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At least 505 records · Page 28Linked to original sources
PubMed2004

Identification and fine mapping of quantitative trait loci for backfat on bovine chromosomes 2, 5, 6, 19, 21, and 23 in a commercial line of Bos taurus.

Backfat thickness is one of the major quantitative traits that affects carcass quality in beef cattle. In this study, we identified and fine-mapped QTL for backfat EBV on bovine chromosomes 2, 5, 6, 19, 21, and 23 using an identical-by-descent haplotype-sharing analysis in a commercial line of Bos taurus. Eleven haplotypes were found to have significant associations with backfat EBV at the comparison-wise P-value threshold, and one at the chromosome-wise P-value threshold on bovine chromosomes 5, 6, 19, 21, and 23. On average, the 12 significant haplotypes had an effect of 0.62 SD on backfat EBV, ranging from 0.38 SD to 1.33 SD. The 12 significant haplotypes spanned nine chromosomal regions, one on chromosome 5 (65.4 to 70.0 cM), three on 6 (8.2 to 11.8 cM, 63.6 to 68.1 cM, and 81.5 to 83.0 cM), three on 19 (4.8 to 15.9 cM, 39.4 to 46.5 cM, and 65.7 to 99.5 cM), one on 21 (46.1 to 53.1 cM), and one on 23 (45.1 to 50.9 cM). Among the nine chromosomal regions, six were new QTL regions and three showed remarkable agreement with QTL regions that were previously reported. Eight of the nine QTL regions were localized to less than or close to 10 cM in genetic distance. The results provide a useful reference for further positional candidate gene research and marker-assisted selection for backfat.

Adipose Tissue↗
PubMed1996

Type I and type II error rates for quantitative trait loci (QTL) mapping studies using recombinant inbred mouse strains.

Effective mapping strategies for quantitative trains must allow for the detection of the more important quantitative trait loci (QTLs) while minimizing false positives. Type I (false-positive) and Type II (false-negative) error rates were estimated from a computer simulation of QTL mapping in the BXD recombinant inbred (RI) set compromising 26 strains of mice, and comparisons made with theoretical predictions. The results are generally applicable to other RI sets when corrections are made for differing strain numbers and marker densities. Regardless of the number or magnitude of simulated QTLs contributing to the trait variance, the p value necessary to provide adequate protection against both Type I (alpha=.0001) and Type II (beta=.2) errors, a QTL would have to account for more than half of the between-strain (genetic) variance if the BXD or similar set was used alone. In contrast, a two-step mapping strategy was also considered, where RI strains are used as a preliminary screen for QTLs to be specifically tested (confirmed) in an F2 (or other) population. In this case, QTLs accounting for approximately 16% of the between-strain variance could be detected with an 80% probability in the BXD set when alpha = 0.2. To balance the competing goals of minimizing Type I and II errors, an economical strategy is to adopt a more stringent alpha initially for the RI screen, since this requires only a limited genome search in the F2 of the RI-implicated regions (approximately 10% of the F2 genome when p < .01 in the RIs). If confirmed QTLs do not account in the aggregate for a sufficient proportion of the genetic variance, then a more relaxed alpha value can be used in the RI screen to increase the statistical power. This flexibility in setting RI alpha values is appropriate only when adequate protection against Type I errors comes from the F2 (or other) confirmation test(s).

Animals↗
PubMedDate not supplied

The efficiency of designs for fine-mapping of quantitative trait loci using combined linkage disequilibrium and linkage.

In a simulation study, different designs were compared for efficiency of fine-mapping of QTL. The variance component method for fine-mapping of QTL was used to estimate QTL position and variance components. The design of many families with small size gave a higher mapping resolution than a design with few families of large size. However, the difference is small in half sib designs. The proportion of replicates with the QTL positioned within 3 cM of the true position is 0.71 in the best design, and 0.68 in the worst design applied to 128 animals with a phenotypic record and a QTL explaining 25% of the phenotypic variance. The design of two half sib families each of size 64 was further investigated for a hypothetical population with effective size of 1000 simulated for 6000 generations with a marker density of 0.25 cM and with marker mutation rate 4 x10(-4) per generation. In mapping using bi-allelic markers, 42 approximately 55 of replicated simulations could position QTL within 0.75 cM of the true position whereas this was higher for multi allelic markers (48 approximately 76 ). The accuracy was lowest (48%) when mutation age was 100 generations and increased to 68% and 76% for mutation ages of 200 and 500 generations, respectively, after which it was about 70% for mutation ages of 1000 generations and older. When effective size was linearly decreasing in the last 50 generations, the accuracy was decreased (56 to 70%). We show that half sib designs that have often been used for linkage mapping can have sufficient information for fine-mapping of QTL. It is suggested that the same design with the same animals for linkage mapping should be used for fine-mapping so gene mapping can be cost effective in livestock populations.

