The Experts below are selected from a list of 249 Experts worldwide ranked by ideXlab platform

Philippe Nghe - One of the best experts on this subject based on the ideXlab platform.

  • Darwinian properties and their trade-offs in autocatalytic RNA reaction networks
    Nature communications, 2021
    Co-Authors: Sandeep Ameta, Simon Arsène, Sophie Foulon, Baptiste Saudemont, Bryce E. Clifton, Andrew D. Griffiths, Philippe Nghe
    Abstract:

    Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Autocatalytic networks have been discovered in various chemistries, but we lack a general understanding of how network topology controls the Darwinian properties of variation, Differential Reproduction, and heredity, which are mediated by the chemical composition. Using barcoded sequencing and droplet microfluidics, we establish a landscape of thousands of networks of RNAs that catalyze their own formation from fragments, and derive relationships between network topology and chemical composition. We find that strong variations arise from catalytic innovations perturbing weakly connected networks, and that growth increases with global connectivity. These rules imply trade-offs between Reproduction and variation, and between compositional persistence and variation along trajectories of network complexification. Overall, connectivity in reaction networks provides a lever to balance variation (to explore chemical states) with Reproduction and heredity (persistence being necessary for selection to act), as required for chemical evolution. Autocatalytic networks may have started evolution during the origin of life. Here, the authors establish a landscape of thousands of RNA networks by barcoded sequencing and microfluidics, and derive relationships between topology and Darwinian properties such as variation and Differential Reproduction.

  • Darwinian properties and their trade-offs in autocatalytic RNA reaction networks
    2019
    Co-Authors: Sandeep Ameta, Simon Arsène, Sophie Foulon, Baptiste Saudemont, Bryce E. Clifton, Andrew D. Griffiths, Philippe Nghe
    Abstract:

    Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Autocatalytic networks have been discovered in various chemistries, but we lack a general understanding of how network topology controls the Darwinian properties of variation, Differential Reproduction, and heredity, which are mediated by the chemical composition. Using barcoded sequencing and droplet microfluidics, we establish a landscape of thousands of networks of RNAs that catalyze their own formation from fragments, and derive relationships between network topology and chemical composition. We find that strong variations arise from catalytic innovations perturbing weakly connected networks, and that Reproduction increases with global connectivity. These rules imply trade-offs between Reproduction and variation, and between compositional persistence and variation along trajectories of network complexification. Overall, connectivity in reaction networks provides a lever to balance variation (to explore chemical states) with Reproduction and heredity (persistence being necessary for selection to act), as required for chemical evolution.

Jonathan Machta - One of the best experts on this subject based on the ideXlab platform.

Sandeep Ameta - One of the best experts on this subject based on the ideXlab platform.

  • Darwinian properties and their trade-offs in autocatalytic RNA reaction networks
    Nature communications, 2021
    Co-Authors: Sandeep Ameta, Simon Arsène, Sophie Foulon, Baptiste Saudemont, Bryce E. Clifton, Andrew D. Griffiths, Philippe Nghe
    Abstract:

    Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Autocatalytic networks have been discovered in various chemistries, but we lack a general understanding of how network topology controls the Darwinian properties of variation, Differential Reproduction, and heredity, which are mediated by the chemical composition. Using barcoded sequencing and droplet microfluidics, we establish a landscape of thousands of networks of RNAs that catalyze their own formation from fragments, and derive relationships between network topology and chemical composition. We find that strong variations arise from catalytic innovations perturbing weakly connected networks, and that growth increases with global connectivity. These rules imply trade-offs between Reproduction and variation, and between compositional persistence and variation along trajectories of network complexification. Overall, connectivity in reaction networks provides a lever to balance variation (to explore chemical states) with Reproduction and heredity (persistence being necessary for selection to act), as required for chemical evolution. Autocatalytic networks may have started evolution during the origin of life. Here, the authors establish a landscape of thousands of RNA networks by barcoded sequencing and microfluidics, and derive relationships between topology and Darwinian properties such as variation and Differential Reproduction.

  • Darwinian properties and their trade-offs in autocatalytic RNA reaction networks
    2019
    Co-Authors: Sandeep Ameta, Simon Arsène, Sophie Foulon, Baptiste Saudemont, Bryce E. Clifton, Andrew D. Griffiths, Philippe Nghe
    Abstract:

    Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Autocatalytic networks have been discovered in various chemistries, but we lack a general understanding of how network topology controls the Darwinian properties of variation, Differential Reproduction, and heredity, which are mediated by the chemical composition. Using barcoded sequencing and droplet microfluidics, we establish a landscape of thousands of networks of RNAs that catalyze their own formation from fragments, and derive relationships between network topology and chemical composition. We find that strong variations arise from catalytic innovations perturbing weakly connected networks, and that Reproduction increases with global connectivity. These rules imply trade-offs between Reproduction and variation, and between compositional persistence and variation along trajectories of network complexification. Overall, connectivity in reaction networks provides a lever to balance variation (to explore chemical states) with Reproduction and heredity (persistence being necessary for selection to act), as required for chemical evolution.

Adolf Heschl - One of the best experts on this subject based on the ideXlab platform.

  • Natural selection and metaphors of “selection”
    Behavioral and Brain Sciences, 2001
    Co-Authors: Adolf Heschl
    Abstract:

    Natural selection in the sense of Darwin always means physical propagation (positive case) or disappearance (negative case) of living organisms due to Differential Reproduction. If one concentrates on this simple materialist principle, one arrives at a much better method of discerning true selection processes from largely nonrandom processes of internal rearrangement (somatic mutations) and reorganisation (operant learning).

Regine Claßen-bockhoff - One of the best experts on this subject based on the ideXlab platform.

  • Sex-Differential Reproduction success and selection on floral traits in gynodioecious Salvia pratensis.
    BMC plant biology, 2019
    Co-Authors: Bo Zhang, Regine Claßen-bockhoff
    Abstract:

    Gynodioecy, a sexual system with hermaphrodite and female individuals in a population, raises the question how the two sexual morphs are maintained. Salvia pratensis is a gynodioecious species featured by its modified stamens that act as a lever mechanism in pollination. Given sexual dimorphism in floral traits of the species, it is predictable that two sexual morphs differ in their interplay with pollinators and thus in their fitness. In this study, we investigated sex-specific Reproduction success and floral adaptation in a population of S. pratensis. We found that two sexual morphs in S. pratensis distinctly differed in their floral proportions. Female flowers fitted better to the pollinators than hermaphrodites in terms of touching the stigmas when being probed, and hence were more efficient in pollen deposition. Floral traits overall underwent stronger selection in the population, with stigma position and corolla length subject to disruptive selection mediated by different body-sized bumble bees; some selections on floral traits were significantly different in the strength, even opposite in the direction between two morphs. Flower production tended to be under correlational selection with floral structural traits, implying that a large plant with many flowers did not show an advantage in fitness unless its flower construction mechanically matched the pollinators well. In conclusion, the pollinator-mediated selection likely played an important role in the evolution and maintenance of sexual dimorphism in the gynodioecious S. pratensis; and sex-divergent mechanical interaction with pollinators served as a critical mechanism by which female individuals were maintained in the population with a female advantage in pollen deposition efficiency (i.e. receiving pollen).