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PubMed2000

Mapping a quantitative trait locus via the EM algorithm and Bayesian classification.

Mapping a locus controlling a quantitative genetic trait (e.g., blood pressure) to a specific genomic region is of considerable interest. Data on the quantitative trait under consideration and several codominant genetic markers with known genomic locations are collected from members of families and statistically analyzed to draw inferences on the genomic position of the trait locus. The vector of parameters of interest comprises the pairwise recombination fractions, theta, between the putative quantitative trait locus and the marker loci. One of the major complications in estimating theta for a quantitative trait in humans is the lack of haplotype information on members of families. The purpose of this study was to devise a computationally simple and efficient method of estimation of theta in the absence of haplotype information. We have proposed a two-stage estimation procedure using the expectation-maximization (EM) algorithm. In the first stage, parameters of the QTL are estimated based on data of a sample of unrelated individuals. From estimates thus obtained, we have used a Bayes' rule to infer QTL genotypes of parents in families. Finally, in the second stage of the procedure, we have proposed an EM algorithm for obtaining the maximum likelihood estimate of theta based on data of informative families (which are identified upon inferring parental QTL genotypes performed in the first stage). We have shown, using simulated data, that the proposed procedure is cost-effective, computationally simple, and statistically efficient. As expected, analysis of data on multiple markers jointly is more efficient than the analysis based on single markers.

Algorithms↗
PubMed2003

Combined high resolution linkage and association mapping of quantitative trait loci.

In this paper, we investigate variance component models of both linkage analysis and high resolution linkage disequilibrium (LD) mapping for quantitative trait loci (QTL). The models are based on both family pedigree and population data. We consider likelihoods which utilize flanking marker information, and carry out an analysis of model building and parameter estimations. The likelihoods jointly include recombination fractions, LD coefficients, the average allele substitution effect and allele dominant effect as parameters. Hence, the model simultaneously takes care of the linkage, LD or association and the effects of the putative trait locus. The models clearly demonstrate that linkage analysis and LD mapping are complementary, not exclusive, methods for QTL mapping. By power calculations and comparisons, we show the advantages of the proposed method: (1) population data can provide information for LD mapping, and family pedigree data can provide information for both linkage analysis and LD mapping; (2) using family pedigree data and a sparse marker map, one may investigate the prior suggestive linkage between trait locus and markers to obtain low resolution of the trait loci, because linkage analysis can locate a broad candidate region; (3) with the prior knowledge of suggestive linkage from linkage analysis, both population and family pedigree data can be used simultaneously in high resolution LD mapping based on a dense marker map, since LD mapping can increase the resolution for candidate regions; (4) models of high resolution LD mappings using two flanking markers have higher power than that of models of using only one marker in the analysis; (5) excluding the dominant variance from the analysis when it does exist would lose power; (6) by performing linkage interval mappings, one may get higher power than by using only one marker in the analysis.

Chromosome Mapping↗
PubMed2006

Complex genetic architecture revealed by analysis of high-density lipoprotein cholesterol in chromosome substitution strains and F2 crosses.

Intercrosses between inbred lines provide a traditional approach to analysis of polygenic inheritance in model organisms. Chromosome substitution strains (CSSs) have been developed as an alternative to accelerate the pace of gene identification in quantitative trait mapping. We compared a classical intercross and three CSS intercrosses to examine the genetic architecture underlying plasma high-density lipoprotein cholesterol (HDL) levels in the C57BL/6J (B) and A/J (A) mouse strains. The B x A intercross revealed significant quantitative trait loci (QTL) for HDL on chromosomes 1, 4, 8, 15, 17, 18, and 19. A CSS survey revealed that many have significantly different HDL levels compared to the background strain B, including chromosomes with no significant QTL in the intercross and, in some cases (CSS-1, CSS-17), effects that are opposite to those observed in the B x A intercross population. Intercrosses between B and three CSSs (CSS-3, CSS-11, and CSS-8) revealed significant QTL but with some unexpected differences from the B x A intercross. Our inability to predict the results of CSS intercrosses suggests that additional complexity will be revealed by further crosses and that the CSS mapping strategy should be viewed as a complement to, rather than a replacement for, classical intercross mapping.

Animals↗
PubMed2003

Genetic correlates of gene expression in recombinant inbred strains: a relational model system to explore neurobehavioral phenotypes.

