Goat farming remains a vital contributor to the livelihoods of millions of small-scale and marginal farmers worldwide (Jaber et al., 2025). Particularly in resource-limited and ecologically vulnerable areas, goats have emerged as a reliable source of nutrition, income and social security (Aslam et al., 2023). Their capacity to adapt to diverse agro-climatic conditions, low feed requirements and multi-purpose utility for meat, milk, manure and hides make them indispensable to integrated farming systems (Singh et al., 2023; Meza-Herrera  et al., 2024). In the context of climate-resilient agriculture, goat production is increasingly recognized as a vital component of sustainable livestock development (Koluman, 2023; Kerven, 2024). According to the 20^th Livestock Census (BAHS, 2019), the India is home to approximately 148.88 million goats, representing approximately 27.8% of the total livestock population and recording a 10.14% growth since the previous census. These animals contribute approximately 13.53% of the total meat and 3.0% of the milk production in the country, thereby significantly supporting the animal protein supply chain (Singh et al., 2023). Beyond economics, goats also serve essential cultural and ritualistic functions in many Indian communities, particularly among tribal populations. 
       
Among India’s diverse goat breeds, the Assam Hill goat is particularly important in the northeastern Hill ecosystem. Known for its adaptability to mountainous terrain, early maturity, higher litter size and good meat quality, it serves as a critical genetic resource for low-input production systems (Gawat et al., 2023; Sarma et al., 2025). However, productivity under traditional systems remains suboptimal, with both genetic and non-genetic factors significantly influencing post-weaning growth and morphometric traits in Assam Hill goats (Sarma et al., 2019). Genetic improvement in goats is essential for enhancing growth, reproduction and adaptability. While phenotypic selection has been widely used, its progress is slow and influenced by environmental factors (Siddiki et al., 2020). Marker-assisted selection (MAS) relies on the identification of functional gene polymorphisms associated with economically important traits and has been successfully applied in goats using candidate genes such as IGF-1 and POU1F1 (Singh et al., 2023; Dige et al., 2020). MAS relies on the identification of functional gene polymorphisms associated with economically important traits. This approach has been successfully used in several goat improvement programs both globally and within India. 
       
One of the most promising candidate genes for growth and reproductive traits is the PROP1 (Prophet of Pit-1) gene, a transcription factor crucial for the development of the anterior pituitary and the regulation of multiple hormones, including Growth Hormone (GH), Prolactin (PRL) and Thyroid Stimulating Hormone (TSH). Genetic variations in PROP1 and its downstream pituitary transcription factors, including POU1F1, are associated with growth and production traits in goats, influencing body weight, milk yield and overall productivity (Liu et al., 2015; Zhou et al., 2016; Dorjay and Abraham, 2021). In goats, polymorphisms in PROP1 have been associated with bodyweight, average daily gain, weaning weight and litter size, which are critical productivity indicators (Ma et al., 2017; Jafari et al., 2014). Although genomic tools have been widely explored in several goat breeds (Ahlawat et al., 2015; Gipson, 2019), there remains a clear knowledge gap regarding the genetic architecture and functional polymorphisms of the PROP1 gene in the Assam Hill goat. Despite its importance as a hardy, underutilized genetic resource, limited or no systematic studies have investigated the association of PROP1 variants with growth and reproductive traits in this breed. Addressing this gap is essential for designing region-specific genomic selection strategies. Integrating PROP1 gene markers into breeding programs supports the early identification of genetically superior individuals and accelerates genetic gains. Such programs can enhance the productivity, profitability and sustainability of goat farming, particularly for marginal farmers in the northeastern and eastern regions of India, where goat rearing is a significant source of livelihood. Ultimately, this approach will contribute not only to the conservation and improvement of indigenous goat breeds but also to the resilience of livestock production systems in climate-sensitive regions.

Study location and sampling
 
The study involved 147 Assam Hill goats reared in their native breeding tracts of Meghalaya and Assam. Animals were selected based on defined criteria, including good health, absence of close genetic relatedness and strict conformity to established breed characteristics. For accurate morphometric assessment, each animal was positioned on a flat, levelled surface to ensure proper vertical measurements. To evaluate growth performance and morphological development, key biometric traits, including body weight (BW), body length (BL), withers height (WH) and chest girth (CG), were measured at 3, 6, 9 and 12 months of age. These measurements were carried out following the standardized phenotypic characterization guidelines recommended by the FAO (2012) for the assessment of animal genetic resources.
 
Blood collection and DNA extraction
 
Approximately 3-4 mL of blood was collected aseptically from the jugular vein into sterile EDTA-coated tubes. Samples were immediately cooled and stored at -20°C until DNA extraction was performed. Genomic DNA was extracted using the Qiagen DNeasy Blood and Tissue Kit and the DNA integrity was confirmed via 1.3% agarose gel electrophoresis. DNA samples were then prepared at 50  ng/µL for polymerase chain reaction (PCR) analysis.
 
