Recent advances in omic technologies for meat quality management

Metabolomics Changes in Meat and Subcutaneous Fat of Male Cattle Submitted to Fetal Programming

This study investigated changes in meat and subcutaneous fat metabolomes and possible metabolic pathways related to prenatal nutrition in beef cattle. For this purpose, 18 Nellore bulls were used for meat sampling and 15 for fat sampling. The nutritional treatments during the gestation were: NP-not programmed or control, without protein-energy supplementation; PP-partially programmed, with protein-energy supplementation (0.3% of body weight (BW)) only in the final third of pregnancy; and FP-full programming, with protein-energy supplementation (0.3% of BW) during the entire pregnancy. The meat and fat samples were collected individually 24 h after slaughter, and the metabolites were extracted using a combination of chemical reagents and mechanical processes and subsequently quantified using liquid chromatography or flow injection coupled to mass spectrometry. The data obtained were submitted to principal component analysis (PCA), analysis of variance (ANOVA), and functional enrichment analysis, with a significance level of 5%. The PCA showed an overlap between the treatments for both meat and fat. In meat, 25 metabolites were statistically different between treatments (p ≤ 0.05), belonging to four classes (glycerophospholipids, amino acids, sphingolipids, and biogenic amine). In fat, 10 significant metabolites (p ≤ 0.05) were obtained in two classes (phosphatidylcholine and lysophosphatidylcholine). The functional enrichment analysis showed alterations in the aminoacyl-tRNA pathway in meat (p = 0.030); however, there was no pathway enriched for fat. Fetal programming influenced the meat and fat metabolomes and the aminoacyl-tRNA metabolic pathway, which is an important candidate for the biological process linked to meat quality and related to fetal programming in beef cattle.

Multi-Omics Approaches to Improve Meat Quality and Taste Characteristics

With rapid advances in meat science in recent decades, changes in meat quality during the pre-slaughter phase of muscle growth and the post-slaughter process from muscle to meat have been investigated. Commonly used techniques have evolved from early physicochemical indicators such as meat color, tenderness, water holding capacity, flavor, and pH to various omic tools such as genomics, transcriptomics, proteomics, and metabolomics to explore fundamental molecular mechanisms and screen biomarkers related to meat quality and taste characteristics. This review highlights the application of omics and integrated multi-omics in meat quality and taste characteristics studies. It also discusses challenges and future perspectives of multi-omics technology to improve meat quality and taste. Consequently, multi-omics techniques can elucidate the molecular mechanisms responsible for changes of meat quality at transcriptome, proteome, and metabolome levels. In addition, the application of multi-omics technology has great potential for exploring and identifying biomarkers for meat quality and quality control that can make it easier to optimize production processes in the meat industry.

Different nutritional systems influence the tenderness and lipid oxidation of ewe lamb meat without altering gene expression

Feeding is a determining factor in the various characteristics of sheep meat and animal performance, the objectives were to evaluate the effect of supplementation of ewe lambs finished in different nutritional planes on the gene expression of CASP3, CAPN1, CAPN2 and CAST and its possible association with meat quality. Samples of the Longissimus lumborum muscle of 24 ewe lambs were used, distributed in 3 groups (n=8): P (pasture), PS (pasture and supplement) and F (feedlot). Physicochemical analyses were performed for centesimal analysis, pH, lipid oxidation, Warner-Bratzler shear force and RT-qPCR for the analysis of relative gene expression of the following genes: CASP3, CAPN1, CAPN2 and CAST. There is an increase in daily weight gain and ethereal extract values in the meat of confined animals, due to the greater energy intake in the nutrition of these animals. Animals kept only on pasture have lower lipid oxidation in meat than other treatments because of the lower percentage of lipids. The Warner-Bratzler shear force is considerably higher in the meat of animals kept only on pasture but is still considered tender. The different nutritional systems do not interfere with the gene expression of CASP3, CAPN1, CAPN2 and CAST in ewe lambs.

Untargeted Metabolomics of Meat Digests: Its Potential to Differentiate Pork Depending on the Feeding Regimen

Meat quality seems to be influenced by the dietary regimes applied for animal feeding. Several research studies are aimed at improving meat quality, preserving it from oxidative processes, by the incorporation of antioxidant components in animal feeding. The main part of these studies evaluates meat quality, determining different parameters directly on meat, while few research studies take into account what may happen after meat ingestion. To address this topic, in this study, an in vitro gastrointestinal digestion protocol was applied to two different pork muscles, longissimus dorsi and rectus femoris, obtained from pigs fed with different diets. In detail, two groups of 12 animals each were subjected to either a conventional diet or a supplemented diet with extruded linseeds as a source of omega-3 fatty acids and plant extracts as a source of phenolics antioxidant compounds. The digested meat was subjected to an untargeted metabolomics approach. Several metabolites deriving from lipid and protein digestion were detected. Our untargeted approach allowed for discriminating the two different meat cuts, based on their metabolomic profiles. Nonetheless, multivariate statistics allowed clearly discriminating between samples obtained from different animal diets. In particular, the inclusion of linseeds and polyphenols in the animal diet led to a decrease in metabolites generated from oxidative degradation reactions, in comparison to the conventional diet group. In the latter, fatty acyls, fatty aldehydes and oxylipins, as well as cholesterol and vitamin D3 precursors and derivatives, could be highlighted.

When Less Is More: Targeting the Myostatin Gene in Livestock for Augmenting Meat Production

How to increase meat production is one of the main questions in animal breeding. Selection for improved body weight has been made and, due to recent genomic advances, naturally occurring variants that are responsible for controlling economically relevant phenotypes have been revealed. The myostatin (MSTN) gene, a superstar gene in animal breeding, was discovered as a negative controller of muscle mass. In some livestock species, natural mutations in the MSTN gene could generate the agriculturally desirable double-muscling phenotype. However, some other livestock species or breeds lack these desirable variants. Genetic modification, particularly gene editing, offers an unprecedented opportunity to induce or mimic naturally occurring mutations in livestock genomes. To date, various MSTN-edited livestock species have been generated using different gene modification tools. These MSTN gene-edited models have higher growth rates and increased muscle mass, suggesting the high potential of utilizing MSTN gene editing in animal breeding. Additionally, post-editing investigations in most livestock species support the favorable influence of targeting the MSTN gene on meat quantity and quality. In this Review, we provide a collective discussion on targeting the MSTN gene in livestock to further encourage its utilization opportunities. It is expected that, shortly, MSTN gene-edited livestock will be commercialized, and MSTN-edited meat will be on the tables of ordinary customers.

