RNA-Seq Analysis of Ruminal Methane Emissions in Beef-on-Dairy Cattle: Evidence for Immune, Nervous, and Endocrine...

Methane (CH₄) emissions present a significant challenge to both environmental sustainability and energy efficiency in ruminants, including beef cattle that are born in dairy herds. Although numerous approaches, including alterations in feed and the use of additives, are under investigation to mitigate these emissions, the genetic selection of animals that produce lower levels of methane offers the potential for enduring and cumulative advantages. Transcriptome analysis represents a crucial advancement in elucidating the networks and mechanisms through which the ruminant genome influences methane emissions. In the present study, methane emissions were measured using a GreenFeed system in beef-on-dairy cattle (n = 11). High-throughput RNA sequencing was conducted on animal blood samples, followed by differential gene expression analysis using methane production (g/d) as a continuous trait. The analysis identified eleven differentially expressed genes (DEGs), including six downregulated (KIAA1211L, LOC107131224, OSCP1, IL12B, LOC618859, FREM1) and five upregulated (DSCAML1, OSBP2, ACAN, PRSS16, CD1B) genes (Padj < 0.05) with one gene exhibiting potential biomarker characteristics. Gene and cell enrichment, as well as pathway analysis, suggested that nervous, immune, and endocrine systems may be involved in ruminal methane production by beef-on-dairy cattle. These findings highlight the potential of transcriptomic biomarkers to guide genetic selection strategies, offering a sustainable pathway to reduce methane emissions and enhance both environmental and agricultural efficiency.