Complex Variation in Measures of General Intelligence and Cognitive Change

Combining information from multiple SNPs may capture a greater amount of genetic variation than from the sum of individual SNP effects and help identifying missing heritability. Regions may capture variation from multiple common variants of small effect, multiple rare variants or a combination of both. We describe regional heritability mapping of human cognition. Measures of crystallised (g_c) and fluid intelligence (g_f) in late adulthood (64–79 years) were available for 1806 individuals genotyped for 549,692 autosomal single nucleotide polymorphisms (SNPs). The same individuals were tested at age 11, enabling us the rare opportunity to measure cognitive change across most of their lifespan. 547,750 SNPs ranked by position are divided into 10, 908 overlapping regions of 101 SNPs to estimate the genetic variance each region explains, an approach that resembles classical linkage methods. We also estimate the genetic variation explained by individual autosomes and by SNPs within genes. Empirical significance thresholds are estimated separately for each trait from whole genome scans of 500 permutated data sets. The 5% significance threshold for the likelihood ratio test of a single region ranged from 17–17.5 for the three traits. This is the equivalent to nominal significance under the expectation of a chi-squared distribution (between 1df and 0) of P<1.44×10⁻⁵. These thresholds indicate that the distribution of the likelihood ratio test from this type of variance component analysis should be estimated empirically. Furthermore, we show that estimates of variation explained by these regions can be grossly overestimated. After applying permutation thresholds, a region for g_f on chromosome 5 spanning the PRRC1 gene is significant at a genome-wide 10% empirical threshold. Analysis of gene methylation on the temporal cortex provides support for the association of PRRC1 and fluid intelligence (P = 0.004), and provides a prime candidate gene for high throughput sequencing of these uniquely informative cohorts.     

Integrating genetic and network analysis to characterize genes related to mouse weight

Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight–related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.     

The Principles of Data Formalization for Building Biological Model of Shoot Development in Flowering Plants

Shoot system of a plant can be divided into elementary molecules composed of phyllome, internode, and meristem of the lateral bud. The capacity of plants for open growth is manifested as multiple reproductions of the modules. These main principles of plant structural organization can be used to formalize and integrate the data from various disciplines studying shoot development—genetics of development, morphology, etc. At the example of a model species Arabidopsis thaliana we show that the data on genetic control of shoot development can be considered in terms of rearrangement of individual modules. Several variants of the module structural reorganization are allowed: reduction or transformation of phyllome, change in the internode length, and triggering active/inactive status of the lateral shoot meristem. Each variant of module structure corresponds to specific pattern of genes activity. Such integration of the data on genetic and structural aspects of morphogenesis can form a basis for mathematical modeling of plant development.     

Variable coloration is associated with dampened population fluctuations in noctuid moths

Theory and recent reviews state that greater genetic and phenotypic variation should be beneficial for population abundance and stability. Experimental evaluations of this prediction are rare, of short duration and conducted under controlled environmental settings. The question whether greater diversity in functionally important traits stabilizes populations under more complex ecological conditions in the wild has not been systematically evaluated. Moths are mainly nocturnal, with a large variation in colour patterns among species, and constitute an important food source for many types of organisms. Here, we report the results of a long-term (2003–2013) monitoring study of 115 100 noctuid moths from 246 species. Analysis of time-series data provide rare evidence that species with higher levels of inter-individual variation in colour pattern have higher average abundances and undergo smaller between-year fluctuations compared with species having less variable colour patterns. The signature of interspecific temporal synchronization of abundance fluctuations was weak, suggesting that the dynamics were driven by species-specific biotic interactions rather than by some common, density-independent factor(s). We conclude that individual variation in colour patterns dampens population abundance fluctuations, and suggest that this may partly reflect that colour pattern polymorphism provides protection from visually oriented predators and parasitoids.     