- Invited Review - Postmortem skeletal muscle metabolism of farm animals approached with metabolomics

Skeletal muscle metabolism regulates homeostatic balance in animals. The metabolic impact persists even after farm animal skeletal muscle is converted to edible meat through postmortem rigor mortis and aging. Muscle metabolites resulting from animal growth and postmortem storage have a significant impact on meat quality, including flavor and color. Metabolomics studies of postmortem muscle aging have identified metabolisms that contain signatures inherent to muscle properties and the altered metabolites by physiological adaptation, with glycolysis as the pivotal metabolism in postmortem aging. Metabolomics has also played a role in mining relevant postmortem metabolisms and pathways, such as the citrate cycle and mitochondrial metabolism. This leads to a deeper understanding of the mechanisms underlying the generation of key compounds that are associated with meat quality. Genetic background, feeding strategy, and muscle type primarily determine skeletal muscle properties in live animals and affect post-mortem muscle metabolism. With comprehensive metabolite detection, metabolomics is also beneficial for exploring biomarker candidates that could be useful to monitor meat production and predict the quality traits. The present review focuses on advances in farm animal muscle metabolomics, especially postmortem muscle metabolism associated with genetic factors and muscle type.

Plasma Metabolomic Profiling Reveals Preliminary Biomarkers of Pork Quality Based on pH Value

This study aimed to identify biomarkers for pork quality evaluation. Firstly, the correlation between indicators of pork quality evaluation was investigated. The pH of pork meat at 45 min post slaughter showed a significant negative correlation with meat color indicators (r: -0.4868--0.3040). Subsequently, porcine plasma samples were further divided into low pH (pH = 6.16 ± 0.22) or high pH (pH = 6.75 ± 0.08) groups. Plasma metabolites in both sample groups were investigated using untargeted metabolomics. In total, 90 metabolites were recognized as differential metabolites using partial least squares discriminant analysis. Pathway enrichment analysis indicated these differential metabolites were enriched in amino acid metabolism and energy metabolism. Correlation analysis revealed that creatinine, L-carnitine, D-sphingosine, citraconic acid, and other metabolites may constitute novel plasma biomarkers with the pH value of pork meat. The current study provides important insights into plasma biomarkers for predicting pork quality based on pH value.

The Sarcoplasmic Protein Profile of Breast Muscle in Turkeys in Response to Different Dietary Ratios of Limiting Amino Acids and Clostridium perfringens-Induced Inflammation

In this study, the effects of the Arginine/Lysine (Arg/Lys) ratio in low- and high-methionine (Met) diets on the sarcoplasmic protein profile of breast muscles from turkeys reared under optimal or challenge (Clostridium perfringens infection) conditions were determined. One-day-old Hybrid Converter female turkey poults (216 in total) obtained from a commercial hatchery on hatching day, and on the basis of their average initial body weight were randomly allocated to 12 pens (4 m² each; 2.0 m × 2.0 m) containing litter bedding and were reared over a 42-day experimental period. Diets with high levels of Lys contained approximately 1.80% and 1.65% Lys and were offered in two successive feeding periods (days 1–28 and days 29–42). The supplemental levels of Lys were consistent with the nutritional specifications for birds at their respective ages as established in the Management Guidelines for Raising Commercial Turkeys. The experiment was based on a completely randomized 3 × 2 × 2 factorial design with three levels of Arg (90%, 100% and 110%) relative to the content of dietary Met (30 or 45%) and without (−) or with (+) C. perfringens challenge at 34, 36, or 37 d of age. Meat samples were investigated in terms of pH, color, and sarcoplasmic protein profile. The experimental factors did not influence meat quality but the dietary Arg content affected meat color. The sarcoplasmic protein profile was influenced by all studied factors, and glycolytic enzymes were the most abundant. This study evidenced strong association between the challenge conditions and the involvement of glycolytic enzymes in cell metabolism, particularly in inflammatory processes, and DNA replication and maintenance in turkeys. The results showed an effect of C. perfringens infection and feeding with different doses of Arg and Met may lead to significant consequences in cell metabolism.

Cellular Aquaculture: Prospects and Challenges

Aquaculture plays an important role as one of the fastest-growing food-producing sectors in global food and nutritional security. Demand for animal protein in the form of fish has been increasing tremendously. Aquaculture faces many challenges to produce quality fish for the burgeoning world population. Cellular aquaculture can provide an alternative, climate-resilient food production system to produce quality fish. Potential applications of fish muscle cell lines in cellular aquaculture have raised the importance of developing and characterizing these cell lines. In vitro models, such as the mouse C2C12 cell line, have been extremely useful for expanding knowledge about molecular mechanisms of muscle growth and differentiation in mammals. Such studies are in an infancy stage in teleost due to the unavailability of equivalent permanent muscle cell lines, except a few fish muscle cell lines that have not yet been used for cellular aquaculture. The Prospect of cell-based aquaculture relies on the development of appropriate muscle cells, optimization of cell conditions, and mass production of cells in bioreactors. Hence, it is required to develop and characterize fish muscle cell lines along with their cryopreservation in cell line repositories and production of ideal mass cells in suitably designed bioreactors to overcome current cellular aquaculture challenges.

Proteomic Technologies and their Application for Ensuring Meat Quality, Safety and Authenticity

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Proteomic tools were extensively used to understand the relationship between muscle proteome and conversion of muscle to meat, post-mortem proteolysis, meat texture, and variation in meat color. Developments in proteomic tools have also resulted in their application for addressing the safety and authenticity issues including meat species identification, detection of animal byproducts, non-meat ingredients and tissues in meat products, traceability, identification of genetically modified ingredients, chemical residues and other harmful substances. Proteomic tools are also being used in some of the potential areas like understanding the effect of animal transportation, stunning, slaughter stress, halal authentication and issues related to animal welfare. Emerging advances in proteomic and peptidomic technologies and their application in traceability, meat microbiology, safety and authentication are taking a major stride as an interesting and complementary alternative to DNA-based methods currently in use. Future research in meat science need to be linked to emerging metabolomic, lipidomic and other omic technologies for ensuring integrated meat quality and safety management. In this paper, a comprehensive overview of the use of proteomics for the assessment of quality and safety in the meat value chain and their potential application is discussed.

