Next Article in Journal
Intestinal Microbiota of Commercial Laying Hens in a Cage-Free System Fed with Probiotics
Previous Article in Journal
Rumen-Protected Methionine Supplementation in the Diet Improved the Production Performance of Dairy Goats by Optimizing the Amino Acid Profile and Lipid Metabolism and Modulating the Colonic Microbiome
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Animals
Volume 15
Issue 23
10.3390/ani15233387
animals-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of MSTN Gene Knockout on Growth Performance and Muscle Transcriptome in Chinese Merino Sheep (Xinjiang Type)

by
Li Zhang
1,2,
Pengfei Li
1,2,
Xu Wang
1,2,
Menghua Kong
1,2,
Weiwei Wu
2,* and
Wenxin Zheng
1,*
1
College of Animal Science, Xinjiang Agricultural University, Urumqi 830091, China
2
Institute of Animal Husbandry, Xinjiang Academy of Animal Science, Urumqi 830009, China
*
Authors to whom correspondence should be addressed.
Animals 2025, 15(23), 3387; https://doi.org/10.3390/ani15233387
Submission received: 4 November 2025 / Revised: 18 November 2025 / Accepted: 20 November 2025 / Published: 24 November 2025
(This article belongs to the Section Animal Genetics and Genomics)
Browse Figures
Review Reports Versions Notes

Simple Summary

Myostatin (MSTN) is a key regulator of muscle development in animals, and its knockout has been shown to significantly enhance growth performance. In this study, MSTN knockout Chinese Merino sheep (Xinjiang type) were used to assess the effects of MSTN deletion on growth performance and the underlying molecular mechanisms. The results demonstrated that MSTN knockout significantly increased body weight, body length, and height, with no adverse effects on hematological or metabolic functions. Transcriptomic analysis identified 121 differentially expressed genes (DEGs), which were involved in critical pathways such as amino acid metabolism, muscle contraction, and immune response. A protein–protein interaction (PPI) network was constructed, revealing 10 key genes that may play pivotal roles in MSTN gene regulation. This study provides valuable theoretical support for gene editing in meat sheep breeding, with substantial practical implications.

Abstract

The MSTN gene plays a critical role in muscle development, and its knockout has been shown to significantly enhance growth performance in animals. In this study, we utilized MSTN knockout Chinese Merino sheep (Xinjiang type), which were previously generated in our laboratory, to compare their growth performance, hematological, and biochemical parameters with those of a control group. The results revealed that the MSTN knockout sheep exhibited significantly improved traits, including body weight, body length, and body height, without adverse effects on blood or metabolic parameters. Transcriptomic analysis identified 121 differentially expressed genes (DEGs) involved in key pathways such as amino acid metabolism, muscle contraction, and immune response. A protein–protein interaction (PPI) network was constructed, highlighting 10 core genes that may play pivotal roles in the biological processes regulated by MSTN. RT-qPCR validation of several key genes confirmed the results of the transcriptomic analysis. This study provides both theoretical foundations and practical insights for gene-edited breeding in meat sheep.

1. Introduction

Myostatin, also known as Growth Differentiation Factor 8 (GDF8), is a member of the transforming growth factor-beta (TGF-β) superfamily and functions as a negative regulator of skeletal muscle development, playing a critical role in the growth and development of animals [1]. MSTN regulates muscle development by inhibiting the proliferation and differentiation of skeletal muscle satellite cells. Its deletion or functional defects result in significant muscle hypertrophy, leading to a characteristic “Double-Muscling” phenotype [2]. Studies have shown that MSTN is highly conserved across various livestock species, including cattle [3], sheep [4], pigs [5], and rabbits [6]. Mutations or knockout of MSTN have been shown to significantly improve meat production traits, emphasizing its potential in livestock genetic improvement and the enhancement of production performance.
With the advancement of molecular biology and genetic engineering, next-generation gene editing tools have enabled the targeted improvement of large animals. Among these tools, CRISPR/Cas-based systems have become key for livestock genetic enhancement due to their efficiency, precision, and flexibility [7]. In recent years, researchers have successfully achieved effective MSTN gene knockout in economically important animals such as pigs and sheep using CRISPR/Cas9, Cpf1, and Prime Editing technologies. These edits have resulted in increased muscle deposition and accelerated growth in the edited individuals [8,9,10]. These findings not only validate the feasibility of MSTN-directed genetic improvement for enhancing meat production traits but also offer new perspectives for molecular breeding in livestock. However, existing studies primarily focus on phenotypic growth traits [11], with limited systematic investigation at the hematological and transcriptomic levels. In particular, research on the molecular mechanisms underlying MSTN-edited sheep, a dual-purpose species for wool and meat, remains insufficient [12]. This gap has hindered the comprehensive application and wider adoption of these findings.
The Chinese Merino sheep (Xinjiang type) is a key breed in the northern pastoral regions of China, renowned for its high-quality fine wool and meat production potential. However, its growth rate and meat production performance are relatively limited [13]. Enhancing skeletal muscle deposition and increasing muscle mass through MSTN-directed breeding offers promising opportunities for the genetic improvement of this breed, providing both theoretical and practical value [14]. Building on this premise, this study utilized an optimized hfCas12Max-T5_sheep gene editing system, which has demonstrated high editing efficiency and accuracy in both sheep cells and individuals [15]. By employing MSTN knockout Chinese Merino sheep, this study systematically compared differences in growth performance, hematological indicators, and muscle transcriptome between the edited and control groups. The objective was to investigate the impact of MSTN knockout on sheep growth, development, and molecular regulatory mechanisms, thereby providing theoretical support and practical insights for gene editing in meat sheep breeding [16].

2. Materials and Methods

2.1. Experimental Animals and Housing Conditions

The animals used in this experiment were sourced from the Qitai Sheep Breeding Farm in Xinjiang. A total of 100 Chinese Merino sheep (Xinjiang type) were selected, comprising 50 MSTN gene-edited sheep (MT) and 50 wild-type control sheep (WT). The sheep were matched for sex and age, and all individuals were in good health. The gene-edited sheep were generated using T7-hfCas12Max-T5_sheep plasmid construction and embryo microinjection techniques. Successful knockout of the target site was confirmed by PCR, Sanger sequencing, and deep-targeted sequencing. The genotype distribution was as follows: among the 50 individuals in the MT group, 32 were homozygous mutants (64%) and 18 were heterozygous mutants (36%). No chimeric individuals were detected, and the mutations consisted of base substitutions or deletions.
All 100 Chinese Merino sheep (Xinjiang type) selected for this experiment were of the same generation and half-siblings, sharing the same sire but different dams, ensuring a consistent genetic background. The male-to-female ratio was 1:1 in both groups, with 25 rams and 25 ewes in each group. All individuals were intact (non-castrated). The ewes used for reproduction were primiparous, and all lambs were single-born, ensuring a consistent early growth environment for both groups and minimizing potential confounding effects.
The sheep were all raised on the same farm from birth under identical management conditions. During the lactation period, the lambs were exclusively fed by their mothers. From 28 days of age, supplementary feeding commenced, and after weaning, the lambs were fed a uniform formula total mixed ration (TMR) with unrestricted access to water. Throughout the experimental period, both groups of sheep were raised in the same environment with identical diets and management practices to ensure the scientific validity and comparability of the results. All sampling and handling procedures adhered strictly to ethical guidelines for animal experiments, ensuring the welfare of the animals.

2.2. Growth Performance Measurement

Growth performance was assessed at eight time points: birth, 30 days, 60 days, 90 days, 120 days, 160 days, 190 days, and 365 days. The traits measured included body weight (kg), withers height (cm), body length (cm), chest girth (cm), cannon circumference (cm), and hip width (cm). Body weight was recorded using an electronic scale to ensure precise measurements, while body dimensions were taken by a single trained operator to minimize inter-observer variability. All measurements were performed in the morning, prior to feeding, to ensure consistency and accuracy across time points.

