Some like it hot... : the evolution and genetics of temperature dependent body size in Drosophila melanogaster

Body size is one of the most obvious and most important characteristic of any organism. A thorough understanding of how and why a certain individual obtains a specific body size, given its evolutionary history and ecological context, is a fundamental question in biology. One special case of variation in size is clinal variation: individuals of the same species indigenous to higher latitudes are on average larger than their conspecifics inhabiting regions at lower latitudes (closer to the equator). This pattern has a genetic basis, is very common in many animal species and represents a long-standing puzzle in evolutionary biology. Drosophila melanogaster populations from temperate and tropical regions were known to produce the clinal variation in body size, very likely as a result of adaptation to the different climates. Aim of this study was to understand the evolution of this genetic difference in average body size between populations adapted to low and high temperatures. Analyses of correlated life-history traits, interaction of selection pressures, biochemistry of resource allocation and global gene expression resulted in formulating the following scenario. We suggest that geographical variation of adult body size in Drosophila melanogaster is plausibly the result of thermal evolution of a genetic trade-off between adult size and larval survival. Because a cold environment seems to select for a large adult body and a warm environment seems to select for increased larval vigor to resist challenges to pre-adult survival, alternative resource allocation strategies have evolved. Cold adapted genotypes seem to invest glycogen reserves preferentially in growth while warm adapted genotypes seem to invest their glycogen reserves preferentially in larval survival. The physiological basis of these alternative strategies is plausibly variation in the utilization of glycogen induced by variation in glycogen processing enzyme activities. A large fraction of the genes found to be differentially expressed across genotypes with different body size are involved in cell growth and maintenance. This suggests that the actual molecular determinants of the divergence in cellular metabolism and body size might be effectors and regulators of cell growth and differentiation through variation in the activity of signal transduction pathways. Thus, the real difference between individuals from different geographical populations seems to be not a quantitative but a qualitative one. Warm and cold adapted genotypes are fundamentally different in their cellular metabolism and physiology. This underlying divergence allows them to exhibit alternative resource allocation strategies that result in adaptive life-historie

Genome-Wide Prediction of Functional Gene-Gene Interactions Inferred from Patterns of Genetic Differentiation in Mice and Men.

The human genome encodes a limited number of genes yet contributes to individual differences in a vast array of heritable traits. A possible explanation for the capacity our genome to generate this virtually unlimited range of phenotypic variation in complex traits is to assume functional interactions between genes. Therefore we searched two mammalian genomes to identify potential epistatic interactions by looking for co-adapted genes marked by excess two-locus genetic differentiation between populations/lineages using publicly available SNP genotype data. The practical motivation for this effort is to reduce the number of pair-wise tests that need to be performed in genome-wide association studies aimed at detecting GxG interactions, by focusing on pairs predicted to be more likely to jointly affect variation in complex traits. Hence, this approach generates a list of candidate interactions that can be empirically tested. In both the mouse and human data we observed two-locus genetic differentiation in excess of what can be expected from chance alone based on simulations. In an attempt to validate our hypothesis that pairs of genes showing excess genetic divergence represent potential functional interactions, we selected a small set of gene combinations postulated to be interacting based on our analyses and looked for a combined effect of the selected genes on variation in complex traits in both mice and man. In both cases the individual effect of the genes were not significant, instead we observed marginally significant interaction effects. These results show that genome wide searches for gene-gene interactions based on population genetic data are feasible and can generate interesting candidate gene pairs to be further tested for their contribution to phenotypic variation in complex traits

PCLO rs2522833 impacts HPA system activity in healthy young adults

Recent genetic studies showed evidence for a role of the single-nucleotide polymorphism rs2522833 within the PCLO gene in the etiology of major depression, and rs2522833 has been shown to modulate hypothalamic pituitary adrenal (HPA) axis activity during antidepressant treatment. Monoaminergic modulation of the HPA system may be one possible pathomechanism by which PCLO exerts its effect on depression. In the present study, we investigated the effect of rs2522833 on the cortisol awakening response (CAR) in healthy young adults. A total of 66 healthy volunteers from the community (36 men and 30 women) aged 18–25 years without individual or family history of affective disorders and schizophrenia collected saliva cortisol samples at 0, 30, 45 and 60 min after awakening on two consecutive working days. We identified a blunted CAR (AUCinc) in rs2522833 risk-allele (C) carriers, possibly indicating exhausted regulatory mechanisms underlying the HPA system. We also identified higher neuroticism scores in rs2522833 risk-allele carriers but no phenotypic correlation between the CAR (AUCinc) and neuroticism. These findings suggest that the rs2522833 risk variant might increase vulnerability to depression both by physiological and behavioral pathways, which appear, however, not to be substantially overlapped. Replication with larger samples is warranted

Resequencing three candidate genes for major depressive disorder in a Dutch cohort

