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PubMed2006

TAMAL: an integrated approach to choosing SNPs for genetic studies of human complex traits.

UNLABELLED: Investigators conducting studies of the molecular genetics of complex traits in humans often need rationally to select a set of single nucleotide polymorphisms (SNPs) from the hundreds or thousands available for a candidate gene. Accomplishing this requires integration of genomic data from distributed databases and is both time-consuming and error-prone. We developed the TAMAL (Technology And Money Are Limiting) web site to help identify promising SNPs for further investigation. For a given list of genes, TAMAL identifies SNPs that meet user-specified criteria (e.g. haplotype tagging SNPs or SNP predicted to lead to amino acid changes) from current versions of online resources (i.e. HapMap, Perlegen, Affymetrix, dbSNP and the UCSC genome browser). AVAILABILITY: TAMAL is a platform independent web-based application available free of charge at http://neoref.ils.unc.edu/tamal. SUPPLEMENTARY INFORMATION: http://neoref.ils.unc.edu/tamal/.

Chromosome Mapping↗
PubMedDate not supplied

The future of path analysis, segregation analysis, and combined models for genetic dissection of complex traits.

Appropriate combined models are discussed for the analysis of complex traits. It is argued that combined models may be necessary for optimally extracting the information from family studies. It is further argued that, especially as we face genes with much smaller effects, our ability to find these genes will depend on how precisely and accurately we are able to model the interrelationships. We need these newer models and methods for optimally extracting the information from family data, and we also need to reorient ourselves as to how we interpret the very information extracted. It is projected that path and segregation analysis, as seen in terms of combined models, will be useful in the new millennium.

Chromosome Segregation↗
PubMed2003

WebQTL: web-based complex trait analysis.

WebQTL is a website that combines databases of complex traits with fast software for mapping quantitative trait loci (QTLs) and for searching for correlations among traits. WebQTL also includes well-curated genotype data for five sets of mouse recombinant inbred (RI) lines. Thus, to identify QTLs, users need provide only quantitative trait data from one of the supported populations. The WebQTL databases include both biological traits--neuroanatomical, pharmacological, and behavioral traits--and microarray-based gene expression data from BXD RI lines. A search function finds correlations between RNA expression and biological traits, and mapping functions find QTLs for either type of trait. The WebQTL service is available at http://www.webqtl.org/.

Animals↗
PubMed2003

Informatics center for mouse genomics: the dissection of complex traits of the nervous system.

In recent years, there has been an explosion in the number of tools and techniques available to researchers interested in exploring the genetic basis of all aspects of central nervous system (CNS) development and function. Here, we exploit a powerful new reductionist approach to explore the genetic basis of the very significant structural and molecular differences between the brains of different strains of mice, called either complex trait or quantitative trait loci (QTL) analysis. Our specific focus has been to provide universal access over the web to tools for the genetic dissection of complex traits of the CNS--tools that allow researchers to map genes that modulate phenotypes at a variety of levels ranging from the molecular all the way to the anatomy of the entire brain. Our website, The Mouse Brain Library (MBL; http://mbl.org) is comprised of four interrelated components that are designed to support this goal: The Brain Library, iScope, Neurocartographer, and WebQTL. The centerpiece of the MBL is an image database of histologically prepared museum-quality slides representing nearly 2000 mice from over 120 strains--a library suitable for stereologic analysis of regional volume. The iScope provides fast access to the entire slide collection using streaming video technology, enabling neuroscientists to acquire high-magnification images of any CNS region for any of the mice in the MBL. Neurocartographer provides automatic segmentation of images from the MBL by warping precisely delineated boundaries from a 3D atlas of the mouse brain. Finally, WebQTL provides statistical and graphical analysis of linkage between phenotypes and genotypes.

Analysis of Variance↗
PubMed2002

Third international meeting on the genetic epidemiology of complex traits, April 4-6, 2002, Cambridge, UK.

The Third International Meeting on the Genetic Epidemiology of Complex Traits was held at Churchill College, Cambridge, UK on April 4-6, 2002. The event was organized by the Twin Research and Genetic Epidemiology Unit, St Thomas' Hospital, London and sponsored by Roche Genetics and Insightful. It provided an interactive forum for discussion of topical issues relating to the genetic analysis of complex diseases and traits. Topics discussed included linkage disequilibrium mapping and candidate gene analysis, as well as cutting edge advances in both technologies and statistical analysis methods. Details of the meeting can be found at http://www.twin-research.ac.uk/.

