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

## TL;DR

This study finds genes linked to methane emissions in beef-on-dairy cattle, suggesting nervous, immune, and hormone systems may influence emissions, which could help breed low-emission cattle.

## Contribution

The study identifies 11 genes and links methane emissions to nervous, immune, and endocrine pathways in beef-on-dairy cattle using RNA sequencing.

## Key findings

- Eleven genes were found to be differentially expressed in relation to methane emissions.
- Nervous, immune, and endocrine systems appear to be involved in methane production in cattle.
- Transcriptomic biomarkers could guide breeding strategies to reduce methane emissions.

## Abstract

Methane produced and emitted by cattle is a major contributor to climate change and represents a loss of dietary energy in livestock systems. While dietary interventions can help reduce these emissions, selecting animals that naturally produce less methane may offer long-term benefits. In this study, we measured methane emissions from a group of beef cattle born to dairy cows and collected blood samples to study their genes. Using advanced genetic techniques, we identified 11 genes associated with individual methane production. Further analysis suggested that the nervous system, immune system, and hormone-related processes might play a role in how much methane cattle produce. These findings may support breeding strategies that reduce methane emissions and contribute to more environmentally sustainable production.

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.