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Results for “QTL mapping”

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PubMed2005

Epistasis and genotype-environment interaction for quantitative trait loci affecting flowering time in Arabidopsis thaliana.

A major goal of evolutionary biology is to understand the genetic architecture of the complex quantitative traits that may lead to adaptations in natural populations. Of particular relevance is the evaluation of the frequency and magnitude of epistasis (gene-gene and gene-environment interaction) as it plays a controversial role in models of adaptation within and among populations. Here, we explore the genetic basis of flowering time in Arabidopsis thaliana using a series of quantitative trait loci (QTL) mapping experiments with two recombinant inbred line (RIL) mapping populations [Columbia (Col) x Landsberg erecta (Ler), Ler x Cape Verde Islands (Cvi)]. We focus on the response of RILs to a series of environmental conditions including drought stress, leaf damage, and apical damage. These data were explicitly evaluated for the presence of epistasis using Bayesian based multiple-QTL genome scans. Overall, we mapped fourteen QTL affecting flowering time. We detected two significant QTL-QTL interactions and several QTL-environment interactions for flowering time in the Ler x Cvi population. QTL-environment interactions were due to environmentally induced changes in the magnitude of QTL effects and their interactions across environments--we did not detect antagonistic pleiotropy. We found no evidence for QTL interactions in the Ler x Col population. We evaluate these results in the context of several other studies of flowering time in Arabidopsis thaliana and adaptive evolution in natural populations.

Arabidopsis↗

PubMed2006

High-resolution quantitative trait locus mapping reveals sign epistasis controlling ovariole number between two Drosophila species.

Identifying the genes underlying genetically complex traits is of fundamental importance for medicine, agriculture, and evolutionary biology. However, the level of resolution offered by traditional quantitative trait locus (QTL) mapping is usually coarse. We analyze here a trait closely related to fitness, ovariole number. Our initial interspecific mapping between Drosophila sechellia (8 ovarioles/ovary) and D. simulans (15 ovarioles/ovary) identified a major QTL on chromosome 3 and a minor QTL on chromosome 2. To refine the position of the major QTL, we selected 1038 additional recombinants in the region of interest using flanking morphological markers (selective phenotyping). This effort generated approximately one recombination event per gene and increased the mapping resolution by approximately seven times. Our study thus shows that using visible markers to select for recombinants can efficiently increase the resolution of QTL mapping. We resolved the major QTL into two epistatic QTL, QTL3a and QTL3b. QTL3a shows sign epistasis: it has opposite effects in two different genetic backgrounds, the presence vs. the absence of the QTL3b D. sechellia allele. This property of QTL3a allows us to reconstruct the probable order of fixation of the QTL alleles during evolution.

Animals↗

PubMed2003

Mapping quantitative trait loci for bean traits and ovule number in Theobroma cacao L.

Quantitative trait loci (QTL) mapping for bean traits and the number of ovules per ovary was carried out in cocoa (Theobroma cacao L.) using three test-cross progenies derived from crosses between a lower Amazon Forastero male parent (Catongo) and three female parents: one upper Amazon Forastero (IMC78) and two Trinitario (DR1 and S52). RFLP (restriction fragment length polymorphism), microsatellite, and AFLP (amplified fragment lengthpolymorphism) markers were used for mapping. Between one and six QTL for bean traits (length, weight, and shape index) and one and four QTL for the number of ovules per ovary were detected using composite interval mapping (CIM). Individual QTL explained between 5 and 24% of the phenotypic variation. QTL clusters were identified on several chromosomes, but particularly on chromosome 4. QTL related to bean traits were detected in the same region in both Trinitario parents and in a close region in the upper Amazon Forastero parent. In reference to a previous diversity study where alleles specific to Criollo and Forastero genotypes were identified, it was possible to speculate on the putative origin (Criollo or Forastero) of favorable QTL alleles segregating in both Trinitario studied.

