Dietary stress remodels the genetic architecture of lifespan variation in outbred Drosophila

Short lifespan is one's fate, long lifespan is one's achievement: lessons from Daphnia

Studies of longevity rely on baseline life expectancy of reference genotypes measured in standardized conditions. Variation among labs, protocols, and genotypes makes longevity intervention studies difficult to compare. Furthermore, extending lifespan under suboptimal conditions or that of a short-lived genotype may be of a lesser theoretical and translational value than extending the maximal possible lifespan. Daphnia is becoming a model organism of choice for longevity research complementing data obtained on traditional models. In this study, we report longevity of several genotypes of a long-lived species D. magna under a variety of protocols, aiming to document the highest lifespan, factors reducing it, and parameters that change with age and correlate with longevity. Combining longevity data from 25 experiments across two labs, we report a strong intraspecific variation, moderate effects of group size and medium composition, and strong genotype-by-environment interactions with respect to food level. Specifically, short-lived genotypes show no caloric restriction (CR) effect, while long-lived ones expand their lifespan even further under CR. We find that the CR non-responsive clones show little correlation between longevity and two measures of lipid peroxidation. In contrast, the long-lived, CR-responsive clones show a positive correlation between longevity and lipid hydroperoxide abundance, and a negative correlation with MDA concentration. This indicates differences among genotypes in age-related accumulation and detoxification of LPO products and their effects on longevity. Our observations support the hypothesis that a long lifespan can be affected by CR and levels of oxidative damage, while genetically determined short lifespan remains short regardless.

Tradeoffs in Modeling Context Dependency in Complex Trait Genetics

Genetic effects on complex traits may depend on context, such as age, sex, environmental exposures or social settings. However, it is often unclear if the extent of context dependency, or Gene-by-Environment interaction (GxE), merits more involved models than the additive model typically used to analyze data from genome-wide association studies (GWAS). Here, we suggest considering the utility of GxE models in GWAS as a tradeoff between bias and variance parameters. In particular, We derive a decision rule for choosing between competing models for the estimation of allelic effects. The rule weighs the increased estimation noise when context is considered against the potential bias when context dependency is ignored. In the empirical example of GxSex in human physiology, the increased noise of context-specific estimation often outweighs the bias reduction, rendering GxE models less useful when variants are considered independently. However, we argue that for complex traits, the joint consideration of context dependency across many variants mitigates both noise and bias. As a result, polygenic GxE models can improve both estimation and trait prediction. Finally, we exemplify (using GxDiet effects on longevity in fruit flies) how analyses based on independently ascertained "top hits" alone can be misleading, and that considering polygenic patterns of GxE can improve interpretation.

How Can Genomics Help or Hinder Wildlife Conservation?

Genomic data are becoming increasingly affordable and easy to collect, and new tools for their analysis are appearing rapidly. Conservation biologists are interested in using this information to assist in management and planning but are typically limited financially and by the lack of genomic resources available for non-model taxa. It is therefore important to be aware of the pitfalls as well as the benefits of applying genomic approaches. Here, we highlight recent methods aimed at standardizing population assessments of genetic variation, inbreeding, and forms of genetic load and methods that help identify past and ongoing patterns of genetic interchange between populations, including those subjected to recent disturbance. We emphasize challenges in applying some of these methods and the need for adequate bioinformatic support. We also consider the promises and challenges of applying genomic approaches to understand adaptive changes in natural populations to predict their future adaptive capacity.

Rapid seasonal changes in phenotypes in a wild Drosophila population

Seasonal environmental change is one of the most rapid and striking environmental variables. Although relatively rapid adaptation to environmental changes over several years or several decades has been described in many taxa, rapid responses to seasonal environments are delicate, and therefore, the detection of the evolutionary responses requires sensitive methods. In this study, we examined seasonal changes in phenotypes related to thermal tolerance and morphological traits of Drosophila lutescens collected at the spring and autumn periods from a single location. We first demonstrated that flies in the two seasonal periods were almost genetically identical using double-digest restriction site-associated DNA sequencing and analysis. Using an experimental design to eliminate the effect of possible confounding factors that influence phenotypes (i.e., maternal effects and the environmental conditions in which each phenotype was analyzed), we showed that the heat tolerance of D. lutescens was significantly higher in the autumn population than in the spring population. Furthermore, cold tolerance was slightly higher in the spring population than in the autumn one. Although wing length and thorax length did not change significantly between seasons, the ratio of wing length to thorax length changed significantly between them. These results suggest that seasonal environmental heterogeneity induces rapid phenotypic changes within a year. Finally, we discuss the possibility of rapid evolutionary responses to seasonal changes.

The evolution of aging and lifespan

Aging is a nearly inescapable trait among organisms yet lifespan varies tremendously across different species and spans several orders of magnitude in vertebrates alone. This vast phenotypic diversity is driven by distinct evolutionary trajectories and tradeoffs that are reflected in patterns of diversification and constraint in organismal genomes. Age-specific impacts of selection also shape allele frequencies in populations, thus impacting disease susceptibility and environment-specific mortality risk. Further, the mutational processes that spawn this genetic diversity in both germline and somatic cells are strongly influenced by age and life history. We discuss recent advances in our understanding of the evolution of aging and lifespan at organismal, population, and cellular scales, and highlight outstanding questions that remain unanswered.