2.3. Blood Sample Collection and Analysis

Blood samples were collected in both heparinized and non-heparinized tubes. The non-heparinized blood was allowed to stand at room temperature to facilitate serum separation, then centrifuged at 3000 rpm for 10 min at 4 °C. The serum was carefully collected and transferred to a 2 mL sterile centrifuge tube. Both serum and heparinized whole blood samples were then sent to Zhongchu Animal Hospital in Urumqi, Xinjiang, for analysis. Hematological analysis was conducted using an automatic veterinary hematology analyzer (AL-90Vet, High Technology Inc., Beijing, China), which provided 46 hematological parameters. Serum biochemical analysis was carried out using an automatic dry chemistry analyzer (Seamaty Minilab VET, Chengdu Seamaty Technology Co., Ltd., Chengdu, China), yielding 24 serum biochemical parameters.

2.4. Muscle Tissue RNA Extraction, Transcriptome Library Construction, and Sequencing

Muscle tissue from the same region of the hind limbs was collected from 3 MSTN-edited Chinese Merino sheep (Xinjiang type) and 3 wild-type Chinese Merino sheep (Xinjiang type) using in vivo sampling techniques. The samples were immediately stored in liquid nitrogen. Total RNA was extracted using the TRIzol method (Thermo Fisher Scientific, Waltham, MA, USA), and RNA concentration and purity were measured with a NanoDrop 2000 spectrophotometer (Thermo Scientific, Waltham, MA, USA). RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
Transcriptome libraries were constructed with the VAHTS Universal V10 RNA-seq Library Prep Kit (Premixed Version) following the manufacturer’s instructions. Library sequencing was performed by Shanghai OE Biotech Co., Ltd. (Shanghai, China) using the Illumina NovaSeq 6000 sequencing platform with 150 bp paired-end sequencing. Following quality control using fastp software (v0.23.4), the sequencing data were aligned to the sheep reference genome (ARS-UI_Ramb_v2.0) with HISAT2 software (v2.2.1), and gene expression levels (FPKM) were calculated. Read counts were obtained using HTSeq-count (v2.0.5).

2.5. Identification of Differentially Expressed Genes and Functional Enrichment Analysis

Principal component analysis (PCA) and plotting were performed using R (v3.2.0) to evaluate the biological reproducibility of the samples. Differentially expressed genes (DEGs) were identified using DESeq2 (v1.40.2), with thresholds set to padj < 0.05 and |log2FoldChange| > 1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the DEGs. Volcano plots were generated using the R package ggplot2 to visualize the upregulated and downregulated gene expression changes. Additionally, enrichment circle plots were created to display significantly enriched functional terms.

2.6. Protein–Protein Interaction Network Construction

To investigate potential interactions between proteins encoded by the differentially expressed genes (DEGs), a protein–protein interaction (PPI) network was constructed using DEGs with padj < 0.05 and |log2FoldChange| ≥ 1. The corresponding genes of the DEGs were first converted to UniProt or Ensembl protein IDs, and protein interaction data were retrieved from the STRING database (v11.5, https://string-db.org, accessed on 6 August 2025), retaining only high-confidence interactions (confidence score ≥ 0.7). The interaction data were then imported into Cytoscape (v3.9.1) to construct the PPI network. Network topology metrics were calculated using the Network Analyzer tool to identify hub proteins. Core modules within the network were further identified using the MCODE plugin. GO and KEGG enrichment analyses were conducted on the proteins within these modules to elucidate the potential roles of the DEGs in key biological processes. This approach visually presents the interaction relationships and functional characteristics of DEG-encoded proteins, offering valuable insights for subsequent mechanistic studies.

2.7. Real-Time Quantitative PCR (RT-qPCR) Validation

To validate the RNA-Seq differential expression results, total RNA was extracted from the same batch of muscle samples using the TRIzol method (Thermo Fisher Scientific, Waltham, MA, USA), and RNA purity and concentration were assessed using the NanoDrop 2000. Genomic DNA was removed, and cDNA was synthesized using the PrimeScript™ RT Reagent Kit (Takara Bio Inc., Kusatsu, Shiga, Japan). RT-qPCR was performed using the SYBR Green method on the QuantStudio 6 Flex real-time PCR system (Thermo Fisher Scientific, Waltham, MA, USA). Primers for target and housekeeping genes were designed to span exon-exon junctions to ensure specificity. Each sample was measured in triplicate, and reactions were carried out according to the manufacturer’s recommended conditions. Relative gene expression levels were calculated using the 2−ΔΔCT method, with significance determined at p < 0.05.

3. Results

3.1. Effects of MSTN Knockout on Body Weight and Body Measurements

To systematically assess the impact of MSTN gene editing on the growth and development of sheep, this study conducted dynamic monitoring of body weight and body measurements from birth to 365 days of age in both MT and WT groups. At birth, the MT group had a significantly higher weight of 3.98 ± 1.00 kg compared to the WT group, which weighed 3.47 ± 0.77 kg (p < 0.05). At 30, 120, and 160 days of age, the MT group exhibited significantly greater body weight, body length, body height, chest girth, cannon circumference, and hip width (p < 0.05), indicating faster growth and skeletal development. At 60 days of age, the MT group showed significantly higher body weight, body length, body height, and hip width compared to the WT group (p < 0.05), while no significant differences were observed in chest girth and cannon circumference (p > 0.05). By 90, 190, and 365 days of age, the MT group continued to show significantly higher body weight, body length, body height, chest girth, and hip width compared to the WT group (p < 0.05), with no significant difference in cannon circumference (p > 0.05) (Table 1). These results demonstrate that MSTN gene knockout significantly promotes early growth and development in sheep, particularly in terms of muscle mass accumulation and skeletal traits, highlighting its important application in accelerating meat sheep breeding and enhancing production performance.

3.2. Effects of MSTN Gene Editing on Hematological and Serum Biochemical Parameters in Sheep

To assess the potential impact of MSTN gene editing on the health status of sheep, this study analyzed the hematological and serum biochemical parameters in both the experimental (MT) and control (WT) groups. There were no significant differences between the MT and WT groups in terms of hematological parameters, including white blood cell count, absolute neutrophil count, absolute lymphocyte count, red blood cell count, hemoglobin concentration, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin concentration, platelet count, and mean platelet volume (p > 0.05) (Table 2). Other hematological indicators are presented in Supplementary Table S1. Regarding serum biochemical parameters, no significant differences were observed between the experimental and control groups in albumin, total protein, albumin/globulin ratio, aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, creatine kinase, creatinine, urea, glucose, total cholesterol, triglycerides, and calcium concentration (p > 0.05) (Table 3). Other serum biochemical indicators are shown in Supplementary Table S2. In conclusion, MSTN gene-edited sheep exhibited normal hematological and serum biochemical parameters with no significant differences compared to the control group, indicating that gene editing did not cause any notable adverse effects on their health or metabolic functions.

3.3. Statistical Analysis of Sequencing Data

RNA-Seq was performed on six samples, generating approximately 284 million raw paired-end 150 bp reads, with an average of 47.1 million reads per sample. A total of 41.44 GB of clean data was obtained, with the effective data volume for each sample ranging from 6.78 to 7.06 GB. After quality control using fastp software, each sample retained approximately 46.47 million high-quality clean reads, with the proportion of valid bases exceeding 96.99%. The Q30 base percentage of clean reads ranged from 96.69% to 96.97%, indicating high sequencing data quality. The GC content of the samples ranged from 55.83% to 56.68%, which is consistent with the expected GC distribution of the sheep genome. Subsequent alignment of the clean reads to the sheep reference genome (ARS-UI_Ramb_v2.0) resulted in a total alignment rate of 97.83% to 99.06%, with correctly paired reads accounting for 91.80% to 92.87%, reflecting good alignment efficiency and suitability for the reference genome (Table 4). Additional data quality control results are presented in Supplementary Tables S3 and S4. In conclusion, the RNA-Seq data obtained are of reliable quality and meet the requirements for subsequent differential expression analysis and functional annotation.

