The ability to alter gene expression, and as such, metabolic pathways within green microalgae, is of a crucial importance in optimizing those algae for biofuel pro­duction. Achieving such alterations and rational modifications of expression relies primarily on the identification of transcription factors (TFs), genes, and enzymes implicated in metabolic pathways driving the synthesis of oil and hydrogenated metabolites that can potentially be used as biofuels. Post-identification, via struc­tural and functional annotations of genomes, the establishment of a library of cloned, ready to transform, open reading frames (ORFs) and TFs makes the optimization process one step closer (Fig. 9.3). Attempts to clone the metabolic ORFeome of model green algae, C. reinhardtti, have been made and published by Ghamsari et al. (2011) and Chang et al. (2011). The structural annotation of the ORFs was based on models generated by the Joint Genome Institute (JGI) (Merchant et al. 2007) and AUGUSTUS gene prediction algorithm (http://augustus. gobics. de/predictions/chlamydomonas/). The outcome leads to the generation of Gateway-compatible clones that can easily be moved to a plethora of available expression vectors.

Another attempt, as part of an ongoing work, is the genome-wide cloning of TFs in C. reinhardtti to add a regulatory dimension to the available clone resources (unpublished data). The completion of such an endeavor will result in a library of TF clones that are Gateway compatible and readily available for transformation to

alter and modify the expression of target genes. Clones can also be obtained from the Chlamydomonas Resource Center (http://www. chlamy. org/). The center hosts a multitude of C. reinhardtti strains, plasmids, molecular kits, and cDNA libraries.

The importance and relevance of cloning has been underlined as a major initial step in the process of algal optimization for biofuel production by making available a library of metabolic and transcription factor clones that can be used to modify the genetic information and expression patterns and, subsequently, directionally alter the metabolism in algal cells toward a higher yield of hydrogenated metabolites suitable for biofuel use.