Molecular Plant Breeding 2020, Vol.11, No.24, 1-8
7
ANPEL, Shanghai, China,
) before UPLC-MS/MS analysis. The experiment was
completed by Wuhan Metware Biology Limited.
3.4 Data analysis method
Transcriptome and metabolomic data were annotated to GO database (
/). The gene
number of each term was calculated, and the functional classification statistics were carried out by using WEGO
software. The correlation between the detected genes and metabolites was analyzed, and the Pearson correlation
coefficient of genes and metabolites was calculated by COR program. Using KEGG database (
.
jp/kegg/). The pathway enrichment of different genes and metabolites was analyzed. O2PLS analysis was used to
explore the association between differentially expressed RNA and different metabolites. O2PLS model is used to
analyze the integration between the two data sets, including the relationship between systems biomics, molecular
regulatory mechanism phenotype correlation. Through O2PLS model, we can not only obtain the correlation
coefficient between variables, but also obtain the weight of variables in the model, so as to find the key regulatory
phenomena more accurately (Chen et al., 2013; Roberts and Pimentel, 2011).
Authors’ contributions
In this study, Yan Xiujuan is responsible for data analysis and paper writing of experimental design; He Xin is responsible for
running point and sampling work; Gao Jingxia and Zhao Yunxia are responsible for assisting data analysis and paper revision; Wang
Xuemei is responsible for guiding experiment and paper writing. All authors read and agree to the final text.
Acknowledgment
This research is jointly funded by the natural fund project of Ningxia Hui Autonomous Region (2019AAC03156) and the whole
industry chain innovation demonstration project of Ningxia Academy of agriculture and Forestry Sciences (QCYL-2018-03).
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