DISCUSSION

Functional and pathway enrichment analysis of target genes

Previous research has identified several genes and signaling pathways that play key roles in muscle fiber formation and pectoral muscle growth across various chicken breeds [14]. However, molecular mechanisms underlying muscle development in the selectively bred KUB chicken remain insufficiently explored. The results of this study indicate that DEGs exhibit considerable variation in expression across developmental stages. GO enrichment analysis indicates that most DEGs are involved in biological processes related to muscle tissue growth, cell differentiation, and contractile function [15]. Furthermore, significant differences in TGFβ2 gene expression levels were observed in KUB chickens, suggesting that this gene exhibits a specific regulatory pattern in muscle development.

Importantly, the KEGG and GO enrichment analyses of DEGs showed notable enrichment in several biological pathways, including focal adhesion, extracellular matrix (ECM)–receptor interaction, and cysteine and methionine metabolism, all of which support increased metabolic activity and muscle tissue development in KUB. Phytase improves phosphorus bioavailability, while protease enhances amino acid digestibility, both of which are critical for protein synthesis and satellite cell activity. Enhanced nutrient supply may therefore potentiate TGFβ2-regulated muscle development pathways, particularly in specific genotypes [16]. The observed genotype-enzyme-level interaction indicates that the growth response to multienzyme supplementation varies with TGFβ2 genotype, supporting the presence of a nutrigenetic mechanism in KUB chickens [17]. This integrative gene-nutrition interaction highlights the potential of TGFβ2 as a candidate marker for genetic selection and for precision feeding strategies in indigenous-derived tropical poultry systems [18].

Effect of the TGFβ2 gene on FI, FCR, BW, and BW gain in KUB chickens

Physiologically, improved growth performance in livestock is highly dependent on genetic activity that regulates the proliferation, differentiation, and maturation of skeletal muscle cells. One key gene that coordinates these processes is TGFβ2 [19]. This gene directly affects growth efficiency and production performance by modulating cell repair processes and preserving the delicate balance between growth and tissue regeneration [20]. Furthermore, TGFβ2 is involved in regulating physiological processes related to nutrient utilization and energy homeostasis, thereby indirectly influencing FI and energy conversion in chickens.

Research shows that genotypic variation in the TGFβ2 gene is significantly associated with differences in BW gain and final weight in chickens, indicating a genetic link between the gene’s expression pattern and growth performance [21]. Individuals with genotypes that express TGFβ2 more actively tend to exhibit higher growth efficiency without significant increases in feed consumption, as well as better physiological resistance to stress and disease [22]. These findings suggest that TGFβ2 may contribute to improved feed conversion efficiency by optimizing muscle growth metabolism. Therefore, chickens with elevated TGFβ2 expression may possess superior genetic merit for growth performance and overall productivity [23].

Meat quality

The influence of multienzyme supplementation on meat physicochemical properties, including pH, texture, CL, and water holding capacity (WHC) as presented in Table 2 and on meat color parameters such as lightness (L*), redness (a*), and yellowness (b*) as shown in Table 3, was systematically evaluated. The pH value is a critical determinant of meat quality, as it directly affects protein denaturation, CL, and textural characteristics. A negative correlation was observed between pH and both lightness (L*) and yellowness (b*), whereas redness (a*) exhibited a positive correlation with pH. Analysis of breast meat from chickens fed multienzyme-supplemented diets demonstrated a decrease in yellowness (b*) and a corresponding increase in redness (a*), suggesting improved meat coloration. The correlation coefficients between color attributes (L*, a*, b*) and pH were highly significant, indicating a strong relationship between enzymatic treatment and color stability. Changes in meat pH and texture are often linked to microbial contamination, such as Salmonella infection, which can decrease pH and compromise texture [24]. A lower pH, associated with higher redness (a*) values, may also influence consumer perception of freshness and overall meat quality, as optimal chicken meat typically exhibits enhanced lightness and redness [25].

CL value decreased significantly as multienzyme dosage increased, whereas both texture and WHC improved markedly (Table 2). This finding is consistent with previous reports indicating that multienzyme supplementation enhances WHC by promoting improved moisture retention within muscle tissues [26]. CL was calculated as the percentage difference between raw and cooked sample weights and was lowest in the SRC group, which also exhibited the highest WHC. This suggests that multienzyme supplementation may enhance meat juiciness by reducing water loss during cooking [27]. The improvement may be attributed to the higher multienzyme concentration in the feed, which facilitates the formation of a denser, more cohesive muscle structure [28]. Furthermore, the type and dosage of multienzymes significantly affected meat texture, likely through enzymatic and biochemical modifications influencing muscle pigment oxidation and structural protein integrity. These changes were associated with improved color characteristics and textural quality [26]. Correlation matrix analysis revealed that CL was inversely related to texture parameters, including chewiness and firmness, suggesting a potential interaction between structural integrity and moisture retention capacity [27].

