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Leveraging Co-Expression Network Analysis to Establish Transcriptional Shifts in the Gut of the Asian Citrus Psyllid During Candidatus Liberibacter asiaticus Infection
1, 2 , 3 , * 1 , * 1, 4
1  Boyce Thompson Institute, Ithaca, NY 14853
2  Department of Entomology, Cornell University, Ithaca, NY 14853
3  Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45211
4  Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ 85721
Academic Editor: Mihailo Jelić


Asian citrus psyllid (ACP, Diaphorina citri) is the vector for the bacteria, Candidatus Liberibacter asiaticus (CLas), that causes Huanglongbing (HLB, citrus greening disease). Although studies have reported proteomic and transcriptomic responses within the psyllid midgut after CLas infection, these analyses have been limited and have not examined correlated expression profiles in relation to CLas infection. With a comprehensive psyllid RNAseq data from the Citrus Greening Expression Network (CGEN), a total of 743 genes (Official Gene Set v3, OGSv3) were determined as differentially expressed genes (DEGs) in response to CLas infection. Forty-one modules of co-expressed genes were identified using a weighted gene co-expression network analysis (WGCNA). The functional analysis of infection-associated modules showed that genes involved in muscle contraction, peptidase and iron binding activities were correlated, which may correspond to enhanced vector dispersal, altered feeding/digestion, and sequestering free iron. Additional associated modules identified that Golgi apparatus and endoplasmic reticulum processes may be a signal indicating altered intracellular protein consumption during infection. This study provides a novel understanding of molecular mechanisms involved in CLas-psyllid interaction which can be potential targets for disrupting CLas transmission.

Keywords: Asian citrus psyllid; Huanglongbing; DEGs; weighted gene co-expression analysis; functional enrichment analysis; citrus; citrus greening; psyllid; pathogen; expression networks; co-expression