AI Cracks the Code of Fish Color Diversity, Revealing How Nature Maintains Extreme Variation
Researchers used deep learning to map the genetic basis of male guppy coloration, finding that hundreds of genes across the entire genome—including duplicates on sex chromosomes—control color patterns. The discovery offers a blueprint for understanding how organisms maintain striking diversity under competing evolutionary pressures, with potential applications in agriculture, conservation, and evolutionary biology research.
Originaltitel: Deep learning reveals the complex genetic architecture of male guppy colouration
<p>The extraordinary variation in male guppy (Poecilia reticulata) colouration is a powerful model for studying the interplay of natural and sexual selection. However, the complexity of this variation has hampered the high-resolution characterization and determination of the genetic architecture underlying male guppy colour and clouded our understanding of how this exceptional level of diversity is maintained. Here we identify the heritability and genetic basis of male colour variation using convolutional neural networks for high-resolution phenotyping coupled with selection experiments, controlled pedigrees and whole-genome resequencing for a genome-wide association study of colour traits. Our phenotypic and genomic results converge to show that colour patterning in guppies is a combination of many heritable features, each with a largely independent genetic architecture spanning the entire genome. Autosomally inherited ornaments are polygenic, with significant contributions from loci involved in neural crest cell migration. Unusually, the results of our genome-wide association study suggest that gene duplicates from the autosomes to the Y chromosome are responsible for much of the sex-linked variation in colour in guppies, providing a potential mechanism for the maintenance of variation of this classic model trait.</p>