Murine susceptibility to radiation-induced pulmonary fibrosis is influenced by a genetic factor implicated in susceptibility to bleomycin-induced pulmonary fibrosis

From evidence of interpatient variability in normal tissue sensitivity to radiotherapy and from radiation studies using inbred mouse strains, it is hypothesized that individual variation in susceptibility to radiation-induced pulmonary fibrosis is genetically controlled. A genetic model has been developed from the fibrosis-prone C57BL/6J and the fibrosis-resistant C3Hf/Kam mouse strains. Inheritance of the fibrotic phenotype was characterized in F1 and F2 (F1 intercross) generations derived from the parental strains. Genetic mapping was used to determine whether the quantitative trait loci (QTL), which influence susceptibility to bleomycin-induced lung fibrosis in these progenitor strains, could be implicated in susceptibility to radiation-induced lung fibrosis. Mice were treated with 14 or 16 Gy (60Co) to the whole thorax. The doses were selected to investigate the response at the LD50 and LD100 of C3Hf/Kam mice. The animals were sacrificed 33 weeks after treatment or when moribund. The percentage of lung with fibrosis for each mouse was quantified with image analysis of a histological section of the lung. For both the 14- and 16-Gy data sets, heritability was estimated at 38 +/- 11%, and the number of genetic factors influencing susceptibility to pulmonary fibrosis was estimated to be one or two. Two hundred fifty-five F2 intercross mice were genotyped with markers at the bleomycin loci on chromosomes 11 and 17 (chromosome 17 marker is at the major histocompatibility complex). Genetic linkage was established for the marker on chromosome 17 (P = 3.0 x 10(-6)), which accounts for 6.6% of the F2 phenotypic variance but not for the markers surrounding the QTL on chromosome 11 (P = 0.37). The inheritance data suggested that susceptibility to radiation-induced pulmonary fibrosis is a heritable trait controlled by two genetic loci, and through genomic mapping, a QTL on chromosome 17 was identified as one of the loci.     

Least squares interval mapping of quantitative trait loci under the infinitesimal genetic model in outbred populations

Genetic marker and phenotypic data for a quantitative trait were simulated on 20 paternal half-sib families with 100 progeny to investigate properties of within-family-regression interval mapping of a postulated single quantitative trait locus (QTL) in a marker interval under the infinitesimal genetic model, which has been the basis of the application of quantitative genetics to genetic improvement programs, and to investigate use of the infinitesimal model as null hypothesis in testing for presence of a major QTL. Genetic effects on the marked chromosome were generated based on a major gene model, which simulated a central biallelic QTL, or based on 101 biallelic QTL of equal effect, which approximated the infinitesimal model. The marked chromosome contained 0, 3.3%, 13.3%, or 33.3% of genetic variance and heritability was 0.25 or 0.70. Under the polygenic model with 3.3% of genetic variance on the marked chromosome, which corresponds to the infinitesimal model for the bovine, significant QTL effects were found for individual families. Correlations between estimates of QTL effects and true chromosome substitution effects were 0.29 and 0.47 for heritabilities of 0.25 and 0.70 but up to 0.85 with 33.3% of polygenic variance on the marked chromosome. These results illustrate the potential of marker-assisted selection even under the infinitesimal genetic model. Power of tests for presence of QTL was substantially reduced when the polygenic model with 3.3% of genetic variance on the chromosome was used as a null hypothesis. The ability to determine whether genetic variance on a chromosome was contributed by a single QTL of major effect or a large number of QTL with minor effects, corresponding to the infinitesimal model, was limited.     

Effect of inaccurate parameter estimates on genetic response to marker-assisted selection in an outbred population

The effect of inaccurate estimates of variance and of the location of the quantitative trait locus on the genetic response to marker-assisted selection was studied by simulation of an adult multiple ovulation and embryo transfer nucleus breeding scheme. Two genetic models were simulated for the quantitative trait locus: a total of 10 alleles or 2 distinct alleles per base parent. For both models, the locus explained either 5 or 10% of phenotypic variance. A polygenic component was simulated, and the two genetic components were summed to 35% heritability for a trait measured on females. Overestimation of variance of the quantitative trait locus had minimal effect on genetic gain for marker-assisted selection over the short term, but decreased long-term response. The long-term loss was reduced when variance of the quantitative trait locus was reestimated after four generations of marker-assisted selection. Selection for favorable alleles at a nonexistent quantitative trait locus resulted in first generation losses of 3 and 7% for postulated quantitative trait loci, explaining 5 and 10% of variance, respectively. The larger the degree of error in location, the larger was the genetic loss compared with the correct location scenario. For the largest simulated location error of 15 cM, genetic superiority of marker-assisted selection was reduced by 80% in the first generation. We concluded that studies should be undertaken to verify estimates of quantitative trait locus and location to make optimal use of marker-assisted selection.     

