A 19 bp Indel of the PLAG1 as a Potential Marker for Growth Performance in Indonesian Ongole Cattle

Beef cattle production plays a strategic role in supporting national food security and meeting the increasing demand for animal-derived protein in Indonesia. Nevertheless, domestic beef production remains insufficient to satisfy national consumption requirements, resulting in a supply deficit of approximately 263 thousand tons annually (BPS, 2024). Enhancing the genetic merit of local cattle populations is therefore considered one of the most sustainable long-term approaches for improving productivity, feed efficiency, carcass quality, and adaptation to tropical production environments (Azovtseva et al., 2024). Recent advances in livestock genomics have further accelerated the implementation of genomic-assisted breeding strategies aimed at improving economically important traits in beef cattle under diverse environmental conditions (Li et al., 2024).

Indonesian Ongole cattle, a Bos indicus derived breed widely distributed in Indonesia, are recognized for their adaptability to hot and humid climates, resistance to environmental stressors, and ability to survive under low-input production systems (Putri et al., 2021; Irma et al., 2025). Despite these adaptive advantages, PO cattle generally exhibit moderate growth performance and carcass productivity compared with specialized commercial beef breeds. Improvement of productive efficiency in PO cattle requires an integrated approach involving nutrition, management, and genetics. Among these factors, genetic background exerts substantial influence on body conformation, growth rate, carcass composition, and feed utilization efficiency (Zhou et al., 2019; Borges et al., 2025). Consequently, identification of functional genetic markers associated with growth-related phenotypes has become increasingly important for accelerating genetic improvement in Indonesian tropical cattle populations.

Molecular breeding approaches, particularly marker-assisted selection (MAS), enable the incorporation of DNA polymorphisms into conventional selection programs to improve breeding accuracy and shorten generation intervals (Lamido et al., 2024). Among candidate genes associated with bovine growth traits, Pleomorphic adenoma gene 1 (PLAG1) has received considerable attention due to its pleiotropic effects on body size, carcass traits, and reproductive performance. The PLAG1 gene, located on bovine chromosome 14 (BTA14), encodes a zinc-finger transcription factor involved in the regulation of insulin-like growth factor pathways, cellular proliferation, embryonic development, and skeletal growth (Takasuga, 2016; Fink et al., 2017). Functional studies have demonstrated that PLAG1 regulates growth-associated pathways through modulation of IGF2 expression and related endocrine mechanisms (D’Occhio et al., 2024). Variants within or near PLAG1 have consistently been identified as major quantitative trait loci (QTL) affecting stature, body weight, carcass composition, and puberty traits in cattle populations worldwide (Karim et al., 2011; Fortes et al., 2012; Engle and Hayes, 2022). In addition, recent evidence indicates that PLAG1 may also contribute to muscle development, adipogenesis, and meat quality regulation through interactions with metabolic signaling pathways (Yu et al., 2025).

Several polymorphisms within PLAG1, including single nucleotide polymorphisms (SNPs) and insertion/deletion (indel) variants, have been associated with economically important growth traits across Bos taurus and Bos indicus breeds. Previous studies reported significant associations between PLAG1 variants and body measurements in Brahman cattle (Trilaksono et al., 2024), body weight in Madura and Bali cattle (Hartati et al., 2026), and skeletal development traits in Chinese cattle populations (Xu et al., 2018; Zhong et al., 2019). However, despite the economic and genetic importance of PO cattle, information regarding PLAG1 polymorphisms and their association with growth performance in this breed remains limited. Furthermore, the effects of PLAG1 variants appear to be breed-dependent, likely due to differences in genetic background, linkage disequilibrium structure, and environmental adaptation (Kowalewska et al., 2024; Trilaksono et al., 2024). Therefore, the present study aimed to evaluate the association of two PLAG1 polymorphisms, namely g.48308C>T and the g.32212 19 bp indel, with growth-related traits in Indonesian Ongole cattle. The findings of this study are expected to provide additional insight into the genetic architecture of growth traits in Indonesian cattle and support the future implementation of PLAG1-based molecular markers in tropical beef cattle breeding programs.

