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Lawrence, C. G.

Publications and source records attributed to Lawrence, C. G..

2 recordsLinked to original sources

Replaying the Tape: Comparative Genomics of Color Pattern in Heliconius

Understanding the repeatability of evolution requires disentangling the roles of constraint, contingency, and convergence in shaping phenotypic diversity. Mullerian mimicry in Heliconius butterflies offers a powerful natural experiment, with co-occurring species independently evolving similar wing color patterns under shared selective regimes. Here, we integrate high-throughput image-based phenotyping, genome-wide association studies (GWAS), and comparative pan-genomics to investigate the genetic architecture underlying convergent wing pattern evolution across parallel hybrid zones in Heliconius erato and H. melpomene. Using automated computer vision pipelines, we extracted and quantified color pattern variation from over 650 butterfly specimens. Principal component analysis (PCA) of recolorized, landmark-aligned wing images captured biologically meaningful axes of variation, which were used as phenotypes in GWAS. We identified strong associations at known patterning loci--including ivory:mir193 (previously coretex), optix, WntA, and vvl--as well as novel regions, including a chromosome 2 inversion in H. erato and a gustatory receptor gene (Gr21a) in H. melpomene. Comparative analyses using a Heliconius pan-genome revealed that while significant associations mapped to homologous regulatory regions across species, the specific variants were lineage-specific, consistent with parallel evolution via distinct cis-regulatory changes. These findings demonstrate that repeated adaptive outcomes can arise through different genetic paths within conserved regulatory architectures. More broadly, our study highlights the power of integrating machine learning, high-resolution phenotyping, and comparative genomics to dissect the molecular basis of convergent evolution in natural populations.

evolutionary biology↗

The perceptual and spatial architecture of Mullerian mimicry in Heliconius Butterflies

Mullerian mimicry theory predicts reciprocal convergence among defended species toward shared warning signals, yet the extent, symmetry, and perceptual basis of this convergence remain poorly quantified. Using deep-learning-based phenotyping combined with neural networks calibrated to avian predator and butterfly visual systems, we quantify mimetic similarity across 56 subspecies of Heliconius erato and H. melpomene. Mimetic phenotypes show broad clustering consistent with recognized mimicry rings, but vary continuously within. Phenotypic similarity is weakly structured by phylogeny and strongly organized geographically, consistent with repeated local convergence. Spatial overlap among co-mimics is heterogeneous, suggesting that frequency-dependent selection operates at variable spatial scales across mimicry communities. Models parameterized to different visual systems reveal that trait salience and discriminatory performance depend on the observer, indicating that apparent imperfect mimicry may arise from receiver-specific perceptual weighting. Asymmetric learning between lineages further suggests that convergence may not always be reciprocal, consistent with one species evolving towards another in advergence. Together, these results recast mimicry as a perceptually structured and spatially dynamic continuum rather than a set of discrete, mutually reinforcing rings, highlighting how community composition and sensory ecology shape the evolution of adaptive resemblance.

evolutionary biology↗