Full genome sequencing, high-density genotyping, expanding sets of microarray assays, and systematic phenotyping of neuroanatomical and behavioral traits are producing a wealth of data on the mouse central nervous system (CNS). These disparate resources are still poorly integrated. One solution is to acquire these data using a common reference population of isogenic lines of mice, providing a point of integration between the data types. Recombinant inbred (RI) mice, derived through inbreeding of progeny from an inbred cross, are a powerful tool for complex trait mapping and analysis of the challenging phenotypes of neuroscientific interest. These isogenic RI lines are a retrievable genetic resource that can be repeatedly studied using a wide variety of assays. Diverse data sets can be related through fixed and known genomes, using tools such as the interactive web-based system for complex trait analysis, www.WebQTL.org. In this report, we demonstrate the use of WebQTL to explore complex interactions among a wide variety of traits--from mRNA transcripts to the impressive behavioral and pharmacological variation among RI strains. The relational approach exploiting a common set of strains facilitates study of multiple effects of single genes (pleiotropy) without a priori hypotheses required. Here we demonstrate the power of this technique through genetic correlation of gene expression with a database of neurobehavioral phenotypes collected in these strains of mice through more than 20 years of experimentation. By repeatedly studying the same panel of mice, early data can be re-examined in light of technological advances unforeseen at the time of their initial collection.

Animals↗
PubMed2002

A statistical method for identification of polymorphisms that explain a linkage result.

Suppose that many polymorphic sites have been identified and genotyped in a region showing strong linkage with a trait. A key question of interest is which site (or combination of sites) in the region influences susceptibility to the trait. We have developed a novel statistical approach to this problem, in the context of qualitative-trait mapping, in which we use linkage data to identify the polymorphic sites whose genotypes could fully explain the observed linkage to the region. The information provided by this analysis is different from that provided by tests of either linkage or association. Our approach is based on the observation that if a particular site is the only site in the region that influences the trait, then-conditional on the genotypes at that site for the affected relatives-there should be no unexplained oversharing in the region among affected individuals. We focus on the affected sib-pair study design and develop test statistics that are variations on the usual allele-sharing methods used in linkage studies. We perform hypothesis tests and derive a confidence set for the true causal polymorphic site, under the assumption that there is only one site in the region influencing the trait. Our method is appropriate under a very general model for how the site influences the trait, including epistasis with unlinked loci, correlated environmental effects within families, and gene-environment interaction. We extend our method to larger sibships and apply it to an NIDDM1 data set.

Alleles↗
PubMed2003

Signatures of selection? Patterns of microsatellite diversity on a chromosome containing a selected locus.

This paper explores patterns of genetic diversity near a locus known to have been under selection. The myostatin gene (GDF-8) has been shown to be associated with double muscling, a phenotype selected for in a number of cattle breeds. We examined population genetic parameters for microsatellite loci at varying distances from GDF-8 in double-muscled (DM) and non-double-muscled (non-DM) cattle breeds in order to assess patterns of diversity. A theoretical analysis was also performed to predict the patterns of diversity expected under different scenarios. We found differences in the patterns of heterozygosity, allele diversity and linkage disequilibrium between DM and non-DM breeds. However, there were some exceptions to the predicted patterns. These are discussed in light of the histories of the breeds and the potential for using microsatellite diversity for mapping trait genes in livestock populations.

Animals↗
PubMed2003

High-resolution joint linkage disequilibrium and linkage mapping of quantitative trait loci based on sibship data.