Chromosome Mapping↗
PubMed2025

Expanded Chromatin Accessibility Mapping Explains Genetic Variation Associated with Complex Traits in Liver.

Genome-wide association studies (GWAS) have identified thousands of loci associated with a variety of common, complex human traits. Recent efforts have focused on characterizing chromatin accessibility to discover regulatory elements that modify the expression of nearby genes, suggesting that trait associations are mediated through changes in gene regulation. Genetic variants associated with differences in chromatin accessibility, known as chromatin accessibility quantitative trait loci (caQTLs), are established contributors to gene expression differences, providing mechanistic hypotheses for signals identified by GWAS. Using the assay for transposase-accessible chromatin with sequencing (ATAC-seq), we assessed chromatin accessibility in 189 diverse human liver samples, identifying over two million accessible chromatin regions enriched for gene regulatory features and, in 175 of these samples, over 14,000 caQTLs. Focusing subsequently on liver-relevant complex traits, we obtained publicly available blood lipids GWAS data and identified 157 loci where caQTLs, expression quantitative trait loci (eQTLs), and GWAS signals colocalized. This generated specific molecular hypotheses about regulatory elements, affected genes, and, in some cases, implicated transcription factors. Finally, we enumerated the set of blood lipid trait signals that lack an obvious proposed mechanism beyond catalogs of liver caQTLs and eQTLs. After integrating 10 multi-omic QTL regulatory mechanism datasets whilst considering limitations in statistical power, we found that approximately 20% of blood lipid GWAS signals lacked a statistical link to a proposed mechanism. Our results demonstrate the value of integrating multiple genomic datasets to improve understanding of GWAS signals, while emphasizing the need for additional experimental approaches to fully characterize complex trait associations.

Journal Article↗
PubMed2001

Novel selection criteria for genome scans of complex traits.

Due to their oligogenic inheritance, the identification of susceptibility loci for complex traits by classical selection criteria has not been very successful. One way to address this problem is to identify statistics that measure the effect of more than one locus simultaneously. In the approach described here, a p-value is assigned to a combination of loci under the null hypothesis that none of them is linked to the disease locus. In order to examine the power of this method to detect multiple loci, the Genetic Analysis Workshop 12 general population simulated data set was analyzed using variance component methods. Using the described novel selection criteria resulted in an increase of power, however, a rejection of the null hypothesis has to be interpreted with care.

Analysis of Variance↗
PubMed1999

Population genomics in Sardinia: a novel approach to hunt for genomic combinations underlying complex traits and diseases.

The availability of highly polymorphic markers permits testing whether complex traits and diseases result from genomic interactions between nonallelic normal variants at separate loci. Such variants may be identified by deviations from the expected distributions of alleles at a high number of polymorphic loci, when individuals with the phenotype of interest are compared to normal controls of the same breeding unit, provided that both groups share the same remote ancestry and had no ancestors in common for the last three to four generations. The circumstances needed for such studies are ideally met on the island of Sardinia. The recurrent finding of the same type of association in separate breeding units between the phenotype of interest and a given genotype should allow a distinction between true genetic identity by descent and randomly occurring identities, as these will be obviously different in separate breeding units. The availability of several breeding units located in sharply different ecological environments will permit assessment of the role of nature/nurture factors in the degree of manifestation of each newly discovered genotype/phenotype association. A pilot study to evaluate the proposed strategy has been carried out in the Sardinian village of Carloforte, a community of about 8,000 individuals who have remained genetically homogeneous. Fifty-five control samples have been genotyped with six tetranucleotide microsatellites and with a subset of the 400 markers contained in the ABI PRISM linkage mapping panel, version 2. The allele frequencies for these microsatellite markers have been determined for these 55 individuals and compared to those from a random sampling of subsets of these 55 persons. For the six tetranucleotide microsatellites, a subset of as few as 20 people displayed the same allele frequency distributions as observed with the original 55 unrelated individuals. In conclusion, when samples are chosen from the same breeding unit, the number of individuals sufficient to draw the genomic profile of an isolated population can be relatively small. Likewise, the number of probands with the phenotype of interest can be even smaller when they are ascertained with the same genealogical criteria as the normal controls. By comparing the genomic profile of the probands to a fraction of the control samples within each of several separate breeding units of common remote ancestry, the search for genotype/phenotype association for mono- and multifactorial traits and diseases should be simplified and yield unequivocal results.

Aged↗
PubMed1996

Production of congenic mouse strains carrying NOD-derived diabetogenic genetic intervals: an approach for the genetic dissection of complex traits.

