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At least 235 records · Page 13Linked to original sources
PubMed2001

The genetic dissection of complex traits in a founder population.

We estimated broad heritabilities (H(2)) and narrow heritabilities (h(2)) and conducted genomewide screens, using a novel association-based mapping approach for 20 quantitative trait loci (QTLs) among the Hutterites, a founder population that practices a communal lifestyle. Heritability estimates ranged from.21 for diastolic blood pressure (DBP) to.99 for whole-blood serotonin levels. Using a multipoint method to detect association under a recessive model we found evidence of major QTLs for six traits: low-density lipoprotein (LDL), triglycerides, lipoprotein (a) (Lp[a]), systolic blood pressure (SBP), serum cortisol, and whole-blood serotonin. Second major QTLs for Lp(a) and for cortisol were identified using a single-point method to detect association under a general two-allele model. The heritabilities for these six traits ranged from.37 for triglycerides to.99 for serotonin, and three traits (LDL, SBP, and serotonin) had significant dominance variances (i.e., H(2) > h(2)). Surprisingly, there was little correlation between measures of heritability and the strength of association on a genomewide screen (P>.50), suggesting that heritability estimates per se do not identify phenotypes that are influenced by genes with major effects. The present study demonstrates the feasibility of genomewide association studies for QTL mapping. However, even in this young founder population that has extensive linkage disequilibrium, map densities <<5 cM may be required to detect all major QTLs.

Adolescent↗
PubMed2003

Cost-effective designs for linkage disequilibrium mapping of complex traits.

The current development of densely spaced collections of single nucleotide polymorphisms (SNPs) will lead to genomewide association studies for a wide range of diseases in many different populations. Determinations of the appropriate number of SNPs to genotype involve a balancing of power and cost. Several variables are important in these determinations. We show that there are different combinations of sample size and marker density that can be expected to achieve the same power. Within certain bounds, investigators can choose between designs with more subjects and fewer markers or those with more markers and fewer subjects. Which designs are more cost-effective depends on the cost of phenotyping versus the cost of genotyping. We show that, under the assumption of a set cost for genotyping, one can calculate a "threshold cost" for phenotyping; when phenotyping costs per subject are less than this threshold, designs with more subjects will be more cost-effective than designs with more markers. This framework for determining a cost-effective study will aid in the planning of studies, especially if there are choices to be made with respect to phenotyping methods or study populations.

Chromosome Mapping↗
PubMed2004

Prospects for admixture mapping of complex traits.

Admixture mapping extends to human populations the principles that underlie linkage analysis of an experimental cross. For detecting genes that contribute to ethnic variation in disease risk, admixture mapping has greater statistical power than family-linkage studies. In comparison with association studies, admixture mapping requires far fewer markers to search the genome and is less affected by allelic heterogeneity. Statistical-analysis programs for admixture mapping are now available, and a genomewide panel of markers for admixture mapping in populations formed by West African-European admixture has been assembled. Some of the remaining technical challenges include the ability to ensure that the statistical methods are robust and to develop marker panels for other admixed populations. Where admixed populations and panels of markers informative for ancestry are available, admixture mapping can be applied to localize genes that contribute to ethnic variation in any measurable trait.

Black People↗
PubMed2003

Simulating complex traits influenced by genes with fuzzy-valued effects in pedigreed populations.

MOTIVATION: Methods involving fuzzy theory have been rarely applied to genetics. We present an open platform for experimentation with fuzzy numbers as a tool to represent imprecise phenotypes in genetic modeling. RESULTS: A C++ library for simulation of genetic information transmission is introduced. The study of genetic linkage was its first goal, though a design so general as possible has been meant. Fuzzy-valued phenotypes are handled by means of fuzzy numbers. AVAILABILITY: ftp://carleos.etsiig.uniovi.es/pub/falin ftp://fisher.ciencias.uniovi.es/pub/falin ftp://bellman.ciencias.uniovi.es/pub/falin Licensed under the GNU General Public License version 2 (see http://www.gnu.org/licenses/gpl.html).

Algorithms↗
PubMed2004

FunMap: functional mapping of complex traits.

SUMMARY: FunMap is a Web-based user interface designed to map quantitative trait loci (QTL) affecting function-valued traits or infinite-dimensional traits in well-structured pedigrees or natural populations. User input includes three files: longitudinal trait data, marker genotypes and/or a linkage map. This software allows for a systematic genome-wide scan and significance test of QTL throughout the map. The dynamic change of QTL effects during the time course of growth is automatically drawn, from which specific biological hypotheses regarding the genetic control mechanisms of growth and development can be tested. AVAILABILITY: http://web.biostat.ufl.edu/~cma/genetics/software.html

Chromosome Mapping↗
PubMed2005

A non-stationary model for functional mapping of complex traits.

