A conserved functional missense SNP (E100K) in sheep MC4R gene leading to functional loss and impacting the growth traits

Abstract

The melanocortin-4 receptor (MC4R), a key regulator of energy balance and feeding behavior, plays a critical role in sheep growth. Herein, we identified a naturally occurring conserved functional SNP (g.59480661G > A, E100K, P.Glu100Lys) in the sheep MC4R gene. Using the Kompetitive Allele Specific PCR method, we detected this mutation in 2,151 sheep from six different breeds. Association analysis revealed that this mutation affects the growth traits of Luxi Blackhead sheep, and the individuals with AA (K100) genotype exhibited superior growth performance compared to the GG (E100) genotype. Additionally, whole-genome sequencing data from 49 sheep breeds, totaling 968 individuals, showed a higher mutation frequency of this variant in some large-sized sheep breeds. Functional studies demonstrated that the E100K mutation does not affect protein localization or transport but reduces surface and total protein expression. The mutated receptor exhibited decreased basal activity and reduced binding efficiency with agonists (α-MSH and β-MSH), resulting in a partial loss of function. Transcriptomic analysis indicated that this mutation affects downstream pathways, including osteoclast differentiation and the MAPK signaling pathway, which may influence growth regulation associated with the E100K mutation. Collectively, these findings underscore the substantial role of the partial loss-of-function MC4R E100K mutation in regulating growth traits in sheep.

This study identifies a conserved functional SNP (E100K) in the sheep MC4R gene that impairs receptor function and significantly affects growth traits. The findings provide valuable insights into the molecular mechanisms underlying sheep growth regulation.

Introduction

The body weight of mammal is influenced by various factors such as genetics, environment conditions, and nutrition. The maintenance of body weight is regulated by feedback mechanisms from breakdown and anabolic pathways, and the central melanocortin system, consisting of pre-proopiomelanocortin (pre-POMC), neuropeptide Y, agouti-related protein, and melanocortin receptors, plays a key role in this process (Baldini and Phelan 2019; Yang and Xu 2020). The melanocortin receptors are members of the G protein-coupled receptor (GPCR) superfamily, comprising five subtypes (MC1R-MC5R), and are instrumental in regulating a range of physiological processes, including animal food intake, energy metabolism, epidermal pigmentation, sebaceous gland secretion, and reproduction (Yang, 2011; Tao, 2017).

As the most distal gene in leptin-mediated appetite regulation, Melanocortin-4 receptor (MC4R) is the first target gene found to be associated with dominant genetic obesity in humans (Fairbrother et al., 2018). As a brain-expressed G_αs-coupled GPCR involved in weight regulation and the occurrence of obesity, MC4R can mediate the regulation of energy homeostasis by leptin, directly regulate food intake and weight reduction, and also participate in hypothalamus regulation of energy balance (Mountjoy et al., 1994; Fan et al., 1997; Kishi et al. 2003). Upon binding with its endogenous ligand (α-MSH, β-MSH, NDP-MSH, ACTH), MC4R can release the G_αs G protein and activate the cAMP-PKA and MAPK-ERK1/2 signaling pathways (Baldini and Phelan 2019). Mutations in MC4R are the most common cause of early-onset obesity, and over 170 distinct mutations linked to early-onset obesity and hyperphagia have been identified so far (Huang et al., 2017). These mutations can affect MC4R function in human by altering ERK1/2 phosphorylation/dephosphorylation, cAMP production, β-arrestin recruitment, receptor recycling, receptor internalization, and cell membrane expression (Brouwers et al., 2021). Based on the functional effects of mutations, MC4R mutations can be classified into three categories: WT-like mutations, loss-of-function (LoF) mutations, and gain-of-function (GoF) mutations (Brouwers et al., 2021). These functional studies provide a missing link between mutation identification and causality in the pathogenesis of obesity.

The mutation of MC4R in domestic animals has been found to affect many economic traits, such as body weight (Liu et al., 2010; Shishay et al., 2019), energy homeostasis (Barb et al., 2004), and feed efficiency (Piórkowska et al., 2010; Kim et al., 2000). The sheep MC4R gene is located on sheep chromosome 23 and consists of a single exon encoding a 332 amino acid GPCR. Al-Thuwaini et al. (2021) found that R18G and H7Q were closely related to live body weight, testosterone, and estradiol in Awassi and Arabi sheep breeds. Similarly, G98R was found to affect the loin-eye area in German Merino sheep (Zuo et al., 2014) and the I173M mutation showed a significant correlation with adult height in Hu sheep (Shan et al., 2020). However, these studies are still in the associative analysis stage, lacking in-depth cellular mechanism research into these mutations. In light of the impact of MC4R mutations on sheep growth traits, this study aims to conduct a more comprehensive investigation into coding-region variations of the MC4R gene in sheep. By scanning the coding region of the sheep MC4R gene in Luxi Blackhead (LXBH) sheep, a missense mutation, E100K (g.59480661G>A, P.Glu100Lys), was discovered. Here, we used this naturally occurring missense variant in MC4R as a tool to investigate the impact of disruption of specific mechanisms on the regulation of growth traits in sheep. The findings from this study can provide valuable information about the functional consequences of the E100K mutation and its potential contribution to the observed effects on sheep growth traits.

Materials and Methods

Ethical approval

All animal procedures were conducted in accordance with the national guidelines for the care and use of laboratory animals and were approved by the Institutional Animal Care and Use Committee of Northwest A&F University (IACUC-NWAFU).

