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PubMed2001

Archival, demographic and genetic studies define a Sardinian sub-isolate as a suitable model for mapping complex traits.

Genetic isolates represent exceptional resources for the mapping of complex traits but not all isolates are similar. We have selected a genetic and cultural isolate, the village of Talana from an isolated area of Sardinia, and propose that this population is suitable for the mapping of complex traits. A wealth of historical and archive data allowed the reconstruction of the demographic and genealogical history of the village. Key features of the population, which has grown slowly with no significant immigration, were defined by using a combination of historical, demographic and genetic studies. The genealogy of each Talana inhabitant was reconstructed and the main maternal and paternal lineages of the village were defined. Haplotype and phylogenetic analyses of the Y chromosome and characterisation of mitochondrial DNA haplogroups were used to determine the number of ancestral village founders. The extent of linkage disequilibrium (LD) was evaluated by the analysis of several microsatellites in chromosomal region Xq13.3, which was previously used to asses the extension of LD. Genealogical reconstructions were confirmed and reinforced by the genetic analyses, since some lineages were found to have merged prior to the beginning of the archival records, suggesting an even smaller number of founders than initially predicted. About 80% of the present-day population appears to derive from eight paternal and eleven maternal ancestral lineages. LD was found to span, on average, a 5-Mb region in Xq13.3. This suggests the possibility of identifying identical-by-descent regions associated with complex traits in a genome-wide search by using a low-density marker map. The present study emphasises the importance of combining genetic studies with genealogical and historical information.

Chromosome Mapping↗
PubMed1997

Advances in statistical methods to map quantitative trait loci in outbred populations.

Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.

Bayes Theorem↗
PubMed2003

Combining gene expression and molecular marker information for mapping complex trait genes: a simulation study.

A method for mapping complex trait genes using cDNA microarray and molecular marker data jointly is presented and illustrated via simulation. We introduce a novel approach for simulating phenotypes and genotypes conditionally on real, publicly available, microarray data. The model assumes an underlying continuous latent variable (liability) related to some measured cDNA expression levels. Partial least-squares logistic regression is used to estimate the liability under several scenarios where the level of gene interaction, the gene effect, and the number of cDNA levels affecting liability are varied. The results suggest that: (1) the usefulness of microarray data for gene mapping increases when both the number of cDNA levels in the underlying liability and the QTL effect decrease and when genes are coexpressed; (2) the correlation between estimated and true liability is large, at least under our simulation settings; (3) it is unlikely that cDNA clones identified as significant with partial least squares (or with some other technique) are the true responsible cDNAs, especially as the number of clones in the liability increases; (4) the number of putatively significant cDNA levels increases critically if cDNAs are coexpressed in a cluster (however, the proportion of true causal cDNAs within the significant ones is similar to that in a no-coexpression scenario); and (5) data reduction is needed to smooth out the variability encountered in expression levels when these are analyzed individually.

Chromosome Mapping↗
PubMed2003

Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson.

An advanced backcross population between an accession of Oryza rufipogon (IRGC 105491) and the U.S. cultivar Jefferson (Oryza sativa ssp. japonica) was developed to identify quantitative trait loci (QTLs) for yield, yield components and morphological traits. The genetic linkage map generated for this population consisted of 153 SSR and RFLP markers with an average interval size of 10.3 cM. Thirteen traits were examined, nine of which were measured in multiple environments. Seventy-six QTLs above an experiment-wise significance threshold of P<0.01 (corresponding to an interval mapping LOD>3.6 or a composite interval mapping LOD>3.9) were identified. For the traits measured in multiple environments, 47% of the QTLs were detected in at least two environments. The O. rufipogon allele was favorable for 53% of the yield and yield component QTLs, including loci for yield, grains per panicle, panicle length, and grain weight. Morphological traits related to the domestication process and/or weedy characteristics, including plant height, shattering, tiller type and awns, were found clustered on chromosomes 1 and 4. Comparisons to previous studies involving wild x cultivated crosses revealed O. rufipogon alleles with stable effects in multiple genetic backgrounds and environments, several of which have not been detected in studies between Oryza sativa cultivars, indicating potentially novel alleles from O. rufipogon. Some O. rufipogon-derived QTLs, however, were in similar regions as previously reported QTLs from Oryza sativa cultivars, providing evidence for conservation of these QTLs across the Oryza genus. In addition, several QTLs for grain weight, plant height, and flowering time were localized to putative homeologous regions in maize where QTLs for these traits have been previously reported, supporting the hypothesis of functional conservation of QTLs across the grasses.

