Genomewide architecture of adaptation in experimentally evolved characterized by widespread pleiotropy.

Dissecting the molecular basis of adaptation remains elusive despite our ability to sequence genomes and transcriptomes. At present, most genomic research on selection focusses on signatures of selective sweeps in patterns of heterozygosity. Other research has studied changes in patterns of gene expression in evolving populations but has not usually identified the genetic changes causing these shifts in expression.

Building Bridges from Genome to Physiology Using Machine Learning and Experimental Evolution.

experimental evolution, with its well-defined selection protocols, has long supplied useful genetic material for the analysis of functional physiology. While there is a long tradition of interpreting the effects of large-effect mutants physiologically, identifying and interpreting gene-to-phenotype relationships has been challenging in the genomic era, with many labs not resolving how physiological traits are affected by multiple genes throughout the genome. experimental evolution has demonstrated that multiple phenotypes change because of the evolution of many loci across the genome, creating the scientific challenge of sifting out differentiated but noncausal loci for individual characters.

Combining Metabolomics and Experimental Evolution Reveals Key Mechanisms Underlying Longevity Differences in Laboratory Evolved Populations.

Experimental evolution with has been used extensively for decades to study aging and longevity. In recent years, the addition of DNA and RNA sequencing to this framework has allowed researchers to leverage the statistical power inherent to experimental evolution to study the genetic basis of longevity itself. Here, we incorporated metabolomic data into to this framework to generate even deeper insights into the physiological and genetic mechanisms underlying longevity differences in three groups of experimentally evolved populations with different aging and longevity patterns.

Genomics of Early Cardiac Dysfunction and Mortality in Obese .

In experimental evolution, we impose functional demands on laboratory populations of model organisms using selection. After enough generations of such selection, the resulting populations constitute excellent material for physiological research. An intense selection regime for increased starvation resistance was imposed on 10 large outbred populations.

Drosophila transcriptomics with and without ageing.

The genomic basis of ageing still remains unknown despite being a topic of study for many years. Here, we present data from 20 experimentally evolved laboratory populations of Drosophila melanogaster that have undergone two different life-history selection regimes. One set of ten populations demonstrates early ageing whereas the other set of ten populations shows postponed ageing.

Genome-Wide Mapping of Gene-Phenotype Relationships in Experimentally Evolved Populations.

Model organisms subjected to sustained experimental evolution often show levels of phenotypic differentiation that dramatically exceed the phenotypic differences observed in natural populations. Genome-wide sequencing of pooled populations then offers the opportunity to make inferences about the genes that are the cause of these phenotypic differences. We tested, through computer simulations, the efficacy of a statistical learning technique called the "fused lasso additive model" (FLAM).

Rapid divergence and convergence of life-history in experimentally evolved Drosophila melanogaster.

Laboratory selection experiments are alluring in their simplicity, power, and ability to inform us about how evolution works. A longstanding challenge facing evolution experiments with metazoans is that significant generational turnover takes a long time. In this work, we present data from a unique system of experimentally evolved laboratory populations of Drosophila melanogaster that have experienced three distinct life-history selection regimes.

Four steps toward the control of aging: following the example of infectious disease.

The biotechnological task of controlling human aging will evidently be complex, given the failure of all simple strategies for accomplishing this task to date. In view of this complexity, a multi-step approach will be necessary. One precedent for a multi-step biotechnological success is the burgeoning control of human infectious diseases from 1840 to 2000.

A model of the evolution of larval feeding rate in Drosophila driven by conflicting energy demands.

Energy allocation is believed to drive trade-offs in life history evolution. We develop a physiological and genetic model of energy allocation that drives evolution of feeding rate in a well-studied model system. In a variety of stressful environments Drosophila larvae adapt by altering their rate of feeding.