Animal and sample collection

This study utilized a total of 2,151 sheep from six different breeds, including 431 Australian White (AUW) sheep from Tianjin Aoqun Sheep Industry Academy Company in Tianjin, China, 488 LXBH sheep from Liaocheng, Shandong, China, 565 Guiqian semi-fine wool (GQSFW) sheep from Guizhou, China, 45 Weining (WN) sheep from Guizhou, China, 333 Hu sheep, and 289 Yuansheng dairy (YSD) sheep from Gansu, China. The selected animals were unrelated, varying in age and sex. Blood samples, approximately 8 mL each, were collected from the jugular vein using EDTA blood collection tubes and stored at −20°C until laboratory analysis. A comprehensive set of growth traits was recorded for each sheep, including body weight, body height, body length, hip height, chest depth, chest width, chest circumference, abdominal girth, cannon circumference, and hip width. The LXBH sheep were classified into lambs (under 6 months old), mature (6-18 months old), and adults (18 months and above) based on their age.

DNA extraction and dilution

DNA extraction from the collected blood samples followed the methodology outlined in previous studies (Köchl et al., 2005). The quality and purity of each DNA sample were evaluated using Nanodrop 2000 (Thermo Fisher Scientific Inc., Wilmington, DE, USA). Afterward, the DNA samples were diluted with ddH₂O to a standardized concentration of 20 ng/μL and preserved at −20°C for subsequent genotyping analyses.

PCR amplification and kompetitive allele specific PCR assay genotyping

A pair of specific PCR primers was designed using the NCBI Primer-BLAST tool to amplify the coding sequence of the sheep MC4R gene. The primers were designed based on the genomic sequence corresponding to the MC4R gene (GenBank accession no. NC_056076.1) and synthesized by Sangon Biotech (Shanghai) Co., Ltd (Table 1). The PCR reactions and procedures followed the methods described in a previous study (Akhatayeva et al., 2022). PCR products were subjected to Sanger sequencing by Sangon Biotech (Shanghai) Co., Ltd (Beijing, China). To identify potential SNPs, Chromas software (Technelysium Pty Ltd, Helensville, Australia) was employed.

Table 1.

Primers for amplifying the coding sequence region of the MC4R gene in sheep and KASP primers for detecting the E100K (g.59480661G>A, P.Glu100Lys) mutation.

Primer names	Sequences (5′–3′)	Utility
sheep-MC4R-F	GGGAGGTTCAGTCAGTCCAGA	Genotyping primers
sheep-MC4R-R	TCTCTTAAGCTTGTGTTTGGCAC
MC4R-E100K-F1	GAAGGTGACCAAGTTCATGCTTTGGTGAGCGTTTCCAACGGGTCCG
MC4R-E100K-F2	GAAGGTCGGAGTCAACGGATTTTGGTGAGTGTTTCCAACGGGTCCA	KASP Assay
MC4R-E100K-R	CATTGTCATCACCCTGCTGAACAGCACAG

The kompetitive allele specific PCR (KASP) genotyping assay for a single SNP involves two allele-specific forward primers and one common reverse primer, as shown in Table 1. The assay mix preparation and PCR amplifications were carried out following the user’s guide and manual for the KASP genotyping system (Zhao et al., 2024). The assays were performed in a 96-well plate, and each reaction had a total volume of 10 µL, which consist of 5 µL 2 × KASP Master Mix, 0.5 µL KASP primer mix, 1.5 µL ddH₂O and 3 µL genomic DNA at 25–250 ng/µL. The KASP genotyping was performed on an ABI Quant Studio 5 real-time PCR system using the following cycling conditions: 1. Pre-denaturation: 94 °C for 10 minutes; 2. Touchdown PCR: denaturation: 95 °C for 15 seconds and annealing: start at 61 °C for 1 minute, and decrease by 1 °C per cycle until reaching 55 °C, for a total of 10 cycles; 3. Amplification: 95 °C for 15 seconds and 55 °C for 1 minutes, repeat the denaturation, annealing, and extension steps for a total of 28 cycles; 4. Cooling: 4 °C indefinitely. The fluorescence signals from the reactions are measured at 30 °C to determine the genotypes of the samples.

Whole genome sequencing and bioinformatic analyses

To investigate the global distribution of the sheep MC4R E100K variant in different sheep breeds, we collected whole genome sequencing (WGS) data from 968 individuals representing 49 breeds from various regions (Europe, Africa, China, and the Middle East). Using VCFtools, we determined the allele frequencies for each breed (Li et al., 2023). The specific breeds and sample sizes are presented in Supplementary Table S1 (see online supplementary material).

The CDS of the MC4R gene from 16 species (Homo sapiens, Gorilla gorilla gorilla, Macaca mulatta, Camelus bactrianus, Canis lupus familiaris, Sus scrofa, Bos taurus, Ovis aries, Capra hircus, Gallus gallus, Parus major, Athene cunicularia, Danio rerio, Bubalus bubalis, Bos mutus, and Equus asinus) were retrieved and subjected to multiple sequence alignment using BioEdit software to assess the evolutionary conservation of MC4R across species (Tamura et al., 2011).

In vitro mutagenesis of MC4R

The WT sheep MC4R was synthesized through reverse transcription-coupled PCR of sheep mRNA, employing primers corresponding to the NCBI reference sequence NM_001126370. These primers included additional BamHI and EcoRI restriction sites at the 5′ and 3′ ends, respectively. The obtained WT sequence was then submitted to Shenggong Biotechnology Co., Ltd for point mutation experiments. A Kozak sequence (GCCACC) was added to the 5′ end of the gene sequence, and three Myc tags were introduced at the N-terminus. Subsequently, the modified sequence was cloned between the BamHI and EcoRI sites of the pcDNA3.1+ vector. Plasmid extraction was carried out using the Endofree Plasmid Maxi Kit from TianGen Biotech. DNA sequencing was performed to validate the accuracy of the entire coding region.

