Decoding Populations in the Ocean Microbiome

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1186/s40168-024-01778-0. This is version 1 of this Preprint.

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Authors

Ramiro Logares 

Abstract

Understanding the characteristics and structure of populations is fundamental to comprehending ecosystem processes and evolutionary adaptations. While the study of animal and plant populations has spanned a few centuries, microbial populations have been under scientific scrutiny for a considerably shorter period. In the ocean, analyzing the genetic composition of microbial populations and their adaptations to multiple niches can yield important insights into ecosystem function and the microbiome's response to global change. However, microbial populations have remained elusive to the scientific community due to the challenges associated with isolating microorganisms in the laboratory. Today, advancements in large-scale metagenomics and metatranscriptomics facilitate the investigation of populations from many uncultured microbial species directly from their habitats. The knowledge acquired thus far reveals substantial genetic diversity among various microbial species, showcasing distinct patterns of population differentiation and adaptations, and highlighting the significant role of selection in structuring populations. In the coming years, population genomics is expected to significantly increase our understanding of the architecture and functioning of the ocean microbiome, providing insights into its vulnerability or resilience in the face of ongoing global change.

DOI

https://doi.org/10.32942/X2801G

Subjects

Life Sciences

Keywords

microbes, populations, ocean, metagenomics, metatranscriptomics, populations, ocean, metagenomics, metatranscriptomics

Dates

Published: 2023-09-30 15:50

Last Updated: 2023-09-30 19:50

License

CC-BY Attribution-NonCommercial 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None