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A unified approach to joint modeling of multiple quantitative and qualitative traits in gene mapping.

Using graph theory, we present a theoretical basis for mapping oligogenes in the joint presence of multiple phenotypic measurements of both quantitative and qualitative types. Various statistical models proposed earlier for several traits of solely single type are special cases of the unified approach given here. Our emphasis is on the generality of the framework, without specifying explicit assumptions about a sampling design. When information about environmental factors potentially affecting the traits is available, it can be incorporated into the genetic model. We adopt the Bayesian inferential machinery due to its firm theoretical basis and its capability of handling uncertain quantities; such as unobserved model parameters, missing marker data, and even different putative genetic models, probabilistically within a single framework. It is shown here that biological hypotheses about single gene affecting simultaneously multiple traits (pleiotropy) can be intuitively imposed as parameter constraints, leading to pleiotropic models for which posterior probabilities can be calculated. Outline of the possible implementation of the Bayesian method is described using the general reversible-jump Markov chain Monte Carlo algorithm. Some future challenges and extensions are also discussed.

Animals↗

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↗

Mapping temporally varying quantitative trait loci in time-to-failure experiments.

Existing methods for mapping quantitative trait loci (QTL) in time-to-failure experiments assume that the QTL effect is constant over the course of the study. This assumption may be violated when the gene(s) underlying the QTL are up- or downregulated on a biologically meaningful timescale. In such situations, models that assume a constant effect can fail to detect QTL in a whole-genome scan. To investigate this possibility, we utilize an extension of the Cox model (EC model) within an interval-mapping framework. In its simplest form, this model assumes that the QTL effect changes at some time point t0 and follows a linear function before and after this change point. The approximate time point at which this change occurs is estimated. Using simulated and real data, we compare the mapping performance of the EC model to the Cox proportional hazards (CPH) model, which explicitly assumes a constant effect. The results show that the EC model detects time-dependent QTL, which the CPH model fails to detect. At the same time, the EC model recovers all of the QTL the CPH model detects. We conclude that potentially important QTL may be missed if their time-dependent effects are not accounted for.

Chromosome Mapping↗

A unified Markov chain Monte Carlo framework for mapping multiple quantitative trait loci.

In this article, a unified Markov chain Monte Carlo (MCMC) framework is proposed to identify multiple quantitative trait loci (QTL) for complex traits in experimental designs, based on a composite space representation of the problem that has fixed dimension. The proposed unified approach includes the existing Bayesian QTL mapping methods using reversible jump MCMC algorithm as special cases. We also show that a variety of Bayesian variable selection methods using Gibbs sampling can be applied to the composite model space for mapping multiple QTL. The unified framework not only results in some new algorithms, but also gives useful insight into some of the important factors governing the performance of Gibbs sampling and reversible jump for mapping multiple QTL. Finally, we develop strategies to improve the performance of MCMC algorithms.

Chromosome Mapping↗

Trans-ethnic fine mapping of a quantitative trait locus for circulating angiotensin I-converting enzyme (ACE).

Circulating angiotensin I-converting enzyme (ACE) levels are influenced by a major quantitative trait locus (QTL) that maps to the ACE gene. Phylogenetic and measured haplotype analyses have suggested that the ACE-linked QTL lies downstream of a putative ancestral breakpoint located near to position 6435. However, strong linkage disequilibrium between markers in the 3' portion of the gene has prevented further resolution of the QTL in Caucasian subjects. We have examined 10 ACE gene polymorphisms in Afro-Caribbean families recruited in JAMAICA: Variance components analyses showed strong evidence of linkage and association to circulating ACE levels. When the linkage results were contrasted with those from a set of British Caucasian families, there was no evidence for heterogeneity between the samples. However, patterns of allelic association between the markers and circulating ACE levels differed significantly in the two data sets. In the British families, three markers [G2215A, Alu insertion/deletion and G2350A] were in complete disequilibrium with the ACE-linked QTL. In the Jamaican families, only marker G2350A showed strong but incomplete disequilibrium with the ACE-linked QTL. These results suggest that additional unobserved polymorphisms have an effect on circulating ACE levels in Jamaican families. Furthermore, our results show that a variance components approach combined with structured, quantitative comparisons between families from different ethnic groups may be a useful strategy for helping to determine which, if any, variants in a small genomic region directly influence a quantitative trait.

Black People↗

Mapping epistatic quantitative trait loci with one-dimensional genome searches.