HEK293T cell culture and luciferase reporter assay

Human embryonic kidney (HEK) 293 T cells were cultured in DMEM supplemented with 10% fetal bovine serum, 100 units/mL of penicillin, and 100 μg/ml streptomycin at 5% CO₂. The luciferase reporter vector pGL4.29 from Promega (Madison, WI, USA) contains a cAMP-responsive element (CRE) in its promoter regions, allowing for the monitoring of the activation of the cAMP signaling pathway (Turgut et al., 2017; Wu et al., 2021). The plasmid transfection procedure followed previous experimental methods (Wu et al., 2021), with a brief overview as follows: HEK293T cells were seeded in 6-well plates 24 hours before transfection, and when cell density reached 60-70%, plasmid transfection was performed. The plasmid transfection mixture included 500 ng of WT(E100) or K100 MC4R plasmid (or empty pcDNA3.1 plasmid), 1000 ng of the luciferase reporter vector, and 300 ng of pEGFP-N1(internal control). After 24 hours of transfection, cells from the 6-well plate were reseeded into a 48-well plate, and 24 hours later, stimulation with agonists was conducted. The agonists α-MSH and β-MSH were sourced from GenScript Biotechnology (Nanjing, China). And diluted with enzyme-free water to a storage concentration of 10^{^-4}M and stored at −20°C. The two ligands (α-MSH, β-MSH) were diluted to the working concentration in serum-free medium and added to the 48-well plate to treat cells for 6 hours. Following treatment, cells were lysed with 1× passive lysis buffer (YEASEN, Shanghai, China), and the luciferase substrate was added for the reaction. Each assay included two additional 48-well plates (n = 3) used as technical replicates, and the data were presented as Mean ± SEM.

Western blot

Following transfection of HEK293T cells with WT(E100) or K100 MC4R plasmid (or empty pcDNA3.1 plasmid), cells were stimulated with 10⁻⁵M α-MSH for 15 minutes after 24 hours. The cultured cells were lysed in RIPA buffer with protease and phosphatase inhibitor cocktails. Protein concentration was determined using the bicinchoninic acid method. Subsequently, 20 μg protein samples were separated using the Tris-Gly electrophoresis system (200 V, 60 min), and transferred to a 0.2 µm PVDF membrane under moist conditions. The membrane was blocked at room temperature for 2 hours in 5% skim milk, washed three times with TBST, and then incubated overnight at 4 °C with Myc antibody (Abmart, Cat# M20002, 1:2000) and Actin antibody (HUABIO, Cat# R1207-1, 1:5000) separately. After washing three times with TBST, the membrane was incubated for 2 hours at room temperature with goat anti-mouse secondary antibody (1:10000). Finally, specific bands were detected using ECL luminescence reagent, and the results were analyzed and quantified using ImageJ software.

Immunofluorescence

In a 12-well plate, sterile coverslips were placed and covered with a layer of agarose. Subsequently, HEK293T cells were seeded, and after 24 hours, transfection was performed. The cells were transfected with either the WT(E100) or the K100 MC4R vector, both carrying the Myc tag. After 24 hours of transfection, the culture medium was removed, and cells were fixed with 4% formaldehyde in PBS for 30 minutes at room temperature. Next, the cells were divided into two groups. One group was permeabilized with 0.1% Triton X-100 for 20 minutes. Following permeabilization, both groups of cells were incubated with 5% bovine serum albumin (BSA) for 1 hour to block nonspecific binding sites. After blocking, cells were incubated overnight at 4 °C with Myc-Tag antibody. The next day, the antibody was washed away, and the cells were further incubated at room temperature for 2 hours with a fluorescently labeled secondary antibody iFluor 488 (HUABIO, Cat# HA1125) at a dilution of 1:500. Finally, Hoechst 33342 dye was added for nuclear staining, and the cells were incubated with the dye for 20 minutes. Slices were imaged using a laser confocal microscope, and the images were processed using FIJI. Results were obtained from three independent experiments.

Flow cytometry assay

The steps for flow cytometry to quantitatively determine the expression levels of MC4R are as follows: Place the cells in a culture dish and transfect them with 2000 ng of WT(E100) or K100 MC4R plasmids. After 24 hours, wash the cells with PBS, centrifuge at 1500 rpm for 5 minutes, and collect the cells in a 2.0 ml centrifuge tube. Fix the cells with 4% paraformaldehyde and incubate with blocking solution (5% BSA). After blocking, incubate the cells with Myc-Tag antibody (dilution 1:200) for 1 hour. After washing the cells, incubate them with fluorescently labeled secondary antibody iFluor 488 (dilution 1:500) for 2 hours. Perform flow cytometry analysis using a C6 flow cytometer to measure the fluorescence emitted by the cells. Calculate the expression levels of MC4R variants using a specific formula, expressed as a percentile of WT(E100) expression (Yan et al., 2022). The entire experiment is conducted at room temperature.

Isolation of sheep skeletal muscle satellite cells, RNA-sequencing, and bioinformatic analyses

Sheep skeletal muscle satellite cells (SCs) were isolated using previously established methods (Zhao et al., 2018; Chen et al., 2024). Briefly, hindlimb muscle tissues from fetal sheep were minced into 1 mm³ fragments and digested at 37 °C with 0.1% type I collagenase for 1 hour. The resulting cell suspension was filtered through a 70 μm cell strainer and centrifuged at 1500r/min for 10 minutes at room temperature to collect SCs. The isolated SCs were cultured in Dulbecco’s Modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F12) supplemented with 10% horse serum, 20% fetal bovine serum, and 1% penicillin/streptomycin. Cells were maintained at 37 °C in a humidified incubator with 5% CO₂. Once seeded in 6-well plates and reaching approximately 60% confluence, SCs were transfected with plasmids using Lipofectamine 3000 reagent (L3000015, Invitrogen, USA) according to the manufacturer’s instructions. After 24 hours of transfection, when SCs reached approximately 80% confluence, the growth medium was replaced with differentiation medium consisting of DMEM/F12 supplemented with 2% horse serum and 1% penicillin/streptomycin to induce myogenic differentiation in vitro. After 5 days of differentiation, total RNA was collected for RNA sequencing.