3.4. Sample Correlation Analysis

To evaluate the overall consistency and reproducibility between sequencing samples, Pearson correlation coefficients were calculated for the normalized gene expression matrix (FPKM) of each sample (Supplementary Table S5), and a correlation heatmap was generated. The correlation coefficients (R2) between samples within the same group were all above 0.86, significantly higher than those between different groups (Figure 1A), indicating good internal consistency among biological replicates and reliable data quality, which meets the requirements for subsequent differential expression analysis. Furthermore, principal component analysis (PCA) showed clear clustering separation of samples from different experimental groups along the first and second principal components (Figure 1B), further supporting the existence of inter-group differences and the stability of intra-group replicates.

3.5. Differential Gene Screening

A total of 121 differentially expressed genes (DEGs) were identified, with 54 genes showing upregulation and 67 genes showing downregulation (|log2 Foldchange| ≥ 1, padj < 0.05) (Figure 2, Supplementary Table S6). The distribution of these DEGs was relatively uniform, with distinct trends of upregulation and downregulation, indicating significant transcriptional differences between the MT and WT groups in muscle tissue. These findings suggest that the identified DEGs may be closely linked to biological processes such as muscle growth regulation, metabolic pathways, and cell signaling mechanisms induced by MSTN gene knockout. This provides a solid data foundation for subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses.

3.6. GO and KEGG Functional Enrichment of Differentially Expressed Genes

Based on the identified differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted to further explore their potential biological functions and associated signaling pathways. The GO enrichment results revealed that, at the biological process (BP) level, the DEGs were predominantly enriched in the negative regulation of oxidative phosphorylation (GO:0090324), RNA polymerase II-mediated transcription (GO:0006357), the urea cycle (GO:0000050), calcium ion transmembrane transport (GO:0070588), and ischemic response (GO:0002931). At the cellular component (CC) level, the DEGs were mainly localized to the sarcolemma (GO:0042383). At the molecular function (MF) level, DEGs were significantly involved in oxidoreductase activity (GO:0016491) (Figure 3A, Detailed FDR values and gene counts refer to Supplementary Table S7). These results suggest that MSTN knockout may affect skeletal muscle development and physiological function by regulating energy metabolism, ion homeostasis, and stress responses.
KEGG pathway analysis further demonstrated that the DEGs were significantly enriched in metabolic pathways related to arginine biosynthesis (oas00220), amino acid biosynthesis (oas01230), and cysteine and methionine metabolism (oas00270). Additionally, DEGs were involved in pathways related to reactive oxygen species (ROS)-mediated chemical carcinogenesis (oas05208), muscle cell cytoskeleton structure (oas04820), and overall metabolic pathways (oas01100) (Figure 3B, Detailed FDR values and gene counts refer to Supplementary Table S8). These findings indicate that MSTN knockout may not only provide the energy and material basis for muscle growth through amino acid metabolism and redox reactions but also regulate skeletal muscle structure and function through cytoskeletal remodeling and stress response. This provides a theoretical basis for further elucidating the molecular mechanisms and identifying key targets for future studies.

3.7. Protein–Protein Interaction Network Construction and Analysis

Based on the 121 differentially expressed genes (DEGs) identified in this study, a protein–protein interaction (PPI) network was constructed using the STRING database, and visualized and modularized in Cytoscape. The initial network contained 107 nodes (including isolated nodes). To improve the clarity of the network, 63 isolated nodes that did not interact with other proteins were removed, resulting in a high-confidence interaction network consisting of 44 nodes and 57 interaction edges. Network topology analysis revealed that the PPI network could be divided into three relatively independent functional modules (Figure 4A–C): Module 1 was primarily enriched in amino acid metabolism and mitochondrial-related proteins; Module 2 focused on muscle contraction, excitation-contraction coupling, and ion channel-related proteins; Module 3 was enriched in interferon-mediated antiviral response-related proteins.
Furthermore, using the Cytoscape plugin cytoHubba and sorting nodes by their Degree values, the top 10 hub genes with the highest connectivity in the network were identified, including IRF7 (Interferon Regulatory Factor 7), ISG15 (Interferon-Stimulated Gene 15), CACNA1S (Calcium Voltage-Gated Channel Subunit Alpha1 S), MX1 (MX Dynamin-Like GTPase 1), RSAD2 (Radical S-Adenosyl Methionine Domain Containing 2), GOT1 (Glutamic-Oxaloacetic Transaminase 1), CLCN1 (Chloride Voltage-Gated Channel 1), RYR1 (Ryanodine Receptor 1), EIF2AK2 (Eukaryotic Translation Initiation Factor 2 Alpha Kinase 2), and MX2 (MX Dynamin-Like GTPase 2). These genes are located at the core of the network and are likely to play crucial roles in the biological processes regulated by MSTN, providing potential candidate targets for further molecular mechanism exploration and functional validation.

3.8. RT-qPCR Validation

To systematically verify the reliability and accuracy of the transcriptome sequencing data, four key candidate genes (ACTN3, RYR1, MX1, IRF7) were randomly selected from the screened differentially expressed genes (DEGs) for validation by quantitative real-time PCR (RT-qPCR) (Figure 5), with primer sequences provided in Supplementary Table S9. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as the reference gene to eliminate systematic variations in RNA extraction efficiency, reverse transcription efficiency, and PCR amplification efficiency among samples. Each candidate gene was set with 3 biological replicates (exactly consistent with the transcriptome sequencing samples: 3 MSTN knockout sheep and 3 wild-type sheep), and each biological replicate was subjected to 3 technical replicates to ensure the reproducibility and robustness of the experimental results. Determined by the standard curve method, the PCR amplification efficiencies of all candidate genes and the reference gene ranged from 95% to 105%, an ideal range, as follows: ACTN3 (97.3%), RYR1 (98.6%), MX1 (101.2%), IRF7 (96.8%), and GAPDH (100.5%). Melting curve analysis showed that all primers exhibited a single sharp peak without non-specific peaks or primer dimers, confirming good primer specificity. The relative expression levels of the candidate genes were calculated using the 2−ΔΔCt method. The results indicated that the expression trends and relative fold changes of the four candidate genes between the MSTN knockout group and the wild-type group were consistent with the transcriptome sequencing data. These findings fully confirm the reliability, accuracy, and biological authenticity of the transcriptome sequencing data in this study.