Review: Quality of animal-source foods

This article critically reviews the current state of knowledge on the quality of animal-source foods according to animal production and food processing conditions, including consumer expectations-behaviours and the effects of consumption of animal-source foods on human health. Quality has been defined through seven core attributes: safety, commercial, sensory, nutritional, technological, convenience, and image. Image covers ethical, cultural and environmental dimensions associated with the origin of the food and the way it is produced and processed. This framework enabled to highlight the priorities given to the different quality attributes. It also helped to identify potential antagonisms and synergies among quality attributes, between production and processing stages, and among stakeholders. Primacy is essentially given to commercial quality attributes, especially for standard commodity animal-source foods. This primacy has strongly influenced genetic selection and farming practices in all livestock commodity chains and enabled substantial quantitative gains, although at the expense of other quality traits. Focal issues are the destructuration of chicken muscle that compromises sensory, nutritional and image quality attributes, and the fate of males in the egg and dairy sectors, which have heavily specialised their animals. Quality can be gained but can also be lost throughout the farm-to-fork continuum. Our review highlights critical factors and periods throughout animal production and food processing routes, such as on-farm practices, notably animal feeding, preslaughter and slaughter phases, food processing techniques, and food formulation. It also reveals on-farm and processing factors that create antagonisms among quality attributes, such as the castration of male pigs, the substitution of marine-source feed by plant-based feed in fish, and the use of sodium nitrite in meat processing. These antagonisms require scientific data to identify trade-offs among quality attributes and/or solutions to help overcome these tensions. However, there are also food products that value synergies between quality attributes and between production and processing phases, particularly Geographical Indications, such as for cheese and dry-cured ham. Human epidemiological studies have found associations between consumption of animal-source foods and increased or decreased risk for chronic non-communicable diseases. These associations have informed public health recommendations. However, they have not yet considered animal production and food processing conditions. A concerted and collaborative effort is needed from scientists working in animal science, food process engineering, consumer science, human nutrition and epidemiology in order to address this research gap. Avenues for research and main options for policy action are discussed.

Research Note: Expression level of heat shock protein 27 in PSE-like and fast-glycolyzing conditions of chicken pectoralis major muscle

This study compared the meat quality traits, histochemical characteristics, and heat shock protein (HSP) 27 expression levels of the broiler Pectoralis major (PM) muscles in groups classified by pale, soft, and exudative (PSE)-like and fast-glycolyzing conditions using the lightness and muscle pH change values. Chicken PM muscles showing higher pH change value and paler meat surface (as HP group) could be associated with the PSE-like condition, and exhibited a lower pH_{24 h} value and higher cooking loss compared to PM muscles showing lower pH change value and normal color (as LN group) (P < 0.05). Greater PM muscle weight and fiber area were observed in the HP group compared to the other groups (P < 0.05); meanwhile, the PM muscles showing higher pH change value with normal color (as HN group) and the PM muscles showing lower pH change value with paler color (as LP group) did not differ in the water holding capacity, Warner-Bratzler shear force, and muscle fiber characteristics (P > 0.05). Muscle samples showing a higher pH change value exhibited a greater level of HSP27 compared to muscle samples showing a lower pH change value (P < 0.05). Therefore, the current findings suggested that the expression level of HSP27 can be a useful indicator for explaining variations in the glycolytic rate of chicken breast muscle.

The Effect of Hybrid Barley in the Diets of Fattening Pigs on Pork Oxidative Stability Related to the Fatty Acid Profile

Feed determines the quality of pork meat, in which the composition of the fatty acid (FA) profile is one of the easiest to modify by the application of selected feed components. Barley grains are considered to have an impact on meat quality, including pork; however, there are still limited data on the use of hybrid barley in fattening pigs' nutrition in relation to meat quality. The aim of this study was to determine the relation between meat quality, i.e., its oxidative stability, especially the FA profile, and fattening pigs' diets with hybrid barley and/or wheat. In group I, hybrid barley (HB) composed 80% of the feed; in group II, a mixture of (40% each) wheat and barley was used; and in group III, wheat (W) composed 80% of the feed. Meat samples were taken from twelve randomly selected carcasses chosen from each group. The meat analyses covered the physicochemical and sensory traits. The results showed that the pork meat of fattening pigs fed fodder with 80% HB had decreased palmitic acid concentrations and increased oleic acid concentrations. The meat of these pigs was characterised by the best marbling, which was closely related to its juiciness after thermal processing and determined its final culinary quality. Moreover, the meat from these pigs exhibited a reddish colour, before and after thermal processing. In summary, the application of hybrid barley into pig nutrition improved the quality of the culinary meat.

Relationship Between Meat Quality, Carcass Characteristics, and Protein Abundance of HSPβ1, HSPA, and DJ1 in Beef Longissimus thoracis Pre-Rigor or After 14 Days’ Aging

