title: Comprehensive meta-analysis, co-expression, and miRNA nested network analysis identifies gene candidates in citrus against Huanglongbing disease.
abstract: BACKGROUND
  Huanglongbing (HLB), the most devastating disease of citrus, is associated with infection by Candidatus Liberibacter asiaticus (CaLas) and is vectored by the Asian citrus psyllid (ACP). Recently, the molecular basis of citrus-HLB interactions has been examined using transcriptome analyses, and these analyses have identified many probe sets and pathways modulated by CaLas infection among different citrus cultivars. However, lack of consistency among reported findings indicates that an integrative approach is needed. This study was designed to identify the candidate probe sets in citrus-HLB interactions using meta-analysis and gene co-expression network modelling.
  
  
  RESULTS
  Twenty-two publically available transcriptome studies on citrus-HLB interactions, comprising 18 susceptible (S) datasets and four resistant (R) datasets, were investigated using Limma and RankProd methods of meta-analysis. A combined list of 7,412 differentially expressed probe sets was generated using a Teradata in-house Structured Query Language (SQL) script. We identified the 65 most common probe sets modulated in HLB disease among different tissues from the S and R datasets. Gene ontology analysis of these probe sets suggested that carbohydrate metabolism, nutrient transport, and biotic stress were the core pathways that were modulated in citrus by CaLas infection and HLB development. We also identified R-specific probe sets, which encoded leucine-rich repeat proteins, chitinase, constitutive disease resistance (CDR), miraculins, and lectins. Weighted gene co-expression network analysis (WGCNA) was conducted on 3,499 probe sets, and 21 modules with major hub probe sets were identified. Further, a miRNA nested network was created to examine gene regulation of the 3,499 target probe sets. Results suggest that csi-miR167 and csi-miR396 could affect ion transporters and defence response pathways, respectively.
  
  
  CONCLUSIONS
  Most of the potential candidate hub probe sets were co-expressed with gibberellin pathway (GA)-related probe sets, implying the role of GA signalling in HLB resistance. Our findings contribute to the integration of existing citrus-HLB transcriptome data that will help to elucidate the holistic picture of the citrus-HLB interaction. The citrus probe sets identified in this analysis signify a robust set of HLB-responsive candidates that are useful for further validation.
authors.affiliation: University of Florida, Institute of Food and Agricultural Sciences, Gulf Coast Research and Education Center, Wimauma, FL, 33598, USA. nrawat@ufl.edu.
authors.forename: Nidhi
authors.initials: N
authors.lastname: Rawat
authors.affiliation: Ocimum BioSolutions, Banjara Hills Road No. 1, VI Floor Reliance Classic, Hyderabad, 500039, India. p_sandhyakiran@yahoo.com.
authors.forename: Sandhya P
authors.initials: SP
authors.lastname: Kiran
authors.affiliation: University of Florida, Institute of Food and Agricultural Sciences, Citrus Research and Education Center, Lake Alfred, FL, 33850, USA. dldu@ufl.edu.
authors.forename: Dongliang
authors.initials: D
authors.lastname: Du
authors.affiliation: University of Florida, Institute of Food and Agricultural Sciences, Citrus Research and Education Center, Lake Alfred, FL, 33850, USA. fgmitter@ufl.edu.
authors.forename: Fred G
authors.initials: FG
authors.lastname: Gmitter
authors.affiliation: University of Florida, Institute of Food and Agricultural Sciences, Gulf Coast Research and Education Center, Wimauma, FL, 33598, USA. zdeng@ufl.edu.
authors.forename: Zhanao
authors.initials: Z
authors.lastname: Deng
mesh_terms: D002957:Citrus / Q000235:genetics* / Q000378:metabolism / Q000382:microbiology*; D056726:Genetic Association Studies; D035683:MicroRNAs / Q000235:genetics / Q000378:metabolism; D008957:Models, Genetic; D010935:Plant Diseases / Q000382:microbiology*; D010940:Plant Proteins / Q000235:genetics* / Q000378:metabolism; D012230:Rhizobiaceae / Q000502:physiology*; D059467:Transcriptome
chemical_list: D035683:MicroRNAs; D010940:Plant Proteins