Metatranscriptomes-based sequence similarity networks uncover genetic signatures within parasitic freshwater microbial eukaryotes.

ABSTRACT:

Background

Microbial eukaryotes play a crucial role in biochemical cycles and aquatic trophic food webs. Their taxonomic and functional diversity are increasingly well described due to recent advances in sequencing technologies. However, the vast amount of data produced by -omics approaches require data-driven methodologies to make predictions about these microorganisms' role within ecosystems. Using metatranscriptomics data, we employed a sequence similarity network-based approach to explore the metabolic specificities of microbial eukaryotes with different trophic modes in a freshwater ecosystem (Lake Pavin, France).

Results

A total of 2,165,106 proteins were clustered in connected components enabling analysis of a great number of sequences without any references in public

SUBMITTER: Monjot A 

PROVIDER: S-EPMC11800578 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature