Genetic loci that regulate healing and regeneration in LG/J and SM/J mice

MRL mice display unusual healing properties. When MRL ear pinnae are hole punched, the holes close completely without scarring, with regrowth of cartilage and reappearance of both hair follicles and sebaceous glands. Studies using (MRL/lpr × C57BL/6)F₂ and backcross mice first showed that this phenomenon was genetically determined and that multiple loci contributed to this quantitative trait. The lpr mutation itself, however, was not one of them. In the present study we examined the genetic basis of healing in the Large (LG/J) mouse strain, a parent of the MRL mouse and a strain that shows the same healing phenotype. LG/J mice were crossed with Small (SM/J) mice and the F₂ population was scored for healing and their genotypes determined at more than 200 polymorphic markers. As we previously observed for MRL and (MRL × B6)F₂ mice, the wound-healing phenotype was sexually dimorphic, with female mice healing more quickly and more completely than male mice. We found quantitative trait loci (QTLs) on chromosomes (Chrs) 9, 10, 11, and 15. The heal QTLs on Chrs 11 and 15 were linked to differential healing primarily in male animals, whereas QTLs on Chrs 9 and 10 were not sexually dimorphic. A comparison of loci identified in previous crosses with those in the present report using LG/J × SM/J showed that loci on Chrs 9, 11, and 15 colocalized with those seen in previous MRL crosses, whereas the locus on Chr 10 was not seen before and is contributed by SM/J.     

Combined-cross analysis of genome-wide linkage scans for experimental autoimmune encephalomyelitis in rat

Unbiased genetic analysis of experimental autoimmune encephalomyelitis (EAE) can provide insights into the pathogenesis of multiple sclerosis. To date five genome-wide scans using F2 crosses between different inbred rats have been performed with the aim of defining EAE-regulating quantitative trait loci (QTLs) as the starting point for identification of the underlying genes. We here report the first combined-cross analysis of three F2 crosses previously performed in our group. The majority of QTLs was shared between the different strain combinations and was therefore reproduced by the combined-cross analysis. Consequently, combined-cross analysis improved the power to detect QTLs with modest effects and narrowed QTL confidence intervals. The findings also demonstrate a lack of power in previous F2 crosses and encourage future use of larger populations. Moreover, the allelic states of shared QTLs could be established, thus providing critical information for narrowing QTLs and identifying the key polymorphism by subsequent haplotype analysis.     

Polymorphism for PCR-analyzed microsatellites between the inbred mouse strains LG and SM

Using agarose gel electrophoresis, we surveyed four strains of inbred mice (AKR/J, C57BL/J, LG/J, and SM/J) for 472 microsatellite loci. Agarose electrophoresis proved to be extremely efficient in separating alleles differing by six or more base pairs and detected a majority of allelic differences of between two and six base pairs. Overall, 64.4% of loci showed polymorphism among the four strains, and pairwise comparisons ranged from 42.1% to 48.1%. Microsatellite polymorphism for strains LG/J and SM/J has not been previously described and was sufficiently high (47.1%) to make these size-divergent strains excellent candidates for quantitative trait loci (QTL) analysis of normal growth.     

Multiple obesity QTLs identified in an intercross between the NZO (New Zealand obese) and the SM (small) mouse strains

The inheritance of adiposity levels has been investigated in an intercross of the obese, diabetes-prone NZO and the small, lean SM mouse strains. Adiposity index (AI) was defined as the sum of four fat pad weights divided by body weight. DNA pools from fat and lean mice were analyzed with microsatellite variants to screen the genome for quantitative trait loci (QTLs) affecting AI. Ten significant QTLs affecting AI were identified on Chromosome (Chr) 1 (three loci), Chr 2, Chr 5 (two loci), Chr 6 (two loci), Chr 7, and Chr 17. Most of the QTLs appear to be novel. Several QTLs differentially affect specific fat depots. Thus, Chr 2 and Chr 7 QTLs affect gonadal more than inguinal fat, while the converse is true for the Chr 17 QTL. Gender influences the expression of several of the QTLs. For example, effects of the proximal Chr 1 QTL (Obq7) on AI appears to be primarily in males. The proximal AI QTL on Chr 6 (Obq13) maps near the neuropeptide Y (Npy) locus. Sequence analysis of the Npy gene revealed a 1-nucleotide deletion within a highly conserved portion of the 3′ untranslated region in strain NZO. However, the deletion is polymorphic among mouse strains. Furthermore, lack of association between this same variant and AI in previously analyzed crosses raises doubt that it is the basis of Obq13. The present cross is the fourth in a series of intercrosses among 10 inbred strains arranged such that each strain is crossed with each adjacent strain within a circle. This design affords multiple opportunities to analyze each segregating QTL. Received: 17 July 2000 / Accepted: 9 October 2000     

