1,161 research outputs found

    Nitrogen and phosphorus limitation of oceanic microbial growth during spring in the Gulf of Aqaba

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    Bioassay experiments were performed to identify how growth of key groups within the microbial community was simultaneously limited by nutrient (nitrogen and phosphorus) availability during spring in the Gulf of Aqaba's oceanic waters. Measurements of chlorophyll a (chl a) concentration and fast repetition rate (FRR) fluorescence generally demonstrated that growth of obligate phototrophic phytoplankton was co-limited by N and P and growth of facultative aerobic anoxygenic photoheterotropic (AAP) bacteria was limited by N. Phytoplankton exhibited an increase in chl a biomass over 24 to 48 h upon relief of nutrient limitation. This response coincided with an increase in photosystem II (PSII) photochemical efficiency (F v /F m), but was preceded (within 24 h) by a decrease in effective absorption crosssection (σPSII) and electron turnover time (τ). A similar response for τ and bacterio-chl a was observed for the AAPs. Consistent with the up-regulation of PSII activity with FRR fluorescence were observations of newly synthesized PSII reaction centers via low temperature (77K) fluorescence spectroscopy for addition of N (and N + P). Flow cytometry revealed that the chl a and thus FRR fluorescence responses were partly driven by the picophytoplankton (æ10 μm) community, and in particular Synechococcus. Productivity of obligate heterotrophic bacteria exhibited the greatest increase in response to a natural (deep water) treatment, but only a small increase in response to N and P addition, demonstrating the importance of additional substrates (most likely dissolved organic carbon) in moderating the heterotrophs. These data support previous observations that the microbial community response (autotrophy relative to heterotrophy) is critically dependent upon the nature of transient nutrient enrichment. © Inter-Research 2009

    Rachis brittleness in a hybrid–parent barley (Hordeum vulgare) breeding germplasm with different combinations at the non‐brittle rachis genes

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    Two dominant, closely linked and complementary genes, Btr1 and Btr2, control rachis brittleness in barley. Recessive mutations in any of these genes turn the fragile rachis (brittle) into a tough rachis phenotype (non‐brittle). The cross of parents with alternative mutations in the btr genes leads to a brittle F1 hybrid that presents grain retention problems. We evaluated rachis fragility through a mechanical test and under natural conditions, in F1 crosses with different compositions at the btr genes. Brittleness was significantly higher in Btr1btr1Btr2btr2 crosses compared to hybrids and inbred parents carrying one of the mutations (btr1btr1Btr2Btr2/Btr1Btr1btr2btr2). This fact could jeopardize the efficient harvest of hybrids bearing alternative mutations, reducing the choice of possible crosses for hybrid barley breeding and hindering the exploitation of potential heterotic patterns. Furthermore, non‐brittle hybrids showed higher brittleness than inbreds, suggesting the presence of other dominant factors affecting the trait. In conclusion, this work encourages a deeper study of the genetic control of the rachis brittleness trait and urges the consideration of rachis tenacity as a target for hybrid barley breeding.This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness grants RFP2015 00006‐00‐00, and RTA2012‐00033‐C03‐02, and by the contract “Iberia region hybrid barley variety development and understanding effects of adaptation genes in hybrids,” between CSIC and Syngenta Crop Protection AG, which included funding for MFC PhD scholarship

    Domestication as innovation : the entanglement of techniques, technology and chance in the domestication of cereal crops

