Construction Of Regulatory Network For Inositol Phosphates Metabolism In Maize And Functional Identification Of New Genes

Inositol phosphates(D-myo-inositol phosphates, IPs, IPs), including IP1–IP6, are widely distributed and play important roles in eukaryotes. While, the molecular basis for phytic acid synthesis in plants is poorly understood limited by currently IPs’ detecting methods and the IPs-metabolism research approaches. Most of the IPs-metabolism genes were isolated form the low phytic acid(lpa) mutant lines in the past decades. However, no new information was obtained recently because there were no more new types of lpa mutants were identified. To understand the IPs-metabolism regulation and discover candidate genes, we integrated “omics” data, including transcriptomics and metabolomics, to analyze how IPs-metabolism was regulated.To accurately detect each IP, we developed an IPC/ESI-MS/MS(ion-pair chromatography/tandem mass spectrometry with an electrospray ionization source, or LC-MS/MS) method for simultaneous separation and determination of natural IPs. By using this method, we screened a broad maize inbred collection for exploring inbred lines with significant difference in phytic acid content, and then monitored the dynamic changes of each IP at different development stages in fresh seeds and embryo. Two inbred lines, B73(high in phytic acid) and Qi319(low in phytic acid), were selected and we finally chose embryo(DAP12, DAP21, DAP30) for RNA-Seq and micro RNA-Seq, aiming to analyze IPs-metabolism at systems biology level.DEG(Differental expression gene analysis) results showed that, some IPs-metabolism related genes were down-regulated in Qi319, MIPS and IPK were persistently down-regulated during the selected development stages. AS(alternative splicing) analysis showed that, new splicing modes were found in ITPK2 and MIPS, those AS patterns showed their specificities between different species as well as at different developmemt stages. And five novel mi RNAs related to IPs-metabolism regulation were identified after analyzing their targets.We also constructed the metabolite-related gene co-expression networks by using the WGCNA(Weighted Gene Co-Expression Network Analysis) method. The network data showed that:1. IPs-metabolism regulationg centralized to Ca2+ signal transduction pathway.2. Ubiquitination related F-box protein was the key nodes between GA(gibberellic acid) signal pathway and IPs-metabolism regulation.3. IPs’ translocation cooperated with transportion of sugars and some cations. The correlation of IP1 with both carbohydrates/inositol-transporters and MIK implied there was an inositol-translocation mechanism during phytic acid synthesis in the embryo.4. We extracted 3 candidate genes involved in IPs-metabolism according to the linkage mechanism in network.5. We identified the 3 candidate genes’ functions by mutant-phenotype-detection and RNA interfering(RNAi) subsequently, the results showed that, the 3 candidate genes were indeed related to the IPs’ content in seeds.We discovered the regulation modes of IPs-metabolism, including AS, mi RNAs and the interaction nodes between IPs-metabolism and other pathways, which were not reported by other researchs previously, what’s more, we identified 3 new genes related to IPs-metabolism. Our approach takes full advantage of the cooperativity of IPs with related genes and other pahways, giving more usefull information for understanding IPs and their metabolism.