Primer design and PCR amplification
 
The complete PROP1 gene sequence (Capra hircus) was retrieved from GenBank (NC_030814.1). Primers targeting exon 2 were designed using Primer 3 (v0.4.0) and synthesized by Eurofins Genomics (India). PCR amplification comprised a 25/ µL reaction containing 50  ng genomic DNA, 0.5 µM of each primer, 9.5 µL nuclease-free water and 12.5 µL Dream Taq Green PCR Master Mix. The thermocycler program was as follows: initial denaturation at 94°C for 3 min; 34 cycles of 94°C for denaturation, 60.3°C for annealing (45 s) and 72°C for extension (1 min), followed by a final extension at 72°C for 7 min. PCR products were resolved on 2% agarose gel in 1 x TAE buffer (Fig 1). Selected amplicons were sequenced and analyzed using Chromas software to identify sequence polymorphisms.


 
Genotyping via PCR-RFLP
 
SNPs identified from the sequence analysis were screened with NEB Cutter v2.0, identifying a g.1860C>T variant with a StuI restriction site. For genotyping, the PCR products were digested with 2 U of StuI at 37°C for 12 hours. Digestion products were separated on a 3.2% agarose gel stained with ethidium bromide to assess genotype patterns (Fig 2). 

​
 
Genetic diversity and bioinformatics analysis
 
Genetic parameters, including allele and genotype frequencies, Shannon’s information index, observed and expected heterozygosity and polymorphic information content (PIC), were calculated using PopGene v1.32. Deviation from Hardy-Weinberg equilibrium (HWE) was assessed using c2 testing at P£0.05. To explore the structural impact of missense mutations, secondary structures were predicted using SOPMA and tertiary models of both wild-type and variant PROP1 proteins were generated with SWISS-MODEL. Phylogenetic relationships were inferred using the Neighbor-Joining algorithm with pairwise genetic distances in MEGA v11.2 and the resulting tree was visualized using the Interactive Tree of Life (iTOL).
 
Association analysis of growth traits
 
Data on growth traits across genotypes were analyzed using the General Linear Model (GLM) procedure in SPSS v18. Initially, potential effects of farm, sex and season of birth were tested and subsequently excluded due to non-significance. The final model applied was:
 

Y_ijk = μ + A_i +G_j +e_ijk

 
Where,
Y_ijk= The observed body measurement.
μ= The overall mean.
A_i= The fixed effect of age.
G_j= The fixed effect of PROP1 genotype.
e_ijk= The residual error.
       
The model demonstrated that both age and genotype had a significant impact on trait variation. The least squares mean differences among genotypes were statistically meaningful, as indicated by p-values below 0.05.

Characterization of PROP1 SNPs and allele frequencies
 
The PROP1 gene was genotyped for a polymorphic locus, namely g.1860C>T. The SNP g.1860C>T was analyzed using the restriction enzyme StuI, which allowed the identification of CC, CT and TT genotypes in the examined goat breed. The heterozygote CT genotype showed the highest frequency and allele C was the most frequent in the resource population.   
 
Population genetic parameters and Hardy Weinberg equilibrium (HWE)
 
At the SNP locus g.1860C>T, three genotypes (both homozygous and heterozygous) were identified. The frequency of allele T was recorded at a minimum of 0.41 and allele C at a maximum of 0.59 (Table 1). This study observed significant deviations (P<0.05) from HWE at the analyzed SNP locus in the examined populations. These deviations may be attributed to a combination of positive selection, genetic drift and the limited sample size, which potentially influences allelic and genotypic distributions at the examined loci.


 
Heterozygosity and genic variation statistics
 
The number of alleles for polymorphic markers was two, similar to the case of biallelic markers. The SNP g.1860C>T showed a PIC (polymorphism information content) value of 0.32 (Table 2). PIC is a statistical measure used to evaluate the informativeness of a genetic marker. The effective number of alleles (ne) for g.1860C>T is 1.94. These values align with those observed for biallelic markers. Effective alleles represent the number of rare variants needed to reach a level of heterozygosity comparable to that of reference populations. Notably, the SNPs under study displayed medium effective allele counts, indicating their potential suitability for selection and their potential impact on goat breeding. The average heterozygosity estimate, reflecting Nei’s genetic differences, is 0.48 in the locus in the examined breed. Shannon’s Information Index at the g.1860C>T is 0.67, assessing within-population genetic diversity in the resource populations. The mean observed homozygosity was 0.79 and the observed heterozygosity value was 0.21 in the examined population. The fixation index is 0.55 in the examined goat population (Table 2). The genotypic distribution and measures of genetic variation suggest a heterozygote deficiency in the examined populations.