Total RNA was extracted using the RNeasy Plus Mini Kit (Qiagen) according to the manufacturer’s protocol. Differentially expressed genes (DEGs) between the two groups were identified using the NOISeq method, with a fold change threshold of ≥2 and a divergence probability of ≥0.8, as described by Tarazona et al. (2011). To explore the potential functions and regulatory pathways of the DEGs, Gene Ontology (GO) and pathway annotation and enrichment analyses were performed using the Gene Ontology Database (http://www.geneontology.org/) and the KEGG pathway database (http://www.genome.jp/kegg/), respectively.

Statistical analysis

EC₅₀ values were calculated using Prism software version 4 (GraphPad Software). Statistical calculations were performed by SPSS software version 24.0. For comparisons on EC₅₀, an unpaired T-test was used. Allele and genotype frequencies were calculated using direct gene counting. Nei’s method was applied to estimate population genetic parameters, including the polymorphism information content (PIC) and expected heterozygosity (He) (http://www.msrcall.com/Gdicall.aspx). The Hardy–Weinberg equilibrium (HWE) test was performed using the SHEsis platform (http://analysis.bio-x.cn). The association between the E100K variant and growth traits was assessed using one-way analysis of variance (ANOVA) implemented in SPSS software. A linear model describing the relationship between sheep genotypes and each growth trait was ­constructed following previously reported methods (Zhu et al., 2019).

Results

The polymorphism identification of sheep MC4R gene

The amplification was performed using the sheep-MC4R-F and R primers, resulting in an amplicon size of 1076 bp (Table 1). The missense mutation E100K (NC_056076.1, g.59480661G > A, P.Glu100Lys) was identified in the CDS regions of the LXBH sheep population (Figure 1A). The KASP primer for this site was developed, and the KASP genotyping method was utilized to genotype the MC4R E100K mutation. It was observed that the KASP genotyping outcomes were consistent with the sequencing outcomes for a subset of samples (Figure 1B). The amino acid at position 100 of the MC4R gene is glutamic acid (Glu) in all 16 species, and in sheep, the amino acid in that position mutates to lysine (Lys) (Figure 1C). This position is highly conserved across species, indicating its importance and functional significance. MC4R is a member of the family of G protein-coupled receptors and consists of a single polypeptide with seven α-helical transmembrane domains (TMs), an extracellular N terminus, three extracellular loops, three intracellular loops, and an intracellular C terminus (Chen et al., 2006). JPRED prediction revealed that the E100 residue is positioned within an α-helix region of MC4R protein. Notably, the E100K mutation occurs in the second transmembrane domain (TM2), as illustrated in Figure 1D.

Figure 1.

Sequence chromatograms of the E100K (g.59480661G>A, P.Glu100Lys) loci within MC4R gene and the transmembrane structure of MC4R protein. (A) DNA sequencing peak of the E100K (g.59480661G>A, P.Glu100Lys) mutation. (B) Cluster plot for the KASP genotyping assay. MC4R gene E100K (g.59480661G>A, P.Glu100Lys) loci GG allele (blue cluster), GA allele (green cluster), and AA allele (red cluster). (C) Sequence alignment of the amino acid at position 100 in 13 species. (D) MC4R protein highlighting amino acids affected by E100K variant. (http://wlab.ethz.ch/protter/start/).

The frequency of the sheep MC4R E100K site

We conducted an analysis to determine the relative frequency of the sheep MC4R E100K variant in various sheep breeds worldwide. These data include whole-genome sequencing data from 968 sheep and KASP genotyping data from 2151 sheep. This analysis was performed to gain a better understanding of the distribution and prevalence of the MC4R gene variant across different populations of sheep breeds. In this study, WGS analysis was conducted, revealing that the E100K polymorphism was detected in 8 out of 49 sheep breeds (Figure 2, Supplementary Table S1—see online supplementary material). In Chinese breeds, the E100K polymorphism was only detected in Hu sheep, and its frequency is relatively low (0.009). Among 24 breeds in the Middle East and Europe, the E100K mutation was identified in 7 breeds. It is noteworthy that Black Dorper sheep and Poll Dorset sheep exhibited a notably high mutation frequency for this polymorphism. Both Poll Dorset sheep and Black Dorper sheep are excellent meat sheep breeds known for their early growth and development, as well as good body mass. The distribution of E100K in different breeds may be associated with the growth conditions of sheep.

Figure 2.

The distribution of E100K (g.59480661G>A, P.Glu100Lys) across global populations.

The KASP genotyping results of six sheep breeds indicated the presence of the E100K mutation in LXBH, AUW, GQSFW, Hu, and WN sheep (Table 2). Furthermore, in these five sheep breeds, the genotype frequencies of this mutation were in accordance with HWE, with the GG genotype being the dominant genotype. The locus exhibited moderate polymorphism in LXBH sheep (PIC > 0.25), while in other breeds, it showed low polymorphism (PIC < 0.25). It is worth mentioning that GG, GA, and AA genotypes were identified in LXBH sheep, and the frequency of the A allele in this population was the highest (0.227).

Table 2.

The genetic diversity of MC4R E100K (g.59480661G>A, P.Glu100Lys) variant.

