Identification of a nuclear localization signal of a yeast ribosomal protein.

To identify a signal involved in transporting a ribosomal protein to the nucleus, we constructed hybrid genes encoding amino-terminal segments of yeast ribosomal protein L3 joined to the amino-terminal end of the entire Escherichia coli beta-galactosidase molecule. The subcellular locations of the corresponding hybrid proteins in yeast were determined by in situ immunofluorescence. The first 21 amino acids of L3 were sufficient to localize beta-galactosidase to the nucleus. This region shows limited homology to portions of other nuclear proteins identified as essential for their transport. Larger fusion proteins were also localized to the nucleus. However, a hybrid protein containing all but the 14 carboxyl-terminal amino acids from L3 initially failed to localize; this defect was corrected by inserting a glycine- and proline-containing bridge between the L3 and beta-galactosidase moieties. The renovated protein was able to associate with ribosomes, suggesting that, in addition to entering the nucleus, this hybrid polypeptide was assembled into 60S ribosomal subunits that were subsequently exported to the cytoplasm

Topographic, Hydraulic, and Vegetative Controls on Bar and Island Development in Mixed Bedrock‐Alluvial, Multichanneled, Dryland Rivers

We investigate processes of bedrock‐core bar and island development in a bedrock‐influenced anastomosed reach of the Sabie River, Kruger National Park (KNP), eastern South Africa. For sites subject to alluvial stripping during an extreme flood event (~4470‐5630 m3 s‐1) in 2012, pre‐ and post‐flood aerial photographs and LiDAR data, 2D morphodynamic simulations, and field observations reveal that the thickest surviving alluvial deposits tend to be located over bedrock topographic lows. At a simulated peak discharge (~4500 m3 s‐1), most sediment (sand, fine gravel) is mobile but localized deposition on bedrock topographic highs is possible. At lower simulated discharges (<1000 m3 s‐1), topographic highs are not submerged, and deposition occurs in lower elevation areas, particularly in areas disconnected from the main channels during falling stage. Field observations suggest that in addition to discharge, rainwash between floods may redistribute sediments from bedrock topographic highs to lower elevation areas, and also highlight the critical role of vegetation colonization in bar stability, and in trapping of additional sediment and organics. These findings challenge the assumptions of preferential deposition on topographic highs that underpin previous analyses of KNP river dynamics, and are synthesized in a new conceptual model that demonstrates how initial bedrock topographic lows become topographic highs (bedrock core‐bars and islands) in the latter stages of sediment accumulation. The model provides particular insight into the development of mixed bedrock‐alluvial anastomosing along the KNP rivers, but similar processes of bar/island development likely occur along numerous other bedrock‐influenced rivers across dryland southern Africa and farther afield

Origin of Irreversibility of Cell Cycle Start in Budding Yeast

In budding yeast, the commitment to entry into a new cell division cycle is made irreversible by positive feedback-driven expression of the G1 cyclins Cln1,2

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Many applications, related to autonomous mobile robots, require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue and handle cooperatively some distributed targets. This problem is formulated by first defining an optimization model and then considering two sub-problems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit a certain number of robots to deal with the found target together. For this latter purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization, and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete the mission. Simulation results indicate that the firefly-based strategy usually provides superior performance and can reduce the wastage of energy, especially in complex scenarios

Sex-specific local life-history adaptation in surface- and cave-dwelling Atlantic mollies (Poecilia mexicana)

Cavefishes have long been used as model organisms showcasing adaptive diversification, but does adaptation to caves also facilitate the evolution of reproductive isolation from surface ancestors? We raised offspring of wild-caught surface- and cave-dwelling ecotypes of the neotropical fish Poecilia mexicana to sexual maturity in a 12-month common garden experiment. Fish were raised under one of two food regimes (high vs. low), and this was crossed with differences in lighting conditions (permanent darkness vs. 12:12 h light:dark cycle) in a 2 × 2 factorial design, allowing us to elucidate potential patterns of local adaptation in life histories. Our results reveal a pattern of sex-specific local life-history adaptation: Surface molly females had the highest fitness in the treatment best resembling their habitat of origin (high food and a light:dark cycle), and suffered from almost complete reproductive failure in darkness, while cave molly females were not similarly affected in any treatment. Males of both ecotypes, on the other hand, showed only weak evidence for local adaptation. Nonetheless, local life-history adaptation in females likely contributes to ecological diversification in this system and other cave animals, further supporting the role of local adaptation due to strong divergent selection as a major force in ecological speciation

Speeding Up Microevolution: The Effects of Increasing Temperature on Selection and Genetic Variance in a Wild Bird Population

The authors show that environmental variation may lead to a positive association between the annual strength of selection and expression of genetic variance in a wild bird population, which can speed up microevolution and have important consequences for how fast natural populations adapt to environmental changes