This paper proposes variance component models for high resolution joint linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) based on sibship data; this can include population data if independent individuals are treated as single sibships. One application of these models is late onset complex disease gene mapping, when parental data are not available. The models simultaneously incorporate both LD and linkage information. The LD information is contained in mean coefficients of sibship data. The linkage information is contained in the variance-covariance matrices of trait values for sibships with at least two siblings. We derive formulas for calculating the probability of sharing two trait alleles identical by descent (IBD) for sibpairs in interval mapping of QTL; this is the coefficient of dominant variance of the trait covariance of sibpairs on major QTL. To investigate the performance of the formulas, we calculate the numerical values via the formulas and get satisfactory approximations. We compare the power and sample sizes for both LD and linkage mapping. By simulation and theoretical analysis, we compare the results with those of Fulker and Abecasis "AbAw" approach. It is well known that the resolution of linkage analysis can be low for complex disease gene mapping. LD mapping, on the other hand, can increase mapping precision and is useful in high resolution mapping. Linkage analysis is less sensitive to population subdivisions and admixtures. The level of LD is sensitive to population stratification which may easily lead to spurious association. Performing a joint analysis of LD and linkage mapping can help to overcome the limits of both approaches. Moreover, the advantages of the two complementary strategies can be utilized maximally. In practice, linkage analysis may be performed using pedigree data to identify suggestive linkage between markers and trait loci based on a sparse marker map. In the presence of linkage, joint LD and linkage mapping can be carried out to do fine gene mapping based on a dense genetic map using both pedigree and population data. Population and pedigree data of any type can be combined to perform a joint analysis of high resolution LD and linkage mapping of QTL by generalizing the method.

Alleles↗
PubMed1997

Mapping-linked quantitative trait loci using Bayesian analysis and Markov chain Monte Carlo algorithms.

A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic markers is presented. Parameter estimation and hypothesis testing was implemented via Markov chain Monte Carlo (MCMC) algorithms. Parameters included were allele frequencies and substitution effects for two biallelic QTL, map positions of the QTL, and markers, allele frequencies of the markers, and polygenic and residual variances. Missing data were polygenic effects and multi-locus marker-QTL genotypes. Three different MCMC schemes for testing the presence of a single or two linked QTL on the chromosome were compared. The first approach includes a model indicator variable representing two unlinked QTL, affecting the trait, one linked and one unlinked QTL, or both QTL linked with the markers. The second approach incorporates an indicator variable for each QTL into the model for phenotype, allowing or not allowing for a substitution effect of a QTL, on phenotype, and the third approach is based on model determination by reversible jump MCMC. Methods were evaluated empirically by analyzing simulated granddaughter designs. All methods identified correctly a second, linked QTL and did not reject the one-QTL model when there was only a single QTL, and no additional or an unlinked QTL.

Algorithms↗
PubMed2004

Linkage analysis: principles and methods for the analysis of human quantitative traits.

Currently, mapping genes for complex human traits relies on two complementary approaches, linkage and association analyses. Both suffer from several methodological and theoretical limitations, which can considerably increase the type-1 error rate and reduce the power to map human quantitative trait loci (QTL). This review focuses on linkage methods for QTL mapping. It summarizes the most common linkage statistics used, namely Haseman-Elston-based methods, variance components, and statistics that condition on trait values. Methods developed more recently that accommodate the X-chromosome, parental imprinting and allelic association in linkage analysis are also summarized. The type-I error rate and power of these methods are discussed. Finally, rough guidelines are provided to help guide the choice of linkage statistics.

Genetic Linkage↗
PubMed1999

Fine-mapping of quantitative trait loci by identity by descent in outbred populations: application to milk production in dairy cattle.

We previously mapped a quantitative trait locus (QTL) affecting milk production to bovine chromosome 14. To refine the map position of this QTL, we have increased the density of the genetic map of BTA14q11-16 by addition of nine microsatellites and three single nucleotide polymorphisms. Fine-mapping of the QTL was accomplished by a two-tiered approach. In the first phase, we identified seven sires heterozygous "Qq" for the QTL by marker-assisted segregation analysis in a Holstein-Friesian pedigree comprising 1,158 individuals. In a second phase, we genotyped the seven selected sires for the newly developed high-density marker map and searched for a shared haplotype flanking an hypothetical, identical-by-descent QTL allele with large substitution effect. The seven chromosomes increasing milk fat percentage were indeed shown to carry a common chromosome segment with an estimated size of 5 cM predicted to contain the studied QTL. The same haplotype was shown to be associated with increased fat percentage in the general population as well, providing additional support in favor of the location of the QTL within the corresponding interval.

Animals↗
PubMed1994

The power of interval mapping of quantitative trait loci, using selected sib pairs.

The interval-mapping procedure of Fulker and Cardon for analysis of a quantitative-trait loci (QTL) is extended for application to selected samples of sib pairs. Phenotypic selection of sib pairs, which is known to yield striking increases in power when a single marker is used, provides further increases in power when the interval-mapping approach is used. The greatest benefits of the combined approach are apparent with coarse maps, where QTLs of relatively modest (15%-20%) heritability can be detected with widely spaced markers (40-60 cM apart) in reasonably sized sibling samples. Useful information concerning QTL location is afforded by interval mapping in both selected and unselected samples.

