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PubMed2006

SAGE programs: model-free linkage analysis for complex cardiovascular phenotypes.

A complex disease trait refers to a phenotype that does not follow simple Mendelian segregation attributable to a single gene locus, but instead may be caused by multiple disease loci, their interactions, polygenic inheritance, and environmental effects. Most cardiovascular disorders are thought to have a polygenic basis with complex interactions with environmental factors. A gene that increases or decreases the risk to a complex cardiovascular disease (susceptibility gene) can now be mapped to a specific chromosomal region by model-free linkage analysis, and follow-up molecular genetic studies can identify the specific gene at the locus. This chapter describes a protocol for model-free linkage analysis of a complex trait, as implemented in the popular genetic analysis software-SAGE. In particular, the Haseman-Elston sib-pair regression method is introduced and implemented with examples to demonstrate how to identify susceptibility loci for complex traits.

Cardiovascular Diseases↗
PubMed1987

Influence of the swine major histocompatibility complex on reproductive traits in miniature swine.

Three swine leukocyte antigen (SLA)-defined strains of miniature swine and one recombinant strain were examined to evaluate the influence of the SLA Complex on litter size and piglet survivability. To separate the effects of sire and dam SLA haplotype from other sire and dam effects, a general linear model was employed to analyse data from 58 litters. Analysis of variance showed that sire and dam haplotype each contributed significantly to the variability observed in litter size among the sire and dam SLA combinations examined (P less than 0.0001, P less than 0.05, respectively). Sow SLA-haplotype as well as sire and dam effects other than those related to haplotype were significant factors contributing to survival until weaning (8 weeks) (P less than 0.10, P less than 0.07, P less than 0.001, respectively), but sire SLA-haplotype did not contribute significantly to this trait. Expected and observed haplotype frequencies of offspring in each litter were compared using chi-square analysis. A discrepancy was observed only in offspring from SLAa/d by SLAa/d matings, for which significantly fewer SLAa/a piglets were weaned than expected (P less than 0.06). Laparotomy during day 35-50 of pregnancy suggested that litter size was not an accurate estimate of ovulation rate and that ovulation rate was similar for dams of ad, ac and dd haplotypes.

Animals↗
PubMed2004

Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars.

Associations between markers and complex quantitative traits were investigated in a collection of 146 modern two-row spring barley cultivars, representing the current commercial germ plasm in Europe. Using 236 AFLP markers, associations between markers were found for markers as far apart as 10 cM. Subsequently, for the 146 cultivars the complex traits mean yield, adaptability (Finlay-Wilkinson slope), and stability (deviations from regression) were estimated from the analysis of variety trial data. Regression of those traits on individual marker data disclosed marker-trait associations for mean yield and yield stability. Support for identified associations was obtained from association profiles, i.e., from plots of P-values against chromosome positions. In addition, many of the associated markers were located in regions where earlier QTL were found for yield and yield components. To study the oligogenic genetic base of the traits in more detail, multiple linear regression of the traits on markers was carried out, using stepwise selection. By this procedure, 18-20 markers that accounted for 40-58% of the variation were selected. Our results indicate that association mapping approaches can be a viable alternative to classical QTL approaches based on crosses between inbred lines, especially for complex traits with costly measurements.

Bayes Theorem↗
PubMed1985

Multi-dimensional complexes of skull traits.

The simultaneous incidence of sutural bones was studied by a multidimensional analysis (Wanke method). On a medieval sample of 249 male and female skulls from Lower Austria the presence of two main complexes of sutural and fontanelle bones was observed. The interaction of possible genetic factors and developmental growth incongruences in causing these phenomena are discussed. The necessity of further studies considering such basic biological aspects with minor skeletal traits is stressed.

Analysis of Variance↗
PubMed1987

The human genome sequence and the analysis of multifactorial traits.

The human genome probably codes for about 10,000 basic functional units, most of which are functionally related families of genes occurring in one or more closely linked clusters. This relatively limited complexity means that a knowledge of the complete gene sequence is well within our grasp and will be fundamental to the analysis of complex multifactorial traits, including all the major chronic human diseases. Genetic marker segregation among 'affected' individuals in a pedigree, however complex, can now be done by using the essentially unlimited collection of restriction fragment length DNA polymorphisms. This can, in principle, identify all the inherited components of any complex trait and, with a knowledge of the human gene sequence, identify their functional basis. Thus one can now envisage a complete genetic and functional analysis of all complex inherited traits, including the major chronic diseases, and normal variation in physical and behavioural attributes.

