The approach sketched out here expands on the concept of Genotype: Phenotype (G:P) maps which provide a means to characterize a mapping of the genotype to a phenotype [5]. Let us take a very small G:P example (Figures 1 and 2). We might think that the simplest relationship would be a 1:1 mapping, with the genome collectively serving as a blueprint for the phenotype. But this simplistic mapping scheme results in a linear, low-resolution phenotype. In such cases, mutations or recombination in each gene have direct effects in the phenotype. The resulting linearity also works against evolvability of the G-P map [6], as every new trait would require a new gene. Simply duplicating genes might appear to solve the problem, but this ultimately results in an extremely large genome.
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Another issue is the information content of a 1:1 mapping. Mapping one gene to one phenotypic trait results in a blocky, 1 bit representation. While we can specify as much detail as we would like in a single gene, it can only be turned on or off in a switchlike fashion. This is a common feature across the tree of life, and basic regulatory mechanisms exhibit common ancestry among bacteria (start sites and modulation) and in the Last Universal Common Ancestor (LUCA; an RNAP that predates DNA replication) [7, 8].
A much more realistic scenario is a G-P map where multiple genes contribute to a single trait, and each trait is the product of epistatic interactions between genes [9]. This not only provides compensatory routes to a partial phenotype in case of functional loss yet also provides a source of regulation resulting in phenotypic variation. Such a nonlinear approach moves us away from the “genes as blueprint” view, and towards a different view of G-P maps. This alternative view enables an emergent approach to gene regulation, where different versions of a phenotype can arise from the same set of genes. The G-P map is thus defined by pleiotropic interactions, which can be mapped out as the translation from one gene to many phenotypes.
G-P maps are defined by convergence as well as emergence. Convergence can be characterized by phenocopying or buffering, or where a single phenotype can result from multiple genotypic interactions. Genotype networks possess a small-world network architecture with assortativity [10].
Figure 2. An example of a G:P:C mapping. Each dot is a unit that corresponds with its level: red dots (G, or genotype) are equivalent to alleles, blue dots (P, or phenotype) are equivalent to affordances, and green dots (C, or culturtype) are equivalent to cultural variants.
In Figure 2, we can see that a G-P map (and by extension the G-P-C map) is constructable as a set of topological braids: branching and convergence patterns between two 1-D physical maps of the genotype (bottom) and phenotype (top). We are interested in a level above the phenotype, however, and this is where our third physical map (culturtype, Figure 2B) comes into play. A culturtype is the culture in which a phenotype operates. Each culturtype is a distinct form of practices and behaviors that shares attributes with other culturtypes. Culturtypes also have a connection to both the genotype and phenotype, offering a means to adapt to environmental conditions when genotypes cannot. From an embodied perspective, collective behaviors can be shaped by the phenotype, which should then map to the culturtype. The mapping between the phenotype and culturtype is similar in nature to the genotype-phenotype mapping. In particular, the relation between phenotypes composed of affordances and culturtypes composed of variants allows us to understand embodied, embedded, and extended cognition in the context of biological diversity [11]. The equivalent of epistasis is a more generic one-to-many mapping, typified by differences in cultural practice. This is typified by branching patterns. By contrast, convergence is defined by functional buffering and similar cultural practices derived from different phenotypes.
Topological braids [12] consist of strands that represent single pathways that map between different sets. In our example, each genotype:phenotype path is defined by a subset of braids, each braid being assigned a braid word as a means of credit assignment. Likewise, each phenotypic component has a subset of braids leading to a culturtype. The G:P:C map is an open braid system in which the number of braids nor number of units at each level remain constant, connecting the open nature of genotype, phenotype, and cultural diversity. Future work might incorporate a phylogenetic approach where braids are mapped to a reticulating phylogenetic tree, where temporal relationships can also be addressed.
References:
[1] Lewens, T. and Buskell, A. (2013). Cultural evolution. Stanford Encyclopedia of Philosophy, https://plato.stanford.edu/entries/evolution-cultural/
[2] Boyd, R. and Richerson, P.J. (1985). Culture and the Evolutionary Process. University of Chicago Press.
[3] Cavalli-Sforza, L.L. and Feldman, M. (1981). Cultural Transmission and Evolution: a quantitative approach. Princeton University Press.
[4] Claidière, N., Scott-Phillips, T.C., and Sperber, D. (2014). How Darwinian Is Cultural Evolution? Royal Society B, 369(1642), 20130368.
[5] Alberch, P. (1991). From genes to phenotype: dynamical systems and evolvability. Genetica, 84, 5–11.
[6] Wagner, G.P. and Zhang, J. (2011). The pleiotropic structure of the genotype-phenotype map: the evolvability of complex organisms. Nature Reviews Genetics, 12(3), 204-213.
[7] Kuo, S-T., Chang, J.K., Chang, C., Shen, W-Y., Hsu, C., Lai, S-W., and Chou, H-H.D. (2025). Unraveling the start element and regulatory divergence of core promoters across the domain bacteria. Nucleic Acids Research, 53, gkaf1310.
[8] Koonin, E.V., Krupovic, M., Ishino, S., and Ishino, Y. (2020). The replication machinery of LUCA: common origin of DNA replication and transcription. BMC Biology, 18, 61.
[9] Pigliucci, M. (2010). Genotype–phenotype mapping and the end of the ‘genes as blueprint’ metaphor. Royal Society London B: Biological Sciences, 365(1540), 557–566.
[10] Aguilar‐RodrÃguez, J., Peel, L., Stella, M., Wagner, A., and Payne, J.L. (2018). The architecture of an empirical genotype‐phenotype map. Evolution, 72(6), 1242–1260.
[11] Alicea, B., Gordon, R., and Parent, J. (2023). Embodied Cognitive Morphogenesis as a Route to Intelligent Systems. Royal Society Interface Focus, 13(3), 20220067.
[12] Weisstein, E.W. (2025). Braid. Wolfram MathWorld. https://mathworld.wolfram.com/ Braid.html AND Artin, E. (1950). The Theory of Braids. American Scientist, 38, 112-119, 1950.
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