Algorithms↗
PubMed2002

Precision and high-resolution mapping of quantitative trait loci by use of recurrent selection, backcross or intercross schemes.

Dissecting quantitative genetic variation into genes at the molecular level has been recognized as the greatest challenge facing geneticists in the twenty-first century. Tremendous efforts in the last two decades were invested to map a wide spectrum of quantitative genetic variation in nearly all important organisms onto their genome regions that may contain genes underlying the variation, but the candidate regions predicted so far are too coarse for accurate gene targeting. In this article, the recurrent selection and backcross (RSB) schemes were investigated theoretically and by simulation for their potential in mapping quantitative trait loci (QTL). In the RSB schemes, selection plays the role of maintaining the recipient genome in the vicinity of the QTL, which, at the same time, are rapidly narrowed down over multiple generations of backcrossing. With a high-density linkage map of DNA polymorphisms, the RSB approach has the potential of dissecting the complex genetic architecture of quantitative traits and enabling the underlying QTL to be mapped with the precision and resolution needed for their map-based cloning to be attempted. The factors affecting efficiency of the mapping method were investigated, suggesting guidelines under which experimental designs of the RSB schemes can be optimized. Comparison was made between the RSB schemes and the two popular QTL mapping methods, interval mapping and composite interval mapping, and showed that the scenario of genomic distribution of QTL that was unlocked by the RSB-based mapping method is qualitatively distinguished from those unlocked by the interval mapping-based methods.

Animals↗
PubMed2002

Comparative mapping of the barley Ppd-H1 photoperiod response gene region, which lies close to a junction between two rice linkage segments.

Comparative mapping of cereals has shown that chromosomes of barley, wheat, and maize can be described in terms of rice "linkage segments." However, little is known about marker order in the junctions between linkage blocks or whether this will impair comparative analysis of major genes that lie in such regions. We used genetic and physical mapping to investigate the relationship between the distal part of rice chromosome 7L, which contains the Hd2 heading date gene, and the region of barley chromosome 2HS containing the Ppd-H1 photoperiod response gene, which lies near the junction between rice 7 and rice 4 linkage segments. RFLP markers were mapped in maize to identify regions that might contain Hd2 or Ppd-H1 orthologs. Rice provided useful markers for the Ppd-H1 region but comparative mapping was complicated by loss of colinearity and sequence duplications that predated the divergence of rice, maize, and barley. The sequences of cDNA markers were used to search for homologs in the Arabidopsis genome. Homologous sequences were found for 13 out of 16 markers but they were dispersed in Arabidopsis and did not identify any candidate equivalent region. The implications of the results for comparative trait mapping in junction regions are discussed.

Arabidopsis↗
PubMed2003

Limits of fine-mapping a quantitative trait.

Once a significant linkage is found, an important goal is reducing the error in the estimated location of the linked locus. A common approach to reducing location error, called fine-mapping, is the genotyping of additional markers in the linked region to increase the genetic information. The utility of fine-mapping for quantitative trait linkage analysis is largely unknown. To explore this issue, we performed a fine-mapping simulation in which the region containing a significant linkage at a 10-centiMorgan (cM) resolution was fine-mapped at 2, 1, and 0.5 cM. We simulated six quantitative trait models in which the proportion of variation due to the quantitative trait locus (QTL) ranged from 0.20-0.90. We used four sampling designs that were all combinations of 100 and 200 families of sizes 5 and 7. Variance components linkage analysis (Genehunter) was performed until 1,000 replicates were found with a maximum lodscore greater than 3.0. For each of these 1,000 replications, we repeated the linkage analysis three times: once for each of the fine-map resolutions. For the most realistic model, reduction in the average location error ranged from 3-15% for 2-cM fine-mapping and from 3-18% for 1-cM fine-mapping, depending on the number of families and family size. Fine-mapping at 0.5 cM did not differ from the 1-cM results. Thus, if the QTL accounts for a small proportion of the variation, as is the case for realistic traits, fine-mapping has little value.

Chromosome Mapping↗
PubMed2005

The period length of fibroblast circadian gene expression varies widely among human individuals.

