GENLIB: new function to simulate haplotype transmission in large complex genealogies.

Summary: Founder populations with deep genealogical data are well suited for investigating genetic variants contributing to diseases. Here, we present a major update of the genealogical analysis R package GENLIB, centered around a new function which can simulate the transmission of haplotypes from founders to probands along very large and complex user-specified genealogies.

Availability And Implementation: The latest update of the GENLIB package (v1.

Comparison of mixed model based approaches for correcting for population substructure with application to extreme phenotype sampling.

Background: Mixed models are used to correct for confounding due to population stratification and hidden relatedness in genome-wide association studies. This class of models includes linear mixed models and generalized linear mixed models. Existing mixed model approaches to correct for population substructure have been previously investigated with both continuous and case-control response variables.

A single historical substitution drives an increase in acetylcholine receptor complexity.

Human adult muscle-type acetylcholine receptors are heteropentameric ion channels formed from four different, but evolutionarily related, subunits. These subunits assemble with a precise stoichiometry and arrangement such that two chemically distinct agonist-binding sites are formed between specific subunit pairs. How this subunit complexity evolved and became entrenched is unclear.

Contingency between Historical Substitutions in the Acetylcholine Receptor Pore.

Human adult muscle-type acetylcholine receptors incorporating a reconstructed ancestral β-subunit exhibit reduced single-channel conductance when compared to wild-type. The ancestral and wild-type β-subunits differ by 132 amino acids, including substitution of residues that line the lumen of the channel pore, near its narrowest constriction. Here we show that a single historical substitution in this region of the ancestral β-subunit accounts for the difference in conductance.

A Cautionary Note on the Effects of Population Stratification Under an Extreme Phenotype Sampling Design.

Extreme phenotype sampling (EPS) is a popular study design used to reduce genotyping or sequencing costs. Assuming continuous phenotype data are available on a large cohort, EPS involves genotyping or sequencing only those individuals with extreme phenotypic values. Although this design has been shown to have high power to detect genetic effects even at smaller sample sizes, little attention has been paid to the effects of confounding variables, and in particular population stratification.

Modeling gene-environment interactions in longitudinal family studies: a comparison of methods and their application to the association between the IGF pathway and childhood obesity.

Background: The interactive effect of the IGF pathway genes with the environment may contribute to childhood obesity. Such gene-environment interactions can take on complex forms. Detecting those relationships using longitudinal family studies requires simultaneously accounting for correlations within individuals and families.

Sampletrees and Rsampletrees: sampling gene genealogies conditional on SNP genotype data.

Unlabelled: : The program sampletrees is a Markov chain Monte Carlo sampler of gene genealogies conditional on either phased or unphased SNP genotype data. The companion program Rsampletrees is for pre- and post-processing of sampletrees files, including setting up the files for sampletrees and storing and plotting the output of a sampletrees run.

Availability And Implementation: sampletrees is implemented in C ++.

A Comparison of Statistical Methods for the Discovery of Genetic Risk Factors Using Longitudinal Family Study Designs.

The etiology of immune-related diseases or traits is often complex, involving many genetic and environmental factors and their interactions. While methodological approaches focusing on an outcome measured at one time point have succeeded in identifying genetic factors involved in immune-related traits, they fail to capture complex disease mechanisms that fluctuate over time. It is increasingly recognized that longitudinal studies, where an outcome is measured at multiple time points, have great potential to shed light on complex disease mechanisms involving genetic factors.

Using gene genealogies to detect rare variants associated with complex traits.

Background And Objective: Standard population genetic theory says that deleterious genetic variants are likely rare and fairly recently introduced. However, can this expectation lead to more powerful tests of association between diseases and rare genetic variation? The gene genealogy describes the relationships between haplotypes sampled from the general population. Although ancestral tree-based methods, inspired by the gene genealogy concept, have been developed for finding associations with common genetic variants, here we ask whether gene genealogies can help in identifying genomic regions containing multiple rare causal variants.

Gene genealogies for genetic association mapping, with application to Crohn's disease.

A gene genealogy describes relationships among haplotypes sampled from a population. Knowledge of the gene genealogy for a set of haplotypes is useful for estimation of population genetic parameters and it also has potential application in finding disease-predisposing genetic variants. As the true gene genealogy is unknown, Markov chain Monte Carlo (MCMC) approaches have been used to sample genealogies conditional on data at multiple genetic markers.

Markov chain Monte Carlo sampling of gene genealogies conditional on unphased SNP genotype data.

The gene genealogy is a tree describing the ancestral relationships among genes sampled from unrelated individuals. Knowledge of the tree is useful for inference of population-genetic parameters and has potential application in gene-mapping. Markov chain Monte Carlo approaches that sample genealogies conditional on observed genetic data typically assume that haplotype data are observed even though commonly-used genotyping technologies provide only unphased genotype data.

Matrix metalloproteinase expression by human alveolar macrophages in relation to emphysema.

An abnormal increase in proteolytic enzymes is thought to play a key role in pulmonary emphysema. Alveolar macrophage proteolytic enzymes include cathepsin L, cathepsin S, matrix metalloproteinase 1, 9, and 12, and a number of studies have implicated these proteinases in the alveolar destruction that characterizes emphysema. The aim of this study was to investigate cathepsin L, cathepsin S, matrix metalloproteinase 1, 9, and 12 mRNA expression in alveolar macrophages isolated from patients with varying degrees of emphysema and to correlate their level of expression with measures of emphysema.

Contribution of alpha- and beta-defensins to lung function decline and infection in smokers: an association study.

Background: Alpha-defensins, which are major constituents of neutrophil azurophilic granules, and beta-defensins, which are expressed in airway epithelial cells, could contribute to the pathogenesis of chronic obstructive pulmonary disease by amplifying cigarette smoke-induced and infection-induced inflammatory reactions leading to lung injury. In Japanese and Chinese populations, two different beta-defensin-1 polymorphisms have been associated with chronic obstructive pulmonary disease phenotypes. We conducted population-based association studies to test whether alpha-defensin and beta-defensin polymorphisms influenced smokers' susceptibility to lung function decline and susceptibility to lower respiratory infection in two groups of white participants in the Lung Health Study (275 = fast decline in lung function and 304 = no decline in lung function).

A comparison of five methods for selecting tagging single-nucleotide polymorphisms.

Our goal was to compare methods for tagging single-nucleotide polymorphisms (tagSNPs) with respect to the power to detect disease association under differing haplotype-disease association models. We were also interested in the effect that SNP selection samples, consisting of either cases, controls, or a mixture, would have on power. We investigated five previously described algorithms for choosing tagSNPS: two that picked SNPs based on haplotype structure (Chapman-haplotypic and Stram), two that picked SNPs based on pair-wise allelic association (Chapman-allelic and Cousin), and one control method that chose equally spaced SNPs (Zhai).

Microarray genotyping resource to determine population stratification in genetic association studies of complex disease.

We have developed a robust microarray genotyping chip that will help advance studies in genetic epidemiology. In population-based genetic association studies of complex disease, there could be hidden genetic substructure in the study populations, resulting in false-positive associations. Such population stratification may confound efforts to identify true associations between genotype/haplotype and phenotype.