This study evaluated associations of heat shock proteins (HSP) and an oxidative stress protein, protein deglycase (DJ1), with beef quality and tenderness. Samples from the longissimus thoracis (N = 99) were collected pre-rigor (day 0) and after 14-d aging. Warner-Bratzler shear force (WBSF), myofibrillar fragmentation index (MFI), and a trained sensory panel were used to determine meat quality. Protein abundance of DJ1 and 2 HSP—HSPβ1 and HSPA—were assessed. Regression analyses demonstrated that DJ1 abundance after 14 d of aging is a predictor of WBSF (P &lt; 0.001), MFI (P = 0.02), and sensory panel tenderness (P &lt; 0.001). Abundance of HSPβ1 after 14 d of aging is also a predictor of MFI (P = 0.03). Additionally, abundance of both HSPβ1 and DJ1 pre-rigor are predictors of juiciness (P &lt; 0.05). Abundance of HSPβ1 pre-rigor was correlated with WBSF (R = 0.67), sensory panel tenderness (R = −0.44), juiciness (R = −0.30), and umami (R = −0.20). Abundance of DJ1 pre-rigor was also correlated with WBSF (R = 0.72), sensory panel tenderness (R = −0.44), juiciness (R = − 0.24), and umami (R = −0.31). After 14-d aging, HSP β 1 abundance was cor- related with WBSF (R = 0.66), sensory panel tenderness (R = −0.34), juiciness (R = −0.34), umami (R = −0.33), and brown/ roasted (R = −0.30). Abundance of DJ1 after 14-d aging was also correlated with WBSF (R = 0.68), sensory panel tenderness (R = −0.41), juiciness (R = −0.21), and umami (R = −0.28). These results demonstrate that abundance of HSPβ1 and DJ1 both pre-rigor and after 14 d of aging are correlated with meat tenderness and end-product quality as assessed by a trained sensory panel. Regression analyses further reveal that abundance of DJ1 and HSPβ1 after 14 d of aging is causative in development of beef tenderness and juiciness, respectively. Taken together, these results suggest that abundance of DJ1 is a predictor of tenderness, whereas abundance of HSPβ1 is related to meat quality but cannot be used to predict tenderness.

Sexual Dimorphism of Metabolite Profiles in Pigs Depends on the Genetic Background

The study aimed to investigate possible systematic effects in the basic underlying variability of individual metabolomic data. In this context, the extent of gender- and genotype-dependent differences reflected in the metabolic composition of three tissues in fattening pigs was determined. The 40 pigs belonged to the genotypes PIx(LWxGL) and PIxGL with gilts and boars, respectively. Blood and tissue samples from M. longissimus dorsi and liver were directly taken at the slaughtering plant and directed to GC × GC qMS metabolite analysis. Differences were observed for various metabolite classes like amino acids, fatty acids, sugars, or organic acids. Gender-specific differences were much more pronounced than genotype-related differences, which could be due to the close genetic relation of the fattening pigs. However, the metabolic dimorphism between gilts and boars was found to be genotype-dependent, and vice versa metabolic differences between genotypes were found to be gender-dependent. Most interestingly, integration into metabolic pathways revealed different patterns for carbon (C) and nitrogen (N) usage in boars and gilts. We suppose a stronger N-recycling and increased energy metabolism in boars, whereas, in gilts, more N is presumably excreted and remaining carbon skeletons channeled into lipogenesis. Associations of metabolites to meat quality factors confirmed the applicability of metabolomics approaches for a better understanding about the impact of drivers (e.g., gender, age, breed) on physiological processes influencing meat quality. Due to the huge complexity of the drivers-traits-network, the derivation of independent biomarkers for meat quality prediction will hardly be possible.

Effects of protein posttranslational modifications on meat quality: A review

Meat quality plays an important role in the purchase decision of consumers, affecting producers and retailers. The formation mechanisms determining meat quality are intricate, as several endogenous and exogenous factors contribute during antemortem and postmortem periods. Abundant research has been performed on meat quality; however, unexpected variation in meat quality remains an issue in the meat industry. Protein posttranslational modifications (PTMs) regulate structures and functions of proteins in living tissues, and recent reports confirmed their importance in meat quality. The objective of this review was to provide a summary of the research on the effects of PTMs on meat quality. The effects of four common PTMs, namely, protein phosphorylation, acetylation, S-nitrosylation, and ubiquitination, on meat quality were discussed, with emphasis on the effects of protein phosphorylation on meat tenderness, color, and water holding capacity. The mechanisms and factors that may affect the function of protein phosphorylation are also discussed. The current research confirms that meat quality traits are regulated by multiple PTMs. Cross talk between different PTMs and interactions of PTMs with postmortem biochemical processes need to be explored to improve our understanding on factors affecting meat quality.

Metabolomics Analysis of the Beef Samples with Different Meat Qualities and Tastes

The purpose of this study was to investigate the meat metabolite profiles related to differences in beef quality attributes (i.e., high-marbled and low-marbled groups) using nuclear magnetic resonance (NMR) spectroscopy. The beef of different marbling scores showed significant differences in water content and fat content. High-marbled meat had mainly higher taste compounds than low-marbled meat. Metabolite analysis showed differences between two marbling groups based on partial least square discriminant analysis (PLS-DA). Metabolites identified by PLS-DA, such as N,N-dimethylglycine, creatine, lactate, carnosine, carnitine, sn-glycero-3-phosphocholine, betaine, glycine, glucose, alanine, tryptophan, methionine, taurine, tyrosine, could be directly linked to marbling groups. Metabolites from variable importance in projection plots were identified and estimated high sensitivity as candidate markers for beef quality attributes. These potential markers were involved in beef taste-related pathways including carbohydrate and amino acid metabolism. Among these metabolites, carnosine, creatine, glucose, and lactate had significantly higher in high-marbled meat compared to low-marbled meat (p<0.05). Therefore, these results will provide an important understanding of the roles of taste-related metabolites in beef quality attributes. Our findings suggest that metabolomics analysis of taste compounds and meat quality may be a powerful method for the discovery of novel biomarkers underlying the quality of beef products.

The Profiling of DNA Methylation and Its Regulation on Divergent Tenderness in Angus Beef Cattle

Beef is an essential food source in the world. Beef quality, especially tenderness, has a significant impact on consumer satisfaction and industry profit. Many types of research to date have focused on the exploration of physiological and developmental mechanisms of beef tenderness. Still, the role and impact of DNA methylation status on beef tenderness have yet to be elucidated. In this study, we exhaustively analyzed the DNA methylation status in divergent tenderness observed in Angus beef. We characterized the methylation profiles related to beef tenderness and explored methylation distributions on the whole genome. As a result, differentially methylated regions (DMRs) associated with tenderness and toughness of beef were identified. Importantly, we annotated these DMRs on the bovine genome and explored bio-pathways of underlying genes and methylation biomarkers in beef quality. Specifically, we observed that the ATP binding cassette subfamily and myosin-related genes were highly methylated gene sets, and generation of neurons, regulation of GTPase activity, ion transport and anion transport, etc., were the significant pathways related with beef tenderness. Moreover, we explored the relationship between DNA methylation and gene expression in DMRs. Some methylated genes were identified as candidate biomarkers for beef tenderness. These results provide not only novel epigenetic information associated with beef quality but offer more significant insights into meat science, which will further help us explore the mechanism of muscle biology.

