ERC FUNDED PROJECTS

Timing is everything in ecology, and because plants provide the foundation for most land-based food webs, the timing of their activities profoundly orchestrates the majority of ecological interactions. Most photosynthetic and growth processes are under circadian control, but many additional processes--approximately 30-40% of all genes—are under circadian control, and yet the Darwinian fitness impact of being “in synch” with the environment has not been systematically studied for any organism. We have developed a toolbox for a native tobacco plant, Nicotiana attenuata, that allows us to “ask the plant” which genes, proteins or metabolites are regulated in particular plant-mediated ecological interactions; identify “the genes that matter” for a given interaction; silence or ectopically express these genes, and conduct field releases with the transformed plants at a nature preserve in the Great Basin Desert to rigorously test hypotheses of gene function. By taking advantage of both our understanding of what it takes for this plant to survive in nature, and the procedures established to disentangle the skein of subtle interactions that determine its performance, we will systematically examine the importance of synchronous entrained endogenous rhythms at all life stages: longevity in the seed bank, germination, rosette growth, elongation, flowering and senescence. Specifically, we propose to silence a key components (starting with NaTOC1) of the plant’s endogenous clock to shorten the plant’s circadian rhythm, both constitutively and with strong dexamethasone-inducible promoters, at all life stages. With a combination of real-time phenotype imaging, metabolite and transcriptome analysis, and ecological know-how, the research will reveal how plants adjust their physiologies to the ever-changing panoply of environmental stresses with which they must cope; by creating arrhythmic plants, we will understand why so many processes are under circadian control.

2 496 002 €

Start date: 2012-04-01, End date: 2017-03-31

Lateral gene transfer (LGT) is the process by which prokaryotes acquire DNA across wide taxonomic boundaries and incorporate it into their genome. Accumulating evidence shows that LGT plays a major role in prokaryote evolution. The biological and evolutionary significance of lateral gene transfer has broad implications for our understanding of microbial biology, not only in terms of evolution, but also in terms of human health. Mechanisms of lateral gene transfer include: transformation, transduction, conjugation, and gene transfer agents. Each of these transfer mechanisms leaves distinct and recognizable molecular footprints in genome sequences. The molecular details of these footprints betray the workings of the corresponding mechanisms in nature, but their relative contributions to the evolution of sequenced genomes have so far not been investigated. By identifying these footprints one can specify and quantify the relative contribution of the different LGT mechanisms during prokaryote genome evolution and thereby uncover more of the biology underlying prokaryote evolution in nature. The goal of this proposal is to quantify those contributions and to bring forth a general computer-based model of prokaryote genome evolution that approximates the underlying evolutionary process far more realistically than phylogenetic trees alone possibly can. Here I propose to apply directed networks to the study of prokaryotic genome evolution in an evolutionary model that allows both for vertical inheritance and for lateral gene transfer events. With methods to identify gene donors, all recent LGTs can be described in a single directed network. This is a fundamentally new, biologically more realistic and evolutionarily more accurate, general computational model of prokaryote genome evolution. Such a model will substantially enrich our ability to understand the process of prokaryote evolution as it is recorded in genomic and metagenomic data.

1 500 000 €

Start date: 2012-07-01, End date: 2018-06-30

Darwin suggested that natural selection not only leads to adaptation but also promotes the origin of species. Ecological speciation acts through divergent natural selection and one of the most informative circumstances in which one can investigate how adaptive traits and how species evolve – and what the genetic basis of species differences and adaptations are - are repeated adaptive radiations that are based on parallel adaptations that evolved more than once. In only a few species has the genetic basis of adaptations been identified so far. It is not generally known what portion of the genome, what kind of genes and what kind of genetic changes cause adaptations. The investigation of the genetics of species formation and adaptations requires the comparative investigation of genetic divergence in the entire genome. This is now possible by applying recent methods in next-generation sequencing technology to a tractable group of closely related species that vary in how far speciation and adaptive divergence has proceeded. In the crater lakes of Nicaragua a natural experiment is taken place where several adaptive radiations of cichlid fish formed independently from two large source lakes within only a few thousand years. These extremely young adaptive radiations consist of species that arose in sympatry and evolved parallel adaptations repeatedly in their new habitats. We will investigate the mechanisms of natural selection and identify the genetic basis of species differences and parallel adaptations - they could be standing genetic variation or repeated de novo mutations - through comparative genomic analyses that will include the establishing of a reference genome, genome resequencing, QTL analyses, population genomics, and linkage and association maps. Then we could test the causal relationship between identified candidate genes and the phenotypic differences and parallel adaptations through functional analyses.

2 338 000 €

Start date: 2012-10-01, End date: 2018-09-30

HIV is one of the most rapidly evolving organisms known. Understanding its evolutionary dynamics is essential for successful drug treatment or vaccine design. At the same time, this rapid evolution makes HIV an ideal model system to study fundamental problems in evolutionary dynamics: In HIV, one can directly observe evolution over genetic distances that correspond to millions of years of evolution in other organisms. This proposal combines time series of ultra-deep sequence data of HIV from individual patients, functional information on drug resistance, and methods from statistical physics to study evolution. The sequence data will observe the dynamics of the genotype distribution in the population, while the exceptionally well characterized biology of HIV will allow the assignment of functional significance to the observed genotypic changes. These two levels of description will be integrated by theoretical models that describe how selection on phenotypes feeds back on the genotype distribution. Specifically, we will determine the fundamental parameters of HIV evolution such as selection strength, recombination rates, and the patterns of genetic interactions from the time resolved data obtained by deep sequencing. We will use the data base of viral sequences that evolved in response to drug treatment to infer the fitness landscapes of drug resistance. These two projects will be integrated in a quantitative model of drug resistance evolution. In a third project, we will quantify how genetic interactions affect the formation of circulant recombinant forms of HIV. Using HIV as a model system, we will develop and test theories of multi-locus evolution, characterize fitness landscapes and genetic interactions, and quantify the impact of recombination on HIV evolution.

1 155 859 €

Start date: 2011-03-01, End date: 2016-02-29