Identification of quantitative trait loci for wood and fibre properties in two full-sib pedigrees of Eucalyptus globulus

Regions of the genome influencing wood and fibre traits in Eucalyptus globulus Labill. have been identified in two full-sib pedigrees that share a common male parent. The first pedigree, cross A, contains 148 progeny, and the second pedigree, cross B, contains 135 progeny. Subsets of progeny of these two controlled crosses were planted at seven sites throughout Australia in 1990. Wood cores were taken at 0.9 m above ground in 1997, and wood and fibre traits were analysed for each individual. Three quantitative trait loci (QTL) affecting wood density, one QTL affecting pulp yield and one QTL affecting microfibril angle have been located in both pedigrees, using single-factor analysis of variance. Other QTLs affecting these traits, as well as fibre length and cellulose content were located in cross A only.     

Association of a lithogenic Abcg5/Abcg8 allele on Chromosome 17 (Lith9) with cholesterol gallstone formation in PERA/EiJ mice

To examine further the genetic determinants of cholesterol gallstone susceptibility in inbred mice, we performed quantitative trait locus (QTL) analysis of an intercross of gallstone-susceptible PERA/EiJ and gallstone-resistant DBA/2J inbred mice. Three hundred twenty-four F₂ offspring were phenotyped for cholelithiasis during consumption of a lithogenic diet and genotyped using microsatellite markers. Linkage analysis was performed by interval mapping. In addition, we analyzed the combined datasets from this cross and from an independent cross of strain PERA and gallstone-resistant I/Ln mice. QTL mapping detected one significant new gallstone susceptibility (Lith) locus on Chromosome 13 (Lith15). A second significant QTL on Chr 6 (Lith16) confirmed a previous QTL. Furthermore, suggestive QTLs confirmed Lith loci from previous crosses on Chromosomes 1, 2, 5, 16 and X. QTL analysis of the dataset derived from the combined crosses increased the detection power and narrowed confidence intervals of Lith loci on Chromosomes 2, 6, 13, and 16. Moreover, the analysis of combined datasets revealed a shared QTL between both crosses on Chromosome 17 (Lith9). Significantly higher mRNA expression of Abcg5 and Abcg8 in strain PERA compared with strains I/Ln and DBA/2 further substantiated that the PERA allele of Abcg5/Abcg8 was responsible for lithogenicity underlying Lith9.     

Quantitative Trait Loci for Murine Growth

Body size is an archetypal quantitative trait with variation due to the segregation of many gene loci, each of relatively minor effect, and the environment. We examine the effects of quantitative trait loci (QTLs) on age-specific body weights and growth in the F(2) intercross of the LG/J and SM/J strains of inbred mice. Weekly weights (1-10 wk) and 75 microsatellite genotypes were obtained for 535 mice. Interval mapping was used to locate and measure the genotypic effects of QTLs on body weight and growth. QTL effects were detected on 16 of the 19 autosomes with several chromosomes carrying more than one QTL. The number of QTLs for age-specific weights varied from seven at 1 week to 17 at 10 wk. The QTLs were each of relatively minor, subequal effect. QTLs affecting early and late growth were generally distinct, mapping to different chromosomal locations indicating separate genetic and physiological systems for early and later murine growth.     

