Title

Systematic Prediction Of Cis-Regulatory Elements In The Chlamydomonas Reinhardtii Genome Using Comparative Genomics

Abstract

Chlamydomonas reinhardtii is one of the most important microalgae model organisms and has been widely studied toward the understanding of chloroplast functions and various cellular processes. Further exploitation of C. reinhardtii as a model system to elucidate various molecular mechanisms and pathways requires systematic study of gene regulation. However, there is a general lack of genome-scale gene regulation study, such as global cis-regulatory element (CRE) identification, in C. reinhardtii. Recently, large-scale genomic data in microalgae species have become available, which enable the development of efficient computational methods to systematically identify CREs and characterize their roles in microalgae gene regulation. Here, we performed in silico CRE identification at the whole genome level in C. reinhardtii using a comparative genomics-based method. We predicted a large number of CREs in C. reinhardtii that are consistent with experimentally verified CREs. We also discovered that a large percentage of these CREs form combinations and have the potential to work together for coordinated gene regulation in C. reinhardtii. Multiple lines of evidence from literature, gene transcriptional profiles, and gene annotation resources support our prediction. The predicted CREs will serve, to our knowledge, as the first large-scale collection of CREs in C. reinhardtii to facilitate further experimental study of microalgae gene regulation. The accompanying software tool and the predictions in C. reinhardtii are also made available through a Web-accessible database (http://hulab.ucf.edu/research/projects/Microalgae/sdcre/motifcomb.html). © 2012 American Society of Plant Biologists. All Rights Reserved.

Publication Date

1-1-2012

Publication Title

Plant Physiology

Volume

160

Issue

2

Number of Pages

613-623

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1104/pp.112.200840

Socpus ID

84867119166 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84867119166

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