Protein co-expression network analysis to investigate biological mechanisms associated with fillet weight in broilers affected by myopathies

This study aimed at providing biological insights into the growth-related myopathies (white striping–WS; wooden breast–WB; spaghetti meat–SM) affecting broilers selected for rapid growth and high breast-yield by exploring the proteome profiles of affected and not-affected (Normal, N) Pectoralis major muscles. Twelve fillets were collected and weighed at a commercial processing plant (3/group; N and severely affected by WS, WB, or SM), and classified based on their macroscopic features. One gram from each sample was used for proteomic analysis through TMT-based mass spectrometry at the Harvard Medical School (Boston, MA, USA). After testing for normality (Shapiro-Wilk Test), fillet weights were analyzed by one-way ANOVA considering the 4 groups as the main effect (R v4.3.2). Proteomic and phenotypic data were used to perform a co-expression network analysis (WGCNA R Package; v1.72-5) and biological interpretations of co-expressed proteins were performed through the DAVID Functional Classification Tool. Gene Ontology (GO) terms with FDR<0.05 were considered statistically significant using Homo sapiens as the background organism. Fillet weights of severe WB, SM, and WS cases were higher than N (P<0.05). While WB fillets were higher than WS (P<0.05), no differences between SM and the other two myopathies were found. From TMT-based mass spectrometry, 4,199 proteins were quantified and mapped to the Gallus gallus Uniprot database. Since only proteins quantified by at least 2 peptides were considered for downstream analysis, the normalized relative abundance of 3,277 proteins was used to construct the co-expression networks. WGCNA identified 10 color-coded groups (i.e., modules) of co-expressed proteins, among which the turquoise (r=+0.82; P<0.01) and brown (r=-0.87; P<0.01) were the most significantly related with fillet weight. For the turquoise module, biological processes involved in the regulation of protein neddylation (P<0.01), cellular oxidant detoxification (P<0.01), cardiac myofibril assembly (P<0.01), and collagen fibril organization (P<0.01) were found. Respiratory chain complex III (P<0.01), mitochondrial membrane organization (P<0.01), endoplasmic reticulum lumen, and collagen-containing extracellular matrix (P<0.01) were among the most significant terms related to the brown module. To conclude, WGCNA applied to proteomic data allowed a biological interpretation of co-expressed protein networks significantly associated with fillet weight variability in broiler breast fillets affected by growth-related myopathies.