Cryptic behaviours, inverse genetic landscapes, and spatial avoidance of inbreeding in the Pacific jumping mouse

Although the behaviour of individuals is known to impact the genetic make-up of a population, observed behavioural patterns do not always correspond to patterns of genetic structure. In particular, philopatric or dispersal-limited species often display lower-than-expected values of relatedness or inbreeding suggestive of the presence of cryptic migration, dispersal, or mating behaviours. I used a combination of microsatellite and mark-recapture data to test for the influence of such behaviours in a dispersal-limited species, the Pacific jumping mouse, within a semi-isolated population over three seasons. Despite short dispersal distances and a low rate of first generation migrants, heterozygosities were high and inbreeding values were low. Dispersal was male-biased; interestingly however, this pattern was only present when dispersal was considered to include movement away from paternal home range. Not unexpectedly, males were polygynous; notably, some females were also found to be polyandrous, selecting multiple neighbouring mates for their single annual litter. Patterns of genetic structure were consistent with these more inconspicuous behavioural patterns. Females were more closely related than males and isolation by distance was present only in females. Furthermore, detailed genetic landscapes revealed the existence of strong, significant negative correlations, with areas of low genetic distance among females overlapping spatially with areas of high genetic distance among males. These results support the hypothesis that the detected cryptic components of dispersal and mating behaviour are reducing the likelihood of inbreeding in this population through paternally driven spatial mixing of male genotypes and polyandry of females.     

The foldability landscape of model proteins

Molecular evolution may be considered as a walk in a multidimensional fitness landscape, where the fitness at each point is associated with features such as the function, stability, and survivability of these molecules. We present a simple model for the evolution of protein sequences on a landscape with a precisely defined fitness function. We use simple lattice models to represent protein structures, with the ability of a protein sequence to fold into the structure with lowest energy, quantified as the foldability, representing the fitness of the sequence. The foldability of the sequence is characterized based on the spin glass model of protein folding. We consider evolution as a walk in this foldability landscape and study the nature of the landscape and the resulting dynamics. Selective pressure is explicitly included in this model in the form of a minimum foldability requirement. We find that different native structures are not evenly distributed in interaction space, with similar structures and structures with similar optimal foldabilities clustered together. Evolving proteins marginally fulfill the selective criteria of foldability. As the selective pressure is increased, evolutionary trajectories become increasingly confined to “neutral networks,” where the sequence and the interactions can be significantly changed while a constant structure is maintained. © 1997 John Wiley & Sons, Inc. Biopoly 42: 427–438, 1997     

Local interactions and the optimization of protein folding

The role of local interactions in protein folding has recently been the subject of some controversy. Here we investigate an extension of Zwanzig's simple and general model of folding in which local and nonlocal interactions are represented by functions of single and multiple conformational degrees of freedom, respectively. The kinetics and thermodynamics of folding are studied for a series of energy functions in which the energy of the native structure is fixed, but the relative contributions of local and nonlocal interactions to this energy are varied over a broad range. For funnel shaped energy landscapes, we find that 1) the rate of folding increases, but the stability of the folded state decreases, as the contribution of local interactions to the energy of the native structure increases, and 2) the amount of native structure in the unfolded state and the transition state vary considerably with the local interaction strength. Simple exponential kinetics and a well-defined free energy barrier separating folded and unfolded states are observed when nonlocal interactions make an appreciable contribution to the energy of the native structure; in such cases a transition state theory type approximation yields reasonably accurate estimates of the folding rate. Bumps in the folding funnel near the native state, which could result from desolvation effects, side chain freezing, or the breaking of nonnative contacts, significantly alter the dependence of the folding rate on the local interaction strength: the rate of folding decreases when the local interaction strength is increased beyond a certain point. A survey of the distribution of strong contacts in the protein structure database suggests that evolutionary optimization has involved both kinetics and thermodynamics: strong contacts are enriched at both very short and very long sequence separations. Proteins 29:282–291, 1997. © 1997 Wiley-Liss, Inc.     