A total of 101 Indonesian Ongole cattle maintained at the Institute for Good Breeding Practice and Green Animal Fodders (BPTU-HPT) Sembawa, Indonesia, were included in this study. All animals were clinically healthy and managed under a semi-intensive production system. The daily ration consisted of approximately 3 kg of commercial concentrate and 30 kg of fresh forage grass per animal.

Phenotypic records included birth weight, body length, withers height, chest girth, hip height, corrected body weight at 750 days, mature body weight, and average daily gain (ADG). Morphometric traits were recorded according to the routine performance recording protocol of BPTU-HPT Sembawa at standardized ages, thereby minimizing age-related variation among animals. These measurements were selected because they are widely used indicators of growth performance, skeletal development, and carcass production potential in beef cattle.

Genomic DNA was isolated from whole blood samples using a commercial extraction kit (Geneaid Biotech Ltd., Taiwan) following the manufacturer’s instructions with slight optimization. Approximately 300 μL of blood was transferred into a 1.5 mL microtube and mixed with three volumes of red blood cell (RBC) lysis buffer. The suspension was allowed to stand for 10 minutes at room temperature and then centrifuged at 3,000 rpm for 5 minutes to remove the supernatant. The resulting pellet was resuspended in 100 μL of RBC lysis buffer and mixed with 200 μL of GB buffer to lyse the cells completely. The tube was incubated at 60°C for 10 minutes with gentle inversion every few minutes. Afterward, 200 μL of absolute ethanol was added to the lysate and vortexed briefly before being transferred to a GD spin column placed in a 2 mL collection tube. The column was centrifuged at 14,000–16,000 rpm for 5 minutes to bind DNA to the membrane. The column was then washed twice, first with 400 μL of W1 buffer and then with 600 μL of wash buffer, each followed by short centrifugation to remove impurities. To ensure complete removal of ethanol, the column was centrifuged again for 3 minutes at maximum speed. Finally, the column was placed in a new 1.5 mL microtube, and 100 μL of pre-warmed elution buffer (60°C) was added to release the DNA. After a 3-minute incubation, the tube was centrifuged at 14,000 rpm for 30 seconds. The purified genomic DNA was then stored at –20°C for downstream analyses, including PCR amplification and genotyping.

Two polymorphic loci within the PLAG1 gene, namely g.48308C>T and g.32212 (19 bp indel), were amplified using the primer pairs listed in Table 1. Polymerase chain reactions (PCR) were performed in a final volume of 25 μL containing 12.5 μL of 2× MyTaq HS Red Mix (Bioline, UK), 1 μL of each primer, 1 μL of genomic DNA, and 9.5 μL of nuclease-free water (Promega, USA). Amplification was carried out in a MiniAmp® Thermal Cycler (Thermo Fisher Scientific, Singapore) under the following conditions: Initial denaturation at 95°C for 5 min; 35 cycles of 95°C for 30 s, 60°C for 30 s, and 72°C for 30 s; followed by a final extension at 72°C for 10 min. PCR products were separated on 1.5% agarose gels prepared in 1× TAE buffer, stained with FluoroSafe, and visualized under ultraviolet illumination. Fragment sizes were estimated using a 100 bp DNA ladder (Figure 1).

Genotyping was performed using PCR–restriction fragment length polymorphism (PCR-RFLP) and fragment size analysis. For the g.32212 (19 bp indel), the insertion (I) allele generated a 142 bp fragment, whereas the deletion (D) allele generated a 123 bp fragment (Figure 1A). Consequently, the DD genotype was identified by a single 123 bp band, the ID genotype by two bands (142 and 123 bp), and the II genotype by a single 142 bp band (Figure 1B).

For the g.48308C>T polymorphism, the 628 bp PCR product was digested with SacII (Figure 2A). The CC genotype produced two fragments of 522 and 106 bp, the TT genotype remained undigested and yielded a single 628 bp fragment, whereas the CT genotype displayed three fragments of 628, 522, and 106 bp (Figure 2B). Genotypes were assigned according to the resulting electrophoretic patterns.

