Molecular markers associated with growth, meat, and carcass traits in sheep: a review

Abstract

Sheep breeding has been a fundamental aspect of livestock farming for thousands of years, supplying humans with wool, meat, and milk. As the livestock sector adapts to contemporary needs, the increasing global demand for animal products, fueled by population growth, highlights the significance of effective breeding techniques. Growth and meat traits are a key factor in sheep breeding, directly impacting resource efficiency and breeder profitability. In this review, we have explored the advantages of molecular marker-assisted selection (MAS) and its specific applications in breeding meat sheep. We summarized research on quantitative trait loci (QTLs) and genome-wide association studies (GWAS), as well as variations in key genes, including myostatin (MSTN), insulin-like growth factor 1 (IGF-1), and calpastatin (CAST), associated with growth, meat quality, and carcass traits in sheep. The advancements in molecular breeding for meat sheep, along with improvements in sheep genetics, genomic selection, and genome editing, have enhanced our understanding of DNA markers and demonstrated the genetic diversity present in meat sheep, significantly enriching sheep breeding strategies. Improvements in sample size, phenotyping efficiency, and the integration of omics studies could enhance our understanding of gene interactions, enabling MAS technology to reach its full potential.

Introduction

Sheep breeding is one of the oldest and most significant branches of livestock farming, providing humans with wool, meat, and milk for thousands of years. Moreover, sheep farming is particularly profitable due to the hardy and low-maintenance nature of these animals, which thrive primarily on nutrient-rich pasture. Their resilience not only enhances the economic viability of sheep breeding but also highlights its sustainability and efficiency.¹ As livestock farming continues to evolve to meet modern demands, the rising worldwide need for animal-based products, driven by population growth, underscores the importance of efficient breeding methods. In the past, breeding practices primarily relied on natural selection, where only the strongest and most productive animals were chosen for reproduction. However, modern advancements have enabled the integration of scientific methods that refine genetic traits and improve breeding efficiency.^2,3

One efficient approach to achieving improved livestock productivity is marker-assisted selection (MAS). MAS is an indirect approach to trait selection, where the choice is made based on genetic markers associated with the desired characteristic rather than the trait itself.⁴ This method aims to integrate genetic data from markers and quantitative trait loci (QTLs) with phenotypic information to enhance the accuracy of genetic evaluation and selection (Fig. 1). A major advantage of MAS is that it directly assesses the genetic composition of an animal, measuring the influence of specific genes on productivity rather than relying solely on observable traits. Molecular markers play a crucial role in MAS, with several types being widely utilized. The most prevalent molecular markers include restriction fragment length polymorphisms (RFLP), single nucleotide polymorphisms (SNPs), amplified fragment length polymorphisms (AFLP), random amplified polymorphic DNA (RAPD), simple sequence repeats (SSR) or microsatellites, etc.⁵ Among these, SNPs and insertions/deletions (InDels) are particularly noteworthy as common genetic markers. Recent research has also underscored the significance of structural variations (SVs), such as copy number variations (CNVs), particularly in sheep, which can be larger in scale and may exert a more pronounced influence on phenotypic traits.⁶ For instance, Ladeira et al.⁷ identified significant CNVs that were associated with meat and carcasss traits in sheep.

Figure 1.

Steps of marker-assisted selection (MAS).

MAS is most effective for traits that have low heritability, particularly when a significant portion of the additive genetic variance is linked to the marker loci.⁸ Growth and meat traits are a key factor in sheep breeding, directly impacting resource efficiency and breeder profitability. Like other quantitative characteristics, these traits are influenced by a complex interplay of genetic factors and environmental conditions such as nutrition and herd management. A deeper understanding of the genetic foundation of growth and carcass-related traits is essential, as it allows for more precise selection strategies. This, in turn, contributes to improved muscle development and ultimately greater meat production. Therefore, our objective is to provide a summary of studies related to growth, meat quality, and carcass traits, with a particular emphasis on molecular markers in meat sheep breeding.