Uncovering of major genetic factors generating naturally occurring variation in heading date among Asian rice cultivars

To dissect the genetic factors controlling naturally occurring variation of heading date in Asian rice cultivars, we performed QTL analyses using F₂ populations derived from crosses between a japonica cultivar, Koshihikari, and each of 12 cultivars originating from various regions in Asia. These 12 diverse cultivars varied in heading date under natural field conditions in Tsukuba, Japan. Transgressive segregation was observed in 10 F₂ combinations. QTL analyses using multiple crosses revealed a comprehensive series of loci involved in natural variation in flowering time. One to four QTLs were detected in each cross combination, and some QTLs were shared among combinations. The chromosomal locations of these QTLs corresponded well with those detected in other studies. The allelic effects of the QTLs varied among the cross combinations. Sequence analysis of several previously cloned genes controlling heading date, including Hd1, Hd3a, Hd6, RFT1, and Ghd7, identified several functional polymorphisms, indicating that allelic variation at these loci probably contributes to variation in heading date. Taken together, the QTL and sequencing results indicate that a large portion of the phenotypic variation in heading date in Asian rice cultivars could be generated by combinations of different alleles (possibly both loss- and gain-of-function) of the QTLs detected in this study.     

Pleiotropic effects on mandibular morphology II: differential epistasis and genetic variation in morphological integration

The evolution of morphological modularity through the sequestration of pleiotropy to sets of functionally and developmentally related traits requires genetic variation in the relationships between traits. Genetic variation in relationships between traits can result from differential epistasis, where epistatic relationships for pairs of loci are different for different traits. This study maps relationship quantitative trait loci (QTLs), specifically QTLs that affect the relationship between individual mandibular traits and mandible length, across the genome in an F2 intercross of the LG/J and SM/J inbred mouse strains (N = 1045). We discovered 23 relationship QTLs scattered throughout the genome. All mandibular traits were involved in one or more relationship QTL. When multiple traits were affected at a relationship QTL, the traits tended to come from a developmentally restricted region of the mandible, either the muscular processes or the alveolus. About one-third of the relationship QTLs correspond to previously located trait QTLs affecting the same traits. These results comprise examples of genetic variation necessary for an evolutionary response to selection on the range of pleiotropic effects.     

Mapping genetic loci that regulate lipid levels in a NZB/B1NJxRF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains

The NZB/B1NJ (NZB) mouse strain exhibits high cholesterol and HDL levels in blood compared with several other strains of mice. To study the genetic regulation of blood lipid levels, we performed a genome-wide linkage analysis in 542 chow-fed F2 female mice from an NZBxRF/J (RF) intercross and in a combined data set that included NZBxRF and MRL/MpJxSJL/J intercrosses. In the NZBxRF F2 mice, the cholesterol and HDL concentrations were influenced by quantitative trait loci (QTL) on chromosome (Chr) 5 [logarithm of odds (LOD) 17-19; D5Mit10] that was in the region identified earlier in crosses involving NZB mice, but two QTLs on Chr 12 (LOD 4.7; D12Mit182) and Chr 19 (LOD 5.7; D19Mit1) were specific to the NZBxRF intercross. Triglyceride levels were affected by two novel QTLs at D12Mit182 (LOD 8.7) and D15Mit13 (LOD 3.5). The combined-cross linkage analysis (1,054 mice, 231 markers) 1) identified four shared QTLs (Chrs 5, 7, 14, and 17) that were not detected in one of the parental crosses and 2) improved the resolution of two shared QTLs. In summary, we report additional loci regulating lipid levels in NZB mice that had not been identified earlier in crosses involving the NZB strain of mice. The identification of shared loci from multiple crosses increases confidence toward finding the QTL gene.     

Genetic factors and diet affect long-bone length in the F34 LG,SM advanced intercross

Previous studies on the LG,SM advanced intercross line have identified approximately 40 quantitative trait loci (QTL) for long -bone (humerus, ulna, femur, and tibia) lengths. In this study, long-bone-length QTL were fine-mapped in the F₃₄ generation (n?=?1424) of the LG,SM advanced intercross. Environmental effects were assessed by dividing the population by sex between high-fat and low-fat diets, producing eight sex/diet cohorts. We identified 145 individual bone-length QTL comprising 45 pleiotropic QTL; 69 replicated QTL from previous studies, 35 were new traits significant at previously identified loci, and 41 were novel QTL. Many QTL affected only a subset of the population based on sex and/or diet. Eight of ten known skeletal growth genes were upregulated in 3-week-old LG/J male proximal tibial growth plates relative to SM/J.The sequences of parental strains LG/J and SM/J indicated the presence of over half a million polymorphisms in the confidence intervals of these 45 QTL. We examined 526 polymorphisms and found that 97 represented radical changes to amino acid composition while 40 were predicted to be deleterious to protein function.Additional experimentation is required to understand how changes in gene regulation or protein function can alter the genetic architecture and interact with the environment to produce phenotypic variation.     