Table 1: Primer pairs targeting two polymorphisms of PLAG1.

Pairwise linkage disequilibrium (LD) between the g.48308C>T SNP and the g.32212 (19 bp indel) was estimated using Haploview version 4.2 (Barrett et al., 2005). LD was quantified using Lewontin’s standardized disequilibrium coefficient (D′) and the squared correlation coefficient (r²).

Allele and genotype frequencies were calculated according to Nei and Kumar (2000), and deviations from Hardy–Weinberg equilibrium (HWE) were assessed using the chi-square (χ²) test.

Associations between PLAG1 genotypes and growth traits were evaluated using the following mixed linear model implemented in MINITAB 19.1:

Yᵢⱼ = μ + Gᵢ + Sⱼ + eᵢⱼ

Where Yᵢⱼ is the observed phenotypic value, μ is the overall mean, Gᵢ is the fixed effect of genotype, Sⱼ is the random effect of sire, and eᵢⱼ is the random residual error.

Morphometric traits were recorded within a standardized age range under the institutional performance recording system. Therefore, age at measurement was not included as a covariate. Statistical significance was declared at P < 0.05, and differences among least-squares means were compared using Tukey’s honestly significant difference (HSD) test.

Because the g.32212 (19 bp indel) locus exhibited a highly unbalanced genotype distribution, a post-hoc power analysis was conducted for chest girth based on the observed effect size. The difference between DD and ID genotypes (2.72 cm) corresponded to a large standardized effect (Cohen’s d ≈ 0.80). Under unequal sample sizes (n = 89 and n = 12) and α = 0.05, the estimated statistical power ranged from 0.70 to 0.75. Although sufficient to detect moderate-to-large effects, this power remained below the conventional threshold of 0.80 and therefore warrants cautious interpretation of the observed association.

Genotyping successfully identified polymorphisms at two loci of the PLAG1 in PO cattle population. For the g.48308C>T locus, three genotypes were detected, CC (n = 16), CT (n = 50), and TT (n = 35), while for the g.32212 (19 bp indel) locus, two genotypes were observed, DD (n= 89) and ID (n= 12) (Table 2). The g.48308C>T locus exhibited moderate genetic variation, as indicated by the balanced distribution among homozygous and heterozygous genotypes. In contrast, the g.32212 locus showed a predominance of the DD genotype, suggesting a lower level of polymorphism.

Table 2: Allele and genotype frequencies for PLAG1 polymorphisms.

Table 3: Association of PLAG1 polymorphism g.48308C>T with growth traits in PO cattle population.

The association between the g.48308C>T polymorphism of the PLAG1 and growth-related traits is presented in Table 3. Statistical analysis revealed no significant differences (P> 0.05) among genotypes (CC, CT, and TT) for any of the evaluated phenotypic traits.

The association analysis of the g.32212 (19 bp indel) polymorphism with growth traits is summarized in Table 4. A nominally significant association (P = 0.042) was observed between the g.32212 (19 bp indel) and chest girth, with DD genotypes showing larger mean values than ID genotypes. Given the highly unbalanced genotype frequencies, this result should be interpreted as suggestive rather than definitive. Other traits, including birth weight, withers height, hip height, corrected body weight at 750 days, mature body weight, body length, and ADG, did not differ significantly (P > 0.05) between genotypes.

Pairwise LD analysis performed using Haploview revealed weak linkage disequilibrium between the g.48308C>T SNP and the g.32212 (19 bp indel), with D′ and r² values of 0.22 and 0.002, respectively (Figure 3). These results indicate a low degree of non-random association and virtually no correlation between the two loci, suggesting that they segregate largely independently in the PO cattle population.

Table 4: Association of g.32212 (19 bp indel) of the PLAG1 with growth traits in PO cattle population.

