QTL influencing autoimmune diabetes and encephalomyelitis map to a 0.15-cM region containing Il2.
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Amino Acid Sequence↗
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[Microsatellite linkage map of rainbow trout and its application for QTL analysis].
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Animals↗
Functional mapping of quantitative trait loci underlying the character process: a theoretical framework.
Unlike a character measured at a finite set of landmark points, function-valued traits are those that change as a function of some independent and continuous variable. These traits, also called infinite-dimensional characters, can be described as the character process and include a number of biologically, economically, or biomedically important features, such as growth trajectories, allometric scalings, and norms of reaction. Here we present a new statistical infrastructure for mapping quantitative trait loci (QTL) underlying the character process. This strategy, termed functional mapping, integrates mathematical relationships of different traits or variables within the genetic mapping framework. Logistic mapping proposed in this article can be viewed as an example of functional mapping. Logistic mapping is based on a universal biological law that for each and every living organism growth over time follows an exponential growth curve (e.g., logistic or S-shaped). A maximum-likelihood approach based on a logistic-mixture model, implemented with the EM algorithm, is developed to provide the estimates of QTL positions, QTL effects, and other model parameters responsible for growth trajectories. Logistic mapping displays a tremendous potential to increase the power of QTL detection, the precision of parameter estimation, and the resolution of QTL localization due to the small number of parameters to be estimated, the pleiotropic effect of a QTL on growth, and/or residual correlations of growth at different ages. More importantly, logistic mapping allows for testing numerous biologically important hypotheses concerning the genetic basis of quantitative variation, thus gaining an insight into the critical role of development in shaping plant and animal evolution and domestication. The power of logistic mapping is demonstrated by an example of a forest tree, in which one QTL affecting stem growth processes is detected on a linkage group using our method, whereas it cannot be detected using current methods. The advantages of functional mapping are also discussed.
Chromosome Mapping↗
QTL analysis in arbitrary pedigrees with incomplete marker information.
Mapping quantitative trait loci (QTL) in arbitrary outbred pedigrees is complicated by the combinatorial possibilities of allele flow relationships and of the founder allelic configurations. Exact methods are only available for rather short and simple pedigrees. Stochastic simulation using Markov chain Monte Carlo (MCMC) integration offers more flexibility. MCMC methods are less natural in a frequentist than in a Bayesian context, which we therefore adopt. Among the MCMC algorithms for updating marker locus genotypes, we implement the descent-graph algorithm. It can be used to update marker locus allele flow relationships and can handle arbitrarily complex pedigrees and missing marker information. Compared with updating marker genotypic information, updating QTL parameters, such as position, effects, and the allele flow relationships is relatively easy with MCMC. We treat the effect of each diploid combination of founder alleles as a random variable and only estimate the variance of these effects, ie, we model diploid genotypic effects instead of the usual partition in additive and dominance effects. This is a variant of the random model approach. The number of QTL alleles is generally unknown. In the Bayesian context, the number of QTL present on a linkage group can be treated as variable. Computer simulations suggest that the algorithm can indeed handle complex pedigrees and detect two QTL on a linkage group, but that the number of individuals in a single extended family is limited to about 50 to 100 individuals.
Chromosome Mapping↗
Detection of QTL for milk production on Chromosomes 1 and 6 of Holstein cattle.
Seventy to 75 sons of each of six Holstein sires were assayed for genotypes at a number of microsatellite loci spanning Chromosomes (Chrs) 1 and 6. The number of informative loci varied from three to eight on each chromosome in different sire families. Linkage order and map distance for microsatellite loci were estimated using CRI-MAP. Estimates of QTL effect and location were made by using a least squares interval mapping approach based on daughter yield deviations of sons for 305-d milk, fat, protein yield, and fat and protein percentage. Thresholds for statistical significance of QTL effects were determined from interval mapping of 10,000 random permutations of the data across the bull sire families and within each sire family separately. Across-sire analyses indicated a significant QTL for fat and protein yield, and fat percentage on Chr 1, and QTL effects on milk yield and protein percentage that might represent one or two QTL on Chr 6. Analyses within each sire family indicated significant QTL effects in five sire families, with one sire possibly being heterozygous for two QTLs. Statistically significant estimates of QTL effects on breeding value ranged from 340 to 640 kg of milk, from 15.6 to 28.4 kg of fat, and 14.4 to 17.6 kg of protein.
