Genomic Signatures of Speciation in Butterflies

The classification of organisms into species is fundamental to the study of life. Contrary to popular belief, simple and quantitative standards for species delineation are often lacking, and debates about species boundaries create obstacles for conservation biology, agriculture, legislation, and education. We chose butterflies as a model system to address this key biological question. We sequenced and analyzed transcriptomes of 186 butterfly specimens representing 25 pairs of species, representing close but clearly distinct species, conspecific populations, and taxa with debated relationships. We found that species are robustly separated from conspecific populations by the combination of two measures computed on Z-linked genes: a fixation index, which detects genetic gaps between species, and the extent of gene flow, which quantifies reproductive isolation. Applying these criteria suggest that all nine butterfly pairs with debated relationships are distinct species, not populations or subspecies. Furthermore, we found that elevated divergence and positive selection in proteins involved in DNA interaction, circadian clock, pheromone sensing, development, and immune response recurrently correlate with speciation. A significant fraction of these divergent proteins are encoded by the Z chromosome, which appears to be more resistant to introgression than autosomes. Taken together, our findings point to potential common speciation mechanisms in butterflies, provide additional support for the important role of the Z chromosome in speciation, and suggest quantitative criteria for species delimitation, which is vital for the exploration of biodiversity.

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Publication Details

Journal
Systematic Biology
Published
2026-03-20
DOI
https://doi.org/10.1093/sysbio/syag029
Primary Topic
Lepidoptera: Biology and Taxonomy
Type
article
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article

Genomic Signatures of Speciation in Butterflies

Qian Cong, Nick V Grishin, Jing Zhang
Systematic Biology
Lepidoptera: Biology and Taxonomy
article

Genomic Signatures of Speciation in Butterflies

Qian Cong, Nick V Grishin, Jing Zhang
article en

Abstract

The classification of organisms into species is fundamental to the study of life. Contrary to popular belief, simple and quantitative standards for species delineation are often lacking, and debates about species boundaries create obstacles for conservation biology, agriculture, legislation, and education. We chose butterflies as a model system to address this key biological question. We sequenced and analyzed transcriptomes of 186 butterfly specimens representing 25 pairs of species, representing close but clearly distinct species, conspecific populations, and taxa with debated relationships. We found that species are robustly separated from conspecific populations by the combination of two measures computed on Z-linked genes: a fixation index, which detects genetic gaps between species, and the extent of gene flow, which quantifies reproductive isolation. Applying these criteria suggest that all nine butterfly pairs with debated relationships are distinct species, not populations or subspecies. Furthermore, we found that elevated divergence and positive selection in proteins involved in DNA interaction, circadian clock, pheromone sensing, development, and immune response recurrently correlate with speciation. A significant fraction of these divergent proteins are encoded by the Z chromosome, which appears to be more resistant to introgression than autosomes. Taken together, our findings point to potential common speciation mechanisms in butterflies, provide additional support for the important role of the Z chromosome in speciation, and suggest quantitative criteria for species delimitation, which is vital for the exploration of biodiversity.

Systematic Biology
Southwestern Medical Center (US), The University of Texas Southwestern Medical Center (US)
Life in Land
Openalex Percentile: Top 11%
Lepidoptera: Biology and Taxonomy
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Genomic Signatures of Speciation in Butterflies — Qian Cong, Nick V Grishin, et al. · Systematic Biology (2026) | TGRS Research Map | TGRS