Cacao↗

PubMed2003

A general statistical framework for mapping quantitative trait loci in nonmodel systems: issue for characterizing linkage phases.

Because of uncertainty about linkage phases of founders, linkage mapping in nonmodel, outcrossing systems using molecular markers presents one of the major statistical challenges in genetic research. In this article, we devise a statistical method for mapping QTL affecting a complex trait by incorporating all possible QTL-marker linkage phases within a mapping framework. The advantage of this model is the simultaneous estimation of linkage phases and QTL location and effect parameters. These estimates are obtained through maximum-likelihood methods implemented with the EM algorithm. Extensive simulation studies are performed to investigate the statistical properties of our model. In a case study from a forest tree, this model has successfully identified a significant QTL affecting wood density. Also, the probability of the linkage phase between this QTL and its flanking markers is estimated. The implications of our model and its extension to more general circumstances are discussed.

Chromosome Mapping↗

PubMed2006

Population and systems genetics analyses of cortisol in pigs divergently selected for stress.

This study presents a systems genetic analysis on the physiology of cortisol in mice and pigs with an aim to show the potential of a comprehensive computational approach to quickly identify candidate genes and avoid a costly whole-genome quantitative trait locus (QTL) mapping. Population genetics analyses were performed on measurements of cortisol from a pig selection experiment. Expression QTL were mapped and gene networks were built using gene expressions for Crhr1 (corticotrophin-releasing hormone receptor) gene and single nucleotide polymorphisms from public mouse data. Results from mouse data were used to infer potential candidate regulatory genes involved in pig cortisol regulation, using a comparative or translational systems genetics approach. The pig data used were from a 10-yr divergent genetic selection experiment, providing data on 417 individuals. Population genetics analysis showed that cortisol is highly genetically determined with heritabilities of 0.40-0.70. Furthermore, a major gene with an additive effect of 86 ng/ml is segregating. Genetical-genomics investigations revealed two trans-acting eQTL for Crhr1 gene expression on chromosomes 2 and 13. Candidate gene search under trans-eQTL peaks yielded 63 genes for Crhr1 expression phenotypes. Functional links for Crhr1 genes with other genes/proteins in the gene network using mouse data were shown for the first 10 statistically significant genes involved. Results show translational or comparative systems genetics approaches reduce costs and time in large-scale genetics and "-omics" investigations. This is the first study to report a strong genetic basis for cortisol physiology using a systems approach.

Animals↗

PubMed2000

Optimal marker density for interval mapping in a backcross population.

An important question in QTL mapping is the optimal choice of marker density. Using analytical results, it is shown for the case of interval mapping in a backcross population, that the power of QTL detection and the standard errors of genetic effect estimates are little affected by an increase of marker density beyond 10 cM. This finding confirms published simulation results by other authors.

Analysis of Variance↗

PubMed2002

Linkage mapping of genes controlling resistance to white rust (Albugo candida) in Brassica rapa (syn. campestris) and comparative mapping to Brassica napus and Arabidopsis thaliana.

Genes for resistance to white rust (Albugo candida) in oilseed Brassica rapa were mapped using a recombinant inbred (RI) population and a genetic linkage map consisting of 144 restriction fragment length polymorphism (RFLP) markers and 3 phenotypic markers. Young seedlings were evaluated by inoculating cotyledons with A. candida race 2 (AC2) and race 7 (AC7) and scoring the interaction phenotype (IP) on a 0-9 scale. The IP of each line was nearly identical for the two races and the population showed bimodal distributions, suggesting that a single major gene (or tightly linked genes) controlled resistance to the two races. The IP scores were converted to categorical resistant and susceptible scores, and these data were used to map a single Mendelian gene controlling resistance to both races on linkage group 4 where resistance to race 2 had been mapped previously. A quantitative trait loci (QTL) mapping approach using the IP scores detected the same major resistance locus for both races, plus a second minor QTL effect for AC2 on linkage group 2. These results indicate that either a dominant allele at a single locus (Acal) or two tightly linked loci control seedling resistance to both races of white rust in the biennial turnip rape cultivar Per. The map positions of white rust resistance genes in B. rapa and Brassica napus were compared and the results indicate where additional loci that have not been mapped may be located. Alignment of these maps to the physical map of the Arabidopsis genome identified regions to target for comparative fine mapping using this model organism.