4. Discussion

MSTN knockout significantly enhanced the growth performance of Chinese Merino sheep (Xinjiang type). Body weight and body measurements (e.g., body length, body height, chest circumference, and rump width) were significantly superior to those of the control group across multiple growth stages. This was particularly evident for traits that directly reflect skeletal muscle deposition and individual development, such as body length, body height, chest circumference, and rump width [17,18]. These advantages persisted from birth through 365 days of age. Consistent with findings from MSTN editing studies in cattle, pigs, goats, and other livestock, these results confirm the cross-species conservation of MSTN as a negative regulator of skeletal muscle growth [19,20]. The core mechanism involves the loss of MSTN, which alleviates the inhibition of skeletal muscle satellite cell proliferation and differentiation, resulting in increased muscle fiber number and diameter. This may also synergistically promote bone growth, ultimately contributing to the simultaneous improvement of body weight and body measurements [21]. This sustained growth advantage indicates that MSTN knockout not only optimizes early muscle deposition but also supports continued performance enhancement throughout the entire growth cycle, providing a solid theoretical foundation for long-term improvement in meat sheep breeding.
Carcass traits are key evaluation indicators for the production efficiency of meat sheep. The positive effects of MSTN knockout on carcass performance have been widely validated across various livestock species, providing valuable references for the application prospects of the breed in this study. In studies on goats and sheep, MSTN deficiency significantly increased dressing percentage and net meat percentage, with a 15–25% increase in longissimus dorsi muscle area [22]. These improvements are strongly correlated with the significant gains in body length, chest circumference, and other body measurements observed in this study. Given the sustained muscle growth advantage of MSTN-edited sheep, it is hypothesized that their lean meat production efficiency post-slaughter will be significantly enhanced, and key carcass indicators, such as longissimus dorsi muscle area, are expected to show similar improvements.
Regarding fat deposition, MSTN knockout has been shown to preferentially direct nutrient allocation to skeletal muscle, reducing the proportion of subcutaneous and visceral fat [23]. For example, MSTN knockout models in pigs exhibit high-quality carcass characteristics, including optimal intramuscular fat content and reduced backfat thickness [24]. This trait is particularly relevant for Chinese Merino sheep (Xinjiang type), a dual-purpose breed for both wool and meat. Moderately reducing fat deposition can improve lean meat percentage, aligning with market demands for high-quality lean meat. However, it is crucial to strike a balance in fat deposition to prevent potential adverse effects on meat quality due to excessive reduction in intramuscular fat content. The activation of amino acid metabolism pathways, as revealed in the transcriptomic analysis of this study, may help optimize nutrient allocation, maintaining a reasonable level of intramuscular fat while enhancing lean meat percentage. This provides potential for the coordinated improvement of carcass quality, contributing to the overall optimization of meat production traits.
Meat quality (including meat color, tenderness, flavor, and juiciness) is a central consideration in breeding practices, and the impact of MSTN knockout on meat quality exhibits species-specific variation. Existing studies have shown that MSTN knockout sheep display reduced shear force in the longissimus dorsi muscle, with no significant change in intramuscular fat content, while maintaining high-quality meat color. In this study, the observed improvement in tenderness may be linked to the differential expression of key genes in the calcium signaling pathway, such as RYR1 and CACNA1S. As a sarcoplasmic reticulum calcium release channel gene, changes in RYR1 expression can influence calcium ion recovery efficiency following muscle contraction, thereby improving muscle tenderness [25]. Additionally, the activation of amino acid metabolism pathways may provide precursors for the synthesis of flavor compounds, such as glutamic acid and inosinic acid [26], which could enhance meat flavor. However, potential risks should be carefully considered. In some species, MSTN knockout has been shown to cause excessively large muscle fiber diameters, which may negatively affect meat tenderness [27]. Moreover, if intramuscular fat content is too low, it could impair the juiciness and flavor balance of the meat [28]. Therefore, further verification is needed for this breed. Subsequent studies should systematically assess shear force, meat color (Lab* values), intramuscular fat content, fatty acid composition, and flavor metabolic profiles in MSTN-edited sheep. This comprehensive evaluation will help clarify the overall impact of gene editing on meat quality and provide robust support for breeding applications.
The blood routine and serum biochemical indicators of MSTN-edited sheep were within the normal range, showing no significant differences from the control group. Consistent with studies on pigs [29], these findings suggest that gene editing did not cause adverse effects on hematopoietic function, immune homeostasis, or liver and kidney metabolism, effectively achieving precise improvement of target traits [30]. Some indicators, such as creatine kinase and lactate dehydrogenase, were slightly elevated in the edited group, which may be related to enhanced muscle metabolism and increased energy consumption [31]. MSTN knockout may be associated with a mild increase in metabolic load while promoting muscle hypertrophy, a phenomenon confirmed in studies on double-gene-edited sheep [32]. Overall, the stability of hematological and biochemical indicators provides important support for the safety of MSTN gene editing technology.
At the molecular level, transcriptomic analysis revealed significant changes in 121 differentially expressed genes (DEGs), which were involved in several biological processes, including amino acid metabolism, muscle contraction, and immune response. Amino acid metabolism is a central process in skeletal muscle synthesis and energy supply. The upregulation of related genes suggests that MSTN deficiency may enhance amino acid uptake and utilization, thereby providing more substrates and energy support for muscle tissue [33]. Previous studies have shown that MSTN-deficient animals generally exhibit higher protein deposition efficiency and nitrogen deposition rate, consistent with the findings of this study [34]. Further analysis highlighted significant changes in the expression of calcium ion channel-related genes such as RYR1, ATP2A1, and CACNB1 following MSTN knockout. As key signaling molecules for muscle contraction and relaxation, alterations in calcium ion homeostasis directly impact muscle fiber type transformation, contraction efficiency, and energy metabolism. Existing studies have pointed out that RyR1 is crucial during myotube fusion and maturation, with its dysfunction hindering muscle differentiation [35,36]. ATP2A1 (SERCA1) activity has been linked to pork quality traits, suggesting that its regulation of calcium recovery significantly impacts muscle relaxation and contraction rate [37]. Additionally, the expression and voltage sensitivity of the Ca_V1.1 channel complex, including its regulatory subunit CACNB1, play a central role in excitation-contraction coupling in skeletal muscle [38].
This study also identified significant changes in the expression of immune-related genes, such as IRF7 and ISG15. It is noteworthy that skeletal muscle, in addition to being the primary organ for movement and metabolism, can function as an “immunoneuroendocrine organ,” secreting various myokines involved in inflammatory responses and immune signaling. As a core transcription factor in the type I interferon signaling pathway, the upregulation of IRF7 suggests that MSTN deficiency may activate antiviral or immune–regulatory pathways, thereby influencing immune–metabolic coupling [39]. Similarly, ISG15, a typical interferon-stimulated gene, plays a vital role in cellular stress responses and antiviral immunity. It regulates protein homeostasis through ISGylation and participates in muscle cell differentiation and maturation [40,41]. These results suggest that MSTN knockout not only alters muscle metabolic pathways but may also affect muscle homeostasis and adaptability by reconstructing immune networks. Previous studies have shown that MSTN cross-regulates inflammation-related pathways, such as NF-κB and interferons [42,43], and the results of this study provide new evidence supporting this hypothesis.
The results of this study are consistent with existing findings in cattle, pigs, and other animals. Following MSTN knockout, differentially expressed genes are primarily enriched in pathways related to amino acid metabolism and muscle energy metabolism, indicating that energy metabolism remodeling is a key mechanism promoting skeletal muscle hypertrophy. MSTN deficiency can not only directly relieve muscle growth inhibition but also indirectly promote myofiber hypertrophy by regulating energy metabolism and signal transduction [44]. Furthermore, MSTN has been shown to cross-regulate immune and inflammatory signals during muscle development, with muscle-secreted factors and calcium signaling pathways playing crucial roles in metabolic regulation and muscle structural remodeling [45]. The findings from this study in sheep suggest that MSTN knockout may synergistically promote rapid skeletal muscle growth and structural remodeling through the coordinated action of energy metabolism regulation, calcium signaling pathway reconstruction, and immune network modulation.
The promoting effect of MSTN knockout on the growth performance of various livestock species is highly conserved. It significantly increases body weight, skeletal muscle weight, and lean meat percentage in species such as cattle, sheep, pigs, and rabbits. At the transcriptomic level, MSTN knockout is enriched in amino acid metabolism, muscle contraction, and calcium signaling pathways [46,47], confirming that the molecular mechanism by which MSTN regulates muscle growth is highly conserved across mammals. These findings provide cross-species evidence supporting the reliability of the results in this study. However, species-specific differences are evident in the effects of MSTN editing on different livestock species. In terms of growth rate improvement, pigs and cattle show greater enhancements than sheep [48], which may be attributed to the genetic background and metabolic characteristics of sheep muscle growth. Regarding fat metabolism, the reduction in fat content is more pronounced in pigs [49], while the effect in sheep is milder [50], which may help maintain meat quality stability. At the molecular level, the immune-related core genes identified in this study, such as IRF7 and ISG15, were not significantly enriched in studies on cattle and pigs, suggesting that MSTN may influence muscle growth through a unique immune–metabolic cross-regulation network in sheep. This species-specific characteristic warrants further in-depth exploration.
Although this study systematically confirmed the significant weight gain and body shape improvement associated with MSTN gene knockout in Chinese Merino sheep (Xinjiang type), without causing adverse effects on hematological and biochemical indicators, transcriptomic data further revealed that MSTN may regulate muscle growth through molecular mechanisms such as energy metabolism, calcium signaling pathways, and immune networks. These findings provide important theoretical support and practical references for the genetic improvement of this breed and for sheep molecular breeding practices. However, certain limitations remain:
First, the risk of off-target effects has not been completely excluded. While the efficient and precise hfCas12Max-T5_sheep system was used and no chimeric individuals were detected, the absence of whole-genome off-target site screening prevents a definitive conclusion regarding potential non-targeted mutations. Second, the study’s cycle and scope are limited. Currently, the focus is on growth and basic physiological indicators up to 365 days of age, lacking data on adult growth, reproductive indicators (such as estrous cycle, conception rate, and litter size), and comprehensive meat quality assessments. Third, no targeted animal welfare evaluation has been conducted. Excessive muscle hypertrophy may affect the sheep’s exercise capacity and bone load, which requires further verification.
To address these limitations, future studies will focus on the following aspects: First, conduct whole-genome off-target site screening to systematically evaluate the potential impact of non-target mutations, thereby ensuring the safety of gene editing technology. Second, extend the feeding cycle to monitor adult growth performance, reproductive performance, and the growth and development of offspring in edited sheep, and assess the genetic stability of the edited traits. Third, supplement comprehensive meat quality analysis, including shear force, meat color (Lab* values), intramuscular fat content, fatty acid composition, and flavor metabolic profiles, to clarify the overall impact of gene editing on meat quality. Fourth, systematically assess the actual impact of muscle hypertrophy on animal welfare by measuring gait parameters, cortisol levels, and bone mineral density. Fifth, conduct in-depth research on the effects of gene editing on grazing adaptability, cold resistance in winter, and forage conversion rate in the context of the pastoral breeding practices of Chinese Merino sheep (Xinjiang type), aiming to balance genetic improvement with ecological sustainability. Sixth, explore synergistic editing strategies combining MSTN with functional genes such as FGF5 to optimize both wool and meat performance in this breed.

