Integrated Analysis of Protein Abundance, Transcript Level, and Tissue Diversity To Reveal Developmental Regulation of Maize
收藏NIAID Data Ecosystem2026-03-10 收录
下载链接:
https://figshare.com/articles/dataset/Integrated_Analysis_of_Protein_Abundance_Transcript_Level_and_Tissue_Diversity_To_Reveal_Developmental_Regulation_of_Maize/5767023
下载链接
链接失效反馈官方服务:
资源简介:
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.
创建时间:
2018-01-08