Alleles↗
Quantitative trait loci affecting delta13C and response to differential water availibility in Arabidopsis thaliana.
Phenotypic plasticity is an important response mechanism of plants to environmental heterogeneity. Here, we explored the genetic basis of plastic responses of Arabidopsis thaliana to water deficit by experimentally mapping quantitative trait loci (QTL) in two recombinant inbred populations (Cvi x Ler and Ler x Col). We detected genetic variation and significant genotype-by-environment interactions for many traits related to water use. We also mapped 26 QTL, including six for carbon isotope composition (delta13C). Negative genetic correlations between fruit length and fruit production as well as between flowering time and branch production were corroborated by QTL colocalization, suggesting these correlations are due to pleiotropy or physical linkage. Water-limited plants were more apically dominant with greater root:shoot ratios and higher delta13C (higher water-use efficiency) when compared to well-watered plants. Many of the QTL effects for these traits interacted significantly with the irrigation treatment, suggesting that the observed phenotypic plasticity is genetically based. We specifically searched for epistatic (QTL-QTL) interactions using a two-dimensional genome scan, which allowed us to detect epistasis regardless of additive genetic effects. We found several significant QTL-QTL interactions including three that exhibited environmental dependence. These results provide preliminary evidence for proposed genetic mechanisms underlying phenotypic plasticity.
Arabidopsis↗
QTL MatchMaker: a multi-species quantitative trait loci (QTL) database and query system for annotation of genes and QTL.
Identifying genes that underlie quantitative trait loci (QTL) is a challenging task. Here, we present a new QTL software system, named QTL MatchMaker. The system is designed to integrate and mine QTL information across human, mouse and rat genomes and to annotate functional genomic data. It combines and organizes information from relevant public databases and publications and integrates QTL, physical, genetic and cytogenetic maps across human, mouse and rat. To make this application available to the research community we have developed a website for high-throughput mapping of expressed sequences to QTL and for selection of candidate genes in the physiological genomics context of complex traits. QTL MatchMaker is accessible at http://pmrc.med.mssm.edu:9090/QTL/jsp/qtlhome.jsp.
Animals↗
Cross-species bacterial artificial chromosome (BAC) library screening via overgo-based hybridization and BAC-contig mapping of a yield enhancement quantitative trait locus (QTL) yld1.1 in the Malaysian wild rice Oryza rufipogon.
The construction of BAC-contig physical maps is an important step towards a partial or ultimate genome sequence analysis. Here, we describe our initial efforts to apply an overgo approach to screen a BAC library of the Malaysian wild rice species, Oryza rufipogon. Overgo design is based on repetitive element masking and sequence uniqueness, and uses short probes (approximately 40 bp), making this method highly efficient and specific. Pairs of 24-bp oligos that contain an 8-bp overlap were developed from the publicly available genomic sequences of the cultivated rice, O. sativa, to generate 20 overgo probes for a 1-Mb region that encompasses a yield enhancement QTL yld1.1 in O. rufipogon. The advantages of a high similarity in melting temperature, hybridization kinetics and specific activities of overgos further enabled a pooling strategy for library screening by filter hybridization. Two pools of ten overgos each were hybridized to high-density filters representing the O. rufipogon genomic BAC library. These screening tests succeeded in providing 69 PCR-verified positive hits from a total of 23,040 BAC clones of the entire O. rufipogon library. A minimal tilling path of clones was generated to contribute to a fully covered BAC-contig map of the targeted 1-Mb region. The developed protocol for overgo design based on O. sativa sequences as a comparative genomic framework, and the pooled overgo hybridization screening technique are suitable means for high-resolution physical mapping and the identification of BAC candidates for sequencing.