QTL and GWAS studies for growth, meat and carcass traits

In the last decade, genome-wide association study (GWAS) has been recognized as more promising and informative. GWAS is a further development of the marker-associated selection method and is based on the use of genetic markers distributed throughout the genome and in linkage disequilibrium (LD) with at least one of the QTL. Large-scale genotyping with whole-genome coverage became possible after the development of the OvineSNP50 BeadChip. However, the quantity of QTL studies conducted on sheep is comparatively low when contrasted with those on other livestock.

SNPs in calpain 6 (CAPN6), integrin subunit alpha 11 (ITGA11), and SCM (Sushi-CCM) domain containing 1 (SCMH1) were associated with body weight in Hu sheep, with CAPN6 exhibiting differential expression in the biceps femoris and longissimus dorsi muscles.⁹ KIT ligand (KITLG), cell adhesion molecule 2 (CADM2), multiple C2-like domains 1(MCTP1), collagen type IV alpha 6 chain (COL4A6) have been found to have significant correlations with body heights in Hu sheep. Additionally, luciferase reporter gene assays demonstrated that these four SNPs can significantly influence gene transcription activity.¹⁰ Genes (e.g., ACSL5, CNTN3, DCLK1, DCT, EFCAB14, FAM184B) were associated with body weight traits in Texel*Kazakh sheep crossbreeds.¹¹ Furthermore, several genes such as growth hormone receptor (GHR) and serine/threonine kinase 32B (STK32B), which are directly linked to growth and development, as well as others like aldolase, fructose-bisphosphate A (ALDOA) and fat mass and obesity associated (FTO) that are more involved in metabolic processes, were found to be associated with growth and meat characteristics.¹² Recent GWAS study identified IGFBP6, ST7, SCD5, FTO, FGF12, DTNBP1 genes for growth traits such as live weight, bicoastal diameter, rump width, heart girth, cannon bone circumference in Kazakh Saryarka sheep.¹³ Furthermore, multiple GWAS have identified genes (e.g., RAB6B, Tf, GIGYF2, MTPN, HYDIN, LRGUK, ZFP90, ATP8A2, PLXDC2) linked to body conformation traits in Iranian breeds.^14,15

Nuclear cap binding protein G (NCAPG) that plays a role in the cell cycle and lactate dehydrogenase A-like protein (LCORL), which is involved in cellular metabolism, were identified on ovine OAR6 to be associated with body weight and size traits.^2,3,16,17 These genes were primarily identified in Merino lineage breeds, and further research could focus on these genes to explore their functions in greater detail. The detailed information on QTLs associated with growth, meat, and carcass traits are provided in Table 1.

Table 1.

QTLs Associated with growth, meat, and carcass traits.