Genetic Architecture of Flowering Time Differs Between Populations With Contrasting Demographic and Selective Histories

Understanding the evolutionary factors that impact the genetic architecture of traits is a central goal of evolutionary genetics. Here, we investigate how quantitative trait variation accumulated over time in populations that colonized a novel environment. We compare the genetic architecture of flowering time in Arabidopsis populations from the drought-prone Cape Verde Islands and their closest outgroup population from North Africa. We find that trait polygenicity is severely reduced in the island populations compared to the continental North African population. Further, trait architectures and reconstructed allelic histories best fit a model of strong directional selection in the islands in accord with a Fisher-Orr adaptive walk. Consistent with this, we find that large-effect variants that disrupt major flowering time genes (FRI and FLC) arose first, followed by smaller effect variants, including ATX2 L125F, which is associated with a 4-day reduction in flowering time. The most recently arising flowering time-associated loci are not known to be directly involved in flowering time, consistent with an omnigenic signature developing as the population approaches its trait optimum. Surprisingly, we find no effect in the natural population of EDI-Cvi-0 (CRY2 V367M), an allele for which an effect was previously validated by introgression into a Eurasian line. Instead, our results suggest the previously observed effect of the EDI-Cvi-0 allele on flowering time likely depends on genetic background, due to an epistatic interaction. Altogether, our results provide an empirical example of the effects demographic history and selection has on trait architecture.

Polygenic adaptation to overnutrition reveals a role for cholinergic signaling in longevity

Overnutrition by high-sugar (HS) feeding reduces both the lifespan and healthspan across taxa. Pressuring organisms to adapt to overnutrition can highlight genes and pathways important for the healthspan in stressful environments. We used an experimental evolution approach to adapt four replicate, outbred population pairs of Drosophila melanogaster to a HS or control diet. Sexes were separated and aged on either diet until mid-life, then mated to produce the next generation, allowing enrichment for protective alleles over time. All HS-selected populations increased their lifespan and were therefore used as a platform to compare allele frequencies and gene expression. Pathways functioning in the nervous system were overrepresented in the genomic data and showed evidence for parallel evolution, although very few genes were the same across replicates. Acetylcholine-related genes, including the muscarinic receptor mAChR-A, showed significant changes in allele frequency in multiple selected populations and differential expression on a HS diet. Using genetic and pharmacological approaches, we show that cholinergic signaling affects Drosophila feeding in a sugar-specific fashion. Together, these results suggest that adaptation produces changes in allele frequencies that benefit animals under conditions of overnutrition and that it is repeatable at the pathway level.

From GWAS to signal validation: An approach for estimating genetic effects while preserving genomic context

Validating associations between genotypic and phenotypic variation remains a challenge, despite advancements in association studies. Common approaches for signal validation rely on gene-level perturbations, such as loss-of-function mutations or RNAi, which test the effect of genetic modifications usually not observed in nature. CRISPR-based methods can validate associations at the SNP level, but have significant drawbacks, including resulting off-target effects and being both time-consuming and expensive. Both approaches usually modify the genome of a single genetic background, limiting the generalizability of experiments. To address these challenges, we present a simple, low-cost experimental scheme for validating genetic associations at the SNP level in outbred populations. The approach involves genotyping live outbred individuals at a focal SNP, crossing homozygous individuals with the same genotype at that locus, and contrasting phenotypes across resulting synthetic outbred populations. We tested this method in Drosophila melanogaster, measuring the longevity effects of a polymorphism at a naturally-segregating cis-eQTL for the midway gene. Our results demonstrate the utility of this method in SNP-level validation of naturally occurring genetic variation regulating complex traits. This method provides a bridge between the statistical discovery of genotype-phenotype associations and their validation in the natural context of heterogeneous genomic contexts.

A Single Nucleotide Variant in the PPARγ-homolog Eip75B Affects Fecundity in Drosophila

Single nucleotide polymorphisms are the most common type of genetic variation, but how these variants contribute to the adaptation of complex phenotypes is largely unknown. Experimental evolution and genome-wide association studies have demonstrated that variation in the PPARγ-homolog Eip75B has associated with longevity and life-history differences in the fruit fly Drosophila melanogaster. Using RNAi knockdown, we first demonstrate that reduced expression of Eip75B in adult flies affects lifespan, egg-laying rate, and egg volume. We then tested the effects of a naturally occurring SNP within a cis-regulatory domain of Eip75B by applying two complementary approaches: a Mendelian randomization approach using lines of the Drosophila Genetic Reference Panel, and allelic replacement using precise CRISPR/Cas9-induced genome editing. Our experiments reveal that this natural polymorphism has a significant pleiotropic effect on fecundity and egg-to-adult viability, but not on longevity or other life-history traits. Our results provide a rare functional validation at the nucleotide level and identify a natural allelic variant affecting fitness and life-history adaptation.