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. 2026 Jan 30;12:100362. doi: 10.1016/j.fochms.2026.100362

Oat grass improves meat tenderness and flavor, reduces fat deposition in small-tailed Han sheep

Li-Wei Wang a,b,1, Jian-Qiang Li a,1, Jiang-Hong An b, Hua Sun b, Fang Liu b, Meng-Ran Zhao b, Li-Li Jiang b, Xing-Ran Dong a, Sarula Tao d, Mengke Bayaer e, Jiang-Feng He b,⁎, Yong-Bin Liu a,c,⁎⁎
PMCID: PMC12906192  PMID: 41695382

Abstract

Oat grass supplementation is a promising strategy for improving meat quality in ruminants. This study investigated its effects on the meat quality of Small-tailed Han sheep. The results revealed that sheep fed oat grass displayed higher expression of key genes (MYL10, MYL2), Actin, and Cytochrome coxidase (Cyto) associated with muscle structure and contraction, while genes (ACTC1, MYH2, PIP4K2B) and proteins (MLC, PFN, Tnc) associated with cardiac contraction and myosin cytoskeletal regulation were downregulated. These molecular changes were likely to underpin meat tenderness and texture. Furthermore, oat grass supplementation influenced metabolic pathways linked to flavor-enhancing compounds, including amino acids and free fatty acids like alanine. These metabolic changes not only improved lamb tenderness but also enhanced its flavor and nutritional profile. This study provides evidence that oat grass supplementation is a practical and effective dietary strategy for optimizing lamb meat quality, offering dual benefits of improved sensory appeal and nutritional value.

Keywords: Meat quality, RNA-seq, TMT proteomics, Small-tailed Han sheep, Longissimus dorsi muscle

Highlights

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    Oat grass supplementation improves lamb meat tenderness and sensory appeal.

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    Alters expression of muscle structure and contraction-related genes and proteins.

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    Downregulates cardiac contraction and cytoskeletal regulation-related genes.

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    Enhances metabolic pathways linked to flavor-enhancing amino acids and fatty acids.

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    Provides a practical dietary strategy to optimize lamb meat quality and nutrition.

1. Introduction

Lamb meat is a popular choice among consumers due to its unique flavor, tender texture, and rich nutritional profile. These qualities make it a highly valued source of protein (Dou et al., 2024). However, modern sheep farming practices, particularly intensive feeding systems that rely heavily on concentrate-based diets, have been linked to declines in meat quality and feed conversion efficiency. These systems negatively affect key attributes such as lamb flavor and texture, reducing the overall appeal of lamb meat (Zhang et al., 2022). To address these challenges, researchers have increasingly turned to dietary interventions, such as incorporating high-quality forage grasses like oat grass into sheep diets (Ren et al., 2025). Studies have shown that these supplements not only improve growth performance, slaughter rates, and meat quality but also enhance antioxidant properties, promote intestinal microbial diversity, and boost muscle metabolite content (Lin et al., 2017).

Enhancing meat quality in livestock production has been a priority, with key indicators such as tenderness and nutrient composition playing crucial roles in meeting consumer demands and increasing market value. Among the dietary strategies employed to achieve these improvements, the inclusion of high-quality forage stands out as a promising approach. For example, studies have shown that incorporating alfalfa into lamb diets enhances meat tenderness and increases its polyunsaturated fatty acid (PUFA) content, thereby improving its nutritional value (Francisco et al., 2020). Similarly, flaxseed supplementation in cattle and poultry diets has elevated omega-3 fatty acid levels and improved meat tenderness compared to traditional feeds (Ponnampalam et al., 2003). Oat-based forages, in particular, have gained significant attention due to their high nutritional value and versatility (Wang et al., 2025). Studies have demonstrated that feeding oat silage to beef cattle improves muscle water retention, tenderness, and muscle fiber density while reducing cross-sectional area, all of which contribute to superior meat quality (Wood et al., 2008). Additionally, oat grass supplementation has been shown to improve feed intake and growth performance in Holstein female calves (Xiao et al., 2021).

Oats (Avena sativa L.) are frequently incorporated into the diets in ruminant production systems due to their high protein content and superior nutritional profile, with particularly widespread application in sheep farming (Agüera et al., 2023). In sheep diets, oat hay has been shown to enhance rumen microbial diversity and species richness, which are necessary for nutrient absorption and intestinal wellness (An et al., 2020). Feeding silage oats to Hu sheep has further demonstrated significant benefits, including improved growth performance, nutrient digestibility, rumen health, slaughter rates, and meat quality (Janssen et al., 2022). These findings highlight the multifaceted advantages of incorporating oat grass into sheep diets, not only for improving meat quality and nutritional value but also for optimizing production efficiency.

Recent advancements in sequencing technologies and bioinformatics have transformed the study of meat quality by uncovering the molecular mechanisms underlying key traits. Techniques such as RNA sequencing (RNA-seq) and tandem mass tag (TMT)-based proteomics provide unprecedented insights into the genetic and proteomic factors underlying meat quality traits. RNA-seq has been used to identify genetic markers and pathways associated with fatty acid (FA) composition, such as in the longissimus dorsi muscle where candidate genes linked to polyunsaturated FA were identified for marker-assisted selection (Kong et al., 2023). Researchers can gain a deeper understanding of the molecular mechanisms governing carcass and meat quality by connecting genotypic variation to phenotypic features through the combination of multi-omics methods like transcriptomics and proteomics (Dou et al., 2024). By integrating multi-omics techniques like transcriptomics and proteomics, researchers have been able to link genotypic variation to phenotypic characteristics, offering better insights into the molecular regulation of carcass and meat quality variables (Arikawa et al., 2024). For example, carcass and meat quality characteristics of Nellore cattle have been studied using genome-wide association studies (GWAS) in conjunction with transcriptomics and proteomics (Frezarim et al., 2025).