SUMMARY: Understanding the genetic control of growth is fundamental to agricultural, evolutionary and biomedical genetic research. In this article, we present a statistical model for mapping quantitative trait loci (QTL) that are responsible for genetic differences in growth trajectories during ontogenetic development. This model is derived within the maximum likelihood context, implemented with the expectation-maximization algorithm. We incorporate mathematical aspects of growth processes to model the mean vector and structured antedependence models to approximate time-dependent covariance matrices for longitudinal traits. Our model has been employed to map QTL that affect body mass growth trajectories in both male and female mice of an F2 population derived from the Large and Small mouse strains. The results from this model are compared with those from the autoregressive-based functional mapping approach. Based on results from computer simulation studies, we suggest that these two models are alternative to one another and should be used simultaneously for the same dataset.

Aging↗
PubMed2005

PAWE-3D: visualizing power for association with error in case-control genetic studies of complex traits.

UNLABELLED: A website that plots power and sample size calculations over a range of up to eight parameters (including diagnostic misclassification error parameters) for two commonly used statistical tests of genetic association, the linear trend test and the genotypic test of association. AVAILABILITY: This method is made available via the website http://linkage.rockefeller.edu/pawe3d/ CONTACT: pawe3d@linkage.rockefeller.edu.

Algorithms↗
PubMed2005

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↗
PubMed1998

A new approach to the problem of multiple comparisons in the genetic dissection of complex traits.

Saturated genetic marker maps are being used to map individual genes affecting quantitative traits. Controlling the "experimentwise" type-I error severely lowers power to detect segregating loci. For preliminary genome scans, we propose controlling the "false discovery rate," that is, the expected proportion of true null hypotheses within the class of rejected null hypotheses. Examples are given based on a granddaughter design analysis of dairy cattle and simulated backcross populations. By controlling the false discovery rate, power to detect true effects is not dependent on the number of tests performed. If no detectable genes are segregating, controlling the false discovery rate is equivalent to controlling the experimentwise error rate. If quantitative loci are segregating in the population, statistical power is increased as compared to control of the experimentwise type-I error. The difference between the two criteria increases with the increase in the number of false null hypotheses. The false discovery rate can be controlled at the same level whether the complete genome or only part of it has been analyzed. Additional levels of contrasts, such as multiple traits or pedigrees, can be handled without the necessity of a proportional decrease in the critical test probability.

Animals↗
PubMed1997

Functional screening and complex traits: human 21q22.2 sequences affecting learning in mice.

Libraries of the mammalian genome have generally been propagated in single cells and have been used for gene discovery through in vitro analyses. We have expanded upon this concept by the creation of panels of YAC transgenic mice propagating targeted megabase regions of the genome. Such a panel of mice can be called an 'in vivo library' and genes can be identified based on functional screens of members of the library. To test this approach, we created a 2 Mb in vivo library of human chromosome 21q22.2. Analysis of the library has revealed that one 570 kb YAC, in two separate founder lines, was associated with distinct learning deficits compared with the other 21q22 YAC transgenics and non-transgenic control animals. We have localized the gene on the YAC that causes the deficits by taking advantage of fragmentation of the YAC during the process of microinjection. The responsible gene is the human minibrain gene, and the homolog of the gene in Drosophila is also associated with learning defects. These results suggest that altered dosage of minibrain is associated with abnormal neural development in flies and mice and, in humans, may also be involved in the molecular pathology of Down syndrome.

Animals↗
PubMed2002

Genetic analysis of phenotype in Trypanosoma brucei: a classical approach to potentially complex traits.

The genome of the African trypanosome, Trypanosoma brucei, is currently being sequenced, raising the question of how the data generated can be used to determine the function of the large number of genes that will be identified. There is a range of possible approaches, and in this paper we discuss the use of a classical genetic approach coupled with positional cloning based on the ability of trypanosomes to undergo genetic exchange. The genetics of these parasites is essentially similar to a conventional diploid Mendelian system with allelic segregation and an independent assortment of markers on different chromosomes. Data are presented showing that recombination occurs between markers on the same chromosome allowing the physical size of the unit of recombination to be determined. Analysis of the available progeny clones from a series of crosses shows that, in principal, large numbers of progeny can readily be isolated from existing cryopreserved products of mating and, taking these findings together, it is clear that genetic mapping of variable phenotypes is feasible. The available phenotypes for analysis are outlined and most are relevant to the transmission and pathogenesis of the parasite. Genetic maps from two crosses are presented based on the use of the technique of AFLP; these maps comprise 146 and 139 markers in 30 and 21 linkage groups respectively. Segregation distortion is exhibited by some of the linkage groups and the possible reasons for this are discussed. The general conclusion, from the results presented, is that a genetic-mapping approach is feasible and will, in the future, allow the genes determining a number of important traits to be identified.