Genes	Variation	Breed and sample size	Traits	Sources
OAR2_117,959,202, OAR2_11804335, OAR19_8,995,957.1, s40847.1	SNPs	Texel × Lleyn (n = 1429)	Carcass traits measured by video image	18
RAB6B, Tf, GIGYF2	SNPs	Lori-Bakhtiari (n = 132)	Birth weight	15
MTPN, HYDIN, LRGUK, ZFP90	SNPs	Baluchi (n = 96)	8-month body weight	19
FOSL2, TGFBI, KCND2, LECT2, TRAK1, LOC101102529 TMEM117	SNPs	Luzhong mutton (n = 277)	Body weight and conformation traits	20
ANKRD44, MACF1, SYN3, DCAF16, FAM184B, NCAPG, LCORL, FUK	SNPs	Alpine Merino (n = 1310)	Live weight	2 , 3
CAPN6, ITGA11, SCMH1	SNPs	Hu (n = 240)	Body weight	9
KITLG, CADM2, MCTP1, COL4A6	SNPs	Hu (n = 202)	Body size traits	10
IGFBP6, ST7, SCD5, FTO, FGF12, DTNBP1	SNPs	Kazakh Saryarka sheep (n = 100)	Live weight, bicoastal diameter, rump width, heart girth, cannon circumference	Dossybayev et al. (2024)
ACSL5, CNTN3, DCLK1, DCT, EFCAB14, FAM184B, GLIS1, GPC5, GRB14, KIAA0513, KIAA1328, LRP1B, MED28, NPHP1, PCDH7, PTPRK, PTPRT, RYR3, TUBB6, ZBTB20	SNPs	Texel and Kazakh Crossbred (n = 578)	Body weight traits	11
APOBR, FTO, ALDOA, STK32B, FAM190A, GHR, POL, RPL7, MSL1, SHISA9	SNPs	Chinese Mongolian fat-tailed (n = 61), German Mutton Merino (n = 161), African white Dorper (n = 100)	Body mass index, meat traits, pre-weaning gain	12
NPPC, ADAMTS1, FBN1	SNPs	Akkaraman (n = 192)	early liveweight traits	21
ATP8A2, PLXDC2	SNPs	Lori-Bakhtiari (n = 130)	Postweaning weight traits	14
OAR6: LAP3, NCAPG, LCORL	SNPs	Australian Merino sheep (n = 1781)	Body weight	16
OAR6: OST/ SPP1, MEPE, IBSP, LCORL, NCAPG;	SNPs	Scottish Blackface lambs (n = 600)	Growth, in vivo carcass traits	17
OAR3: EFEMP1, SPTBN1, FSHR, OAR24: SH2B1, MAPK3, TBX6, KIF22, IL4R, IL21R, OAR1: KAT2B
TP53, BMPR1A, PIK3R5, RPL26, PRKDC	SNPs	Frizarta (n = 524)	Body size traits	22
SLC9C1, VSTM2A, FRG1	SNPs	Hulunbuir (n = 799)	Growth traits	23

Major genes/loci associated with growth, meat quality and carcass traits

Molecular markers in the hypothalamus–pituitary (HP) axis pathway

The hypothalamus-pituitary axis is integral to regulating growth and meat traits in livestock through the secretion of various hormones that influence growth, metabolism, reproduction. This axis involves a complex interplay between the hypothalamus, the pituitary gland, and various target organs.²⁴

The hypothalamus secretes growth hormone-releasing hormone (GHRH), which stimulates the pituitary gland to release growth hormone (GH). GH promotes growth by stimulating the liver and other tissues to produce insulin-like growth factor 1 (IGF-1), which is essential for cell growth and differentiation. IGF-1 exerts its effects by binding to the IGF-1 receptor (IGF-1R). This binding triggers the receptor’s intrinsic tyrosine kinase activity. Upon IGF-1R activation, insulin receptor substrate 1 (IRS1) is phosphorylated on tyrosine residues (see Fig. 2). Phosphorylated IRS1 recruits phosphatidylinositol 3-kinase (PI3K), which converts phosphatidylinositol 4,5-bisphosphate (PIP2) to phosphatidylinositol 3,4,5-trisphosphate (PIP3). The increase in PIP3 leads to the recruitment and activation of phosphoinositide-dependent kinase 1 (PDK1). PDK1 phosphorylates and activates protein kinase B (AKT) (Fig. 2). This activation is the phosphorylation of forkhead box O (FoxO) transcription factors. Phosphorylated FoxOss are required for the transcriptional regulation of the ubiquitin ligases atrogin-1, and muscle ring finger 1 (MuRF1), leading to the ubiquitylation of muscle proteins. AKT also promotes the activation of the mammalian target of rapamycin complex 1 (mTORC1), a key regulator of cell growth and protein synthesis. mTORC1 in turn stimulates protein synthesis, which leads to increased translation of mRNAs involved in muscle growth. Besides, activated Akt phosphorylates glycogen synthase kinase 3 beta (GSK3β) at specific serine residues (Ser9 in humans), leading to its inactivation. Inhibition of GSK3β promotes cell survival, growth, and metabolism by preventing the degradation of various proteins.²⁵

Figure 2.

