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A proteomic analysis of peanut seed at different stages of underground development to understand the changes of seed proteins

文献类型： 外文期刊

作者： Li, Haifen 1 ; Liang, Xuanqiang 2 ; Zhou, Baojin 3 ; Chen, Xiaoping 2 ; Hong, Yanbin 2 ; Zhou, Ruo 3 ; Li, Shaoxiong 2 ;

作者机构： 1.South China Agr Univ, State Key Lab Conservat & Utilizat Subtrop Agrobi, Guangzhou, Peoples R China

2.Guangdong Acad Agr Sci GAAS, Crops Res Inst, South China Peanut Subctr, Natl Ctr Oilseed Crops Improvement,Guangdong Key, Guangzhou, Peoples R China

3.Deepxomics Co Ltd, Tech Serv Dept, Shenzhen, Peoples R China

期刊名称：PLOS ONE （ 影响因子：3.24； 五年影响因子：3.788 ）

ISSN： 1932-6203

年卷期： 2020 年 15 卷 12 期

页码：

收录情况： SCI

摘要： In order to obtain more valuable insights into the protein dynamics and accumulation of allergens in seeds during underground development, we performed a proteomic study on developing peanut seeds at seven different stages. A total of 264 proteins with altered abundance and contained at least one unique peptide was detected by matrix-assisted laser desorption ionization time-of-flight/time-of-flight mass spectrometry (MALDI-TOF/TOF MS). All identified proteins were classified into five functional categories as level 1 and 20 secondary functional categories as level 2. Among them, 88 identified proteins (IPs) were related to carbohydrate/ amino acid/ lipid transport and metabolism, indicating that carbohydrate/amino acid/ lipid metabolism played a key role in the underground development of peanut seeds. Hierarchical cluster analysis showed that all IPs could be classified into eight cluster groups according to the abundance profiles, suggesting that the modulatory patterns of these identified proteins were complicated during seed development. The largest group contained 41 IPs, the expression of which decreased at R 2 and reached a maximum at R3 but gradually decreased from R4. A total of 14 IPs were identified as allergen-like proteins by BLAST with A genome (Arachis duranensis) or B genome (Arachis ipaensis) translated allergen sequences. Abundance profile analysis of 14 identified allergens showed that the expression of all allergen proteins was low or undetectable by 2-DE at the early stages (R1 to R4), and began to accumulate from the R5 stage and gradually increased. Network analysis showed that most of the significant proteins were involved in active metabolic pathways in early development. Real time RT-PCR analysis revealed that transcriptional regulation was approximately consistent with expression at the protein level for 8 selected identified proteins. In addition, some amino acid sequences that may be associated with new allergens were also discussed.

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