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Comparative transcriptomics enables the identification of functional orthologous genes involved in early leaf growth.

Authors
  • Vercruysse, Jasmien
  • Van Bel, Michiel
  • Osuna-Cruz, Cristina M
  • Kulkarni, Shubhada R
  • Storme, Véronique
  • Nelissen, Hilde
  • Gonzalez, Nathalie
  • Vandepoele, Klaas
Publication Date
Jan 01, 2020
Source
ProdInra
Keywords
Language
English
License
Green
External links

Abstract

Leaf growth is a complex trait for which many similarities exist in different plant species, suggesting functional conservation of the underlying pathways. However, a global view of orthologous genes involved in leaf growth showing conserved expression in dicots and monocots is currently missing. Here we present a genome-wide comparative transcriptomics analysis between Arabidopsis and maize, identifying conserved biological processes and gene functions active during leaf growth. Despite the orthology complexity between these distantly related plants, 926 orthologous gene groups including 2,829 Arabidopsis and 2,974 maize genes with similar expression during leaf growth were found, indicating conservation of the underlying molecular networks. We found 65% of these genes involved in one-to-one orthology, whereas only 28.7% of the groups with divergent expression had one-to-one orthology. Within the pool of genes with conserved expression, 19 transcription factor families were identified, demonstrating expression conservation of regulators active during leaf growth. Additionally, 25 Arabidopsis and 25 maize putative targets of the TCP TFs with conserved expression were determined based on the presence of enriched transcription factor binding sites. Based on large-scale phenotypic data, we observed that genes with conserved expression have a higher probability to be involved in leaf growth and that leaf-related phenotypes are more frequently present for genes having orthologs between dicots and monocots than clade-specific genes. This study shows the power of integrating transcriptomics with orthology data to identify or select candidates for functional studies during leaf development in flowering plants.

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