Building on previous findings, our research group explored the metabolomic effects of supplementing 30% oat grass in the diet of Small-tailed Han sheep, demonstrating its significant positive impact on growth performance and meat quality (Wang et al., 2023). We build on this work in the present study aims to examine the molecular processes behind these observed improvements. In particular, we used TMT-based proteomics and RNA-seq transcriptomics to find important genes, proteins, and regulatory pathways linked to characteristics of meat quality. By integrating these multi-omics approaches, we aim to provide a comprehensive understanding of how oat grass supplementation enhances lamb meat quality. This research not only deepens our understanding of the molecular basis of forage utilization in sheep production but also offers a theoretical framework for advancing forage oat research and improving sheep breeding practices.

2. Materials and methods

2.1. Animals and feeding regimes

A total of 40 Small-tailed Han sheep, approximately 90 days old and with an average live weight of 17.2 ± 1.3 kg, were selected for the study. The experiment lasted 100 days, consisting of a 10-day adaptation phase and a 90-day feeding period. The lambs were randomly assigned to two dietary groups (n = 20 per group): the oat supplementation dietary group (OS) and the control group (CON). The OS group was fed a pelleted concentrate mixed with oat grass in a 70:30 ratio based on dry matter basis, while the CON group received a maize-based diet. Table S1 provides the experimental diets' nutritional profiles and detailed ingredient compositions. All sheep had unlimited access to salt blocks and clean drinking water during the trial. Ten lambs from each group were fasted for twenty-four hours at the conclusion of the feeding period before being slaughtered. Following slaughter, the longissimus dorsi muscle was removed from the left side of the 12th and 13th ribs. For further analysis, the samples were tagged, snap-frozen in liquid nitrogen, and kept at −80 °C.

2.2. Carcass characteristics and meat samples

Following a 100-day feeding trial, 10 lambs were randomly selected from each treatment group and individually weighed after a 24-h fasting period. All lambs were slaughtered by trained personnel at a local commercial abattoir. Immediately following slaughter, the hot carcass weight was noted, and the dressing % was computed as the carcass weight divided by the live weight. Ten grams of muscle were taken from each carcass's left side, including the longissimus dorsi (LD), intercostal muscles (IM), and hind leg muscles (HLM). The LD muscle was used for transcriptomic and proteomic sequencing, while the IM and HLM samples were retained for validation assays. The GR (fat depth) value, measured 110 mm from the midpoint of the 12th rib, was recorded as an indicator of carcass fat content. Additionally, the initial pH of the LD muscle was measured 45 min post-slaughter. Small-tailed Han sheep's growth performance and carcass parameters were assessed in relation to oat grass supplementation (Wang et al., 2023).

2.3. RNA-Seq analysis

2.3.1. RNA isolation and library preparation

TRIzol reagent was used to extract total RNA from tissue samples in accordance with the manufacturer's instructions. An Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) was used to assess RNA integrity, while a Nanodrop 2000 spectrophotometer (Thermo Scientific, MA, USA) was used to detect RNA concentration and purity. The TruSeq Stranded mRNA LT Sample Prep Kit (Illumina, San Diego, CA, USA) was used to prepare sequencing libraries in accordance with the manufacturer's instructions. OE Biotech Co., Ltd. (Shanghai, China) carried out transcriptome sequencing and the ensuing bioinformatic studies.

2.3.2. RNA sequencing and differentially expressed genes analysis

An Illumina HiSeq X Ten platform was used to sequence RNA sequencing libraries, producing high-quality 150 bp paired-end reads. Trimmomatic was used to eliminate low-quality reads from raw sequencing data, producing clean reads for further analysis. Clean reads were aligned to the Oar_Rambouillet_v1.0 genome using HISAT2 for accurate gene mapping and expression quantification. Gene expression levels were calculated as FPKM values using Cufflinks, and gene read counts were obtained with HTSeq-count. Differential expression analysis was performed using the DESeq R package, applying thresholds of P-value <0.05 and |log₂FC| > 1 to identify significantly differentially expressed genes (DEGs). Hierarchical cluster analysis (HCA) was conducted to visualize gene expression patterns across groups. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database were used for functional enrichment analysis of differentially expressed genes (DEGs). This research, which was conducted using R software and was based on the hypergeometric distribution, sought to pinpoint biological processes and pathways connected to the observed variations in gene expression. This integrated workflow, encompassing RNA extraction, sequencing, data processing, statistical analysis, and functional annotation, provides a comprehensive overview of gene expression patterns and their biological significance.

2.3.3. Protein digestion and TMT Labeling

TMT-based quantitative proteomics analyzed the proteome of LD samples. Protein lysates were centrifuged at 2000 ×g for 10 min at 4 °C. To pellet the proteins, the supernatant was treated with trichloroacetic acid, incubated at 4 °C, and then centrifuged for three minutes at 12,000 ×g. A bicinchoninic acid (BCA) test kit was used to quantify the pellet after cleaning with acetone and redissolving in 8 M urea. Proteins were enzymatically degraded with trypsin overnight at 37 °C. The resulting peptides were desalted using StrataTM X C18 solid-phase extraction cartridges and then vacuum-lyophilized.

Peptides were dissolved in 0.5 M triethylammonium bicarbonate (TEAB) and labeled using the TMT kit method. The tagged peptides were fractionated using high pH reversed-phase high-performance liquid chromatography (HPLC), yielding 18 fractions that were subsequently lyophilized. An EASY nLC 1000 ultra-high-performance liquid chromatography (UHPLC) system with mobile phase A was employed for further separation. Peptides were then analyzed by mass spectrometry after being ionized using a nano electrospray ionization (NSI) source.

