Rusa deer microbiota: the importance of preliminary data analysis for meaningful diversity comparisons

Area of Science:

• Conservation Biology
• Microbiome Research
• Wildlife Ecology

Background:

• The gut microbiome plays a crucial role in wildlife health and conservation.
• Factors like behavior and habitat influence animal microbiota, but sampling methods can introduce data abnormalities.
• Preliminary data analysis, such as rarefaction, is essential before downstream microbiome analysis.

Purpose of the Study:

• To investigate the impact of data rarefaction and aggregation on the comparison of gut microbial diversity in wild rusa deer.
• To assess how different statistical approaches affect microbiome data interpretation in a conservation context.

Main Methods:

• Collected 85 fecal samples from 11 rusa deer populations across three national parks.
• Sequenced 16S rRNA gene fragments using the Illumina Nova-Seq platform.
• Applied data rarefaction (minimum and fixed library sizes) and aggregation (11 populations into 3 sites) for diversity analysis.

Main Results:

• Significant differences in alpha and beta diversity were observed between deer populations, irrespective of rarefaction library size.
• No significant diversity differences were found between the broader research sites.
• Data rarefaction and aggregation methods yielded varying diversity metric values.

Conclusions:

• Statistical analysis methods, including data normalization, are critical in microbiome studies for conservation biology.
• Detailed reporting of data normalization is recommended to account for suboptimal sampling, especially with fecal samples.