Alleles↗
PubMed2003

Fine mapping of quantitative trait loci and assessment of positional candidate genes for backfat on bovine chromosome 14 in a commercial line of Bos taurus.

Backfat thickness is one of the major quantitative traits that affect carcass quality in beef cattle. In this study, we have fine mapped a QTL for backfat EBV on bovine chromosome 14, using an identical-by-descent haplotype-sharing analysis, in a commercial line of Bos taurus. We also examined the association between gene-specific single nucleotide polymorphism (SNP) markers of the genes diacylgcerol acyltransferase 1 (DGAT1) and thyroglobulin (TG) and the backfat EBV. The results indicate that the QTL region for backfat identified on chromosome 14 is in agreement with previous studies. However, neither of the two polymorphisms of candidate genes tested, DGAT1 nor TG, showed a significant (P > 0.10) association with the backfat EBV in the cattle populations examined. However, a strong association (P = 0.0058) was detected between a microsatellite marker (CSSM66) lying approximately mid-way between the two candidate genes and the backfat EBV. These results suggest that other SNP of DGAT1, TG, or other gene(s) in the chromosomal region should be examined to test whether they have a significant effect on lipid metabolism.

Acyltransferases↗
PubMed2002

Fine mapping of a quantitative trait locus for twinning rate using combined linkage and linkage disequilibrium mapping.

A novel and robust method for the fine-scale mapping of genes affecting complex traits, which combines linkage and linkage-disequilibrium information, is proposed. Linkage information refers to recombinations within the marker-genotyped generations and linkage disequilibrium to historical recombinations before genotyping started. The identity-by-descent (IBD) probabilities at the quantitative trait locus (QTL) between first generation haplotypes were obtained from the similarity of the marker alleles surrounding the QTL, whereas IBD probabilities at the QTL between later generation haplotypes were obtained by using the markers to trace the inheritance of the QTL. The variance explained by the QTL is estimated by residual maximum likelihood using the correlation structure defined by the IBD probabilities. Unlinked background genes were accounted for by fitting a polygenic variance component. The method was used to fine map a QTL for twinning rate in cattle, previously mapped on chromosome 5 by linkage analysis. The data consisted of large half-sib families, but the method could also handle more complex pedigrees. The likelihood of the putative QTL was very small along most of the chromosome, except for a sharp likelihood peak in the ninth marker bracket, which positioned the QTL within a region <1 cM in the middle part of bovine chromosome 5. The method was expected to be robust against multiple genes affecting the trait, multiple mutations at the QTL, and relatively low marker density.

Animals↗
PubMed1996

A genetic map of quantitative trait loci for body weight in the mouse.

The genetic basis of body weight in the mouse was investigated by measuring frequency changes of microsatellite marker alleles in lines divergently selected for body weight from a base population of a cross between two inbred strains. In several regions of the genome, sharp peaks of frequency change at linked markers were detected, which suggested the presence of single genes of moderate effect, although in several other regions, significant frequency changes occurred over large portions of chromosomes. A method based on maximum likelihood was used to infer effects and map positions of quantitative trait loci (QTLs) based on genotype frequencies at one or more marker loci. Eleven QTLs with effects in the range 0.17-0.28 phenotypic standard deviations were detected; but under an additive model, these did not fully account for the observed selection response. Tests for the presence of more than one QTL in regions where there were large changes of marker allele frequency were mostly inconclusive.

Alleles↗
PubMed2003

High-resolution mapping of quantitative trait loci by selective recombinant genotyping.