Chromosomes, Artificial, Bacterial↗
FunMap: functional mapping of complex traits.
SUMMARY: FunMap is a Web-based user interface designed to map quantitative trait loci (QTL) affecting function-valued traits or infinite-dimensional traits in well-structured pedigrees or natural populations. User input includes three files: longitudinal trait data, marker genotypes and/or a linkage map. This software allows for a systematic genome-wide scan and significance test of QTL throughout the map. The dynamic change of QTL effects during the time course of growth is automatically drawn, from which specific biological hypotheses regarding the genetic control mechanisms of growth and development can be tested. AVAILABILITY: http://web.biostat.ufl.edu/~cma/genetics/software.html
Chromosome Mapping↗
Involvement of antibody production quantitative trait loci in the susceptibility to pristane-induced arthritis in the mouse.
Mice obtained by bidirectional selective breeding for high (HIII) or low (LIII) antibody (Ab) production are resistant or extremely susceptible to pristane-induced arthritis (PIA), respectively. Several quantitative trait loci regulating Ab production (Ab QTL) have been mapped in these lines, which were used to investigate the influence of these Ab QTL in PIA. Parental HIII and LIII mice and their F1 and F2 intercrosses were injected twice with pristane, and arthritis was observed for 200 days. In LIII mice PIA was more severe and incidence was 100% at day 105, while F1 and F2 mice showed intermediate values. HIII mice were totally resistant. Microsatellite polymorphisms of Ab QTL were analysed and D3Mit100 alleles cosegregated significantly with PIA incidence, severity and onset in F2 intercross mice, while the other four markers showed suggestive values. Results indicate colocalization of QTL for Ab production and PIA susceptibility. Moreover, the different cytokine and IgG isotype profiles observed in HIII and LIII lines after PIA induction are useful to candidate genes endowed with the regulation of the Ab production and arthritis phenotypes.
Animals↗
Quantitative trait loci affecting fertility and calving traits in Swedish dairy cattle.
Impaired fertility is the main reason for involuntary culling of dairy cows in Sweden. The objective of this study was to map quantitative trait loci (QTL) influencing fertility and calving traits in the Swedish dairy cattle population. The traits analyzed were number of inseminations, 56-d nonreturn rate, interval from calving to first insemination, fertility treatments, heat intensity score, stillbirth, and calving performance. A genome scan covering 20 bovine chromosomes was performed using 145 microsatellite markers. The mapping population consisted of 10 sires and their 417 sons in a granddaughter design. Nine of the sires were of the Swedish Red Breed, and one was a Swedish Holstein. Least squares regression was used to map loci affecting the analyzed traits, and permutation tests were used to set significance thresholds. Cofactors were used in the analyses of individual chromosomes to adjust for QTL found on other chromosomes. The use of cofactors increased both the number of QTL found and the significance level. In the initial analysis, we found 13 suggestive QTL that were mapped to chromosomes 6, 7, 9, 11, 13, 15, 20, and 29. When cofactors were included, 30 QTL were detected on chromosomes 1, 3, 4, 18, 19, 22, and 25, in addition to the 8 previously mentioned chromosomes. Some of the results from the cofactor analysis may be false positives and require further validation. In conclusion, we were able to map several QTL affecting fertility and calving traits in Swedish dairy cattle.
Animals↗
On the generalized poisson regression mixture model for mapping quantitative trait loci with count data.
