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PubMed1997

Obesity QTLs on mouse chromosomes 2 and 17.

The inheritance of obesity has been analyzed in an intercross between the mouse strains AKR/J and C57L/J. Two novel obesity quantitative trait loci (QTLs) have been identified using the strategy of selective DNA pooling. One QTL affecting adiposity, Obq3, was mapped to a 39-cM segment near the middle of Chromosome 2, with a peak lod score (5.1) just distal to the D2Mit15 locus. The AKR/J Obq3 allele confers increased adiposity in a nearly additive manner, and males are more affected than females. A second obesity QTL (Obq4) maps to the centromeric end of Chromosome 17, with a lod score peak of 4.6 at D17Mit143. The obesity-conferring allele is contributed by C57L/J and acts in a recessive or an additive manner. Obq4 also has more influence in males and affects the inguinal fat depot differentially. Obq3 and Obq4 account for 7.0 and 6.1% of the phenotypic variance in adiposity (gender-merged data), respectively. The possible relationships between these QTLs and previously described obesity QTLs and candidate genes are discussed. The large number of different obesity QTLs that have been described in mice and the relatively small effects contributed by individual loci suggest considerable genetic complexity.

Adipose Tissue↗
PubMedDate not supplied

Towards marker assisted selection in livestock.

In recent years, genomic tools have become available for most livestock species and are now being used routinely to map quantitative trait loci underlying the genetic variance for numerous economically important traits. Fine-mapping methods are being devised to refine the initially coarse map positions of the quantitative trait loci to the point required for marker assisted selection and, eventually, the positional cloning of the underlying genes. Mapping information on QTL is beginning to be used to increase genetic response by enhancing genetic variance, selection accuracy, selection intensity and by reducing the generation interval. Optimal use of MAS will require the development of more robust methods for the routine genotyping of preimplantation embryos for multiple markers.

Animals↗
PubMed1996

Complex interactions of new quantitative trait loci, Sluc1, Sluc2, Sluc3, and Sluc4, that influence the susceptibility to lung cancer in the mouse.

Many complex traits, including susceptibility to lung cancer, are controlled by multiple genes--quantitative trait loci (QTLs). We facilitated the mapping of QTLs by making use of recombinant congenic strains (RCS), a system of mouse inbred strains in which the genetic complexity is reduced, and by applying MQM-mapping (multiple-QTL models or marker-QTL-marker), a multilocus method with an increased power of detecting of individual QTLs and interacting QTLs (epistasis). The mouse strain O20 develops significantly larger N-ethyl-N-nitrosourea induced lung tumours than mice of the RC strain OcB-9 (ref. 5); the latter share approximately 87.5% of their genes with strain O20 and 12.5% with strain B10.O20 (refs 6,7). QTL analysis of 222 (OcB-9 x O20) F2 mice revealed four new loci that influence susceptibility to lung cancer (Sluc genes). They are involved in two significant, partly counteracting interactions which mask their individual main effects: Sluc1 (on chromosome 19) interacts with Sluc2 (chromosome 2), and Sluc3 (chromosome 6) interacts with Sluc4 (chromosome 11). Together with the data of van Wezel et al. in the accompanying report, our results indicate that interactions between tumour susceptibility genes are a common phenomenon which complicates their mapping.

Animals↗
PubMed2002

Genes affecting aging: mapping quantitative trait loci in Drosophila melanogaster using amplified fragment length polymorphisms (AFLPs).

This study examines the use of AFLPs (amplified fragment length polymorphisms) for locating QTL for longevity. Inbred long and short-lived lines from selected stocks of D. melanogaster were backcrossed and measurements of life span compiled into a distribution. AFLP markers assorting with long life were screened from the extremes of that distribution. To test their association with further recombination, a second F1 was backcrossed for three generations and measured. Sires and progeny were genotyped for the markers initially screened. Three AFLP primer pairs identified markers assorting with long life in six of 48 sires. An a posteriori test showed that families of sires with putative markers lived significantly longer on average. A second test showed that within families, progeny with markers lived significantly longer than sibs without them. Marker positions were mapped by hybridization to a P1 genomic miniblot. AFLP markers were cloned, sequenced and matched to known genomic sequences in a BLAST search. Positions were compared to QTL known from other studies. The BLAST search indicated hybridization at multiply dispersed sites throughout the genome. Marker positions also corresponded to many from independent QTL maps. These results indicate that some QTL consist of dispersed duplications that contribute independently to longevity.