Chromosome Mapping↗
PubMed2006

Multicomponent latent trait models for complex tasks.

Contemporary views on cognitive theory (e.g., Sternberg and Perez, 2005) regard typical measurement tasks, such as ability and achievement test items, multidimensional, rather than unidimensional. Assessing the levels and the sources of multidimensionality in an item domain is important for item selection as well as for item revision and development. In this paper, multicomponent latent trait models (MLTM) and traditional multidimensional item response theory models are described mathematically and compared for the nature of the dimensions that can be estimated. Then, some applications are presented to provide examples of MLTM. Last, practical estimation procedures are described, along with syntax, for the estimation of MLTM and a related model.

Cognition↗
PubMed2006

Improving the power of association tests for quantitative traits in family studies.

Association mapping based on family studies can identify genes that influence complex human traits while providing protection against population stratification. Because no gene is likely to have a very large effect on a complex trait, most family studies have limited power. Among the commonly used family-based tests of association for quantitative traits, the quantitative transmission-disequilibrium tests (QTDT) based on the variance-components model is the most flexible and most powerful. This method assumes that the trait values are normally distributed. Departures from normality can inflate the type I error and reduce the power. Although the family-based association tests (FBAT) and pedigree disequilibrium tests (PDT) do not require normal traits, nonnormality can also result in loss of power. In many cases, approximate normality can be achieved by transforming the trait values. However, the true transformation is unknown, and incorrect transformations may compromise the type I error and power. We propose a novel class of association tests for arbitrarily distributed quantitative traits by allowing the true transformation function to be completely unspecified and empirically estimated from the data. Extensive simulation studies showed that the new methods provide accurate control of the type I error and can be substantially more powerful than the existing methods. We applied the new methods to the Collaborative Study on the Genetics of Alcoholism and discovered significant association of single nucleotide polymorphisms (SNP) tsc0022400 on chromosome 7 with the quantitative electrophysiological phenotype TTTH1, which was not detected by any existing methods. We have implemented the new methods in a freely available computer program.

Alcoholism↗
PubMed2003

Quantitative trait locus analysis as a gene discovery tool.

Quantitative trait locus analysis has been a mainstay approach for obtaining a genetic description of complex agronomic traits for plants. What is sometimes overlooked is the role quantitative trait locus (QTL) analysis can play in identifying genes that underlay complex traits. In this chapter, I will describe the basic steps required to conduct QTL analysis in crop plants. This process involves choices by the investigator on type of population to be studied, molecular marker system to be used to genotype the population, and methods for QTL analysis. Examples of cloned genes, first identified as QTL, are also given to persuade the reader of the power of QTL analysis to discover genes controlling traits and phenotypes.

Chromosome Mapping↗
PubMed1996

Complex interactions of new quantitative trait loci, Sluc1, Sluc2, Sluc3, and Sluc4, that influence the susceptibility to lung cancer in the mouse.

Many complex traits, including susceptibility to lung cancer, are controlled by multiple genes--quantitative trait loci (QTLs). We facilitated the mapping of QTLs by making use of recombinant congenic strains (RCS), a system of mouse inbred strains in which the genetic complexity is reduced, and by applying MQM-mapping (multiple-QTL models or marker-QTL-marker), a multilocus method with an increased power of detecting of individual QTLs and interacting QTLs (epistasis). The mouse strain O20 develops significantly larger N-ethyl-N-nitrosourea induced lung tumours than mice of the RC strain OcB-9 (ref. 5); the latter share approximately 87.5% of their genes with strain O20 and 12.5% with strain B10.O20 (refs 6,7). QTL analysis of 222 (OcB-9 x O20) F2 mice revealed four new loci that influence susceptibility to lung cancer (Sluc genes). They are involved in two significant, partly counteracting interactions which mask their individual main effects: Sluc1 (on chromosome 19) interacts with Sluc2 (chromosome 2), and Sluc3 (chromosome 6) interacts with Sluc4 (chromosome 11). Together with the data of van Wezel et al. in the accompanying report, our results indicate that interactions between tumour susceptibility genes are a common phenomenon which complicates their mapping.

Animals↗
PubMed2002

Genetics of obesity and type 2 diabetes: tracking pathogenic traits during the predisease period.

