Analysis of gut microbiota in the Feces of Korean native black goat using 16S rRNA sequencing

Despite the recent surge in consumer demand for native goats as an alternative meat source, driven by shifting perceptions of health foods, there is a notable lack of prior research on this livestock breed. This study aimed to characterize the gut microbiota of native goat populations to enhance our understanding of the species and to provide fundamental data for improving productivity. Fecal samples collected from January to April 2024 were analyzed using 16S rRNA sequencing to assess the gut microbiota composition. The analysis revealed that the phyla Bacillota and Bacteroidota were the most abundant, playing key roles in fiber degradation and short-chain fatty acid production, which are crucial for the physiological and functional health of the animals. The gut microbiota composition was found to be similar to that of other ruminants. Interestingly, individuals with lower abundances of Bacillota and Bacteroidota showed relatively higher levels of Bacteroidales, suggesting that their digestive efficiency was not compromised. The gut microbiota of deceased animals also displayed a similar composition to that of healthy individuals, with no specific associations with particular diseases identified. The findings from this study provide foundational data on the gut microbiota of native goats, which could be further elaborated through additional research.

Authors

Publication Details

Journal
Journal of Animal Breeding and Genomics
Published
2024-09-30
DOI
https://doi.org/10.12972/jabng.20240301
Primary Topic
Agriculture, Soil, Plant Science
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of gut microbiota in the Feces of Korean native black goat using 16S rRNA sequencing

Woo Cheol Jeong, Ho‐Chan Kang, Ji Yeong Kim, Hyun‐Tae Lim et al.
Journal of Animal Breeding and Genomics
Agriculture, Soil, Plant Science
article

Analysis of gut microbiota in the Feces of Korean native black goat using 16S rRNA sequencing

Woo Cheol Jeong, Ho‐Chan Kang, Ji Yeong Kim, Hyun‐Tae Lim, Cheol Hyun Myung, Sang Hyun Song, Dae Hyeok Jin, Seung Chang Kim
article en

Abstract

Despite the recent surge in consumer demand for native goats as an alternative meat source, driven by shifting perceptions of health foods, there is a notable lack of prior research on this livestock breed. This study aimed to characterize the gut microbiota of native goat populations to enhance our understanding of the species and to provide fundamental data for improving productivity. Fecal samples collected from January to April 2024 were analyzed using 16S rRNA sequencing to assess the gut microbiota composition. The analysis revealed that the phyla Bacillota and Bacteroidota were the most abundant, playing key roles in fiber degradation and short-chain fatty acid production, which are crucial for the physiological and functional health of the animals. The gut microbiota composition was found to be similar to that of other ruminants. Interestingly, individuals with lower abundances of Bacillota and Bacteroidota showed relatively higher levels of Bacteroidales, suggesting that their digestive efficiency was not compromised. The gut microbiota of deceased animals also displayed a similar composition to that of healthy individuals, with no specific associations with particular diseases identified. The findings from this study provide foundational data on the gut microbiota of native goats, which could be further elaborated through additional research.

Journal of Animal Breeding and GenomicsVol. 8(3)
Rural Development Administration
Openalex Percentile: Top 88%
Agriculture, Soil, Plant Science
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.