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    The origins of agriculture involved pathways of domestication in which human behaviours and plant genetic adaptations were entangled. These changes resulted in consequences that were unintended at the start of the process. This paper highlights some of the key innovations in human behaviours, such as soil preparation, harvesting and threshing, and how these were coupled with genetic ‘innovations’ within plant populations. We identify a number of ‘traps’ for early cultivators, including the needs for extra labour expenditure on crop-processing and soil fertility maintenance, but also linked gains in terms of potential crop yields. Compilations of quantitative data across a few different crops for the traits of nonshattering and seed size are discussed in terms of the apparently slow process of domestication, and parallels and differences between different regional pathways are identified. We highlight the need to bridge the gap between a Neolithic archaeobotanical focus on domestication and a focus of later periods on crop-processing activities and labour organization. In addition, archaeobotanical data provide a basis for rethinking previous assumptions about how plant genetic data should be related to the origins of agriculture and we contrast two alternative hypotheses: gradual evolution with low selection pressure versus metastable equilibrium that prolonged the persistence of ‘semi-domesticated’ populations. Our revised understanding of the innovations involved in plant domestication highlight the need for new approaches to collecting, modelling and integrating genetic data and archaeobotanical evidence

    Deletion of Mgr2p Affects the Gating Behavior of the TIM23 Complex

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    The TIM23 complex is a hub for translocation of preproteins into or across the mitochondrial inner membrane. This dual sorting mechanism is currently being investigated, and in yeast appears to be regulated by a recently discovered subunit, the Mgr2 protein. Deletion of Mgr2p has been found to delay protein translocation into the matrix and accumulation in the inner membrane. This result and other findings suggested that Mgr2p controls the lateral release of inner membrane proteins harboring a stop-transfer signal that follows an N-terminal amino acid signal. However, the mechanism of lateral release is unknown. Here, we used patch clamp electrophysiology to investigate the role of Mgr2p on the channel activity of TIM23. Deletion of Mgr2p decreased normal channel frequency and increased occurrence of a residual TIM23 activity. The residual channel lacked gating transitions but remained sensitive to synthetic import signal peptides. Similarly, a G145L mutation in Tim23p displaced Mgr2p from the import complex leading to gating impairment. These results suggest that Mgr2p regulates the gating behavior of the TIM23 channel.Peer reviewe

    Status and Potential of Single-cell Transcriptomics for Understanding Plant Development and Functional Biology

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    Funding Information University of Western Australia Acknowledgments The authors would like to extend sincere thanks to Robert Salomon for inspiring to write this manuscript. Resources were provided by The University of Western Australia.Peer reviewedPostprin

    Geographic mosaics and changing rates of cereal domestication

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    Domestication is the process by which plants or animals evolved to fit a human-managed environment, and it is marked by innovations in plant morphology and anatomy that are in turn correlated with new human behaviours and technologies for harvesting, storage and field preparation. Archaeobotanical evidence has revealed that domestication was a protracted process taking thousands of plant generations. Within this protracted process there were changes in the selection pressures for domestication traits as well as variation across a geographic mosaic of wild and cultivated populations. Quantitative data allow us to estimate the changing selection coefficients for the evolution of non-shattering (domestic-type seed dispersal) in Asian rice (Oryza sativa L.), barley (Hordeum vulgare L.), emmer wheat (Triticum dicoccon (Shrank) Schübl.) and einkorn wheat (Triticum monococcum L.). These data indicate that selection coefficients tended to be low, but also that there were inflection points at which selection increased considerably. For rice, selection coefficients of the order of 0.001 prior to 5500 BC shifted to greater than 0.003 between 5000 and 4500 BC, before falling again as the domestication process ended 4000–3500 BC. In barley and the two wheats selection was strongest between 8500 and 7500 BC. The slow start of domestication may indicate that initial selection began in the Pleistocene glacial era

    Weak pairwise correlations imply strongly correlated network states in a neural population

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    Biological networks have so many possible states that exhaustive sampling is impossible. Successful analysis thus depends on simplifying hypotheses, but experiments on many systems hint that complicated, higher order interactions among large groups of elements play an important role. In the vertebrate retina, we show that weak correlations between pairs of neurons coexist with strongly collective behavior in the responses of ten or more neurons. Surprisingly, we find that this collective behavior is described quantitatively by models that capture the observed pairwise correlations but assume no higher order interactions. These maximum entropy models are equivalent to Ising models, and predict that larger networks are completely dominated by correlation effects. This suggests that the neural code has associative or error-correcting properties, and we provide preliminary evidence for such behavior. As a first test for the generality of these ideas, we show that similar results are obtained from networks of cultured cortical neurons.Comment: Full account of work presented at the conference on Computational and Systems Neuroscience (COSYNE), 17-20 March 2005, in Salt Lake City, Utah (http://cosyne.org

    Can we identify non-stationary dynamics of trial-to-trial variability?"

