Trait Correlations in the Genomics Era

© 2017 Elsevier Ltd Thinking about the evolutionary causes and consequences of trait correlations has been dominated by quantitative genetics theory that is focused on hypothetical loci. Since this theory was initially developed, technology has enabled the identification of specific genetic variants that contribute to trait correlations. Here, we review studies of the genetic basis of trait correlations to ask: What has this new information taught us? We find that causal variants can be pleiotropic and/or linked in different ways, indicating that pleiotropy and linkage are not alternative genetic mechanisms. Further, many trait correlations have a polygenic basis, suggesting that both pleiotropy and linkage likely contribute. We discuss implications of these findings for the evolutionary causes and consequences of trait correlations

Anticipated effects of abiotic environmental change on intraspecific social interactions

Peer reviewedPublisher PD

Natural Variation in Decision-Making Behavior in Drosophila melanogaster

There has been considerable recent interest in using Drosophila melanogaster to investigate the molecular basis of decision-making behavior. Deciding where to place eggs is likely one of the most important decisions for a female fly, as eggs are vulnerable and larvae have limited motility. Here, we show that many natural genotypes of D. melanogaster prefer to lay eggs near nutritious substrate, rather than in nutritious substrate. These preferences are highly polymorphic in both degree and direction, with considerable heritability (0.488) and evolvability

A randomized, phase III trial of capecitabine plus bevacizumab (Cape-Bev) versus capecitabine plus irinotecan plus bevacizumab (CAPIRI-Bev) in first-line treatment of metastatic colorectal cancer: The AIO KRK 0110 Trial/ML22011 Trial

<p>Abstract</p> <p>Background</p> <p>Several randomized trials have indicated that combination chemotherapy applied in metastatic colorectal cancer (mCRC) does not significantly improve overall survival when compared to the sequential use of cytotoxic agents (CAIRO, MRC Focus, FFCD 2000-05). The present study investigates the question whether this statement holds true also for bevacizumab-based first-line treatment including escalation- and de-escalation strategies.</p> <p>Methods/Design</p> <p>The AIO KRK 0110/ML22011 trial is a two-arm, multicenter, open-label randomized phase III trial comparing the efficacy and safety of capecitabine plus bevacizumab (Cape-Bev) versus capecitabine plus irinotecan plus bevacizumab (CAPIRI-Bev) in the first-line treatment of metastatic colorectal cancer. Patients with unresectable metastatic colorectal cancer, Eastern Cooperative Oncology Group (ECOG) performance status 0-1, will be assigned in a 1:1 ratio to receive either capecitabine 1250 mg/m²bid for 14d (d1-14) plus bevacizumab 7.5 mg/kg (d1) q3w (Arm A) or capecitabine 800 mg/m²BID for 14d (d1-14), irinotecan 200 mg/m²(d1) and bevacizumab 7.5 mg/kg (d1) q3w (Arm B). Patients included into this trial are required to consent to the analysis of tumour tissue and blood for translational investigations. In Arm A, treatment escalation from Cape-Bev to CAPIRI-Bev is recommended in case of progressive disease (PD). In Arm B, de-escalation from CAPIRI-Bev to Cape-Bev is possible after 6 months of treatment or in case of irinotecan-associated toxicity. Re-escalation to CAPIRI-Bev after PD is possible. The primary endpoint is time to failure of strategy (TFS). Secondary endpoints are overall response rate (ORR), overall survival, progression-free survival, safety and quality of life.</p> <p>Conclusion</p> <p>The AIO KRK 0110 trial is designed for patients with disseminated, but asymptomatic mCRC who are not potential candidates for surgical resection of metastasis. Two bevacizumab-based strategies are compared: one starting as single-agent chemotherapy (Cape-Bev) allowing escalation to CAPIRI-Bev and another starting with combination chemotherapy (CAPIRI-Bev) and allowing de-escalation to Cape-Bev and subsequent re-escalation if necessary.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier <a href="http://www.clinicaltrials.gov/ct2/show/NCT01249638">NCT01249638</a></p> <p>EudraCT-No.: 2009-013099-38</p

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Data from: Genetic variation in social environment construction influences the development of aggressive behavior in Drosophila melanogaster