Research in Beef Tenderness and Palatability in the Era of Big Data

For decades, research has focused on predicting beef palatability using muscle biochemical traits, and various biomarkers. In these approaches, a precise definition of the variable to predict (tenderness assessed by panelists, untrained consumers, or shear force), and repeatability of the measurements are crucial for creating significant data resources for the derivation of robust predictive models, and rigorous validation testing. This “big data” approach also requires careful definition of traits and transparent principles for data sharing and management. As in other fields, meat science researchers should improve the Findability, Accessibility, Interoperability, and Reuse of data (known as the FAIR principles). Furthermore, with the rapid evolution of new measurement technologies, the traits that they measure must be consistently described, enhancing our ability to integrate these new measurements into existing description systems. For beef, strategic choices have been made in order to consider real consumers’ expectations, not well estimated correctly by lab approaches. This strategy has been successfully developed in Australia, which set up the “Meat Standards Australia” grading scheme, now partly adopted by the beef industry. The ambitions of the International Meat Research 3G Foundation is to develop beef ontology, to set up an international database with a huge number of consumers’ scores related to beef palatability and collected according to standard protocols. The foundation also aims to support the beef industry by offering an international predictive model of beef palatability, flexible enough to take into account any local livestock characteristics or regional consumer specificity. This approach is supported by the United Nations Economic Commission for Europe (UNECE), which is promoting development of regulations and norms, technical cooperation and exchange of best expertise and practices. This will substantially improve the transparency of data flow and price signaling between all participants of the value chain, from beef producers through to consumers at retail.

Using Genetic Panels to Predict Tenderness in Beef Cattle

Genetic panel use as a selection tool has grown in popularity in the beef industry. The objective of the study was to determine whether beef cattle genetically selected for tenderness generated a tender product. Igenity® (IT) panel results were provided by a cattle producer for 52 steers, which were harvested at a commercial harvest facility. Boneless strip loins (Institutional Meat Purchase Specifications #180; United States Department of Agriculture [USDA] Choice, n = 32; USDA Prime n = 20) were collected from the left side of each carcass and transported to the University of Idaho Meat Science Laboratory. Four steaks were cut from each subprimal and assigned to aging periods of 7, 14, and 21 d for Warner-Bratzler Shear Force (WBSF) analysis or 21 d for consumer sensory analysis. Carcasses were assigned to tenderness groups based on their IT tenderness indexes (Low IT, 3 – 6, n = 30; High IT, 7 – 10, n = 22). Data were analyzed using the mixed model procedure of SAS version 9.4 (SAS Institute Inc., Cary, NC). An interaction was observed between tenderness group and USDA quality grade (P = 0.015) when analyzing WBSF. All of the cattle had less than 4.14 kg of WBSF; however, USDA Prime steers that were in the High IT tenderness group produced more tender steaks than High IT USDA Choice, Low IT USDA Prime, and Low IT USDA Choice steers. Consumers were not able to detect tenderness differences between IT tenderness groups (P = 0.11) or USDA quality grades (P = 0.11), but they found USDA Prime steaks to be more acceptable (P = 0.01), juicier (P = 0.01), and more flavorful (P = 0.02) than USDA Choice steaks. In conclusion, regardless of tenderness group, USDA Prime steaks were preferred by consumers over USDA Choice steaks in terms of flavor, juiciness, and acceptability.

Identification of single-nucleotide variants associated with susceptibility to Salmonella in pigs using a genome-wide association approach

BACKGROUND

Salmonella enterica serovars are a major cause of foodborne illness and have a substantial impact on global human health. In Canada, Salmonella is commonly found on swine farms and the increasing concern about drug use and antimicrobial resistance associated with Salmonella has promoted research into alternative control methods, including selecting for pig genotypes associated with resistance to Salmonella. The objective of this study was to identify single-nucleotide variants in the pig genome associated with Salmonella susceptibility using a genome-wide association approach. Repeated blood and fecal samples were collected from 809 pigs in 14 groups on farms and tonsils and lymph nodes were collected at slaughter. Sera were analyzed for Salmonella IgG antibodies by ELISA and feces and tissues were cultured for Salmonella. Pig DNA was genotyped using a custom 54 K single-nucleotide variant oligo array and logistic mixed-models used to identify SNVs associated with IgG seropositivity, shedding, and tissue colonization.

RESULTS

Variants in/near PTPRJ (p = 0.0000066), ST6GALNAC3 (p = 0.0000099), and DCDC2C (n = 3, p < 0.0000086) were associated with susceptibility to Salmonella, while variants near AKAP12 (n = 3, p < 0.0000358) and in RALGAPA2 (p = 0.0000760) may be associated with susceptibility.

CONCLUSIONS

Further study of the variants and genes identified may improve our understanding of neutrophil recruitment, intracellular killing of bacteria, and/or susceptibility to Salmonella and may help future efforts to reduce Salmonella on-farm through genetic approaches.

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

In the past decades, metabolomics has been used to comprehensively understand a variety of food materials for improvement and assessment of food quality. Farm animal skeletal muscles and meat are one of the major targets of metabolomics for the characterization of meat and the exploration of biomarkers in the production system. For identification of potential biomarkers to control meat quality, studies of animal muscles and meat with metabolomics (MEATabolomics) has been conducted in combination with analyses of meat quality traits, focusing on specific factors associated with animal genetic background and sensory scores, or conditions in feeding system and treatments of meat in the processes such as postmortem storage, processing, and hygiene control. Currently, most of MEATabolomics approaches combine separation techniques (gas or liquid chromatography, and capillary electrophoresis)-mass spectrometry (MS) or nuclear magnetic resonance (NMR) approaches with the downstream multivariate analyses, depending on the polarity and/or hydrophobicity of the targeted metabolites. Studies employing these approaches provide useful information to monitor meat quality traits efficiently and to understand the genetic background and production system of animals behind the meat quality. MEATabolomics is expected to improve the knowledge and methodologies in animal breeding and feeding, meat storage and processing, and prediction of meat quality.