The discovery of epistatically interacting QTL is hampered by the intractability and low power to detect QTL in multidimensional genome searches. We describe a new method that maps epistatic QTL by identifying loci of high QTL by genetic background interaction. This approach allows detection of QTL involved not only in pairwise but also higher-order interaction, and does so with one-dimensional genome searches. The approach requires large populations derived from multiple related inbred-line crosses as is more typically available for plants. Using maximum likelihood, the method contrasts models in which QTL allelic values are either nested within, or fixed over, populations. We apply the method to simulated doubled-haploid populations derived from a diallel among three inbred parents and illustrate the power of the method to detect QTL of different effect size and different levels of QTL by genetic background interaction. Further, we show how the method can be used in conjunction with standard two-locus QTL detection models that use two-dimensional genome searches and find that the method may double the power to detect first-order epistasis.

Alleles↗

Multiple cross and inbred strain haplotype mapping of complex-trait candidate genes.

Identifying complex-trait candidate genes after initial low-resolution mapping has proven to be a difficult and labor-intensive undertaking, usually requiring years to develop and analyze congenic strains. As a result, to date, few complex-trait genes have been discovered. Recently it was suggested that SNP haplotype analysis in inbred strains might be useful for mapping of complex traits. In this study, we have combined medium-resolution haplotype mapping with multiple experimental cross-mapping experiments to reduce the number of potential candidate genes in a complex-trait candidate interval. Coincident mapping of a modifier gene in multiple experimental crosses using different inbred strains is consistent with the common inheritance of a modifier allele. A haplotype map was developed in four inbred strains of mice used in our complex-trait mapping crosses across the proximal 10 cM of proximal Chromosome 19 to identify haplotype blocks that segregate appropriately. Only ~23 out of >400 genes met this criteria. This strategy coupled with tissue and expression arrays, as well as our recently described common pathway analysis to reduce the number of high-priority candidates, may provide a rapid, efficient method to identify and prioritize complex-trait candidate genes without requiring construction of congenic mouse strains.

Animals↗

Methods for genetic linkage analysis using trisomies.

Certain genetic disorders are rare in the general population, but more common in individuals with specific trisomies. Examples of this include leukemia and duodenal atresia in trisomy 21. This paper presents a linkage analysis method for using trisomic individuals to map genes for such traits. It is based on a very general gene-specific dosage model that posits that the trait is caused by specific effects of different alleles at one or a few loci and that duplicate copies of "susceptibility" alleles inherited from the nondisjoining parent give increased likelihood of having the trait. Our mapping method is similar to identity-by-descent-based mapping methods using affected relative pairs and also to methods for mapping recessive traits using inbred individuals by looking for markers with greater than expected homozygosity by descent. In the trisomy case, one would take trisomic individuals and look for markers with greater than expected homozygosity in the chromosomes inherited from the nondisjoining parent. We present statistical methods for performing such a linkage analysis, including a test for linkage to a marker, a method for estimating the distance from the marker to the trait gene, a confidence interval for that distance, and methods for computing power and sample sizes. We also resolve some practical issues involved in implementing the methods, including how to use partially informative markers and how to test candidate genes.

Chromosome Mapping↗

Model for mapping imprinted quantitative trait loci in an inbred F2 design.

The role of imprinting in shaping development has been ubiquitously observed in plants, animals, and humans. However, a statistical method that can detect and estimate the effects of imprinted quantitative trait loci (iQTL) over the genome has not been extensively developed. In this article, we propose a maximum likelihood approach for testing and estimating the imprinted effects of iQTL that contribute to variation in a quantitative trait. This approach, implemented with the EM algorithm, allows for a genome-wide scan for the existence of iQTL. This approach was used to reanalyze published data in an F(2) family derived from the LG/S and SM/S mouse strains. Several iQTL that regulate the growth of body weight by expressing paternally inherited alleles were identified. Our approach provides a standard procedure for testing the statistical significance of iQTL involved in the genetic control of complex traits.

Algorithms↗

Mapping of quantitative trait loci controlling timing of bud flush in Salix.

Dormancy release is an important phenological stage, which determines plant growth and survival in northern temperate regions. Spring bud flushing was studied in a Salix pedigree (n=82) derived from a cross between the male hybrid clone "Björn" (Salix viminalis x Salix schwerinii) and the female clone "78183" (Salix viminalis). The timing of bud flush was recorded outdoors in two consecutive years (1998, 1999) and indoor in the spring of 1998. Timing of bud flush was found to be under moderately strong genetic control (clonal mean heritabilities ranging from 0.43 to 0.72). Phenotypic correlations between height growth and bud flushing were negative but non-significant (r=0.1-0.3). Using a Salix linkage map composed of 325 AFLP and 38 RFLP markers, six quantitative trait loci (QTLs) and three unmapped marker loci associated with timing of bud flush were detected. Four QTLs were detected in the field experiment while two QTLs and three unmapped marker loci were identified in the indoor experiment. One QTL associated with indoor bud flushing coincided with one of the QTL detected from the field data. Individual QTL explained 6-16% of the phenotypic variance [corrected]. None of the bud flush QTLs coincided with QTLs controlling height growth identified previously in the same pedigree.