A second-generation linkage map of the bovine genome

We report a bovine linkage map constructed with 1236 polymorphic DNA markers and 14 erythrocyte antigens and serum proteins. The 2990-cM map consists of a sex-specific, X chromosome linkage group and 29 sex-averaged, autosomal linkage groups with an average interval size of 2.5 cM. The map contains 627 new markers and 623 previously linked markers, providing a basis for integrating the four published bovine maps. Orientation and chromosomal assignment of all the linkage groups, except BTA20 and BTA22, was provided by 88 markers that were assigned previously to chromosomes. This map provides sufficient marker density for genomic scans of populations segregating quantitative trait loci (QTL) and subsequent implementation of marker-assisted selection (MAS) mating schemes.     

Interval mapping of growth in divergent swine cross

A genomic scan of 18 swine autosomal chromosomes was constructed with 119 polymorphic microsatellite (ms) markers to identify quantitative trait loci (QTL) for 11 growth traits in the University of Illinois Meishan x Yorkshire Swine Resource Family. A significant QTL effect was found for post-weaning average daily gain (ADG) between 5.5 and 56 kg of body weight that mapped between markers SW373 and SW1301 near the telomere of Chromosome (Chr) 1 q (SSC1). This QTL effect had a nominal (pointwise) p-value of 0.000007, a genome wide p-value of 0.012, and accounted for 26% of the F2 phenotypic variance. The same chromosome region also had significant effects on ADG between birth and 56 kg body weight (p-value =. 000227), and on ADG between 35 and 56 kg (p-value =.00077). These observations suggest that a significant QTL for post-weaning growth resides on SSC1.     

Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth

Quantitative trait loci (QTL) influencing body weight were mapped by linkage analysis in crosses between a high body weight selected line (DU6) and a control line (DUKs). The two mouse lines differ in body weight by 106% and in abdominal fat weight by 100% at 42 days. They were generated from the same base population and maintained as outbred colonies. Determination of line-specific allele frequencies at microsatellite markers spanning the genome indicated significant changes between the lines on 15 autosomes and the X chromosome. To confirm these effects, a QTL analysis was performed using structured F2 pedigrees derived from crosses of a single male from DU6 with a female from DUKs. QTL significant at the genome-wide level were mapped for body weight on chromosome 11; for abdominal fat weight on chromosomes 4, 11, and 13; for abdominal fat percentage on chromosomes 3 and 4; and for the weights of liver on chromosomes 4 and 11, of kidney on chromosomes 2 and 9, and of spleen on chromosome 11. The strong effect on body weight of the QTL on chromosome 11 was confirmed in three independent pedigrees. The effect was additive and independent of sex, accounting for 21-35% of the phenotypic variance of body weight within the corresponding F2 populations. The test for multiple QTL on chromosome 11 with combined data from all pedigrees indicated the segregation of two loci separated by 36 cM influencing body weight.     

Interacting quantitative trait loci control phenotypic variation in murine estradiol-regulated responses

The steroid hormone estradiol (E2) elicits a spectrum of systemic and uterotropic responses in vivo. For example, E2 treatment of ovariectomized adult and sexually immature rodents leads to uterine leukocytic infiltration, cell proliferation, and organ growth. E2-regulated growth is also associated with a variety of normal and pathological phenotypes. Historically, the uterine growth response has been used as the key model to understand the molecular and biochemical mechanisms underlying E2-dependent growth. In this study, genome exclusion mapping identified two quantitative trait loci (QTL) in the mouse, Est2 and Est3 on chromosomes 5 and 11, respectively, that control the phenotypic variation in uterine wet weight. Both QTL are linked to a variety of E2-regulated genes, suggesting that they may represent loci within conserved gene complexes that play fundamental roles in mediating the effects of E2. Interaction and multiple trait analyses using the uterine leukocyte response and wet weight suggest that Est4, a QTL on chromosome 10, may encode an interacting factor that influences the quantitative variation in both responses. Our results show that E2-dependent responses can be genetically controlled and that a genetic basis may underlie the variation observed in many E2-dependent phenotypes.     