The Pleomorphic adenoma gene 1 (PLAG1) encodes a zinc-finger transcription factor involved in the regulation of growth, development, somatic cell proliferation, and skeletal formation (Wang et al., 2022). Variants within or near PLAG1 have been consistently associated with economically important traits, including body size, carcass composition, and reproductive performance across livestock species (Li et al., 2019; Zhong et al., 2019; Mia et al., 2022). Given its pleiotropic role, PLAG1 has emerged as one of the most important candidate genes influencing growth-related traits in cattle.

In the present study, the g.32212 (19 bp indel) polymorphism was significantly associated with chest girth in PO cattle, with animals carrying the DD genotype exhibiting larger chest girth than those with the ID genotype. Chest girth is an important indicator of thoracic development, body capacity, and carcass production potential (Buchanan et al., 2002). This finding agrees with previous studies reporting associations between PLAG1 polymorphisms and growth-related traits in cattle. For example, Trilaksono et al. (2024) reported significant effects of the g.48308C>T SNP and the 19 bp indel on body weight and chest girth in Brahman cattle, whereas Cahyadi et al. (2022) demonstrated that an intronic PLAG1 variant influenced body length in Bali cattle. Collectively, these findings support the involvement of PLAG1 in skeletal growth and body conformation in Indonesian cattle breeds.

The biological relevance of the 19 bp indel is further supported by studies conducted in other cattle populations. Xu et al. (2018) identified the same indel in multiple Chinese cattle breeds and reported significant associations with growth traits, suggesting that this variant, or a closely linked functional mutation, may contribute to skeletal development. Similarly, Zhou et al. (2019) demonstrated that the 19 bp indel was widely distributed across 37 Chinese native breeds and significantly associated with body height and chest circumference. Together with the present results, these studies indicate that the PLAG1 19 bp indel may represent a conserved source of genetic variation influencing body size in cattle.

Despite the observed association, the results should be interpreted cautiously due to the highly unbalanced genotype distribution at the g.32212 locus, characterized by the absence of the II genotype and the low frequency of heterozygotes. The insertion allele frequency was only 0.059, yielding an expected II genotype frequency of approximately 0.35% under Hardy–Weinberg equilibrium. Consequently, fewer than one II individual would be expected in the sampled population, indicating that the absence of this genotype is likely attributable to low allele frequency and limited sample size rather than biological lethality or strong negative selection. Similar genotype distributions have been reported in Bos indicus-derived cattle populations carrying the same polymorphism (Xu et al., 2018; Trilaksono et al., 2024).

The skewed genotype distribution may also reduce statistical power and increase susceptibility to Type I error, particularly in association studies involving low-frequency variants (Edwards et al., 2005; Serdar et al., 2021). Nevertheless, post-hoc analysis indicated that the observed association with chest girth was accompanied by a relatively large effect size (Cohen’s d ≈ 0.80), partially compensating for the reduced power associated with unequal sample sizes. Moreover, consistent associations of the same 19 bp indel with growth- and body size-related traits across independent cattle populations provide additional biological support for the observed relationship (Xu et al., 2018; Zhou et al., 2019; Mia et al., 2022). Nonetheless, validation in larger populations remains necessary before this variant can be confidently incorporated into marker-assisted selection programs.

In contrast, no significant association was detected between the g.48308C>T SNP and any of the evaluated growth traits. This discrepancy may be explained, at least in part, by the weak linkage disequilibrium observed between the two PLAG1 polymorphisms (D′ = 0.22; r² = 0.002). Although both variants are located within the same gene, the extremely low r² value indicates that the 3′ UTR SNP does not effectively tag the 19 bp indel in the studied population. Therefore, the association observed for the indel is unlikely to be attributable to linkage with the g.48308C>T SNP and more likely reflects an independent genetic signal or linkage with another functional variant within the PLAG1 region.

Several genomic studies provide additional support for the role of PLAG1 in growth regulation. Song et al. (2016) identified a pleiotropic quantitative trait nucleotide within the PLAG1–CHCHD7 region that explained a substantial proportion of variation in multiple carcass traits in Simmental cattle. Furthermore, Li et al. (2019) reported genotype-dependent differences in PLAG1 mRNA expression among tissues and developmental stages, suggesting that sequence variation within this region may influence growth through transcriptional regulation. Likewise, Hou et al. (2020) demonstrated associations between PLAG1 variants and adult body height in Chinese cattle, supporting the notion that PLAG1 exerts stronger effects on skeletal development and mature body size than on early-life growth traits.