 
Prediction of protein structure and genetic divergence analysis
 
This study detected a missense mutation at the rs1860 site of the PROP1 gene, resulting in an amino acid substitution from Alanine (Ala) to Valine (Val). According to SOPMA predictions, the secondary structure of proteins (2-D), the wild-type PROP1 protein at the rs1860 locus, was composed of approximately 33.33% extended strand and 66.67 % random coil. The mutant protein at the rs1860 site of the PROP1 gene showed similar compositions of all parameters. The predicted two-dimensional structures for the SNP locus of PROP1 protein are shown in Fig.3a. The predicted three-dimensional (3-D) structures and QMEAN values for both the wild-type and mutant PROP1 (rs1860) proteins are shown in Fig 3b. No alterations in the overall 3-D structure were detected in either the wild-type or mutant proteins.


 
Phylogenetic analysis of the PROP1 gene
 
Phylogenetic analysis was conducted to investigate the evolutionary position of the PROP1 gene in the studied goat breed. PROP1 gene sequences from several species were obtained through the NCBI BLAST tool. The phylogenetic tree was constructed using these sequences to visualize evolutionary relationships (Fig 4). The tree revealed a close clustering of the goat PROP1 gene with that of Ovis aries, suggesting significant genetic similarity. Additionally, pairwise genetic distances between the goat breed and other species were computed to quantify evolutionary divergence, with results summarized in Table 3. These distances align with the clustering observed in the phylogenetic tree, further confirming the inferred evolutionary relationships.




 
Association of PROP1 genotypes with growth traits
 
Significant variation (p<0.05) was observed in growth traits among PROP1 genotypes (g.1860C>T) in Assam Hill goats (Table 4). Animals with the CC genotype exhibited consistently higher body weights at 3 months (5.88±0.24 kg), 6 months (9.47±0.75 kg) and 12 months (14.09±0.20 kg) compared to CT and TT genotypes. At 9 months, TT animals showed a marked increase in body weight (11.93±0.42 kg), exceeding both CC (11.28±0.60 kg) and CT (10.97±0.84 kg), although the differences were not statistically significant (p>0.05). A highly significant difference (p<0.01) in body length was observed at 6 months, where CC animals (47.16±0.24 cm) outperformed than CT (45.07±0.83 cm) and TT (45.69±0.72 cm) animals. Wither height at 3 months also differed significantly (p<0.05), with CC goats (25.78±0.09 cm) measuring taller than CT (23.17±0.42 cm) and TT (24.14±0.79 cm). However, no significant differences in wither height were recorded at 6, 9, or 12 months (p>0.05). Chest girth was highest in CC animals at 3 months (24.82±0.76/ cm), though not statistically significant and converged across genotypes by 6 and 9 months. At 12 months, TT animals exhibited a marginal advantage in chest girth (55.14±0.88 cm), compared to CC (54.02±0.52 cm) and CT (54.92±0.47 cm), with no significant genotype effect (p>0.05). These results indicate that the CC genotype is positively associated with superior early growth traits, while TT individuals demonstrate compensatory growth in later stages. The CT genotype exhibited intermediate performance, suggesting a possible additive or incomplete dominance effect at this locus. 


       
Unraveling the genetic determinants of growth traits in goats is a key priority in breeding programs aimed at enhancing productivity and economic value (Yang et al., 2024; Aboul-Naga  et al., 2025; Panigrahi et al., 2025). Phenotypic traits such as body weight, length, wither height and chest girth serve as vital indicators of meat production, reproductive capacity and overall robustness (Dakhlan et al., 2025; Dauda et al., 2025; Husen et al., 2025). Growth performance and body measurements of Assam local goats have also been shown to respond significantly to management and production systems, reinforcing their importance as selection criteria (Hoque  et al., 2020). Incorporating molecular tools, especially marker-assisted selection (MAS), has emerged as a potent strategy for accelerating genetic improvement (Moniruzzaman et al., 2014; Wadood et al., 2025). Single nucleotide polymorphisms (SNPs) among genetic markers are especially valuable due to their high abundance, genomic stability and capacity to dissect complex quantitative traits. Indeed, GWAS in goat populations has identified numerous growth-associated SNPs within genes such as SOHLH2, CCNA2 and SOX7, highlighting the polygenic architecture underlying these traits (Shangguan et al., 2024; Yang et al., 2024). 
       