Breeds	Genotype frequency	Allelic frequencies	HWE P values	Ho	He	Ne	PIC
LXBH (n = 488)	GG (n = 338) GA (n = 125) AA (n = 25)	G (0.773) A (0.227)	0.937	0.649	0.351	1.542	0.290
AUW  (n = 431)	GG (n = 421) GA (n = 10) AA (n = 0)	G (0.988) A (0.012)	0.971	0.977	0.023	1.023	0.023
GQSFW  (n = 565)	GG (n = 561) GA (n = 4) AA (n = 0)	G (0.996) A (0.004)	0.996	0.993	0.007	1.007	0.007
WN  (n = 45)	GG (n = 44) GA (n = 1) AA (n = 0)	G (0.998) A (0.011)	0.997	0.978	0.022	1.022	0.022
Hu  (n = 333)	GG (n = 329) GA (n = 4) AA (n = 0)	G (0.994) A (0.006)	0.994	0.998	0..012	1.012	0.012
YSD  (n = 289)	GG (n = 289) GA (n = 0) AA (n = 0)	G (1.000) A (0)	1.000	1.000	0	1.000	0

Associations between the sheep MC4R E100K mutation and growth traits of the LXBH sheep

To investigate the effects of the mutation, we examined the relationship between MC4R genotypes and variations in body measurement traits in a population of 488 LXBH sheep. Three genotypes (GG, GA, and AA) of the sheep MC4R E100K mutation were identified in LXBH population. The results of the association analysis between the MC4R gene E100K mutation and growth traits in different age groups of LXBH sheep are shown in Table 3 and Supplementary Table S2 (see online supplementary material). The results showed that the E100K missense mutation was significantly correlated with body weight, chest depth, chest width, chest circumference, abdominal girth, chest width index and chest circumference index in adult LXBH sheep (P < 0.05, Table 3). In lambs, the mutation was significantly correlated with body height, hip width, body trunk index and cannon circumference index (P < 0.05, Table 3). The results of this study revealed a significant association between the AA(K100) genotype and higher values for most growth traits, indicating that individuals with the AA(K100) genotype had superior growth characteristics compared to those with the GG(E100) genotype (P < 0.05). The results of this study suggest that the sheep MC4R E100K loci may be involved in regulating growth traits in LXBH sheep.

Table 3.

Association analysis of MC4R E100K (g.59480661G>A, P.Glu100Lys) and growth traits in LXBH sheep.

	Traits	Genotypes (Mean ± SEM)			P Values
		GG (E100, n = 73)	GA (E100K, n = 31)	AA (K100, n = 10)
Adult	Body weight (kg)	65.74 ± 2.13b	72.23 ± 3.78b	83.20 ± 7.35a	0.019
	Chest depth (cm)	30.70 ± 0.51b	32.09 ± 0.80b	34.46 ± 1.81a	0.031
	Chest width (cm)	23.12 ± 0.57B	25.14 ± 0.87B	28.69 ± 1.87A	0.002
	Chest circumference (cm)	97.04 ± 1.22b	100.42 ± 2.19b	107.50±4.21a	0.017
	Abdominal girth (cm)	118.11 ± 1.26b	120.19 ± 1.19b	128.70 ± 2.74a	0.014
	Chest width index (%)	74.87 ± 1.15b	78.26 ± 1.93b	84.28 ± 5.29a	0.025
	Chest circumference index (%)	33.38 ± 0.794B	36.19 ± 1.09B	40.17±2.50A	0.005
		GG (E100, n = 71)	GA (E100K, n = 40)	AA (K100, n = 5)
	Body height (cm)	57.86 ± 0.46a	55.85 ± 0.66b	58.60 ± 0.92a	0.028
Lambs	Hip width (cm)	14.77 ± 0.32b	13.70 ± 0.487b	16.60 ± 0.81a	0.043
	Body trunk index (%)	116.85 ± 0.88a	119.26 ± 1.42a	109.59 ± 2.88b	0.030
	Cannon circumference index (%)	13.58 ± 0.18b	14.25 ± 0.27a	14.85 ± 0.51a	0.047

Note: The superscript letters A, B indicate highly significant differences (P < 0.01), while a, b indicate significant differences (P < 0.05).

E100K mutation affects the cell membrane surface expression and total expression of MC4R protein

In previous studies, it was observed that the expression levels of human MC4R E100 protein are downregulated after mutagenesis (Yang et al., 2009). Therefore, we investigated whether the E100K mutation in the sheep MC4R gene affects protein expression levels. HEK293T cells were transfected with recombinant vectors containing WT(E100) and K100 MC4R, and the expression of MC4R protein was examined under both stimulated and unstimulated conditions, as depicted in Figure 3A. The analysis results revealed a significant downregulation in receptor expression with the K100 mutation (Figure 3B), After stimulation with α-MSH, it was observed that the expression level of the K100 MC4R protein was downregulated (Figure 3C).To further explore the impact of this mutation on MC4R protein expression, flow cytometry was used to analyze the cell surface expression and total expression levels of WT(E100) and K100 MC4R proteins, as shown in Figure 3D. The expression of the K100 receptor on the cell membrane was significantly reduced (P < 0.05), and consistently, the total expression of the K100 receptor was also significantly decreased (P < 0.05, Figure 3E). To investigate whether the E100K mutation affects the membrane localization of MC4R protein, immunofluorescence staining using anti-Myc antibody was performed on HEK293T cells expressing WT(E100) and K100 recombinant plasmids. Imaging was conducted using laser confocal microscopy under both non-permeable (-) and permeable (+) conditions, as illustrated in Figure 3F. The results showed that both WT(E100) and K100 MC4R receptors can be expressed on the cell membrane, and the mutation does not impact receptor internalization.

Figure 3.

Effects of E100K MC4R on protein expression and receptor internalization. (A) Western blotting results of WT(E100) and K100 MC4R before (−) and after (+) stimulation by α-MSH. (B) Grayscale analysis results of WT(E100) and K100 proteins. (C) Grayscale analysis results of WT(E100) and K100 proteins after αMSH treatment. (D) Flow cytometry detected the cell membrane surface expression of WT(E100) and K100 MC4R proteins. (E) Flow cytometry detected the total expression of WT(E100) and K100 MC4R proteins. (F) Membrane localization of WT(E100) and K100 MC4R, localization of MC4R protein before and after cell permeability, staining with anti-Myc labeled antibody, confocal laser imaging using 100× oil mirror (scale: 20μm), blue for nucleus, (+) for triton permeability. *P<0.05, **P<0.01, ***P<0.001. Data represent mean ± SEM of three replicates (n = 3).