Arabidopsis↗

PubMed1998

Quantitative trait locus mapping in dairy cattle by means of selective milk DNA pooling using dinucleotide microsatellite markers: analysis of milk protein percentage.

"Selective DNA pooling" accomplishes quantitative trait locus (QTL) mapping through densitometric estimates of marker allele frequencies in pooled DNA samples of phenotypically extreme individuals. With poly(TG) microsatellites, such estimates are confounded by "shadow" ("stutter") bands. A correction procedure was developed on the basis of an observed linear regression between shadow band intensity and allele TG repeat number. Using this procedure, a selective DNA pooling study with respect to milk protein percentage was implemented in Israel-Holstein dairy cattle. Pools were prepared from milk samples of high and low daughters of each of seven sires and genotyped with respect to 11 markers. Highly significant associations with milk protein percentage were found for 5 of the markers; 4 of these markers confirmed previous reports. Selective DNA pooling accessed 80.6 and 48.3%, respectively, of the information that would have been available through individual selective genotyping or total population genotyping. In effect, the statistical power of 45,600 individual genotypings was obtained from 328 pool genotypings. This methodology can make genome-wide mapping of QTL accessible to moderately sized breeding organizations.

Animals↗

PubMed2000

Genetic analysis of seed-soluble oligosaccharides in relation to seed storability of Arabidopsis.

Seed oligosaccharides (OSs) and especially raffinose series OSs (RSOs) are hypothesized to play an important role in the acquisition of desiccation tolerance and consequently in seed storability. In the present work we analyzed the seed-soluble OS (sucrose, raffinose, and stachyose) content of several Arabidopsis accessions and thus identified the genotype Cape Verde Islands having a very low RSO content. By performing quantitative trait loci (QTL) mapping in a recombinant inbred line population, we found one major QTL responsible for the practically monogenic segregation of seed stachyose content. This locus also affected the content of the two other OSs, sucrose, and raffinose. Two candidate genes encoding respectively for galactinol synthase and raffinose synthase were located within the genomic region around this major QTL. In addition, three smaller-effect QTL were identified, each one specifically affecting the content of an individual OS. Seed storability was analyzed in the same recombinant inbred line population by measuring viability (germination) under two different seed aging assays: after natural aging during 4 years of dry storage at room temperature and after artificial aging induced by a controlled deterioration test. Thus, four QTL responsible for the variation of this trait were mapped. Comparison of the QTL genetic positions showed that the genomic region containing the major OS locus did not significantly affect the seed storability. We concluded that in the studied material neither RSOs nor sucrose content had a specific effect on seed storability.

Arabidopsis↗

PubMed2003

Molecular dissection of a dormancy QTL region near the chromosome 7 (5H) L telomere in barley.