Analytical and clinical performance of an automated immunoassay system (Immulite) for estradiol in serum

Mouse strains congenic for individual quantitative trait loci (QTLs) conferring hypnotic sensitivity to ethanol were constructed by backcrossing genotypically selected ILS x ISS N2 individuals to either inbred Long Sleep (ILS) or inbred Short Sleep (ISS) mice. We used a novel "speed congenic" approach in which N2 mice were genotyped for markers flanking each of the five originally identified QTLs. Genotypic selection for ISS regions at four of the five QTLs, and for ILS/ISS at the fifth QTL, allowed rapid fixation of the genetic background. We call this strategy "QTL-Marker-Assisted Counter Selection" or QMACS. By the N4 generation, phenotypic assessments showed that in some sublines the QTL had not been captured; these sublines were discarded and positive lines split to create new replicate sublines. One QTL, on Chromosome (Chr) 8, was not confirmed. At the N8, virtually all sublines on the remaining QTLs retained the phenotypic difference between heterozygotes and ISS homozygotes. Small numbers of interim congenics were produced at the N6 and later generations in which the ILS QTL was made homozygous on the ISS background; as expected, these congenic mice showed an increased sleep time. For later backcrosses (after the N4), the parents were selected on the basis of phenotype as well as genotype. The parent-offspring correlation over all QTLs was significant, supporting the use of phenotypic selection in congenic construction.     

Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects

The efficiency of marker-assisted selection (MAS) depends on the power of quantitative trait locus (QTL) detection and unbiased estimation of QTL effects. Two independent samples N = 344 and 107 of F2 plants were genotyped for 89 RFLP markers. For each sample, testcross (TC) progenies of the corresponding F3 lines with two testers were evaluated in four environments. QTL for grain yield and other agronomically important traits were mapped in both samples. QTL effects were estimated from the same data as used for detection and mapping of QTL (calibration) and, based on QTL positions from calibration, from the second, independent sample (validation). For all traits and both testers we detected a total of 107 QTL with N = 344, and 39 QTL with N = 107, of which only 20 were in common. Consistency of QTL effects across testers was in agreement with corresponding genotypic correlations between the two TC series. Most QTL displayed no significant QTL x environment nor epistatic interactions. Estimates of the proportion of the phenotypic and genetic variance explained by QTL were considerably reduced when derived from the independent validation sample as opposed to estimates from the calibration sample. We conclude that, unless QTL effects are estimated from an independent sample, they can be inflated, resulting in an overly optimistic assessment of the efficiency of MAS.     

Detection of putative loci affecting conformational type traits in an elite population of United States Holsteins using microsatellite markers

Quantitative trait loci affecting conformational type traits were studied in seven large grandsire families of US Holsteins using the granddaughter design and 16 microsatellite markers on 10 chromosomes. The most significant marker effect was marker BM203 (chromosome 27) for dairy form in a single grandsire family. A multivariate analysis for dairy form and milk yield was also conducted, and the result was highly significant, indicating that a segregating quantitative trait locus or loci affecting dairy form and milk yield could exist near BM203 on chromosome 27. Marker BM1258 (chromosome 23) had a significant effect on udder depth. A multivariate analysis on udder depth and somatic cell score was conducted for markers 513 and BM1258, and both markers showed significant effects on these two traits, indicating that one or several quantitative trait loci affecting udder depth and mastitis might exist on chromosome 23. Marker BM4204 (chromosome 9) had a significant effect on foot angle and on the composite index of traits pertaining to feet and legs, indicating that one or several quantitative trait loci affecting traits pertaining to feet and legs might exist on chromosome 9. Selection on these markers could increase genetic progress within these families.     