Recent evidence also indicates that PLAG1 influences traits beyond body size. Engle and Hayes (2022), using genomic data from 2,839 Australian Brahman cows, reported significant associations between PLAG1 variants and both growth and fertility traits, suggesting that the gene contributes to endocrine pathways affecting somatic and reproductive development. In addition, Wang et al. (2023) showed that PLAG1 copy number variations were associated with body size traits in goats, highlighting the conserved biological role of PLAG1 across ruminant species and emphasizing the potential importance of structural variants, including indels, in regulating growth-related phenotypes.

The absence of association for the g.48308C>T SNP may reflect limited statistical power, breed-specific linkage disequilibrium patterns, or interactions between genetic background and environmental conditions. Previous studies have demonstrated that the phenotypic effects of PLAG1 variants vary among cattle breeds and production systems (Engle and Hayes, 2022). Furthermore, PLAG1 generally exerts stronger effects on mature stature and skeletal dimensions than on juvenile growth traits (Karim et al., 2011; Fortes et al., 2012), which may explain the lack of detectable effects for several traits evaluated in the present study.

Overall, the results suggest that the PLAG1 g.32212 (19 bp indel) polymorphism may contribute to variation in chest girth in PO cattle. Combined with evidence from Brahman, Bali, and Chinese cattle populations, the findings further support the role of PLAG1 as an important growth-related gene in cattle. However, because of the limited sample size and highly unbalanced genotype distribution, the observed association should be regarded as preliminary until confirmed in larger populations. Future studies incorporating larger datasets, genome-wide association analyses, and functional genomic approaches will be valuable for elucidating the molecular mechanisms through which PLAG1 influences growth, body conformation, and production traits in tropical cattle.

This study confirmed polymorphisms at two PLAG1 loci in PO cattle. The g.32212 (19 bp indel) variant showed a significant association with chest girth in PO cattle, indicating potential relevance to body measurement. However, due to limited genotype balance, this finding should be considered preliminary and requires validation in larger populations before application in breeding programs. Further study using larger populations, additional PLAG1 variants, and whole-genome association approaches (GWAS) is recommended to validate these findings.

This study was funded by RKAT Universitas Sebelas Maret for Fiscal Year 2025 under the Penelitian Unggulan Terapan (PUTA-UNS) with Research Assignment Agreement Number: 369/UN27.22/PT.01.03/2025. The authors sincerely thank the staff of the Institute for Good Breeding Practice and Green Animal Fodders Sembawa (BPTU-HPT Sembawa), Indonesia, for their valuable assistance during blood sample collection and phenotypic data recording. Their technical expertise and dedication were essential to the successful completion of this study.

This study is the first to evaluate the effects and linkage disequilibrium of the PLAG1 g.48308C>T SNP and the 19 bp indel in Indonesian Ongole cattle. It demonstrates a breed-specific association of the 19 bp indel with chest girth and provides new genetic evidence supporting the potential application of PLAG1 in marker-assisted selection for beef cattle breed.

DDP: Writing original draft, investigation, formal analysis, data curation. AERM: Methodology, Formal analysis. WP: Writing review and editing, validation, funding acquisition, supervision. YY: Validation, funding acquisition, formal analysis. SS: Validation, funding acquisition, formal analysis. HK: Investigation, data curation. MI: Investigation, data curation. MC: Writing review and editing, validation, methodology, funding acquisition, conceptualization, supervision.

All animal procedures related to blood collection were reviewed and approved by the Research Ethics Commission of the National Research and Innovation Agency (BRIN), Indonesia, under approval number 81/Klirens/X/2021.

The authors declare that no generative AI and AI assisted technology was used in the creation of this manuscript.

The authors have declared no conflict of interest.