Testing for genetic associations in arbitrarily structured populations

Testing for genetic associations in arbitrarily structured populations
Minsun Song, Wei Hao, John D. Storey
doi: http://dx.doi.org/10.1101/012682

We present a new statistical test of association between a trait (either quantitative or binary) and genetic markers, which we theoretically and practically prove to be robust to arbitrarily complex population structure. The statistical test involves a set of parameters that can be directly estimated from large-scale genotyping data, such as that measured in genome-wide associations studies (GWAS). We also derive a new set of methodologies, called a genotype-conditional association test (GCAT), shown to provide accurate association tests in populations with complex structures, manifested in both the genetic and environmental contributions to the trait. We demonstrate the proposed method on a large simulation study and on the Northern Finland Birth Cohort study. In the Finland study, we identify several new significant loci that other methods do not detect. Our proposed framework provides a substantially different approach to the problem from existing methods. We provide some discussion on its similarities and differences with the linear mixed model and principal component approaches.

The competition between simple and complex evolutionary trajectories in asexual populations

The competition between simple and complex evolutionary trajectories in asexual populations

Ian E. Ochs, Michael M. Desai
Comments: 8 pages, 3 figures
Subjects: Populations and Evolution (q-bio.PE)

On rugged fitness landscapes where sign epistasis is common, adaptation can often involve either individually beneficial “uphill” mutations or more complex mutational trajectories involving fitness valleys or plateaus. The dynamics of the evolutionary process determine the probability that evolution will take any specific path among a variety of competing possible trajectories. Understanding this evolutionary choice is essential if we are to understand the outcomes and predictability of adaptation on rugged landscapes. We present a simple model to analyze the probability that evolution will eschew immediately uphill paths in favor of crossing fitness valleys or plateaus that lead to higher fitness but less accessible genotypes. We calculate how this probability depends on the population size, mutation rates, and relevant selection pressures, and compare our analytical results to Wright-Fisher simulations. We find that the probability of valley crossing depends nonmonotonically on population size: intermediate size populations are most likely to follow a “greedy” strategy of acquiring immediately beneficial mutations even if they lead to evolutionary dead ends, while larger and smaller populations are more likely to cross fitness valleys to reach distant advantageous genotypes. We explicitly identify the boundaries between these different regimes in terms of the relevant evolutionary parameters. Above a certain threshold population size, we show that the degree of evolutionary “foresight” depends only on a single simple combination of the relevant parameters.

Reproductive workers show queen-like gene expression in an intermediately eusocial insect, the buff-tailed bumble bee Bombus terrestris

Reproductive workers show queen-like gene expression in an intermediately eusocial insect, the buff-tailed bumble bee Bombus terrestris.

Mark Christian Harrison, Robert L Hammond, Eamonn B Mallon
doi: http://dx.doi.org/10.1101/012500

Bumble bees represent a taxon with an intermediate level of eusociality within Hymenoptera. The clear division of reproduction between a single founding queen and the largely sterile workers is characteristic for highly eusocial species, whereas the morphological similarity between the bumble bee queen and the workers is typical for more primitively eusocial hymenopterans. Also, unlike other highly eusocial hymenopterans, division of labour among worker sub-castes is plastic and not predetermined by morphology or age. We conducted a differential expression analysis based on RNA-seq data from 11 combinations of developmental stage and caste to investigate how a single genome can produce the distinct castes of queens, workers and males in the buff-tailed bumble bee Bombus terrestris. Based on expression patterns, we found males to be the most distinct of all adult castes (2,411 transcripts differentially expressed compared to non-reproductive workers). However, only relatively few transcripts were differentially expressed between males and workers during development (larvae: 71, pupae: 162). This indicates the need for more distinct expression patterns to control behaviour and physiology in adults compared to those required to create different morphologies. Among the female castes, the expression of over ten times more transcripts differed signifcantly between reproductive workers and their non-reproductive sisters than when comparing reproductive workers to the mother queen. This suggests a strong shift towards a more queen-like behaviour and physiology when a worker becomes fertile. This is in contrast to findings for higher eusocial species, in which reproductive workers are more similar to non-reproductive workers than the queen.

An experimental test of the relationship between melanism and desiccation survival in insects

An experimental test of the relationship between melanism and desiccation survival in insects

Subhash Rajpurohit, Lisa Marie Peterson, Andrew Orr, Anthony J. Marlon, Allen G Gibbs
doi: http://dx.doi.org/10.1101/012369

We used experimental evolution to test the ?melanism-desiccation? hypothesis, which proposes that dark cuticle in several Drosophila species is an adaptation for increased desiccation tolerance. We selected for dark and light body pigmentation in replicated populations of D. melanogaster and assayed traits related to water balance. We also scored pigmentation and desiccation tolerance in populations selected for desiccation survival. Populations in both selection regimes showed large differences in the traits directly under selection. However, after over 40 generations of pigmentation selection, dark-selected populations were not more desiccation-tolerant than light-selected and control populations, nor did we find significant changes in carbohydrate amounts that could affect desiccation resistance. Body pigmentation of desiccation-selected populations did not differ from control populations after over 140 generations of selection. Our results do not support an important role for melanization in Drosophila water balance.