Application of Molecular Marker Assisted Selection in Gene Pyramiding and Selection of New Cultivars

The feasibility of molecule markers' application in gene pyramiding has been proved, and obvious progresses in crop breeding have been made till now. Furthermore, different QTLs or molecular markers linked tightly to yield, quality or resistance may be used for marker assisted selection. MAS will be applied widely in crop breeding due to the development of more gene-based markers and efficient quantitative trait locus (QTL) as well as lower cost marking systems.     

Identification of quantitative trait loci governing arthritis severity and humoral responses in the murine model of Lyme disease

A spectrum of disease severity has been observed in patients with Lyme disease, with approximately 60% of untreated individuals developing arthritis. The murine model of Lyme disease has provided strong evidence that the genetic composition of the host influences the severity of arthritis following infection with Borrelia burgdorferi: infected C3H mice develop severe arthritis while infected C57BL/6N mice develop mild arthritis. Regions of the mouse genome controlling arthritis severity and humoral responses during B. burgdorferi infection were identified in the F2 intercross generation of C3H/HeNCr and C57BL/6NCr mice. Rear ankle swelling measurements identified quantitative trait loci (QTL) on chromosomes 4 and 5, while histopathological scoring identified QTL on a unique region of chromosome 5 and on chromosome 11. The identification of QTL unique for ankle swelling or histopathological severity suggests that processes under distinct genetic control are responsible for these two manifestations of Lyme arthritis. Additional QTL that control the levels of circulating Igs induced by B. burgdorferi infection were identified on chromosomes 6, 9, 11, 12, and 17. Interestingly, the magnitude of the humoral response was not correlated with the severity of arthritis in infected F2 mice. This work defines several genetic loci that regulate either the severity of arthritis or the magnitude of humoral responses to B. burgdorferi infection in mice, with implications toward understanding the host-pathogen interactions involved in disease development.     

Quantitative trait loci (QTL) analyses and alcohol-related behaviors

Recombinant inbred (RI) strains can make an important contribution toward the merger of molecular genetics and quantitative genetics in the quest for quantitative trait loci (QTL). We present preliminary analyses of alcohol-related processes from our ongoing research using the BXD RI series. Issues concerning reliability, genetic correlations, and RI QTL analysis are discussed. Several strategies for replication and extension of QTL candidate regions are considered: F1 crosses between RI strains, F2 crosses, heterogeneous stock, interspecific backcrosses, QTL selection, and the use of murine QTL in chromosomal regions syntenic to human chromosomes as candidate chromosomal regions for human QTL.     

Mapping quantitative trait loci for carcass and meat quality traits in a wild boar x Large White intercross

An intercross between wild boar and a domestic Large White pig population was used to map quantitative trait loci (QTL) for body proportions, weight of internal organs, carcass composition, and meat quality. The results concerning growth traits and fat deposition traits have been reported elsewhere. In the present study, all 200 F2 animals, their parents, and their grandparents were genotyped for 236 markers. The marker genotypes were used to calculate the additive and dominance coefficients at fixed positions in the genome of each F2 animal, and the trait values were regressed onto these coefficients in intervals of 1 cM. In addition, the effect of proportion of wild boar alleles was tested for each chromosome. Significant QTL effects were found for percentage lean meat and percentage lean meat plus bone in various cuts, proportion of bone in relation to lean meat in ham, muscle area, and carcass length. The significant QTL were located on chromosomes 2, 3, 4, and 8. Each QTL explained 9 to 16% of the residual variance of the traits. Gene action for most QTL was largely additive. For meat quality traits, there were no QTL that reached the significance threshold. However, the average proportion of wild boar alleles across the genome had highly significant effects on reflectance and drip loss. The results show that there are several chromosome regions with a considerable effect on carcass traits in pigs.     

Worker social identity and health-related costs for organizations: a comparative study between ethnic groups

We have used an interspecific backcross to generate a detailed genetic map around the mouse tail and kidney developmental mutation Danforth's short tail (Sd). The map includes 14 simple sequence repeat (SSR) markers and four genes in a 5-cM region encompassing Sd. In addition we have used a DNA pooling approach to carry out a genome scan to localize quantitative trait loci (QTL) that modify the tail length of Sd progeny of the backcross. This has allowed us to identify a major QTL on chromosome 10 in the region of nodal and three other putative tail length QTL on chromosomes 1, 9, and 18.     

