ObjectivesGenome‐wide association studies (GWAS) have become increasingly popular to identify associations between single nucleotide polymorphisms (SNPs) and phenotypic traits. The GWAS method is commonly applied within the social sciences. However, statistical analyses will need to be carefully conducted and the use of dedicated genetics software will be required. This tutorial aims to provide a guideline for conducting genetic analyses.MethodsWe discuss and explain key concepts and illustrate how to conduct GWAS using example scripts provided through GitHub (https://github.com/MareesAT/GWA_tutorial/ ).In addition to the illustration of standard GWAS, we will also show how to apply polygenic risk score (PRS) analysis. PRS does not aim to identify individual SNPs but aggregates information from SNPs across the genome in order to provide individual‐level scores of genetic risk.ResultsThe simulated data and scripts that will be illustrated in the current tutorial provide hands‐on practice with genetic analyses. The scripts are based on PLINK, PRSice, and R, which are commonly used, freely available software tools that are accessible for novice users.ConclusionsBy providing theoretical background and hands‐on experience, we aim to make GWAS more accessible to researchers without formal training in the field.
The adsorption of nucleic acids to mineral matrixes can result in low extraction yields and negatively influences molecular microbial ecology studies, in particular for low-biomass environments on Earth and Mars. We determined the recovery of nucleic acids from a range of minerals relevant to Earth and Mars. Clay minerals, but also other silicates and nonsilicates, showed very low recovery (< 1%). Consequently, optimization of DNA extraction was directed towards clays. The high temperatures and acidic conditions used in some methods to dissolve mineral matrices proved to destruct DNA. The most efficient method comprised a high phosphate solution (P/EtOH; 1 M phosphate, 15% ethanol buffer at pH 8) introduced at the cell-lysing step in DNA extraction, to promote chemical competition with DNA for adsorption sites. This solution increased DNA yield from clay samples spiked with known quantities of cells up to nearly 100-fold. DNA recovery was also enhanced from several mineral samples retrieved from an aquifer, while maintaining reproducible DGGE profiles. DGGE profiles were obtained for a clay sample for which no profile could be generated with the standard DNA isolation protocol. Mineralogy influenced microbial community composition. The method also proved suitable for the recovery of low molecular weight DNA (< 1.5 kb).
Humankind's innate curiosity makes us wonder whether life is or was present on other planetary bodies such as Mars. The EuroGeoMars 2009 campaign was organized at the Mars Desert Research Station (MDRS) to perform multidisciplinary astrobiology research. MDRS in southeast Utah is situated in a cold arid desert with mineralogy and erosion processes comparable to those on Mars. Insight into the microbial community composition of this terrestrial Mars analogue provides essential information for the search for life on Mars: including sampling and life detection methodology optimization and what kind of organisms to expect. Soil samples were collected from different locations. Culture-independent molecular analyses directed at ribosomal RNA genes revealed the presence of all three domains of life (Archaea, Bacteria and Eukarya), but these were not detected in all samples. Spiking experiments revealed that this appears to relate to low DNA recovery, due to adsorption or degradation. Bacteria were most frequently detected and showed high alpha-and beta-diversity. Members of the Actinobacteria, Proteobacteria, Bacteroidetes and Gemmatimonadetes phyla were found in the majority of samples. Archaea alpha-and beta-diversity was very low. For Eukarya, a diverse range of organisms was identified, such as fungi, green algae and several phyla of Protozoa. Phylogenetic analysis revealed an extraordinary variety of putative extremophiles, mainly Bacteria but also Archaea and Eukarya. These comprised radioresistant, endolithic, chasmolithic, xerophilic, hypolithic, thermophilic, thermoacidophilic, psychrophilic, halophilic, haloalkaliphilic and alkaliphilic micro-organisms. Overall, our data revealed large difference in occurrence and diversity over short distances, indicating the need for high-sampling frequency at similar sites. DNA extraction methods need to be optimized to improve extraction efficiencies.