Mammalian circadian behavior is governed by a central clock in the suprachiasmatic nucleus of the brain hypothalamus, and its intrinsic period length is believed to affect the phase of daily activities. Measurement of this period length, normally accomplished by prolonged subject observation, is difficult and costly in humans. Because a circadian clock similar to that of the suprachiasmatic nucleus is present in most cell types, we were able to engineer a lentiviral circadian reporter that permits characterization of circadian rhythms in single skin biopsies. Using it, we have determined the period lengths of 19 human individuals. The average value from all subjects, 24.5 h, closely matches average values for human circadian physiology obtained in studies in which circadian period was assessed in the absence of the confounding effects of light input and sleep-wake cycle feedback. Nevertheless, the distribution of period lengths measured from biopsies from different individuals was wider than those reported for circadian physiology. A similar trend was observed when comparing wheel-running behavior with fibroblast period length in mouse strains containing circadian gene disruptions. In mice, inter-individual differences in fibroblast period length correlated with the period of running-wheel activity; in humans, fibroblasts from different individuals showed widely variant circadian periods. Given its robustness, the presented procedure should permit quantitative trait mapping of human period length.

3T3 Cells↗
PubMed1998

Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects.

The efficiency of marker-assisted selection (MAS) depends on the power of quantitative trait locus (QTL) detection and unbiased estimation of QTL effects. Two independent samples N = 344 and 107 of F2 plants were genotyped for 89 RFLP markers. For each sample, testcross (TC) progenies of the corresponding F3 lines with two testers were evaluated in four environments. QTL for grain yield and other agronomically important traits were mapped in both samples. QTL effects were estimated from the same data as used for detection and mapping of QTL (calibration) and, based on QTL positions from calibration, from the second, independent sample (validation). For all traits and both testers we detected a total of 107 QTL with N = 344, and 39 QTL with N = 107, of which only 20 were in common. Consistency of QTL effects across testers was in agreement with corresponding genotypic correlations between the two TC series. Most QTL displayed no significant QTL x environment nor epistatic interactions. Estimates of the proportion of the phenotypic and genetic variance explained by QTL were considerably reduced when derived from the independent validation sample as opposed to estimates from the calibration sample. We conclude that, unless QTL effects are estimated from an independent sample, they can be inflated, resulting in an overly optimistic assessment of the efficiency of MAS.

Chromosome Mapping↗
PubMed2025

Chromosome-level genome assembly and annotation of Petunia hybrida.

Petunia hybrida is the world's most popular garden plant and is regarded as a supermodel for studying the biology associated with the Asterid clade, the largest of the two major groups of flowering plants. Unlike other Solanaceae, petunia has a base chromosome number of seven, not 12. This along with recombination suppression has previously hindered efforts to assemble its genome to chromosome level. Here we achieve a chromosome-level assembly for P. hybrida using a combination of short-read and long-read sequencing, optical mapping (Bionano) and Hi-C technologies. The resulting assembly spans 1253.6 Mb with a BUSCO score of 99.8%. A total of 35,089 genes were predicted and of those 29,655 were functionally annotated. Syntenic regions between petunia, tomato and pepper were identified, highlighting rearrangements that have occurred since their divergence indicating that the 12 chromosomes of Solanaceae did not originate from whole genome duplication of an ancestral species with seven chromosomes like petunia. This assembly will enhance trait mapping efficiency and serve as a valuable resource for functional genomic studies.

Petunia↗
PubMed2000

Fine mapping of quantitative trait loci using advanced intercross lines of mice and positional cloning of the corresponding genes.

High-resolution mapping of quantitative trait loci (QTLs) is an essential step towards positional cloning and identification of the corresponding genes. Most QTL detection and mapping studies in mice have been carried out using F2 intercross and backcross populations. As a consequence of the limited number of recombination events in small chromosomal regions, this has generally permitted mapping to only relatively large confidence intervals of 20 to 40 cM. A number of population designs have been proposed to increase recombination level in crosses. This includes advanced intercross lines (AIL) described by Darvasi and Soller [Genomics. 1995; 141: 1199-1207]. In this report demonstration of the utility of the AIL approach for fine mapping of QTL, which previously had been mapped with 95% confidence interval to 20 to 40 cM in a F2 intercross, will be presented. The methodological approaches to go from the fine-mapped QTL to the identification of the actual genes and mutations are discussed.

Animals↗