RoL: FELS: EAGER: Mining for ancient toolkits: Emergence of planar structures across kingdoms

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Both Animal and Plant Kingdoms have evolved flat lateral (planar) appendages, for example, wings and leaves. Despite the lack of obvious functional similarity, planar structures in animals and plants may result from the merging of dorsal and ventral tissues, each of which is defined by different gene regulatory networks. This study will carry out a series of comparative gene expression analyses across homologous and analogous organs within Classes and across Kingdoms in order to determine whether there are shared, and perhaps universal, gene expression networks regulating the development of planar appendages. The data and insights may enable the development of new fundamental concepts in biology. This project will also enhance student learning in undergraduate and graduate courses and provide opportunities for participating undergraduate students to develop their critical thinking. Due to its location and university mission, Wayne State has a deep commitment to encouraging underrepresented and first-generation college students to explore careers in science and to develop a deep appreciation of science with respect to our national welfare. Studies of multiple organisms demonstrate that although dorsal/ventral (adaxial/abaxial) gene regulatory networks (GRNs) are necessary for planar structures, they are not sufficient. This fact suggests that there must be additional, presently undefined, emergent GRNs that are required for planar development. The experimental design is based on comparative transcriptome analyses between planar and non-planar homologous organs and planar and non-planar non-homologous, analogous organs in selected lineages of angiosperms and arthropods. These comparative analyses will seek to detect regulatory modules at different levels and help identify shared and perhaps universal toolboxes governing the development of planar structures. Data from RNAseq libraries will be mapped to de novo assemblies to quantify expression, and to determine gene functional identities. Expression counts of genes will be comprehensively analyzed to identify functional co-expression gene networks. Finally, detailed biological patterning across Classes and Kingdoms will be performed through analysis of protein domains within networks to detect deep overlapping regulatory modules.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.