4.8 Article

Phylogenomic analysis of the APETALA2 transcription factor subfamily across angiosperms reveals both deep conservation and lineage-specific patterns

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PLANT JOURNAL
卷 103, 期 4, 页码 1516-1524

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WILEY
DOI: 10.1111/tpj.14843

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synteny networks; phylogenomics; AP2; EREBP transcription factors; plant embryogenesis; root and shoot development; floral development

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The APETALA2 (AP2) subfamily of transcription factors are key regulators of angiosperm root, shoot, flower and embryo development. The broad diversity of anatomical and morphological structures is potentially associated with the genomic dynamics of theAP2subfamily. However, a comprehensive phylogenomic analysis of theAP2subfamily across angiosperms is lacking. We combined phylogenetic and synteny analysis of distinctAP2subclades in the completed genomes of 107 angiosperm species. We identified major changes in copy number variation and genomic context within subclades across lineages, and discuss how these changes may have contributed to the evolution of lineage-specific traits. MultipleAP2subclades show highly conserved patterns of copy number and synteny across angiosperms, while others are more dynamic and show distinct lineage-specific patterns. As examples of lineage-specific morphological divergence due toAP2subclade dynamics, we hypothesize that loss ofPLETHORA1/2in monocots correlates with the absence of taproots, whereas independent lineage-specific changes ofPLETHORA4/BABY BOOMandWRINKLED1genes in Brassicaceae and monocots point towards regulatory divergence of embryogenesis between these lineages. Additionally, copy number expansion ofTOE1andTOE3/AP2in asterids is implicated with differential regulation of flower development. Moreover, we show that the genomic context ofAP2s is in general highly specialized per angiosperm lineage. To our knowledge, this study is the first to shed light on the evolutionary divergence of theAP2subfamily subclades across major angiosperm lineages and emphasizes the need for lineage-specific characterization of developmental networks to understand trait variability further.

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