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Comparative network analysis reveals that tissue specificity and gene function are important factors influencing the mode of expression evolution in Arabidopsis and rice

Sara Movahedi (UGent) , Yves Van de Peer (UGent) and Klaas Vandepoele (UGent)
(2011) PLANT PHYSIOLOGY. 156(3). p.1316-1330
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Bioinformatics: from nucleotids to networks (N2N)
Abstract
Microarray experiments have yielded massive amounts of expression information measured under various conditions for the model species Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa). Expression compendia grouping multiple experiments make it possible to define correlated gene expression patterns within one species and to study how expression has evolved between species. We developed a robust framework to measure expression context conservation (ECC) and found, by analyzing 4,630 pairs of orthologous Arabidopsis and rice genes, that 77% showed conserved coexpression. Examples of nonconserved ECC categories suggested a link between regulatory evolution and environmental adaptations and included genes involved in signal transduction, response to different abiotic stresses, and hormone stimuli. To identify genomic features that influence expression evolution, we analyzed the relationship between ECC, tissue specificity, and protein evolution. Tissue-specific genes showed higher expression conservation compared with broadly expressed genes but were fast evolving at the protein level. No significant correlation was found between protein and expression evolution, implying that both modes of gene evolution are not strongly coupled in plants. By integration of cis-regulatory elements, many ECC conserved genes were significantly enriched for shared DNA motifs, hinting at the conservation of ancestral regulatory interactions in both model species. Surprisingly, for several tissue-specific genes, patterns of concerted network evolution were observed, unveiling conserved coexpression in the absence of conservation of tissue specificity. These findings demonstrate that orthologs inferred through sequence similarity in many cases do not share similar biological functions and highlight the importance of incorporating expression information when comparing genes across species.
Keywords
TRANSCRIPTOME, STRESS, SEQUENCE, CONSERVATION, DIVERGENCE, DUPLICATE GENES, SUBSTITUTION RATES, LOCAL COEXPRESSION DOMAINS, COMPARATIVE GENOMICS, CIS-REGULATORY ELEMENTS

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Citation

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Chicago
Movahedi, Sara, Yves Van de Peer, and Klaas Vandepoele. 2011. “Comparative Network Analysis Reveals That Tissue Specificity and Gene Function Are Important Factors Influencing the Mode of Expression Evolution in Arabidopsis and Rice.” Plant Physiology 156 (3): 1316–1330.
APA
Movahedi, S., Van de Peer, Y., & Vandepoele, K. (2011). Comparative network analysis reveals that tissue specificity and gene function are important factors influencing the mode of expression evolution in Arabidopsis and rice. PLANT PHYSIOLOGY, 156(3), 1316–1330.
Vancouver
1.
Movahedi S, Van de Peer Y, Vandepoele K. Comparative network analysis reveals that tissue specificity and gene function are important factors influencing the mode of expression evolution in Arabidopsis and rice. PLANT PHYSIOLOGY. 2011;156(3):1316–30.
MLA
Movahedi, Sara, Yves Van de Peer, and Klaas Vandepoele. “Comparative Network Analysis Reveals That Tissue Specificity and Gene Function Are Important Factors Influencing the Mode of Expression Evolution in Arabidopsis and Rice.” PLANT PHYSIOLOGY 156.3 (2011): 1316–1330. Print.
@article{1864506,
  abstract     = {Microarray experiments have yielded massive amounts of expression information measured under various conditions for the model species Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa). Expression compendia grouping multiple experiments make it possible to define correlated gene expression patterns within one species and to study how expression has evolved between species. We developed a robust framework to measure expression context conservation (ECC) and found, by analyzing 4,630 pairs of orthologous Arabidopsis and rice genes, that 77\% showed conserved coexpression. Examples of nonconserved ECC categories suggested a link between regulatory evolution and environmental adaptations and included genes involved in signal transduction, response to different abiotic stresses, and hormone stimuli. To identify genomic features that influence expression evolution, we analyzed the relationship between ECC, tissue specificity, and protein evolution. Tissue-specific genes showed higher expression conservation compared with broadly expressed genes but were fast evolving at the protein level. No significant correlation was found between protein and expression evolution, implying that both modes of gene evolution are not strongly coupled in plants. By integration of cis-regulatory elements, many ECC conserved genes were significantly enriched for shared DNA motifs, hinting at the conservation of ancestral regulatory interactions in both model species. Surprisingly, for several tissue-specific genes, patterns of concerted network evolution were observed, unveiling conserved coexpression in the absence of conservation of tissue specificity. These findings demonstrate that orthologs inferred through sequence similarity in many cases do not share similar biological functions and highlight the importance of incorporating expression information when comparing genes across species.},
  author       = {Movahedi, Sara and Van de Peer, Yves and Vandepoele, Klaas},
  issn         = {0032-0889},
  journal      = {PLANT PHYSIOLOGY},
  keyword      = {TRANSCRIPTOME,STRESS,SEQUENCE,CONSERVATION,DIVERGENCE,DUPLICATE GENES,SUBSTITUTION RATES,LOCAL COEXPRESSION DOMAINS,COMPARATIVE GENOMICS,CIS-REGULATORY ELEMENTS},
  language     = {eng},
  number       = {3},
  pages        = {1316--1330},
  title        = {Comparative network analysis reveals that tissue specificity and gene function are important factors influencing the mode of expression evolution in Arabidopsis and rice},
  url          = {http://dx.doi.org/10.1104/pp.111.177865},
  volume       = {156},
  year         = {2011},
}

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