bioRxivEvolutionary BiologyPreprint
Gene family evolution reveals dietary adaptations in butterflies and moths
Yi‐Ming WengiD, Jose I. MartineziD, Amanda MarkeeiD, David M. PlotkiniD, Yash SondhiiD, Andrew J. MongueiD, Paul B. FrandseniD, Akito Y. KawaharaiD
Abstract
Butterflies and moths (Lepidoptera) are a hyperdiverse lineage of nearly 160,000 described species and their evolutionary success is postulated to be tightly correlated with the radiation of their primary host -- angiosperms. Previous studies found that a significant number of emergent gene families are specific to Lepidoptera, with many genes linked to odorant receptors and peptidases, suggesting that such genetic innovations may be linked to their diversification. Here, we use genomic resources to identify lineage-specific gene families in four nested lepidopteran clades (e.g. Lepidoptera, Glossata, Ditrysia, and Apoditrysia). Among nearly a hundred gene families specific to each group, a handful of gene families have specific and interpretable functions. We found that many digestion-related gene families emerged early in the evolution of Lepidoptera, followed by genes associated with detoxification and immunity. This result aligns with the evolutionary transition in ancient Lepidoptera diets to terrestrial plants, highlighting the emergence of detoxification mechanisms in the megadiverse Ditrysia as a critical adaptation driven by the proliferation of plant chemical defenses. We also found gene families originating from horizontal gene transfer (HGT) events, likely introduced from bacteria and fungi to the common ancestors of Lepidoptera and Ditrysia, respectively. These HGT-derived genes likely played a pivotal role in supporting the dietary transition from algae, diatoms, and aquatic plant debris to fungi and primitive terrestrial plants, ultimately enabling the adaptation to the most dominant angiosperm species.
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- research focus: phylogenetics / evolution
- approach: statistical model
- Citations
- 1
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