Secondary mass spectrometry data were processed using MaxQuant software (vl.5.2.8) to identify differentially expressed proteins (DEPs). DEPs were defined based on FC and P-value thresholds: |log₂FC| > 0.26 and P < 0.05. A global false discovery rate (FDR) of <1% was applied, with a minimum of two peptides required for protein quantification. Proteome Discover 2.4 software and the UniPort protein database were utilized for further analysis. Functional annotation of DEPs was conducted using GO and KEGG pathway analysis. These investigations contributed to a better understanding of the differential proteins' roles in biological processes and mechanisms by revealing biological activities and signaling pathways connected to them.

2.4. Multi-omics joint-level analysis

This multi-omics approach elucidates complex biological processes and interactions, thereby yielding critical insights into post-transcriptional and post-translational regulatory mechanisms. By integrating DEGs and DEPs, key connections between the transcriptome and proteome are identified. A central component of this analysis is the construction of a protein-protein interaction (PPI) network, which maps protein relationships and highlights their functional roles within cellular systems. To enhance the PPI network analysis, virtual nodes are incorporated to identify regulatory mechanisms and interactions that may not be directly observable. PPI network illustrates the functional associations between the differentially expressed genes DEGs and DEPs. In the network, nodes colored in red denote up-regulated genes/proteins, while those in blue represent down-regulated ones. The number of edges between two nodes corresponds to the strength of interaction evidence, with a greater number of connections indicating higher confidence in the predicted functional relationship. These virtual nodes provide additional context for understanding underlying biological processes. To guarantee that only statistically significant connections are included in the study, a significance level of P < 0.05 is used. This integrative analysis of transcriptomics and proteomics data not only advances our understanding of gene regulation but also establishes further functional studies and systems biology research.

2.5. RT-qPCR validation

To validate the reliability of the RNA-Seq data, five candidate genes (MYL2, MYH2, MYL10, PIP4K2B, and ACTC1) associated with key pathways identified from DEGs were selected for RT-qPCR analysis. A reverse transcriptase kit (Takara, Dalian, China) was used to create first-strand cDNA after total RNA was extracted using TransZol reagent (TransGen Biotech, Beijing, China). Using the SYBR premix Ex TaqTM kit (Takara, Dalian, China), RT-qPCR was carried out on a Light Cycler 480 system (Roche Applied Science, Mannheim, Germany). The amplification procedure comprised an initial denaturation at 95 °C, 42 cycles of 95 °C for 5 s, and 20 s of annealing at an optimal temperature, and extension at 72 °C for 30 s. Gene-specific primers were designed using Oligo 7.0 and Primer 5 software (Table S2), with GAPDH serving as the reference gene. To guarantee precision and repeatability, each reaction was carried out three times. The 2-ΔΔCT technique was used to determine relative gene expression levels (Schmittgen & Livak, 2008), providing a quantitative comparison of gene expression across samples.

2.6. Western blot analysis

20 mg of muscle tissue samples were homogenized and lysed in RIPA buffer (Beyotime, Shanghai, China) with 1% protease inhibitor cocktail (Abmole, TX, USA) in order to extract total protein. The proteins were separated using 10% SDS-PAGE and then put onto PVDF membranes for immunoblotting. The membranes were treated with secondary antibodies conjugated with horseradish peroxidase (HRP) (Solarbio, Beijing, China) after being incubated for an entire night at 4 °C with primary antibodies against MYL10, PFN2, and PI4K2B (Solarbio, Beijing, China). To determine relative levels of protein expression, protein bands were seen using an enhanced chemiluminescence (ECL Plus) detection system (Tanon 5200), and band intensity was measured using ImageJ software.

2.7. Statistical analysis

SPSS 27.0 (IBM, Chicago, USA) was used for statistical analysis. ANOVA was used to evaluate differences in DEGs and DEPs within GO-enriched key pathways, as well as to analyze key gene validation results. Independent t-tests were conducted to assess statistical significance where applicable. Data visualizations were created using GraphPad Prism (9.0), and results are expressed as mean ± SEM. A significance threshold of P < 0.05 was applied to identify statistically significant differences across all analyzes.

3. Results

3.1. Overall statistics for transcriptomic analysis

The transcriptomic analysis generated 228,726,232 and 221,997,754 high-quality reads from CON and OS groups, respectively. Of these, 224,793,334 reads in CON and 218,472,835 reads in OS were successfully mapped to the Oar_Rambouillet_v1.0 genome, with mapping ratios of 98.28% and 98.41%, respectively. Unique mapping accounted for 85.87% in CON and 85.08% in OS. All libraries exhibited Q30% values exceeding 95.08%, confirming the high quality of sequencing data (Table S3). Gene expression correlation analysis revealed correlations above 88% across all samples (Fig. 1A), ensuring the reliability of the data for downstream analyzes. A total of 21,136 genes were identified, among which 101 DEGs were detected between OS and CON, including 66 upregulated and 35 downregulated genes (Fig. 1C). Hierarchical clustering analysis (HCA) further confirmed significant differences in gene expression profiles between the two groups (Fig. 1B, C).

Fig. 1.

Fig. 1

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The number of differentially expressed mRNAs in Group OS vs. Group CON comparisons. (A) Heat map of correlation coefficients between samples, (B) HCA of DEGs, (C) Volcano plot of DEGs, (D) GO term enrichment for DEGs in the Group OS vs. Group CON comparisons. (E) KEGG term enrichment for DEGs in the Group OS vs. Group CON comparisons. CON: Control, OS: Oat Supplemented.