DensiTree 2: Seeing Trees Through the Forest

DensiTree 2: Seeing Trees Through the Forest

Remco Bouckaert, Joseph Heled
doi: http://dx.doi.org/10.1101/012401

Motivation: Phylogenetic analysis like Bayesian MCMC or bootstrapping result in a collection of trees. Trees are discrete objects and it is generally difficult to get a mental grip on a distributions over trees. Visualisation tools like DensiTree can give good intuition on tree distributions. It works by drawing all trees in the set transparently thus highlighting areas where the tree in the set agrees. In this way, both uncertainty in clade heights and uncertainty in topology can be visualised. In our experience, a vanilla DensiTree can turn out to be misleading in that it shows too much uncertainty due to wrongly ordering taxa or due to unlucky placement of internal nodes. Results: DensiTree is extended to allow visualisation of meta-data associated with branches such as population size and evolutionary rates. Furthermore, geographic locations of taxa can be shown on a map, making it easy to visually check there is some geographic pattern in a phylogeny. Taxa orderings have a large impact on the layout of the tree set, and advances have been made in finding better orderings resulting in significantly more informative visualisations. We also explored various methods for positioning internal nodes, which can improve the quality of the image. Together, these advances make it easier to comprehend distributions over trees. Availability: DensiTree is freely available from http://compevol. auckland.ac.nz/software/.

The genomic signature of social interactions regulating honey bee caste development

The genomic signature of social interactions regulating honey bee caste development
Svjetlana Vojvodic, Brian R Johnson, Brock Harpur, Clement Kent, Amro Zayed, Kirk E Anderson, Timothy Linksvayer
doi: http://dx.doi.org/10.1101/012385

Social evolution theory posits the existence of genes expressed in one individual that affect the traits and fitness of social partners. The archetypal example of reproductive altruism, honey bee reproductive caste, involves strict social regulation of larval caste fate by care-giving nurses. However, the contribution of nurse-expressed genes, which are prime socially-acting candidate genes, to the caste developmental program and to caste evolution remains mostly unknown. We experimentally induced new queen production by removing the current colony queen, and we used RNA sequencing to study the gene expression profiles of both developing larvae and their care-giving nurses before and after queen removal. By comparing the gene expression profiles between both queen-destined larvae and their nurses to worker-destined larvae and their nurses in queen-present and queen-absent conditions, we identified larval and nurse genes associated with larval caste development and with queen presence. Of 950 differentially-expressed genes associated with larval caste development, 82% were expressed in larvae and 18% were expressed in nurses. Behavioral and physiological evidence suggests that nurses may specialize in the short term feeding queen- versus worker-destined larvae. Estimated selection coefficients indicated that both nurse and larval genes associated with caste are rapidly evolving, especially those genes associated with worker development. Of the 1863 differentially-expressed genes associated with queen presence, 90% were expressed in nurses. Altogether, our results suggest that socially-acting genes play important roles in both the expression and evolution of socially-influenced traits like caste.

Evaluating intra- and inter-individual variation in the human placental transcriptome

Evaluating intra- and inter-individual variation in the human placental transcriptome
David A Hughes, Martin Kircher, Zhisong He, Song Guo, Genevieve L Fairbrother, Carlos S Moreno, Philipp Khaitovich, Mark Stoneking
doi: http://dx.doi.org/10.1101/012468

Background: Gene expression variation is a phenotypic trait of particular interest as it represents the initial link between genotype and other phenotypes. Analyzing how such variation apportions among and within groups allows for the evaluation of how genetic and environmental factors influence such traits. It also provides opportunities to identify genes and pathways that may have been influenced by non-neutral processes. Here we use a population genetics framework and next generation sequencing to evaluate how gene expression variation is apportioned among four human groups in a natural biological tissue, the placenta. Results: We estimate that on average, 33.2%, 58.9% and 7.8% of the placental transcriptome is explained by variation within individuals, among individuals and among human groups, respectively. Additionally, when technical and biological traits are included in models of gene expression they account for roughly 2% of total gene expression variation. Notably, the variation that is significantly different among groups is enriched in biological pathways associated with immune response, cell signaling and metabolism. Many biological traits demonstrated correlated changes in expression in numerous pathways of potential interest to clinicians and evolutionary biologists. Finally, we estimate that the majority of the human placental transcriptome (65% of expressed genes) exhibits expression profiles consistent with neutrality; the remainder are consistent with stabilizing selection (26%), directional selection (4.9%), or diversifying selection (4.8%). Conclusion: We apportion placental gene expression variation into individual, population and biological trait factors and identify how each influence the transcriptome. Additionally, we advance methods to associate expression profiles with different forms of selection.