Aging↗
PubMed2006

Fine mapping of collagen-induced arthritis quantitative trait loci in an advanced intercross line.

The generation of advanced intercross lines (AIL) is a powerful approach for high-resolution fine mapping of quantitative trait loci (QTLs), because they accumulate much more recombination events compared with conventional F2 intercross and N2 backcross. However, the application of this approach is severely hampered by the requirements of excessive resources to maintain such crosses, i.e., in terms of animal care, space, and time. Therefore, in this study, we produced an AIL to fine map collagen-induced arthritis (CIA) QTLs using comparatively limited resources. We used only 308 (DBA/1 x FVB/N)F11/12 AIL mice to refine QTLs controlling the severity and onset of arthritis as well as the Ab response and T cell subset in CIA, namely Cia2, Cia27, and Trmq3. These QTLs were originally identified in (DBA/1 x FVB/N)F2 progeny. The confidence intervals of the three QTLs were refined from 40, 43, and 48 Mb to 12, 4.1, and 12 Mb, respectively. The data were complemented by the use of another QTL fine-mapping approach, haplotype analysis, to further refine Cia2 into a 2-Mb genomic region. To aid in the search for candidate genes for the QTLs, genome-wide expression profiling was performed to identify strain-specific differentially expressed genes within the confidence intervals. Of the 1396 strain-specific differentially expressed genes, 3, 3, and 12 genes were within the support intervals of the Cia2, Cia27, and Trmq3, respectively. In addition, this study revealed that Cia27 and Trmq3 controlling anti-CII IgG2a Ab and CD4:CD8 T cell ratio, respectively, also regulated CIA clinical phenotypes.

Animals↗
PubMedDate not supplied

Prediction of identity by descent probabilities from marker-haplotypes.

The prediction of identity by descent (IBD) probabilities is essential for all methods that map quantitative trait loci (QTL). The IBD probabilities may be predicted from marker genotypes and/or pedigree information. Here, a method is presented that predicts IBD probabilities at a given chromosomal location given data on a haplotype of markers spanning that position. The method is based on a simplification of the coalescence process, and assumes that the number of generations since the base population and effective population size is known, although effective size may be estimated from the data. The probability that two gametes are IBD at a particular locus increases as the number of markers surrounding the locus with identical alleles increases. This effect is more pronounced when effective population size is high. Hence as effective population size increases, the IBD probabilities become more sensitive to the marker data which should favour finer scale mapping of the QTL. The IBD probability prediction method was developed for the situation where the pedigree of the animals was unknown (i.e. all information came from the marker genotypes), and the situation where, say T, generations of unknown pedigree are followed by some generations where pedigree and marker genotypes are known.

Algorithms↗
PubMed2003

Bayesian model choice and search strategies for mapping interacting quantitative trait Loci.

Most complex traits of animals, plants, and humans are influenced by multiple genetic and environmental factors. Interactions among multiple genes play fundamental roles in the genetic control and evolution of complex traits. Statistical modeling of interaction effects in quantitative trait loci (QTL) analysis must accommodate a very large number of potential genetic effects, which presents a major challenge to determining the genetic model with respect to the number of QTL, their positions, and their genetic effects. In this study, we use the methodology of Bayesian model and variable selection to develop strategies for identifying multiple QTL with complex epistatic patterns in experimental designs with two segregating genotypes. Specifically, we develop a reversible jump Markov chain Monte Carlo algorithm to determine the number of QTL and to select main and epistatic effects. With the proposed method, we can jointly infer the genetic model of a complex trait and the associated genetic parameters, including the number, positions, and main and epistatic effects of the identified QTL. Our method can map a large number of QTL with any combination of main and epistatic effects. Utility and flexibility of the method are demonstrated using both simulated data and a real data set. Sensitivity of posterior inference to prior specifications of the number and genetic effects of QTL is investigated.