GO enrichment analysis identified 568 significantly enriched GO terms (P < 0.05) among the DEGs. In the biological process category, DEGs were primarily associated with proximal/distal pattern formation, long-term synaptic potentiation, lipid metabolic process, and cell-cell adhesion. Notably, key DEGs such as LOC101104893, PTPRN2, and SLC16A11 were enriched in the lipid metabolic process term (Fig. 1D). In the molecular function category, DEGs were predominantly involved in peptide antigen binding and calcium ion binding. Key DEGs associated with calcium ion binding included CDH1, CIB4, DGKG, KCNIP1, MEGF6, MYL10, MYL6B, SCUBE3, and TPO.

KEGG enrichment analysis identified 61 significantly enriched pathways (P < 0.05) among the DEGs (Table S4). These pathways were primarily associated with the immune system, signal transduction, signaling molecules and interaction, amino acid metabolism, cell motility, transport and catabolism, nucleotide metabolism, and lipid metabolism (Fig. 1E). In the immune system category, key enriched DEGs included GNB3 and MYL10. For amino acid metabolism, TPO was the primary DEG identified. In the cell motility category, FGF10 and MYL10 were significantly enriched, while PMVK and XDH were enriched in transport and catabolism. For lipid metabolism category, DGKG and SMPD3 were the main DEGs. Among these, DGKG plays a critical role in insulin signaling and lipid metabolism.

3.2. Overall statistics for proteomics analysis

LC-MS/MS analysis generated 318,808 total spectra, leading to the identification of 59,263 spectra, 20,892 peptides, 16,562 unique polypeptides, and 2266 proteins (Fig. S1.A). Over 66% of the identified proteins contained at least two peptides, and 97.48% had a molecular mass of ≥10 kDa (Fig. S1.), confirming the high quality of the proteomic data. Additionally, 60.81% of the protein sequences exhibited coverage distributions of >10% (Fig. S1·D). Principal component analysis (PCA) revealed that components 1 and 2 accounted for 40.21% and 15.20% of the total variability, respectively, effectively separating all experimental groups and demonstrating significant diversity in protein expression profiles (Fig. 2A). A total of 202 DEPs were identified between the OS and CON groups, including 37 upregulated and 165 downregulated proteins (Fig. 2B, C).

Fig. 2.

Fig. 2

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The number of differentially expressed proteins in Group OS vs. Group CON comparisons. (A) PCA diagram. (B) Volcano plot of DEPs. (C) HCA of DEPs. (D) GO term enrichment for DEPs in the Group OS vs. Group CON comparisons. (E) KEGG term (Up) enrichment for DEPs in the Group OS vs. Group CON comparisons. CON: Control, OS: Oat Supplemented.

GO enrichment analysis identified 361 significantly enriched GO terms (P < 0.05) among the DEPs. In the biological process category, DEPs were predominantly associated with cardiac muscle contraction, cardiac myofibril assembly, cardiac muscle tissue morphogenesis, and the transition between fast and slow fibers (Fig. 2D). Key DEPs enriched in cardiac muscle contraction term included MYL2, MYL4, and CSRP3. MYL2, a member of the myosin light chain family, regulates myofiber activity, skeletal muscle growth, and contraction. Phosphorylation of MYL2 at Ser19 and Thr18 enhances ATPase activity in the myosin heavy chain, influencing myofiber type transitions and promoting muscle growth (Sheikh et al., 2015). The cysteine- and glycine-rich protein 3 gene, which encodes CSRP3, is necessary for striated muscle cell growth and development (Arber & Caroni, 1996).

DEPs enriched in cardiac myofibril assembly included MYLK2, ANKRD1, and ACTC1 (Fig. 2D). MYLK2 plays a key role in muscle fiber growth and meat yield (Li et al., 2014), while ACTC1, the primary actin isoform in embryonic hearts, is essential for cardiac development and muscle growth. Additionally, copy number variations in ACTC1 have been linked to beef production traits, such as muscle weight and feed intake (Keel et al., 2018).

DEPs associated with the transition between fast and slow fibers included ATP2A2 and TNNT1. TNNC1, encoded by TNNC1 gene, regulates cardiac and slow skeletal muscle function, contributing to sarcomere structure and the development of dilated cardiomyopathy (Pierzchala et al., 2014). DEPs were mostly involved in identical protein binding and actin monomer binding in the molecular function category. DEPs were enriched in phrases like the myosin complex, sarcoplasmic reticulum membrane, and unconventional myosin complex within the cellular component category.

KEGG enrichment analysis identified 31 significantly enriched pathways (P < 0.05) among the DEPs. These pathways included protein digestion and absorption, cardiac muscle contraction, pantothenate and CoA biosynthesis, β-alanine metabolism, tryptophan metabolism, histidine metabolism, valine, leucine, and isoleucine degradation, and FA degradation (Fig. 2E). In cardiac muscle contraction pathway, W5QFH1, encoded by the ACTC1 gene. ACTC1, was a key DEP. ACTC1 is the most abundant transverse α-actin isoform in mature hearts and plays a critical role in myocardial contractility (Pourcel et al., 2020). In pathways related to pantothenate and CoA biosynthesis and FA degradation, W5Q9L8, encoded by ALDH3 A2, was enriched. ALDH3 A2 catalyzes the oxidation of long-chain aliphatic aldehydes to FAs, supporting lipid metabolism and detoxification of aldehydes generated during lipid peroxidation (Li et al., 2019).

3.3. Correlation between transcriptome and proteome

The integrated transcriptome and proteome analysis of OS and CON groups revealed key molecular pathways and regulatory factors associated with meat quality (Fig. 3). Venn diagram analysis identified MYL10 as a common regulatory gene between the transcriptome and proteome, with its corresponding protein being W5PZ84 (Fig. 3A). PPI network analysis using the STRING database demonstrated that MYL10 gene interacts with MYLK3, MYH10, MYH9, and MYH7B, underscoring its central role in cardiac actin cytoskeletal regulation and muscle metabolism (Fig. 3B).

