Paper detail

Competency of the Developmental Layer Alters Evolutionary Dynamics in an Artificial Embryogeny Model of Morphogenesis

Biological genotypes do not code directly for phenotypes; developmental physiology is the control layer that separates genomes from capacities ascertained by selection. A key aspect is competency, as cells are not a passive material but descendants of unicellular organisms with complex context-sensitive capabilities. We used an evolutionary simulation in the context of minimal artificial embryogeny to probe the effects of different degrees of cellular competency on evolutionary dynamics. Virtual embryos consisted of a single axis of positional information values provided by cells' genomes, operated upon by an evolutionary cycle in which embryos' fitness was proportional to monotonicity of the axial gradient. Evolutionary dynamics were evaluated in two modes: hardwired "mosaic" development (genotype directly encodes phenotype), and a more realistic mode in which cells interact prior to evaluation by the fitness function ("regulative" development). Even minimal competency with respect to improving their position in the embryo results in better performance of the evolutionary search. Crucially, we observed that as competency of cells masks the raw fitness of the genomes, the phenotypic fitness gains are then mostly due to improvements of cells' developmental problem-solving capacities, not the structural genome. This suggests the existence of a powerful ratchet mechanism: evolution progressively becomes locked in to improvements in the intelligence of its agential substrate, with reduced pressure on the structural genome. A feedback loop in which evolution increasingly puts more effort into the developmental software than perfecting the hardware explains the very puzzling divergence of genome from anatomy in species like planaria, identifies a possible drive for scaling intelligence over time, and suggests strategies for engineering novel systems in silico and in bioengineering.

preprint2022arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.