showed that a blood pressure QTL was in the 24-cM chromosomal segment between Syt2 and D13M1Mit108. This segment does not include the renin locus, which is thus excluded from being the gene on rat Chr 13 responsible for genetic differences in blood pressure detected by linkage analysis.

Animals↗

Mapping quantitative trait loci for hearing loss in Black Swiss mice.

In common inbred mouse strains, hearing loss is a highly prevalent quantitative trait, which is mainly controlled by the Cdh23(753A) variant and alleles at numerous other strain-specific loci. Here, we investigated the genetic basis of hearing loss in non-inbred strains. Mice of Swiss Webster, CF-1, NIH Swiss, ICR, and Black Swiss strains exhibited hearing profiles characteristic of progressive, sensorineural hearing impairment. In particular, CF-1, Black Swiss, and NIH Swiss mice showed early-onset hearing impairment, ICR and Swiss Webster mice expressed a delayed-onset hearing loss, and NMRI mice had normal hearing. By quantitative trait locus (QTL) mapping, two significant QTLs were identified underlying hearing loss in Black Swiss mice: one QTL mapped to chromosome (chr) 10 (named ahl5, LOD 8.9, peak association 35-42 cM) and a second QTL localized to chr 18 (ahl6, LOD 3.8, 38-44 cM). Ahl5 and ahl6 account for 61% and 32% of the variation in the backcross, respectively. Cadherin 23 (Cdh23) and protocadherin 15 (Pcdh15), mapping within the 95% confidence interval of ahl5, bear nucleotide polymorphisms in coding exons, but these appear to be unrelated to the hearing phenotype. Haplotype analyses across the Cdh23 locus demonstrated the phylogenetic relationship between Black Swiss and common inbred strains.

Age Factors↗

Marker-assisted characterization of Asian wheat lines for resistance to Fusarium head blight.

The major quantitative trait locus (QTL) on 3BS from Sumai 3 and its derivatives has been used as a major source of resistance to Fusarium head blight (FHB) worldwide, but resistance genes from other sources are necessary to avoid complete dependence on a single source of resistance. Fifty-nine Asian wheat landraces and cultivars differing in the levels of FHB resistance were evaluated for type II FHB resistance and for genetic diversity on the basis of amplified fragment length polymorphism (AFLP) and simple sequence repeats (SSRs). Genetic relationships among these wheat accessions estimated by cluster analysis of molecular marker data were consistent with their geographic distribution and pedigrees. Chinese resistant landraces had broader genetic diversity than that of accessions from southwestern Japan. The haplotype pattern of the SSR markers that linked to FHB resistance quantitative trait loci (QTLs) on chromosomes 3BS, 5AS and 6BS of Sumai 3 suggested that only a few lines derived from Sumai 3 may carry all the putative QTLs from Sumai 3. About half of the accessions might have one or two FHB resistance QTLs from Sumai 3. Some accessions with a high level of resistance, may carry different FHB resistance loci or alleles from those in Sumai 3, and are worth further investigation. SSR data also clearly suggested that FHB resistance QTLs on 3BS, 5AS, and 6BS of Sumai 3 were derived from Chinese landrace Taiwan Xiaomai.

Alleles↗

Constant light-induced retinal damage and the RPE65-MET450 variant: assessment of the NZW/LacJ mouse.

PURPOSE: In a previous constant light-induced retinal damage (CLD) quantitative genetics study between the albino C57BL/6J-c2J (B6al) and BALB/c mouse strains, we identified a very strong and highly significant quantitative trait locus (QTL) on distal Chr 3 that we associated with a variant of the Rpe65 gene. The B6al strain carries the MET450 variant of RPE65 and is resistant to CLD while the BALB/c strain carries the LEU450 variant and is sensitive. Since then, we have discovered that the NZW/LacJ (NZW) albino mouse strain is sensitive to CLD but carries the MET450 variant of RPE65. The purpose of this study was to determine if the NZW mouse disproves the hypothesis that the MET450 variant of RPE65 protects the mouse retina against constant light-induced retinal damage. METHODS: F2 progeny were bred from an intercross between the NZW/LacJ and B6al mouse strains. After a prolonged exposure to moderate constant light, F2 mice were phenotyped for retinal outer nuclear layer thickness as the quantitative trait. A subset of 156 of the 201 F2 mice was genotyped for a set of markers spanning the genome, and any marker with a significant association with the quantitative trait was genotyped in the remaining 45 F2s. Data were analyzed for QTL by the Map Manager QTX software. RESULTS: No QTL was identified at distal Chr 3, although several QTL on Chrs 1 (two), 10, 13, 14, 16, and X were detected. One QTL on middle Chr 1 (LOD 5.22) mapped to the same location of a QTL (LOD 6.8) in a previous intense, short exposure light-induced retinal damage study conducted with an intercross between the 129S1/SvImJ and BALB/c strains. QTL on Chrs 1 (distal), 10, and 14 also appeared in other retinal damage quantitative genetics studies. Three pairs of genes exhibited significant epistatic effects. Two of the pairs involved synergistic interactions between NZW and B6al alleles, and the third between two B6al alleles. CONCLUSIONS: If another gene besides Rpe65 was responsible for the QTL in the original BALB/c x B6al study, and the NZW mouse carried a light sensitive allele of this gene, a QTL should have been present in this study. Since a QTL on Chr 3 was not found, the hypothesis that RPE65-MET450 protects the retina from constant light-induced damage is left intact. The explanation for the NZW mouse being sensitive to constant light while carrying the RPE65-MET450 variant is that other light sensitive QTL (gene alleles) negate the protective effect.

Animals↗