Bayes Theorem↗
PubMed2004

Optimal sampling of a population to determine QTL location, variance, and allelic number.

In a population intended for breeding and selection, questions of interest relative to a specific segregating QTL are the variance it generates in the population, and the number and effects of its alleles. One approach to address these questions is to extract several inbreds from the population and use them to generate multiple mapping families. Given random sampling of parents, sampling strategy may be an important factor determining the power of the analysis and its accuracy in estimating QTL variance and allelic number. We describe appropriate multiple-family QTL mapping methodology and apply it to simulated data sets to determine optimal sampling strategies in terms of family number versus family size. Genomes were simulated with seven chromosomes, on which 107 markers and six QTL were distributed. The total heritability was 0.60. Two to ten alleles were segregating at each QTL. Sampling strategies ranged from sampling two inbreds and generating a single family of 600 progeny to sampling 40 inbreds and generating 40 families of 15 progeny each. Strategies involving only one to five families were subject to variation due to the sampling of inbred parents. For QTL where more than two alleles were segregating, these strategies did not sample QTL alleles representative of the original population. Conversely, strategies involving 30 or more parents were subject to variation due to sampling of QTL genotypes within the small families obtained. Given these constraints, greatest QTL detection power was obtained for strategies involving five to ten mapping families. The most accurate estimation of the variance generated by the QTL, however, was obtained with strategies involving 20 or more families. Finally, strategies with an intermediate number of families best estimated the number of QTL alleles. We conclude that no overall optimal sampling strategy exists but that the strategy adopted must depend on the objective.

Alleles↗
PubMed2001

Inbred lines of mice derived from long-term growth selected lines: unique resources for mapping growth genes.

Lines of mice selected for many generations for high or low growth in several laboratories around the world have been collected, and from these, inbred lines are being developed by recurrent full-sib mating in Edinburgh. There are seven high selected lines and four low lines (each low line is from the same base population as one of the high lines), and the histories of each are summarized. Mean body weight of males at 70 days of age in the Edinburgh laboratory in the heaviest inbred line (77 g) is 4.8-fold higher than in the lightest line (16 g), and 1.9-fold higher than in the least extreme high line (41 g). Litter size, food intake, and fat content also differ substantially. These inbred extreme selected lines are a uniquely valuable resource for QTL or gene mapping, candidate gene identification, and elucidation of epistatic effects.

Animals↗
PubMed1998

Quantitative trait loci for honey bee stinging behavior and body size.

A study was conducted to identify quantitative trait loci (QTLs) that affect colony-level stinging behavior and individual body size of honey bees. An F1 queen was produced from a cross between a queen of European origin and a drone descended from an African subspecies. Haploid drones from the hybrid queen were individually backcrossed to sister European queens to produce 172 colonies with backcross workers that were evaluated for tendency to sting. Random amplified polymorphic DNA markers were scored from the haploid drone fathers of these colonies. Wings of workers and drones were used as a measure of body size because Africanized bees in the Americas are smaller than European bees. Standard interval mapping and multiple QTL models were used to analyze data. One possible QTL was identified with a significant effect on tendency to sting (LOD 3.57). Four other suggestive QTLs were also observed (about LOD 1.5). Possible QTLs also were identified that affect body size and were unlinked to defensive-behavior QTLs. Two of these were significant (LOD 3.54 and 5.15).

Animals↗
PubMed2003

Quantitative trait loci affecting milk production traits in Finnish Ayrshire dairy cattle.

A whole genome scan of Finnish Ayrshire was conducted to map quantitative trait loci (QTL) affecting milk production. The analysis included 12 half-sib families containing a total of 494 bulls in a granddaughter design. The families were genotyped with 150 markers to construct a 2764 cM (Haldane) male linkage map. In this study interval mapping with multiple-marker regression approach was extended to analyse multiple chromosomes simultaneously. The method uses identified QTL on other chromosomes as cofactors to increase mapping power. The existence of multiple QTL on the same linkage group was also analyzed by fitting a two-QTL model to the analysis. Empirical values for chromosome-wise significance thresholds were determined using a permutation test. Two genome-wise significant QTL were identified when chromosomes were analyzed individually, one affecting fat percentage on chromosome (BTA) 14 and another affecting fat yield on BTA12. The cofactor analysis revealed in total 31 genome-wise significant QTL. The result of two-QTL analysis suggests the existence of two QTL for fat percentage on BTA3. In general, most of the identified QTL confirm results from previous studies of Holstein-Friesian cattle. A new QTL for all yield components was identified on BTA12 in Finnish Ayrshire.

