Research

We work on four main themes in evolutionary biology.

1) Speciation

Research on this topic focuses on the processes both driving and constraining the formation of new species. Both comparative (e.g., Funk et al. 2006 PNAS, Nosil 2013 Evolution) and experimental (e.g., Nosil et al. 2002 Nature, Nosil and Crespi 2006 PNAS) approaches are used to address these issues. This work is closely tied to that on genome evolution, described below, and current topics being investigated in speciation are the role of chemical communication in sexual isolation and reinforcement (see home page of Rudy Riesch), the genomic basis of traits affecting extrinsic reproductive isolation (see home page of Aaron Comeault), and the role of genetic conflict in speciation (e.g., Crespi and Nosil 2013 TREE).

2) Genome Evolution

Research into the causes of genome evolution has been re-vitalized by the advent of next-generation sequencing. However, the field is still in its infancy and much work remains to be done to develop explicit hypotheses for how genomes evolve and implement tests that can distinguish among alternative hypotheses. In this regard, work in the lab focuses on combining ecological, experimental, computational, and genomic data to study genome evolution. This work is closely tied to that on speciation described above. Some example studies concern genomic divergence during sympatric speciation of Rhagoletis flies (e.g., Michel et al. 2010 PNAS) and the genomic consequences of multiple speciation processes in Timema stick insects (e.g., Nosil et al. 2012 Proc B, Gompert et al. 2014 Ecology Letters, Soria-Carrasco et al. Science 2014). Current projects are examining genome evolution across disparate time scales, for example using the adaptive radiation of Timema stick insects (see home page of Moritz Muschick).

Figure 6. of Gompert et al. 2014, credit: Rosa Marin.

figure63) Eco-evolutionary Dynamics

Evolutionary change in individual species has been hypothesized to have far-reaching consequences for entire ecological communities, and such coupling of ecological and evolutionary dynamics (eco-evolutionary dynamics) has been demonstrated for various systems. However, the relative importance of evolutionary dynamics for ecological dynamics remains unclear. We are investigating how spatial patterns of local adaptation in the stick insect Timema cristinae, driven by natural selection, gene flow and founder effects, structure metapopulations, arthropod communities, and multitrophic interactions (Farkas et al. 2013 Curr Bio).

Graphical abstract of Farkas et al. 2013 Current Biology, credit: Rosa Marin.

4) Theoretical Models

In addition to empirical work, I collaborate on theoretical models of speciation, genome evolution, and eco-evolutionary dynamics (see Collaborators page, particularly Jeff Feder, Sam Flaxman, and Ilkka Hanski). Example projects have focused on speciation via adaptation to similar ecological environments (e.g., Nosil and Flaxman 2011 Proc B), the role of genetic hitchhiking in speciation and genome evolution (e.g., Feder and Nosil 2010 Evolution, Flaxman et al. 2013 Evolution, Flaxman et al. Mol Ecol 2014), and the significance of structural variants within genomes, such as chromosomal inversions, for evolution (e.g., Feder and Nosil 2009 Evolution, Feder et al. 2011 Evolution).


Resources

Computing power

The Nosil Lab of Evolutionary Biology (http://nosil-lab.group.shef.ac.uk) has exclusive access to a high-capacity storage server with 60 TB of capacity and a high-performance computer with 48 cores and 256 GB of memory. These state of art computer resources fulfil the requirements of computational power, storage capacity, and flexibility required for processing and analysing the large genomic datasets generated by high-throughput technologies. In addition, the University of Sheffield provides free additional computational power in the form of the Iceberg HPC cluster (http://www.shef.ac.uk/wrgrid/iceberg). Iceberg is especially well suited for processing large numbers of jobs in parallel: it has 3,440 processors, over 30 TB of distributed memory, and the nodes are interconnected through a high bandwidth, low latency network. The cluster also has 8 NVIDIA Tesla M2070 (448 cores, 6 GB RAM) and 8 NVIDIA Tesla K40M (2,880 cores, 12 GB RAM) GPU units that allow for cutting-edge GPGPU computation. Finally, it is also possible to purchase additional storage and dedicated computation time through the Corporate Information and Computing Services of the University of Sheffield, which adds extra flexibility to cope with unexpected peaks of computational work.


We are largely funded by a European Research Council (ERC) Starter Grant and a Royal Society of London University Research Fellowship to P.N.

Other sources of funding (allocated to various lab members and collaborators) include the Natural Environmental Research Council (NERC) of the UK, the Unity of Knowledge Fund (UKF), the Human Frontiers Science Program (HFSP), the Japanese Society for the Promotion of Science (JSPS), and the Swiss National Science Foundation (SNSF).

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