Gene expression analysis for feed efficiency trait in liver tissue of lactating Girolando cows

The selection of high feed efficiency (FE) animals impacts sustainability and profitability of beef and dairy cattle production systems. An approach to investigate the mechanisms of FE involves analyzing gene expression profile in liver. This study used residual feed intake as a metric of FE to select 10 Gir x Holstein crossbred cows (Girolando F1) divided into high (HE) and low (LE) FE groups. Hepatic biopsies were used for differential gene expression investigation using RNA-seq analyses which revealed 20,787 known genes mapped accordingly to the bovine reference genome. The comparison of HE and LE revealed 149 significantly differentially expressed genes (DEG), 41 up-regulated, and 108 down-regulated in the LE group. Among DEG, some stood out as potential candidate genes, including DLK1, CACNG4, SLC2A12, SLC26A4, DUOX2, and DUOXA2. Functional enrichment analyses showed pathways that potentially influence FE, such as the negative regulation of leukocyte migration, regulation of calcium channel activity, negative regulation of cell migration and adhesion, extracellular matrix (ECM) organization, and thyroid hormone synthesis. ECM composition and immune system roles were also highlighted. These results could help understanding the mechanisms related to FE in dairy cattle and the development of selection strategies to improve this trait.

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Journal
Genetics and Molecular Biology
Published
2025-12-01
DOI
https://doi.org/10.1590/1678-4685-gmb-2025-0036
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
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article

Gene expression analysis for feed efficiency trait in liver tissue of lactating Girolando cows

Marcos Vinícius Gualberto Barbosa da Silva, F. S. Machado, Mariana Magalhães Campos, Ana Luíza Franco et al.
Genetics and Molecular Biology
Genetic and phenotypic traits in livestock
article

Gene expression analysis for feed efficiency trait in liver tissue of lactating Girolando cows

Marcos Vinícius Gualberto Barbosa da Silva, F. S. Machado, Mariana Magalhães Campos, Ana Luíza Franco, J. C. do C. Panetto, Marta Fonseca Martins, L Ribeiro Pereira, M. O. Machado, Robert Domingues, Thierry Ribeiro Tomich, Wanessa Araújo Carvalho, Daniele Ribeiro de Lima Reis Faza
article en

Abstract

The selection of high feed efficiency (FE) animals impacts sustainability and profitability of beef and dairy cattle production systems. An approach to investigate the mechanisms of FE involves analyzing gene expression profile in liver. This study used residual feed intake as a metric of FE to select 10 Gir x Holstein crossbred cows (Girolando F1) divided into high (HE) and low (LE) FE groups. Hepatic biopsies were used for differential gene expression investigation using RNA-seq analyses which revealed 20,787 known genes mapped accordingly to the bovine reference genome. The comparison of HE and LE revealed 149 significantly differentially expressed genes (DEG), 41 up-regulated, and 108 down-regulated in the LE group. Among DEG, some stood out as potential candidate genes, including DLK1, CACNG4, SLC2A12, SLC26A4, DUOX2, and DUOXA2. Functional enrichment analyses showed pathways that potentially influence FE, such as the negative regulation of leukocyte migration, regulation of calcium channel activity, negative regulation of cell migration and adhesion, extracellular matrix (ECM) organization, and thyroid hormone synthesis. ECM composition and immune system roles were also highlighted. These results could help understanding the mechanisms related to FE in dairy cattle and the development of selection strategies to improve this trait.

Genetics and Molecular BiologyVol. 48(4)
Universidade Federal de Juiz de Fora (BR), Brazilian Agricultural Research Corporation (BR)
Responsible consumption and production
Openalex Percentile: Top 22%
Genetic and phenotypic traits in livestock
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Gene expression analysis for feed efficiency trait in liver tissue of lactating Girolando cows — Marcos Vinícius Gualberto Barbosa da Silva, F. S. Machado, et al. · Genetics and Molecular Biology (2025) | TGRS Research Map | TGRS