Functional characteristics of WT(E100) and mutant sheep MC4R in HEK293T cells

Previous studies have indicated that certain mutations on the MC4R receptor can affect the receptor’s basal activity and cAMP signal transduction (Lubrano et al., 2003; Lotta et al., 2019). Building upon this, we investigated the impact of the E100K mutation on receptor activation. Transfecting HEK293T cells with pGL4.29, pEGFP-N1, and either WT(E100) or K100 MC4R, followed by assessing constitutive activity (cAMP basal level) through a dual luciferase reporter gene assay without agonist stimulation (Figure 4A), revealed a significant reduction in basal cAMP production by the K100 MC4R receptor compared to WT(E100) (P < 0.05, Figure 4B).

Figure 4.

Effects of E100K MC4R on basal activity and cAMP signal activation. (A) Brief steps of the basal activity and cAMP signal transduction experiments. (B) Basal cAMP (%WT) mediated by WT(E100) and K100 MC4Rs. (C) Activation of cAMP signaling mediated by WT(E100) and K100 MC4Rs stimulated using α-MSH. (D) The α-MSH-stimulated cAMP response Rmax value of WT(E100) and K100 MC4Rs. (E) The α-MSH-stimulated cAMP response EC₅₀ (M) of WT(E100) and K100 MC4Rs. (F) Activation of cAMP signaling mediated by WT(E100) and K100 MC4Rs stimulated using β-MSH. (G) The β-MSH-stimulated cAMP response Rmax value of WT(E100) and K100 MC4Rs. (H) The β-MSH-stimulated cAMP response EC₅₀ (M) of WT(E100) and K100 MC4Rs. *P<0.05, **P<0.01, ***P<0.001. Data represent mean ± SEM of three replicates (n = 3).

The cAMP signaling activation of WT(E100) and E100K MC4R receptors was investigated using luciferase reporter systems, with stimulation by two agonists, α-MSH and β-MSH, in HEK293T cells transiently transfected with MC4R WT(E100) and K100 receptors (Figure 4A). Stimulation with α-MSH and β-MSH at concentrations ranging from 10⁻¹⁰ to 10⁻⁵ revealed dose-dependent signaling capabilities, as depicted in Figure 4C and F. Both WT(E100) and K100 receptors exhibited dose-dependent responses to ligand stimulation. Data from concentration-response experiments were fitted to non-linear regression models to calculate the response value of each ligand at the receptor mutation (Rmax) and the ligand’s potency at the receptor mutation (EC₅₀). As shown in Figure 4D and G, the Rmax value of cAMP for the K100 receptor significantly decreased under stimulation by both agonists. The E100K mutation in the MC4R gene led to a substantial reduction in α-MSH binding affinity and potency. Specifically, under α-MSH stimulation, the signaling potency (EC₅₀) of K100 MC4R was determined to be 0.36 ± 0.23 µM, significantly higher than that of the WT(E100) receptor (P < 0.05, Figure 4E). This result was similarly confirmed in the response to β-MSH stimulation, where the cAMP activity of the K100 receptor decreased to 90% of that observed for WT(E100) MC4R (P < 0.05, Figure 4H). The specific Rmax and EC₅₀ values are presented in Table 4.

Table 4.

The signaling properties of WT(E100) and K100 MC4Rs in response to ligand stimulation.

Ligand		cAMP response
		EC50 (µM)	Rmax(%WT)
α-MSH	WT (E100)	0.0056 ± 0.0001A	100.00 ± 10.00A
	K100	0.36 ± 0.23B	31.83 ± 2.10B
β-MSH	WT (E100)	0.15 ± 0.01A	100.00 ± 1.20A
	K100	1.38 ± 0.32B	55.22 ± 2.20B

Note: The superscript letters A and B indicate highly significant differences (P < 0.01) between the groups.

The transcriptional regulation of sheep MC4R E100K mutant

Subsequently, pcDNA3.1, WT (E100), and K100 MC4R plasmids were transfected into sheep skeletal muscle SCs. Samples were collected for transcriptome sequencing to investigate the patterns of DEGs and their associated pathways (n = 4). The numbers of upregulated and downregulated genes in the three comparison groups are shown in Figure 5A. Filtering the transcriptome sequencing data revealed 142 DEGs in the pcDNA3.1 vs. WT comparison, including 28 significantly upregulated and 114 significantly downregulated genes (Figure 5B). In the WT vs. K100 group, 81 peaks of upregulated genes and 33 peaks of downregulated genes were identified (Figure 5C). Similarly, the pcDNA3.1 vs. K100 group showed 57 upregulated peaks and 54 downregulated peaks (Figure 5D). The heatmap illustrates the expression patterns of DEGs in the pcDNA3.1 vs. WT and WT vs. K100 comparisons (Figure 5E and F). GO analysis showed that the DEGs in the pcDNA3.1 vs. WT group were significantly enriched in categories such as G-protein coupled receptor binding, peptide receptor activity, G-protein coupled peptide receptor activity, chemokine receptor binding, and cytokine receptor binding (Figure 5G). In contrast, DEGs in the WT vs. K100 group were enriched in biological processes including MAP kinase tyrosine/serine/threonine phosphatase activity, MAP kinase phosphatase activity, and receptor agonist activity (Figure 5H). Using the KEGG database for pathway enrichment analysis of DEGs, the most significantly enriched pathways in the pcDNA3.1 vs. WT comparison included the TNF signaling pathway, cytokine-cytokine receptor interaction, regulation of lipolysis in adipocytes, and the NF-kappa B signaling pathway (Figure 5I). In the WT vs. K100 comparison, the mutated MC4R receptor primarily impacted the MAPK signaling pathway (Figure 5J). Additionally, transcriptome analysis after transfecting WT and K100 MC4R vectors into 293 T cells showed that DEGs were enriched in biological processes such as response to cAMP and activin receptor binding. The most significantly enriched pathways included the PPAR signaling pathway, osteoclast differentiation, and the MAPK signaling pathway (Supplementary Figure S1—see online supplementary material for a colour version of this figure).