Influence of Genetic Variants in Type I Interferon Genes on Melanoma Survival and Therapy

Melanoma is an immunogenic tumor; however, the efficacy of immune-therapy shows large inter-individual variation with possible influence of background genetic variation. In this study we report the influence of genetic polymorphisms in the type I interferon gene cluster on chromosome 9p22 on melanoma survival. We genotyped 625 melanoma patients recruited in an oncology center in Germany for 44 polymorphisms located on chromosome 9p22 that were informative for 299 polymorphisms and spanned 15 type I interferon genes. Our results showed associations between time to metastasis/survival and two linked (r² = 0.76) polymorphisms, rs10964859 (C>G) and rs10964862 (C>A). The rs10964859 polymorphism was located at 3′UTR and rs10964862 was 9.40 Kb towards 5′UTR of IFNW1 gene. The carriers of the variant alleles of the rs10964859 and rs10964862 polymorphisms were associated with a reduced disease-free survival. The validation of data in an independent group of 710 patients from Spain showed that the direction of the effect was similar. Stratification based on therapy showed that the adverse effect on metastasis development was statistically significant in the patients from Spain who did not receive any treatment and were homozygous for variant allele of rs10964862 (HR = 2.52, 95% CI 1.07–5.90; P = 0.03). Patients homozygous for rs10964859 (HR = 2.01, 95% CI 1.17–3.44; P = 0.01) and rs10964862 (HR 1.84, 95%CI 1.03–3.27, P = 0.04) were associated to increased risk of death following metastasis. GTCGACAA haplotype, found in 8.8% of the patients, was associated with an increased risk of death (HR 1.94, 95%CI 1.16–3.26, P = 0.01). In conclusion, our results identified genetic variants in interferon genes that influence melanoma progression and survival with modulation of effect due to treatment status.     

Population Analysis of Large Copy Number Variants and Hotspots of Human Genetic Disease

Copy number variants (CNVs) contribute to human genetic and phenotypic diversity. However, the distribution of larger CNVs in the general population remains largely unexplored. We identify large variants in ~2500 individuals by using Illumina SNP data, with an emphasis on “hotspots” prone to recurrent mutations. We find variants larger than 500 kb in 5%–10% of individuals and variants greater than 1 Mb in 1%–2%. In contrast to previous studies, we find limited evidence for stratification of CNVs in geographically distinct human populations. Importantly, our sample size permits a robust distinction between truly rare and polymorphic but low-frequency copy number variation. We find that a significant fraction of individual CNVs larger than 100 kb are rare and that both gene density and size are strongly anticorrelated with allele frequency. Thus, although large CNVs commonly exist in normal individuals, which suggests that size alone can not be used as a predictor of pathogenicity, such variation is generally deleterious. Considering these observations, we combine our data with published CNVs from more than 12,000 individuals contrasting control and neurological disease collections. This analysis identifies known disease loci and highlights additional CNVs (e.g., 3q29, 16p12, and 15q25.2) for further investigation. This study provides one of the first analyses of large, rare (0.1%–1%) CNVs in the general population, with insights relevant to future analyses of genetic disease.     

Disease-driven detection of differential inherited SNP modules from SNP network

Detection of the synergetic effects between variants, such as single-nucleotide polymorphisms (SNPs), is crucial for understanding the genetic characters of complex diseases. Here, we proposed a two-step approach to detect differentially inherited SNP modules (synergetic SNP units) from a SNP network. First, SNP-SNP interactions are identified based on prior biological knowledge, such as their adjacency on the chromosome or degree of relatedness between the functional relationships of their genes. These interactions form SNP networks. Second, disease-risk SNP modules (or sub-networks) are prioritised by their differentially inherited properties in IBD (Identity by Descent) profiles of affected and unaffected sibpairs. The search process is driven by the disease information and follows the structure of a SNP network. Simulation studies have indicated that this approach achieves high accuracy and a low false-positive rate in the identification of known disease-susceptible SNPs. Applying this method to an alcoholism dataset, we found that flexible patterns of susceptible SNP combinations do play a role in complex diseases, and some known genes were detected through these risk SNP modules. One example is GRM7, a known alcoholism gene successfully detected by a SNP module comprised of two SNPs, but neither of the two SNPs was significantly associated with the disease in single-locus analysis. These identified genes are also enriched in some pathways associated with alcoholism, including the calcium signalling pathway, axon guidance and neuroactive ligand-receptor interaction. The integration of network biology and genetic analysis provides putative functional bridges between genetic variants and candidate genes or pathways, thereby providing new insight into the aetiology of complex diseases.     