Gene and protein expression of myosin heavy chain in Nellore cattle comparing growth or meat tenderness traits

The objective was to investigate gene and protein expression of myosin heavy chain (MyHC) in Nellore cattle slaughtered at different weights (BW) or degrees of meat tenderness. Ninety animals with initial BW 370 ± 37 kg, 24 months of age, were slaughtered after 95 days on feed. We evaluated shear force (SF), myofibrillar fragmentation index, ribeye area, backfat thickness, marbling, color, and cooking losses. Subsequently, 24 animals were selected and divided into four contrasting groups, in which light (BW = 504.58 ± 32.36 kg) versus heavy animals (BW = 604.83 ± 42.97 kg) and animals with tender (SF = 3.88 ± 0.57 kg) versus tough meat (SF = 7.95 ± 1.04 kg) were compared. The MYH7, MYH2 and MYH1 genes were analyzed by real-time PCR. The MyHC isoforms (MyHC-I, MyHC-IIa, and MyHC-IIx) were quantified by SDS-PAGE electrophoresis. We found lower expression of MYH2 and MYH1 genes in heavy compared to light animals and a higher amount of MyHC-I isoform in the tough meat group compared to the tender meat group. Protein expression of MyHC-IIa was higher in the tender meat group. A negative correlation was found of this protein and SF (tenderness), suggesting MyHC-IIa as a biomarker of meat quality.

Predicting the Quality of Meat: Myth or Reality?

This review is aimed at providing an overview of recent advances made in the field of meat quality prediction, particularly in Europe. The different methods used in research labs or by the production sectors for the development of equations and tools based on different types of biological (genomic or phenotypic) or physical (spectroscopy) markers are discussed. Through the various examples, it appears that although biological markers have been identified, quality parameters go through a complex determinism process. This makes the development of generic molecular tests even more difficult. However, in recent years, progress in the development of predictive tools has benefited from technological breakthroughs in genomics, proteomics, and metabolomics. Concerning spectroscopy, the most significant progress was achieved using near-infrared spectroscopy (NIRS) to predict the composition and nutritional value of meats. However, predicting the functional properties of meats using this method-mainly, the sensorial quality-is more difficult. Finally, the example of the MSA (Meat Standards Australia) phenotypic model, which predicts the eating quality of beef based on a combination of upstream and downstream data, is described. Its benefit for the beef industry has been extensively demonstrated in Australia, and its generic performance has already been proven in several countries.

Statistical model choice including variable selection based on variable importance: A relevant way for biomarkers selection to predict meat tenderness

In this paper, we describe a new computational methodology to select the best regression model to predict a numerical variable of interest Y and to select simultaneously the most interesting numerical explanatory variables strongly linked to Y. Three regression models (parametric, semi-parametric and non-parametric) are considered and estimated by multiple linear regression, sliced inverse regression and random forests. Both the variables selection and the model choice are computational. A measure of importance based on random perturbations is calculated for each covariate. The variables above a threshold are selected. Then a learning/test samples approach is used to estimate the Mean Square Error and to determine which model (including variable selection) is the most accurate. The R package modvarsel (MODel and VARiable SELection) implements this computational approach and applies to any regression datasets. After checking the good behavior of the methodology on simulated data, the R package is used to select the proteins predictive of meat tenderness among a pool of 21 candidate proteins assayed in semitendinosus muscle from 71 young bulls. The biomarkers were selected by linear regression (the best regression model) to predict meat tenderness. These biomarkers, we confirm the predominant role of heat shock proteins and metabolic ones.

Dietary β-glucan supplementation improves growth performance, carcass traits and meat quality of finishing pigs

This experiment was conducted to investigate growth performance, carcass traits and meat quality of finishing pigs with dietary β-glucan supplementation. A total of 96 healthy pigs (Duroc × Landrace × Yorkshire; initial average BW = 25 kg) were randomly allocated into 4 dietary treatments with 6 replicates per treatment and 4 pigs per replicate. The control group was fed a basal diet, and the experimental diets were supplemented with 50, 100 and 200 mg/kg Agrobacterium sp. ZX09 β-glucan, respectively. The experiment lasted 103 d. The basal diet supplemented with 100 mg/kg β-glucan significantly increased average daily gain and feed conversion ratio, probably due to the improved digestibility of dry matter, gross energy and crude protein (P < 0.05). Beta-glucan supplementation from 100 to 200 mg/kg of diet significantly increased carcass length (P < 0.05). The basal diet supplemented with 100 mg/kg β-glucan supplementation also significantly (P < 0.05) increased muscle pH, reduced drip losses and increased a^∗ values. The basal diet supplemented with 100 mg/kg β-glucan increased the content of intramuscular fat and changed the proportion of saturated fatty acid and unsaturated fatty acid, thereby improved the flavor of meat. In conclusion, the basal diet supplemented with 100 mg/kg Agrobacterium sp. ZX09 β-glucan improves growth performance, nutrient digestibility, carcass length, and pork quality of finishing pigs.

A proteomic-based approach for the search of biomarkers in Iberian wild deer (Cervus elaphus) as indicators of meat quality

The positive perception of deer meat among consumers is growing. Consequently, further efforts are needed to control its meat quality. Specifically, the aim of this study was to search protein biomarkers in connection with tenderness and intramuscular fat (IMF) content of Iberian wild red deer (Cervus elaphus) meat. Twelve venison samples classified as tender, intermediate and tough meat, as well as with different IMF were studied, using quantitative proteomic by SWATH-MS combined with bioinformatic analyses. The study of muscle proteome showed significant differences among these three groups of meat samples, since five differentially abundant proteins (IVD, LAMB1, MYL3, SDHC and SDHA) and six (FABP4, IVD, LAMB1, MYL3, CRYZ and SERPINB6) were strongly correlated with tenderness and IMF, respectively. The proteomic approach provides protein biomarkers linked to venison meat quality and marked changes in proteins related to oxidoreductase complex in skeletal muscle. SIGNIFICANCE: Meat tenderness and IMF are major concerns in game meat. The proteomic approach demonstrated a strong correlation between proteins and these quality traits, despite the complexity of samples (wild animals hunted at different ages). Our results suggest that several proteins can be biomarkers and provide a molecular insight.

