Evolutionary dynamics of chloroplast genomes in low light: A case study of the endolithic green alga ostreobium quekettii

Vanessa R. Marcelino, Ma Chiela M. Cremen, Chistopher J. Jackson, Anthony A.W. Larkum, Heroen Verbruggen

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36 Citations (Scopus)


Some photosynthetic organisms live in extremely low light environments. Light limitation is associated with selective forces as well as reduced exposure tomutagens, and over evolutionary timescales it can leave a footprint on species' genomes. Here, we present the chloroplast genomes of four green algae (Bryopsidales, Ulvophyceae), including the endolithic (limestone-boring) alga Ostreobium quekettii, which is a low light specialist. We use phylogenetic models and comparative genomic tools to investigate whether the chloroplast genome of Ostreobium corresponds to our expectations of how low light would affect genome evolution. Ostreobium has thesmallest andmostgene-dense chloroplastgenome amongUlvophyceae reported todate, matchingour expectation that light limitation would impose resource constraints reflected in the chloroplast genome architecture. Rates of molecular evolution are significantly slower along the phylogenetic branch leading to Ostreobium, in agreement with the expected effects of low light and energy levels on molecular evolution. We expected the ability of Ostreobium to perform photosynthesis in very low light to be associatedwithpositive selection ingenes relatedtothephotosynthetic machinery, but instead,weobservedthat these genesmay be under stronger purifying selection. Besides shedding light on the genome dynamics associated with a low light lifestyle, this study helps to resolve the role of environmental factors in shaping the diversity of genome architectures observed in nature.

Original languageEnglish
Pages (from-to)2939-2951
Number of pages13
JournalGenome Biology and Evolution
Issue number9
Publication statusPublished - Sept 2016
Externally publishedYes


  • boring algae
  • genome streamlining
  • photosynthesis
  • rates of evolution
  • stoichiogenomics.

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