Evolution of Plant Niche Construction Traits in Biogeomorphic Landscapes

By virtue of niche construction traits, plants play a significant role in shaping landscapes. The resultant outcome is a change in the selective environment, which influences the evolution of these same plants. So far almost all biogeomorphic models have assumed that niche construction traits are invariant in time. On the other hand, niche construction studies have assumed that independent abiotic changes are either nonexistent or are simply linear. Here, I considered the concomitant evolution of plant niche construction traits during landscape development. I constructed a geo-evolutionary model that couples a population genetic module with a landscape development module. Allowing plants to evolve always results in landforms different from those that appear when evolution is not accounted for. The topographic difference between cases with and without evolution ranges from a small difference in the steady-state topography, to drastic differences in landforms. The amount of difference is contingent upon forms of landscape development and the strength of geo-evolutionary coupling. Allowing the landscape to develop while evolution occurs changes evolutionary trajectories for niche construction traits. The landscape can even develop spatial structures that suppress selection. Model results clearly support the need to integrate niche construction theory and biogeomorphology to better understand both.

Phylogenetic history of vascular plant metabolism revealed using a macroevolutionary common garden

While the fundamental biophysics of C 3 photosynthesis is highly conserved across plants, substantial leaf structural and enzymatic variation translates into variability in rates of carbon assimilation. Although this variation is well documented, it remains poorly understood how photosynthetic rates evolve, and whether macroevolutionary changes are related to the evolution of leaf morphology and biochemistry. A substantial challenge in large-scale comparative studies is disentangling evolutionary adaptation from environmental acclimation. We overcome this by using a ‘macroevolutionary common garden’ approach in which we measured metabolic traits ( J max and V cmax ) from 111 phylogenetically diverse species in a shared environment. We find substantial phylogenetic signal in these traits at moderate phylogenetic timescales, but this signal dissipates quickly at deeper scales. Morphological traits exhibit phylogenetic signal over much deeper timescales, suggesting that these are less evolutionarily constrained than metabolic traits. Furthermore, while morphological and biochemical traits (LMA, N area and C area ) are weakly predictive of J max and V c max , evolutionary changes in these traits are mostly decoupled from changes in metabolic traits. This lack of tight evolutionary coupling implies that it may be incorrect to use changes in these functional traits in response to global change to infer that photosynthetic strategy is also evolving.

A non-olfactory shark adenosine receptor activates CFTR with unique pharmacology and structural features

Adenosine receptors (ADORs) are G-protein coupled purinoceptors that have several functions including regulation of chloride secretion via CFTR in human airway and kidney. We cloned an ADOR from Squalus acanthias (shark) that likely regulates CFTR in the rectal gland. Phylogenic- and expression- analyses indicate that elasmobranch ADORs are non-olfactory, and appear to represent extant predecessors of mammalian ADORs. We therefore designate the shark ADOR as the A0 receptor. We co-expressed A0 with CFTR in Xenopus laevis oocytes and characterized the coupling of A0 to the chloride channel. Two electrode voltage clamping was performed and current-voltage (I-V) responses were recorded to monitor CFTR status. Only in A0- and CFTR- co-injected oocytes did adenosine analogs produce a significant concentration-dependent activation of CFTR consistent with its electrophysiological signature. A pharmacological profile for A0 was obtained for ADOR agonists and antagonists that differed markedly from all mammalian ADOR subtypes (agonists: R-PIA > S-PIA > CGS21680 > CPA > 2ClADO > CV1808 = DPMA > NECA) and (antagonists: DPCPX > PD115199 > 8PT > CGC > CGS15943). Structures of human ADORs permitted a high-confidence homology model of the shark A0 core which revealed unique structural features of ancestral receptors. We conclude: (1) A0 is a novel and unique adenosine receptor ancestor by functional and structural criteria; (2) A0 likely activates CFTR in vivo and this receptor activates CFTR in oocytes indicating an evolutionary coupling between ADORs and chloride secretion; and (3) A0 appears to be a non-olfactory evolutionary ancestor of all four mammalian ADOR subtypes.

A Reproducibility Analysis-based Statistical Framework for Residue-Residue Evolutionary Coupling Detection

Direct coupling analysis (DCA) has been widely used to predict residue-residue contacts to assist protein/RNA structure and interaction prediction. However, effectively selecting residue pairs for contact prediction according to the result of DCA is a non-trivial task, since the number of highly predictive residue pairs and the coupling scores obtained from DCA are highly dependent on the number and the length of the homologous sequences forming the multiple sequence alignment, the detailed settings of the DCA algorithm, the functional characteristics of the macromolecule, etc. In this study, we present a general statistical framework for selecting predictive residue pairs through significant evolutionary coupling detection, referred to as IDR-DCA, which is based on reproducibility analysis of the coupling scores from replicated DCA. IDR-DCA was applied to select residue pairs for contact prediction for 150 proteins, 30 protein-protein interactions and 36 RNAs, in which we applied three widely used DCA software to perform the DCA. We show that with the application of IDR-DCA, the predictive residue pairs can be effectively selected through a universal threshold independent on the DCA software.

Humans as the world’s greatest eco-evolutionary force

Humans are dominant global drivers of ecological and evolutionary change, rearranging ecosystems and natural selection in many ways. Here, we show increasing evidence that human activity also plays a disproportionate role in shaping the eco-evolutionary potential of systems. We suggest the net outcome of human influences on trait change, ecology, and the feedbacks that link them, will often (but not always) be to increase the intensity of eco-evolutionary coupling, with important consequences for stability and resilience of populations, communities, and ecosystems. We also integrate existing ecological and evolutionary metrics to predict and manage the eco-evolutionary dynamics of human-impacted systems. To support this framework, we use a simple eco-evo feedbacks model to show that factors affecting coupling strength are major determinants of eco-evolutionary dynamics. Our framework suggests that proper management of anthropogenic effects requires a science of human-effects on eco-evolutionary potential.

Evolutionary coupling range varies widely among enzymes

Recent studies proposed that active sites induce long-range evolutionary constraints in enzymes. However, the prevalence of such long-range evolutionary coupling is unknown and its relationship to the underlying physical coupling is unclear. Here I show that evolutionary coupling is not universally long range, but that range varies widely among enzymes, from 2Å to 20Å, influencing from 10% to 87% of protein sites. Moreover, evolutionary coupling range is not determined by physical coupling, which is short-range for all enzymes, but by selection pressure. The reason for this is that increasing selection pressure turns small physical couplings into large evolutionary couplings.