Unknown,Transcriptomics,Genomics,Proteomics

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Transcriptome analysis to elucidate puffing disorder in Citrus

ABSTRACT: To identify genes associated with citrus peel development and manifestation of peel disorders, we analyzed flavedo, albedo and juice sac tissues from navel orange displaying, and not displaying, the puff disorder. Symptomatic and healthy M-bM-^@M-^\NavelM-bM-^@M-^] orange fruits were harvested from an orchard located in in Pauma Valley, San Diego County, California, USA. Sampling for all analysis (healthy or disordered Navel orange) was performed at the same time, from trees grown under the same agronomic, soil, and environmental conditions. Healthy and disordered fruits were analyzed at the mature stage. All transcriptome analysis was performed on mature fruit. For each type of fruit, three tissues (flavedo, albedo, and juice sacs) from three different trees (biological replicates) were separately analyzed. Four symptomatic fruits comprised one biological replicate each. Two healthy fruits comprised two biological replicates of control samples. A 1 cm-thick equatorial disc and four sections (N, S, E, and W) were cut per fruit. Each section of flavedo, albedo, and juice sac tissue was dissected. gene expression variation underlying quality trait, different genotypes

ORGANISM(S): Citrus sinensis

SUBMITTER: Abhaya Dandekar

PROVIDER: E-GEOD-49957 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Use of Information Dependent Acquisition mass spectra and Sequential Window Acquisition of all Theoretical fragment-ion mass spectra for fruit juices metabolomics and authentication. LC-MS based untargeted metabolomics are the main untargeted methods used for juice metabolomics to solve the authentication problem faced in fruit juice industry. Objectives To evaluate the performances of different untargeted metabolomics methods on fruit juices metabolomics and authentication, orange and apple fruit juices were selected for this study. Methods IDA-MS and SWATH-MS based on UHPLC-QTOF were used for the metabolomics and authenticity determination of apple and orange juices, including the lab-made samples of oranges (Citrus sinensis Osb.) from Jiangxi Province, apples (Malus domestica Borkh) from Shandong Province, and different brands of commercial orange and apple juice samples from markets. Results IDA-MS and SWATH-MS could both acquire numerous MS1 features and MS2 information of juice components, while SWATH-MS excels at the acquisition rate of MS2. Distinctive separation between authentic orange juice and not authentic orange juice could be seen from principal component analysis and hierarchical clustering analysis based on both IDA-MS and SWATH-MS. After analysis of variance, fold change analysis and orthogonal projection to latent structures discriminant mode, 53 and 46 potential markers were defined by IDA-MS and SWATH-MS (with 77.4% and 100% MS2 acquisition rate) separately. Subsequently, these potential markers were putatively annotated using general chemical databases with 6 more annotated by SWATH-MS. Furthermore, 7 of the potential markers, l-asparagine, umbelliferone, glucosamine, phlorin, epicatechin, phytosphingosine and chlorogenic acid, were identified with standards. For the consideration of model simplicity, two determined makers (umbelliferone and chlorogenic acid) were selected to construct the DD-SIMCA model in commercial samples because of their good correlation with apple adulteration proportion, and the sensitivity and specificity of the model were 100% and 95%. Conclusion SWATH-MS excels at the MS2 acquisition of juice components and potential markers. This study provides an overall performance comparison between IDA-MS and SWATH-MS, and guidance for the method selection on fruit juice metabolomics and juice authenticity determination. Two of the potential markers determined, umbelliferone and chlorogenic acid, could be used as apple juice indicators in orange juice.

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Transcriptome analysis to elucidate puffing disorder in Citrus

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