The mechanism of actions of some important genes in myoblasts. Myostatin exerts its effects primarily through the activation of the SMAD signaling pathway. IGF-1 exerts its effects by binding to the IGF-1 receptor (IGF-1R) and further triggers a series of intracellular signaling Cascades. Calpain facilitates myoblast differentiation and muscle formation through protein degradation, while calpastatin modulates calpain activity to ensure that these processes occur in a controlled manner (see details in the text).

Considering the crucial role of IGF-1 in muscle development, researchers investigated the relationship between its variations and growth as well as muscle traits in sheep. For instance, Su et al.²⁶ reported that the expressions of the IGF-1 were associated with meat quality traits such as muscle fiber diameter and muscle fiber shear stress. It was reported that the polymorphism in exon 3 of ovine IGF1 may serve as a potential gene marker for certain carcass and growth traits, such as hot carcass weight and growth rate to weaning.²⁷ In Santa Ines sheep, polymorphisms in IGF-1 and GH genes had an additive effects on carcass traits such as loin weight, rib weight and yield, internal carcass length, rump girth, etc.²⁸ Furhtermore, genotypes of IGF-1 and IGFR1 genes were associated with birth weight and height, body length, chest girth at weaning, average daily gain in Hulun Buir sheep.²⁹ In addition, the A allele of the g.857G > A variant was related to the to higher body weights.³⁰

At the GHR gene, the SNP was related to the body weight, cannon circumference, body length, chest circumference in male sheep.³¹ Later studies focused on identification of InDels in the GHR, GHRH, and GHRHR in Chinese sheep breeds, such as Hu, Small-tail Han sheep, Tong and Lanzhou fat-tailed, Duolang, Bashibai, Altay sheep, where they found a significant association with several growth traits.³² Similarly, Akhatayeva et al.³³ also reported significant association of InDels with growth traits in Luxi-black head sheep. Moreover, pituitary-specific transcription factor 1 (POU1F1), also known as Pit-1, is a transcription factor that plays a crucial role in the regulation of GH and other hormones involved in growth and development. Variations in POU1F1 may influence the levels of GH produced, thereby affecting growth rates, body weight, and overall size. POU1F1 genotypes showed significant effects on weaning weight in Iranian breeds.³⁴

The activity of the hypothalamus-pituitary axis can be influenced by nutrition and environmental conditions, including temperature, photoperiod, and stress. Adequate nutrition supports optimal hormone production and function, leading to better growth and meat quality. Understanding the variations in these genes can help in breeding and management practices aimed at improving meat production efficiency and quality.

Markers associated with muscle development and myostatin signaling

The myostatin (MSTN) gene, which encodes the myostatin protein, is a member of the transforming growth factor-beta (TGF-β) superfamily and is a critical negative regulator of muscle growth. Myostatin exerts its effects primarily through the activation of the SMAD signaling pathway (see Fig. 2). When myostatin binds to its receptor (ActRIIB), it activates the SMAD2 and SMAD3 proteins, which translocate to the nucleus and regulate the expression of key myogenic regulatory factors such as MyoD and myogenin, which are essential for muscle cell differentiation and growth. In response to various stimuli, calcium ions enter the muscle cells. Myostatin signaling can lead to the inhibition of the Akt pathway. The inhibition of Akt leads to decreased mTORC1 activity, which in turn reduces protein synthesis in muscle cells. This can contribute to muscle wasting conditions. While direct inhibition of Akt signaling by myostatin, in turn activates FOXO transcription factors, leading to increased expression of Atrogin-1 and MuRF1, which are involved in the ubiquitin-proteasome pathway for muscle protein degradation. In addition, IGF-1 regulates the myostatin pathway primarily through the activation of the AKT/mTOR pathway, which inhibits myostatin expression and its muscle growth-inhibiting effects, promoting muscle hypertrophy and overall growth.³⁵