Animals↗
PubMed2001

Enhanced efficiency of quantitative trait loci mapping analysis based on multivariate complexes of quantitative traits.

An approach to increase the efficiency of mapping quantitative trait loci (QTL) was proposed earlier by the authors on the basis of bivariate analysis of correlated traits. The power of QTL detection using the log-likelihood ratio (LOD scores) grows proportionally to the broad sense heritability. We found that this relationship holds also for correlated traits, so that an increased bivariate heritability implicates a higher LOD score, higher detection power, and better mapping resolution. However, the increased number of parameters to be estimated complicates the application of this approach when a large number of traits are considered simultaneously. Here we present a multivariate generalization of our previous two-trait QTL analysis. The proposed multivariate analogue of QTL contribution to the broad-sense heritability based on interval-specific calculation of eigenvalues and eigenvectors of the residual covariance matrix allows prediction of the expected QTL detection power and mapping resolution for any subset of the initial multivariate trait complex. Permutation technique allows chromosome-wise testing of significance for the whole trait complex and the significance of the contribution of individual traits owing to: (a) their correlation with other traits, (b) dependence on the chromosome in question, and (c) both a and b. An example of application of the proposed method on a real data set of 11 traits from an experiment performed on an F(2)/F(3) mapping population of tetraploid wheat (Triticum durum x T. dicoccoides) is provided.

Chromosome Mapping↗
PubMed2003

Molecular dissection of a quantitative trait locus: a phenylalanine-to-tyrosine substitution in the transmembrane domain of the bovine growth hormone receptor is associated with a major effect on milk yield and composition.

We herein report on our efforts to improve the mapping resolution of a QTL with major effect on milk yield and composition that was previously mapped to bovine chromosome 20. By using a denser chromosome 20 marker map and by exploiting linkage disequilibrium using two distinct approaches, we provide strong evidence that a chromosome segment including the gene coding for the growth hormone receptor accounts for at least part of the chromosome 20 QTL effect. By sequencing individuals with known QTL genotype, we identify an F to Y substitution in the transmembrane domain of the growth hormone receptor gene that is associated with a strong effect on milk yield and composition in the general population.

Amino Acid Substitution↗
PubMed2005

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↗
PubMed2006

Effects of quantitative trait loci on chromosomes 1, 2, 4, and 7 on growth, carcass, and meat quality traits in backcross Meishan x Large White pigs.

The aim of this work was to estimate whether genetic dissection of QTL on chromosomes 1, 2, 4, and 7, detected in an F2 Meishan x Large White population, can be achieved with a recombinant back-cross progeny test approach. For this purpose, a first generation of backcross (BC1) was produced by using frozen semen of F1 Large White x Meishan boars with Large White females. Four BC1 boars were selected because of their heterozygosity for at least 1 of the 4 regions. The BC1 boars were crossed with Large White sows, and the resulting BC2 offspring were measured for several growth and body composition traits. Contrary to the F2 animals, BC2 animals were also measured for meat quality traits in adductor, gluteus superficialis (GS), longissimus dorsi, and biceps femoris (BF) muscles. Each BC1 boar was tested for a total of 39 traits and for the 4 regions with statistical interval mapping analyses. The QTL effects obtained in BC1 families showed some differences compared with those described in F1 families. However, we confirmed QTL effects for growth in the SW1301-SW2512 markers interval on chromosome 1 and also for body composition in the SW1828-SW2512 markers interval on chromosome 1, in the SW2443-SWR783 markers interval on chromosome 2, and in the SW1369-SW632 markers interval on chromosome 7. In addition, we detected new QTL for growth traits on chromosome 2 and for meat quality traits on chromosomes 1 and 2. Growth of animals from weaning to the end of the test was influenced by the IGF2 gene region on chromosome 2. Concerning meat quality, ultimate pH of adductor, longissimus dorsi, and BF were affected by the interval delimited by UMNP3000 and SW2512 markers on chromosome 1, and a* of GS, L* of BF, and water-holding capacity of GS were affected by QTL located between marker loci SW2443 and SWR783 on chromosome 2. Recombinant progeny testing appeared to be a suitable strategy for the genetic dissection of the QTL investigated.