Major depressive disorder (MDD) is a psychiatric disorder, characterized by periods of low mood of more than two weeks, loss of interest in normally enjoyable activities and behavioral changes. MDD is a complex disorder and does not have a single genetic cause. In 2009 a genome wide association study (GWAS) was performed on the Dutch GAIN-MDD cohort. Many of the top signals of this GWAS mapped to a region spanning the gene PCLO, and the non-synonymous coding single nucleotide polymorphism (SNP) rs2522833 in the PCLO gene became genome wide significant after post-hoc analysis. We performed resequencing of PCLO, GRM7, and SLC6A4 in 50 control samples from the GAIN-MDD cohort, to detect new genomic variants. Subsequently, we genotyped these variants in the entire GAIN-MDD cohort and performed association analysis to investigate if rs2522833 is the causal variant or simply in linkage disequilibrium with a more associated variant. GRM7 and SLC6A4 are both candidate genes for MDD from literature. We aimed to gather more evidence that rs2522833 is indeed the causal variant in the GAIN-MDD cohort or to find a previously undetected common variant in either PCLO, GRM7, or SLC6A4 with a higher association in this cohort. After next generation sequencing and association analysis we excluded the possibility of an undetected common variant to be more associated. For neither PCLO nor GRM7 we found a more associated variant. For SLC6A4, we found a new SNP that showed a lower P-value (P = 0.07) than in the GAIN-MDD GWAS (P = 0.09). However, no evidence for genome-wide significance was found. Although we did not take into account rare variants, we conclude that our results provide further support for the hypothesis that the non-synonymous coding SNP rs2522833 in the PCLO gene is indeed likely to be the causal variant in the GAIN-MDD cohort

Genotype-by-Environment Interactions and Adaptation to Local Temperature Affect Immunity and Fecundity in Drosophila melanogaster

Natural populations of most organisms harbor substantial genetic variation for resistance to infection. The continued existence of such variation is unexpected under simple evolutionary models that either posit direct and continuous natural selection on the immune system or an evolved life history “balance” between immunity and other fitness traits in a constant environment. However, both local adaptation to heterogeneous environments and genotype-by-environment interactions can maintain genetic variation in a species. In this study, we test Drosophila melanogaster genotypes sampled from tropical Africa, temperate northeastern North America, and semi-tropical southeastern North America for resistance to bacterial infection and fecundity at three different environmental temperatures. Environmental temperature had absolute effects on all traits, but there were also marked genotype-by-environment interactions that may limit the global efficiency of natural selection on both traits. African flies performed more poorly than North American flies in both immunity and fecundity at the lowest temperature, but not at the higher temperatures, suggesting that the African population is maladapted to low temperature. In contrast, there was no evidence for clinal variation driven by thermal adaptation within North America for either trait. Resistance to infection and reproductive success were generally uncorrelated across genotypes, so this study finds no evidence for a fitness tradeoff between immunity and fecundity under the conditions tested. Both local adaptation to geographically heterogeneous environments and genotype-by-environment interactions may explain the persistence of genetic variation for resistance to infection in natural populations

Comprehensive mRNA Expression Profiling Distinguishes Tauopathies and Identifies Shared Molecular Pathways

Background: Understanding the aetiologies of neurodegenerative diseases such as Alzheimer's disease (AD), Pick's disease (PiD), Progressive Supranuclear Palsy (PSP) and Frontotemporal dementia (FTD) is often hampered by the considerable clinical and molecular overlap between these diseases and normal ageing. The development of high throughput genomic technologies such as microarrays provide a new molecular tool to gain insight in the complexity and relationships between diseases, as they provide data on the simultaneous activity of multiple genes, gene networks and cellular pathways. Methodology/Principal Findings: We have constructed genome wide expression profiles from snap frozen post-mortem tissue from the medial temporal lobe of patients with four neurodegenerative disorders (5 AD, 5 PSP, 5 PiD and 5 FTD patients) and 5 control subjects. All patients were matched for age, gender, ApoE-e and MAPT (tau) haplotype. From all groups a total of 790 probes were shown to be differently expressed when compared to control individuals. The results from these experiments were then used to investigate the correlations between clinical, pathological and molecular findings. From the 790 identified probes we extracted a gene set of 166 probes whose expression could discriminate between these disorders and normal ageing. Conclusions/Significance: From genome wide expression profiles we extracted a gene set of 166 probes whose expression could discriminate between neurological disorders and normal ageing. This gene set can be further developed into an accurate microarray-based classification test. Furthermore, from this dataset we extracted a disease specific set of genes and identified two aging related transcription factors (FOXO1A and FOXO3A) as possible drug targets related to neurodegenerative disease

Determining the genome-wide kinship coefficient seems unhelpful in distinguishing consanguineous couples with a high versus low risk for adverse reproductive outcome

