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Local adaptation and migratory habits balance spatial-genetic structure between continental and insular chestnut tiger butterflies in East Asia.

Min-Xin LuoHsin-Pei LuBing-Hong HuangChia-Lung HuangYu-Feng HsuPei-Chun Liao
Published in: Molecular ecology (2022)
Geographic and climatic differences between islands and continents may affect the evolution of their biota, and promote divergent selection in species distributed in both landscapes. To assess spatial-genetic structure, we genotyped 18 expressed sequence tag-simple sequence repeat (EST-SSR) loci and sequenced two mtDNA markers (ND5 and COI) and one nuclear marker (EF1α) in two subspecies of the butterfly Parantica sita. Compared with nuclear markers, mtDNA had a stronger signal of population structure. Approximate Bayesian computation (ABC) suggested that a continuous-gene-flow model best described the data. According to this model, the two subspecies diverged approximately 23.1 kya, with 10 times more introgression from the continental (ssp. sita) to the insular subspecies (ssp. niphonica) than vice versa. Ecological niche modelling was performed to predict the paleo- and current potential distributions and elucidate the geohistorical process, which revealed a northeastern, insular origin. Winter precipitation and annual temperature range were the main determinants of the subspecies distributions. Maximum-likelihood population-effects models showed that the population differentiation of the insular and continental subspecies was primarily affected by environmental resistance and local climate. Sex-biased migration capacity and long-term precipitation-driven divergence between the continental and insular lineages shaped the current genetic structure of P. sita. Evidence from the nuclear markers confirmed intersubspecific gene flow despite adaptive divergence between the subspecies. These results imply that the continental subspecies is still capable of returning to the island and introgressing with the insular subspecies.
Keyphrases
  • copy number
  • genome wide
  • mitochondrial dna
  • dna methylation
  • human health
  • risk assessment
  • big data
  • transcription factor
  • genetic diversity
  • genome wide analysis