Selective recombinant genotyping (SRG) is a three-stage procedure for high-resolution mapping of a QTL that has previously been mapped to a known confidence interval (target C.I.). In stage 1, a large mapping population is accessed and phenotyped, and a proportion, P, of the high and low tails is selected. In stage 2, the selected individuals are genotyped for a pair of markers flanking the target C.I., and a group of R individuals carrying recombinant chromosomes in the target interval are identified. In stage 3, the recombinant individuals are genotyped for a set of M markers spanning the target C.I. Extensive simulations showed that: (1) Standard error of QTL location (SEQTL) decreased when QTL effect (d) or population size (N) increased, but was constant for given "power factor" (PF = d(2)N); (2) increasing the proportion selected in the tails beyond 0.25 had only a negligible effect on SEQTL; and (3) marker spacing in the target interval had a remarkably powerful effect on SEQTL, yielding a reduction of up to 10-fold in going from highest (24 cM) to lowest (0.29 cM) spacing at given population size and QTL effect. At the densest marker spacing, SEQTL of 1.0-0.06 cM were obtained at PF = 500-16,000. Two new genotyping procedures, the half-section algorithm and the golden section/half-section algorithm, allow the equivalent of complete haplotyping of the target C.I. in the recombinant individuals to be achieved with many fewer data points than would be required by complete individual genotyping.

Algorithms↗
PubMed2006

Mapping of quantitative trait loci determining NK cell-mediated resistance to MHC class I-deficient bone marrow grafts in perforin-deficient mice.

NK cells reject allogeneic and MHC class I-deficient bone marrow (BM) grafts in vivo. The mechanisms used by NK cells to mediate this rejection are not yet thoroughly characterized. Although perforin plays a major role, perforin-independent mechanisms are involved as well. C57BL/6 mice deficient in perforin (B6 perforin knockout (PKO)) reject class I-deficient TAP-1 KO BM cells as efficiently as normal B6 mice. In contrast, perforin-deficient 129S6/SvEvTac mice (129 PKO) cannot mediate this rejection while normal 129 mice efficiently reject. This suggests that in 129, but not in B6, mice, perforin is crucial for NK cell-mediated rejection of MHC class I-deficient BM grafts. To identify loci linked to BM rejection in perforin-deficient mice, we generated backcross 1 progeny by crossing (129 x B6)F(1) PKO mice to 129 PKO mice. In transplantation experiments, >350 backcross 1 progeny were analyzed and displayed a great variation in ability to reject TAP-1 KO BM grafts. PCR-based microsatellite mapping identified four quantitative trait loci (QTL) on chromosomes 2, 4, and 8, with the QTL on chromosome 8 showing the highest significance, as well as a fifth epistatic QTL on chromosome 3. This study describes the first important step toward identifying BM graft resistance gene(s).

Animals↗
PubMed2001

Mapping of quantitative trait locus related to submergence tolerance in rice with aid of chromosome walking.

The major QTL for submergence tolerance was locate in the 5.9 cM interval between flanking RFLP markers. To narrow down this region, a physical map was constructed using YAC and BAC clones. A 400-kb YAC was identified in this region and later its end fragments were used to screen a rice BAC library. Through chromosome walking, 24 positive BAC clones formed two contigs around linked-RFLP markers, R1164 and RZ698. Using one YAC end, six BAC ends and three RFLP markers, a fine-scale map was constructed of the 6.8-cM interval of S10709-RZ698 on rice chromosome 9. The submergence tolerance and related trait were located in a small, well-defined region around BAC-end marker 180D1R and RFLP marker R1164. The physical-to-map distance ratio in this region is as small as 172.5 kb/cM, showing that this region is a hot spot for recombination in the rice genome.

Chromosome Walking↗
PubMed2005

Structured antedependence models for functional mapping of multiple longitudinal traits.

In this article, we present a statistical model for mapping quantitative trait loci (QTL) that determine growth trajectories of two correlated traits during ontogenetic development. This model is derived within the maximum likelihood context, incorporated by mathematical aspects of growth processes to model the mean vector and by structured antedependence (SAD) models to approximate time-dependent covariance matrices for longitudinal traits. It provides a quantitative framework for testing the relative importance of two mechanisms, pleiotropy and linkage, in contributing to genetic correlations during ontogeny. This model has been employed to map QTL affecting stem height and diameter growth trajectories in an interspecific hybrid progeny of Populus, leading to the successful discovery of three pleiotropic QTL on different linkage groups. The implications of this model for genetic mapping within a broader context are discussed.

Journal Article↗
PubMed2002

Conservation of gene function in the solanaceae as revealed by comparative mapping of domestication traits in eggplant.