5. Conclusions

This study demonstrated that MSTN gene knockout significantly enhanced the growth performance of Chinese Merino sheep (Xinjiang type), with notable improvements in body weight, body shape, and muscle development. Gene editing did not cause any adverse effects on the hematological or metabolic functions of the sheep. Transcriptomic analysis identified 121 differentially expressed genes, primarily involved in amino acid metabolism and muscle contraction. Through protein–protein interaction (PPI) network analysis, 10 key genes were identified, which may play crucial roles in the molecular mechanisms underlying MSTN gene regulation. RT-qPCR validation further confirmed the reliability of these findings. This study provides important theoretical insights and practical references for the application of MSTN gene editing in meat sheep breeding.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ani15233387/s1, Table S1: 46 hematological parameters in the experimental and control groups; Table S2: 24 serum biochemical parameters in the experimental and control groups; Table S3: Results of sequencing data quality preprocessing; Table S4: Alignment rate statistics of reads to the reference genome; Table S5: Gene expression levels in the experimental and control groups; Table S6: Differential gene expression analysis; Table S7: GO enrichment analysis of differentially expressed genes; Table S8: KEGG pathway analysis of differentially expressed genes; Table S9: RT-qPCR primers used in this study.

Author Contributions

Conceptualization, L.Z. and W.Z.; methodology, P.L. and W.Z.; validation, M.K.; formal analysis, L.Z.; investigation, L.Z., P.L., X.W. and M.K.; resources, X.W. and W.W.; data curation, L.Z., P.L. and M.K.; writing—original draft preparation, L.Z.; writing—review and editing, W.W. and W.Z.; visualization, X.W.; supervision, W.W. and W.Z.; project administration, W.W.; funding acquisition, W.W. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Major Reproductive Research Program of the Autonomous Region—Efficient Breeding Technology for Sheep (2023A02011-2); the National Science and Technology Major Project—Establishment of the In Vitro Embryo Production Technology System and Creation of Gene-Edited Sheep (2023ZD0405103-02); the third batch of the “2 + 5” Key Talent Program (Science and Technology Innovation Team)—Research on Precision Breeding Technology for Cattle and Sheep (2024TSYCTD0012); the third batch of the “2 + 5” Key Talent Program (Science and Technology Innovation Platform)—Xinjiang Uygur Autonomous Region Sheep Engineering Research Center; the “Tianshan Talents” Program—Leading Scientific and Technological Innovation Talents (Team) (20221100619); and the National Wool Sheep Industry Technology System (CARS-39-21).

Institutional Review Board Statement

The animal study protocol was approved by the Institutional Review Board of the Institute of Animal Husbandry, Xinjiang Academy of Animal Science (Protocol No.: DL [2025] No. 11 of Institute of Animal Husbandry, Xinjiang Academy of Animal Science; Approval Date: 3 November 2025). The sheep used in this experiment were owned by the Institute of Animal Husbandry, Xinjiang Academy of Animal Science, and thus no informed consent from individual owners was required. All experimental procedures were performed to minimize animal suffering, strictly following the approved ethical guidelines to ensure compliance with animal welfare requirements.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw RNA-seq data have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database, associated with Bio Project accession number PRJNA1367960 (https://www.ncbi.nlm.nih.gov/sra/, accessed on 23 November 2025). All other relevant raw data are available from the authors upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

MSTNMyostatin
DEGsDifferentially expressed genes
PPIProtein–protein interaction
GDF8Growth Differentiation Factor 8
TGF-βTransforming growth factor-beta
MTMSTN gene-edited sheep
WTWild-type control sheep
PCRPolymerase chain reaction
TMRTotal mixed ration
PCAPrincipal component analysis
RT-qPCRReal-time quantitative PCR

