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Updated: Feb 12, 2026

Genetic Manipulation in Δku80 Strains for Functional Genomic Analysis of Toxoplasma gondii
Published on: July 12, 2013
Genome variation in nine co-occurring toxic Cylindrospermopsis raciborskii strains
Anusuya Willis1, Jason N Woodhouse2, Sarah E Ongley3
1Australian Rivers Institute, Griffith University, QLD, Australia.
Abstract:
Cyanobacteria form harmful algal blooms and are highly adapted to a range of habitats, in part due to their phenotype plasticity. This plasticity is partially the result of co-existence of multiple strains within a single population. The toxic cyanobacterium Cylindrospermopsis raciborskii has remarkable phenotypic plasticity, strain variation and environmental adaptation resulting in an expansion of its global range. To understand the genetic basis of the high level of plasticity within a C. raciborskii population, the genomes of nine co-occurring strains were compared. The strains differed in morphology, toxin cell quotas and physiology, despite being obtained from a single water sample. Comparative genomics showed that three coiled strains were 3.9 Mbp in size, with 3544 ± 11 genes, while straight strains were 3.8 Mbp in size, with 3485 ± 20 genes. The core proteome comprised 86% of the genome and consisted of 2891 orthologous groups (OGs), whereas the variable genome comprised ∼14% (847 OGs), and the strain specific genome only ∼1% (433 OGs).There was a high proportion of variable strain-specific genes for the very closely related strains, which may underpin strain differentiation. The variable genes were associated with environmental responses and adaptation, particularly phage defence, DNA repair, membrane transport, and stress, illustrative of the adaptability of the strains in response to environmental and biological stressors. This study shows that high genomic variability exists between co-occurring strains and may be the basis of strain phenotypic differences and plasticity of populations. Therefore management and prediction of blooms of this harmful species requires different approaches to capture this strain variability.
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