Individuals are not merely subject to their social environments; they choose and create them, through a process called social environment (or social niche) construction. When genotypes differ in social environment-constructing behaviors, different genotypes are expected to experience different social environments. As social experience often affects behavioral development, quantitative genetics and psychology theories predict that genetic variation in social environment construction should have an important role in determining phenotypic variation; however, this hypothesis has not been tested directly. I identify multiple mechanisms of social environment construction that differ among natural genotypes of Drosophila melanogaster and investigate their consequences for the development of aggressive behavior. Male genotypes differed in the group sizes that they preferred and in their aggressive behavior; both of these behaviors influenced social experience, demonstrating that these behaviors function as social environment-constructing traits. Further, the effects of social experience—as determined in part by social environment construction—carried over to affect focal male aggression at a later time and with a new opponent. These results provide manipulative experimental support for longstanding hypotheses in psychology, that genetic variation in social environment construction has a causal role in behavioral development. More broadly, these results imply that studies of the genetic basis of complex traits should be expanded to include mechanisms by which genetic variation shapes the environments that individuals experience

Data from: Genetic composition of social groups influences male aggressive behaviour and fitness in natural genotypes of Drosophila melanogaster

Indirect genetic effects (IGEs) describe how an individual’s behaviour—which is influenced by his or her genotype—can affect the behaviours of interacting individuals. IGE research has focused on dyads. However, insights from social networks research, and other studies of group behaviour, suggest that dyadic interactions are affected by the behaviour of other individuals in the group. To extend IGE inferences to groups of three or more, IGEs must be considered from a group perspective. Here, I introduce the “focal interaction” approach to study IGEs in groups. I illustrate the utility of this approach by studying aggression among natural genotypes of Drosophila melanogaster. I chose two natural genotypes as “focal interactants”: the behavioural interaction between them was the “focal interaction.” One male from each focal interactant genotype was present in every group, and I varied the genotype of the third male—the “treatment male.” Genetic variation in the treatment male’s aggressive behaviour influenced the focal interaction, demonstrating that IGEs in groups are not a straightforward extension of IGEs measured in dyads. Further, the focal interaction influenced male mating success, illustrating the role of IGEs in behavioural evolution. These results represent the first manipulative evidence for IGEs at the group level

Data from: Natural genetic variation in social environment choice: context-dependent gene-environment correlation in Drosophila melanogaster

Gene-environment correlation (rGE) occurs when an individual’s genotype determines its choice of environment, generating a correlation between environment and genotype frequency. In particular, social rGE, caused by genetic variation in social environment choice, can critically determine both individual development and the course of social selection. Despite its foundational role in social evolution and developmental psychology theory, natural genetic variation in social environment choice has scarcely been examined empirically. Drosophila melanogaster provides an ideal system for investigating social rGE. Flies live socially in nature and have many opportunities to make social decisions; and natural, heterozygous genotypes may be replicated, enabling comparisons between genotypes across environments. Using this approach, I show that all aspects of social environment choice vary among natural genotypes, demonstrating pervasive social rGE. Surprisingly, genetic variation in group-size preference was density-dependent, indicating that the behavioral and evolutionary consequences of rGE may depend on the context in which social decisions are made. These results provide the first detailed investigation of social rGE, and illustrate that that genetic variation may influence organismal performance by specifying the environment in which traits are expressed

second-order IGEs

This file includes all data from the paper, Genetic composition of social groups influences male aggressive behaviour and fitness in natural genotypes of Drosophila melanogaster." The columns "A_col" and "B_col" describe which paint color was received by A and B males. Columns labelled "X_onpatch" describe whether or not the male was on the patch. For example, "A_onpatch" describes whether the A male landed on the patch during the 30-minute observation period; if so, a 1 is recorded in that column, or a 0 if not. Columns labelled "XatY_lunge" describe the number of times that the genotype X male lunged at the genotype Y male. For example, the column labelled "AatB_lunge" records the number of times that the A male lunged at the B male during the 30-minute observation period

development experiment data for dryad

Data from the development experiment. Includes the number of focal lunges measured on days 1 and 2 for each individual (day1.focal.lunge and day2.focal.lunge), the number of times each focal male was attacked by stimulus males (day1.at.focal.lunge, day2.at.focal.lunge), and the amount of time the focal male spent on patch on day 2 (day2.time) as well as identifiers such as genotype