Fig. 3.

Fig. 3

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Correlation analysis of the DEGs and DEPs. (A) In sheep samples. (DEGs: differential expression genes, DEPs: differential expression proteins; “up” and “down” separately represent up/down-regulated expression of genes or proteins). (B) PPI analysis reveals the relationship between target DEGs and DEPs. The more lines between two genes/proteins, the greater the chance of that interaction. (C) PPI analysis showing the relationships of the target DEGs and DEPs. The size of the nodes represents the P value of the DEGs or DEPs, with a large node representing a low P value, and a small node representing a high P value. Red indicates up-regulated genes/proteins, and blue indicates down-regulated genes/proteins. More lines between two genes/proteins represents mor0e possible interactions. (D) KEGG map of cardiac muscle contraction pathway and regulation of actin cytoskeleton pathway. CON: Control, OS: Oat Supplemented. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

The cardiac contractile pathway and actin cytoskeleton regulation pathway were the primary pathways enriched by co-regulated MYL10. Proteomic analysis identified several downregulated proteins, including W5Q8N4:MYL2, W5PZ84:MYL10, W5NU05:MYLK2, W5PJD3:PIP4K2B, W5P8Y4:INSRR, W5P3G5:PFN2, and M4WDN5:TMSB4X (Fig. 3D).

STRING-based PPI network analysis of DEPs highlighted key node proteins such as ALB, ACTC1, SOD1, and MYH2. Additionally, critical node proteins at the proteomic level included W5PWE9, W5QFH1, PO9670, and W5PTO9 (Fig. 3C). Among these, W5QFH1 (encoded by ACTC1) was enriched in the cardiac contractile pathway, where it regulates myocardial contraction. Proteins such as W5QFH1:ACTC1 and EOA292:COX2 were upregulated, such as TNNC1 (A0A1L2D5U0), MYL2 (W5Q8N4), MYL4 (W5PQ67), and ATP2A2 (W5Q3Y4) were downregulated (Fig. 3D). These findings highlight the complex regulation of muscle contraction and metabolism at both the transcriptomic and proteomic levels.

3.4. Validation of RNA-seq-based key DEGs by RT-qPCR

The mRNA expression levels of five differentially expressed genes (DEGs) involved in cardiac contraction and myosin cytoskeletal assembly pathways were examined using RT-qPCR in order to validate the RNA-seq results. The veracity of the transcriptome analysis was confirmed by the RT-qPCR results, which agreed with the RNA-seq data (Fig. 4). MYL10, MYL2, and ACTC1 expression levels in the IM tissue of Small-tailed Han sheep were substantially higher in the OS group than in the CON group, by 2.57 times, 2.32 times, and 1.52 times, respectively. On the other hand, MYH2 and PIP4K2B were downregulated to 0.44 and 0.42 times the control levels, respectively (Fig. 4A). Similar expression patterns were seen in the HLM tissue, with MYL10, MYL2, and ACTC1 elevated by 2.83, 2.31, and 1.50 times, respectively, and MYH2 and PIP4K2B downregulated to 0.22 and 0.41 times, respectively, in the OS group compared to the CON group (Fig. 4B).

Fig. 4.

Fig. 4

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Validation of RNA-Seq by RT-qPCR analysis. (A) Validation of differential expression of DEGs in intercostal muscle of the Small-tailed Han sheep. (B) Validation of differential expression of DEGs in the hind leg muscle of Small-tailed Han sheep. CON: Control, OS: Oat Supplemented.

3.5. Validation of MYL10 protein expression by Western blot

Western Blot analysis was conducted to validate the protein expression levels of MYL10, PFN2, and PI4K2B in the Longissimus dorsi muscle of Small-tailed Han sheep. The results revealed that the protein levels of all three regulators were significantly downregulated in the OS group compared to the CON group (P < 0.05), consistent with the TMT proteomics data (Fig. 5). These findings confirm the reliability of the proteomic analysis and highlight the regulatory roles of these proteins in pathways associated with muscle development and meat quality.

Fig. 5.

Fig. 5

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Expression of MYL10, PFN2, and PI4K2B protein in the longissimus dorsi muscle. Note: Data are presented as mean ± standard error. Significant differences between groups are indicated (P < 0.05). Abbreviations: CON, Control; OS, Oat Supplemented.

4. Discussion

Meeting the growing demand for high-quality mutton has become a critical challenge in modern livestock farming, particularly under intensive production systems where maintaining consistent meat quality is difficult. As sheep farming continues to expand, the need for high-quality forage has risen in parallel. Dietary supplementation represents a promising strategy to improve the sensory quality and nutritional profile of mutton while reducing reliance on synthetic antibiotic feed additives (Jeon et al., 2023).

Among forage options, oat grass is widely regarded as an ideal feed for livestock due to its excellent palatability, high protein content, and digestibility (Zhang et al., 2021). Studies have demonstrated that oat grass supplementation enhances feed conversion efficiency, improves animal performance, and positively influences meat quality (Xiao et al., 2021). For instance, metabolomic analysis has shown that supplementing sheep diets with oat grass at a 7:3 ratio (dry matter: dietary supplementation) significantly increased specific metabolites and amino acids in the longissimus dorsi muscle, resulting in more nutritious meat and the accumulation of flavor-enhancing compounds (Wang et al., 2023). Despite these promising findings, the molecular mechanisms through which oat supplementation influences sheep meat quality remain to be fully elucidated. In order to close this gap, the current study uses integrated transcriptome and proteomic analysis to identify the primary molecular pathways and regulatory mechanisms that oat grass supplementation uses to affect meat quality and muscle development. By identifying these pathways, this study provides novel insights into the biological processes driving the observed improvements in mutton quality, paving the way for more targeted dietary strategies in sheep farming.

