Calibrating the Performance of SNP Arrays for Whole-Genome Association Studies

To facilitate whole-genome association studies (WGAS), several high-density SNP genotyping arrays have been developed. Genetic coverage and statistical power are the primary benchmark metrics in evaluating the performance of SNP arrays. Ideally, such evaluations would be done on a SNP set and a cohort of individuals that are both independently sampled from the original SNPs and individuals used in developing the arrays. Without utilization of an independent test set, previous estimates of genetic coverage and statistical power may be subject to an overfitting bias. Additionally, the SNP arrays' statistical power in WGAS has not been systematically assessed on real traits. One robust setting for doing so is to evaluate statistical power on thousands of traits measured from a single set of individuals. In this study, 359 newly sampled Americans of European descent were genotyped using both Affymetrix 500K (Affx500K) and Illumina 650Y (Ilmn650K) SNP arrays. From these data, we were able to obtain estimates of genetic coverage, which are robust to overfitting, by constructing an independent test set from among these genotypes and individuals. Furthermore, we collected liver tissue RNA from the participants and profiled these samples on a comprehensive gene expression microarray. The RNA levels were used as a large-scale set of quantitative traits to calibrate the relative statistical power of the commercial arrays. Our genetic coverage estimates are lower than previous reports, providing evidence that previous estimates may be inflated due to overfitting. The Ilmn650K platform showed reasonable power (50% or greater) to detect SNPs associated with quantitative traits when the signal-to-noise ratio (SNR) is greater than or equal to 0.5 and the causal SNP's minor allele frequency (MAF) is greater than or equal to 20% (N = 359). In testing each of the more than 40,000 gene expression traits for association to each of the SNPs on the Ilmn650K and Affx500K arrays, we found that the Ilmn650K yielded 15% times more discoveries than the Affx500K at the same false discovery rate (FDR) level

Gene set analysis for longitudinal gene expression data

<p>Abstract</p> <p>Background</p> <p>Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. GSA performs statistical tests for independent microarray samples at the level of gene sets rather than individual genes. Nowadays, an increasing number of microarray studies are conducted to explore the dynamic changes of gene expression in a variety of species and biological scenarios. In these longitudinal studies, gene expression is repeatedly measured over time such that a GSA needs to take into account the within-gene correlations in addition to possible between-gene correlations.</p> <p>Results</p> <p>We provide a robust nonparametric approach to compare the expressions of longitudinally measured sets of genes under multiple treatments or experimental conditions. The limiting distributions of our statistics are derived when the number of genes goes to infinity while the number of replications can be small. When the number of genes in a gene set is small, we recommend permutation tests based on our nonparametric test statistics to achieve reliable type I error and better power while incorporating unknown correlations between and within-genes. Simulation results demonstrate that the proposed method has a greater power than other methods for various data distributions and heteroscedastic correlation structures. This method was used for an IL-2 stimulation study and significantly altered gene sets were identified.</p> <p>Conclusions</p> <p>The simulation study and the real data application showed that the proposed gene set analysis provides a promising tool for longitudinal microarray analysis. R scripts for simulating longitudinal data and calculating the nonparametric statistics are posted on the North Dakota INBRE website <url>http://ndinbre.org/programs/bioinformatics.php</url>. Raw microarray data is available in Gene Expression Omnibus (National Center for Biotechnology Information) with accession number GSE6085.</p

Statistical Power of Model Selection Strategies for Genome-Wide Association Studies

