Héloïse Bastide, Manuela López-Villavicencio, David Ogereau, Joanna Lledo, Anne-Marie Dutrillaux, Vincent Debat, Violaine Llaurens
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引用次数: 0
Abstract
The genomic processes enabling speciation and species coexistence in sympatry are still largely unknown. Here we describe the whole-genome sequencing and assembly of 3 closely related species from the butterfly genus Morpho: Morpho achilles (Linnaeus, 1758), Morpho helenor (Cramer, 1776), and Morpho deidamia (Höbner, 1819). These large blue butterflies are emblematic species of the Amazonian rainforest. They live in sympatry in a wide range of their geographical distribution and display parallel diversification of dorsal wing color pattern, suggesting local mimicry. By sequencing, assembling, and annotating their genomes, we aim at uncovering prezygotic barriers preventing gene flow between these sympatric species. We found a genome size of 480 Mb for the 3 species and a chromosomal number ranging from 2n = 54 for M. deidamia to 2n = 56 for M. achilles and M. helenor. We also detected inversions on the sex chromosome Z that were differentially fixed between species, suggesting that chromosomal rearrangements may contribute to their reproductive isolation. The annotation of their genomes allowed us to recover in each species at least 12,000 protein-coding genes and to discover duplications of genes potentially involved in prezygotic isolation like genes controlling color discrimination (L-opsin). Altogether, the assembly and the annotation of these 3 new reference genomes open new research avenues into the genomic architecture of speciation and reinforcement in sympatry, establishing Morpho butterflies as a new eco-evolutionary model.
期刊介绍:
GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.