Statistical methods for mapping quantitative trait loci (QTL) have been extensively studied. While most existing methods assume normal distribution of the phenotype, the normality assumption could be easily violated when phenotypes are measured in counts. One natural choice to deal with count traits is to apply the classical Poisson regression model. However, conditional on covariates, the Poisson assumption of mean-variance equality may not be valid when data are potentially under- or overdispersed. In this article, we propose an interval-mapping approach for phenotypes measured in counts. We model the effects of QTL through a generalized Poisson regression model and develop efficient likelihood-based inference procedures. This approach, implemented with the EM algorithm, allows for a genomewide scan for the existence of QTL throughout the entire genome. The performance of the proposed method is evaluated through extensive simulation studies along with comparisons with existing approaches such as the Poisson regression and the generalized estimating equation approach. An application to a rice tiller number data set is given. Our approach provides a standard procedure for mapping QTL involved in the genetic control of complex traits measured in counts.
Algorithms↗
Construction of a comparative RFLP map of Echinochloa crus-galli toward QTL analysis of flooding tolerance.
To analyze quantitative trait loci (QTLs) affecting flooding tolerance and other physiological and morphological traits in Echinochloa crus-galli, a restriction fragment length polymorphism (RFLP) map was constructed using 55 plants of the F(2) population ( E. crus-galli var. praticola x E. crus-galli var. formosensis). One hundred forty-one loci formed 41 linkage groups. The total map size was 1,468 cM and the average size of linkage groups was 35.8 cM. The average distance between markers was 14.7 cM and the range was 0-37.2 cM. Early comparisons to the genetic maps of other taxa suggest appreciable synteny with buffelgrass ( Pennisetum spp.) and sorghum ( Sorghum spp.). One hundred ninty-one F(2) plants were used to analyze QTLs of flooding tolerance, plant morphology, heading date, number of leaves, and plant height. For flooding tolerance, two QTLs were detected and one was mapped on linkage group 24. Other traits, including plant morphology, heading date, number of leaves, and plant height were highly correlated. Three genomic regions accounted for most of the mapped QTLs, each explaining 2-4 of the significant marker-trait associations. The high observed correlation between the traits appears to result from QTLs with a large contribution to the phenotypic variance at the same or nearby locations.
Chromosome Mapping↗
Combined line-cross and half-sib QTL analysis of crosses between outbred lines.
Data from an F 2 cross between breeds of livestock are typically analysed by least squares line-cross or half-sib models to detect quantitative trait loci (QTL) that differ between or segregate within breeds. These models can also be combined to increase power to detect QTL, while maintaining the computational efficiency of least squares. Tests between models allow QTL to be characterized into those that are fixed (LC QTL), or segregating at similar (HS QTL) or different (CB QTL) frequencies in parental breeds. To evaluate power of the combined model, data wih various differences in QTL allele frequencies (FD) between parental breeds were simulated. Use of all models increased power to detect QTL. The line-cross model was the most powerful model to detect QTL for FD>0.6. The combined and half-sib models had similar power for FD<0.4. The proportion of detected QTL declared as LC QTL decreased with FD. The opposite was observed for HS QTL. The proportion of CB QTL decreased as FD deviated from 0.5. Accuracy of map position tended to be greatest for CB QTL. Models were applied to a cross of Berkshire and Yorkshire pig breeds and revealed 160 (40) QTL at the 5% chromosome (genome)-wise level for the 39 growth, carcass composition and quality traits, of which 72, 54, and 34 were declared as LC, HS and CB QTL. Fourteen CB QTL were detected only by the combined model. Thus, the combined model can increase power to detect QTL and mapping accuracy and enable characterization of QTL that segregate within breeds.
Animals↗
Interval mapping of multiple quantitative trait loci.