Insulin-dependent (Type 1) diabetes (IDD) in the NOD mouse is inherited as a complex polygenic trait making the identification of susceptibility genes difficult. Currently none of the non-MHC IDD susceptibility genes in NOD have been identified. In this paper we describe the congenic mouse approach that we are using for the dissection of complex traits, such as IDD. We produced a series of six congenic strains carrying NOD-derived diabetogenic genomic intervals, which were previously identified by linkage analysis, on a resistant background. These congenic strains were produced for the purpose of characterizing the function of each of these genes, alone and in combinations, in IDD pathogenesis and to allow fine mapping of the NOD IDD susceptibility genes. Histological examination of pancreata from 6 to 8-month-old congenic mice reveals that intervals on Chromosomes (Chrs) 1 and 17, but not 3, 6, and 11, contain NOD-derived genes that can increase the trafficking of mononuclear cells into the pancreas. Insulitis was observed only very rarely, even in older congenic mice, indicating that multiple genes are required for this phenotype. These results demonstrate the utility of this congenic approach for the study of complex genetic traits.

Animals↗
PubMed2002

Association mapping, using a mixture model for complex traits.

Association mapping for complex diseases using unrelated individuals can be more powerful than family-based analysis in many settings. In addition, this approach has major practical advantages, including greater efficiency in sample recruitment. Association mapping may lead to false-positive findings, however, if population stratification is not properly considered. In this paper, we propose a method that makes it possible to infer the number of subpopulations by a mixture model, using a set of independent genetic markers and then testing the association between a genetic marker and a trait. The proposed method can be effectively applied in the analysis of both qualitative and quantitative traits. Extensive simulations demonstrate that the method is valid in the presence of a population structure.

Alleles↗
PubMed2025

Simple scaling laws control the genetic architectures of human complex traits.

Genome-wide association studies have revealed that the genetic architectures of complex traits vary widely, including in terms of the numbers, effect sizes, and allele frequencies of significant hits. However, at present we lack a principled way of understanding the similarities and differences among traits. Here, we describe a probabilistic model that combines the effects of mutation, drift, and stabilizing selection at individual sites with a genome-scale model of phenotypic variation. In this model, the architecture of a trait arises from the distribution of selection coefficients of mutations and from two scaling parameters. We fit this model for 95 highly polygenic quantitative traits of different kinds from the UK Biobank. Notably, we infer that all these traits have fairly similar, though not identical, distributions of selection coefficients. This similarity suggests that differences in architectures of highly polygenic traits arise mainly from the two scaling parameters: the mutational target size and heritability per site, which vary by orders of magnitude among traits. When these two scale factors are accounted for, we find that the architectures of all 95 traits are very similar.

Humans↗
PubMed1990

Linkage strategies for genetically complex traits. I. Multilocus models.

In order to investigate linkage detection strategies for genetically complex traits, multilocus models of inheritance need to be specified. Here, two types of multilocus model are described: (1) a multiplicative model, representing epistasis (interaction) among loci, and (2) an additive model, which is shown to closely approximate genetic heterogeneity, which is characterized by no interlocus interaction. A ratio lambda R of risk for type R relatives that is compared with population prevalence is defined. For a single-locus model, lambda R - 1 decreases by a factor of two with each degree of relationship. The same holds true for an additive multilocus model. For a multiplicative (epistasis) model, lambda R - 1 decreases more rapidly than by a factor of two with degree of relationship. Examination of lambda R values for various classes of relatives can potentially suggest the presence of multiple loci and epistasis. For example, data for schizophrenia suggest multiple loci in interaction. It is shown in the second paper of this series that lambda R is the critical parameter in determining power to detect linkage by using affected relative pairs.

Genetic Linkage↗
PubMed2006

Quantitative trait analysis of seed yield and other complex traits in hybrid spring rapeseed (Brassica napus L.): 2. Identification of alleles from unadapted germplasm.