Background. Frequency and quantity of alcohol consumption are metrics commonly used to measure alcohol consumption behaviors. Epidemiological studies indicate that these alcohol consumption measures are differentially associated with (mental) health outcomes and socioeconomic status (SES). The current study aims to elucidate to what extent genetic risk factors are shared between frequency and quantity of alcohol consumption, and how these alcohol consumption measures are genetically associated with four broad phenotypic categories: (i) SES; (ii) substance use disorders; (iii) other psychiatric disorders; and (iv) psychological/personality traits.Methods. Genome-Wide Association analyses were conducted to test genetic associations with alcohol consumption frequency (N = 438 308) and alcohol consumption quantity (N = 307 098 regular alcohol drinkers) within UK Biobank. For the other phenotypes, we used genome-wide association studies summary statistics. Genetic correlations (rg) between the alcohol measures and other phenotypes were estimated using LD score regression.Results. We found a substantial genetic correlation between the frequency and quantity of alcohol consumption (rg = 0.52). Nevertheless, both measures consistently showed opposite genetic correlations with SES traits, and many substance use, psychiatric, and psychological/personality traits. High alcohol consumption frequency was genetically associated with high SES and low risk of substance use disorders and other psychiatric disorders, whereas the opposite applies for high alcohol consumption quantity.Conclusions. Although the frequency and quantity of alcohol consumption show substantial genetic overlap, they consistently show opposite patterns of genetic associations with SES-related phenotypes. Future studies should carefully consider the potential influence of SES on the shared genetic etiology between alcohol and adverse (mental) health outcomes.
BackgroundDepression is a clinically heterogeneous disorder. Previous large-scale genetic studies of depression have explored genetic risk factors of depression case–control status or aggregated sums of depressive symptoms, ignoring possible clinical or genetic heterogeneity.MethodsWe analyse data from 148 752 subjects of white British ancestry in the UK Biobank who completed nine items of a self-rated measure of current depressive symptoms: the Patient Health Questionnaire (PHQ-9). Genome-Wide Association analyses were conducted for nine symptoms and two composite measures. LD Score Regression was used to calculate SNP-based heritability (h2 SNP) and genetic correlations (rg) across symptoms and to investigate genetic correlations with 25 external phenotypes. Genomic structural equation modelling was used to test the genetic factor structure across the nine symptoms.ResultsWe identified nine genome-wide significant genomic loci (8 novel), with no overlap in loci across symptoms. h2 SNP ranged from 6% (concentration problems) to 9% (appetite changes). Genetic correlations ranged from 0.54 to 0.96 (all p < 1.39 × 10−3) with 30 of 36 correlations being significantly smaller than one. A two-factor model provided the best fit to the genetic covariance matrix, with factors representing ‘psychological’ and ‘somatic’ symptoms. The genetic correlations with external phenotypes showed large variation across the nine symptoms.ConclusionsPatterns of SNP associations and genetic correlations differ across the nine symptoms, suggesting that current depressive symptoms are genetically heterogeneous. Our study highlights the value of symptom-level analyses in understanding the genetic architecture of a psychiatric trait. Future studies should investigate whether genetic heterogeneity is recapitulated in clinical symptoms of major depression.
Epidemiological studies show high comorbidity between different mental health problems, indicating that individuals with a diagnosis of one disorder are more likely to develop other mental health problems. Genetic studies reveal substantial sharing of genetic factors across mental health traits. However, mental health is also genetically correlated with socio-economic status (SES) and it is therefore important to investigate and disentangle the genetic relationship between mental health and SES. We used summary statistics from large genome-wide association studies (average N~160,000) to estimate the genetic overlap across nine psychiatric disorders and seven substance use traits and explored the genetic influence of three different indicators of SES. Using Genomic Structural Equation Modelling, we show significant changes in patterns of genetic correlations after partialling out SES-associated genetic variation. Our approach allows the separation of disease-specific genetic variation and genetic variation shared with SES, thereby improving our understanding of the genetic architecture of mental health.
Low-frequency and rare exonic variants with large effects do not play a major role in alcohol and tobacco use, nor does the aggregate effect of ExomeChip variants. However, our results confirmed the role of the CHRNA5-CHRNA3-CHRNB4 cluster of nicotinic acetylcholine receptor subunit genes in tobacco use.
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