Predicting structural effects in HIV-1 protease mutant complexes with flexible ligand docking and protein side-chain optimization

We present a computational approach for predicting structures of ligand-protein complexes and analyzing binding energy landscapes that combines Monte Carlo simulated annealing technique to determine the ligand bound conformation with the dead-end elimination algorithm for side-chain optimization of the protein active site residues. Flexible ligand docking and optimization of mobile protein side-chains have been performed to predict structural effects in the V32I/I47V/V82I HIV-1 protease mutant bound with the SB203386 ligand and in the V82A HIV-1 protease mutant bound with the A77003 ligand. The computational structure predictions are consistent with the crystal structures of these ligand-protein complexes. The emerging relationships between ligand docking and side-chain optimization of the active site residues are rationalized based on the analysis of the ligand-protein binding energy landscape. Proteins 33:295–310, 1998. © 1998 Wiley-Liss, Inc.     

Modeling Sequence-Space Exploration and Emergence of Epistatic Signals in Protein Evolution

During their evolution, proteins explore sequence space via an interplay between random mutations and phenotypic selection. Here, we build upon recent progress in reconstructing data-driven fitness landscapes for families of homologous proteins, to propose stochastic models of experimental protein evolution. These models predict quantitatively important features of experimentally evolved sequence libraries, like fitness distributions and position-specific mutational spectra. They also allow us to efficiently simulate sequence libraries for a vast array of combinations of experimental parameters like sequence divergence, selection strength, and library size. We showcase the potential of the approach in reanalyzing two recent experiments to determine protein structure from signals of epistasis emerging in experimental sequence libraries. To be detectable, these signals require sufficiently large and sufficiently diverged libraries. Our modeling framework offers a quantitative explanation for different outcomes of recently published experiments. Furthermore, we can forecast the outcome of time- and resource-intensive evolution experiments, opening thereby a way to computationally optimize experimental protocols.     

Improved management of farm dams increases vegetation cover,water quality,and macroinvertebrate biodiversity

In many farming landscapes, aquatic features, such as wetlands, creeks, and dams, provide water for stock and irrigation, while also acting as habitat for a range of plants and animals. Indeed, some species threatened by land‐use change may otherwise be considerably rarer—or even suffer extinction—in the absence of these habitats. Therefore, a critical issue for the maintenance of biodiversity in agricultural landscapes is the extent to which the management of aquatic systems can promote the integration of agricultural production and biodiversity conservation. We completed a cross‐sectional study in southern New South Wales (southeastern Australia) to quantify the efficacy of two concurrently implemented management practices—partial revegetation and control of livestock grazing—aimed at enhancing the vegetation structure, biodiversity value, and water quality of farm dams. We found that excluding livestock for even short periods resulted in increased vegetation cover. Relative to unenhanced dams (such as those that remained unfenced), those that had been enhanced for several years were characterized by reduced levels of turbidity, nutrients, and fecal contamination. Enhanced dams also supported increased richness and abundance of macroinvertebrates. In contrast, unenhanced control dams tended to have high abundance of a few macroinvertebrate taxa. Notably, differences remained between the macroinvertebrate assemblages of enhanced dams and nearby “natural” waterbodies that we monitored as reference sites. While the biodiversity value of semilotic, natural waterbodies in the region cannot be replicated by artificial lentic systems, we consider the extensive system of farm dams in the region to represent a novel ecosystem that may nonetheless support some native macroinvertebrates. Our results show that management interventions such as fencing and grazing control can improve water quality in farm dams, improve vegetation structure around farm dams, and support greater abundance and diversity of aquatic macroinvertebrates.     

Picking up the pieces: a biosphere reserve framework for a fragmented landscape – The Coastal Lowlands of the Western Cape, South Africa