The interval mapping method is widely used for the mapping of quantitative trait loci (QTLs) in segregating generations derived from crosses between inbred lines. The efficiency of detecting and the accuracy of mapping multiple QTLs by using genetic markers are much increased by employing multiple QTL models instead of the single QTL models (and no QTL models) used in interval mapping. However, the computational work involved with multiple QTL models is considerable when the number of QTLs is large. In this paper it is proposed to combine multiple linear regression methods with conventional interval mapping. This is achieved by fitting one QTL at a time in a given interval and simultaneously using (part of) the markers as cofactors to eliminate the effects of additional QTLs. It is shown that the proposed method combines the easy computation of the single QTL interval mapping method with much of the efficiency and accuracy of multiple QTL models.
Chromosome Mapping↗
Comparative mapping of BTA15 and HSA11 including a region containing a QTL for meat tenderness.
The starting point of the present study was the reported identification of a chromosomal region on bovine Chromosome (Chr) 15 (BTA15) carrying loci affecting meat tenderness. A comparative linkage map of BTA15 and human Chr 11 (HSA11) was constructed to identify potential positional candidate genes and to provide a resource of genetic markers to support marker-assisted selection (MAS). Relative rearrangements between the bovine and human genomes for these chromosomes are the most complex observed in comparative mapping between the two species, with nine alternating blocks of conserved synteny between HSA11 and bovine Chrs 15 and 29. The results of this study were the addition of nine genes to the HSA11/BTA15 comparative linkage map, and development of five microsatellite markers within the quantitative trait locus (QTL) interval. One gene with known effects on muscle development (MYOD1) was mapped to the interval. A second gene (CALCA) involved in regulation of calcium levels, a key factor in postmortem tenderization, also mapped within the interval. Refinement of the comparative map and QTL position will reduce the interval on the human transcription map to be scanned in search of candidates, reducing the effort and resources required to identify the allelic variation responsible for the genetic effect.
Animals↗
Mapping and characterization of FLC homologs and QTL analysis of flowering time in Brassica oleracea.
The FLC gene product is an inhibitor of flowering in Arabidopsis. FLC homologs in Brassica species are thought to control vernalization. We cloned four FLC homologs (BoFLCs) from Brassica oleracea. Three of these, BoFLC1, BoFLC3 and BoFLC5, have been previously characterized. The fourth novel sequence displayed 98% sequence homology to the previously identified gene BoFLC4, but also showed 91% homology to BrFLC2 from Brassica rapa. Phylogenetic analysis showed that this clone belongs to the FLC2 clade. Therefore, we designated this gene BoFLC2. Based on the segregation of RFLP, SRAP, CAPS, SSR and AFLP loci, a detailed linkage map of B. oleracea was constructed in the F(2) progeny obtained from a cross of B. oleracea cv. Green Comet (broccoli; non-vernalization type) and B. oleracea cv. Reiho (cabbage; vernalization type), which covered 540 cM, 9 major linkage groups. Six quantitative trait loci (QTL) controlling flowering time were detected. BoFLC1, BoFLC3 and BoFLC5 were not linked to the QTLs controlling flowering time. However, the largest QTL effect was located in the region where BoFLC2 was mapped. Genotyping of F(2 )plants at the BoFLC2 locus showed that most of the early flowering plants were homozygotes of BoFLC-GC, whereas most of the late- and non-flowering plants were homozygotes of BoFLC-Rei. The BoFLC2 homologs present in plants of the non-vernalization type were non-functional, due to a frameshift in exon 4. Moreover, duplications and deletions of BoFLC2 were detected in broccoli and a rapid cycling line, respectively. These results suggest that BoFLC2 contributes to the control of flowering time in B. oleracea.
Arabidopsis Proteins↗
[Comparison of the detection of QTL for yield traits in different generations of a rice cross using two mapping approaches].
In the F2 and recombinant inbred populations of Zhenshan 97B/Milyang 46, RFLP linkage maps were constructed to detect QTL for yield and its component traits. Results indicated that QTL having substantial additive effects were generally detected in both F2 and recombinant inbred populations. In addition, the trait performances were measured either based on a single plant or on replicated trials in the recombinant inbred population hardly affected the detection of QTL of higher effects.
Chromosome Mapping↗