Genome-wide association of foraging behavior in Drosophila melanogaster fails to support large-effect alleles at the foraging gene

Genome-wide association of foraging behavior in Drosophila melanogaster fails to support large-effect alleles at the foraging gene
Thomas Turner, Christopher C Giauque, Daniel R Schrider, Andrew D Kern

Thirty four years ago, it was postulated that natural populations of Drosophila melanogaster are comprised of two behavioral morphs termed “rover” and “sitter”, and that this variation is caused mainly by large-effect alleles at a single locus. Since that time, considerable data has been amassed that compares the behavior and physiology of these morphs. Contrary to common assertions, however, published support for the existence of common large effect alleles in nature is quite limited. To further investigate, we quantified the foraging behavior of 36 natural strains, performed a genome-wide association study, and described patterns of molecular evolution at the foraging locus. Though there was significant variation in foraging behavior among genotypes, this variation was continuously distributed and not significantly associated with genetic variation at the foraging gene. Patterns of molecular population genetic variation at this gene also provide no support for the hypothesis that for is a target of long term balancing selection We propose that additional data is required to support a hypothesis of common alleles of large effect on foraging behavior in nature. Genome-wide association does support a role for natural variation at several other loci, including the sulfateless gene, though these associations should be considered preliminary until validated with a larger sample size.

Regulatory variants explain much more heritability than coding variants across 11 common diseases

Regulatory variants explain much more heritability than coding variants across 11 common diseases
Alexander Gusev, S Hong Lee, Benjamin M Neale, Gosia Trynka, Bjarni J Vilhjalmsson, Hilary Finucane, Han Xu, Chongzhi Zang, Stephan Ripke, Eli Stahl, n/a Schizophrenia Working Group of the PGC, n/a SWE-SCZ Consortium, Anna K Kahler, Christina M Hultman, Shaun M Purcell, Steven A McCarroll, Mark Daly, Bogdan Pasaniuc, Patrick F Sullivan, Naomi R Wray, Soumya Raychaudhuri, Alkes L Price

Common variants implicated by genome-wide association studies (GWAS) of complex diseases are known to be enriched for coding and regulatory variants. We applied methods to partition the heritability explained by genotyped SNPs (h2g) across functional categories (while accounting for shared variance due to linkage disequilibrium) to genotype and imputed data for 11 common diseases. DNaseI Hypersensitivity Sites (DHS) from 218 cell-types, spanning 16% of the genome, explained an average of 79% of h2g (5.1× enrichment; P < 10−20); further enrichment was observed at enhancer and cell-type specific DHS elements. The enrichments were much smaller in analyses that did not use imputed data or were restricted to GWAS- associated SNPs. In contrast, coding variants, spanning 1% of the genome, explained only 8% of h2g (13.8× enrichment; P = 5 × 10−4). We replicated these findings but found no significant contribution from rare coding variants in an independent schizophrenia cohort genotyped on GWAS and exome chips.

Genetic Influences on Brain Gene Expression in Rats Selected for Tameness and Aggression

Genetic Influences on Brain Gene Expression in Rats Selected for Tameness and Aggression

Henrike O. Heyne, Susann Lautenschläger, Ronald Nelson, François Besnier, Maxime Rotival, Alexander Cagan, Rimma Kozhemyakina, Irina Z. Plyusnina, Lyudmila Trut, Örjan Carlborg, Enrico Petretto, Leonid Kruglyak, Svante Pääbo, Torsten Schöneberg, Frank W. Albert
(Submitted on 14 Apr 2014)

Inter-individual differences in many behaviors are partly due to genetic differences, but the identification of the genes and variants that influence behavior remains challenging. Here, we studied an F2 intercross of two outbred lines of rats selected for tame and aggressive behavior towards humans for more than 64 generations. By using a mapping approach that is able to identify genetic loci segregating within the lines, we identified four times more loci influencing tameness and aggression than by an approach that assumes fixation of causative alleles, suggesting that many causative loci were not driven to fixation by the selection. We used RNA sequencing in 150 F2 animals to identify hundreds of loci that influence brain gene expression. Several of these loci colocalize with tameness loci and may reflect the same genetic variants. Through analyses of correlations between allele effects on behavior and gene expression, differential expression between the tame and aggressive rat selection lines, and correlations between gene expression and tameness in F2 animals, we identify the genes Gltscr2, Lgi4, Zfp40 and Slc17a7 as candidate contributors to the strikingly different behavior of the tame and aggressive animals.

Natural CMT2 variation is associated with genome-wide methylation changes and temperature adaptation

Natural CMT2 variation is associated with genome-wide methylation changes and temperature adaptation

Xia Shen, Jennifer De Jonge, Simon Forsberg, Mats Pettersson, Zheya Sheng, Lars Hennig, Örjan Carlborg

As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and variability in seasonal temperatures where the plastic allele had reduced genome-wide CHH methylation. Cmt2 mutants were more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature- stress.

