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Subtle biogeochemical regimes in the Indian Ocean revealed by spatial and diel frequency of Prochlorococcus haplotypes
Author(s) -
Larkin Alyse A.,
Garcia Catherine A.,
Ingoglia Kimberly A.,
Garcia Nathan S.,
Baer Steven E.,
Twining Benjamin S.,
Lomas Michael W.,
Martiny Adam C.
Publication year - 2020
Publication title -
limnology and oceanography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.7
H-Index - 197
eISSN - 1939-5590
pISSN - 0024-3590
DOI - 10.1002/lno.11251
Subject(s) - prochlorococcus , biogeochemical cycle , biology , ecology , diel vertical migration , ocean gyre , oceanography , genetics , synechococcus , geology , subtropics , cyanobacteria , bacteria
While the majority of studies use the environment to describe microbial populations, the high diversity of microbes can conversely be used as a resource to understand subtle environmental variability. Here, we used a high‐resolution spatial and temporal analysis of Prochlorococcus sp. in the Eastern Indian Ocean to determine whether ecotypes and microdiverse taxa can be used to identify fine‐scale biogeochemical regimes in this under‐studied region. A total of 246 DNA samples were collected every 4–6 h in April 2016 on GO‐SHIP cruise I09N, which transected gyre, equatorial, and monsoonal ecosystems between Western Australia and the Bay of Bengal. Using amplicon sequencing of the highly variable rpo C1 marker, we found that the region was largely dominated by the Prochlorococcus HL‐II clade. Conserved single nucleotide polymorphisms (SNPs) were used to identify four microdiverse haplotypes, or SNP‐delineated taxa, within the HL‐II clade of Prochlorococcus . The haplotypes showed regional patterns of relative gene count abundance that were significantly correlated with environmental conditions. Additionally, we used nonlinear least squares models to fit the sine wave function to our data and demonstrate that the haplotypes show distinct patterns in relative diel frequency, providing evidence that these microdiverse populations are ecologically and evolutionarily distinct. Overall, we show how the integration of a genomics data set into a biogeochemical framework can reveal a more nuanced understanding of a complex ocean basin.