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    Identifying sources of the apparent variability in non-stationary scenarios is a fundamental problem in many biological data analysis settings. For instance, neurophysiological responses to the same task often vary from each repetition of the same experiment (trial) to the next. The origin and functional role of this observed variability is one of the fundamental questions in neuroscience. The nature of such trial-to-trial dynamics however remains largely elusive to current data analysis approaches. A range of strategies have been proposed in modalities such as electro-encephalography but gaining a fundamental insight into latent sources of trial-to-trial variability in neural recordings is still a major challenge. In this paper, we present a proof-of-concept study to the analysis of trial-to-trial variability dynamics founded on non-autonomous dynamical systems. At this initial stage, we evaluate the capacity of a simple statistic based on the behaviour of trajectories in classification settings, the trajectory coherence, in order to identify trial-to-trial dynamics. First, we derive the conditions leading to observable changes in datasets generated by a compact dynamical system (the Duffing equation). This canonical system plays the role of a ubiquitous model of non-stationary supervised classification problems. Second, we estimate the coherence of class-trajectories in empirically reconstructed space of system states. We show how this analysis can discern variations attributable to non-autonomous deterministic processes from stochastic fluctuations. The analyses are benchmarked using simulated and two different real datasets which have been shown to exhibit attractor dynamics. As an illustrative example, we focused on the analysis of the rat's frontal cortex ensemble dynamics during a decision-making task. Results suggest that, in line with recent hypotheses, rather than internal noise, it is the deterministic trend which most likely underlies the observed trial-to-trial variability. Thus, the empirical tool developed within this study potentially allows us to infer the source of variability in in-vivo neural recordings

    Genetic structure and differentiation in cultivated fig (Ficus carica L.)

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    One hundred ninety-four germplasm accessions of fig representing the four fig types, Common, Smyrna, San Pedro, and Caprifig were analyzed for genetic diversity, structure, and differentiation using genetic polymorphism at 15 microsatellite loci. The collection showed considerable polymorphism with observed number of alleles per locus ranging from four for five different loci, MFC4, LMFC14, LMFC22, LMFC31 and LMFC35 to nine for LMFC30 with an average of 4.9 alleles per locus. Seven of the 15 loci included in the genetic structure analyses exhibited significant deviation from panmixia, of which two showed excess and five showed deficiency of heterozygote. The cluster analysis (CA) revealed ten groups with 32 instances of synonymy among cultivars and groups differed significantly for frequency and composition of alleles for different loci. The principal components analysis (PCA) confirmed the results of CA with some groups more differentiated than the others. Further, the model based Bayesian approach clustering suggested a subtle population structure with mixed ancestry for most figs. The gene diversity analysis indicated that much of the total variation is found within groups (HG/HT = 0.853; 85.3%) and the among groups within total component (GGT = 0.147) accounted for the remaining 14.7%, of which ~64% accounted for among groups within clusters (GGC = 0.094) and ~36% among clusters (GCT = 0.053). The analysis of molecular variance (AMOVA) showed approximately similar results with nearly 87% of variation within groups and ~10% among groups within clusters, and ~3% among clusters. Overall, the gene pool of cultivated fig analyzed possesses substantial genetic polymorphism but exhibits narrow differentiation. It is evident that fig accessions from Turkmenistan are somewhat genetically different from the rest of the Mediterranean and the Caucasus figs. The long history of domestication and cultivation with widespread dispersal of cultivars with many synonyms has resulted in a great deal of confusion in the identification and classification of cultivars in fig
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