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Updated: Jun 18, 2026

Mating and Tetrad Separation of Chlamydomonas reinhardtii for Genetic Analysis
Published on: August 12, 2009
Efficient DNA-free co-targeting of nuclear genes in Chlamydomonas reinhardtii
Claudia Battarra1, Max Angstenberger2,3, Roberto Bassi4
1Department of Biotechnology, University of Verona, Cà Vignal 1, Strada le Grazie 15, 31734, Verona, Italy.
Abstract:
Chlamydomonas reinhardtii, a model organism for unicellular green microalgae, is widely used in basic and applied research. Nonetheless, proceeding towards synthetic biology requires a full set of manipulation techniques for inserting, removing, or editing genes. Despite recent advancements in CRISPR/Cas9, still significant limitations in producing gene knock-outs are standing, including (i) unsatisfactory genome editing (GE) efficiency and (ii) uncontrolled DNA random insertion of antibiotic resistance markers. Thus, obtaining efficient gene targeting without using marker genes is instrumental in developing a pipeline for efficient engineering of strains for biotechnological applications. We developed an efficient DNA-free gene disruption strategy, relying on phenotypical identification of mutants, to (i) precisely determine its efficiency compared to marker-relying approaches and (ii) establish a new DNA-free editing tool. This study found that classical CRISPR Cas9-based GE for gene disruption in Chlamydomonas reinhardtii is mainly limited by DNA integration. With respect to previous results achieved on synchronized cell populations, we succeeded in increasing the GE efficiency of single gene targeting by about 200 times and up to 270 times by applying phosphate starvation. Moreover, we determined the efficiency of multiplex simultaneous gene disruption by using an additional gene target whose knock-out did not lead to a visible phenotype, achieving a co-targeting efficiency of 22%. These results expand the toolset of GE techniques and, additionally, lead the way to future strategies to generate complex genotypes or to functionally investigate gene families. Furthermore, the approach provides new perspectives on how GE can be applied to (non-) model microalgae species, targeting groups of candidate genes of high interest for basic research and biotechnological applications.
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