Chromosome Mapping↗
PubMed2003

Quantitative trait locus mapping for atherosclerosis susceptibility.

PURPOSE OF REVIEW: Atherosclerosis is a complex trait with both environmental and genetic aspects. Although some progress has been made in defining genes associated with atherosclerosis in humans, animal models have been useful in learning about pathways and genes involved in atherogenesis. This review describes an unbiased genetic mapping method called quantitative trait locus mapping and progress in using this method to identify genes that alter atherosclerosis susceptibility in mice. RECENT FINDINGS: Approximately 10 well defined genetic loci have been described that are associated with lesion severity in diet-induced or gene knockout mouse models of atherosclerosis. Recently, two of these genetic loci were narrowed considerably by analysis of genetic recombinants within these loci. In addition, a computational method to discover quantitative trait loci has been applied to atherosclerosis. However, none of the genes responsible for these atherosclerosis quantitative trait loci has been definitively identified. The recent completion of the mouse draft genome should facilitate the task of identifying these genes. SUMMARY: Quantitative trait locus mapping studies in mouse models of atherosclerosis have defined genetic regions that alter lesion severity. The identification of the responsible genes may lead to insights into the pathogenesis of atherosclerosis as well as to candidates for human genetic association studies.

Animals↗
PubMed2005

Methodology of mapping quantitative trait loci for ordinal traits of disease resistance in livestock.

Methodology of QTL mapping for ordinal traits of disease resistance based on the framework of a generalized linear model (GLM) was presented. The location and effect parameters of putative QTL were estimated using maximum likelihood method. The efficiency and power were compared with the linear model (LM). The factors influencing QTL detection efficiency (e.g. QTL effect and heritability) were simulated in our study too. Daughter design with multiple families was applied,and the number of segregating population was 500. Results showed that the threshold model has a certain advantage in location estimation and power of QTL mapping, and has efficiency and accuracy for ordinal traits. In addition,the accuracy of QTL mapping depends on the effect of putative quantitative trait loci and the value of heritability. With the increase of QTL effect and heritability, the accuracy of QTL mapping improves slightly.

Animals↗
PubMed1998

Efficient, robust, and unified method for mapping complex traits (I): two-point linkage analysis.

The completion of a preliminary human genome map and development of molecular methods have enabled researchers to assay a large number of polymorphic markers that are evenly spaced along the entire human genome. Among many applications, marker data are valuable for mapping complex traits through linkage or linkage-disequilibrium analysis, the former of which is the focus of this paper, the first in a series on this subject. Formalizing the concept and computation for linkage analysis, Elston and Stewart [1971; Human Heredity 21:523-542] introduced a likelihood function to capture relevant genetic information and a recursive algorithm for computing the likelihood function. However, the computing burden is prohibitive in processing complex pedigrees. Since that fundamental development, improving the computational algorithm and extending the method has been a dynamic area of research. The primary objective of this communication is to introduce a semiparametric method for linkage analysis. It is a particularly suitable approach with desirable properties for mapping complex traits that may be binary, continuous, and partially observed (i.e., censored). It incorporates candidate genes, environmental factors, and their interactions with the putative gene and is expected to be robust and efficient in comparison with likelihood-based methods. The properties of the estimates have been studied in finite samples with a limited simulation study. This method is illustrated with an application to family data contributed to the Breast Cancer Consortium.

Algorithms↗
PubMed2006

Causal inference of regulator-target pairs by gene mapping of expression phenotypes.

BACKGROUND: Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, then loci involved in regulatory control can theoretically be implicated. Recent efforts to construct gene regulatory networks from genotype and gene expression data have shown that biologically relevant networks can be achieved from an integrative approach. In this paper, we consider the problem of identifying individual pairs of genes in a direct or indirect, causal, trans-acting relationship. RESULTS: Inspired by epistatic models of multi-locus quantitative trait (QTL) mapping, we propose a unified model of expression and genotype to identify quantitative trait genes (QTG) by extending the conventional linear model to include both genotype and expression of regulator genes and their interactions. The model provides mapping of specific genes in contrast to standard linkage approaches that implicate large QTL intervals typically containing tens of genes. In simulations, we found that the method can often detect weak trans-acting regulators amid the background noise of thousands of traits and is robust to transcription models containing multiple regulator genes. We reanalyze several pleiotropic loci derived from a large set of yeast matings and identify a likely alternative regulator not previously published. However, we also found that many regulators can not be so easily mapped due to the presence of cis-acting QTLs on the regulators, which induce close linkage among small neighborhoods of genes. QTG mapped regulator-target pairs linked to ARN1 were combined to form a regulatory module, which we observed to be highly enriched in iron homeostasis related genes and contained several causally directed links that had not been identified in other automatic reconstructions of that regulatory module. Finally, we also confirm the surprising, previously published results that regulators controlling gene expression are not enriched for transcription factors, but we do show that our more precise mapping model reveals functional enrichment for several other biological processes related to the regulation of the cell. CONCLUSION: By incorporating interacting expression and genotype, our QTG mapping method can identify specific regulator genes in contrast to standard QTL interval mapping. We have shown that the method can recover biologically significant regulator-target pairs and the approach leads to a general framework for inducing a regulatory module network topology of directed and undirected edges that can be used to identify leads in pathway analysis.