Moderate seed dormancy is desirable in barley (Hordeum vulgare L.). It is difficult for breeders to manipulate seed dormancy in practical breeding programs because of complex inheritance and large environmental effects. Quantitative trait locus (QTL) mapping opens a way for breeders to manipulate quantitative trait genes. A seed dormancy QTL, SD2, was mapped previously in an 8-cM interval near the chromosome 7 (5H) L telomere from a cross of 'Steptoe' (dormant)/'Morex' (non-dormant) by the North American Barley Genome Project using an interval mapping method and a relatively low-resolution genetic map. SD2 has a moderate dormancy effect, which makes it a promising candidate gene for moderate seed dormancy in barley cultivar development. The fine mapping of SD2 is required for efficient manipulation of SD2 in breeding and would facilitate the study of dormancy in barley. Ten different Morex isolines were generated, including regenerated Morex, of which nine lines had duplicates. The isolines together with Steptoe and Morex were grown in growth room and field environments for 2 years (2000 and 2001). In the growth room, relatively low growing temperatures (25 degrees C day/15 degrees C night) were employed to promote seed dormancy development. Seed germination percentage, determined at different post-harvest after-ripening periods, was used to measure seed dormancy. Fine mapping using the substitution mapping method based on differences among isolines resolved the SD2 QTL into an 0.8-cM interval between molecular markers MWG851D and MWG851B near the chromosome 7 (5H) L telomere. Relatively low temperatures (< or =25 degrees C) during seed development promoted the expression of the SD2 dormancy QTL. The chromosome region above the MWG851D-MWG851B interval might play a role in reducing barley seed dormancy during after-ripening.

Chromosome Mapping↗

PubMed2006

A microsatellite-based consensus linkage map for species of Eucalyptus and a novel set of 230 microsatellite markers for the genus.

BACKGROUND: Eucalypts are the most widely planted hardwood trees in the world occupying globally more than 18 million hectares as an important source of carbon neutral renewable energy and raw material for pulp, paper and solid wood. Quantitative Trait Loci (QTLs) in Eucalyptus have been localized on pedigree-specific RAPD or AFLP maps seriously limiting the value of such QTL mapping efforts for molecular breeding. The availability of a genus-wide genetic map with transferable microsatellite markers has become a must for the effective advancement of genomic undertakings. This report describes the development of a novel set of 230 EMBRA microsatellites, the construction of the first comprehensive microsatellite-based consensus linkage map for Eucalyptus and the consolidation of existing linkage information for other microsatellites and candidate genes mapped in other species of the genus. RESULTS: The consensus map covers approximately 90% of the recombining genome of Eucalyptus, involves 234 mapped EMBRA loci on 11 linkage groups, an observed length of 1,568 cM and a mean distance between markers of 8.4 cM. A compilation of all microsatellite linkage information published in Eucalyptus allowed us to establish the homology among linkage groups between this consensus map and other maps published for E. globulus. Comparative mapping analyses also resulted in the linkage group assignment of other 41 microsatellites derived from other Eucalyptus species as well as candidate genes and QTLs for wood and flowering traits published in the literature. This report significantly increases the availability of microsatellite markers and mapping information for species of Eucalyptus and corroborates the high conservation of microsatellite flanking sequences and locus ordering between species of the genus. CONCLUSION: This work represents an important step forward for Eucalyptus comparative genomics, opening stimulating perspectives for evolutionary studies and molecular breeding applications. The generalized use of an increasingly larger set of interspecific transferable markers and consensus mapping information, will allow faster and more detailed investigations of QTL synteny among species, validation of expression-QTL across variable genetic backgrounds and positioning of a growing number of candidate genes co-localized with QTLs, to be tested in association mapping experiments.

Alleles↗

PubMed1997

MCMC segregation and linkage analysis.

Our objective was to infer the genetic model for the quantitative traits using a variety of methods developed in our group. Only a single data set was analyzed in any one analysis, although some comparison between data sets was made. In addition, the simulated model was not known during the course of the analysis. Basic modeling and segregation analyses for the five quantitative traits was followed by several simple genome scans to indicate areas of interest. A Markov chain Monte Carlo (MCMC) multipoint quantitative trait locus (QTL) mapping approach was then used to estimate the posterior probabilities of linkage of QTL to each chromosome simultaneously with trait model parameters, and to further localize the genes. Comparisons between the nuclear family and pedigree data sets indicated a greater power for QTL detection and mapping with the pedigree data sets. Even with the pedigree data, however, precise localization of the QTL did not appear to be possible using single replicate data sets. Two of the three genes with effects on trait Q1 were detected by the MCMC method.