The findings by Boman et al.³⁶ indicated that the c.960delG mutation in the MSTN gene significantly affects meat and fat characteristics more than the c.2360G > A mutation, which is consistent with the latter’s role in reducing myostatin protein levels to about one-third due to translational inhibition, as shown through protein blotting (Table 2). It was observed that the allele ‘A’ was associated with decreased carcass traits, whereas the presence of the allele ‘B’ was associated with increased carcass traits.³⁸ Another study identified total of 28 nucleotide substitutions were identified from nucleotide c.-1199 in the promoter region to c.*1813 and including the well-described substitution c.*1232G > A (g + 6223G > A) in New Zealand sheep breeds. However, their effect on growth or muscle traits were not tested.⁴⁰ In Egyptian and Saudi Arabia sheep breeds, SNPs, including c.18 G > T and c.241 C > T were significantly associated with birth weight and average daily weight gain.³⁹ Later, Pan et al.⁴¹ found that Charolais lambs with CC and CT genotypes showed better performance in weight and chest width, whereas individuals with the TT genotype excelled in tube circumference and limb length, indicating that genetic differences at this locus may affect lamb growth and development. Polymorphisms in the MSTN gene’s first intron and well-known c.*1232G > A position was determined in Colored Polish Merino sheep, revealing five alleles (MSTN-A, MSTN-B, MSTN-C, MSTN-E, and MSTN-E1) and significant associations between these genetic variations and various carcass, meat quality, and biometric traits.⁴² Sheep with the c.-2449GC genotype exhibited higher loin meat and proportion yields than those with the c.-2449GG genotype, while the c.-2379CC genotype was linked to increased birth, tailing, and weaning weights compared to c.-2379TC, but did not affect growth rate.⁴³

Table 2.

Genes associated with growth and meat traits in sheep.

Genes	Breeds and sample sizes	Traits	Effect	Sources
IGF-1	New Zealand Romney (n = 848)	Growth and carcass traits	p < 0.05	27
	Munjal sheep (n = 50)	conformational traits	p < 0.05	37
	Harnali sheep (n = 110)	performance traits	p < 0.05	30
	Santa Ines lamb (n = 191)	Carcass traits	p < 0.05	28
	Hulun Buir lambs (n = 229)	Growth traits	p < 0.05	29
IGFR	Hulun Buir lambs (n = 229)	Growth traits	p < 0.05	29
GH	Santa Ines lamb (n = 191)	Carcass traits	p < 0.05	28
GHR	Chinese breeds (n = 969)	Growth traits	p < 0.05	32
	Luxi Blackhead sheep (n = 646)	Growth traits	p < 0.05	33
	Hu sheep (n = 375), Tan sheep (n = 31), Dorper (n = 82)	Growth traits	p < 0.05	31
GHRHR	Chinese breeds (n = 969)	Growth traits	p < 0.05	32
POU1F1	Iranian breeds (n = 180)	Growth traits	p < 0.05	34
MSTN	Norwegian White (n = 121)	Carcass traits	p < 0.05	36
	New Zealand Romney (n = 517)	Carcass traits	p < 0.05	38
	Barki (n = 17), Rahmani (n = 21), Ossimi (n = 22), Najdi (n = 15)	Growth traits	p < 0.05	39
	NZ Romney (n = 72), Coopworth (n = 12), Corriedale (n = 12), Dorper (n = 12), Perendale (n = 12), Suffolk (n = 12), Merino (n = 12), Dorset Down (n = 19), Coopdale (n = 7), Poll Dorset (n = 21), Texel (n = 10), other crossbreeds (n = 17)	–	–	40
	Charolais (n = 604), Australian White (n = 160), Charolais*Han (n = 120), Australian*Han (n = 120)	Body size traits	p < 0.05	41
	Polish Merino (n = 106)	Carcass traits	p < 0.05	42
	New Zealand Romney (n = 357)	Growth and carcass traits	p < 0.05	43
	Santa Inês (n = 192)	Meat pH and tenderness	p < 0.05	44
CAST	Lori-Bakhtiari (n = 243), Zel breed (n = 175), Zel-Atabay cross-bred (n = 40), Chall (n = 29),	–	–	45
	European breeds (n = 317)	Meat quality and carcass traits	p < 0.05	46
	Edilbay breed (n = 100)	Slaughter qualities and meat chemical composition	p > 0.05	47
	1/2 Poll Dorset × 1/2 North-Caucasian meat-and-wool crossbreed (n = 91)	Meat quality	p > 0.05	48
	commercial abattoir (n = 132)	Meat tenderness	p > 0.05	49
	Sonid (n = 378)	fatty acid composition of the longissimus thoracis muscle	p < 0.05	50 , 51
	Awassi (n = 87)	Final body weight and longissimus muscle width	p < 0.05	52
	Wool and hair sheep (n = 142)	Body weight	p < 0.05	53
CAPN3	Merino × Garut (n = 85)	Birth weight	p < 0.05	54
	New Zealand Romney (n = 513)	Meat yield	p < 0.05	55
CAPNS1	Polish Merino (n = 105)	Carcass traits	p < 0.05	56
DGAT1	New Zealand sheep (n = 120), Southdown (n = 87)	Meat traits	p < 0.05	57
	Iranian sheep (n = 309)	Carcass traits	p < 0.05	58
	Texel lambs (n = 461)	Carcass traits	p < 0.05	59
BMPRIB	Chinese breeds (n = 1.875)	Growth traits	P < 0.0005	60
	Suhu meat sheep (n = 2241)	Body weight, body size	p < 0.05	61
MCR4	Hu sheep (n = 206)	Body measurements	p < 0.05	62
	Colombian hair sheep (n = 168)	Body weight	p < 0.05	63
	German Merino sheep (n = 32)	Growth and meat	p < 0.05	64
FABP4	New Zealand Romney lambs (n = 749)	Carcass traits	p < 0.05	65
GSKIP	New Zealand Romney (n = 840)	Growth and carcass	p < 0.05	66
MYF5	grassland short-tailed sheep (n = 533)	Growth and ultrasound traits	p < 0.05	67
UCP1	New Zealand Romney (n = 314)	Carcass traits	p < 0.05	68
	New Zealand Romney (n = 587), Texel (n = 236)	Carcass traits	p < 0.05	69
LPIN1	New Zealand Romney (n = 242)	Birth weight and carcass traits	p < 0.05	70 , 71
KIAA1217, SNTA1	Ujumqin sheep (n = 642)	Growth traits	p < 0.05	72