Algorithms↗
PubMed2002

[Mapping quantitative trait loci for fat deposition in carcass in pigs].

One of the major determining factors in the price of market hogs today is backfat depth. Therefore, identification of regions of the genome affecting this trait is necessary. Gene-mapping technologies have provided scientists the necessary reagents to conduct genomewide searches for genes affecting any phenotype determined in part by the genetic makeup of the animal. Over the past few years, several experimental crosses have been used to detect quantitative triat loci (QTL) for fatness and meat quality traits in pigs. In an intercross between Large White and Meishan pigs, 81 F2 progenies in 1998 were slaughtered and phenotyped for fat deposite traits. F2 animals, their parents, and their grandparents were typed for molecular markers covering chromosomes (SSC) 1,2,3,4,6 and 7, since previous studies had revealed QTL affecting fatness traits on these chromosomes. Linear model and least square analyses were used for mapping these traits. Furthermore, a QTL accounting for imprinting effects was used. A total of 14 QTL at chromosome-wide level were detected on SSC1, 3-4, 6 and 7 for 12 fatness traits. There were evidences for imprinting effects on SSC7 for four traits at 60 cM and nearby. There were QTL for average backfat thickness (BFT) on SSC1, 4 and 7. Among them, BFT QTL on SSC1 and 7 may be the common locus for Sus scrofa. QTL for internal fat percentage was on SSC7 and QTL for average sidefat on SSC6.

Adipose Tissue↗
PubMed2001

Mapping quantitative trait loci in oligogenic models.

We discuss strategies for mapping quantitative trait loci with emphasis on certain issues of study design that have recently received attention: e.g. genotyping only selected pedigrees and the comparative value of large pedigrees versus sib pairs. We use a standard variance components model and a parametrization of the genetic effects in which the 'segregation' parameters are locally orthogonal to the 'linkage' parameters. This permits simple explicit expressions for the expectation of the score statistic, which we use to compare the power of different strategies. We also discuss robustness of the score statistic.

Journal Article↗
PubMed2004

Mapping quantitative trait loci with censored observations.

The existing statistical methods for mapping quantitative trait loci (QTL) assume that the phenotype follows a normal distribution and is fully observed. These assumptions may not be satisfied when the phenotype pertains to the survival time or failure time, which has a skewed distribution and is usually subject to censoring due to random loss of follow-up or limited duration of the experiment. In this article, we propose an interval-mapping approach for censored failure time phenotypes. We formulate the effects of QTL on the failure time through parametric proportional hazards models and develop efficient likelihood-based inference procedures. In addition, we show how to assess genome-wide statistical significance. The performance of the proposed methods is evaluated through extensive simulation studies. An application to a mouse cross is provided.

Chromosome Mapping↗
PubMed2001

Mapping quantitative trait Loci using generalized estimating equations.

A number of statistical methods are now available to map quantitative trait loci (QTL) relative to markers. However, no existing methodology can simultaneously map QTL for multiple nonnormal traits. In this article we rectify this deficiency by developing a QTL-mapping approach based on generalized estimating equations (GEE). Simulation experiments are used to illustrate the application of the GEE-based approach.

Algorithms↗
PubMed2002

Mapping quantitative trait loci and identification of genes that control fatness in poultry.

Chicken genomics has benefited from the rapid technological advances in the genomics of model organisms and man. A number of resources and approaches are now well established, in the chicken, including genetic markers and maps (both genetic and physical), quantitative trait loci mapping, comparative mapping, expressed sequence tag and bacterial artificial chromosome resources, and physical mapping. In addition, the next phase of gene discovery, functional genomics, is underway. Progress in mapping quantitative trait loci for growth and fatness traits will be discussed, as an application of these new technologies and approaches in the study of avian physiology and genetics.

Adipose Tissue↗
PubMed2006

Selective trade-offs and sex-chromosome evolution in Silene latifolia.