The modern generalization of sedentary life and caloric abundance has created new physiological conditions capable of changing the level of expression of a number of genes involved in fuel metabolism and body weight regulation. It is likely that the genetic variants or alleles of these genes have in the past participated in the adaptation of human physiology to its evolutionary constraints. The nature and prevalence of polymorphisms responsible for the quantitative variation of complex metabolic traits may have been different among human populations, depending on their environment and ancestral genetic background. These polymorphisms could likely explain differences in disease susceptibility and prevalence among groups of humans. From complex traits to potentially complex alleles, understanding the molecular genetic basis underlying quantitative variation will continue to be a growing concern among geneticists dealing with obesity and type 2 diabetes, the main fuel disorders of the modern era. Genomics and genetic epidemiology now allow high-level linkage and association studies to be designed. But the pooling of large trans-geographic cohorts may in fact increase the genetic heterogeneity of studied traits and dilute genotype-phenotype associations. In this article, we underscore the importance of selecting the traits to be subjected to quantitative genetic analysis. Although this is not possible for most other multifactorial diseases, obesity and type 2 diabetes can be subjected to a pregenetic dissection of complexity into simpler quantitative traits (QTs). This dissection is based on the pathogenic mechanisms, and the time course of the traits, and the individuals' age, within the predisease period rather than on descriptive parameters after disease diagnosis. We defend that this approach of phenotypes may ease future associations to be established between QTs of intermediate complexity and genetic polymorphisms.

Diabetes Mellitus↗
PubMed2001

Trait contributions of complex dysregulated behavioral organization in schizophrenic patients.

BACKGROUND: The "temporal architecture" of behavior is a construct that can be used to quantify the structure of behavioral sequences in the temporal domain-for example, by using a two-choice prediction task to investigate how past responses, stimuli, and outcomes influence the decision-making process. Using this task, previous investigations of the temporal architecture of the behavior in schizophrenic patients have identified an increased frequency of alternating highly predictable and highly unpredictable response sequences in the same test session in the same patient. Here, the hypothesis is tested that this dysregulation is stable over time and independent of psychosocial factors and symptomatic fluctuations. METHODS: Ninety-one schizophrenic patients were tested on a 128 trial version of the two-choice prediction task; of those, 58 subjects completed a retest session 40 days later. Three sets of measures were obtained: simple response biases, dynamical entropy, and mutual information functions. These measures were subjected to a factor analysis, and the reliability of the resulting factors was examined. RESULTS: First, three factors were obtained, which quantify 1) the level of dysregulation on this task; 2) the extent to which a win-stay/lose-shift strategy was used; and 3) the amount of simple response perseveration. Second, Crohnbach alpha for these factors was .699, .721, and .458, respectively. Third, there were no significant differences in the level of these factors within individual patients at the two time points. Fourth, neither symptom measures (Scale for the Assessment of Positive Symptoms and Scale for the Assessment of Negative Symptoms subscale scores) nor psychosocial or clinical variables (age, gender, illness duration, medication status) were able to predict the level of these factors at test or at retest. CONCLUSIONS: These results support the hypothesis that the fundamental dysregulation of the temporal architecture of behavior in schizophrenic patients is stable across time and independent of symptomatic status. Future studies will examine the heritability of this dysfunction.

Adult↗
PubMed1999

Coadapted gene complexes for morphological traits in Drosophila mercatorum. Two-loci interactions.

The availability of molecular and morphological markers in a parthenogenetically reproducing strain of Drosophila mercatorum allowed us to design an experiment in which we could obtain a sample of completely homozygous recombinant females from two different parental homozygous strains. The phenotypic values of body-size-related measures and bristle numbers (sternopleural and abdominal) were measured in females sampled from the parental, F1 and F2 generations. The DNA extracted from the F2 flies was scored for five Mendelian segregating loci through double stringency PCR. In addition, the flies were scored for three morphological recessive loci. We estimated all single-locus and all two-loci associations between the marker loci with the principal components of the morphological data, which allowed us also to estimate the epistatic parameters. The results suggest that the underlying genetic architecture of the morphological phenotypes cannot be regarded as a result of additivity only, but instead, involves many different kinds of interactions that are distributed around an additive mean.

Animals↗
PubMed1995

[Comparative analysis of variability in a complex of anthropometric traits in full-term and premature neonates].

