Distribution and biogeography of Sanguina snow algae: Fine‐scale sequence analyses reveal previously unknown population structure

It has been previously suggested that snow algal species within the genus Sanguina (S. nivaloides and S. aurantia) show no population structure despite being found globally (S. nivaloides) or throughout the Northern Hemisphere (S. aurantia). However, systematic biogeographic research into global distributions is lacking due to few genetic and no genomic resources for these snow algae. Here, using all publicly available and previously unpublished Sanguina sequences of the Internal Transcribed Spacer 2 region, we investigated whether this purported lack of population structure within Sanguina species is supported by additional evidence. Using a minimum entropy decomposition (MED) approach to examine fine‐scale genetic population structure, we find that these snow algae populations are largely distinct regionally and have some interesting biogeographic structuring. This is in opposition to the currently accepted idea that Sanguina species lack any observable population structure across their vast ranges and highlights the utility of fine‐scale (sub‐OTU) analytical tools to delineate geographic and genetic population structure. This work extends the known range of S. aurantia and emphasizes the need for development of genetic and genomic tools for additional studies on snow algae biogeography. It has been previously suggested that snow algae within the genus Sanguina are globally cosmopolitan both in terms of occurrence and population structure. Using all publicly available and previously unpublished Sanguina sequences of the Internal Transcribed Spacer regions, we investigate whether this purported global population ubiquity of Sanguina is supported by evidence. Here, in direct opposition to the currently accepted cosmopolitan nature of these algae populations, we demonstrate global population structure and highlight the utility of fine‐scale (sub‐OTU) analytical tools to delineate geographic and genetic population structure.