Alleles of sexually antagonistic genes (i.e., genes with alleles affecting fitness in opposite directions in the two sexes) can avoid expression in the sex to which they are detrimental via two processes: they are subsumed into the nonrecombining, sex-determining portion of the sex chromosomes or they evolve sex-limited expression. The former is considered more likely and leads to Y-chromosome degeneration. We mapped quantitative trait loci of major effect for sexually dimorphic traits of Silene latifolia to the recombining portions of the sex chromosomes and found them to exhibit sex-specific expression, with the Y chromosome in males controlling a relatively larger proportion of genetic variance than the X in females and the average autosome. Both reproductive and ecophysiological traits map to the recombining region of the sex chromosomes. We argue that genetic correlations among traits maintain recombination and polymorphism for these genes because of balancing selection in males, whereas sex-limited expression represses detrimental alleles in females. Our data suggest that the Y chromosome of S. latifolia plays a major role in the control of key metabolic activities beyond reproductive functions.

Alleles↗
PubMed1998

Combining different line crosses for mapping quantitative trait loci using the identical by descent-based variance component method.

Mapping quantitative trait loci (QTLs) is usually conducted with a single line cross. The power of such QTL mapping depends highly on the two parental lines. If the two lines are fixed for the same allele at a putative QTL, the QTL is undetectable. On the other hand, if a QTL is segregating in the line cross and is detected, the estimated variance of the QTL cannot be extrapolated beyond the statistical inference space of the two parental lines. To reduce the likelihood of missing a QTL and to increase the statistical inference space of the estimated QTL variance, we present a consensus QTL mapping strategy. We adopt the identical by descent (IBD)-based variance component method originally applied to human linkage analysis by combining multiple line crosses as independent families. We explore the properties of consensus QTL mapping and demonstrate the method with F2, backcross (BC), and full-sib (FS) families. In addition, we examine the effects of the QTL heritability, marker informativeness, QTL position, the number of families, and family size. We show that F2 families notably outperform BC and FS families in detecting a QTL. There is a substantial reduction in the standard deviation of the estimated QTL position and the separation of the QTL and polygenic variance. Finally, we show that the power to detect a QTL is greater when using a small number of large families than a large number of small families.

Chromosome Mapping↗
PubMed1995

Alcohol acceptance, preference, and sensitivity in mice. II. Quantitative trait loci mapping analysis using BXD recombinant inbred strains.

Quantitative trait loci (QTL) mapping of complex phenotypes has emerged as an important feature of the recombinant inbred (RI) strain methodology. In this second study of our series on alcohol-related behaviors in mice, we examine alcohol acceptance, preference, and hypnotic dose sensitivity (HDS) to a standard dose of alcohol measured in BXD RI strains to identify candidate QTL regions responsible for their heritability. We detected highly significant marker associations for acceptance on chromosome 12 (Eif4e), for preference on chromosome 1 (D1Rti2) and chromosome 7 (D7Mit7), and for HDS on chromosome 7 (Mpmv1). These are the strongest QTL associations that we detected, but several other candidate QTL regions are reported. Given the limited number of BXD RI strains available, the large number of markers used herein, and the consequent chance of identifying false marker associations, these RI QTL mapping results must be seen as tentative, but an important first step toward identifying QTL for alcohol-related behaviors.

Alcohol Drinking↗
PubMed2000

A method for fine mapping quantitative trait loci in outbred animal stocks.

High-resolution mapping of quantitative trait loci (QTL) in animals has proved to be difficult because the large effect sizes detected in crosses between inbred strains are often caused by numerous linked QTLs, each of small effect. In a study of fearfulness in mice, we have shown it is possible to fine map small-effect QTLs in a genetically heterogeneous stock (HS). This strategy is a powerful general method of fine mapping QTLs, provided QTLs detected in crosses between inbred strains that formed the HS can be reliably detected in the HS. We show here that single-marker association analysis identifies only two of five QTLs expected to be segregating in the HS and apparently limits the strategy's usefulness for fine mapping. We solve this problem with a multipoint analysis that assigns the probability that an allele descends from each progenitor in the HS. The analysis does not use pedigrees but instead requires information about the HS founder haplotypes. With this method we mapped all three previously undetected loci [chromosome (Chr.) 1 logP 4.9, Chr. 10 logP 6.0, Chr. 15 logP 4.0]. We show that the reason for the failure of single-marker association to detect QTLs is its inability to distinguish opposing phenotypic effects when they occur on the same marker allele. We have developed a robust method of fine mapping QTLs in genetically heterogeneous animals and suggest it is now cost effective to undertake genomewide high-resolution analysis of complex traits in parallel on the same set of mice.

Animals↗