Genome-wide functional annotation and structural verification of metabolic ORFeome of Chlamydomonas reinhardtii

BMC Genomics

Research

Changyu Fan¹  Yun Shen¹  Xinping Yang¹  Dawit Balcha¹  Tong Hao¹  Santhanam Balaji¹  Lila Ghamsari¹  Kourosh Salehi-Ashtiani²  Haiyuan Yu³  Jason A Papin⁴ 

[1] Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, 02115, Boston, MA, USA;Department of Genetics, Harvard Medical School, 02115, Boston, MA, USA;Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, 02115, Boston, MA, USA;Department of Genetics, Harvard Medical School, 02115, Boston, MA, USA;New York University Abu Dhabi, Abu Dhabi, UAE, and Center for Genomics and Systems Biology, Department of Biology, New York University, 10003, New York, NY, USA;Department of Biological Statistics and Computational Biology and Weill Institute for Cell and Molecular Biology, Cornell University, 14853, Ithaca, NY, USA;Department of Biomedical Engineering, University of Virginia, 22908, Charlottesville, VA, USA;

关键词: Sanger Sequencing;    Enzyme Commission;    Joint Genome Institute;    Enzyme Commission Number;    Structural Annotation;   

DOI  :  10.1186/1471-2164-12-S1-S4

来源: Springer

【 摘 要 】

BackgroundRecent advances in the field of metabolic engineering have been expedited by the availability of genome sequences and metabolic modelling approaches. The complete sequencing of the C. reinhardtii genome has made this unicellular alga a good candidate for metabolic engineering studies; however, the annotation of the relevant genes has not been validated and the much-needed metabolic ORFeome is currently unavailable. We describe our efforts on the functional annotation of the ORF models released by the Joint Genome Institute (JGI), prediction of their subcellular localizations, and experimental verification of their structural annotation at the genome scale.ResultsWe assigned enzymatic functions to the translated JGI ORF models of C. reinhardtii by reciprocal BLAST searches of the putative proteome against the UniProt and AraCyc enzyme databases. The best match for each translated ORF was identified and the EC numbers were transferred onto the ORF models. Enzymatic functional assignment was extended to the paralogs of the ORFs by clustering ORFs using BLASTCLUST.In total, we assigned 911 enzymatic functions, including 886 EC numbers, to 1,427 transcripts. We further annotated the enzymatic ORFs by prediction of their subcellular localization. The majority of the ORFs are predicted to be compartmentalized in the cytosol and chloroplast. We verified the structure of the metabolism-related ORF models by reverse transcription-PCR of the functionally annotated ORFs. Following amplification and cloning, we carried out 454FLX and Sanger sequencing of the ORFs. Based on alignment of the 454FLX reads to the ORF predicted sequences, we obtained more than 90% coverage for more than 80% of the ORFs. In total, 1,087 ORF models were verified by 454 and Sanger sequencing methods. We obtained expression evidence for 98% of the metabolic ORFs in the algal cells grown under constant light in the presence of acetate.ConclusionsWe functionally annotated approximately 1,400 JGI predicted metabolic ORFs that can facilitate the reconstruction and refinement of a genome-scale metabolic network. The unveiling of the metabolic potential of this organism, along with structural verification of the relevant ORFs, facilitates the selection of metabolic engineering targets with applications in bioenergy and biopharmaceuticals. The ORF clones are a resource for downstream studies.

【 授权许可】

Unknown   
© Ghamsari et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.