References

  1. Chen, M.M.; Zhao, Y.P.; Zhao, Y.; Deng, S.L. Regulation of myostatin on the growth and development of skeletal muscle. Front. Cell Dev. Biol. 2021, 9, 785712. [Google Scholar] [CrossRef]
  2. McPherron, A.; Lawler, A.; Lee, S.J. Regulation of skeletal muscle mass in mice by a new TGF-beta superfamily member. Nature 1997, 387, 83–90. [Google Scholar] [CrossRef]
  3. Luo, S.; Liu, Y.; Bu, L.; Wang, D.; Wen, Z.; Yang, Y.; Xu, Y.; Wu, D.; Li, G.; Yang, L. The Impact of MSTN Gene Editing on Meat Quality and Metabolomics: A Comparative Study Among Three Breeds of MSTN-Edited and Non-Edited Cattle. Animals 2025, 15, 47. [Google Scholar] [CrossRef]
  4. He, Z.; Zhang, T.; Jiang, L.; Zhou, M.; Wu, D.; Mei, J.; Cheng, Y. Use of CRISPR/Cas9 technology efficiently targeted goat myostatin through zygotes microinjection resulting in double-muscled phenotype in goats. Biosci. Rep. 2018, 38, BSR20180742. [Google Scholar] [CrossRef] [PubMed]
  5. Zhu, X.-X.; Zhan, Q.-M.; Wei, Y.-Y.; Yan, A.-F.; Feng, J.; Liu, L.; Lu, S.-S.; Tang, D.-S. CRISPR/Cas9-mediated MSTN disruption accelerates the growth of Chinese Bama pigs. Reprod. Domest. Anim. 2020, 55, 1314–1327. [Google Scholar] [CrossRef]
  6. Zhang, T.; Lu, Y.; Song, S.; Lu, R.; Zhou, M.; He, Z.; Yuan, T.; Yan, K.; Cheng, Y. ‘Double-muscling’ and pelvic tilt phenomena in rabbits with the cystine-knot motif deficiency of myostatin on exon 3. Biosci. Rep. 2019, 39, BSR20190207. [Google Scholar] [CrossRef]
  7. Ledesma, A.V.; Van Eenennaam, A.L. Global status of gene-edited animals for agricultural applications. Vet. J. 2024, 305, 106142. [Google Scholar] [CrossRef]
  8. Bi, Y.; Hua, Z.; Liu, X.; Hua, W.; Ren, H.; Xiao, H.; Zhang, L.; Li, L.; Wang, Z.; Laible, G.; et al. Isozygous and selectable marker-free MSTN knockout cloned pigs generated by the combined use of CRISPR/Cas9 and Cre/LoxP. Sci. Rep. 2016, 6, 31729. [Google Scholar] [CrossRef] [PubMed]
  9. Chen, M.-M.; Zhao, Y.; Xu, X.-L.; Zhang, X.-S.; Zhang, J.-L.; Wu, S.-J.; Liu, Z.-M.; Yuan, Y.-M.; Guo, X.-F.; Qi, S.-Y.; et al. A MSTN Del73C mutation with FGF5 knockout sheep by CRISPR/Cas9 promotes skeletal muscle myofiber hyperplasia. eLife 2024, 12, RP86827. [Google Scholar] [CrossRef] [PubMed]
  10. Zou, Y.-L.; Li, Z.-Y.; Zou, Y.-J.; Hao, H.-Y.; Hu, J.-X.; Li, N.; Li, Q.-Y. Generation of pigs with a Belgian Blue mutation in MSTN using CRISPR/Cpf1-assisted ssODN-mediated homologous recombination. J. Integr. Agric. 2019, 18, 1329–1336. [Google Scholar] [CrossRef]
  11. Dilger, A.C.; Chen, X.; Honegger, L.T.; Marron, B.M.; Beever, J.E. The potential for gene-editing to increase muscle growth in pigs: Experiences with editing myostatin. CABI Agric. Biosci. 2022, 3, 106. [Google Scholar] [CrossRef]
  12. Maynard, L.H.; Humbert, O.; Peterson, C.W.; Kiem, H.-P. Genome editing in large animal models. Mol. Ther. 2021, 29, 2921–2934. [Google Scholar] [CrossRef]
  13. Tian, Y.; An, J.; Zhang, X.; Di, J.; He, J.; Yasen, A.; Ma, Y.; Sailikehan, G.; Huang, X.; Tian, K. Genome-Wide Scan for Copy Number Variations in Chinese Merino Sheep Based on Ovine High-Density 600K SNP Arrays. Animals 2024, 14, 2897. [Google Scholar] [CrossRef] [PubMed]
  14. Zhang, L.; Duan, Y.; Zhao, S.; Xu, N.; Zhao, Y. Caprine and Ovine Genomic Selection—Progress and Application. Animals 2024, 14, 2659. [Google Scholar] [CrossRef]
  15. Duan, Z.; Liang, Y.; Sun, J.; Zheng, H.; Lin, T.; Luo, P.; Wang, M.; Liu, R.; Chen, Y.; Guo, S.; et al. An engineered Cas12i nuclease that is an efficient genome editing tool in animals and plants. Innovation 2024, 5, 100564. [Google Scholar] [CrossRef] [PubMed]
  16. Chen, J.H.; Wang, J.Q.; Zhao, H.R.; Tan, X.; Yan, S.H.; Zhang, H.Y.; Wang, T.F.; Tang, X.C. Molecular breeding of pigs in the genome editing era. Genet. Sel. Evol. 2025, 57, 12. [Google Scholar] [CrossRef]
  17. Zhou, S.W.; Kalds, P.; Luo, Q.; Sun, K.X.; Zhao, X.E.; Gao, Y.W.; Cai, B.; Huang, S.H.; Kou, Q.F.; Petersen, B.; et al. Optimized Cas9:sgRNA delivery efficiently generates biallelic MSTN knockout sheep without affecting meat quality. BMC Genom. 2022, 23, 348. [Google Scholar] [CrossRef]
  18. Gu, R.; Wang, H.; Meng, C.; Gui, H.; Li, Y.; Chen, F.; Zhang, C.; Zhang, H.; Ding, Q.; Zhang, J.; et al. Efficient and Specific Generation of MSTN-Edited Hu Sheep Using C-CRISPR. Genes 2023, 14, 1216. [Google Scholar] [CrossRef]
  19. Baig, M.H.; Ahmad, K.; Moon, J.S.; Park, S.Y.; Lim, J.H.; Chun, H.J.; Qadri, A.F.; Hwang, Y.C.; Jan, A.F.; Ahmad, S.S.; et al. Myostatin and its regulation: A comprehensive review of myostatin inhibiting strategies. Front. Physiol. 2022, 13, 876078. [Google Scholar] [CrossRef] [PubMed]
  20. Sheng, H.; Guo, Y.; Zhang, L.; Zhang, J.; Miao, M.; Tan, H.; Hu, D.; Li, X.; Ding, X.; Li, G.; et al. Proteomic Studies on the Mechanism of Myostatin Regulating Cattle Skeletal Muscle Development. Front. Genet. 2021, 12, 752129. [Google Scholar] [CrossRef]
  21. Hai, C.; Liu, X.; Bai, C.; Su, G.; Yang, L.; Li, G. Loss of Myostatin Shapes the Transcriptomic and Epigenetic Landscapes Across Multiple Muscle Types in Cattle. Curr. Issues Mol. Biol. 2025, 47, 431. [Google Scholar] [CrossRef] [PubMed]
  22. Wang, X.; Li, N.; Zhang, Y.; Liu, J.; Li, J.; Gao, S.; Wang, Y.; Yang, L. Generation of Gene-Modified Goats Targeting MSTN and FGF5 via Zygote Injection of CRISPR/Cas9 System. Sci. Rep. 2015, 5, 13878. [Google Scholar] [CrossRef]
  23. Gao, L.; Liu, Y.; Zhang, Y.; Li, J.; Wang, X. Mstn Knockdown Decreases the Trans-differentiation from Myocytes to Adipocytes by Reducing Jmjd3 Expression via the SMAD2/SMAD3 Complex. Biosci. Biotechnol. Biochem. 2019, 83, 2090–2096. [Google Scholar] [CrossRef]
  24. Malgwi, I.; D’Andrea, M.; Schiavon, S.; Badiani, A. Genes Related to Fat Metabolism in Pigs and Intramuscular Fat Content of Pork: A Focus on Nutrigenetics and Nutrigenomics. Animals 2022, 12, 150. [Google Scholar] [CrossRef]
  25. Bannister, M.L.; Zhou, H.; Dulhunty, A.F. Malignant hyperthermia mutation sites in the Leu2442-Pro2477 (DP4) region of RyR1 are clustered in a structurally and functionally definable area. Biochem. J. 2007, 403, 519–528. [Google Scholar] [CrossRef]
  26. Brosnan, J.T.; Brosnan, M.E. Glutamate, at the interface between amino acid and carbohydrate metabolism. J. Nutr. 2000, 130, 988S–990S. [Google Scholar] [CrossRef]
  27. Degens, H.; Qiao, L.; Yang, Y. Myostatin Knockout Mice Have Larger Muscle Fibers With Normal Function and Morphology. Muscle Nerve 2025, 61, 730–738. [Google Scholar] [CrossRef] [PubMed]