Combining data from multiple inbred line crosses improves the power and resolution of quantitative trait loci mapping

Rodent inbred line crosses are widely used to map genetic loci associated with complex traits. This approach has proven to be powerful for detecting quantitative trait loci (QTL); however, the resolution of QTL locations, typically approximately 20 cM, means that hundreds of genes are implicated as potential candidates. We describe analytical methods based on linear models to combine information available in two or more inbred line crosses. Our strategy is motivated by the hypothesis that common inbred strains of the laboratory mouse are derived from a limited ancestral gene pool and thus QTL detected in multiple crosses are likely to represent shared ancestral polymorphisms. We demonstrate that the combined-cross analysis can improve the power to detect weak QTL, can narrow support intervals for QTL regions, and can be used to separate multiple QTL that colocalize by chance. Moreover, combined-cross analysis can establish the allelic states of a QTL among a set of parental lines, thus providing critical information for narrowing QTL regions by haplotype analysis.     

Mapping quantitative trait loci for murine growth: a closer look at genetic architecture

Over 20 years ago, D. S. Falconer and others launched an important avenue of research into the quantitative of body size growth in mice. This study continues in that tradition by locating quantitative trait loci (QTLs) responsible for murine growth, such as age-specific weights and growth periods, and examining the genetic architecture for body weight. We identified a large number of potential QTLs in an earlier F2 intercross (Intercross I) of the SM/J and LG/J inbred mouse strains. Many of these QTLs are replicated in a second F2 intercross (Intercross II) between the same two strains. These replicated regions provide candidate regions for future fine-mapping studies. We also examined body size and growth QTLs using the combined data set from these two intercrosses, resulting in 96 microsatellite markers being scored for 1045 individuals. An examination of the genetic architecture for age-specific weight and growth periods resulted in locating 20 separate QTLs, which were mainly additive in nature, although dominance was found to affect early growth and body size. QTLs affecting early and late growth were generally distinct, mapping to separate chromosome locations. This QTL pattern indicates largely separate genetic and physiological systems for early and later murine growth, as Falconer suggested. We also found sex-specific QTLs for body size with implications for the evolution of sexual dimorphism.     

Genetic architecture of adiposity in the cross of LG/J and SM/J inbred mice

The genetic basis of variation in obesity in human populations is thought to be owing to many genes of relatively small effect and their interactions. The LG/J by SM/J intercross of mouse inbred strains provides an excellent model system in which to investigate multigenic obesity. We previously mapped a large number of quantitative trait loci (QTLs) affecting adult body weight in this cross. We map body composition traits, adiposity, and skeletal size, in a replicate F₂ intercross of the same two strains containing 510 individuals. Using interval-mapping methods, we located eight QTLs affecting adiposity (Adip1–8). Two of these adiposity loci also affected tail length (Adip4 and Adip6) along with seven additional tail length QTLs (Skl1–7). A further four QTLs (Wt1–4) affect adult weight but not body composition. These QTLs have relatively small effects, typically about 0.2–0.4 standard deviation units, and account for between 3% and 10% of the variance in individual characters. All QTLs participated in epistatic interactions with other QTLs. Most of these interactions were due to additive-by-additive epistasis, which can nullify the apparent effects of single loci in our population. Adip8 interacts with all the other adiposity QTLs and seems to play a central role in the genetic system affecting obesity in this cross. Only two adiposity QTLs, Adip4 and Adip6, also affect tail length, indicating largely separate genetic control of variation in adiposity and skeletal size. Body size and obesity QTLs in the same locations as those discovered here are commonly found in mapping experiments with other mouse strains. Received: 11 January 2000 / Accepted: 17 August 2000     

Identification of genetic determinants of IGF‐1 levels and longevity among mouse inbred strains