The coastal lowlands of the Western Cape (CLWC) form part of the fynbos biome, an area renowned for its high levels of plant diversity and endemism. The vegetation of the CLWC has been severely reduced and fragmented, and is currently impacted on by agricultural, pastoral, coastal resort and urban development, as well as alien plant spread. Furthermore, most of the vegetation communities are under-represented within existing protected areas. In response to this urgent need for increased conservation efforts, an initiative to establish a UNESCO-MAB biosphere reserve in the area has been launched. The aim of this project was to use biological criteria to identify areas that could potentially contain the core areas and buffer zones of a biosphere reserve. A reserve selection algorithm was chosen which provides a flexible tool for selecting representative areas for protection. The algorithm is a step-wise heuristic, which has rules for including mandatory polygons, forcing adjacency, including desirable (e.g. Red Data Book plant species) and excluding undesirable features (e.g. bisection by major roads). Farm boundaries (cadastral units) were used as selection units, resulting in a total of 1717 parcels. The selection process was conducted three times with target areas set at 10%, 25% and 50% of the original extent of each vegetation type within the study area. Areas of 62834 ha, 121199 ha and 242397 ha, respectively, or 36% 49% and 76% of the available land in the study area being selected. It is recommended that the area identified as the 50% target area be considered the future site of core areas and buffer zones for the proposed biosphere reserve. The algorithm successfully maintained a high degree of connectivity between selected areas. This is important considering the high levels of plant beta diversity associated with edaphic gradients. Rather than presenting a definitive reserve system, this study provides a tool allowing biological criteria to be included explicitly within the negotiation process. As the biosphere reserve is assembled, priorities can be re-assessed.     

Relationship between Soil Arthropods and Soil Properties in a Suburb of Qianjiang City,Hubei, China

Nine categories of soil arthropods and 24 soil phy sicochemical properties were surveyed in 31 plots of a suburb of Qianjiang City, Hubei, China, in 1993 to 1994. Using factor analysis, 24 soil properties were reduced to five key soil factors (salt content, available K and P, organic matter, soil particles, Cd content), which were composed of 12 variables. Both simple correlation and canonical correlation analysis of the key soil factors and soil arthropods revealed positive correlations between Isopoda and Formicidae and the salt content factor, and between Chilopoda and the available P and K factor. Canonical correlation analysis also revealed a positive relationship between Formicidae, Isopoda, Diplopoda, and Staphylinidae and available K and P, and between Araneae, Staphylinidae, Diplopoda, and Formicidae and organic matter; and indicated a close relationship between Araneae, Staphylinidae, Diplopoda, and Formicidae and sandy loam soil. Results also indicated that Cd concentrations of 0.15?mg/kg to 0.41?mg/kg in soil with a high content of water did not significantly influence the nine arthropod categories.     

The importance of explicit chain representation in protein folding models: an examination of Ising-like models

A class of models that represents a protein chain as a sequence of "folded" and "unfolded" residues has recently been used to correlate rates and mechanisms of protein folding with the protein native structure. In order to better understand the conditions under which these "Ising-like" models apply, we compare results from this model to those obtained from an off-lattice model which uses the same potential function. We find that Ising-like models by construction impose folding via a highly sequential nucleation-condensation mechanism, which in turn leads to more rugged energy landscapes, fewer "pathways" to the native state, and in the specific case examined here, the cold shock protein A from Escherichia coli, a qualitative difference in the most likely order of events in folding.     

Detecting a hierarchical genetic population structure: the case study of the Fire Salamander (Salamandra salamandra) in Northern Italy

The multistep method here applied in studying the genetic structure of a low dispersal and philopatric species, such as the Fire Salamander Salamandra salamandra, was proved to be effective in identifying the hierarchical structure of populations living in broad‐leaved forest ecosystems in Northern Italy. In this study, 477 salamander larvae, collected in 28 sampling populations (SPs) in the Prealpine and in the foothill areas of Northern Italy, were genotyped at 16 specie‐specific microsatellites. SPs showed a significant overall genetic variation (Global F_ST = 0.032, P < 0.001). The genetic population structure was assessed by using STRUCTURE 2.3.4. We found two main genetic groups, one represented by SPs inhabiting the Prealpine belt, which maintain connections with those of the Eastern foothill lowland (PEF), and a second group with the SPs of the Western foothill lowland (WF). The two groups were significantly distinct with a Global F_ST of 0.010 (P < 0.001). While the first group showed a moderate structure, with only one divergent SP (Global F_ST = 0.006, P < 0.001), the second group proved more structured being divided in four clusters (Global F_ST = 0.017, P = 0.058). This genetic population structure should be due to the large conurbations and main roads that separate the WF group from the Prealpine belt and the Eastern foothill lowland. The adopted methods allowed the analysis of the genetic population structure of Fire Salamander from wide to local scale, identifying different degrees of genetic divergence of their populations derived from forest fragmentation induced by urban and infrastructure sprawl.