Unadapted germplasm may contain alleles that could improve hybrid cultivars of spring oilseed Brassica napus. Quantitative trait loci (QTL) mapping was used to identify potentially useful alleles from two unadapted germplasm sources, a Chinese winter cultivar and a re-synthesized B. napus, that increase seed yield when introgressed into a B. napus spring hybrid combination. Two populations of 160 doubled haploid (DH) lines were created from crosses between the unadapted germplasm source and a genetically engineered male-fertility restorer line (P1804). A genetically engineered male-sterile tester line was used to create hybrids with each DH line (testcrosses). The two DH line populations were evaluated in two environments and the two testcross populations were evaluated in three or four environments for seed yield and other agronomic traits. Several genomic regions were found in the two testcross populations which contained QTL for seed yield. The map positions of QTL for days to flowering and resistance to a bacterial leaf blight disease coincided with QTL for seed yield and other agronomic traits, suggesting the occurrence of pleiotropic or linked effects. For two hybrid seed yield QTL, the favorable alleles increasing seed yield originated from the unadapted parents, and one of these QTL was detected in multiple environments and in both populations. In this QTL region, a chromosome rearrangement was identified in P1804, which may have affected seed yield.

Alleles↗
PubMed1997

Trade-off between false positives and false negatives in the linkage analysis of complex traits.

This study examines the issue of false positives in genomic scans for detecting complex trait loci using subpair linkage methods and investigates the trade-off between the rate of false positives and the rate of false negatives. It highlights the tremendous cost in terms of power brought about by an excessive control of type I error and, at the same time, confirms that a larger number of false positives can occur otherwise in the course of a genomic scan. Finally, it compares the power and rate of false positives obtained in preplanned replicated studies conducted using a liberal significance level to those for single-step studies that use the same total sample size but stricter levels of significance. For the models considered here, replicate studies were found more attractive as long as one is willing to accept a trade-off, exchanging a much lower rate of false negatives for a slight increase in the rate of false positives.

False Negative Reactions↗
PubMed2006

Analysing the effect of candidate genes on complex traits: an application in multiple sclerosis.

The conventional approach of candidate gene studies in complex diseases is to look at the effect of one gene at a time. However, as the outcome of chronic diseases is influenced by a large number of alleles, simultaneous analysis is needed. We demonstrate the application of multivariate regression and cluster analysis to a multiple sclerosis (MS) dataset with genotypes for 489 patients at 11 candidate genes selected on their involvement in the immune response. Using multivariate regression, we observed that different sets of genes were associated with different disease characteristics that reflect different aspects of disease. Out of 15 polymorphisms, we identified one that contributed to the severity of disease. In addition, the set of 15 polymorphisms was predictive for yearly increase in lesion volume as seen on T1-weighted MRI (p=0.044). From this set, no individual polymorphisms could be identified after adjustment for multiple hypotheses testing. By means of a cluster analysis, we aimed to identify subgroups of patients with different pathogenic subtypes of MS on the basis of their genetic profile. We constructed genetic profiles from the genotypes at the 11 candidate genes. The approach proved to be feasible. We observed three clusters in the sample of patients. In this study, we observed no significant differences in the usual clinical and MRI outcome measures between the different clusters. However, a number of consistent trends indicated that this clustering might be related to the course of disease. With a larger number of genes regulating the course of disease, we may be able to identify clinically relevant clusters. The analyses are easily implemented and will be applicable to candidate gene studies of complex traits in general.

Adult↗
PubMed2006

Meeting report for the 4th annual Complex Trait Consortium meeting: from QTLs to systems genetics.

The fourth annual meeting of the Complex Trait Consortium (CTC) was held in Groningen, the Netherlands on June 26-29, 2005. This meeting, which set a new attendance record, followed three previous and highly successful meetings. The focus at this meeting was on continued resource development and the exiting new field of systems genetics, the integration and anchoring of multi-dimensional data-types to underlying genetic variation. A new aspect at the meeting was the three-minute, 'come see my poster' presentations that generated significant interaction at the poster sessions. If the 2005 meeting is an indicator of things to come, future meetings promise to offer even more exciting research efforts to integrate high-throughput biological measurements with genetic variation to unravel the mechanisms responsible for inter-individual variation.

Animals↗
PubMed1995

Statistical methods for linkage analysis of complex traits from high-resolution maps of identity by descent.

A multilocus model for complex traits is described that generalizes the additive and multiplicative models and hence allows simultaneously for both heterogeneity and gene interaction (epistasis). Statistical methods of linkage analysis are discussed under the assumption that identity by descent data from a dense set of polymorphic markers are available. Three methods, single locus search, simultaneous search and conditional search, are described and compared.

Chromosome Mapping↗
PubMed1995

Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results.

Genetic studies are under way for many complex traits, spurred by the recent feasibility of whole genome scans. Clear guidelines for the interpretation of linkage results are needed to avoid a flood of false positive claims. At the same time, an overly cautious approach runs the risk of causing true hints of linkage to be missed. We address this problem by proposing specific standards designed to maintain rigor while also promoting communication.

Genetic Linkage↗