Effects of Supplements Differing in Fatty Acid Profile to Late Gestational Beef Cows on Steer Progeny Finishing Phase Growth Performance, Carcass Characteristics, and mRNA Expression of Myogenic and Adipogenic Genes

Silva JV, Palmer E, Ranches J, Bittar JHJ, Santos GCM, Pickett A, Cooke RF, Vendramini JMB, Moriel P. Bakery waste supplementation to late gestating Bos indicus-influenced beef cows successfully impacted offspring postnatal performance

This study evaluated the growth and immune function of beef calves born to cows supplemented with bakery waste containing two concentrations of crude fat. On day 0 (~90 d before calving), 108 multiparous Brangus crossbred cows were stratified by body weight (BW; 551 ± 65 kg) and body condition score (BCS, 5.5 ± 0.9) and randomly allocated into 1 of 18 bahiagrass (Paspalum notatum) pastures (6 cows and 4.3 ha per pasture). Treatments were randomly assigned to pastures (6 pastures per treatment) and consisted of no prepartum supplementation (NOSUP) and isocaloric and isonitrogenous supplementation of low-fat (LFAT; 6.4% crude fat) or high-fat (HFAT; 10.7% crude fat) bakery waste from days 0 to 70 (1 kg DM per cow per day). Calves were weaned on day 292 (201 ± 17 d of age). Then, 15 heifers per treatment were randomly selected and assigned to drylot pens from days 300 to 345 and vaccinated against respiratory pathogens on days 300 and 315. Cow BCS near calving (day 70) was the least (P ≤ 0.05) for NOSUP cows and did not differ (P = 0.12) between LFAT and HFAT cows. Cow BCS at the start of the breeding season (day 140) was greater (P = 0.05) for HFAT vs. NOSUP cows and intermediate (P ≥ 0.35) for LFAT cows. Plasma concentrations of total polyunsaturated fatty acids in HFAT cows did not differ (P ≥ 0.76) compared with LFAT cows but were greater (P ≤ 0.05) compared to NOSUP cows on day 70. Final pregnancy percentage did not differ (P ≥ 0.26) among treatments, but a greater percentage of HFAT cows calved (P ≤ 0.05) their second offspring during the first 21 d of the calving season compared to NOSUP and LFAT cows (bred by natural service). Weaning BW was the greatest (P ≤ 0.05) for LFAT and least for NOSUP calves. Maternal treatments did not impact (P ≥ 0.11) postweaning growth and total DM intake of calves. Average plasma cortisol concentrations were greater (P = 0.03) for NOSUP vs. HFAT calves and intermediate for LFAT calves (P ≥ 0.26). Serum titers against infectious bovine rhinotracheitis and bovine respiratory syncytial virus were greater or tended to be greater (P ≤ 0.08) for HFAT vs. LFAT calves and intermediate (P ≥ 0.27) for NOSUP calves at the end of preconditioning. Thus, supplemental fat concentration fed to late-gestating beef cows had variable effects on calf performance. Low-fat bakery waste led to the greatest calf preweaning growth, whereas high-fat bakery waste enhanced maternal reproduction and had minor benefits to calf humoral immune function.

Use of a graph neural network to the weighted gene co-expression network analysis of Korean native cattle

In the general framework of the weighted gene co-expression network analysis (WGCNA), a hierarchical clustering algorithm is commonly used to module definition. However, hierarchical clustering depends strongly on the topological overlap measure. In other words, this algorithm may assign two genes with low topological overlap to different modules even though their expression patterns are similar. Here, a novel gene module clustering algorithm for WGCNA is proposed. We develop a gene module clustering network (gmcNet), which simultaneously addresses single-level expression and topological overlap measure. The proposed gmcNet includes a “co-expression pattern recognizer” (CEPR) and “module classifier”. The CEPR incorporates expression features of single genes into the topological features of co-expressed ones. Given this CEPR-embedded feature, the module classifier computes module assignment probabilities. We validated gmcNet performance using 4,976 genes from 20 native Korean cattle. We observed that the CEPR generates more robust features than single-level expression or topological overlap measure. Given the CEPR-embedded feature, gmcNet achieved the best performance in terms of modularity (0.261) and the differentially expressed signal (27.739) compared with other clustering methods tested. Furthermore, gmcNet detected some interesting biological functionalities for carcass weight, backfat thickness, intramuscular fat, and beef tenderness of Korean native cattle. Therefore, gmcNet is a useful framework for WGCNA module clustering.

Improving Beef Progeny Performance Through Developmental Programming

Maternal nutritional management during gestation appears to modulate fetal development and imprint offspring postnatal health and performance, via altered organ and tissue development and tissue-specific epigenetics. This review highlighted the studies demonstrating how developmental programming could be explored by beef producers to enhance offspring performance (growth, immune function, and reproduction), including altering cow body condition score (BCS) during pregnancy and maternal supplementation of protein and energy, polyunsaturated fatty acids (PUFA), trace minerals, frequency of supplementation, specific amino acids, and vitamins. However, this review also highlighted that programming effects on offspring performance reported in the literature were highly variable and depended on level, duration, timing, and type of nutrient restriction during gestation. It is suggested that maternal BCS gain during gestation, rather than BCS per se, enhances offspring preweaning growth. Opportunities for boosting offspring productive responses through maternal supplementation of protein and energy were identified more consistently for pre- vs. post-weaning phases. Maternal supplementation of specific nutrients (i.e., PUFA, trace minerals, and methionine) demonstrated potential for improving offspring performance, health and carcass characteristics during immunological challenging scenarios. Despite the growing body of evidence in recent years, the complexity of investigating developmental programming in beef cattle production is also growing and potential reasons for current research challenges are highlighted herein. These challenges include: (1) intrinsic difficulty of accurately measuring cow milk production multiple times in cow-calf systems; (2) larger focus on Bos taurus vs. Bos indicus breeds despite the predominance of Bos indicus-influenced beef breeds in tropical/subtropical environments and their specific, and sometimes opposite, physiological and performance outcomes compared to Bos taurus breeds; (3) limited focus on interaction between prenatal and postnatal management; (4) sex-specific outcomes following similar maternal nutrition during gestation; (5) greater focus on nutrient deficiency vs. excess; (6) limited implementation of immunological challenges; and (7) lack of multigeneration and longer periods of offspring evaluation. This review provides multiple evidence that such obstacles need to be overcome in order to significantly advance the scientific knowledge of developmental programming in beef cattle and promote global beef production.