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For decades, the unicellular alga Chlamydomonas reinhardtii has been a model organism for studies of photosynthesis, chloroplast structure and function, and cilia biology, and currently it shows much promise in biofuel research. In the laboratory, it can be grown and manipulated much like bacteria or yeast and can grow either autotrophically or heterotrophically in defined liquid medium or on agar plates. A wide variety of genetic resources and phenotypic mutants are available (Harris, 2008), and the genome of strain CC-503 has been sequenced and annotated as the reference genome (Merchant et al., 2007).
Most current research with Chlamydomonas uses one or more of several dozen interrelated strains, and it is believed that these laboratory strains all are derived from several Chlamydomonas lines grown by Gilbert Smith in the 1940s and 1950s (Smith and Regnery, 1950). Descendants of these strains show a wide range of phenotypic diversity regarding nitrate and micronutrient utilization, responses to light, and tolerance of iron-limited conditions (see figure, top panel). Gallaher et al. (2015) use whole-genome sequencing to resequence a variety of laboratory strains in current use, and they provide valuable insights into the genetic basis for much of the observed phenotypic diversity. In a study of 39 strains, they discovered a total of over 600,000 single nucleotide variants in the 109-Mb Chlamydomonas genome, using CC-503 as the reference genome. For a number of strains, the basal variant rate compared with the reference genome was 0.002% but jumped 1000-fold to 2% in numerous regions of the genome.
Phenotypic variation of Chlamydomonas laboratory strains in response to iron concentration (top panel). Geographic clustering of field strains is shown in the bottom panel. (Reprinted from Gallaher et al. [2015], Supplemental Figure 1A, and Flowers et al. [2015], Figure 2A.)
Because these regions of high variation rate occurred at specific locations in the genome and in multiple strains, the authors hypothesized that the blocks of variation arose by the crossing of two ancestral strains that had diverged ∼2% from each other. They designated these as haplotypes 1 and 2. They then defined 41 distinct sequence blocks so that, within each block, each of the 39 lab strains was either completely haplotype 1 or haplotype 2. A binary code was assigned to each strain, and this acted as a unique fingerprint to allow positive identification and characterization. Based on their data, they then suggest replacing the current three-lineage model of Chlamydomonas strains with a more accurate five-lineage model. Although over 99% of the SNVs could be attributed to differences between the two ancestral haplotypes, the remainder (over 4000) were due to mutations that had accumulated since the initial distribution of the strains in the 1950s. Furthermore, the authors show evidence for widespread transposon jumping in the Chlamydomonas genome, even finding transposition events that appeared to occur between the sequencing of the Chlamydomonas reference genome and the present time.
In addition to providing a valuable resource for Chlamydomonas researchers, this work enabled the authors to identify several strains that had been mislabeled. By comparing the fingerprints of parental and progeny strains, they were also able to correct some inaccuracies in the histories of some strains. They then examined three pairs of strains resulting from repeated backcrosses that were performed to create near-isogenic lines and could determine how isogenic they really were at the nucleotide level. In the process, they identified some isogenic pairs that will be very useful for further study.
In a related study of genomic diversity in Chlamydomonas, Flowers et al. (2015) used whole-genome resequencing to analyze genetic diversity in 12 field isolates from the United States and Canada plus eight commonly used laboratory strains. They discovered a high level of nucleotide diversity compared with the reference strain CC-503, finding 2.8 ± 0.7 single-nucleotide polymorphisms per site. Consistent with previous results showing a very high degree of genomic diversity in Chlamydomonas, they note that ∼35% of the SNPs were restricted to one or another of the Chlamydomonas strains. Principal component and neighbor-joining tree analyses show evidence for geographic structuring among the field isolates, which cluster into three main populations: southeastern US, northeastern US/Canada, and midwestern US (see figure, bottom panel). This was supported using a clustering algorithm, which suggested the existence of two or more ancestral populations. Unexpectedly, a strain from the western US is closely related to the reference laboratory strain CC-503 but appears to be distinct from the other field isolates.
Although detailed study of SNPs revealed dense clusters of SNPs in protein-coding regions, the most conserved genes, often invariant at the amino acid level, were found in genes involved in photosynthesis, light perception, protein translation, and molecular pattern recognition pathways. Because the majority of the life cycle of Chlamydomonas is haploid, loss-of-function mutations are not well tolerated. Accordingly, few deletions were found in single-copy genes, with most being found in members of gene families, such as kinases and peptidases. They examined a set of genes unique to Chlamydomonas and found that loss-of-function mutations were overrepresented in this set. In contrast, gene deletions were significantly depleted in a set of several thousand “ancient genes,” defined as those that are shared with Arabidopsis thaliana. Interestingly, among laboratory strains, they found numerous large-scale duplications, including duplication of an entire chromosome arm in one strain. The authors suggest that these duplications could confer a selective advantage for cells grown in culture and can help us understand how wild strains adapt to laboratory conditions.
In summary, this work describes the genetic basis for much of the phenotypic diversity seen in common Chlamydomonas laboratory strains. Considered together, these studies give us fresh insight into the origin, identity, and genetic variation of Chlamydomonas strains, and they provide a valuable genomic resource to the Chlamydomonas and plant science communities. This not only will assist in identification of quantitative trait loci in Chlamydomonas but also will provide a huge reservoir of functional variation for future genetic studies. Using RNA-seq analyses, it provides a method to positively identify Chlamydomonas strains and help with interpretation of gene expression data. In addition to identifying mislabeled strains, this work will help future researchers better choose and characterize their strains for Chlamydomonas research.
