AsiaEvo Home Page Forums Proposals for Symposia Fitness landscapes bridge evolution and molecular biology

  • Creator
  • #276
    Hsin-Hung David
    I like this idea

    >> Organizers
    1. Hsin-Hung David Chou. National Taiwan University, Taiwan R.O.C.
    2. Fyodor Kondrashov. Okinawa Institute of Science and Technology, Japan.

    >> Confirmed speakers
    1. Hsin-Hung David Chou, National Taiwan University.
    2. Fyodor Kondrashov, Okinawa Institute of Science and Technology.
    3. Nobuhiko Tokuriki, University of British Columbia.
    4. Olivier Tenaillon, University of Paris.
    5. Andreas Wagner, University of Zurich.
    6. Arjan G. M. de Visser, Wageningen University.

    In light of an interdisciplinary endeavor to reveal the molecular mechanisms of evolution, we propose a symposium titled “Fitness landscapes bridge evolution and molecular biology” with the goal of fostering the bonding between evolutionary biology, genomics, and bioengineering.

    Living systems are built and supported by molecular machinery crafted and perfected by evolution. For decades, research in biology has been pursued by two schools with seemingly different scopes and limited crosstalk. Microevolutionary biologists surveyed natural variation to illuminate population structure, selection modes, and functionally important residues in genes and regulatory elements. On the other hand, molecular biologists perform gene knockout and biochemical characterization to unravel molecular function, cellular network architecture, and the interaction between genetic components. However, in recent years the rift between evolution and molecular biology is closing through exploration of the molecular fitness landscape (i.e., comprehensive sequence-function relationship of DNA, RNA, and proteins).

    Coined by Sewall Wright in the 1930s, the fitness landscape metaphor provides a powerful framework to conceive how the genotypes and phenotypes of organisms evolve in response to mutation, drift, and selection. Fitness landscapes are multi-dimension graphs composed of nodes representing all possible sequence variants, edges delineating potential mutation steps, and node height showing fitness values (i.e., molecular function or cellular fecundity). Fitness landscapes provide a practical basis for elucidating the biophysical principles of molecular function, revealing the cause and prevalence of epistasis, explaining the functional significance of standing genetic variation, engineering enzymes with higher reactivity and specificity, and predicting the evolution of antibiotic resistance, infectious disease, and endangered species.

    Despite the significance and utility of fitness landscapes, earlier research is theoretical, mainly due to the limited experimental capacity to generate and characterize mutants. Fortunately, recent technological advances in DNA sequencing, oligo library synthesis, and massively parallel functional assays have enabled the realization of empirical fitness landscapes through robustly scoring the fitness of many thousands of molecular variants in single experiments. With fruitful results accumulated from fitness landscape expedition over a decade, we feel now is the right moment to gather experts to share the latest findings and brainstorm future directions. Specifically, this symposium will revolve around three themes:

    1. Fitness landscapes reveal the biophysical principles of molecular machinery.
    2. Influence of fitness landscape topology on evolutionary dynamics.
    3. Applications of fitness landscapes in drug discovery and protein engineering.

    The symposium shall engage researchers in population genetics, molecular evolution, genomics, computational biology, and synthetic biology. Moreover, we anticipate the interaction to catalyze international and cross-disciplinary collaboration that yields novel insights into evolutionary mechanisms, molecular biophysics, and the adaptation of living systems in response to climate change.

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  • Author
    • #286
      Hsin-Hung David

      confirmed speaker #7 Xiao Yi, Shenzhen Institute of Synthetic Biology, China

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