Figure 5.

RNA sequencing to analyze the regulation of E100K MC4R on downstream signaling pathways in sheep skeletal muscle satellite cells (n = 4). (A) Number of DEGs across three comparison groups. (B–D) Volcano plots: upregulated significantly downregulated genes in pcDNA3.1 vs. WT MC4R, WT MC4R vs. K100 MC4R and pcDNA3.1 vs. K100 MC4R. (E–F) Heatmap: upregulated and downregulated DEGs in pcDNA3.1 vs. WT MC4R and WT MC4R vs. K100 MC4R. (G–H) GO analysis of DEGs in pcDNA3.1 vs. WT MC4R and WT MC4R vs. K100 MC4R. (I–J) KEGG pathway analysis in pcDNA3.1 vs. WT MC4R and WT MC4R vs. K100 MC4R.

Discussion

The MC4R gene plays a pivotal role in regulating food intake and energy expenditure in mammals, and multiple mutations have been reported to influence growth and developmental traits. Functional characterization of these variants is essential for establishing causal links between specific mutations and their associated phenotypes (Fan et al., 2008). In livestock species, particularly sheep, the increasing demand for animal products has intensified efforts to improve economically important traits and to identify key genes contributing to growth performance (Wang et al., 2025). Numerous growth- and reproduction-related genes have been identified in sheep (Cui et al., 2022; Lu et al., 2020; Gebreselassie et al., 2019), and increasing attention has been directed toward understanding how mutations within these genes affect phenotypic variation. Although MC4R variants have been associated with growth traits in sheep, the cytological mechanisms underlying these mutations remain insufficiently understood.

In this study, we identified a naturally occurring missense mutation in the sheep MC4R gene, E100K (g.59480661G > A, p. Glu100Lys), which is associated with improved growth traits. The AA (K100) genotype showed superior performance compared with the GG (E100) genotype, and this allele was present at relatively high frequencies in some large-bodied sheep breeds. Functional analyses revealed that the E100K substitution reduces MC4R protein expression, lowers basal receptor activity, and weakens agonist-induced signaling, indicating a partial LoF effect. Such impaired MC4R activity is consistent with increased body weight in individuals carrying the K100 allele (Figure 6; Graphical summary).

Figure 6.

Graphical summary.

In this study, we found that the MC4R E100K (g.59480661G > A, p. Glu100Lys) mutation occurs at a relatively high frequency in several large-bodied sheep breeds, including Black Dorper and Poll Dorset. All three genotypes (GG, GA, and AA) were also detected in LXBH sheep, a multi-fetal meat sheep breed developed using Blackhead Dorper as the sire and Small-tailed Han sheep as the dam (Liu et al., 2022). Consistent with the WGS results, the allele frequency reached 0.6 in Black Dorper and remained relatively high (0.227) in LXBH sheep, indicating potential population or regional differences in the distribution of this variant. Furthermore, association analysis in LXBH sheep demonstrated that individuals with the AA (K100) genotype exhibited significantly higher body weight, body height, chest circumference, and chest width compared with those carrying the GG (E100) genotype, suggesting superior growth performance. These results imply that the E100K mutation may serve as a useful genetic marker for improving growth traits in sheep breeding. The E100K mutation is situated within the TM2 domain of the MC4R receptor. As the TM2 domain is particularly crucial for maintaining the stability of the entire seven transmembrane (7TM) bundle, thereby regulating both its function and agonistic metal ion binding. Previous mutagenesis studies indicate that TM2 is involved in agonist binding and signaling (Chen et al., 2006; Chen et al., 2007; Yang et al., 2009), based on this, we speculate that the E100K mutation in the MC4R gene may affect the receptor’s function, but the specific impact remains to be further investigated.

Previous studies have shown that MC4R expressed in HEK293T can stimulate transcription when stimulated with different levels of melanocortin analogues, and cAMP signal pathways can be detected using a CRE-mediated reporter gene transcription activity assay (Kim et al., 2002). The similarity between human MC4R and sheep MC4R is 92.7%, so we also explored the regulatory effect of this mutation in 293 T cells. In this study, we demonstrated that the E100K mutation in the sheep MC4R gene reduces the protein expression level, basal activity, and agonist binding efficiency of the MC4R receptor, playing a crucial role in determining the growth traits of sheep. We speculate that the E100K mutation represents a LoF mutation. Consistent with this, MC4R negatively regulates feed intake and body weight and plays a pivotal role in energy homeostasis (Gonçalves et al., 2018; Krashes et al., 2016). Moreover, MC4R deficiency in mice has been shown to increase both fat and lean mass (Huszar et al., 1997), and our results align with these observations. The MC4R LoF mutation in human was associated with greater body weight, higher BMI, and increased fat mass, with carriers having higher rates of overweight or obesity (Wade et al., 2021). In animals, some LoF mutations of MC4R have been identified. For instance, in pigs, a missense variant (P.Asp298Asn) in MC4R reduces receptor constitutive activity, cell surface expression, and cAMP production, and is associated with growth and obesity (Kim et al., 2004; Zhang et al., 2020). This variant is significantly linked to increased test daily gain, higher lean meat percentage, and lower backfat thickness (Jokubka et al., 2006). In goats, the MC4R gene LoF mutation (p.I204M) alters function by impairing constitutive activity and signaling, potentially regulating appetite (Wade et al., 2021).