The IGF‐1 signaling pathway plays an important role in regulating longevity. To identify the genetic loci and genes that regulate plasma IGF‐1 levels, we intercrossed MRL/MpJ and SM/J, inbred mouse strains that differ in IGF‐1 levels. Quantitative trait loci (QTL) analysis of IGF‐1 levels of these F2 mice detected four QTL on chromosomes (Chrs) 9 (48 Mb), 10 (86 Mb), 15 (18 Mb), and 17 (85 Mb). Haplotype association mapping of IGF‐1 levels in 28 domesticated inbred strains identified three suggestive loci in females on Chrs 2 (13 Mb), 10 (88 Mb), and 17 (28 Mb) and in four males on Chrs 1 (159 Mb), 3 (52 and 58 Mb), and 16 (74 Mb). Except for the QTL on Chr 9 and 16, all loci co‐localized with IGF‐1 QTL previously identified in other mouse crosses. The most significant locus was the QTL on Chr 10, which contains the Igf1 gene and which had a LOD score of 31.8. Haplotype analysis among 28 domesticated inbred strains revealed a major QTL on Chr 10 overlapping with the QTL identified in the F2 mice. This locus showed three major haplotypes; strains with haplotype 1 had significantly lower plasma IGF‐1 and extended longevity (P < 0.05) than strains with haplotype 2 or 3. Bioinformatic analysis, combined with sequencing and expression studies, showed that Igf1 is the most likely QTL gene, but that other genes may also play a role in this strong QTL.     

High‐precision genetic mapping of behavioral traits in the diversity outbred mouse population

Historically our ability to identify genetic variants underlying complex behavioral traits in mice has been limited by low mapping resolution of conventional mouse crosses. The newly developed Diversity Outbred (DO) population promises to deliver improved resolution that will circumvent costly fine‐mapping studies. The DO is derived from the same founder strains as the Collaborative Cross (CC), including three wild‐derived strains. Thus the DO provides more allelic diversity and greater potential for discovery compared to crosses involving standard mouse strains. We have characterized 283 male and female DO mice using open‐field, light–dark box, tail‐suspension and visual‐cliff avoidance tests to generate 38 behavioral measures. We identified several quantitative trait loci (QTL) for these traits with support intervals ranging from 1 to 3 Mb in size. These intervals contain relatively few genes (ranging from 5 to 96). For a majority of QTL, using the founder allelic effects together with whole genome sequence data, we could further narrow the positional candidates. Several QTL replicate previously published loci. Novel loci were also identified for anxiety‐ and activity‐related traits. Half of the QTLs are associated with wild‐derived alleles, confirming the value to behavioral genetics of added genetic diversity in the DO. In the presence of wild‐alleles we sometimes observe behaviors that are qualitatively different from the expected response. Our results demonstrate that high‐precision mapping of behavioral traits can be achieved with moderate numbers of DO animals, representing a significant advance in our ability to leverage the mouse as a tool for behavioral genetics .     

Mapping and characterisation of QTL × E interactions for traits determining grain and stover yield in pearl millet

A mapping population of 104 F(3) lines of pearl millet, derived from a cross between two inbred lines H 77/833-2 x PRLT 2/89-33, was evaluated, as testcrosses on a common tester, for traits determining grain and stover yield in seven different field trials, distributed over 3 years and two seasons. The total genetic variation was partitioned into effects due to season (S), genotype (G), genotype x season interaction (G x S), and genotype x environment-within-season interaction [G x E(S)]. QTLs were determined for traits for their G, G x S, and G x E(S) effects, to assess the magnitude and the nature (cross over/non-crossover) of environmental interaction effects on individual QTLs. QTLs for some traits were associated with G effects only, while others were associated with the effects of both G and G x S and/or G, G x S and G x E(S) effects. The major G x S QTLs detected were for flowering time (on LG 4 and LG 6), and mapped to the same intervals as G x S QTLs for several other traits (including stover yield, harvest index, biomass yield and panicle number m(-2)). All three QTLs detected for grain yield were unaffected by G x S interaction however. All three QTLs for stover yield (mapping on LG 2, LG 4 and LG 6) and one of the three QTLs for grain yield (mapping on LG 4) were also free of QTL x E(S) interactions. The grain yield QTLs that were affected by QTL x E(S) interactions (mapping on LG 2 and LG 6), appeared to be linked to parallel QTL x E(S) interactions of the QTLs for panicle number m(-2) on (LG 2) and of QTLs for both panicle number m(-2) and harvest index (LG 6). In general, QTL x E(S) interactions were more frequently observed for component traits of grain and stover yield, than for grain or stover yield per se.     