Furthermore, the MSTN gene was one of the primary targets edited using CRISPR-Cas9 technology, leading to the development of several transgenic sheep with enhanced muscle growth characteristics. The research by Crispo et al.⁷³ effectively employed CRISPR/Cas9 technology to create myostatin knock-out sheep, leading to successful gene editing, a lack of myostatin, and greater body weight in comparison to their wild-type counterparts. The MSTNDel73C mutation, in conjunction with FGF5 knockout, may influence the proliferation and myogenic differentiation of skeletal muscle satellite cells by regulating FOSL1 expression and activity through the MEK1/2-ERK1/2-FOSL1 pathway, ultimately impacting muscle phenotype in sheep.⁷⁴ Using the single cell clone method, MSTN-Cas9/gRNA4 positive cell lines were created, and following SCNT, 3 transgenic sheep with MSTN gene deletion were produced, achieving a pregnancy rate of 40%.⁷⁵ The C-CRISPR system effectively produced MSTN knockout Hu sheep exhibiting a double-muscled phenotype, demonstrating its potential as a valuable tool for enhancing breeding in livestock.^50,51 In addition, using TALEN technology and somatic cell nuclear transfer (SCNT), researchers successfully created MSTN biallelic knockout Small-Tail Han sheep that developed normally and displayed enhanced body weight and muscle growth.⁷⁶