We conducted transcriptomic analyses to investigate the impact of the E100K mutation on gene expression and pathways associated with organismal growth and development. Key genes such as KLF15, GATA3, HOXB7, and EEF1A1, were identified as potentially critical mediators of the regulatory effects of the E100K mutation on sheep growth traits (Almalki et al., 2016; Gao et al., 2023; Liu et al., 2024). Consistent with our experimental findings, which demonstrated that the E100K mutation affects receptor activation, GO enrichment analysis revealed significant impacts on processes including response to cAMP and activin receptor binding. Moreover, previous studies have shown that MC4R contributes to the activation of the MAPK pathway (Chu et al., 2012). In sheep skeletal muscle SCs and 293 T cells, the K100 MC4R variant was found to alter the expression of specific genes within the MAPK pathway, suggesting that the E100K mutation may modulate MAPK signaling downstream of MC4R. We observed a high degree of conservation at the E100 amino acid position in 16 species. Additionally, the residue glutamic acid 100 (E100) is highly conserved across the entire MCR family (Yun et al., 2015). This suggests a crucial functional role for this site. Consistent with this speculation, previous studies have indicated that the E100 amino acid of MC4R gene plays a significant role in agonist/antagonist binding and signal transduction (Chen et al., 2007; Yang et al., 2009). Previous research, utilizing homology models and structure-activity relationships of peptide agonists, identified E100 in TM2 as a crucial amino acid in the binding site of MC4R (Hogan et al., 2006). E100, located in an ion-binding pocket, is known to be essential for the signal transduction of human MC4R gene. Through site-specific mutagenesis, the conserved amino acid at position 100, Glu (E), is mutated to Ala (A). Subsequently, the expression level of NDP-MSH and the binding affinity of the mutant receptor are significantly lower than that of human MC4R-WT (Chen et al., 2007). Similarly, the E100A mutation significantly reduces the binding affinity of the mutated MC4R receptor for THIQ and almost completely abolishes α-MSH signaling (Yang et al., 2009; Israeli et al., 2021; Fatima et al., 2022). Indeed, a common feature of GPCRs is that mutations occurring at highly conserved functional residues can alter receptor function. For MC4R, substitutions in conservative amino acid residues such as D122 (TM3), D126 (TM3), F254 (TM6), W258 (TM6), F261 (TM6), and H264 (TM6) have been shown to reduce cAMP production (Yang et al., 2009). This research contributes to the molecular understanding of how the E100K mutation in the conserved amino acid of the MC4R gene influences the growth traits of sheep.

This study provides the first functional evidence of the MC4R E100K mutation in sheep. However, this study still has several limitations. The association analysis was conducted only in the LXBH sheep population. Given the substantial differences in allele frequencies and selection histories among sheep breeds, validation in larger and more genetically diverse populations will be necessary to assess the stability and universality of the E100K mutation across different genetic backgrounds. Second, the functional characterization of the E100K mutation in this study relied primarily on in vitro systems, including HEK293T cells and sheep skeletal muscle SCs. Although these models provide valuable mechanistic insights, they cannot fully replicate the complex physiological environment in vivo. Future studies involving knock-in models in sheep or mice will help to clarify the physiological effects of this mutation and to verify its potential value for breeding applications.

Overall, by integrating population-level association analysis, in vitro functional assays, and transcriptomic profiling, we provide a comprehensive understanding of how MC4R E100K variant influences growth traits. These findings not only elucidate the molecular mechanisms underlying MC4R-mediated growth regulation but also highlight the potential application of E100K as a genetic marker in sheep breeding programs.

Conclusion

In conclusion, this study identifies and functionally characterizes a naturally occurring missense mutation (E100K) in the sheep MC4R gene. We demonstrate that this mutation is significantly associated with multiple growth traits, including body weight, body height, chest width, and chest depth. Functional assays further confirm that the E100K variant leads to a partial loss of MC4R activity, thereby providing mechanistic insights into how natural genetic variation modulates growth performance. Collectively, these findings deepen our understanding of MC4R-mediated growth regulation in sheep and offer valuable genetic information for future molecular breeding programs.

Abbreviations: 

AUW

Australian White sheep

CDS

coding sequence

CRE

cAMP-responsive element

DEGs

differentially expressed genes

GO

Gene Ontology

GoF

gain-of-function

GPCR

G protein-coupled receptor

GQSFW

Guiqian semi-fine wool sheep

KASP

kompetitive allele specific PCR

KEGG

Kyoto Encyclopedia of Genes and Genomes

LoF

loss-of-function

LXBH

Luxi Blackhead sheep

MC4R

nelanocortin-4 receptor

Pre-POMC

pre-proopiomelanocortin

SNP

single nucleotide polymorphism

WGS

whole genome sequencing

WN

Weining sheep

YSD

Yuansheng dairy sheep

Author Contributions

Yuta Yang (Conceptualization, Data curation, Investigation, Methodology, Software, Validation, Writing—original draft, Writing—review & editing), Peiyao Liu (Conceptualization, Investigation, Software, Validation, Writing—original draft), Taotao Yan (Conceptualization, Investigation, Validation, Writing—original draft), Xiangding Wang (Conceptualization, Writing—original draft), Qian Zhou (Conceptualization, Data curation, Methodology, Software, Writing—original draft), Yang Li (Methodology, Writing—review & editing), Ran Li (Methodology, Writing—review & editing), Qingfeng Zhang (Methodology, Writing—review & editing), Chuanying Pan (Conceptualization, Supervision, Writing—review & editing), and Xianyong Lan (Conceptualization, Funding acquisition, Methodology, Supervision, Validation, Writing—original draft, Writing—review & editing)

Supplementary Data

Supplementary data are available at Journal of Animal Science online.

Conflict of interest statement. The authors declare no conflict of interest.

Data Availability

All data associated with this study are presented in the paper and its supplemental materials.