A quantitative trait locus for alcohol consumption in selectively bred rat lines

Selective breeding for high and low alcohol consumption led to the establishment of alcohol-preferring (P) and alcohol-nonpreferring (NP) rat lines that differ greatly in their alcohol consumption. These lines were inbred and F2 intercross progenies were generated to detect quantitative trait loci (QTLs) influencing alcohol consumption. A QTL on chromosome 4 was identified with a maximum lod score of 8.6. This QTL acts in an additive fashion and accounts for 11% of the total phenotypic variability and approximately one-third of the genetic variability. Neuropeptide Y, an endogenous anxiolytic and neuromodulator, has been mapped to this same region of chromosome 4. This study is an advance in genome analyses, demonstrating that crosses between divergent, selectively bred rat lines can be used to identify QTLs. Localization of a gene influencing alcohol consumption may have important implications for the etiology of alcohol abuse and alcoholism in humans.     

Advances in statistical methods to map quantitative trait loci in outbred populations

Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.     

The impact of genetic markers on selection

Genetic marker technologies, such as marker-assisted selection, parentage identification, and gene introgression can be applied to livestock selection programs. Highly saturated genetic maps are now available for cattle, swine, and sheep to provide the genetic framework for developing MAS programs. These programs rely on three phases for commercialization of the technology: the detection phase, in which quantitative trait loci are located and their effects on the phenotype measured; the evaluation phase, in which the markers are evaluated in commercial populations; and the implementation phase, in which markers are combined with phenotypic and pedigree information in genetic evaluation for predicting the genetic merit of individuals within the population. Predicting the economic impact of genetic technologies is a complex process that requires quantitative prediction and economic analysis. Evaluating the impact of these benefits across an industry can be achieved through a process in which gains from implementation of a genetic technology are assessed at the individual, enterprise, and industry levels. A pattern of annual benefits and costs can be predicted using gene flows that can be evaluated by conventional economic analysis.     

Selection with recurrent backcrossing to develop congenic lines for quantitative trait loci analysis

SEWALL WRIGHT suggested that genes of large effect on a quantitative trait could be isolated by recurrent backcrossing with selection on the trait. Loci [quantitative trait loci (QTL)] at which the recurrent and nonrecurrent lines have genes of different large effect on the trait would remain segregating, while other loci would become fixed for the gene carried by the recurrent parent. If the recurrent line is inbred and the backcrossing and selection is conducted in a series of replicate lines, in each of which only one backcross parent is selected for each generation, the lines will become congenic to the recurrent parent except for the QTL of large effect and closely linked regions of the genome, and these regions can be identified using a dense set of markers that differ between the parental lines. Such lines would be particularly valuable for subsequent fine-scale mapping and gene cloning; but by chance, even QTL of large effect will be lost from some lines. The probability that QTL of specified effect remain segregating is computed as a function of its effect on the trait, the intensity of selection, and the number of generations of backcrossing. Analytical formulas are given for one or two loci, and simulation is used for more. It is shown that the method could have substantial discriminating ability and thus potential practical value.     

A two-stage half-sib design for mapping quantitative trait loci in food animals

Daughter and granddaughter half-sib designs for mapping quantitative trait loci were modified to increase experimental power. This new design includes a two-stage procedure, in contrast to conventional one-step half-sib designs. In stage 1, a few progeny of each sire are genotyped for marker loci. Based on the analyses of stage 1 data, some sires are chosen to continue genotyping more progeny for stage 2. When multiple chromosomes are under investigation, chromosomes and sires for stage 2 are selected based on the analysis of stage 1 data. Sire selection results in increased frequency of heterozygous genotypes of interest in stage 2 if the markers are linked to those genes. Chromosome selection can increase the proportion of chromosomes with segregating quantitative trait loci in stage 2 if not all of the chromosomes evaluated in stage 1 have segregating quantitative trait loci. Numerical results indicated that two-stage half-sib designs are generally more powerful than conventional designs when 1) the noncentrality parameter is moderate or larger, 2) larger quantitative trait loci are mapped using tightly linked markers in larger families, and 3) variation is large in numbers and sizes of segregating quantitative trait loci among the chromosomes evaluated in stage 1.