Genome-wide association studies (GWAS) aim to identify genetic variants related to diseases by examining the associations between phenotypes and hundreds of thousands of genotyped markers. Because many genes are potentially involved in common diseases and a large number of markers are analyzed, it is crucial to devise an effective strategy to identify truly associated variants that have individual and/or interactive effects, while controlling false positives at the desired level. Although a number of model selection methods have been proposed in the literature, including marginal search, exhaustive search, and forward search, their relative performance has only been evaluated through limited simulations due to the lack of an analytical approach to calculating the power of these methods. This article develops a novel statistical approach for power calculation, derives accurate formulas for the power of different model selection strategies, and then uses the formulas to evaluate and compare these strategies in genetic model spaces. In contrast to previous studies, our theoretical framework allows for random genotypes, correlations among test statistics, and a false-positive control based on GWAS practice. After the accuracy of our analytical results is validated through simulations, they are utilized to systematically evaluate and compare the performance of these strategies in a wide class of genetic models. For a specific genetic model, our results clearly reveal how different factors, such as effect size, allele frequency, and interaction, jointly affect the statistical power of each strategy. An example is provided for the application of our approach to empirical research. The statistical approach used in our derivations is general and can be employed to address the model selection problems in other random predictor settings. We have developed an R package markerSearchPower to implement our formulas, which can be downloaded from the Comprehensive R Archive Network (CRAN) or http://bioinformatics.med.yale.edu/group/

Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation

Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates

What "best practice" could be in Palliative Care: an analysis of statements on practice and ethics expressed by the main Health Organizations

<p>Abstract</p> <p>Background</p> <p>In palliative care it would be necessary to refer to a model. Nevertheless it seems that there are no official statements which state and describe that model. We carried out an analysis of the statements on practice and ethics of palliative care expressed by the main health organizations to show which dimensions of end-of-life care are taken into consideration.</p> <p>Methods</p> <p>The official documents by the most representative health organisations committed to the definition of policies and guidelines for palliative and end-of-life care had been considered. The documents were analysed through a framework of the components of end-of-life care derived from literature, which was composed of 4 main "areas" and of 12 "sub-areas".</p> <p>Results</p> <p>Overall, 34 organizations were identified, 7 international organisations, and 27 organisations operating on the national level in four different countries (Australia, Canada, UK and United States). Up to 56 documents were selected and analysed. Most of them (38) are position statements. Relevant quotations from the documents were presented by "areas" and "sub-areas". In general, the "sub-areas" of symptoms control as well as those referring to relational and social issues are more widely covered by the documents than the "sub-areas" related to "preparation" and to "existential condition". Indeed, the consistency of end-of-life choices with the patient's wishes, as well as completion and meaningfulness at the end of life is given only a minor relevance.</p> <p>Conclusions</p> <p>An integrated model of the best palliative care practice is generally lacking in the documents. It might be argued that the lack of a fixed and coherent model is due to the relevance of unavoidable context issues in palliative care, such as specific cultural settings, patient-centred variables, and family specificity. The implication is that palliative care staff have continuously to adapt their model of caring to the specific needs and values of each patient, more than applying a fixed, although maybe comprehensive, care model.</p

In Vivo Assessment of Cold Adaptation in Insect Larvae by Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy

Background Temperatures below the freezing point of water and the ensuing ice crystal formation pose serious challenges to cell structure and function. Consequently, species living in seasonally cold environments have evolved a multitude of strategies to reorganize their cellular architecture and metabolism, and the underlying mechanisms are crucial to our understanding of life. In multicellular organisms, and poikilotherm animals in particular, our knowledge about these processes is almost exclusively due to invasive studies, thereby limiting the range of conclusions that can be drawn about intact living systems. Methodology Given that non-destructive techniques like 1H Magnetic Resonance (MR) imaging and spectroscopy have proven useful for in vivo investigations of a wide range of biological systems, we aimed at evaluating their potential to observe cold adaptations in living insect larvae. Specifically, we chose two cold-hardy insect species that frequently serve as cryobiological model systems–the freeze-avoiding gall moth Epiblema scudderiana and the freeze-tolerant gall fly Eurosta solidaginis. Results In vivo MR images were acquired from autumn-collected larvae at temperatures between 0°C and about -70°C and at spatial resolutions down to 27 µm. These images revealed three-dimensional (3D) larval anatomy at a level of detail currently not in reach of other in vivo techniques. Furthermore, they allowed visualization of the 3D distribution of the remaining liquid water and of the endogenous cryoprotectants at subzero temperatures, and temperature-weighted images of these distributions could be derived. Finally, individual fat body cells and their nuclei could be identified in intact frozen Eurosta larvae. Conclusions These findings suggest that high resolution MR techniques provide for interesting methodological options in comparative cryobiological investigations, especially in vivo

