A genome-wide screen for hyposmia susceptibility Loci

Olfactory dysfunction is an important public health problem in the United States, with approximately 14 million elderly Americans having chronic olfactory impairment. We performed a genome-wide linkage scan for loci influencing susceptibility to hyposmia in the Hutterites, a founder population of European ancestry. Using interviews regarding the olfactory medical history and psychophysical smell testing, we identified 25 individuals with severe hyposmia. Elimination of subjects with confounding conditions yielded 7 hyposmics for analysis. A 52-member pedigree including all affected individuals was constructed from the larger, >1623-member pedigree, and a genome-wide screen for loci influencing the trait of hyposmia using 1123 markers was performed. The most significant evidence for linkage with hyposmia extended over a 45 cM region on chromosome 4q (P = 0.0013). Although this signal meets the criteria for suggestive linkage only and will require replication, these results offer the strongest data to date on the effects of genetic variation on olfactory dysfunction.     

A genome-wide association study of direct gestation length in US Holstein and Italian Brown populations

Direct gestation length influences economically important traits in dairy cattle that are related to birth and peri-natal survival of the calf. The objective of this study was to identify single nucleotide polymorphisms (SNPs) that are significantly associated with direct gestation length through a genome-wide association study. Data used in the analysis included 7,308,194 cow gestation lengths from daughters of 4743 United States Holstein sires in the Cooperative Dairy DNA Repository population and 580,157 gestation lengths from 749 sires in the Italian Brown population. Association analysis included 36,768 and 35,082 SNPs spanning all autosomes for Holstein and Brown Swiss, respectively. Multiple shrinkage Bayesian was employed. Estimates of heritability for both populations were moderate, with values of 0.32 (±0.03) and 0.29 (±0.02) for Holstein and Brown Swiss, respectively. A panel of SNPs was identified, which included SNPs that have significant effects on direct gestation length, of which the strongest candidate region is located on chromosome 18. Two regions not previously linked to direct calving ease and calf survival were identified on chromosome 7 and 28, corresponding to regions that contain genes related to embryonic development and foetal development. SNPs were also identified in regions that have been previously mapped for calving difficulty and longevity. This study identifies target regions for the investigation of direct foetal effects, which are a significant factor in determining the ease of calving.     

A high-density screen for linkage in multiple sclerosis

To provide a definitive linkage map for multiple sclerosis, we have genotyped the Illumina BeadArray linkage mapping panel (version 4) in a data set of 730 multiplex families of Northern European descent. After the application of stringent quality thresholds, data from 4,506 markers in 2,692 individuals were included in the analysis. Multipoint nonparametric linkage analysis revealed highly significant linkage in the major histocompatibility complex (MHC) on chromosome 6p21 (maximum LOD score [MLS] 11.66) and suggestive linkage on chromosomes 17q23 (MLS 2.45) and 5q33 (MLS 2.18). This set of markers achieved a mean information extraction of 79.3% across the genome, with a Mendelian inconsistency rate of only 0.002%. Stratification based on carriage of the multiple sclerosis–associated DRB1*1501 allele failed to identify any other region of linkage with genomewide significance. However, ordered-subset analysis suggested that there may be an additional locus on chromosome 19p13 that acts independent of the main MHC locus. These data illustrate the substantial increase in power that can be achieved with use of the latest tools emerging from the Human Genome Project and indicate that future attempts to systematically identify susceptibility genes for multiple sclerosis will have to involve large sample sizes and an association-based methodology.     

A robust method for testing association in genome-wide association studies

In genetic association studies, due to the varying underlying genetic models, no single statistical test can be the most powerful test under all situations. Current studies show that if the underlying genetic models are known, trend-based tests, which outperform the classical Pearson χ2 test, can be constructed. However, when the underlying genetic models are unknown, the χ2 test is usually more robust than trend-based tests. In this paper, we propose a new association test based on a generalized genetic model, namely the generalized order-restricted relative risks model. Through a Monte Carlo simulation study, we show that the proposed association test is generally more powerful than the χ2 test, and more robust than those trend-based tests. The proposed methodologies are also illustrated by some real SNP datasets.     

A genome-wide screen for noncoding elements important in primate evolution

Background  

A major goal in the study of human evolution is to identify key genetic changes which occurred over the course of primate evolution. According to one school of thought, many such changes are likely to be found in noncoding sequence. An approach to identifying these involves comparing multiple genomes to identify conserved regions with an accelerated substitution rate in a particular lineage. Such acceleration could be the result of positive selection.     

