Systems Analysis of Seed Filling in Arabidopsis: Using General Linear Modeling to Assess Concordance of Transcript and Protein Expression

Previous systems analyses in plants have focused on a single developmental stage or time point, although it is often important to additionally consider time-index changes. During seed development a cascade of events occurs within a relatively brief time scale. We have collected protein and transcrip...

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Bibliographic Details
Published in:Plant physiology (Bethesda) 2010-04, Vol.152 (4), p.2078-2087
Main Authors: Hajduch, Martin, Hearne, Leonard B, Miernyk, Jan A, Casteel, Jill E, Joshi, Trupti, Agrawal, Ganesh K, Song, Zhao, Zhou, Mingyi, Xu, Dong, Thelen, Jay J
Format: Article
Language:English
Subjects:
Arabidopsis - embryology
Correlation coefficients
Correlations
Datasets
Developmental stages
Electrophoresis, Gel, Two-Dimensional
Fatty Acids - metabolism
Filling period
Gels
Gene Expression Profiling
Genes
Linear Models
Plant Proteins - metabolism
Protein synthesis
Proteomics
RNA, Messenger - metabolism
Seeds
Seeds - metabolism
SYSTEMS BIOLOGY, MOLECULAR BIOLOGY, AND GENE REGULATION
Tandem Mass Spectrometry
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Summary:Previous systems analyses in plants have focused on a single developmental stage or time point, although it is often important to additionally consider time-index changes. During seed development a cascade of events occurs within a relatively brief time scale. We have collected protein and transcript expression data from five sequential stages of Arabidopsis (Arabidopsis thaliana) seed development encompassing the period of reserve polymer accumulation. Protein expression profiling employed two-dimensional gel electrophoresis coupled with tandem mass spectrometry, while transcript profiling used oligonucleotide microarrays. Analyses in biological triplicate yielded robust expression information for 523 proteins and 22,746 genes across the five developmental stages, and established 319 protein/transcript pairs for subsequent pattern analysis. General linear modeling was used to evaluate the protein/transcript expression patterns. Overall, application of this statistical assessment technique showed concurrence for a slight majority (56%) of expression pairs. Many specific examples of discordant protein/transcript expression patterns were detected, suggesting that this approach will be useful in revealing examples of posttranscriptional regulation.
ISSN:0032-0889
1532-2548
1532-2548
DOI:10.1104/pp.109.152413