Oat grass supplementation has emerged as a promising strategy for improving sheep meat quality, as demonstrated by this study's findings, which uncover two key molecular mechanisms driving these improvements. Firstly, the cardiac contraction pathway was identified as a central regulator of intramuscular substance metabolism. This pathway facilitates the metabolism of FAs and amino acids, reducing excessive intramuscular fat (IMF) deposition and enhancing the nutritional profile of mutton. Secondly, the actin cytoskeletal regulation pathway was found to govern myofiber assembly, leading to smaller myofibril diameters, reduced muscle shear force, and improved meat tenderness. Integrating these findings with metabolomic analysis of the longissimus dorsi muscle further highlights the role of oat grass supplementation in accelerating intramuscular substance metabolism, particularly FA metabolism, while preventing excessive IMF accumulation. Collectively, these results provide molecular evidence for the ability of oat grass supplementation to improve lamb meat quality by enhancing flavor, tenderness, and overall nutritional value.

Meeting customer expectations and increasing the effectiveness of animal production systems depend on raising the quality of livestock meat. Meat quality directly influences consumer acceptance, as it determines key palatability attributes such as tenderness, juiciness, and flavor (Zhang et al., 2024). However, achieving consistent meat quality remains challenging due to its multifactorial nature, which is influenced by age, sex, genetic background, and the nutritional composition of the diet (Ma et al., 2024).

Recent studies highlight oat grass supplementation as an effective strategy to improve meat quality by modulating fatty acid composition and enhancing antioxidant activity (Su et al., 2022). For instance, in rams resulting from crossbreeding of Lesser Frosted sheep and Ujumqin sheep, feeding fermentation-mixed rations (FTMRs) supplemented with oat grass significantly increased monounsaturated fatty acid (MUFA) levels (P < 0.05), while PUFA and SFA levels remained stable (Liu et al., 2023). This improvement in fatty acid profiles contributes to healthier and more nutritionally appealing meat.

In addition to improving FA composition, oat grass supplementation positively influences intestinal flora, which plays a pivotal role in meat quality. Sheep fed oat straw exhibited a significantly higher abundance of dominant rumen bacteria compared to those fed corn stover (P < 0.05), enhancing rumen fermentation efficiency and contributing to better lamb meat performance (Sun et al., 2022). These changes in rumen microbiota are linked to improved antioxidant activity, which further supports the enhancement of meat quality.

To elucidate the molecular mechanisms by which oat grass supplementation enhances meat quality, this study employed an integrated transcriptomic and proteomic approach. RNA-seq analysis identified DEGs and their enriched pathways, while TMT-based proteomics revealed DEPs and their associated pathways. Transcriptome analysis revealed significant differences in gene expression between the OS and CON groups, which were associated with meat quality attributes including tenderness, juiciness, and flavor. With enriched pathways related to signal transduction, signaling molecule interactions, immune system functions, cellular motility, transport and catabolism, and nucleotide, lipid, and amino acid metabolism (Fig. 1E). Notably, key DEGs such as ACTC1, MYH2, and MYL10 were significantly upregulated in the OS group. These genes are functionally implicated in the regulation of myofibril formation and myocardial metabolism, processes essential for improving muscular structure and performance (Fig. 1D, Fig. 4B). MYL10 is upregulated at the transcriptional level but downregulated at the protein level (Fig. 4, Fig. 5). This process may involve post-transcriptional negative regulation. This discordance between mRNA and protein levels suggests the involvement of post-transcriptional regulatory mechanisms, such as microRNA-mediated translational repression or ubiquitin-proteasome-dependent protein degradation, which warrants further investigation. There is little literature on the post-transcriptional regulation of MYL10, so this direction could be further explored in the future. However, studies have shown that the expression of MYL10 and MYL2 is closely related to muscle fiber assembly, and a slower assembly of muscle fibers can reduce their diameter, thereby affecting shear force (Yadav & Szczesna-Cordary, 2017).

Proteomic analysis further validated these findings, revealing significant differences in protein expression between the OS and CON groups. Enriched pathways included protein digestion and uptake, myocardial contraction, pantothenic acid and CoA biosynthesis, amino acid metabolism (e.g., alanine, tryptophan, and histidine), branched-chain amino acid degradation (valine, leucine, and isoleucine), and fatty acid degradation (Fig. 2E). Key DEPs, including MLC, ACTIN, and PFN, were differentially expressed in the OS group. These proteins play critical roles in promoting intramyocardial substance metabolism and regulating myosin assembly and depolymerization, processes that are integral to muscle development and meat quality enhancement (Fig. 2D, Fig. 5).

Amino acid metabolic pathways emerged as a consistently enriched in both transcriptomic and proteomic analyzes (Fig. 2E), underscoring its critical role in shaping the flavor profile of mutton. Amino acids are key determinants of meat flavor, with distinct taste properties: sweetness-enhancing amino acids, such as alanine, serine, glycine, and proline, contribute to sweet taste, while bitter-tasting amino acids—including methionine, valine, lysine, isoleucine, phenylalanine, tyrosine, tryptophan, histidine, and arginine—impart bitterness (Ullrich et al., 2017). Additionally, sourness is influenced by glutamic acid and aspartic acid (Wong et al., 2011). In this study, oat grass supplementation was shown to modulate amino acid metabolism, promoting the accumulation of sweet-tasting alanine and the metabolism of bitter-tasting tryptophan and histidine, while degrading bitter-tasting valine and isoleucine (Fig. 2E). This selective regulation of amino acid composition enhanced the sweetness and reduced the bitterness of mutton, leading to an improved flavor profile. Moreover, the overall adjustment of amino acid content contributed to the fresh and desirable taste of mutton, emphasizing the potential of oat grass supplementation to enhance meat quality in Small-tailed Han sheep.

