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Long-Read Sequencing for Species-Level Resolution of the Equine Gut Microbiota Reveals the Need for Improved Databases.
Abstract: Differences in gut microbiota composition related to diet have been reported in horses, but characterization of specific microbial taxa remains limited, particularly at the species level. The objective of this study was to use long-read sequencing of the 16S rRNA gene to provide additional taxonomic insight into the intestinal microbiota in horses. Fecal samples were collected from 12 horses on pasture and from 6 of them after switching to a hay diet. Sequencing yielded low read counts per sample, and the analysis failed to detect statistical differences in alpha- and beta-diversity among dietary groups ( > 0.05). Species-level taxonomic resolution was not substantially enhanced using long-read sequencing, as only 3% of reads were assigned at the species level, and an additional 3% of reads were assigned at the genus level. The majority of reads (49%) were classified at the family level. Accordingly, in this dataset, long-read sequencing did not provide additional biological insight into diet-associated differences in the equine gut microbial community. This limited added value can be explained by the low sequencing depth obtained for several samples and the current incompleteness of reference databases for equine bacterial taxa, highlighting ongoing challenges in achieving high-resolution characterization of the equine gut microbiome.
Publication Date: 2026-05-09 PubMed ID: 42193750PubMed Central: PMC13203547DOI: 10.3390/ani16101459Google Scholar: Lookup The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- Journal Article
Summary
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Overview
- This study investigated the use of long-read sequencing technology to analyze the gut microbiota of horses at a detailed taxonomic level, focusing on how diet influences microbial composition.
- The research highlighted challenges in identifying species-level differences due to low sequencing depth and limitations of existing microbial reference databases for horses.
Background and Research Objective
- Gut microbiota in horses varies depending on diet, but detailed identification of specific microbes, especially at the species level, remains difficult.
- Traditional sequencing methods often provide genus or higher taxonomic resolution but struggle to reliably identify species.
- The objective was to apply long-read sequencing of the 16S rRNA gene, which can sequence longer stretches of DNA and potentially improve species-level identification, to better characterize the equine gut microbiome.
Methods
- Fecal samples were collected from 12 horses that were initially grazing on pasture.
- Six of these horses were subsequently switched to a hay-only diet, and additional fecal samples were collected from them to examine diet-related changes.
- Long-read sequencing technology was used to analyze the 16S rRNA gene, aiming to classify bacteria present in the samples down to the species level.
Key Findings
- The number of sequencing reads obtained per sample was low, which limited the data available for analysis.
- No statistically significant differences were found in alpha-diversity (microbial diversity within a sample) or beta-diversity (differences between samples) between dietary groups (pasture vs. hay diet).
- Only 3% of total sequencing reads were confidently assigned to a species, and another 3% were assigned at the genus level, indicating limited resolution despite the long-read approach.
- Nearly half of the reads (49%) could only be classified at the family level, highlighting the challenges in identifying bacteria deeper in the taxonomic hierarchy.
- The incomplete nature of current reference databases for equine gut bacteria contributed to the poor species-level assignments.
Interpretation and Significance
- Long-read sequencing did not significantly improve species-level resolution of the equine gut microbiota compared to existing methods, partly due to insufficient sequencing depth and gaps in reference data.
- The findings emphasize that databases for equine-specific bacterial taxa need to be expanded and refined to support more detailed microbiome studies.
- Improved sequencing coverage and richer microbial reference collections will be necessary in future research to better understand diet-related microbial shifts at species-level resolution in horse guts.
- This work highlights ongoing challenges in gut microbiome characterization for horses, which could impact understanding of nutrition, health, and disease management in equine practice.
Conclusions
- The study shows that current long-read 16S rRNA gene sequencing approaches, while promising, are insufficient alone for detailed species-level analysis of equine gut microbiota under the given experimental conditions.
- Better sequencing depth and more comprehensive, species-level equine microbial reference databases are needed to harness the full potential of long-read sequencing in this field.
Cite This Article
APA
Leduc L, Boucher L, Mach N, Leclère M, Costa M.
(2026).
Long-Read Sequencing for Species-Level Resolution of the Equine Gut Microbiota Reveals the Need for Improved Databases.
Animals (Basel), 16(10), 1459.
https://doi.org/10.3390/ani16101459 Publication
Researcher Affiliations
- Department of Clinical Sciences, Université de Montréal, Saint-Hyacinthe, QC J2S 2M2, Canada.
- Department of Veterinary Biomedical Sciences, Université de Montréal, Saint-Hyacinthe, QC J2S 2M2, Canada.
- Interactions Hôtes-Agents Pathogènes, École nationale vétérinaire Toulouse, Institut national de recherche pour l'agriculture, l'alimentation et l'environnement, Université Toulouse, 31999 Toulouse, France.
- Department of Clinical Sciences, Université de Montréal, Saint-Hyacinthe, QC J2S 2M2, Canada.
- Department of Veterinary Biomedical Sciences, Université de Montréal, Saint-Hyacinthe, QC J2S 2M2, Canada.
Grant Funding
- #RGPIN/4514-2018 / Natural Sciences and Engineering Research Council of Canada
Conflict of Interest Statement
The authors declare no conflicts of interest.
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