A genome-wide shRNA screen for new OxPhos related genes

The mitochondrial oxidative phosphorylation (OxPhos) system produces most of the ATP required by the cell. The structural proteins of the OxPhos holoenzymes are well known, but important aspects of their biogenesis and regulation remain to be uncovered and a significant fraction of mitochondrial proteins have yet to be identified. We have used a high throughput, genome-wide RNA interference (RNAi) approach to identify new OxPhos-related genes. We transduced a mouse fibroblast cell line with a lentiviral-based shRNA-library, and screened the cell population for growth impairment in galactose-based medium, which requires an intact OxPhos system. Candidate genes were ranked according to their co-expression with known genes encoding OxPhos mitochondria-located proteins. For the top ranking candidates the cellular process in which they are involved was evaluated. Our results show that the use of genome-wide RNAi together with screening for deficient growth in galactose medium is a suitable approach to identifying OxPhos-related and cellular energy metabolism-related genes. Interestingly also ubiquitin-proteasome related genes were selected.     

A genome-wide RNAi screen reveals multiple regulators of caspase activation

Apoptosis is an evolutionally conserved cellular suicide mechanism that can be activated in response to a variety of stressful stimuli. Increasing evidence suggests that apoptotic regulation relies on specialized cell death signaling pathways and also integrates diverse signals from additional regulatory circuits, including those of cellular homeostasis. We present a genome-wide RNA interference screen to systematically identify regulators of apoptosis induced by DNA damage in Drosophila melanogaster cells. We identify 47 double- stranded RNA that target a functionally diverse set of genes, including several with a known function in promoting cell death. Further characterization uncovers 10 genes that influence caspase activation upon the removal of Drosophila inhibitor of apoptosis 1. This set includes the Drosophila initiator caspase Dronc and, surprisingly, several metabolic regulators, a candidate tumor suppressor, Charlatan, and an N-acetyltransferase, ARD1. Importantly, several of these genes show functional conservation in regulating apoptosis in mammalian cells. Our data suggest a previously unappreciated fundamental connection between various cellular processes and caspase-dependent cell death.     

A gene-centric approach to genome-wide association studies

Genic variants are more likely to alter gene function and affect disease risk than those that occur outside genes. Variants in genes, however, might not be sufficiently covered by the existing approaches to genome-wide association studies. Our analysis of the HapMap ENCODE data indicates that this concern is valid, and that an alternative approach that focuses on genic variants provides a more complete coverage of functionally important regions and a greater genotyping efficiency. We therefore argue that resources should be developed to make gene-centric genome-wide association studies feasible.     

A dynamic model for genome-wide association studies

Although genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data.     

A genome-wide association study of BMI in American Indians

Numerous studies have been done to understand genetic contributors to BMI, but only a limited number of studies have been done in nonwhite groups such as American Indians. A genome-wide association study (GWAS) for BMI was therefore performed in Pima Indians. BMI measurements from a longitudinal study of 1,120 Pima Indians and 454,194 single-nucleotide polymorphisms (SNPs) from the 1 million Affymetrix SNP panel were used (35% of SNPs were excluded due to minor allele frequency <0.05). Data included BMI measured at multiple examinations collected from 1965 to 2004, as well as the maximum BMI at one of these visits. General and within-family tests were performed using a maximum-likelihood based mixed model procedure. No SNP reached a genome-wide significance level (estimated at P < 4.94 × 10(-7)). For repeated measures analyses, the strongest associations for general and within-family tests mapped to two different regions on chromosome 6 (rs9342220 (P = 1.39 × 10(-6)) and rs7758764 (P = 2.51 × 10(-6)), respectively). For maximum BMI, the strongest association for the general tests mapped to chromosome 4 (rs17612333; P = 1.98 × 10(-6)) and to chromosome 3 (rs11127958; P = 1.53 × 10(-6)) for the within-family tests. Further analysis is important because only a few of these regions have been previously implicated in a GWAS and genetic susceptibility may differ by ethnicity.     

A genome-wide RNAi screen identifies regulators of cholesterol-modified hedgehog secretion in Drosophila

Hedgehog (Hh) proteins are secreted molecules that function as organizers in animal development. In addition to being palmitoylated, Hh is the only metazoan protein known to possess a covalently-linked cholesterol moiety. The absence of either modification severely disrupts the organization of numerous tissues during development. It is currently not known how lipid-modified Hh is secreted and released from producing cells. We have performed a genome-wide RNAi screen in Drosophila melanogaster cells to identify regulators of Hh secretion. We found that cholesterol-modified Hh secretion is strongly dependent on coat protein complex I (COPI) but not COPII vesicles, suggesting that cholesterol modification alters the movement of Hh through the early secretory pathway. We provide evidence that both proteolysis and cholesterol modification are necessary for the efficient trafficking of Hh through the ER and Golgi. Finally, we identified several putative regulators of protein secretion and demonstrate a role for some of these genes in Hh and Wingless (Wg) morphogen secretion in vivo. These data open new perspectives for studying how morphogen secretion is regulated, as well as provide insight into regulation of lipid-modified protein secretion.     