Animals↗
PubMed2004

Integrative genomics: in silico coupling of rat physiology and complex traits with mouse and human data.

Integration of the large variety of genome maps from several organisms provides the mechanism by which physiological knowledge obtained in model systems such as the rat can be projected onto the human genome to further the research on human disease. The release of the rat genome sequence provides new information for studies using the rat model and is a key reference against which existing and new rat physiological results can be aligned. Previously, we described comparative maps of the rat, mouse, and human based on EST sequence comparisons combined with radiation hybrid maps. Here, we use new data and introduce the Integrated Genomics Environment, an extensive database of curated and integrated maps, markers, and physiological results. These results are integrated by using VCMapview, a java-based map integration and visualization tool. This unique environment allows researchers to relate results from cytogenetic, genetic, and radiation hybrid studies to the genome sequence and compare regions of interest between human, mouse, and rat. Integrating rat physiology with mouse genetics and clinical results from human by using the respective genomes provides a novel route to capitalize on comparative genomics and the strengths of model organism biology.

Animals↗
PubMed2006

Power and sample size for testing associations of haplotypes with complex traits.

Evaluation of the association of haplotypes with either quantitative traits or disease status is common practice, and under some situations provides greater power than the evaluation of individual marker loci. The focus on haplotype analyses will increase as more single nucleotide polymorphisms (SNPs) are discovered, either because of interest in candidate gene regions, or because of interest in genome-wide association studies. However, there is little guidance on the determination of the sample size needed to achieve the desired power for a study, particularly when linkage phase of the haplotypes is unknown, and when a subset of tag-SNP markers is measured. There is a growing wealth of information on the distribution of haplotypes in different populations, and it is not unusual for investigators to measure genetic markers in pilot studies in order to gain knowledge of the distribution of haplotypes in the target population. Starting with this basic information on the distribution of haplotypes, we derive analytic methods to determine sample size or power to test the association of haplotypes with either a quantitative trait or disease status (e.g., a case-control study design), assuming that all subjects are unrelated. Our derivations cover both phase-known and phase-unknown haplotypes, allowing evaluation of the loss of efficiency due to unknown phase. We also extend our methods to when a subset of tag-SNPs is chosen, allowing investigators to explore the impact of tag-SNPs on power. Simulations illustrate that the theoretical power predictions are quite accurate over a broad range of conditions. Our theoretical formulae should provide useful guidance when planning haplotype association studies.

Computer Simulation↗
PubMed2025

Genetic effects on chromatin accessibility reveal the molecular mechanisms of complex traits in maize.

Cis-regulatory elements (CREs) are critical for modulating gene expression and phenotypic diversity in maize. While genome-wide association study (GWAS) hits and expression quantitative trait loci (eQTLs) are often enriched in CREs, their molecular mechanisms remain poorly understood. Characterizing CREs within accessible chromatin regions (ACRs) offers a powerful approach to link noncoding variants to chromatin structure alterations and phenotypic variation. Here, we generated ATAC-seq profiles from seedling leaves of 214 maize inbred lines, identifying 82&#x2009;174 consensus ACRs. Notably, 39.55% of these ACRs exhibited significant population-wide chromatin accessibility variation. By mapping chromatin accessibility quantitative trait loci (caQTLs), we discovered 27&#x2009;004 loci, including 1398 predicted to disrupt transcription factor (TF)-binding sites. Integration with multi-omics data revealed 7405 caACR-target gene pairs and linked 56 caACRs to GWAS signals for 51 agronomic traits, with significant enrichment in flowering-related pathways. Functional candidates such as ZmZIM30 - putatively regulated by caACRs - emerged as key regulators of flowering time. At the fad7 locus associated with linolenic acid content, allelic variants overlapping a caQTL showed differential chromatin accessibility. Our study provides a high-resolution cis-elements of maize leaves, deciphers the genetic basis of chromatin accessibility variation, and bridges noncoding caQTLs to molecular mechanisms underlying GWAS hits.

Zea mays↗
PubMed2004

Methods for genetic dissection of complex traits.

In this Perspective, the author responds to a recent SAGE KE Perspective. An alternative view of the benefits of quantitative trait loci mapping as a way to understand the molecular mechanisms of life-span determination is presented.

Animals↗