The availability of the complete genome sequence of many plant species has allowed analysis by various statistical methods that have promoted understanding of the function of genomes. Analysis of coding sequences and the upstream promoter elements is one of the most important issues while studying the genome complexity. Promoter of a gene plays an important role in regulating the expression behavior of a gene and determines when, where and to what extent that gene will be expressed. Understanding the promoter structure allows predictions concerning promoter positions in context of the start codon and the expression profiles of the linked gene, and sheds light on unknown transcriptional networks. RNA polymerase II synthesizes mRNA transcripts and their core DNA binding sites generally include various regulatory elements. Specific binding of RNA Pol-II to the promoters play a major role in modulating the gene expression. DNA-binding transcription factors (TFs) are one of the important components in this regulatory network. Therefore, one major task of deciphering transcriptional regulatory networks is to identify all transcription factor binding sites (TFBSs) bound by all TFs encoded in a genome, which eventually will provide the information necessary to construct models for transcriptional regulatory networks.
In silico analysis
Once a plant promoter with a unique expression pattern is identified, it is desirable to characterize the promoter as well as the corresponding gene to gain a detailed insight into its function. Although the exact information to delineate a promoter and its regulatory elements requires experimental approaches like promoter deletions (Li et al., 2001), substitutions (Harlow et al., 1996) and linker scanning (Li and Shapiro, 1993), Prior computational analysis of the sequence can serve as a guide to establish a platform for further promoter analysis. The use of different promoter prediction algorithms will leads to identification of potential cis-acting regulatory elements (CAREs), TFs and putative transcription start site (TSS). These prediction tools are based on 'search by signals' in which the algorithms aim to identify regulatory regions based on sequence context in the DNA sequence provided. A number of public databases and software tools are available for analyzing the putative cis-acting motifs and regulatory elements in a promoter region. Some of the commonly used promoter prediction and analysis tools for identification of regulatory elements are listed below.
EPD Eukaryotic promoter database
Softberry; NSITE-PL: search for consensus regulatory sequences
PLACE plant cis-acting regulatory elements
PlantCARE plants cis-acting regulatory elements
TAIR: Plant Promoter and Regulatory Element Resources
plantPAN: Gene Group Analysis
Transcription Factor Binding Sites:
Softberry; TSSP: Search for TF-binding sites
Phylogenetic analysis of regulatory elements:
However, the in silico detection of CAREs does not necessarily mean all the elements identified on the DNA sequence by the software are functionally relevant. Since, these cis-acting elements generally consists of very short stretch of nucleotides, there is always a random chance of finding such sequences in a long DNA sequence (Blanchette and Sinha 2001). One of the few approaches to overcome the above limitation is to carry out a phylogenetic foot-printing to find conserved regulatory elements among the functionally related promoters of diverse species or between co-expressed genes (Saha et al. 2007a).
In addition, the promoter elements are also known to contain the transcription start site (TSS) or +1 site, therefore locating functional TSS in the cloned DNA fragment is an important step in characterizing a promoter element. The techniques like primer extension, RNase protection assay, S1 nuclease analysis and 5' rapid amplification of cDNA ends (RACE) are employed for mapping of TSS. For analyzing regulatory elements of a promoter, various transgenic-based in vivo promoter analyses as well as in vitro analysis for trans-acting factor binding to regulatory elements are important in deciphering the transcriptional regulation of a gene. Identification of candidate TFs are possible through experimental approaches like electrophoretic mobility shift assay (EMSA) and foot printing techniques using DNaseI and dimethyl sulphate (DMS).
Transgenic-based promoter analysis
Characterization of a promoter module and its regulatory regions requires a suitable transgenic assay system to monitor the in vivo activity level. The transgenic analysis of plant promoter includes steps like designing of vector constructs consisting of putative promoter fragments, a suitable method for introduction of tailor-made constructs in plant system and generation of number of transgenics and a reliable assay method to monitor the pattern and level of activity. Designing of vector constructs usually involves a promoterless reporter gene and a putative promoter fragment. Based on the nature and strategy of promoter analysis, constructs are varies and designed accordingly for
(i) Promoter deletion,
(ii) Linker scanning,
(iii) Base substitution mutagenesis and
(iv) Identification of enhancer element in the promoter sequence.
The in vivo activity of the promoter analysis constructs are generally monitored in the native plant system or in model plant species like Arabidopsis, tobacco or rice. The recombinant vector cassettes are introduced into plant system either through transient or stable transformation methods in plants.
Blanchette, M. and Sinha, S. (2001). Separating real motifs from their artifacts. Bioinformatics 17: 30-38.
Bucher, P. (1990). Weight matrix descriptions of four eukaryotic RNA polymerase II promoter elements derived from 502 unrelated promoter sequences. J. Mol. Biol. 212: 563-578.
Davuluri, R.V., Sun, H., Palaniswamy, S.K., Matthews, N., Molina, C., Kurtz, M. and Grotewold, E. (2003). AGRIS: Arabidopsis Gene Regulatory Information Server, an information resource of Arabidopsis cis-regulatory elements and transcription factors. BMC Bioinformatics, 23: 25.
Higo, K., Ugawa, Y., Iwamoto, M. and Korenaga, T. (1999). Plant cis-acting regulatory DNA elements (PLACE) database: 1999. Nucleic Acids Research, 27: 297-300.
Lescot, M., DΓ©hais, P., Thijs, G., Marchal, K., Moreau, Y., Van de Peer, Y., RouzΓ©, P. and Rombauts, S. (2002) PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Research, 30: 325-327.
Li, X.M. and Shapiro, L. J. (1993). Three-step PCR mutagenesis for 'linker scanning'. Nucleic Acids Research, 21: 3745-3748.
Saha, D., Prasad, A.M., Sujatha, T.P., Kumar, V., Jain, P.K., Bhat, S.R. and Srinivasan, R. (2007a). In silico analysis of the Lateral Organ Junction (loj) gene and promoter of Arabidopsis thaliana. In Silico Biology, 7: 7-19.
About Author / Additional Info:
A scientist in the field of Plant Biotechnology from India