Background: Offspring of consanguineous couples are at increased risk of congenital disorders. The risk increases as parents are more closely related. Individuals that have the same degree of relatedness according to their pedigree, show variable genomic kinship coefficients. To investigate whether we can differentiate between couples with high- and low risk for offspring with congenital disorders, we have compared the genomic kinship coefficient of consanguineous parents with a child affected with an autosomal recessive disorder with that of consanguineous parents with only healthy children, corrected for the degree of pedigree relatedness. Methods: 151 consanguineous couples (73 cases and 78 controls) from 10 different ethnic backgrounds were genotyped on the Affymetrix platform and passed quality control checks. After pruning SNPs in linkage disequilibrium, 57,358 SNPs remained. Kinship coefficients were calculated using three different toolsets: PLINK, King and IBDelphi, yielding five different estimates (IBDelphi, PLINK (all), PLINK (by population), King robust (all) and King homo (by population)). We performed a one-sided Mann Whitney test to investigate whether the median relative difference regarding observed and expected kinship coefficients is bigger for cases than for controls. Furthermore, we fitted a mixed effects linear model to correct for a possible population effect. Results: Although the estimated degrees of genomic relatedness with the different toolsets show substantial variability, correlation measures between the different estimators demonstrated moderate to strong correlations. Controls have higher point estimates for genomic kinship coefficients. The one-sided Mann Whitney test did not show any evidence for a higher median relative difference for cases compared to controls. Neither did the regression analysis exhibit a positive association between case–control status and genomic kinship coefficient. Conclusions: In this case–control setting, in which we compared consanguineous couples corrected for degree of pedigree relatedness, a higher degree of genomic relatedness was not significantly associated with a higher likelihood of having an affected child. Further translational research should focus on which parts of the genome and which pathogenic mutations couples are sharing. Looking at relatedness coefficients by determining genome-wide SNPs does not seem to be an effective measure for prospective risk assessment in consanguineous parents

On the Use of Variance per Genotype as a Tool to Identify Quantitative Trait Interaction Effects: A Report from the Women's Genome Health Study

Testing for genetic effects on mean values of a quantitative trait has been a very successful strategy. However, most studies to date have not explored genetic effects on the variance of quantitative traits as a relevant consequence of genetic variation. In this report, we demonstrate that, under plausible scenarios of genetic interaction, the variance of a quantitative trait is expected to differ among the three possible genotypes of a biallelic SNP. Leveraging this observation with Levene's test of equality of variance, we propose a novel method to prioritize SNPs for subsequent gene–gene and gene–environment testing. This method has the advantageous characteristic that the interacting covariate need not be known or measured for a SNP to be prioritized. Using simulations, we show that this method has increased power over exhaustive search under certain conditions. We further investigate the utility of variance per genotype by examining data from the Women's Genome Health Study. Using this dataset, we identify new interactions between the LEPR SNP rs12753193 and body mass index in the prediction of C-reactive protein levels, between the ICAM1 SNP rs1799969 and smoking in the prediction of soluble ICAM-1 levels, and between the PNPLA3 SNP rs738409 and body mass index in the prediction of soluble ICAM-1 levels. These results demonstrate the utility of our approach and provide novel genetic insight into the relationship among obesity, smoking, and inflammation

A Fine-Mapping Study of 7 Top Scoring Genes from a GWAS for Major Depressive Disorder

Major depressive disorder (MDD) is a psychiatric disorder that is characterized -amongst others- by persistent depressed mood, loss of interest and pleasure and psychomotor retardation. Environmental circumstances have proven to influence the aetiology of the disease, but MDD also has an estimated 40% heritability, probably with a polygenic background. In 2009, a genome wide association study (GWAS) was performed on the Dutch GAIN-MDD cohort. A non-synonymous coding single nucleotide polymorphism (SNP) rs2522833 in the PCLO gene became only nominally significant after post-hoc analysis with an Australian cohort which used similar ascertainment. The absence of genome-wide significance may be caused by low SNP coverage of genes. To increase SNP coverage to 100% for common variants (m.a.f.>0.1, r2>0.8), we selected seven genes from the GAIN-MDD GWAS: PCLO, GZMK, ANPEP, AFAP1L1, ST3GAL6, FGF14 and PTK2B. We genotyped 349 SNPs and obtained the lowest P-value for rs2715147 in PCLO at P = 6.8E−7. We imputed, filling in missing genotypes, after which rs2715147 and rs2715148 showed the lowest P-value at P = 1.2E−6. When we created a haplotype of these SNPs together with the non-synonymous coding SNP rs2522833, the P-value decreased to P = 9.9E−7 but was not genome wide significant. Although our study did not identify a more strongly associated variant, the results for PCLO suggest that the causal variant is in high LD with rs2715147, rs2715148 and rs2522833