Title

Motif Analysis Unveils The Possible Co-Regulation Of Chloroplast Genes And Nuclear Genes Encoding Chloroplast Proteins

Keywords

Chloroplast gene transcriptional regulation; DNA regulatory sequences; Motif analysis; Nuclear-genes encoding chloroplast proteins

Abstract

Chloroplasts play critical roles in land plant cells. Despite their importance and the availability of at least 200 sequenced chloroplast genomes, the number of known DNA regulatory sequences in chloroplast genomes are limited. In this paper, we designed computational methods to systematically study putative DNA regulatory sequences in intergenic regions near chloroplast genes in seven plant species and in promoter sequences of nuclear genes in Arabidopsis and rice. We found that -35/-10 elements alone cannot explain the transcriptional regulation of chloroplast genes. We also concluded that there are unlikely motifs shared by intergenic sequences of most of chloroplast genes, indicating that these genes are regulated differently. Finally and surprisingly, we found five conserved motifs, each of which occurs in no more than six chloroplast intergenic sequences, are significantly shared by promoters of nuclear-genes encoding chloroplast proteins. By integrating information from gene function annotation, protein subcellular localization analyses, protein-protein interaction data, and gene expression data, we further showed support of the functionality of these conserved motifs. Our study implies the existence of unknown nuclear-encoded transcription factors that regulate both chloroplast genes and nuclear genes encoding chloroplast protein, which sheds light on the understanding of the transcriptional regulation of chloroplast genes. © 2012 Springer Science+Business Media B.V.

Publication Date

9-1-2012

Publication Title

Plant Molecular Biology

Volume

80

Issue

2

Number of Pages

177-187

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/s11103-012-9938-6

Socpus ID

84865416481 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84865416481

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