Quantitative trait loci (QTL) for domestication-related traits were identified in an interspecific F(2) population of eggplant (Solanum linnaeanum x S. melongena). Although 62 quantitative trait loci (QTL) were identified in two locations, most of the dramatic phenotypic differences in fruit weight, shape, color, and plant prickliness that distinguish cultivated eggplant from its wild relative could be attributed to six loci with major effects. Comparison of the genomic locations of the eggplant fruit weight, fruit shape, and color QTL with the positions of similar loci in tomato, potato, and pepper revealed that 40% of the different loci have putative orthologous counterparts in at least one of these other crop species. Overall, the results suggest that domestication of the Solanaceae has been driven by mutations in a very limited number of target loci with major phenotypic effects, that selection pressures were exerted on the same loci despite the crops' independent domestications on different continents, and that the morphological diversity of these four crops can be explained by divergent mutations at these loci.

Chromosome Mapping↗
PubMed2002

Mapping of quantitative trait loci determining agronomic important characters in hexaploid wheat ( Triticum aestivum L.).

A set of 114 recombinant inbred lines of the 'International Triticeae Mapping Initiative' mapping population was grown during the seasons 1997, 1998, 1999 and 2000 under several environments. Twenty morphological (glume colour, awn colour, waxiness, leaf erectness, peduncle length), agronomical (ear emergence time, flowering time, grain filling time, ear length, plant height, lodging, grain number, thousand-grain-weight, grain weight per ear, grain protein content, winter hardiness) and disease resistance (powdery mildew, yellow rust, leaf rust, fusarium) traits were studied. Not all traits were scored in each experiment. In total 210 QTLs with a LOD threshold of >2.0 (minor QTLs) were detected of which 64 reached a LOD score of >3.0 (major QTLs). Often QTLs were detected in comparable positions in different experiments. Homologous and homoeologous relationships of the detected QTLs, and already described major genes or QTLs determining the same traits in wheat or other Triticeae members, are discussed.

Journal Article↗
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↗
PubMed2006

The efficiency of mapping of quantitative trait loci using cofactor analysis in half-sib design.

This simulation study was designed to study the power and type I error rate in QTL mapping using cofactor analysis in half-sib designs. A number of scenarios were simulated with different power to identify QTL by varying family size, heritability, QTL effect and map density, and three threshold levels for cofactor were considered. Generally cofactor analysis did not increase the power of QTL mapping in a half-sib design, but increased the type I error rate. The exception was with small family size where the number of correctly identified QTL increased by 13% when heritability was high and 21% when heritability was low. However, in the same scenarios the number of false positives increased by 49% and 45% respectively. With a liberal threshold level of 10% for cofactor combined with a low heritability, the number of correctly identified QTL increased by 14% but there was a 41% increase in the number of false positives. Also, the power of QTL mapping did not increase with cofactor analysis in scenarios with unequal QTL effect, sparse marker density and large QTL effect (25% of the genetic variance), but the type I error rate tended to increase. A priori, cofactor analysis was expected to have higher power than individual chromosome analysis especially in experiments with lower power to detect QTL. Our study shows that cofactor analysis increased the number of false positives in all scenarios with low heritability and the increase was up to 50% in low power experiments and with lower thresholds for cofactors.

Chromosome Mapping↗
PubMed2005

Functional mapping of quantitative trait loci that interact with the hg mutation to regulate growth trajectories in mice.

The high growth (hg) mutation increases body size in mice by 30-50%. Given the complexity of the genetic regulation of animal growth, it is likely that the effect of this major locus is mediated by other quantitative trait loci (QTL) with smaller effects within a web of gene interactions. In this article, we extend our functional mapping model to characterize modifier QTL that interact with the hg locus during ontogenetic growth. Our model is derived within the maximum-likelihood context, incorporated by mathematical aspects of growth laws and implemented with the EM algorithm. In an F2 population founded by a congenic high growth (HG) line and non-HG line, a highly additive effect due to the hg gene was detected on growth trajectories. Three QTL located on chromosomes 2 and X were identified to trigger significant additive and/or dominant effects on the process of growth. The most significant finding made from our model is that these QTL interact with the hg locus to affect the shapes of the growth process. Our model provides a powerful means for understanding the genetic architecture and regulation of growth rate and body size in mammals.

Age Factors↗
PubMed1998

Complex traits on the map.

The lod score method for localizing mendelian disease genes in human genetics is reviewed. Current ways of applying this technique to hypothesized genes underlying complex traits are discussed. In contrast to these parametric methods, allele-sharing methods using affected sib pairs are reviewed. Based on such allele-sharing data, a particular type of analysis is outlined which can identify sets of disease loci. This method makes use of pattern-recognition techniques as implemented in artificial neural networks (ANNs).

Alleles↗