Markers in protein turnover and meat tenderness pathways

Calpain plays a crucial role in various cellular processes, including muscle protein turnover and meat tenderness. Calpastatin (CAST) encodes the calpastatin protein, a specific inhibitor of calpain, a family of calcium-dependent cysteine proteases.⁷⁷ The regulation of calpain activity by calpastatin is particularly important in the context of meat quality and carcass traits. In response to various stimuli, calcium ions enter the muscle cells. The increase in intracellular calcium concentration activates calpain. Activated calpain then cleaves various substrates, including structural proteins (like titin, nebulin) that are part of the muscle fibers, signaling proteins that can alter cell signaling pathways and apoptotic factors that can lead to muscle cell death. Meanwhile, calpastatin is expressed in muscle cells and binds to active calpain, preventing it from degrading essential muscle proteins. During muscle stress conditions, the expression of calpastatin can be upregulated to protect muscle integrity.⁷⁸

Previous research primarily utilized PCR-RFLP and PCR-SSCP techniques to identify variations in the CAST gene. For example, the PCR-SSCP method revealed seven variations among Iranian sheep breeds, highlighting significant differences in two haplotypes between thin-tailed and fat-tailed breeds⁷⁸. It has been reported that lambs of synthetic meaty lines possessing the ‘AA’ CAST genotypes exhibited the greatest muscle percentage and the least fat percentage in their hind legs, while rams with the ‘AC’ genotypes had the highest levels of intramuscular fat in their loins, which suggests advantageous benefits and practical applications in meat sheep MAS.⁴⁶ Moreover, recent study revealed that the mutations, such as c.1210C > T and c.1437G > A, are correlated with certain fatty acid compositions and classes in the longissimus lumborum of grazing Sonid sheep. Additionally, the c.646G > C (G216R) and c.1210C > T (R404C) missense mutations were predicted to affect the Calpain inhibitory domains of the CAST gene.^50,51 Several studies showed that CAST gene polymorphisms affected body weights in sheep.^52,53 However, some works found insignificant associations between the genotypes of CAST gene and meat quality traits.^48,49 The study indicated that the ‘AA’ of CAST was predominant in the Edilbay breed, suggesting indirect selection for this genotype during its development. Despite minor differences in key traits, rams with the AB genotypes exhibited more intensive growth and greater nutrient accumulation in their muscle tissues.⁴⁷

Calpain small subunit 1 (CAPNS1) encodes a small subunit of calpain, which is essential for the activity of calpain enzymes. The CAPNS1 genotypes were significantly related to meat quality parameters in Polish Merino lambs.⁵⁶ Meanwhile, calpain 3 (CAPN3) variations were associated with birth weight and carcass traits.^54,55 Genetic variations in these genes can influence growth rates and muscle composition, which directly relate to meat yield and quality in sheep.

Summing up, the CAST gene’s effects are likely more pronounced in lambs due to their active muscle development and growth phase, where the gene’s regulation of muscle quality traits can have a significant impact. As sheep mature, these effects may diminish, leading to a focus on lamb meat traits in research and breeding efforts.

Additional molecular markers linked to growth and carcass traits

Diacylglycerol o-acyltransferase 1 (DGAT1) is an enzyme involved in lipid metabolism, particularly in the synthesis of triglycerides from diacylglycerol and acyl-CoA.^70,71 This enzyme plays a significant role in fat storage and energy metabolism, which can indirectly influence muscle traits. An intronic SNP (rs411875883) has been significantly linked to fat thickness, rib-eye area, live weight measurements, etc. and ‘TT’ animals exhibited lower values, while ‘CC’ animals had higher values in Texel sheep.⁵⁹ Moreover, the B1 variant in intron 1 of the DGAT1 gene was associated with enhanced loin meat yield in New Zealand sheep, indicating its potential as a valuable gene marker for enhancing meat characteristics.⁵⁷ Another study identified that sheep with the ‘CC’ genotype at the DGAT1 locus exhibited significantly greater fat-tail weight and backfat thickness compared to other genotypes, highlighting the positive influence of the ‘C’ allele on these traits in fat-tailed sheep.⁵⁸

Recognizing the crucial role of the bone morphogenetic protein receptor type 1B (BMPR1B) gene in reproduction, several studies have investigated its association with growth traits across various sheep breeds.^60,61 For instance, Su et al.⁶¹ revealed that FecB mutation in the BMPRIB gene has negative effect on body weight and body size in 2241 Suhu meat sheep. This gene is part of the bone morphogenetic protein (BMP) signaling pathway, which is important in bone and cartilage development.