A genome-wide association study of female sexual dysfunction

Background

Female sexual dysfunction (FSD) is an important but controversial problem with serious negative impact on women’s quality of life. Data from twin studies have shown a genetic contribution to the development and maintenance of FSD.

Methodology/Principal Findings

We performed a genome-wide association study (GWAS) on 2.5 million single-nucleotide polymorphisms (SNPs) in 1,104 female twins (25–81 years of age) in a population-based register and phenotypic data on lifelong sexual functioning. Although none reached conventional genome-wide level of significance (10×-8), we found strongly suggestive associations with the phenotypic dimension of arousal (rs13202860, P = 1.2×10⁻⁷; rs1876525, P = 1.2×10⁻⁷; and rs13209281 P = 8.3×10⁻⁷) on chromosome 6, around 500kb upstream of the locus HTR1E (5-hydroxytryptamine receptor 1E) locus, related to the serotonin brain pathways. We could not replicate previously reported candidate SNPs associated with FSD in the DRD4, 5HT2A and IL-1B loci.

Conclusions/Significance

We report the first GWAS of FSD symptoms in humans. This has pointed to several “risk alleles” and the implication of the serotonin and GABA pathways. Ultimately, understanding key mechanisms via this research may lead to new FSD treatments and inform clinical practice and developments in psychiatric nosology.     

A genome-wide association study of osteochondritis dissecans in the Thoroughbred

Osteochondrosis is a developmental orthopaedic disease that occurs in horses, other livestock species, companion animal species, and humans. The principal aim of this study was to identify quantitative trait loci (QTL) associated with osteochondritis dissecans (OCD) in the Thoroughbred using a genome-wide association study. A secondary objective was to test the effect of previously identified QTL in the current population. Over 300 horses, classified as cases or controls according to clinical findings, were genotyped for the Illumina Equine SNP50 BeadChip. An animal model was first implemented in order to adjust each horse's phenotypic status for average relatedness among horses and other potentially confounding factors which were present in the data. The genome-wide association test was then conducted on the residuals from the animal model. A single SNP on chromosome 3 was found to be associated with OCD at a genome-wide level of significance, as determined by permutation. According to the current sequence annotation, the SNP is located in an intergenic region of the genome. The effects of 24 SNPs, representing QTL previously identified in a sample of Hanoverian Warmblood horses, were tested directly in the animal model. When fitted alongside the significant SNP on ECA3, two of these SNPs were found to be associated with OCD. Confirmation of the putative QTL identified on ECA3 requires validation in an independent sample. The results of this study suggest that a significant challenge faced by equine researchers is the generation of sufficiently large data sets to effectively study complex diseases such as osteochondrosis.     

Heritability in the genome-wide association era

Heritability, the fraction of phenotypic variation explained by genetic variation, has been estimated for many phenotypes in a range of populations, organisms, and time points. The recent development of efficient genotyping and sequencing technology has led researchers to attempt to identify the genetic variants responsible for the genetic component of phenotype directly via GWAS. The gap between the phenotypic variance explained by GWAS results and those estimated from classical heritability methods has been termed the "missing heritability problem". In this work, we examine modern methods for estimating heritability, which use the genotype and sequence data directly. We discuss them in the context of classical heritability methods, the missing heritability problem, and describe their implications for understanding the genetic architecture of complex phenotypes.     

Two-stage two-locus models in genome-wide association

Studies in model organisms suggest that epistasis may play an important role in the etiology of complex diseases and traits in humans. With the era of large-scale genome-wide association studies fast approaching, it is important to quantify whether it will be possible to detect interacting loci using realistic sample sizes in humans and to what extent undetected epistasis will adversely affect power to detect association when single-locus approaches are employed. We therefore investigated the power to detect association for an extensive range of two-locus quantitative trait models that incorporated varying degrees of epistasis. We compared the power to detect association using a single-locus model that ignored interaction effects, a full two-locus model that allowed for interactions, and, most important, two two-stage strategies whereby a subset of loci initially identified using single-locus tests were analyzed using the full two-locus model. Despite the penalty introduced by multiple testing, fitting the full two-locus model performed better than single-locus tests for many of the situations considered, particularly when compared with attempts to detect both individual loci. Using a two-stage strategy reduced the computational burden associated with performing an exhaustive two-locus search across the genome but was not as powerful as the exhaustive search when loci interacted. Two-stage approaches also increased the risk of missing interacting loci that contributed little effect at the margins. Based on our extensive simulations, our results suggest that an exhaustive search involving all pairwise combinations of markers across the genome might provide a useful complement to single-locus scans in identifying interacting loci that contribute to moderate proportions of the phenotypic variance.