A Developmental Network Theory of Gynandromorphs, Sexual Dimorphism and Species Formation
Abstract
Gynandromorphs are creatures where at least two different body sections are a different sex. Bilateral gynandromorphs are half male and half female. Here we develop a theory of gynandromorph ontogeny based on developmental control networks. The theory explains the embryogenesis of all known variations of gynandromorphs found in multicellular organisms. The theory also predicts a large variety of more subtle gynandromorphic morphologies yet to be discovered. The network theory of gynandromorph development has direct relevance to understanding sexual dimorphism (differences in morphology between male and female organisms of the same species) and medical pathologies such as hemihyperplasia (asymmetric development of normally symmetric body parts in a unisexual individual). The network theory of gynandromorphs brings up fundamental open questions about developmental control in ontogeny. This in turn suggests a new theory of the origin and evolution of species that is based on cooperative interactions and conflicts between developmental control networks in the haploid genomes and epigenomes of potential sexual partners for reproduction. This network-based theory of the origin of species is a paradigmatic shift in our understanding of evolutionary processes that goes beyond gene-centered theories.
- Publication:
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arXiv e-prints
- Pub Date:
- December 2012
- DOI:
- 10.48550/arXiv.1212.5439
- arXiv:
- arXiv:1212.5439
- Bibcode:
- 2012arXiv1212.5439W
- Keywords:
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- Quantitative Biology - Molecular Networks;
- Quantitative Biology - Genomics;
- Quantitative Biology - Populations and Evolution
- E-Print:
- 22 pages. Key Words: Gynandromorphs, developmental control networks, cenome, CENEs, epigenomics, origin of species, evolution of species, sexual dimorphism, unisexual hemimorphism, synsexhemimorphism, hemihyperplasia, hemihypertrophy, bilateral symmetry, multicellular development, developmental systems biology, embryonic development, computational modeling, simulation