Adipose Tissue↗
PubMed2002

A genome scan for quantitative trait loci in a wild population of red deer (Cervus elaphus).

Recent empirical evidence indicates that although fitness and fitness components tend to have low heritability in natural populations, they may nonetheless have relatively large components of additive genetic variance. The molecular basis of additive genetic variation has been investigated in model organisms but never in the wild. In this article we describe an attempt to map quantitative trait loci (QTL) for birth weight (a trait positively associated with overall fitness) in an unmanipulated, wild population of red deer (Cervus elaphus). Two approaches were used: interval mapping by linear regression within half-sib families and a variance components analysis of a six-generation pedigree of >350 animals. Evidence for segregating QTL was found on three linkage groups, one of which was significant at the genome-wide suggestive linkage threshold. To our knowledge this is the first time that a QTL for any trait has been mapped in a wild mammal population. It is hoped that this study will stimulate further investigations of the genetic architecture of fitness traits in the wild.

Animals↗
PubMed2004

Fine mapping of a murine growth locus to a 1.4-cM region and resolution of linked QTL.

Previous work identified a QTL affecting murine size (particularly tail length) in a cross between C57BL/6J and DBA/2J mice and refined its location to an 8-cM region between D1Mit30 and D1Mit57. The present study used recombinant progeny testing to fine map this QTL. Individuals from a partially congenic strain carrying chromosomes recombinant between D1Mit30 and D1Mit57 were mated to DBA/2J, generating 942 progeny. Two QTL affecting 10-week tail length were identified in this population: one at 9.7 cM distal to D1Mit30 (the position estimated in previous work), and another of smaller effect near D1Mit30. A second population ( n = 787) was generated by mating siblings from the progeny test population that were heterozygous for the same segment of chromosome, including only recombinants between D1Mit265 and D1Mit57. In the latter population, two QTL were also identified: one at 10.2 cM distal to D1Mit30, and another of smaller effect at the distal end of the mapped region (at D1Mit150). When the two populations were analyzed together, the estimated location of the central QTL was 10.2 cM distal to D1Mit30 and there was marginally significant evidence of the distal QTL. The central QTL explained approximately 7% of the phenotypic variance, and the 95% confidence interval for its position (determined by bootstrapping) was a 1.4-cM region, approximately the region from D1Mit451 to D1Mit219. The central QTL also affected tail length and body mass at 3 and 6 weeks of age, but to a lesser degree than 10-week tail length.

Animals↗
PubMed1998

The molecular basis of quantitative genetic variation in central and secondary metabolism in Arabidopsis.

To find the genes controlling quantitative variation, we need model systems where functional information on physiology, development, and gene regulation can guide evolutionary inferences. We mapped quantitative trait loci (QTLs) influencing quantitative levels of enzyme activity in primary and secondary metabolism in Arabidopsis. All 10 enzymes showed highly significant quantitative genetic variation. Strong positive genetic correlations were found among activity levels of 5 glycolytic enzymes, PGI, PGM, GPD, FBP, and G6P, suggesting that enzymes with closely related metabolic functions are coregulated. Significant QTLs were found influencing activity of most enzymes. Some enzyme activity QTLs mapped very close to known enzyme-encoding loci (e.g., hexokinase, PGI, and PGM). A hexokinase QTL is attributable to cis-acting regulatory variation at the AtHXK1 locus or a closely linked regulatory locus, rather than polypeptide sequence differences. We also found a QTL on chromosome IV that may be a joint regulator of GPD, PGI, and G6P activity. In addition, a QTL affecting PGM activity maps within 700 kb of the PGM-encoding locus. This QTL is predicted to alter starch biosynthesis by 3.4%, corresponding with theoretical models, suggesting that QTLs reflect pleiotropic effects of mutant alleles.

Analysis of Variance↗