An integrative multi-omics analysis has identified candidate genomic, transcriptomic, and microbial features associated with body weight variation in Hanwoo steers.
Hanwoo, an indigenous Korean cattle breed, holds high economic value in Korea, where improving body weight represents an ongoing priority for farm profitability and animal productivity. Because growth traits are shaped across multiple biological layers, including host genetics, transcriptomic regulation, and rumen microbial ecology, the study evaluated these interconnected layers simultaneously rather than relying on a single-omics perspective.
To address this complexity, the researchers applied DIABLO, a supervised multi-omics integration framework that detects latent components across heterogeneous biological datasets. The investigation examined 58 steers, combining genomic profiles consisting of 42,091 single-nucleotide polymorphisms, rumen tissue transcriptomic data obtained via RNA sequencing, and rumen microbial profiles generated through 16S ribosomal RNA sequencing.
After adjusting body weight measurements for animal age, the steers were classified into high- and low-body-weight groups. A preliminary feature pre-selection step yielded 100 discriminant single-nucleotide polymorphisms, 161 candidate transcriptomic expression features with large effects, and 20 candidate microbial features exhibiting nominal abundance differences between the two weight cohorts.
Multi-omics integration highlighted exploratory associations linking host variants, gene expression, and rumen microbes, including three single-nucleotide polymorphisms—ARS-BFGL-NGS-104362, ARS-BFGL-NGS-43924, and ARS-BFGL-NGS-24293—that remained significantly associated with steer body weight. These genetic variants were linked to epithelial and metabolic genes, specifically FUT1, KRTDAP, and TCN1, which displayed strong correlations with Anaerobutyricum, an exploratory candidate genus known for producing butyrate.
The investigators noted that these integrated findings suggest candidate host epithelial and rumen microbial axes associated with body weight variation rather than establishing causal biological mechanisms. Owing to the modest sample size of 58 steers and the supervised nature of the DIABLO framework, the authors designated the resulting multi-omics signature as hypothesis-generating, emphasizing that validation in larger independent cohorts remains necessary.
From an agricultural and physiological standpoint, body weight in Hanwoo cattle represents a critical economic benchmark influencing overall farm productivity in Korea. The investigation was structured around the recognition that complex phenotypic growth traits do not arise from a single biological mechanism. Instead, the researchers highlighted that variation in steer weight is collectively governed across several distinct biological strata, specifically involving host genomic variation, transcriptional activity within the rumen tissue, and the microbial ecology inhabiting the rumen environment. Because analyzing any of these layers in isolation provides an incomplete perspective, the research team implemented a multi-layered investigative approach to capture the interactions operating among them.
To characterize these biological domains, the researchers gathered multi-omics measurements from a cohort of 58 steers. An initial step in the experimental design involved adjusting measured steer body weight for animal age, which allowed the animals to be categorized into distinct high-body-weight and low-body-weight comparison groups. The underlying genomic architecture was evaluated using a panel of 42,091 single-nucleotide polymorphisms, while the host transcriptomic landscape of the rumen was profiled through RNA sequencing. In parallel, the composition of the rumen microbial community was characterized using 16S ribosomal RNA sequencing, establishing three complementary molecular datasets for each animal.
Data processing and feature prioritization were conducted through DIABLO, an acronym for Data Integration Analysis for Biomarker discovery using Latent cOmponents. Before carrying out multi-omics integration, a feature pre-selection phase was executed to isolate the most informative variables distinguishing the high-weight and low-weight cohorts. This preliminary filtering step yielded 100 discriminant single-nucleotide polymorphisms from the genomic data, 161 large-effect candidate expression features from the transcriptomic measurements, and 20 candidate microbial features that exhibited nominal differences in abundance between the two animal groups.
Subsequent integration across these pre-selected datasets revealed exploratory tripartite associations connecting specific genomic loci, expressed host transcripts, and rumen microbial taxa. Among the evaluated markers, three single-nucleotide polymorphisms, namely ARS-BFGL-NGS-104362, ARS-BFGL-NGS-43924, and ARS-BFGL-NGS-24293, retained significant associations with steer body weight. These genetic variants demonstrated functional connections to genes involved in epithelial and metabolic processes, specifically FUT1, KRTDAP, and TCN1. Furthermore, expression profiles of these candidate epithelial and metabolic genes showed robust correlations with the abundance of Anaerobutyricum, an exploratory candidate bacterial genus characterized as a butyrate-producing microorganism.
In detailing the biological implications of these observations, the researchers underscored that the identified relationships reflect candidate host epithelial and rumen microbial axes associated with body weight differences, rather than demonstrated causal mechanisms. The authors framed the multi-omics signature as hypothesis-generating due to specific study constraints, notably the modest cohort size of 58 animals and the supervised structure of the DIABLO analytical framework. Consequently, confirming the validity of these candidate biomarkers and their potential relevance to Hanwoo growth performance will require subsequent verification within larger, independent cattle populations.
Subject of Research: Multi-omics candidate features associated with body weight in Hanwoo steers
Article Title: Integrative multi-omics analysis of host genetics, rumen transcriptome and microbiome prioritizes candidate features associated with body weight in Hanwoo steers
Article References: Jeong, T., Park, W., Jang, S., Lee, P.-Y., Park, J.-E., & Lim, D. (2026). Integrative multi-omics analysis of host genetics, rumen transcriptome and microbiome prioritizes candidate features associated with body weight in Hanwoo steers. Animal Microbiome. https://doi.org/10.1186/s42523-026-00619-9
Image Credits: AI Generated
DOI: 10.1186/s42523-026-00619-9
Keywords: Hanwoo cattle, body weight, multi-omics, rumen transcriptome, rumen microbiome, DIABLO framework, single-nucleotide polymorphisms, Anaerobutyricum, Integrative, analysis, host, genetics
News Source: William Thompson. (November 9, 2026). Multi-Omics Study Identifies Key Biological Features Linked to Hanwoo Cattle Weight. Scienmag.