Genetic Analysis of Human Traits In Vitro: Drug Response and Gene Expression in Lymphoblastoid Cell Lines

Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype–phenotype relationships in human cells, including searches for QTLs influencing levels of individual mRNAs and responses to drugs and radiation. In the course of attempting to map genes for drug response using 269 LCLs from the International HapMap Project, we evaluated the extent to which biological noise and non-genetic confounders contribute to trait variability in LCLs. While drug responses could be technically well measured on a given day, we observed significant day-to-day variability and substantial correlation to non-genetic confounders, such as baseline growth rates and metabolic state in culture. After correcting for these confounders, we were unable to detect any QTLs with genome-wide significance for drug response. A much higher proportion of variance in mRNA levels may be attributed to non-genetic factors (intra-individual variance—i.e., biological noise, levels of the EBV virus used to transform the cells, ATP levels) than to detectable eQTLs. Finally, in an attempt to improve power, we focused analysis on those genes that had both detectable eQTLs and correlation to drug response; we were unable to detect evidence that eQTL SNPs are convincingly associated with drug response in the model. While LCLs are a promising model for pharmacogenetic experiments, biological noise and in vitro artifacts may reduce power and have the potential to create spurious association due to confounding

Synchronized turbo apoptosis induced by cold-shock

In our research on the role of apoptosis in the pathogenesis of the autoimmune disease systemic lupus erythematosus (SLE), we aim to evaluate the effects of early and late apoptotic cells and blebs on antigen presenting cells. This requires the in vitro generation of sufficiently large and homogeneous populations of early and late apoptotic cells. Here, we present a quick method encountered by serendipity that results in highly reproducible synchronized homogeneous apoptotic cell populations. In brief, granulocytic 32Dcl3 cells are incubated on ice for 2 h and subsequently rewarmed at 37°C. After 30–90 min at 37°C more than 80–90% of the cells become early apoptotic (Annexin V positive/propidium iodide negative). After 24 h of rewarming at 37°C 98% of the cells were late apoptotic (secondary necrotic; Annexin V positive/propidium iodide positive). Cells already formed apoptotic blebs at their cell surface after approximately 20 min at 37°C. Inter-nucleosomal chromatin cleavage and caspase activation were other characteristics of this cold-shock-induced process of apoptosis. Consequently, apoptosis could be inhibited by a caspase inhibitor. Finally, SLE-derived anti-chromatin autoantibodies showed a high affinity for apoptotic blebs generated by cold-shock. Overall, cold-shock induced apoptosis is achieved without the addition of toxic compounds or antibodies, and quickly leads to synchronized homogeneous apoptotic cell populations, which can be applied for various research questions addressing apoptosis

Parallel molecular routes to cold adaptation in eight genera of New Zealand stick insects.

The acquisition of physiological strategies to tolerate novel thermal conditions allows organisms to exploit new environments. As a result, thermal tolerance is a key determinant of the global distribution of biodiversity, yet the constraints on its evolution are not well understood. Here we investigate parallel evolution of cold tolerance in New Zealand stick insects, an endemic radiation containing three montane-occurring species. Using a phylogeny constructed from 274 orthologous genes, we show that stick insects have independently colonized montane environments at least twice. We compare supercooling point and survival of internal ice formation among ten species from eight genera, and identify both freeze tolerance and freeze avoidance in separate montane lineages. Freeze tolerance is also verified in both lowland and montane populations of a single, geographically widespread, species. Transcriptome sequencing following cold shock identifies a set of structural cuticular genes that are both differentially regulated and under positive sequence selection in each species. However, while cuticular proteins in general are associated with cold shock across the phylogeny, the specific genes at play differ among species. Thus, while processes related to cuticular structure are consistently associated with adaptation for cold, this may not be the consequence of shared ancestral genetic constraints