Distribution of genotype and allele frequency

Crossbreeding is an important mechanism that contributes to increased genetic diversity and heterozygosity in livestock populations [29]. The process of gene flow between populations introduces new alleles into the gene pool, thereby enriching genetic variation and increasing heterozygosity at both the population and subpopulation levels [30]. In the context of the TGFβ2 gene, previous studies have reported two major alleles (T and C) and three genotype combinations (TT, CT, and CC) in a chicken population [31]. A similar polymorphism pattern was also found in local Indonesian chickens, including KUB chickens, with two alleles (T and C) and three genotypes (TT, CT, and CC) [32]. However, the frequency distribution showed dominance of the T allele over the C allele, likely influenced by inbreeding practices and strong selection pressure on the TGFβ2 gene. Changes in the frequency of the TGFβ2 allele in KUB chickens may reflect an adaptive response to environmental conditions and nutritional factors provided during rearing [33]. Feed supplementation with enzymes such as phytase and protease has been reported to affect the bioavailability of essential amino acids and minerals, thereby altering the transcriptional activity and expression of the TGFβ2 gene [34].

Certain alleles of the TGFβ2 gene, such as the T allele, are thought to be associated with higher nutrient utilization efficiency and increased muscle protein deposition, while the C allele may be associated with a more conservative metabolic strategy under conditions of nutrient deficiency or excess [35]. Thus, nutritional selection pressure arising from variations in feed composition can influence allele frequency dynamics in the KUB chicken population. These results indicate a synergistic interaction between genetic factors (TGFβ2 gene polymorphisms) and nutritional factors (enzyme content and nutrient availability), which collectively contribute to metabolic adaptation, growth efficiency, and the physiological performance of KUB chickens in tropical environments.

Genetic variation in the TGFβ2 genes

The hypothalamus, which primarily expresses the TGFβ2 gene, is crucial for regulating poultry FI and energy balance. Furthermore, this gene is expressed in other tissues, including erectile tissue, where TGFβ2 is reported to contribute to physiological mechanisms underlying erectile function [36]. The candidate gene approach has been widely used to identify genomic regions associated with important traits in livestock, including specific genetic markers for selection and breeding. Several previous studies reported the presence of four variations in the TGFβ2 gene promoter region in chickens [37], as well as five SNPs in the 5’UTR region and one SNP in the exon region (c.129A/G) [38]. Another study also identified four additional SNPs in the 3’UTR region using PCR-SSCP and DNA sequencing. In this study, analysis of a 387-bp fragment of the TGFβ2 gene in KUB chickens revealed no significant polymorphisms. However, when the gene sequence was compared with GenBank (NCBI) reference data, two new SNPs were identified in the 5'UTR region. This difference indicates that the TGFβ2 gene in KUB chickens has unique sequence variations compared with other poultry species, and thus could be used as a molecular marker for the genetic identification of KUB chickens.

Furthermore, this study also identified two SNPs in the exon region, as well as one additional SNP detected after comparison with the GenBank TGFβ2 sequence. The two identified point mutations, c.103C/T and c.99G/A, are unique variations not found in the other two reference sequences in GenBank. This finding aligns with a previous report that also identified SNPs in the exon region of the TGFβ2 gene in chickens [38]. That study reported one synonymous substitution at position c.93G/A (GG→AG) and one nonsynonymous substitution at position 293G/A, which causes an amino acid change from glycine to arginine. Overall, these results strengthen the evidence of genetic diversity in TGFβ2 in KUB chickens and provide an important scientific basis for further research on the function of this gene in the physiological performance of local poultry. In addition, three restriction enzymes, RsaI, AluI, and KpnI, were successfully used for genotyping by PCR-RFLP [39]. These three enzymes recognize specific sequences GT’AC, G’GTAC_C, and G_GTAC’C, respectively. The use of restriction enzymes as a molecular analysis tool has proven effective for evaluating genetic diversity and gene function _in _vivo, and similar methods have also been applied in genotyping the TGFβ2 gene in other local chicken populations [40].