Adaptation, Physiological↗

Simulating the collaborative cross: power of quantitative trait loci detection and mapping resolution in large sets of recombinant inbred strains of mice.

It has been suggested that the collaborative cross, a large set of recombinant inbred strains derived from eight inbred mouse strains, would be a powerful resource for the dissection of complex phenotypes. Here we use simulation to investigate the power of the collaborative cross to detect and map small genetic effects. We show that for a fixed population of 1000 individuals, 500 RI lines bred using a modified version of the collaborative cross design are adequate to map a single additive locus that accounts for 5% of the phenotypic variation to within 0.96 cM. In the presence of strong epistasis more strains can improve detection, but 500 lines still provide sufficient resolution to meet most goals of the collaborative cross. However, even with a very large panel of RILs, mapping resolution may not be sufficient to identify single genes unambiguously. Our results are generally applicable to the design of RILs in other species.

Animals↗

QTL mapping of root traits in a doubled haploid population from a cross between upland and lowland japonica rice in three environments.

To genetically dissect drought resistance associated with japonica upland rice, we evaluated a doubled haploid (DH) population from a cross between two japonica cultivars for seven root traits under three different growing conditions (upland, lowland and upland in PVC pipe). The traits included basal root thickness (BRT), total root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), ratio of root fresh weight to shoot fresh weight (RFW/SFW) and ratio of root dry weight to shoot dry weight (RDW/SDW). The BRT was significantly correlated with the index of drought resistance, which was defined as the ratio of yield under the stress of the upland condition to that under the normal lowland condition. A complete genetic linkage map with 165 molecular markers covering 1,535 cM was constructed. Seven additive quantitative trait loci (QTLs) and 15 pairs of epistatic loci for BRT and RN were identified under upland and lowland conditions, and 12 additive QTLs and 17 pairs of epistatic QTLs for BRT, RN, MRL, RFW, RFW/SFW and RDW/SDW were identified under the PVC pipe condition. Four additive QTLs and one pair of epistatic QTLs controlling IDR were also found. These QTLs individually explained up to 25.6% of the phenotypic variance. QTL x environment (Q x E) interactions were detected for all root traits, and the contributions of these interactions ranged from 1.1% to 19.9%. Five co-localized QTLs controlling RFW and RDW, RFW/SFW, RDW/SDW and IDR, BRT and RN, RN, MRL and IDR were found. Four types of QTLs governing BRT and RN were classified by their detection in the upland and lowland conditions. Some common QTLs for root traits across different backgrounds were also revealed. These co-localized QTLs and common QTLs will facilitate marker-assisted selection for root traits in rice breeding programs.

Adaptation, Physiological↗

Amplified fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the yellow fever mosquito Aedes aegypti.

The yellow fever mosquito Aedes aegypti has been the subject of extensive genetic research due to its medical importance and the ease with which it can be manipulated in the laboratory. A molecular genetic linkage map was constructed using 148 amplified fragment length polymorphism (AFLP) and six single-strand conformation polymorphism (SSCP) markers. Eighteen AFLP primer combinations were used to genotype two reciprocal F2 segregating populations. Each primer combination generated an average of 8.2 AFLP markers eligible for linkage mapping. The length of the integrated map was 180.9 cM, giving an average marker resolution of 1.2 cM. Composite interval mapping revealed a total of six QTL significantly affecting Plasmodium susceptibility in the two reciprocal crosses of Ae. aegypti. Two common QTL on linkage group 2 were identified in both crosses that had similar effects on the phenotype, and four QTL were unique to each cross. In one cross, the four main QTL accounted for 64% of the total phenotypic variance, and digenic epistasis explained 11.8% of the variance. In the second cross, the four main QTL explained 66% of the variance, and digenic epistasis accounted for 16% of the variance. The actions of these QTL were either dominance or underdominance. Our results indicated that at least three new QTL were mapped on chromosomes 1 and 3. The polygenic nature of susceptibility to P. gallinaceum and epistasis are important factors for significant variation within or among mosquito strains. The new map provides additional information useful for further genetic investigation, such as identification of new genes and positional cloning.