Functional Maps of Protein Complexes from Quantitative Genetic Interaction Data

Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relationships by integration of quantitative genetic interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate that this method is >50% more accurate at identifying functionally related protein pairs than previous approaches. Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits. Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism. These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function

Combined effects of precipitation and nitrogen deposition on native and invasive winter annual production in California deserts

Primary production in deserts is limited by soil moisture and N availability, and thus is likely to be influenced by both anthropogenic N deposition and precipitation regimes altered as a consequence of climate change. Invasive annual grasses are particularly responsive to increases in N and water availabilities, which may result in competition with native forb communities. Additionally, conditions favoring increased invasive grass production in arid and semi-arid regions can increase fire risk, negatively impacting woody vegetation that is not adapted to fire. We conducted a seeded garden experiment and a 5-year field fertilization experiment to investigate how winter annual production is altered by increasing N supply under a range of water availabilities. The greatest production of invasive grasses and native forbs in the garden experiment occurred under the highest soil N (inorganic N after fertilization = 2.99 g m−2) and highest watering regime, indicating these species are limited by both water and N. A classification and regression tree (CART) analysis on the multi-year field fertilization study showed that winter annual biomass was primarily limited by November–December precipitation. Biomass exceeded the threshold capable of carrying fire when inorganic soil N availability was at least 3.2 g m−2 in piñon-juniper woodland. Due to water limitation in creosote bush scrub, biomass exceeded the fire threshold only under very wet conditions regardless of soil N status. The CART analyses also revealed that percent cover of invasive grasses and native forbs is primarily dependent on the timing and amount of precipitation and secondarily dependent on soil N and site-specific characteristics. In total, our results indicate that areas of high N deposition will be susceptible to grass invasion, particularly in wet years, potentially reducing native species cover and increasing the risk of fire

A complete set of nascent transcription rates for yeast genes

The amount of mRNA in a cell is the result of two opposite reactions: transcription and mRNA degradation. These reactions are governed by kinetics laws, and the most regulated step for many genes is the transcription rate. The transcription rate, which is assumed to be exercised mainly at the RNA polymerase recruitment level, can be calculated using the RNA polymerase densities determined either by run-on or immunoprecipitation using specific antibodies. The yeast Saccharomyces cerevisiae is the ideal model organism to generate a complete set of nascent transcription rates that will prove useful for many gene regulation studies. By combining genomic data from both the GRO (Genomic Run-on) and the RNA pol ChIP-on-chip methods we generated a new, more accurate nascent transcription rate dataset. By comparing this dataset with the indirect ones obtained from the mRNA stabilities and mRNA amount datasets, we are able to obtain biological information about posttranscriptional regulation processes and a genomic snapshot of the location of the active transcriptional machinery. We have obtained nascent transcription rates for 4,670 yeast genes. The median RNA polymerase II density in the genes is 0.078 molecules/kb, which corresponds to an average of 0.096 molecules/gene. Most genes have transcription rates of between 2 and 30 mRNAs/hour and less than 1% of yeast genes have >1 RNA polymerase molecule/gene. Histone and ribosomal protein genes are the highest transcribed groups of genes and other than these exceptions the transcription of genes is an infrequent phenomenon in a yeast cell

Mutualism and Adaptive Divergence: Co-Invasion of a Heterogeneous Grassland by an Exotic Legume-Rhizobium Symbiosis

Species interactions play a critical role in biological invasions. For example, exotic plant and microbe mutualists can facilitate each other's spread as they co-invade novel ranges. Environmental context may influence the effect of mutualisms on invasions in heterogeneous environments, however these effects are poorly understood. We examined the mutualism between the legume, Medicago polymorpha, and the rhizobium, Ensifer medicae, which have both invaded California grasslands. Many of these invaded grasslands are composed of a patchwork of harsh serpentine and relatively benign non-serpentine soils. We grew legume genotypes collected from serpentine or non-serpentine soil in both types of soil in combination with rhizobium genotypes from serpentine or non-serpentine soils and in the absence of rhizobia. Legumes invested more strongly in the mutualism in the home soil type and trends in fitness suggested that this ecotypic divergence was adaptive. Serpentine legumes had greater allocation to symbiotic root nodules in serpentine soil than did non-serpentine legumes and non-serpentine legumes had greater allocation to nodules in non-serpentine soil than did serpentine legumes. Therefore, this invasive legume has undergone the rapid evolution of divergence for soil-specific investment in the mutualism. Contrary to theoretical expectations, the mutualism was less beneficial for legumes grown on the stressful serpentine soil than on the non-serpentine soil, possibly due to the inhibitory effects of serpentine on the benefits derived from the interaction. The soil-specific ability to allocate to a robust microbial mutualism may be a critical, and previously overlooked, adaptation for plants adapting to heterogeneous environments during invasion