Insights into the Molecular Basis of Huanglongbing Tolerance in Persian Lime (Citrus latifolia Tan.) through a Transcriptomic Approach

Abstract

Huanglongbing (HLB) is a vascular disease of Citrus caused by three species of the α-proteobacteria “Candidatus Liberibacter”, with “Candidatus Liberibacter asiaticus” (CLas) being the most widespread and the one causing significant economic losses in citrus-producing regions worldwide. However, Persian lime (Citrus latifolia Tanaka) has shown tolerance to the disease. To understand the molecular mechanisms of this tolerance, transcriptomic analysis of HLB was performed using asymptomatic and symptomatic leaves. RNA-Seq analysis revealed 652 differentially expressed genes (DEGs) in response to CLas infection, of which 457 were upregulated and 195 were downregulated. KEGG analysis revealed that after CLas infection, some DEGs were present in the plant–pathogen interaction and in the starch and sucrose metabolism pathways. DEGs present in the plant–pathogen interaction pathway suggests that tolerance against HLB in Persian lime could be mediated, at least partly, by the ClRSP2 and ClHSP90 genes. Previous reports documented that RSP2 and HSP90 showed low expression in susceptible citrus genotypes. Regarding the starch and sucrose metabolism pathways, some genes were identified as being related to the imbalance of starch accumulation. On the other hand, eight biotic stress-related genes were selected for further RT-qPCR analysis to validate our results. RT-qPCR results confirmed that symptomatic HLB leaves had high relative expression levels of the ClPR1, ClNFP, ClDR27, and ClSRK genes, whereas the ClHSL1, ClRPP13, ClPDR1, and ClNAC genes were expressed at lower levels than those from HLB asymptomatic leaves. Taken together, the present transcriptomic analysis contributes to the understanding of the CLas-Persian lime interaction in its natural environment and may set the basis for developing strategies for the integrated management of this important Citrus disease through the identification of blanks for genetic improvement.