A comparative study on genetic effects of artificial and natural habitat fragmentation on Loropetalum chinense (Hamamelidaceae) in Southeast China

Elucidating the demographic and landscape features that determine the genetic effects of habitat fragmentation has become fundamental to research in conservation and evolutionary biology. Land-bridge islands provide ideal study areas for investigating the genetic effects of habitat fragmentation at different temporal and spatial scales. In this context, we compared patterns of nuclear microsatellite variation between insular populations of a shrub of evergreen broad-leaved forest, Loropetalum chinense, from the artificially created Thousand-Island Lake (TIL) and the Holocene-dated Zhoushan Archipelago of Southeast China. Populations from the TIL region harboured higher levels of genetic diversity than those from the Zhoushan Archipelago, but these differences were not significant. There was no correlation between genetic diversity and most island features, excepting a negative effect of mainland–island distance on allelic richness and expected heterozygosity in the Zhoushan Archipelago. In general, levels of gene flow among island populations were moderate to high, and tests of alternative models of population history strongly favoured a gene flow-drift model over a pure drift model in each region. In sum, our results showed no obvious genetic effects of habitat fragmentation due to recent (artificial) or past (natural) island formation. Rather, they highlight the importance of gene flow (most likely via seed) in maintaining genetic variation and preventing inter-population differentiation in the face of habitat ‘insularization'' at different temporal and spatial scales.     

Hypertension and Genetic Variation in Endothelial-Specific Genes

Genome-wide association (GWA) studies usually detect common genetic variants with low-to-medium effect sizes. Many contributing variants are not revealed, since they fail to reach significance after strong correction for multiple comparisons. The WTCCC study for hypertension, for example, failed to identify genome-wide significant associations. We hypothesized that genetic variation in genes expressed specifically in the endothelium may be important for hypertension development. Results from the WTCCC study were combined with previously published gene expression data from mice to specifically investigate SNPs located within endothelial-specific genes, bypassing the requirement for genome-wide significance. Six SNPs from the WTCCC study were selected for independent replication in 5205 hypertensive patients and 5320 population-based controls, and successively in a cohort of 16537 individuals. A common variant (rs10860812) in the DRAM (damage-regulated autophagy modulator) locus showed association with hypertension (P = 0.008) in the replication study. The minor allele (A) had a protective effect (OR = 0.93; 95% CI 0.88–0.98 per A-allele), which replicates the association in the WTCCC GWA study. However, a second follow-up, in the larger cohort, failed to reveal an association with blood pressure. We further tested the endothelial-specific genes for co-localization with a panel of newly discovered SNPs from large meta-GWAS on hypertension or blood pressure. There was no significant overlap between those genes and hypertension or blood pressure loci. The result does not support the hypothesis that genetic variation in genes expressed in endothelium plays an important role for hypertension development. Moreover, the discordant association of rs10860812 with blood pressure in the case control study versus the larger Malmö Preventive Project–study highlights the importance of rigorous replication in multiple large independent studies.     

TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies

To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype–phenotype models, show that TATES''s false positive rate is correct, and that TATES''s statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests based on composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype–phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor.     