Integrated transcriptomic and proteomic analysis revealed that oat grass supplementation significantly elevated the expression of Actin and Cyto proteins in the longissimus dorsi muscle. These proteins are critical components of the cardiometabolic pathway (Fig. 3D), a complex process driven by excitation contraction coupling (ECC), where electrical excitation of cardiomyocytes regulates calcium ion (Ca2+) dynamics (Bers, 2008). In the OS group, the upregulation of the electron transport chain Cyto protein, particularly COX2, in the mitochondria facilitated the exchange of H+, Na+, and Ca2+ ions. This process promoted the release of Ca2+ from the mitochondria into the cytoplasm, enhancing intracellular calcium signaling. Simultaneously, the downregulation of the SERCA enzyme (ATP2A2) on the sarcoplasmic reticulum inhibited the reuptake of Ca2+ from the cytoplasm, leading to sustained cytoplasmic Ca2+ levels. Additionally, Actin expression (ACTC1) was significantly upregulated, while the expression of myosin-related proteins (MYL2 and MYL4) and the Ca2+-binding troponin C subunit (TNNC1) were downregulated. These coordinated changes in protein expression suggest a regulated modulation of calcium-dependent muscle contraction and myofibril architecture. Despite the downregulation of specific proteins, the overall cardiometabolic pathway was significantly upregulated (P < 0.05), highlighting the role of oat grass supplementation in modulating calcium signaling and muscle function.

Intramyocardial FA metabolism is closely linked to myocardial contractile function. Excessive accumulation of long-chain FAs can lead to inappropriate activation of peroxisome proliferator-activated receptor alpha (PPARα), which may subsequently disrupt the expression of cardiac contractile proteins (Sharma et al., 2004). ACTC1 expression has been shown to regulate muscle development and lipid deposition in Qinchuan cattle (Mei et al., 2020). The findings of this study align with these observations, demonstrating that oat grass supplementation enhanced muscle contraction metabolism, improved FA metabolism, and reduced excessive fat deposition in sheep. Metabolic data further supported these results, showing that the GR value of the longissimus dorsi muscle was significantly reduced in the OS group, indicating improved growth performance, reduced subcutaneous fat deposition, and enhanced FA metabolism (Wang et al., 2023). These results highlight the potential of oat grass supplementation to optimize muscle growth and fat distribution, contributing to improved overall meat quality in sheep.

The study revealed that oat grass supplementation upregulated the expression of ACTC1 and COX2, promoting FA metabolism through the cardiac muscle contraction pathway. These findings underscore the role of oat grass in modulating molecular pathways critical for muscle metabolism and overall meat quality. Integrative Venn analysis of transcriptomic and proteomic data further highlighted the regulatory role of MYL10 (encoding MLC protein) in the myosin cytoskeletal regulatory pathway, a key determinant of meat tenderness. MYL10, a member of the myosin light chain family, is essential for maintaining myofiber activity and structural integrity (Zhang et al., 2015). Additionally, the study identified MYH10 as a critical node factor in muscle fiber regulation. This gene is closely associated with muscle development, differentiation, and fiber composition, further emphasizing its importance in muscle-related functional pathways (Zhuang et al., 2020).

Tenderness, a critical determinant of overall meat quality, profoundly influences the sensory experience and consumer acceptance of meat products. This key attribute is directly associated with muscle shear force, a parameter that reflects the structural and metabolic properties of muscle fibers. This study demonstrated that oat grass supplementation enhances lamb meat tenderness by modulating the expression of key genes and proteins involved in muscle fiber structure and FA metabolism, including MYH10, ACTC1, and COX2. These molecular changes collectively promote FA metabolism, regulate muscle contraction through the cardiometabolic pathway, reduce excessive fat deposition, and improve meat tenderness via the myosin cytoskeletal regulatory pathway.

Tenderness is influenced by a combination of factors, including IMF, moisture content, and the structure and density of muscle fibers. Previous studies have shown that finer muscle fibers contribute to improved meat texture and taste (Zhao et al., 2022). Supplementation with oat-based diets in beef cattle has been shown to enhance muscle tenderness and improve overall beef palatability, primarily through increasing muscle fiber density and reducing fiber cross-sectional area (Li et al., 2023). Similarly, the findings of this study revealed that oat grass supplementation improved lamb meat tenderness, with the myosin cytoskeletal regulatory pathway identified as the primary mechanism underlying these improvements.

The improvement in meat tenderness involves the regulation of key signaling pathways and proteins associated with muscle fiber structure, contraction, and cytoskeletal dynamics. This study revealed that oat grass supplementation influenced the expression of several critical genes and proteins, leading to structural and functional changes in muscle fibers. Co-analysis results indicated the downregulation of receptor tyrosine kinases (RTKs, involving INSRR), which reduced the reception of extracellular signaling molecules involved in muscle fiber remodeling. Additionally, the expression of myosin light chain kinases (MLCK, encoded by MYLK2) and myosin light chain proteins (MLC, encoded by MYL10 and MYL2) was downregulated, resulting in decreased type II myosin expression and reduced actin cytoskeletal assembly. These changes are closely linked to alterations in muscle contraction and fiber morphology.