An Original Methodology for the Selection of Biomarkers of Tenderness in Five Different Muscles

For several years, studies conducted for discovering tenderness biomarkers have proposed a list of 20 candidates. The aim of the present work was to develop an innovative methodology to select the most predictive among this list. The relative abundance of the proteins was evaluated on five muscles of 10 Holstein cows: gluteobiceps, semimembranosus, semitendinosus, Triceps brachii and Vastus lateralis. To select the most predictive biomarkers, a multi-block model was used: The Data-Driven Sparse Partial Least Square. Semimembranosus and Vastus lateralis muscles tenderness could be well predicted (R² = 0.95 and 0.94 respectively) with a total of 7 out of the 5 times 20 biomarkers analyzed. An original result is that the predictive proteins were the same for these two muscles: µ-calpain, m-calpain, h2afx and Hsp40 measured in m. gluteobiceps and µ-calpain, m-calpain and Hsp70-8 measured in m. Triceps brachii. Thus, this method is well adapted to this set of data, making it possible to propose robust candidate biomarkers of tenderness that need to be validated on a larger population.

Beef tenderness and intramuscular fat proteomic biomarkers: Effect of gender and rearing practices

This study analyzed the effect of gender on the abundances of 20 protein biomarkers of tenderness and/or intramuscular fat content in five muscles: Longissimus thoracis, previously identified as biomarkers of tenderness and/or intramuscular Semimembranosus, Rectus abdominis, Triceps brachii and Semitendinosus, from cows and steers of the Protected Designation Origin Maine Anjou. The protein abundances were quantified using Reverse Phase Protein Array with specific validated antibodies. Among the 20 studied proteins, the abundance of 8 biomarkers involved in energetic metabolism, contraction and cellular stress, was different according to gender. The gender effect was different depending on the muscle type with greater abundances in Semitendinosus, Rectus abdominis and Longissimus thoracis muscles. On the basis of animal characteristics and rearing factors, three rearing practices classes were identified for cows. Among the factors, fattening duration modified the abundance of 12 proteins mainly in Triceps brachii muscle. A positive correlation between the abundance of the small HSP20 and slaughter age was observed in the 5 muscles. Two proteins, Four and a half LIM domains 1 (FHL1) and Glycogen phosphorylase (PYGB) appeared to be muscle, gender and rearing practices independent. These results constitute valuable data to understand how to manage beef quality by controlling these different factors. SIGNIFICANCE: This study is the first to compare the relative abundance of 20 proteins previously identified as biomarkers of tenderness and/or intramuscular fat (IMF) content of beef meat between cows and steers among 5 different muscles. Its originality is in the use of Reverse Phase Protein Array for fast quantification of the proteins and the integration of data from rearing factors, carcass characteristics and biomarkers of meat qualities. The findings provide evidence for modulating biomarker levels by controlling the choice of animal type and rearing factors according to the type of muscle that would produce animals with the desired meat qualities.

Comparing SRM and SWATH Methods for Quantitation of Bovine Muscle Proteomes

Mass spectrometry (MS) has become essential for efficient and accurate quantification of proteins and proteomes and, thus, a key technology throughout all biosciences. However, validated MS methods are still scarce for meat quality research applications. The objective of this work was to develop and compare two targeted proteomic methods, namely, selected reaction monitoring (SRM) and sequential window acquisition of all theoretical spectra (SWATH), for the quantification of 11 bovine muscle proteins that may be indicators of meat color. Both methods require evaluation of spectra from proteotypic and quantotypic peptides, and we here report our evaluation of which peptides and MS parameters are best suited for robust quantification of these 11 proteins. We observed that the SRM approach provides better reproducibility, linearity, and sensitivity than SWATH and is therefore ideal for targeted quantification of low-abundance proteins, while the SWATH approach provides a more time-efficient method for targeted protein quantification of high-abundance proteins and, additionally, supports the search for novel biomarkers.

Data from the Farmgate-to-Meat Continuum Including Omics-Based Biomarkers to Better Understand the Variability of Beef Tenderness: An Integromics Approach

This study is based on an integromic approach of 71 young bulls' data from the farmgate-to-meat continuum including omics-based biomarkers, to understand beef tenderness variability in two muscle cuts that differ by their contractile and metabolic properties. By the means of chemometrics using partial least-squares (PLS) and principal component regressions (PCR), important variables from a list of 49 that characterize four levels of the continuum (rearing factors-carcass-muscle-meat) were identified to explain tenderness of Longissimus thoracis (LT) and Semitendinosus (ST) muscles evaluated by a sensory panel and instrumental Warner-Bratzler shear force (WBSF). The PLS and PCR analyses validated 16 and 15 variables for LT and 12 and 14 for ST from the whole continuum to explain sensory tenderness and WBSF, respectively. Among the explanatory variables in the four models and in line with the role of apoptosis in tenderness determinism, HSP70-1A/B (a heat shock protein) was retained to explain beef tenderness irrespective of muscle and evaluation method. Similarly, dressing percentage from the carcass level was another robust predictor but in a muscle-dependent direction manner. HSP20, ENO3, and MyHC-I as three muscle protein biomarkers and dry matter intake (DMI) as a rearing factor were involved in three models to explain beef tenderness. This study highlighted also that several variables were muscle-specific irrespective of the evaluation method of tenderness. For LT muscle, six variables including three carcass traits (fatness score, fat carcass %, and muscle carcass %), two muscle biomarkers (HSP70-8 and MyHC-IIx/b), and one meat quality trait (pH_3h) were found. For ST muscle, five variables were validated from two rearing factors (average daily gain and feed efficiency) and three structural protein biomarkers (α-actin, MyBP-H, and CapZ-β). Finally, for WBSF only, lactate dehydrogenase chain B (LDH-B) was retained positively for LT and negatively for ST muscles. Overall, this trial showed that tenderness of LT and ST muscle cuts is influenced by variables belonging to the whole continuum with relationships that depend on both the muscle type and the evaluation method. It further highlighted the potential of integromic/chemometric approaches on the farmgate-to-meat continuum data to better understand the sophisticated biological processes that orchestrate the conversion of muscle into meat and tenderness determinism.

