Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle

Abstract

Beef tenderness, a complex trait affected by many factors, is economically important to beef quality, industry, and consumer's palatability. In this study, RNA-Seq was used in network analysis to better understand the biological processes that lead to differences in beef tenderness. Skeletal muscle transcriptional profiles from 24 Nellore steers, selected by extreme estimated breeding values (EBVs) for shear force after 14 days of aging, were analyzed and 22 differentially expressed transcripts were identified. Among these were genes encoding ribosomal proteins, glutathione transporter ATP-binding cassette, sub-family C (CFTR/MRP), member 4 (ABCC4), and synaptotagmin IV (SYT4). Complementary co-expression analyses using Partial Correlation with Information Theory (PCIT), Phenotypic Impact Factor (PIF) and the Regulatory Impact Factor (RIF) methods identified candidate regulators and related pathways. The PCIT analysis identified ubiquitin specific peptidase 2 (USP2), growth factor receptor-bound protein 10 (GBR10), anoctamin 1 (ANO1), and transmembrane BAX inhibitor motif containing 4 (TMBIM4) as the most differentially hubbed (DH) transcripts. The transcripts that had a significant correlation with USP2, GBR10, ANO1, and TMBIM4 enriched for proteasome KEGG pathway. RIF analysis identified microRNAs as candidate regulators of variation in tenderness, including bta-mir-133a-2 and bta-mir-22. Both microRNAs have target genes present in the calcium signaling pathway and apoptosis. PIF analysis identified myoglobin (MB), enolase 3 (ENO3), and carbonic anhydrase 3 (CA3) as potentially having fundamental roles in tenderness. Pathways identified in our study impacted in beef tenderness included: calcium signaling, apoptosis, and proteolysis. These findings underscore some of the complex molecular mechanisms that control beef tenderness in Nellore cattle.

Keywords: RNA-Seq; bovine; meat; microRNA; networks; transcriptome.

FIGURE 1

Negative DH between the H and L groups for EBVSF at 14 days of aging. The center spot represents a hub transcript with a high value of DH, red lines represent positive DH and blue lines represent negative DH. All lines represent significant partial correlations ≥ 0.90 at p-value < 0.05 based on the information theory approach, which accounts for all comparisons in the analysis.

FIGURE 2

Positive DH between the H and L groups for EBVSF at 14 days of aging. The center spot represents a hub transcript with a high value of DH, the red lines represent positive DH and blue lines represent negative DH. All lines represent significant partial correlations ≥ 0.90 at p-value < 0.05 based on the information theory approach, which accounts for all comparisons in the analysis.