Chromosome Mapping↗

PubMed2002

Simultaneous mining of linkage and linkage disequilibrium to fine map quantitative trait loci in outbred half-sib pedigrees: revisiting the location of a quantitative trait locus with major effect on milk production on bovine chromosome 14.

A maximum-likelihood QTL mapping method that simultaneously exploits linkage and linkage disequilibrium and that is applicable in outbred half-sib pedigrees is described. The method is applied to fine map a QTL with major effect on milk fat content in a 3-cM marker interval on proximal BTA14. This proximal location is confirmed by applying a haplotype-based association method referred to as recombinant ancestral haplotype analysis. The origin of the discrepancy between the QTL position derived in this work and that of a previous analysis is examined and shown to be due to the existence of distinct marker haplotypes associated with QTL alleles having large substitution effects.

Animals↗

PubMed2006

An empirical Bayes method for updating inferences in analysis of quantitative trait loci using information from related genome scans.

Individual genome scans for quantitative trait loci (QTL) mapping often suffer from low statistical power and imprecise estimates of QTL location and effect. This lack of precision yields large confidence intervals for QTL location, which are problematic for subsequent fine mapping and positional cloning. In prioritizing areas for follow-up after an initial genome scan and in evaluating the credibility of apparent linkage signals, investigators typically examine the results of other genome scans of the same phenotype and informally update their beliefs about which linkage signals in their scan most merit confidence and follow-up via a subjective-intuitive integration approach. A method that acknowledges the wisdom of this general paradigm but formally borrows information from other scans to increase confidence in objectivity would be a benefit. We developed an empirical Bayes analytic method to integrate information from multiple genome scans. The linkage statistic obtained from a single genome scan study is updated by incorporating statistics from other genome scans as prior information. This technique does not require that all studies have an identical marker map or a common estimated QTL effect. The updated linkage statistic can then be used for the estimation of QTL location and effect. We evaluate the performance of our method by using extensive simulations based on actual marker spacing and allele frequencies from available data. Results indicate that the empirical Bayes method can account for between-study heterogeneity, estimate the QTL location and effect more precisely, and provide narrower confidence intervals than results from any single individual study. We also compared the empirical Bayes method with a method originally developed for meta-analysis (a closely related but distinct purpose). In the face of marked heterogeneity among studies, the empirical Bayes method outperforms the comparator.

Chromosome Mapping↗

PubMed2025

Foliar disease resistance phenomics of fungal pathogens: image-based approaches for mapping quantitative resistance in cereal germplasm.

Host plant resistance is the most effective and environmentally sustainable means of reducing yield losses caused by fungal foliar pathogens of cereal species. Cereal genebank collections hold diverse pools of potentially underutilized disease resistance alleles, and cereal genomic resources are well advanced due to large-scale sequencing and genotyping efforts. Genome-Wide Association Studies (GWAS) have emerged as the predominant association genetics technique to initially discover novel disease resistance loci or alleles in these diverse collections. Traditional disease resistance phenotyping methods are reliant on visual estimation of disease symptom severity and have successfully supported genetic mapping studies either via GWAS or QTL mapping in biparental populations facilitating both marker development and gene cloning efforts. Due to foliar pathogens having a high capacity to evolve, there is a need to pyramid disease resistance genes with diverse mechanisms for durable control. Resistance expressed as a quantitative trait, known as quantitative resistance (QR), is hypothesized to be more durable, unlike major R-gene resistance that is race-specific and can be vulnerable to breaking down without gene stewardship. However, assessing QR visually is challenging, particularly when complicated by complex genotype × environment (G × E) effects in the field. High-throughput image-based phenotyping provides accurate and unbiased data that can support foliar disease resistance screening efforts of genebank collections using GWAS. In this review, we discuss image-based disease phenotyping based on macroscopic (visible symptoms) and microscopic features during the host-pathogen interaction. Quantitative image analysis approaches using conventional and artificial intelligence (AI) algorithms are also discussed.