Furthermore, loci in the melanocortin 4 receptor gene (MCR4) were related to body weight and meat traits.^62–64 The MC4R is a member of the melanocortin receptor family and is primarily expressed in the central nervous system, particularly in regions of the hypothalamus that are critical for appetite regulation.⁷⁹

Several genes (e.g., fatty acid binding protein 4 (FABP4), uncoupling protein 1 (UCP1), and lipid phosphate phosphatase 1 (LPIN1)) that play significant roles in lipid metabolism and energy regulation, were associated with carcass traits in sheep.^65,68–71 Nevertheless, the current association analysis between gene variations and meat traits in sheep remains insufficient to advance industry developments.

Challenges and future directions

Although MAS in sheep breeding is a powerful tool that leverages genetic markers to improve growth and quality traits, multiple studies on GWAS and association analyses have relied on small sample sizes, which may compromise the reliability of their findings. Therefore, increasing the sample size is crucial for enhancing the robustness of the studies. Additionally, a significant challenge is addressing the bottlenecks in phenotyping for MAS. The use of technologies like imaging, automated measurement tools, and sensor-based systems can enhance both the accuracy and efficiency of the phenotyping process. Moreover, phenotypic traits can be significantly affected by environmental factors such as nutrition, housing, and management practices. This variability can obscure genetic influences and complicate the identification of reliable markers. Conducting phenotypic assessments across various environments can help mitigate the impact of environmental variability. Besides, development of more accurate models that account for environmental factors will enhance the effectiveness of MAS. These approaches enable the identification of stable genetic markers that perform well under different conditions.

Furthermore, identifying and understanding the interactions among the genes that are responsible for particular traits remains a challenge. To address the challenge, the researchers should consider implementing the integrative genomic approaches. Incorporating transcriptomics, proteomics, and metabolomics alongside genomics can provide a more holistic understanding of the biological mechanisms underlying traits of interest.⁸⁰ By employing these approaches, we can better understand the complexities of gene interactions and their contributions to various traits. Also, utilizing big data analytics and artificial intelligence in breeding programs can improve decision-making processes and enhance the predictive power of genetic evaluations.

Advancements in genomic technologies, such as CRISPR/Cas9, could improve the accuracy of genetic evaluations and facilitate targeted modifications in breeding programs. Most gene editing research in sheep has concentrated primarily on the MSTN gene due to its significant impact on meat traits. However, this focus has led to the neglect of other potentially important genes. The ability to edit specific genes allows breeders to achieve desired traits in fewer generations, accelerating the breeding process. This can be particularly beneficial in meat sheep production, where market demands can change rapidly. Thus, to enhance the effectiveness of MAS in meat sheep breeds, it is crucial to expand research efforts to include a broader range of genes. This comprehensive approach could lead to more effective strategies for improving meat quality and production traits in sheep.

Last but not least, breeding programs may increasingly focus on traits related to sustainability, such as feed efficiency, lower greenhouse gas emissions, and resilience to climate change.

Conclusion

MAS is an efficient approach to achieve improved livestock productivity. In our study, we noted that while numerous investigations have concentrated on the variations of MSTN, CAST, and IGF-1 genes associated with meat and carcass traits, many of these studies relied on relatively small sheep populations. To fully harness the potential of MAS, it is essential to increase sample sizes, employ advanced phenotyping techniques, integrate omics data, and conduct further research on CRISPR/Cas9 applications. These enhancements could lead to more effective strategies for improving meat quality and production, allowing MAS technology to realize its full capabilities.

Funding Statement

This work was supported by the grant funding for scientific projects for 2024–2026 of the Ministry of Education and Science of the Republic of Kazakhstan AP23489419 ‘The use of the genetic potential of the Edilbay breed to improve the productive qualities of the Degeres sheep breed’.

Disclosure statement

The authors declare no conflict of interest.