Weedy Adaptation in Setaria spp.: VI. S. faberi Seed hull shape as soil germination signal antenna

Weedy Adaptation in Setaria spp.: VI. S. faberi Seed hull shape as soil germination signal antenna

J.L. Donnelly, D.C. Adams, J. Dekker
(Submitted on 27 Mar 2014)

Ecological selection forces for weedy and domesticated traits have influenced the evolution of seed shape in Setaria resulting in similarity in seed shape that reflects similarity in ecological function rather than reflecting phylogenetic relatedness. Seeds from two diploid subspecies of Setaria viridis, consisting of one weedy subspecies and two races of the domesticated subspecies, and four other polyploidy weedy species of Setaria. We quantified seed shape from the silhouettes of the seeds in two separate views. Differences in shape were compared to ecological role (weed vs. crop) and the evolutionary trajectory of shape change by phylogenetic grouping from a single reference species was calculated. Idealized three-dimensional models were created to examine the differences in shape relative to surface area and volume. All populations were significantly different in shape, with crops easily distinguished from weeds, regardless of relatedness between the taxa. Trajectory of shape change varied by view, but separated crops from weeds and phylogenetic groupings. Three-dimensional models gave further evidence of differences in shape reflecting adaptation for environmental exploitation. The selective forces for weedy and domesticated traits have exceeded phylogenetic constraints, resulting in seed shape similarity due to ecological role rather than phylogenetic relatedness. Seed shape and surface-to-volume ratio likely reflect the importance of the water film that accumulates on the seed surface when in contact with soil particles. Seed shape may also be a mechanism of niche separation between taxa.

Epigenetic Modifications are Associated with Inter-species Gene Expression Variation in Primates

Epigenetic Modifications are Associated with Inter-species Gene Expression Variation in Primates

Xiang Zhou, Carolyn Cain, Marsha Myrthil, Noah Lewellen, Katelyn Michelini, Emily Davenport, Matthew Stephens, Jonathan Pritchard, Yoav Gilad

Changes in gene regulation level have long been thought to play an important role in evolution and speciation, especially in primates. Over the past decade, comparative genomic studies have revealed extensive inter-species differences in gene expression levels yet we know much less about the extent to which regulatory mechanisms differ between species. To begin addressing this gap, we performed a comparative epigenetic study in primate lymphoblastoid cell lines (LCLs), to query the contribution of RNA polymerase II (Pol II) and four histone modifications (H3K4me1, H3K4me3, H3K27ac, and H3K27me3) to inter-species variation in gene expression levels. We found that inter-species differences in mark enrichment near transcription start sites are significantly more often associated with inter-species differences in the corresponding gene expression level than expected by chance alone. Interestingly, we also found that first-order interactions among the histone marks and Pol II do not markedly contribute to the degree of association between the marks and inter-species variation in gene expression levels, suggesting that the marginal effects of the five marks dominate this contribution.

Genetic influences on translation in yeast

Genetic influences on translation in yeast

Frank W. Albert, Dale Muzzey, Jonathan Weissman, Leonid Kruglyak
(Submitted on 13 Mar 2014)

Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosome profiling to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes, more than half as many as showed genetic differences in mRNA levels. Similarly, allele specific measurements in the diploid hybrid between the two strains revealed roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, strong effects on translation were rare, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. Across all expressed genes, there was a tendency for translation to more often reinforce than buffer mRNA differences, resulting in footprint differences with greater magnitudes than the mRNA differences. A reanalysis of two earlier studies which reported translational buffering between two yeast species showed that translational reinforcement is in fact more common between these species, consistent with our results. Finally, we catalogued instances of premature translation termination in the two yeast strains. Overall, genetic variation clearly influences translation, but primarily does so by subtly modulating differences in mRNA levels. Translation does not appear to create strong discrepancies between genetic influences on mRNA and protein levels.

Mapping quantitative trait loci underlying function-valued phenotypes

Mapping quantitative trait loci underlying function-valued phenotypes

Il-Youp Kwak, Candace R. Moore, Edgar P. Spalding, Karl W. Broman
(Submitted on 12 Mar 2014)

Most statistical methods for QTL mapping focus on a single phenotype. However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time. While there exist methods for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models. We propose two simple, fast methods that maintain high power and precision and are amenable to extensions with multiple-QTL models using a penalized likelihood approach. After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes. Our methods have been implemented as a package for R, funqtl.

Conditions for the validity of SNP-based heritability estimation

Conditions for the validity of SNP-based heritability estimation
James J Lee, Carson C Chow

The heritability of a trait ($h^2$) is the proportion of its population variance caused by genetic differences, and estimates of this parameter are important for interpreting the results of genome-wide association studies (GWAS). In recent years, researchers have adopted a novel method for estimating a lower bound on heritability directly from GWAS data that uses realized genetic similarities between nominally unrelated individuals. The quantity estimated by this method is purported to be the contribution to heritability that could in principle be recovered from association studies employing the given panel of SNPs ($h^2_\textrm{SNP}$). Thus far the validity of this approach has mostly been tested empirically. Here, we provide a mathematical explication and show that the method should remain a robust means of obtaining $h^2_\textrm{SNP}$ under circumstances wider than those under which it has so far been derived.

Approaching allelic probabilities and Genome-Wide Association Studies from beta distributions

Approaching allelic probabilities and Genome-Wide Association Studies from beta distributions

José Santiago García-Cremades, Angel del Río, José A. García, Javier Gayán, Antonio González-Pérez, Agustín Ruiz, O. Sotolongo-Grau, Manuel Ruiz-Marín
(Submitted on 25 Feb 2014)

In this paper we have proposed a model for the distribution of allelic probabilities for generating populations as reliably as possible. Our objective was to develop such a model which would allow simulating allelic probabilities with different observed truncation and de- gree of noise. In addition, we have also introduced here a complete new approach to analyze a genome-wide association study (GWAS) dataset, starting from a new test of association with a statistical distribution and two effect sizes of each genotype. The new methodologi- cal approach was applied to a real data set together with a Monte Carlo experiment which showed the power performance of our new method. Finally, we compared the new method based on beta distribution with the conventional method (based on Chi-Squared distribu- tion) using the agreement Kappa index and a principal component analysis (PCA). Both the analyses show found differences existed between both the approaches while selecting the single nucleotide polymorphisms (SNPs) in association.