One gene of particular interest is PROP1 (Prophet of PIT 1), a transcription factor central to anterior pituitary development. PROP1 regulates the proliferation of somatotropes, the cells responsible for synthesizing growth hormone (GH), which is vital for postnatal growth (Ward et al., 2005; Perez Millan et al., 2016). Variants in PROP1 have been associated with growth and reproductive phenotypes in ruminants. In sheep, SNPs in PROP1 intron 1 (e.g., c.109+40/T>C) were significantly correlated with weaning weight and growth rate (Ekegbu et al., 2019). Similar associations between pituitary transcription factor genes and growth traits have been reported in Indian goat breeds, where polymorphisms in the POU1F1 gene significantly influenced body weight in Osmanabadi goats (Pawar et al., 2021). Moreover, in Chinese goat breeds, SNPs within the POU1F1-PROP1-PITX1-SIX3 pathway have been associated with multiple growth metrics, including chest circumference and cannon bone girth (Ma et al., 2017). Pan et al., (2013) reported that the H173R missense mutation in the bovine PROP1 gene significantly affects growth traits. These findings underscore the potential of PROP1 polymorphisms as genetic markers for growth performance in livestock populations.  
       
In the current investigation, SNP within PROP1, such as g.1860C>T, were genotyped and analyzed for associations with growth traits in Assam hill goats. The observed association of the PROP1 g.1860C>T polymorphism with growth traits in Assam Hill goats aligns with previous findings in cattle and sheep, where PROP1 variants were linked to somatic growth performance (Pan et al., 2013; Ekegbu et al., 2019). The superior early growth in CC genotypes and later compensatory growth in TT animals suggest genotype-specific growth patterns consistent with PROP1’s regulatory role in pituitary development and growth hormone expression. These findings support the potential utility of the gene in caprine genetic improvement programs. Genetic diversity parameters further support the utility of this SNPs in breeding programs. The PIC values are 0.32, indicating moderate polymorphism and sufficient allelic variation for effective selection (Botstein et al., 1980). The observed heterozygosity levels in the present study suggest a balanced genetic structure essential for maintaining allelic diversity while allowing for the selection of desirable traits (Tosser-Klopp  et al., 2016; Kichamu et al., 2025). These findings emphasize the importance of combining unlinked loci in breeding programs to enhance trait predictability and selection efficiency.  
       
An Alanine-to-Valine substitution at the rs1860 position of the PROP1 gene may subtly alter its DNA-binding affinity and transcriptional activity despite preserving overall structural conformation. Even minor side-chain substitutions, such as Ala’!Val, are known to influence transcription factor specificity and binding strength (Aditham et al., 2021). This suggests that the g.1860C>T variant in goats may impact growth traits by modulating PROP1’s regulatory function. Phylogenetic analyses further demonstrate that PROP1 is highly conserved among small ruminants, particularly goats and sheep. This underscores its crucial regulatory role in growth and pituitary development, suggesting its potential utility in cross-species genetic improvement strategies. Incorporating PROP1 SNPs into marker-assisted selection (MAS) can significantly enhance early selection by reducing dependence on late-appearing phenotypic traits (Deniskova and Barbato, 2022; Khan et al., 2023). However, growth characteristics are inherently polygenic and influenced by environmental factors, making genomic selection (GS) based on high-density SNP arrays a more robust strategy for accurately predicting breeding values (Deniskova and Barbato, 2022; Ncube et al., 2025).
       
Considering these results, the study holds significant relevance for practical breeding programs. The superior early growth performance observed in goats carrying the CC genotype suggests its potential as an effective early selection marker for improving body weight and linear body measurements in meat-oriented production systems. Integrating the PROP1 g.1860C>T variant into marker-assisted selection (MAS) schemes could therefore accelerate genetic progress by facilitating more precise and timely identification of superior kids. Given the crucial role of Assam Hill goats in supporting the livelihoods of tribal communities across Northeast India, the identification of functional polymorphisms such as PROP1 offers opportunities to develop more structured, sustainable breeding strategies while maintaining the breed’s adaptation to local environments.

This study underscores the genetic and functional relevance of the PROP1 g.1860C>T SNP in Assam Hill goats. The allele frequencies, significant deviation from the Hardy-Weinberg equilibrium and moderate polymorphism suggest the presence of underlying selective forces and constrained genetic diversity. Although structural modeling of the Ala’®Val substitution revealed no significant changes, potential effects on transcriptional regulation remain to be explored. Phylogenetic analysis confirmed the evolutionary conservation of PROP1 among small ruminants. Notably, the CC genotype was consistently associated with superior early growth traits, supporting its utility as a candidate marker in selection programs. However, further studies are required in larger and more diverse caprine populations to validate these findings and enhance their applicability in genetic improvement programs.
 

The authors express their gratitude to the Director of ICAR- Research Complex for North Eastern Hilly (NEH) Region, Umiam, (Meghalaya) and ICAR-Research Complex for Eastern Region, Patna (Bihar), for the essential support provided in conducting the research.
 
Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
Informed consent
 
All animal procedures for experiments were approved by the Committee of Experimental Animal care and handling techniques were approved by the Institute of Animal ethics Committee.
 

All authors declare that they have no conflict of interest.