Variations of four anthropometric traits (body weight, body length, circumference of head, and circumference of chest) were compared in 149 premature and 819 full-term newborns. The average value of every studied trait for premature newborns was much less than that for full-term newborns. In premature boys, the correlation between body weight and length and circumferences of head and chest was substantially decreased. The coefficient of linear correlation between body mass and body weight for premature newborns was higher than that for full-term newborns. This was accounted for by the peculiarities of growth of the fetus during late prenatal development. Premature, boys and girls, in contrast to full-term children, did not differ considerably in the average values of the anthropometric traits studied. Therefore, the differences between newborn boys and girls in weight and size (sexual dimorphism) are formed at the last month of prenatal development.

Anthropometry↗
PubMed1997

Impact of adjustments for intermediate phenotypes on the power to detect linkage.

Since the manifestation of a complex disease is likely to be influenced through multiple genetic and/or environmental pathways, it may be advantageous to adjust for these multiple factors in a genetic analysis of a complex quantitative trait. Sib-pair linkage analysis was performed on the simulated complex quantitative trait Q1 after adjustment for age, sex, and the environmental factor (i.e., minimally adjusted) and all combinations of the four intermediate phenotypes Q2, Q3, Q4, and Q5 (n = 15) for all 200 replications of the nuclear families data set. From the minimally adjusted Q1, the power to detect suggestive linkage to any of the three loci affecting Q1 was 0.585 with a false positive rate of 0.0025. Adjusting Q1 for Q3 increased the power to detect suggestive linkage to 0.860 with a similar false positive rate. Additional adjustments for Q2, Q4, and Q5 yielded no substantial improvements in power nor changes in the false positive rate. The power to detect significant linkage was also substantially improved after adjustment of Q1 for Q3 with no change in the false positive rate. The adjustment of a complex trait for other factors in the causal pathway reduces the phenotype variability and enhances the ability to detect linkage.

Chromosome Mapping↗
PubMed2004

Towards the molecular understanding of the polar overdominance phenomenon associated with the callipyge phenotype in sheep.

Most medically or agronomically important phenotypes are "complex" inherited traits. They are influenced by genes but not transmitted according to Mendel's laws. Recently, Steve Henikoff wrote: "The nature of quantitative-trait variation is one of the last unexplored frontiers in genetics, awaiting the future and definitive identification of complex trait determinants, wether they be genetic or epigenetic" (Nature Genetics, 2003). The callipyge phenotype is a muscular hypertrophy in sheep that is characterized by a complex inheritance pattern referred to as polar overdominance: only heterozygous individuals having received the CLPG mutation from their sire exhibit the phenotype. We have spent the last ten years attempting to dissect the molecular basis of this unique phenomenon. These studies have lead to a working model including: (i) DLKI, a paternally expressed growth promoter, (ii) a maternally expressed DLK1 trans-acting repressor that is likely to be a non-coding RNA, and (iii) the CLPG mutation inactivating a silencer element controlling both the expression of DLK1 and its trans-acting repressor in skeletal muscle. This research is not only of fundamental interest, but may as well lead to a better understanding and hence control of "complex" diseases exhibiting "parent-of-origin" effects.

Animals↗
PubMed2001

In silico mapping of complex disease-related traits in mice.

Experimental murine genetic models of complex human disease show great potential for understanding human disease pathogenesis. To reduce the time required for analysis of such models from many months down to milliseconds, a computational method for predicting chromosomal regions regulating phenotypic traits and a murine database of single nucleotide polymorphisms were developed. After entry of phenotypic information obtained from inbred mouse strains, the phenotypic and genotypic information is analyzed in silico to predict the chromosomal regions regulating the phenotypic trait.

Algorithms↗
PubMed2005

Bayesian model selection for genome-wide epistatic quantitative trait loci analysis.

The problem of identifying complex epistatic quantitative trait loci (QTL) across the entire genome continues to be a formidable challenge for geneticists. The complexity of genome-wide epistatic analysis results mainly from the number of QTL being unknown and the number of possible epistatic effects being huge. In this article, we use a composite model space approach to develop a Bayesian model selection framework for identifying epistatic QTL for complex traits in experimental crosses from two inbred lines. By placing a liberal constraint on the upper bound of the number of detectable QTL we restrict attention to models of fixed dimension, greatly simplifying calculations. Indicators specify which main and epistatic effects of putative QTL are included. We detail how to use prior knowledge to bound the number of detectable QTL and to specify prior distributions for indicators of genetic effects. We develop a computationally efficient Markov chain Monte Carlo (MCMC) algorithm using the Gibbs sampler and Metropolis-Hastings algorithm to explore the posterior distribution. We illustrate the proposed method by detecting new epistatic QTL for obesity in a backcross of CAST/Ei mice onto M16i.

Algorithms↗