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Updated: Feb 16, 2026

Experimental Design for Laser Microdissection RNA-Seq: Lessons from an Analysis of Maize Leaf Development
Published on: March 5, 2017
Integrated Analysis of Protein Abundance, Transcript Level, and Tissue Diversity To Reveal Developmental Regulation
Haitao Jia1, Wei Sun1, Manfei Li1
1National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University , Wuhan 430070, P. R. China.
Abstract:
The differentiation and subsequent development of plant tissues or organs are tightly regulated at multiple levels, including the transcriptional, posttranscriptional, translational, and posttranslational levels. Transcriptomes define many of the tissue-specific gene expression patterns in maize, and some key genes and their regulatory networks have been established at the transcriptional level. In this study, the sequential window acquisition of all theoretical spectra-mass spectrometry technique was employed as a quantitative proteome assay of four representative maize tissues, and a set of high-confidence proteins was identified. Integrated analysis of the proteome and transcriptome revealed that protein abundance was positively correlated with mRNA level with weak to moderate correlation coefficients, but the abundance of key proteins for function or architecture in a given tissue was closely tempospatially regulated at the transcription level. A subset of differentially expressed proteins, specifically tissue-specific highly expressed proteins, was identified, for example, reproductive structure and flower development-related proteins in tassel and ear, lipid and fatty acid biosynthetic process-related proteins in immature embryo, and inorganic substance and oxidation reduction responsive proteins in root, potentially revealing the physiology, morphology, and function of each tissue. Furthermore, we found many new proteins in specific tissues that were highly correlated with their mRNA levels, in addition to known key factors. These proteome data provide new perspective for understanding many aspects of maize developmental biology. Raw proteomics data are available via ProteomeXchange with identifier PXD008464.
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