Accelerating Citrus Gene Discovery for HLB Tolerance/Resistance

Accelerating Citrus Gene Discovery for HLB Tolerance/Resistance

Report Date: 10/02/2015
Project: 724   Year: 2015
Category: Plant Improvement
Author: Fred Gmitter
Sponsor: Citrus Research and Development Foundation

Most commonly grown citrus cultivars are sensitive to Huanglongbing (HLB). However, some citrus species and related genera are substantially more tolerant, such as Citrus jambhiri (rough lemon), Poncirus trifoliata and Microcitrus australis. Genome analysis will improve our understanding of the HLB tolerance mechanisms. Nuclear DNA from Citrus jambhiri was used to generate more than 235 million paired-end reads (2 X 100 nt) of the rough lemon genome. A reference-guided method was used to assemble the rough lemon genome. Based on analysis of the SNPs identified, rough lemon was found to have originated from the interspecific hybridization of mandarin, citron and pummelo, and its chloroplast is probably derived from mandarin. RNA-sequencing data was used for gene annotation, and some differentially expressed (DE) genes were identified. Most of DE genes were up-regulated in HLB affected trees, compared with non-affected trees. These DE genes were mainly involved in response to stress, carbohydrate metabolic process, response to abiotic stimulus, cell wall organization or biogenesis, ion transport and signaling. Based on our meta-analysis and co-expression network analysis of previously published gene expression data, we have shortlisted 2,000 HLB-responsive candidate genes in citrus (Du et al., 2015; Rawat et al., 2015). To identify sequence polymorphisms and validate the expression patterns of candidate genes, we have isolated genomic DNA and RNA from 20 citrus accessions. The DNA and RNA preps are being evaluated for quality and are to be sent to a commercial DNA sequencing company for large-scale sequencing on the HiSeq 2500. The sequencing data of these samples will be analyzed with the focus on 2000 candidate genes. The genomic indel variations and SNPs will be identified within these sequenced accessions for the selected candidate genes.


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