Beef tenderness and intramuscular fat proteomic biomarkers: muscle type effect

Tenderness and intramuscular fat content are key attributes for beef sensory qualities. Recently some proteomic analysis revealed several proteins which are considered as good biomarkers of these quality traits. This study focuses on the analysis of 20 of these proteins representative of several biological functions: muscle structure and ultrastructure, muscle energetic metabolism, cellular stress and apoptosis. The relative abundance of the proteins was measured by Reverse Phase Protein Array (RPPA) in five muscles known to have different tenderness and intramuscular lipid contents: Longissimus thoracis (LT), Semimembranosus (SM), Rectus abdominis (RA), Triceps brachii (TB) and Semitendinosus (ST). The main results showed a muscle type effect on 16 among the 20 analyzed proteins. They revealed differences in protein abundance depending on the contractile and metabolic properties of the muscles. The RA muscle was the most different by 11 proteins differentially abundant comparatively to the four other muscles. Among these 11 proteins, six were less abundant namely enolase 3 (ENO3), phosphoglucomutase 1 (PGK1), aldolase (ALDOA), myosin heavy chain IIX (MyHC-IIX), fast myosin light chain 1 (MLC1F), triosephosphate isomerase 1 (TPI1) and five more abundant: Heat shock protein (HSP27, HSP70-1A1, αB-crystallin (CRYAB), troponin T slow (TNNT1), and aldolase dehydrogenase 1 (ALDH1A1). Four proteins: HSP40, four and a half LIM domains protein 1 (FHL1), glycogen phosphorylase B (PYGB) and malate dehydrogenase (MDH1) showed the same abundance whatever the muscle. The correlations observed between the 20 proteins in all the five muscles were used to construct a correlation network. The proteins the most connected with the others were in the following order MyHC-IIX, CRYAB, TPI1, PGK1, ALDH1A1, HSP27 and TNNT1. This knowledge is important for understanding the biological functions related to beef tenderness and intramuscular fat content.

Use of liquid isoelectric focusing (OFFGEL) on the discovery of meat tenderness biomarkers

Protein biomarkers of meat tenderness are known to be of primary importance for the prediction of meat quality, and hence, industry profitability. Proteome analysis was performed on meat from 8 Main Anjou beef cattle, previously classified as tender or tough meats by Warner Bratzler shear force measurements. Myofibrillar fraction of Longissimus thoracis muscle was separated by a novel fractionation approach based on liquid isoelectric focusing (OFFGEL) and further analyzed by SDS-PAGE and liquid chromatography coupled to tandem mass spectrometry. Obtained OFFGEL fraction profiles were reproducible allowing the comparison of both meat qualities and revealing 7 protein bands capable to discriminate between tender and tough samples. The proteins present in these bands were troponin T, Heat Shock protein beta-1, creatine kinase, actin, troponin C, myosins 1 and 2 and myozenin-1. The latter protein has not been previously reported as a marker of meat tenderness.

SIGNIFICANCE

This study introduces an innovative proteomic approach for the study of muscle proteome. The fact of obtaining fractions in liquid state after OFFGEL fractionation allows for a faster analysis of proteins by mass spectrometry, being an interesting alternative to more classical proteomic approaches based on two dimensional gel electrophoresis (2-DE).

Reverse phase protein arrays for the identification/validation of biomarkers of beef texture and their use for early classification of carcasses

The validation of biomarkers and tools for the prediction of beef texture remains a challenging task. In this study, reverse phase protein arrays (RPPA) quantified 29 protein biomarkers in the m. Longissimus thoracis of Charolais cattle sampled early post-mortem. Myosin heavy chain 1 (MHC1, slow-oxidative fibers) and Retinal dehydrogenase 1 (ALDH1A1, oxidative enzyme) discriminated between tender and juicy vs. tough meat with residues classes and are validated as prime biomarkers of beef texture. Several proteins belonging to energy metabolism, heat shock and oxidative stress, cytoskeletal, cell signaling and apoptosis were related with tenderness. Among the unusual proteins, Four and a half LIM domains 1 (FHL1) and Tripartite motif protein 72 (TRIM72) correlated respectively negatively and positively with beef tenderness. Principal component regression was used for the first time to explain beef texture traits using biomarkers. The results are very promising as they revealed sophisticated mechanisms behind the tenderizing process.

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits.

Invited review: Measurable biomarkers linked to meat quality from different pig production systems

Abstract. Biological processes underlie all livestock traits, including post-mortem meat quality traits. Biomarkers are molecular components of the biological processes showing differential expression associated with the phenotype of the trait. The phenotypes of the meat quality traits are determined by the animal's genotype interacting with the environment affecting the expression of the genome. The omics technologies enable measuring the expression of the genome at all levels: transcriptome, proteome, and metabolome. Associations between the phenotype of the traits and expressions measured with the omics techniques are a first step in developing biomarkers. Biomarkers enable the monitoring, diagnosis, and prediction of changes in meat quality related to external (environmental, e.g. feed and animal management conditions) stimuli and interactions with the genotype. In this paper we review the development of biomarkers for meat quality of pigs in diverse pig breeds, environments, and pork production chains.

Muscle transcriptome analysis reveals molecular pathways and biomarkers involved in extreme ultimate pH and meat defect occurrence in chicken

The processing ability and sensory quality of chicken breast meat are highly related to its ultimate pH (pHu), which is mainly determined by the amount of glycogen in the muscle at death. To unravel the molecular mechanisms underlying glycogen and meat pHu variations and to identify predictive biomarkers of these traits, a transcriptome profiling analysis was performed using an Agilent custom chicken 8 × 60 K microarray. The breast muscle gene expression patterns were studied in two chicken lines experimentally selected for high (pHu+) and low (pHu-) pHu values of the breast meat. Across the 1,436 differentially expressed (DE) genes found between the two lines, many were involved in biological processes related to muscle development and remodelling and carbohydrate and energy metabolism. The functional analysis showed an intensive use of carbohydrate metabolism to produce energy in the pHu- line, while alternative catabolic pathways were solicited in the muscle of the pHu+ broilers, compromising their muscle development and integrity. After a validation step on a population of 278 broilers using microfluidic RT-qPCR, 20 genes were identified by partial least squares regression as good predictors of the pHu, opening new perspectives of screening broilers likely to present meat quality defects.