From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics
Author(s):
Manrubia, Susanna; Cuesta, José A.; Aguirre, Jacobo; Ahnertgh, Sebastian E.; Altenberg, Lee; Cano, Alejandro V.; Catalan Fernandez, Pablo; Diaz-Uriarte, Ramon; Elena, Santiago F.; García-Martín, Juan Antonio; Hogewegs, Paulien; Khatri, Bhavin S.; Krug, Joachim; Louis, Ard A.; Martin, Nora S.; Payne, Joshua L.; Tarnowski, Matthew J.; Weiß, Marcel
Publisher:
Elsevier
Issued date:
2021-09
Citation:
Manrubia, S., Cuesta, J. A., Aguirre, J., Ahnert, S. E., Altenberg, L., Cano, A. V., Catalán, P., Diaz-Uriarte, R., Elena, S. F., García-Martín, J. A., Hogeweg, P., Khatri, B. S., Krug, J., Louis, A. A., Martin, N. S., Payne, J. L., Tarnowski, M. J. & Weiß, M. (2021). From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics. Physics of Life Reviews, 38, 55–106.
ISSN:
1571-0645
xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
Ministerio de Economía y Competitividad (España)
Ministerio de Ciencia, Innovación y Universidades (España)
Sponsor:
Acknowledgements
All authors are indebted to the Centre Européen de Calcul Atomique et Moléculaire (CECAM) for supporting the organization of the workshop “From genotypes to function. Challenges in the computation of realistic genotype-phenotype maps”, which took place in Zaragoza (March 13th to March 15th, 2019) and triggered the production of this work. These are additional sources of financial support of the authors:
SM: grant FIS2017-89773-P (MINECO/FEDER, EU); “Severo Ochoa” Centers of Excellence to CNB, SEV 2017-0712.
JAC: grants FIS2015-64349-P (MINECO/FEDER, EU) and PGC2018-098186-B-I00 (MICINN/FEDER, EU).
JA: grant FIS2017-89773-P (MINECO/FEDER, EU); “Severo Ochoa” Centers of Excellence to CNB, SEV 2017-0712.
SEA: the Gatsby Charitable Foundation.
LA: Foundational Questions Institute (FQXi) and Fetzer Franklin Fund, a donor advised fund of Silicon Valley Community Foundation, for FQXi Grant number FQXi-RFP-IPW-1913, Stanford Center for Computational, Evolutionary and Human Genomics and the Morrison Institute for Population and Resources Studies, Stanford University, the 2015 Information Processing in Cells and Tissues Conference, and the Mathematical Biosciences Institute at The Ohio State University, for its support through National Science Foundation Award #DMS 0931642.
PC: Ramón Areces Postdoctoral Fellowship.
RDU: grant BFU2015-67302-R (MINECO/FEDER, EU).
SFE: grants BFU2015-65037-P (MCIU-FEDER) and PROMETEOII/2014/012 (Generalitat Valenciana).
JK: DFG within CRC1310 “Predictability in Evolution”.
NSM: Gates Cambridge Scholarship; Winton Programme for the Physics of Sustainability.
JLP: Swiss National Science Foundation, grant PP00P3_170604.
MJT: grants EP/L016494/1 (EPSRC/BBSRC Centre for Doctoral Training in Synthetic Biology) and BB/L01386X/1 (BBSRC/EPSRC Synthetic Biology Research Centre, BrisSynBio).
MW: the EPSRC and the Gatsby Charitable Foundation.
Project:
Gobierno de España. FIS2015-64349-P
Gobierno de España. PGC2018-098186-B-I00
Gobierno de España. FIS2017-89773-P
Gobierno de España. BFU2015-67302-R
Gobierno de España. BFU2015-65037-P
Keywords:
Experimental evolution
,
Fitness landscape
,
Genotype network
,
Genotype-phenotype map
,
Molecular evolution
,
Phenotypic bias
Rights:
© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.
Atribución-NoComercial-SinDerivadas 3.0 España
Abstract:
Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still
Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics¿cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.
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