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This study determined the extent to which bovine longissimus lumborum muscle (LLM) myofibers are influenced by nutrition for 120 d from weaning and the time-course of recovery after severe postweaning nutritional restriction. After weaning, 3 groups of Belmont Red cattle, a tropically adapted breed, were fed to achieve rapid growth (RG,or =0.6 kg of BW gain/d; n = 16), slow growth (SG, 0.2 kg of BW gain/d; n = 17), or BW loss (WL, 10% loss of weaning weight; n = 17) over 120 d. They were then grazed as 1 group at pasture with forage supplementation for 600 d until slaughter at approximately 500 kg of BW. Samples of LLM were taken from 8 to 12 animals per treatment 6 d before (baseline) and 115, 204, 324, and 476 d after commencement of the study and from all cattle at slaughter (d 721). Myofiber characteristics were determined by immunocytochemical staining of myosin heavy chains. Cross-sectional areas (CSA) of the major myofiber types 1, 2A, and 2X in WL were reduced at d 115 compared with baseline and with the growth groups (all P0.001); however, there was little difference in the percentage of the different myofiber types (all P0.10). Differences in CSA of the major myofiber types between WL and the growth groups at 115 d were smallest for type 1 (slow oxidative) and greatest for type 2X (fast glycolytic). Consequently, the relative area (percentage of total myofiber area) of type 1 myofibers in WL was significantly greater at 115 d than in the growth groups (P0.001). During recovery from postweaning nutritional restriction, significant differences in major myofiber type percentages were not evident (all P0.10), and by 721 d CSA of myofiber types differed little between the treatment groups, although SG had greater CSA of type 1 (P0.05) and type 2A (P0.01) myofibers than WL and RG. At 721 d, the relative area of type 2A myofibers was less in WL compared with SG (P0.01) and RG (P0.05) and of type 2X myofibers greater (P0.05) in WL compared with SG. It is concluded that in the LLM of cattle undergoing severe nutritional restriction immediately postweaning, the size of the more glycolytic fiber types is more adversely affected than the more oxidative types, resulting in an increased relative area of type 1, slow oxidative myofibers. However, given adequate time and nutriment at pasture, LLM myofiber characteristics of cattle recovered to near normal after severe, chronic nutritional restriction immediately postweaning, consistent with earlier findings for beef quality.

Gene expression profiles of LM from beef cattle that underwent significant postweaning undernutrition were studied using complementary DNA (cDNA) microarrays. After 114 d of undernutrition, the RNA from LM showed 2- to 6-fold less expression of many genes from the classes of muscle structural proteins, muscle metabolic enzymes, and extracellular matrix compared with animals on a rapid growth diet. The expression levels of these genes had mostly returned to pretreatment levels after 84 d of realimentation. The gene expression changes associated with undernutrition and BW loss showed an emphasis on downregulation of gene expression specific to fast-twitch fibers, typical of starving mammals, with a preferential atrophy of glycolytic fast-twitch fibers. We also identified a small group of genes that showed 2- to 5-fold elevated expression in LM after 114 d of undernutrition. Putative roles for these genes in atrophying skeletal muscle are regulation of myogenic differentiation (CSRP3), maintenance of mesenchymal stem cells (CYR61), modulation of membrane function (TM4SF2), prevention of oxidative damage (SESN1), and regulation of muscle protein degradation (SQSTM1). A significant increase in stearoyl-CoA desaturase (SCD) gene expression was observed in atrophying muscle, suggesting either that increased fatty acid synthesis is part of the tissue response to caloric restriction, or that SCD plays another role in energy metabolism in the mixed cellular environment of bovine skeletal muscle.

Expression profiling using microarrays allows for the detailed characterization of the gene networks that regulate an animal's response to environmental stresses. During nutritional restriction, processes such as protein turnover, connective tissue remodeling, and muscle atrophy take place in the skeletal muscle of the animal. These processes and their regulation are of interest in the context of managing livestock for optimal production efficiency and product quality. Here we expand on recent research applying complementary DNA (cDNA) microarray technology to the study of the effect of nutritional restriction on bovine skeletal muscle. Using a custom cDNA microarray of 9,274 probes from cattle muscle and s.c. fat libraries, we examined the differential gene expression profile of the LM from 10 Brahman steers under three different dietary treatments. The statistical approach was based on mixed-model ANOVA and model-based clustering of the BLUP solutions for the gene x diet interaction effect. From the results, we defined a transcript profile of 156 differentially expressed array elements between the weight loss and weight gain diet substrates. After sequence and annotation analyses, the 57 upregulated elements represented 29 unique genes, and the 99 downregulated elements represented 28 unique genes. Most of these co-regulated genes cluster into groups with distinct biological function related to protein turnover and cytoskeletal metabolism and contribute to our mechanistic understanding of the processes associated with remodeling of muscle tissue in response to nutritional stress.

In functional genomic laboratories, it is common to use the same microarray slide across studies, each investigating a unique biological question, and each analyzed separately due to computational limitations and/or because there is no hybridization of samples from different studies on one slide. However, the question of analyzing data from multiple studies is a major current issue in microarray data analysis because there are gains to be made in the accuracy of estimated effects by exploiting a covariance structure between gene expression data across studies. We propose an approach for combining multiple studies using multivariate mixed models, with the assumption of a nonzero correlation among genes across experiments, while imposing a null residual covariance. We applied this method to jointly analyze three experiments in genetics of cattle with a total of 54 arrays, each with 19,200 spots and 7,638 elements. The resulting seven-variate model contains 752,476 equations and 56 covariances. To identify differentially expressed genes, we applied model-based clustering to a linear combination of the random gene x variety interaction effect. We enhanced the biological interpretation of the results by applying an iterative algorithm to identify the gene ontology classes that significantly changed in each experiment. We found 118 elements with coordinate expression that clustered into distinct biological functions such as adipogenesis and protein turnover. These results contribute to our understanding of the mechanistic processes involved in adipogenesis and nutrient partitioning.