Analysis of Peanut Leaf Proteome

Peanut (Arachis hypogaea) is one of the most important sources of plant protein. Current selection of genotypes requires molecular characterization of available populations. Peanut genome database has several EST cDNAs which can be used to analyze gene expression. Analysis of proteins is a direct approach to define function of their associated genes. Proteome analysis linked to genome sequence information is critical for functional genomics. However, the available protein expression data is extremely inadequate. Proteome analysis of peanut leaf was conducted using two-dimensional gel electrophoresis in combination with sequence identification using MALDI/TOF to determine their identity and function related to growth, development and responses to stresses. Peanut leaf proteins were resolved into 300 polypeptides with pI values between 3.5 and 8.0 and relative molecular masses from 12 to 100 kDa. A master leaf polypeptide profile was generated based on the consistently expressed protein pattern. Proteins present in 205 spots were identified using GPS software and Viridiplantae database (NCBI). Identity of some of these proteins included RuBisCO, glutamine synthetase, glyoxisomal malate dehydrogenase, oxygen evolving enhancer protein and tubulin. Bioinformatical analyses showed that there are 133 unique protein identities. They were categorized into 10 and 8 groups according to their cellular compartmentalization and biological functionality, respectively. Enzymes necessary for carbohydrate metabolism and photosynthesis dominated in the set of identified proteins. The reference map derived from a drought-tolerant cv.Vemana should serve as the basis for further investigations of peanut physiology such as detection of expressed changes due to biotic and abiotic stresses, plant development. Furthermore, the leaf proteome map will lead to development of protein markers for cultivar identification at seedling stage of the plant. Overall, this study will contribute to improve our understanding of plant genetics and metabolism, and overall assist in the selection and breeding programs geared toward crop improvement.

花生（Arachis hypogaea）是最重要的植物蛋白来源之一。当前花生基因型选育工作需对现有种质群体进行分子表征。花生基因组数据库中存有若干可用于基因表达分析的表达序列标签（Expressed Sequence Tag, EST）cDNA。蛋白质组分析是解析其关联基因功能的直接手段。结合基因组序列信息的蛋白质组分析，对功能基因组学研究至关重要。但目前已有的蛋白质表达数据极度匮乏。本研究采用双向凝胶电泳（two-dimensional gel electrophoresis）结合基质辅助激光解吸电离飞行时间质谱（Matrix-Assisted Laser Desorption/Ionization Time of Flight, MALDI-TOF）序列鉴定技术，对花生叶片蛋白质组进行分析，以明确其与生长、发育及胁迫响应相关的蛋白身份与功能。花生叶片蛋白经分离后得到300个多肽斑点，其等电点（pI）范围为3.5至8.0，相对分子质量区间为12至100千道尔顿（kDa）。基于稳定表达的蛋白谱，构建了花生叶片多肽参考图谱。采用GPS软件及Viridiplantae数据库（NCBI），对205个蛋白斑点进行了鉴定。部分鉴定得到的蛋白包括核酮糖-1,5-二磷酸羧化酶/加氧酶（Ribulose-1,5-bisphosphate carboxylase/oxygenase, RuBisCO）、谷氨酰胺合成酶、乙醛酸体苹果酸脱氢酶、放氧增强蛋白及微管蛋白。生物信息学（Bioinformatics）分析显示，共得到133个独特的蛋白鉴定结果。研究人员分别根据细胞亚定位与生物学功能，将这些蛋白划分为10个类别与8个功能组。在已鉴定的蛋白中，参与碳水化合物代谢与光合作用的酶类占主导地位。本研究基于耐旱品种Vemana构建的叶片参考图谱，可作为花生生理学后续研究的基础，例如用于检测生物胁迫（biotic stresses）与非生物胁迫（abiotic stresses）及植物发育过程中的蛋白表达变化。此外，该叶片蛋白质组图谱将有助于开发用于植物苗期品种鉴定的蛋白标记。综上，本研究有助于加深对植物遗传与代谢过程的理解，并为面向作物遗传改良的基因型选育与育种工作提供有力支撑。