Fish as Model Systems to Study Epigenetic Drivers in Human Self-Domestication and Neurodevelopmental Cognitive Disorders
- PMID: 35741749
- PMCID: PMC9222608
- DOI: 10.3390/genes13060987
Fish as Model Systems to Study Epigenetic Drivers in Human Self-Domestication and Neurodevelopmental Cognitive Disorders
Abstract
Modern humans exhibit phenotypic traits and molecular events shared with other domesticates that are thought to be by-products of selection for reduced aggression. This is the human self-domestication hypothesis. As one of the first types of responses to a novel environment, epigenetic changes may have also facilitated early self-domestication in humans. Here, we argue that fish species, which have been recently domesticated, can provide model systems to study epigenetic drivers in human self-domestication. To test this, we used in silico approaches to compare genes with epigenetic changes in early domesticates of European sea bass with genes exhibiting methylation changes in anatomically modern humans (comparison 1), and neurodevelopmental cognitive disorders considered to exhibit abnormal self-domestication traits, i.e., schizophrenia, Williams syndrome, and autism spectrum disorders (comparison 2). Overlapping genes in comparison 1 were involved in processes like limb morphogenesis and phenotypes like abnormal jaw morphology and hypopigmentation. Overlapping genes in comparison 2 affected paralogue genes involved in processes such as neural crest differentiation and ectoderm differentiation. These findings pave the way for future studies using fish species as models to investigate epigenetic changes as drivers of human self-domestication and as triggers of cognitive disorders.
Keywords: DNA methylation; cognitive disorders; domestication; domestication syndrome; epigenetics; fish; human evolution; neural crest; self-domestication; vertebrates.
Conflict of interest statement
The authors declare no conflict of interest.
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- Wilkins A.S. Revisiting two hypotheses on the “domestication syndrome” in light of genomic data. Vavilov J. Genet. Breed. 2017;21:435–442. doi: 10.18699/VJ17.262. - DOI
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