Pleiotropic patterns of quantitative trait loci for 70 murine skeletal traits

Quantitative trait locus (QTL) studies of a skeletal trait or a few related skeletal components are becoming commonplace, but as yet there has been no investigation of pleiotropic patterns throughout the skeleton. We present a comprehensive survey of pleiotropic patterns affecting mouse skeletal morphology in an intercross of LG/J and SM/J inbred strains (N = 1040), using QTL analysis on 70 skeletal traits. We identify 798 single-trait QTL, coalescing to 105 loci that affect on average 7-8 traits each. The number of traits affected per locus ranges from only 1 trait to 30 traits. Individual traits average 11 QTL each, ranging from 4 to 20. Skeletal traits are affected by many, small-effect loci. Significant additive genotypic values average 0.23 standard deviation (SD) units. Fifty percent of loci show codominance with heterozygotes having intermediate phenotypic values. When dominance does occur, the LG/J allele tends to be dominant to the SM/J allele (30% vs. 8%). Over- and underdominance are relatively rare (12%). Approximately one-fifth of QTL are sex specific, including many for pelvic traits. Evaluating the pleiotropic relationships of skeletal traits is important in understanding the role of genetic variation in the growth and development of the skeleton.     

New quantitative trait loci that regulate wound healing in an intercross progeny from DBA/1J and 129×1/SvJ inbred strains of mice

Wound healing/regeneration mouse models are few, and studies performed have mainly utilized crosses between MRL/MPJ (a good healer) and SJL/J (a poor healer) or MRL/lpr (a good healer) and C57BL/6J (a poor healer). Wound healing is a complex trait with many genes involved in the expression of the phenotype. Based on data from previous studies that common and additional quantitative trait loci (QTL) were identified using different crosses of inbred strains of mice for various complex traits, we hypothesized that a new cross would identify common and additional QTL, unique modes of inheritance, and interacting loci, which are responsible for variation in susceptibility to fast wound healing. In this study, we crossed DBA/1J (DBA, a good healer) and 129/SvJ (129, a poor healer) and performed a genome-wide scan using 492 (DBA×129) F2 mice and 98 markers to identify QTL that regulate wound healing/regeneration. Four QTL on chromosomes 1, 4, 12, and 18 were identified which contributed toward wound healing in F2 mice and accounted for 17.1% of the phenotypic variation in ear punch healing. Surprisingly, locus interactions contributed to 55.7% of the phenotype variation in ear punch healing. In conclusion, we have identified novel QTL and shown that minor interacting loci contribute significantly to wound healing in DBA×129 mice cross. The authors Masinde, Li, and Nguyen contributed equally to this article.     

油菜油分、蛋白质和硫苷含量相关性分析及QTL定位

为定位与油分、蛋白质和硫苷含量等品质性状相关的数量性状位点（QTL）,以2个含油量较高的甘蓝型油菜（Brassica napus）品系8908B和R1为研究材料,配置正反交组合。在正反交F2代群体中,含油量和蛋白质含量都存在极显著的负相关,相关系数分别为-0．68和-0．81,含油量和硫苷含量相关性不显著：蛋白质含量和硫苷含量在正交群体中相关性不显著,但在反交群体中存在显著负相关（相关系数r=-0．45）。利用正交F2代群体中的118个单株,构建了包含121个标记的遗传连锁图谱,图谱长1298．7cM,有21个连锁群（LGs）。采用复合区间作图法,在连锁图上定位了2个与含油量有关的QTL,分别位于LG8和LG10,其贡献率分别为4．8％和13．7％,增效基因都来源于R1;定位了2个与蛋白质含量有关的QTL：pr01和pr02,分别位于LG1和LG3,其贡献率分别为15．2％和14．1％,位点pr07由8908B提供增效基因,pro2则由R1提供增效基因：定位了4个与硫苷含量有关的QTL,其中LG20上有2个,LG4和LG8上各1个,它们的贡献率在1．9％-25．4％之间,除LG20上glu7的增效基因来自R1外,其余3个QTL位点均由8908B提供增效基因。