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.
Highlights
Meat tenderness is an important beef palatability trait for consumers, and most of the biological mechanisms involved in this trait are not completely understood (Ouali et al, 2006)
The top differentially hubbed (DH) transcripts identified by partial correlation with information theory (PCIT) analysis and the functional analyses performed on the correlated transcripts were associated with the proteasome KEGG pathway
The myoglobin (MB), enolase 3 (ENO3), and carbonic anhydrase 3 (CA3) were top transcripts identified by phenotypic impact factor (PIF) analysis
Summary
Meat tenderness is an important beef palatability trait for consumers, and most of the biological mechanisms involved in this trait are not completely understood (Ouali et al, 2006). Tenderness and other phenotypes associated with meat quality such as taste and color, are difficult to measure directly, and can only be determined after an animal is slaughtered (Gonçalves, 2015; Mateescu et al, 2017). For complex traits such as beef tenderness, next-generation sequencing (NGS) technologies have been applied in transcriptomic analyses to identify DE genes and biological pathways potentially involved with meat quality phenotypes (Metzker, 2010). The key regulator of muscle growth, myostatin, was not DE in animals carrying the mutation, but this gene was differentially wired based on the RIF analysis (Hudson et al, 2009)
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