Genetic Variation in the Human Brain Dopamine System Influences Motor Learning and Its Modulation by L-Dopa

Dopamine is important to learning and plasticity. Dopaminergic drugs are the focus of many therapies targeting the motor system, where high inter-individual differences in response are common. The current study examined the hypothesis that genetic variation in the dopamine system is associated with significant differences in motor learning, brain plasticity, and the effects of the dopamine precursor L-Dopa. Skilled motor learning and motor cortex plasticity were assessed using a randomized, double-blind, placebo-controlled, crossover design in 50 healthy adults during two study weeks, one with placebo and one with L-Dopa. The influence of five polymorphisms with established effects on dopamine neurotransmission was summed using a gene score, with higher scores corresponding to higher dopaminergic neurotransmission. Secondary hypotheses examined each polymorphism individually. While training on placebo, higher gene scores were associated with greater motor learning (p = .03). The effect of L-Dopa on learning varied with the gene score (gene score*drug interaction, p = .008): participants with lower gene scores, and thus lower endogenous dopaminergic neurotransmission, showed the largest learning improvement with L-Dopa relative to placebo (p<.0001), while L-Dopa had a detrimental effect in participants with higher gene scores (p = .01). Motor cortex plasticity, assessed via transcranial magnetic stimulation (TMS), also showed a gene score*drug interaction (p = .02). Individually, DRD2/ANKK1 genotype was significantly associated with motor learning (p = .02) and its modulation by L-Dopa (p<.0001), but not with any TMS measures. However, none of the individual polymorphisms explained the full constellation of findings associated with the gene score. These results suggest that genetic variation in the dopamine system influences learning and its modulation by L-Dopa. A polygene score explains differences in L-Dopa effects on learning and plasticity most robustly, thus identifying distinct biological phenotypes with respect to L-Dopa effects on learning and plasticity. These findings may have clinical applications in post-stroke rehabilitation or the treatment of Parkinson''s disease.     

Endothelial Protein C Receptor Gene Variants Not Associated with Severe Malaria in Ghanaian Children

Background

Two recent reports have identified the Endothelial Protein C Receptor (EPCR) as a key molecule implicated in severe malaria pathology. First, it was shown that EPCR in the human microvasculature mediates sequestration of Plasmodium falciparum-infected erythrocytes. Second, microvascular thrombosis, one of the major processes causing cerebral malaria, was linked to a reduction in EPCR expression in cerebral endothelial layers. It was speculated that genetic variation affecting EPCR functionality could influence susceptibility to severe malaria phenotypes, rendering PROCR, the gene encoding EPCR, a promising candidate for an association study.

Methods

Here, we performed an association study including high-resolution variant discovery of rare and frequent genetic variants in the PROCR gene. The study group, which previously has proven to be a valuable tool for studying the genetics of malaria, comprised 1,905 severe malaria cases aged 1–156 months and 1,866 apparently healthy children aged 2–161 months from the Ashanti Region in Ghana, West Africa, where malaria is highly endemic. Association of genetic variation with severe malaria phenotypes was examined on the basis of single variants, reconstructed haplotypes, and rare variant analyses.

Results

A total of 41 genetic variants were detected in regulatory and coding regions of PROCR, 17 of which were previously unknown genetic variants. In association tests, none of the single variants, haplotypes or rare variants showed evidence for an association with severe malaria, cerebral malaria, or severe malaria anemia.

Conclusion

Here we present the first analysis of genetic variation in the PROCR gene in the context of severe malaria in African subjects and show that genetic variation in the PROCR gene in our study population does not influence susceptibility to major severe malaria phenotypes.     

Intra-Population Genetic Variation in the Temporal Pattern of Egg Maturation in a Parasitoid Wasp

Parasitoid wasps are taxonomically and biologically extremely diverse. A conceptual framework has recently been developed for understanding life-history evolution and diversification in these animals, and it has confirmed that each of two linked life-history traits – the mode of larval development and the temporal pattern of egg maturation – acts as an organiser of life-history. The framework has been predicated on the assumption that there exists sufficient genetic variation in the latter trait to allow it to be shaped by natural selection. Focusing on the parasitoid wasp Trichogramma brassicae, our aim was to test the validity of that assumption, using established quantitative genetic methods. We demonstrate the existence of a statistically significant degree of intra-population polygenic variation in the temporal pattern of egg production within the wasp population we studied. Furthermore, our results, together with published data on clinal variation in the egg maturation pattern of another species, suggest that intra-specific evolutionary shifts in the temporal pattern of egg maturation of parasitoid wasps can result from a change in allocation to egg production either before, or very shortly after adult emergence, without there being an accompanying change in lifetime fecundity. As well as opening new avenues of research into the reproductive strategies, behaviour, community organisation and biological control potential of parasitoid wasps, this discovery also has implications for studies of life-history evolution and diversification in insects generally.     

