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Dryad

Data from: Metabarcoding of fecal pellets in wild muskox populations reveals negative relationships between microbiome and diet alpha diversity

Cite this dataset

Prewer, Erin (2024). Data from: Metabarcoding of fecal pellets in wild muskox populations reveals negative relationships between microbiome and diet alpha diversity [Dataset]. Dryad. https://doi.org/10.5061/dryad.h9w0vt4n3

Abstract

Microbiome diversity and diet composition concomitantly influence species health, fitness, immunity, and digestion. In environments where diet varies spatially and temporally, microbiome plasticity may promote rapid host adaptation to available resources. For northern ungulates in particular, metabarcoding of noninvasively collected fecal pellets presents unprecedented insights into their diverse ecological requirements and niches by clarifying the interrelationships of microbiomes, key to deriving nutrients, in context of altered forage availability in changing climates. Muskoxen (Ovibos moschatus) are Arctic-adapted species that experience fluctuating qualities and quantities of vegetation. Geography and seasonality have been noted to influence microbiome composition and diversity in muskoxen, yet it is unclear how their microbiomes intersect with diet. Following observations from other species, we hypothesized increasing diet diversity would result in higher microbiome diversity in muskoxen. We assessed diet composition in muskoxen using three common plant metabarcoding markers and explored correlations with microbiome data. Patterns of dietary diversity and composition were not fully concordant among the markers used, yet all reflected the primary consumption of willows and sedges. Individuals with similar diets had more similar microbiomes, yet in contrast to most literature, yielded negative relationships between microbiome and diet alpha diversity. This negative correlation may reflect the unique capacities of muskoxen to survive solely on high-fiber Arctic forage and provide insight into their resiliency to exploit changing dietary resources in a rapidly warming Arctic altering vegetation diversity.

README: Muskox Diet Metabarcoding from Metabarcoding of fecal pellets in wild muskox populations reveals negative relationships between microbiome alpha diversity and diet.


In this study, we amplify three common plant markers, TRNL, RBCL, and ITS from fecal samples to assess the diet of wild muskoxen across much of their Canadian range. Sampling from across different ecozones and seasons was performed to better understand the spectrum of wild muskoxen diets and how diet is influenced by geography and seasonality. We then compared the diversity and composition of the diet to that of the microbiome to determine how vegetation in different landscapes contribute to bacterial variation in muskox gut microbiomes, in context of their high fibre diet. These data provide insight into the plasticity of microbiomes relative to vegetation availability, which in turn also allow for predictions of the long-term impact climate change and concomitant vegetation changes have on muskox viability.

Description of the Data and file structure

This data includes raw sequence files for each sample used in this study. Each sample is labelled with it's sample ID and contains reads associated with all three markers utilized in this study (TRNL, RBCL and ITS2). This dataset also includes the OTU tables in a biom format for all three markers individually. The biom file can be imported into R and identifies organisms to the order level. The biom files also include the metadata information which includes season and ecozone the samples were collected. Finally it contains an excel mapping file in Qiime2 format that can also be imported into R. The mapping files include the metadata for each sample used including ecozone and season collected.

Sharing/access Information

n/a

Methods

DNA from fecal samples were extracted using the Qiagen Power Fecal DNA extraction kit. The Illumina 16S metagenomic library protocol was followed using ITS2, RBCL, and TRNL markers.

Usage notes

Data includes raw fastq files for each sample. Each raw file includes reads from ITS2, RBCL and TRNL.

Funding

Natural Sciences and Engineering Research Council

ArcticNet