Aedes↗

FLOSS: flexible ordered subset analysis for linkage mapping of complex traits.

The FLOSS software package is a flexible framework for ordered subset analysis. FLOSS is specifically designed for use with the Merlin linkage analysis package, but FLOSS can be used with any linkage analysis software package that reports NPL Z-scores for each locus and family. When FLOSS is used with the Merlin linkage analysis package, one can use either non-parametric Z-scores or Kong and Cox linear allele sharing model LOD scores. Monte Carlo P-values are calculated using a permutation test with an efficient Besag-Clifford sequential stopping rule. FLOSS also has a flexible tool for assigning family covariate scores from Merlin input files. FLOSS includes user documentation and is written in Java for easy portability. The FLOSS source code is documented and designed to be extensible.

Algorithms↗

Genetic mapping of quantitative trait loci affecting susceptibility in chicken to develop pulmonary hypertension syndrome.

Pulmonary hypertension syndrome (PHS), also referred to as ascites syndrome, is a growth-related disorder of chickens frequently observed in fast-growing broilers with insufficient pulmonary vascular capacity at low temperature and/or at high altitude. A cross between two genetically different broiler dam lines that originated from the White Plymouth Rock breed was used to produce a three-generation population. This population was used for the detection and localization of quantitative trait loci (QTL) affecting PHS-related traits. Ten full-sib families consisting of 456 G2 birds were typed with 420 microsatellite markers covering 24 autosomal chromosomes. Phenotypic observations were collected on 4202 G3 birds and a full-sib across family regression interval mapping approach was used to identify QTL. There was statistical evidence for QTL on chicken chromosome 2 (GGA2), GGA4 and GGA6. Suggestive QTL were found on chromosomes 5, 8, 10, 27 and 28. The most significant QTL were located on GGA2 for right and total ventricular weight as percentage of body weight (%RV and %TV respectively). A related trait, the ratio of right ventricular weight as percentage to total ventricular weight (RATIO), reached the suggestive threshold on this chromosome. All three QTL effects identified on GGA2 had their maximum test statistic in the region flanked by markers MCW0185 and MCW0245 (335-421 cM).

Animals↗

Genetic mapping of quantitative trait loci governing longevity of Caenorhabditis elegans in recombinant-inbred progeny of a Bergerac-BO x RC301 interstrain cross.

Recombinant-inbred populations, generated from a cross between Caenorhabditis elegans strains Bergerac-BO and RC301, were used to identify quantitative trait loci (QTL) affecting nematode longevity. Genotypes of young controls and longevity-selected worms (the last-surviving 1% from a synchronously aged population) were assessed at dimorphic transposon-specific markers by multiplex polymerase chain reaction. The power of genetic mapping was enhanced, in a novel experimental design, through map expansion by accrual of recombinations over several generations, internally controlled longevity selection from a genetically heterogeneous, homozygous population, and selective genotyping of extremely long-lived worms. Analysis of individual markers indicated seven life-span QTL, situated near markers on chromosomes I (tcbn2), III (stP127), IV (stP13), V (stP6, stP23, and stP128), and X (stP41). These loci were corroborated, and mapped with increased precision, by nonparametric interval mapping-which supported all loci implicated by single-marker analysis. In addition, a life-span QTL on chromosome II (stP100-stP196), was significant only by interval mapping. Congenic lines were constructed for the longevity QTL on chromosomes III and X, by backcrossing the Bergerac-BO QTL allele into an RC301 background with selection for flanking markers. Survival data for these lines demonstrated consistent and significant effects of each QTL on life span.

Alleles↗

Functional mapping for quantitative trait loci governing growth rates: a parametric model.

Are there-specific quantitative trait loci (QTL) governing growth rates in biology? This is emerging as an exciting but challenging question for contemporary developmental biology, evolutionary biology, and plant and animal breeding. In this article, we present a new statistical model for mapping QTL underlying age-specific growth rates. This model is based on the mechanistic relationship between growth rates and ages established by a variety of mathematical functions. A maximum likelihood approach, implemented with the EM algorithm, is developed to provide the estimates of QTL position, growth parameters characterized by QTL effects, and residual variances and covariances. Based on our model, a number of biologically important hypotheses can be formulated concerning the genetic basis of growth. We use forest trees as an example to demonstrate the power of our model, in which a QTL for stem growth diameter growth rates is successfully mapped to a linkage group constructed from polymorphic markers. The implications of the new model are discussed.

Age Factors↗