  28. Ponnampalam, E.N.; Mann, N.J.; Norng, S.; Bekhit, A.E.D.; Trotter, M.D.; Hopkins, D.L. Sensory and Flavor Chemistry Characteristics of Australian Beef: Influence of Intramuscular Fat, Feed, and Breed. J. Agric. Food Chem. 2016, 64, 3425–3435. [Google Scholar] [CrossRef]
  29. Pei, Y.; Fan, Z.; Song, Y.; Chen, C.; Mu, Y.; Li, B.; Feng, Z.; Li, H.; Li, K. Viscera characteristics of MSTN-edited heterozygous pigs. Front. Genet. 2022, 13, 764965. [Google Scholar] [CrossRef]
  30. Wu, D.; Gu, M.; Wei, Z.; Bai, C.; Su, G.; Liu, X.; Zhao, Y.; Yang, L.; Li, G. Myostatin Knockout Regulates Bile Acid Metabolism by Promoting Bile Acid Synthesis in Cattle. Animals 2022, 12, 205. [Google Scholar] [CrossRef] [PubMed]
  31. Luo, Z.B.; Han, S.; Yin, X.J.; Liu, H.; Wang, J.; Xuan, M.; Hao, C.; Wang, D.; Liu, Y.; Chang, S.; et al. Fecal transplant from myostatin deletion pigs positively impacts the gut-muscle axis. eLife 2023, 12, e81858. [Google Scholar] [CrossRef]
  32. Chen, M.; Zhao, Y.; Li, Y.; Chen, T.; Zhou, W.; Zhang, X.; Deng, S.; Liu, Z.; Qi, S.; Wang, L.; et al. Reproduction and viscera organ characteristics of MSTN and FGF5 dual-gene knockout sheep. Front. Vet. Sci. 2023, 10, 1119312. [Google Scholar] [CrossRef] [PubMed]
  33. Gu, M.; Wang, S.; Di, A.; Wu, D.; Hai, C.; Liu, X.; Bai, C.; Su, G.; Yang, L.; Li, G. Combined Transcriptome and Metabolome Analysis of Smooth Muscle of Myostatin Knockout Cattle. Int. J. Mol. Sci. 2023, 24, 8120. [Google Scholar] [CrossRef]
  34. Welle, S.; Bhatt, K.; Pinkert, C.A. Myofibrillar protein synthesis in myostatin-deficient mice. Am. J. Physiol. Endocrinol. Metab. 2005, 288, E1088–E1094. [Google Scholar] [CrossRef] [PubMed]
  35. Qiu, K.; Wang, Y.; Xu, D.; He, L.; Zhang, X.; Yan, E.; Wang, L.; Yin, J. Ryanodine receptor RyR1-mediated elevation of Ca2+ concentration is required for the late stage of myogenic differentiation and fusion. J. Anim. Sci. Biotechnol. 2022, 13, 9. [Google Scholar] [CrossRef]
  36. Li, X.; Zhao, X.; Qin, Z.; Li, J.; Sun, B.; Liu, L. Regulation of calcium homeostasis in endoplasmic reticulum–mitochondria crosstalk: Implications for skeletal muscle atrophy. Cell Commun. Signal. 2025, 23, 17. [Google Scholar] [CrossRef] [PubMed]
  37. Chai, J.; Xiong, Q.; Shang, Y.Y.; Zheng, R.; Peng, J.; Jiang, S.W. Evidence for a new allele at the SERCA1 locus affecting pork meat quality in part through the imbalance of Ca2+ homeostasis. J. Anim. Sci. 2009, 87, 3276–3283. [Google Scholar] [CrossRef]
  38. Pflügers Archiv Editorial Staff. Skeletal muscle CaV1.1 channelopathies. Pflügers Arch. Eur. J. Physiol. 2020, 472, 739–754. [Google Scholar] [CrossRef]
  39. Nodari, A.; Scambi, I.; Peroni, D.; Calabria, E.; Benati, D.; Mannucci, S.; Manfredi, M.; Frontini, A.; Visonà, S.; Bozzato, A.; et al. Interferon regulatory factor-7 impairs cellular metabolism in aging adipose-derived stromal cells. J. Cell Sci. 2021, 134, jcs256230. [Google Scholar] [CrossRef]
  40. Olie, C.S.; Pinto-Fernández, A.; Damianou, A.; Vendrell, I.; Mei, H.; Hamer, B.; Wal, E.; Greef, J.C.; Raz, V.; Kessler, B.M. USP18 is an essential regulator of muscle cell differentiation and maturation. Cell Death Dis. 2023, 14, 231. [Google Scholar] [CrossRef]
  41. Perng, Y.-C.; Lenschow, D.J. ISG15 in antiviral immunity and beyond. Nat. Rev. Microbiol. 2018, 16, 423–439. [Google Scholar] [CrossRef]
  42. Han, S.-Z.; Gao, K.; Chang, S.-Y.; Choe, H.-M.; Paek, H.-J.; Quan, B.-H.; Liu, X.-Y.; Yang, L.-H.; Lv, S.-T.; Yin, X.-J.; et al. miR-455-3p Is Negatively Regulated by Myostatin in Skeletal Muscle and Promotes Myoblast Differentiation. J. Agric. Food Chem. 2023, 71, 3456–3467. [Google Scholar] [CrossRef] [PubMed]
  43. Nageeb, R.S.; Mohamed, N.M.; Soliman, A.S.; Ebald, A.M.; Mohammad, N.A. Serum level of myostatin and type I interferon-inducible gene expression in dermatomyositis patients and its relation to insulin resistance. Egypt J. Neurol. Psychiatry Neurosurg. 2024, 60, 136. [Google Scholar] [CrossRef]
  44. Jin, Z.; Choe, H.M.; Lv, S.; Chang, S.; Yin, X. Esophageal striated muscle hypertrophy and muscle fiber type transformation in MSTN knockout pigs. Transgenic Res. 2022, 31, 341–349. [Google Scholar] [CrossRef]
  45. Sammut, M.J.; Thorne, B.R.; Melling, C.W.J. Skeletal muscle growth to combat diabetes and obesity: The potential role of muscle-secreted factors. Obesity 2025, 33, 435–451. [Google Scholar] [CrossRef]
  46. Gim, G.-M.; Kwon, D.-H.; Eom, K.-H.; Moon, J.H. Production of MSTN-Mutated Cattle Without Exogenous Gene Integration Using CRISPR-Cas9. Biotechnol. J. 2021, 17, 2100198. [Google Scholar] [CrossRef]
  47. Wang, Y.; Li, N.; Lv, Z.; Zhang, Y.; Cao, J.; Liu, B.; Wang, X.; Han, Y.; Bai, Y.; Li, J.; et al. Generation and Evaluation of Myostatin Knock-Out Rabbits and Goats Using CRISPR/Cas9 System. Sci. Rep. 2016, 6, 29855. [Google Scholar] [CrossRef]
  48. Perea, A.; Pérez, E.; Rodríguez, A.; García-García, R.; Fernández, A.; de la Fuente, J.; Silvestre, M.A.; González, S. Efficient Generation of Myostatin Knock-Out Sheep Using CRISPR/Cas9 Technology and Microinjection into Zygotes. PLoS ONE 2015, 10, e0136690. [Google Scholar] [CrossRef]
  49. Guo, X.; Li, N.; Liu, G.; Zhang, Y.; Wang, Y.; Lv, Z.; Cao, J.; Liu, B.; Han, Y.; Bai, Y.; et al. Myostatin Regulates Fatty Acid Desaturation and Fat Deposition Through MEF2C/miR222/SCD5 Cascade in Pigs. Commun. Biol. 2020, 3, 612. [Google Scholar] [CrossRef]
  50. Zhang, X.; Liu, C.; Kong, Y.; Li, F.; Yue, X. Effects of intramuscular fat on meat quality and its regulation mechanism in Tan sheep. Front. Nutr. 2022, 9, 908355. [Google Scholar] [CrossRef]
Animals 15 03387 g001
Figure 1. Pearson correlation analysis of samples (A) and principal component analysis of samples (B).
Figure 1. Pearson correlation analysis of samples (A) and principal component analysis of samples (B).
Animals 15 03387 g001
Animals 15 03387 g002
Figure 2. Volcano plot of differentially expressed genes.
Figure 2. Volcano plot of differentially expressed genes.
Animals 15 03387 g002
Animals 15 03387 g003
Figure 3. GO functional enrichment (A) and KEGG functional enrichment (B).
Figure 3. GO functional enrichment (A) and KEGG functional enrichment (B).
Animals 15 03387 g003
Animals 15 03387 g004
Figure 4. PPI network interaction analysis of differentially expressed genes (A–C). Panels (A–C) represent three distinct gene co-expression modules. Node colors indicate different functional clusters or gene families (specific color definitions are consistent with the legend in the original study).