Sexually selected skin colour is heritable and related to fecundity in a non-human primate

Sexual selection promotes the prevalence of heritable traits that increase an individual''s reproductive rate. Despite theoretically strong directional selection, sexually selected traits can show inter-individual variation. Here, we investigate whether red skin ornamentation, a rare example of a male mammalian trait involved in mate attraction, influences fecundity and is heritable in rhesus macaques (Macaca mulatta), and explore the mechanisms that are involved in maintaining trait variation. Interestingly, the trait is expressed by and is attractive to both sexes. We collected facial images of 266 free-ranging individuals and modelled skin redness and darkness to rhesus macaque vision. We used 20 years of genetic parentage data to calculate selection gradients on the trait and perform heritability analyses. Results show that males who were both darkly coloured and high-ranking enjoyed higher fecundity. Female skin redness was positively linked to fecundity, although it remains unclear whether this influences male selectiveness. Heritability explained 10–15% of the variation in redness and darkness, and up to 30% for skin darkness when sexes are considered separately, suggesting sex-influenced inheritance. Our results suggest that inter-individual variation is maintained through condition-dependence, with an added effect of balancing selection on male skin darkness, providing rare evidence for a mammalian trait selected through inter-sexual selection.     

Identification and characterisation of a developmentally regulated mammalian gene that utilises -1 programmed ribosomal frameshifting

Translational recoding of mRNA through a –1 ribosomal slippage mechanism has been observed in RNA viruses and retrotransposons of both eukaryotes and prokaryotes. Whilst this provides a potentially powerful mechanism of gene regulation, the utilization of –1 translational frameshifting in regulating mammalian gene expression has remained obscure. Here we report a mammalian gene, Edr, which provides the first example of –1 translational recoding in a eukaryotic cellular gene. In addition to bearing functional frameshift elements that mediate expression of distinct polypeptides, Edr bears both CCHC zinc-finger and putative aspartyl protease catalytic site retroviral-like motifs, indicative of a relic retroviral-like origin for Edr. These features, coupled with conservation of Edr as a single copy gene in mouse and man and striking spatio-temporal regulation of expression during embryogenesis, suggest that Edr plays a functionally important role in mammalian development.     

Isolation-by-distance in landscapes: considerations for landscape genetics

In landscape genetics, isolation-by-distance (IBD) is regarded as a baseline pattern that is obtained without additional effects of landscape elements on gene flow. However, the configuration of suitable habitat patches determines deme topology, which in turn should affect rates of gene flow. IBD patterns can be characterized either by monotonically increasing pairwise genetic differentiation (for example, F_ST) with increasing interdeme geographic distance (case-I pattern) or by monotonically increasing pairwise genetic differentiation up to a certain geographical distance beyond which no correlation is detectable anymore (case-IV pattern). We investigated if landscape configuration influenced the rate at which a case-IV pattern changed to a case-I pattern. We also determined at what interdeme distance the highest correlation was measured between genetic differentiation and geographic distance and whether this distance corresponded to the maximum migration distance. We set up a population genetic simulation study and assessed the development of IBD patterns for several habitat configurations and maximum migration distances. We show that the rate and likelihood of the transition of case-IV to case-I F_ST–distance relationships was strongly influenced by habitat configuration and maximum migration distance. We also found that the maximum correlation between genetic differentiation and geographic distance was not related to the maximum migration distance and was measured across all deme pairs in a case-I pattern and, for a case-IV pattern, at the distance where the F_ST–distance curve flattens out. We argue that in landscape genetics, separate analyses should be performed to either assess IBD or the landscape effects on gene flow.