Additionally, the release of phosphatidylinositol 4,5-bisphosphate (PIP2) molecules was inhibited by the downregulation of phosphatidylinositol-4-phosphate 5-kinase (PI4P5K, encoded by PIP4K2B), which disrupted focal complex assembly and weakened the link between the intracellular cytoskeleton and the extracellular matrix. This disruption impaired cell migration and the establishment of myofibril morphology, critical processes for maintaining muscle fiber integrity. Similarly, the study identified the downregulation of actin-binding proteins such as PFN2 (profilin) and TMSB4 (actin-chelating protein, involving TMSB4X), which inhibited actin polymerization. This reduction in actin filament formation resulted in smaller muscle fiber cross-sectional areas, directly contributing to improved tenderness by reducing muscle fiber density and rigidity.

Meat tenderness is strongly influenced by the structural dynamics of myofibrils, particularly their assembly and contraction. During cooking, the thermal denaturation of myofibrillar proteins increases contraction, reduces water-holding capacity, and increases connective tissue tension, which collectively result in higher shear force and reduced tenderness (Xiao et al., 2025). In contrast, this study demonstrated that oat grass supplementation positively modulated myofiber assembly and morphology, leading to reduced muscle shear force and improved lamb tenderness. Specifically, the downregulation of MLC protein expression altered myofibril structure, contributing to a reduction in muscle fiber cross-sectional area. These structural modifications enhance lamb tenderness and improve its sensory quality by reducing muscle fiber density and rigidity.

5. Conclusions

This study highlights the significant potential of oat grass supplementation as a dietary strategy to enhance the meat quality of Small-tailed Han sheep. By promoting muscle metabolism, reducing fat deposition, improving tenderness, and enriching flavor, oat grass supplementation addresses key factors influencing both the sensory and nutritional properties of lamb meat. Integrated transcriptomic and proteomic analyzes identified MYL10 and W5QFH1 as critical regulators underlying these improvements. MYL10 modulates the myosin cytoskeleton, reducing myofiber diameter and enhancing tenderness, while W5QFH1 regulates cardiac muscle contraction, supporting muscle metabolism and minimizing fat accumulation. Furthermore, oat grass supplementation altered the profile of flavor-related amino acids, reducing bitter-tasting amino acids and increasing those associated with sweetness and umami, thus improving the overall flavor of lamb. These findings not only demonstrate the practical benefits of oat grass supplementation but also provide a foundation for the development of sustainable, forage-based feeding systems in sheep farming.

CRediT authorship contribution statement

Li-Wei Wang: Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization. Jian-Qiang Li: Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization. Jiang-Hong An: Validation. Hua Sun: Visualization. Fang Liu: Visualization. Meng-Ran Zhao: Methodology. Li-Li Jiang: Methodology. Xing-Ran Dong: Software. Sarula Tao: Investigation. Mengke Bayaer: Investigation. Jiang-Feng He: Writing – review & editing, Supervision, Project administration, Funding acquisition, Conceptualization. Yong-Bin Liu: Writing – review & editing, Supervision, Project administration, Funding acquisition, Conceptualization.

Ethics statement

The Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences' Animal Care and Use Committee in Hohhot, China, approved all sheep-related experiments (permission number. 2022003).

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Declaration of generative AI in scientific writing.

Neither generative artificial intelligence (AI) nor AI-assisted technologies were employed by the writers during the writing process.

Acknowledgment

This work was supported by the Natural Science Foundation of the Inner Mongolia Autonomous Region (2023QN03019), the Ordos Major Science & Technology Project (ZD20232314), and the Scientific Research Start-up Fund for Introduced High-level Talents (Li-wei Wang). Support was also received from the National Technology System for Mutton Sheep Production (CARS-38). Funding was obtained from the following sources: the Inner Mongolia Joint Breeding Research Project for Sheep (YZ2023011), the Inner Mongolia Mutton Sheep Industry Technology System, and the Inner Mongolia Science and Technology Project “Open Competition for Leading Projects” (2022JBGS0012, 2022JBGS0024).

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.fochms.2026.100362.

Contributor Information

Jiang-Feng He, Email: 13704781032@163.com.

Yong-Bin Liu, Email: ybliu117@126.com.

Appendix A. Supplementary data

Supplementary material 1

Fig. S1 Identification and quantitative evaluation of proteins and the number of differentially abundant proteins in (control/experiment) Group OS vs. Group CON comparisons.

mmc1.docx (226KB, docx)
Supplementary material 2

Table S1 Ingredient composition and nutritional levels of the experimental diets.

mmc2.docx (12.5KB, docx)
Supplementary material 3

Table S2 Parameters of primer pairs used for RT-qPCR.

mmc3.docx (14.5KB, docx)
Supplementary material 4

Table S3 Genome map Rate.

mmc4.docx (17KB, docx)
Supplementary material 5

Table S4 Significantly enriched GO terms and KEGG identified by RNA-Seq analysis.

mmc5.xlsx (53.1KB, xlsx)

Data availability

Data will be made available on request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary material 1

Fig. S1 Identification and quantitative evaluation of proteins and the number of differentially abundant proteins in (control/experiment) Group OS vs. Group CON comparisons.

mmc1.docx (226KB, docx)
Supplementary material 2

Table S1 Ingredient composition and nutritional levels of the experimental diets.

mmc2.docx (12.5KB, docx)
Supplementary material 3

Table S2 Parameters of primer pairs used for RT-qPCR.

mmc3.docx (14.5KB, docx)
Supplementary material 4

Table S3 Genome map Rate.

mmc4.docx (17KB, docx)
Supplementary material 5

Table S4 Significantly enriched GO terms and KEGG identified by RNA-Seq analysis.

mmc5.xlsx (53.1KB, xlsx)

Data Availability Statement

Data will be made available on request.

Articles from Food Chemistry: Molecular Sciences are provided here courtesy of Elsevier

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