Disease Resistance↗

PubMed2003

The role of ACE2 in cardiovascular physiology.

The renin-angiotensin system (RAS) is critically involved in cardiovascular and renal function and in disease conditions, and has been shown to be a far more complex system than initially thought. A recently discovered homologue of angiotensin-converting enzyme (ACE)--ACE2--appears to negatively regulate the RAS. ACE2 cleaves Ang I and Ang II into the inactive Ang 1-9 and Ang 1-7, respectively. ACE2 is highly expressed in kidney and heart and is especially confined to the endothelium. With quantitative trait locus (QTL) mapping, ACE2 was defined as a QTL on the X chromosome in rat models of hypertension. In these animal models, kidney ACE2 messenger RNA and protein expression were markedly reduced, making ACE2 a candidate gene for this QTL. Targeted disruption of ACE2 in mice failed to elicit hypertension, but resulted in severe impairment in myocardial contractility with increased angiotensin II levels. Genetic ablation of ACE in the ACE2 null mice rescued the cardiac phenotype. These genetic data show that ACE2 is an essential regulator of heart function in vivo. Basal renal morphology and function were not altered by the inactivation of ACE2. The novel role of ACE2 in hydrolyzing several other peptides-such as the apelin peptides, opioids, and kinin metabolites-raises the possibility that peptide systems other than angiotensin and its derivatives also may have an important role in regulating cardiovascular and renal function.

Angiotensin II↗

PubMed2000

Genetic architecture of a morphological shape difference between two Drosophila species.

The size and shape of the posterior lobe of the male genital arch differs dramatically between Drosophila simulans and D. mauritiana. This difference can be quantified with a morphometric descriptor (PC1) based on elliptical Fourier and principal components analyses. The genetic basis of the interspecific difference in PC1 was investigated by the application of quantitative trait locus (QTL) mapping procedures to segregating backcross populations. The parental difference (35 environmental standard deviations) and the heritability of PC1 in backcross populations (>90%) are both very large. The use of multiple interval mapping gives evidence for 19 different QTL. The greatest additive effect estimate accounts for 11. 4% of the parental difference but could represent multiple closely linked QTL. Dominance parameter estimates vary among loci from essentially no dominance to complete dominance, and mauritiana alleles tend to be dominant over simulans alleles. Epistasis appears to be relatively unimportant as a source of variation. All but one of the additive effect estimates have the same sign, which means that one species has nearly all plus alleles and the other nearly all minus alleles. This result is unexpected under many evolutionary scenarios and suggests a history of strong directional selection acting on the posterior lobe.

Animals↗

PubMed2007

Separation of base allele and sampling term effects gives new insights in variance component QTL analysis.

BACKGROUND: Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional VC model, each individual has a unique QTL effect and the relationship between these random effects is given as a covariance structure (known as the identity-by-descent (IBD) matrix). RESULTS: We present an alternative notation of the variance component model, where the elements of the random effect are independent base generation allele effects and sampling term effects. The relationship between the phenotypic vales and the random effect is given by an incidence matrix, which results in a novel, but statistically equivalent, version of the traditional VC model. A general algorithm to estimate this incidence matrix is presented. Since the model is given in terms of base generation allele effects and sampling term effects, these effects can be estimated separately using best linear unbiased prediction (BLUP). From simulated data, we showed that biallelic QTL effects could be accurately clustered using the BLUP obtained from our model notation when markers are fully informative, and that the accuracy increased with the size of the QTL effect. We also developed a measure indicating whether a base generation marker homozygote is a QTL heterozygote or not, by comparing the variances of the sampling term BLUP and the base generation allele BLUP. A ratio greater than one gives strong support for a QTL heterozygote. CONCLUSION: We developed a simple presentation of the VC QTL model for identification of base generation allele effects in QTL linkage analysis. The base generation allele effects and sampling term effects were separated in our model notation. This clarifies the assumptions of the model and should also enhance the development of genome scan methods.

Alleles↗