Figure 4. PPI network interaction analysis of differentially expressed genes (A–C). Panels (A–C) represent three distinct gene co-expression modules. Node colors indicate different functional clusters or gene families (specific color definitions are consistent with the legend in the original study).
Animals 15 03387 g004
Animals 15 03387 g005
Figure 5. RT-qPCR validation of differentially expressed genes (DEGs). * p < 0.05 indicates a significant difference between groups.
Figure 5. RT-qPCR validation of differentially expressed genes (DEGs). * p < 0.05 indicates a significant difference between groups.
Animals 15 03387 g005
Table 1. Effects of MSTN gene knockout on body weight and body measurements at different stages of sheep development.
Table 1. Effects of MSTN gene knockout on body weight and body measurements at different stages of sheep development.
Age (Days)GroupBody Weight (kg)Body Length (cm)Withers Height (cm)Chest Girth (cm)Cannon Circumference (cm)Hip Width (cm)
30 MT 11.09 ± 3.16 a 43.23 ± 3.82 a 46.47 ± 3.60 a 51.14 ± 5.64 a 6.36 ± 0.60 a 12.82 ± 1.42 a
WT 8.22 ± 1.48 b 37.79 ± 2.45 b 41.61 ± 2.45 b 42.44 ± 2.03 b 6.03 ± 0.38 b 10.62 ± 0.37 b
60 MT 18.32 ± 3.92 a 52.23 ± 4.46 a 53.17 ± 3.22 a 60.10 ± 5.40 a 6.63 ± 0.65 a 13.30 ± 1.64 a
WT 16.07 ± 2.91 b 50.56 ± 3.64 b 50.82 ± 3.30 b 58.88 ± 4.52 a 6.43 ± 0.55 a 12.10 ± 1.16 b
90 MT 23.94 ± 4.52 a 59.38 ± 3.69 a 57.82 ± 3.70 a 67.82 ± 5.51 a 7.04 ± 0.56 a 17.31 ± 1.46 a
WT 20.54 ± 2.92 b 56.88 ± 3.41 b 54.85 ± 2.24 b 65.28 ± 4.05 b 6.93 ± 0.52 a 15.17 ± 1.06 b
120 MT 28.52 ± 5.15 a 61.39 ± 4.62 a 58.81 ± 2.69 a 72.55 ± 5.18 a 7.05 ± 0.57 a 19.11 ± 1.58 a
WT 24.11 ± 3.49 b 58.56 ± 3.71 b 56.38 ± 2.35 b 69.27 ± 4.60 b 6.78 ± 0.57 b 16.58 ± 1.21 b
160 MT 35.18 ± 5.85 a 66.22 ± 4.54 a 62.71 ± 3.14 a 78.46 ± 5.76 a 7.55 ± 0.73 a 21.74 ± 2.26 a
WT 29.20 ± 3.71 b 60.24 ± 3.20 b 59.24 ± 3.36 b 74.62 ± 4.00 b 7.39 ± 0.59 a 18.46 ± 1.28 b
190 MT 38.39 ± 6.56 a 67.23 ± 4.35 a 64.00 ± 2.77 a 82.30 ± 5.40 a 7.70 ± 0.63 a 19.70 ± 1.63 a
WT 31.93 ± 4.88 b 64.91 ± 4.11 b 61.58 ± 2.81 b 77.43 ± 4.35 b 7.52 ± 0.58 a 17.71 ± 1.28 b
365 MT 61.07 ± 10.59 a 80.85 ± 5.86 a 71.37 ± 4.48 a 113.16 ± 8.80 a 11.20 ± 1.35 a 32.40 ± 2.93 a
WT 50.20 ± 7.97 b 75.60 ± 5.29 b 68.23 ± 4.06 b 104.70 ± 7.36 b 11.08 ± 1.14 a 27.50 ± 2.41 b
Note: All measurement data are presented as mean ± standard deviation (Mean ± SD). Differences in lamb growth traits (body weight, body length, withers height, chest girth, cannon circumference, and hip width) between groups at different ages were analyzed using one-way analysis of variance (ANOVA), followed by post hoc multiple comparisons. Different letters (ab) indicate significant differences between groups at the same age (p < 0.05), while the same letter indicates no significant difference between groups at the same age (p > 0.05).
Table 2. Hematological parameters of gene-edited sheep (MT group) and control sheep (WT group).
Table 2. Hematological parameters of gene-edited sheep (MT group) and control sheep (WT group).
IndicatorUnitMT GroupWT Groupp-Value
White Blood Cell Count 109/L 7.35 ± 1.085.70 ± 1.18 0.752
Absolute Neutrophil Count 109/L 1.42 ± 0.351.32 ± 0.38 0.374
Absolute Lymphocyte Count 109/L 5.37 ± 0.944.02 ± 0.94 0.153
Red Blood Cell Count 1012/L 8.98 ± 0.758.30 ± 1.97 0.607
Hemoglobin Concentration g/L 84.11 ± 10.4985.71 ± 20.62 0.910
Hematocrit % 27.83 ± 4.2227.35 ± 7.41 0.926
Mean Corpuscular Volume fL 30.91 ± 2.5032.74 ± 1.33 0.325
Mean Corpuscular Hemoglobin Concentration g/L 303.09 ± 9.70315.61 ± 12.45 0.242
Platelet Count 109/L 168.60 ± 48.88184.20 ± 75.61 0.779
Mean Platelet Volume fL 6.48 ± 2.097.18 ± 4.26 0.813
Table 3. Hematological and serum biochemical parameters of gene-edited sheep (MT group) and control sheep (WT group).
Table 3. Hematological and serum biochemical parameters of gene-edited sheep (MT group) and control sheep (WT group).
IndicatorUnitMT GroupWT Groupp-Value
Albumin g/L 36.56 ± 1.4233.83 ± 2.28 0.153
Total Protein g/L 72.40 ± 4.4773.13 ± 2.64 0.819
Albumin/Globulin Ratio 1.02 ± 0.070.87 ± 0.18 0.240
Aspartate Aminotransferase U/L 178.00 ± 38.31139 ± 23.07 0.205
Alanine Aminotransferase U/L 27.00 ± 3.4625.33 ± 2.08 0.515
Lactate Dehydrogenase U/L 595.00 ± 27.62533.67 ± 62.05 0.193
Creatine Kinase U/L 92.33 ± 11.2473.33 ± 10.50 0.099
Creatinine umol/L 118.07 ± 10.77160.60 ± 46.97 0.201
Urea mmol/L 5.78 ± 0.626.17 ± 0.51 0.455
Glucose mmol/L 4.66 ± 0.474.97 ± 0.62 0.530
Total Cholesterol mmol/L 1.56 ± 0.111.96 ± 0.36 0.134
Triglycerides mmol/L 0.52 ± 0.230.58 ± 0.01 0.744
Calcium mmol/L 2.40 ± 0.182.28 ± 0.08 0.378
Note: Differences in hematological and serum biochemical parameters between the two groups were analyzed using Student’s t-test, with results presented as p-values (p < 0.05 indicates a significant difference; p > 0.05 indicates no significant difference).
Table 4. Sequencing data statistics.
Table 4. Sequencing data statistics.
GroupSampleTotal ReadsTotal Mapped ReadsClean Bases
(G)		Valid Bases
(%)		Q30
(%)		GC
(%)
MT 1 46,957,018 46,440,752 6.87 97.54 96.90 56.68
2 46,931,116 46,325,269 6.90 97.99 96.72 56.62
3 47,106,932 46,083,379 6.93 97.98 96.69 56.05
WT 1 48,464,622 48,010,755 7.06 96.99 96.97 55.90
2 47,057,204 46,444,644 6.90 97.72 96.79 55.83
3 46,073,008 45,485,260 6.78 97.98 96.69 55.99
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, L.; Li, P.; Wang, X.; Kong, M.; Wu, W.; Zheng, W. Effects of MSTN Gene Knockout on Growth Performance and Muscle Transcriptome in Chinese Merino Sheep (Xinjiang Type). Animals 2025, 15, 3387. https://doi.org/10.3390/ani15233387

AMA Style

Zhang L, Li P, Wang X, Kong M, Wu W, Zheng W. Effects of MSTN Gene Knockout on Growth Performance and Muscle Transcriptome in Chinese Merino Sheep (Xinjiang Type). Animals. 2025; 15(23):3387. https://doi.org/10.3390/ani15233387

Chicago/Turabian Style

Zhang, Li, Pengfei Li, Xu Wang, Menghua Kong, Weiwei Wu, and Wenxin Zheng. 2025. "Effects of MSTN Gene Knockout on Growth Performance and Muscle Transcriptome in Chinese Merino Sheep (Xinjiang Type)" Animals 15, no. 23: 3387. https://doi.org/10.3390/ani15233387

APA Style

Zhang, L., Li, P., Wang, X., Kong, M., Wu, W., & Zheng, W. (2025). Effects of MSTN Gene Knockout on Growth Performance and Muscle Transcriptome in Chinese Merino Sheep (Xinjiang Type). Animals, 15(23), 3387. https://doi.org/10.3390/ani15233387

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop