1 Introduction

Tilapia, particularly those from the genus Oreochromis, are now keystone species in global aquaculture for possessing superior biological and ecological traits. They grow very rapidly, are extremely fecund, and can survive extremely wide conditions of the environment, ranging from salinity to temperature gradients. They are omnivorous, and their diet can be effectively used, with most cases of vegetable diets, which is cheaper and has lower environmental effects (Lal et al., 2024). Tilapias are stressor-resistant and disease-resistant and thus can tolerate intensive farming systems.The final answer is:. The Nile tilapia (Oreochromis niloticus), for example, is well-known to be extremely prolific, tolerant of high density, and able to adapt to all forms of aquaculture systems ranging from extensive ponds to RAS. These characteristics have rendered tilapia a successful aquaculture fish globally, and they have also been called the "aquatic chicken" due to their yield and high acceptability as a food fish (Eze, 2019).

Increased global demand for fish protein--resulting from population increase, urbanization, and health-conscious consumer purchasing behavior--brought people's attention to the selection of species mainly attractive for their positive growth characteristics. Although fast-growing and high-yielding species are economically advantageous by making production periods shorter and turnover levels higher for producers, they have better feed conversion ratios, lower production costs, and profits are increased. Production Production programs through genetic improvement on such traits have recorded significant gains. For example, the genetically improved farmed tilapia or GIFT strains have experienced tremendous improvements in their growth performance and yield, thus improving the sustainability and the economically viability of tilapia farming. The principles behind such improvements highlight the necessity for applying nature's own selective breeding process toward optimizing the efficiency of production systems and in meeting the necessary seafood demand needed worldwide (Taipe et al., 2025).

Application of conventional selective breeding methods, though effective, is time-consuming and could be non-specific in improving quantitative traits that are regulated by multiple genes. Marker-Assisted Selection (MAS) has been an effective method in fish genetic breeding through which animals bearing desirable quality genetic markers for traits such as rapid growth and high yield can be identified and selected. With the utilization of molecular markers, the breeders can accelerate the selection, increase accuracy, along with achieving earlier genetic gains. In tilapia breeding, MAS enables the early detection of superior alleles and thereby makes it possible for the broodstock with greater genetic potential to be selectable. The method not only accelerates the development of improved strains but also assists in understanding the genetic architecture of economically important traits. The application of MAS in breeding programs is the single largest aquaculture genetics input that holds the promise of increased aquaculture productivity and sustainability.

2 Genetic Basis and Breeding Progress of Tilapia

2.1 Current status of genetic resources and breeding history of tilapia

Nile tilapia (Oreochromis niloticus) is among the world aquaculture highs; there are massive genes pools within the African Continent but its large-scale production within Asia and elsewhere. The species is genetically diverse in the region although the farmed populations tend to be narrower in genetic base (Figure 1) (Geletu and Zhao, 2022). Selective breeding schemes, such as the Genetically Improved Farmed Tilapia (GIFT) scheme, have played a crucial role in developing high-performing lines by cross-mating genetic material between different populations along with relative species (Etherington et al., 2022; Barría et al., 2023). Some of the newer advancements include chromosome-scale genome assemblies, molecular markers for determining ancestry and monitoring genetic diversity in breeding programs, for example, those of Avallone et al. (2020), Etherington et al. (2022), and Barría et al. (2023). Nonetheless, threat from habitat loss, introgressive hybridization, and human activities has caused genetic deterioration in wild populations that needs conservation and use of genetic resources in an appropriate manner (Geletu and Zhao, 2022; Tibihika et al., 2024; Kwikiriza et al., 2025).

2.2 Limitations and bottlenecks of existing breeding strategies for rapid growth and high yield

Notwithstanding progress, the current breeding schemes are faced with various challenges. Domestic tilapia has a relatively narrow genetic base, therefore increasing the possibility of inbreeding and reducing the ability to adapt (Geletu and Zhao, 2022; Kwikiriza et al., 2025). Irreplaceable loss of genetic variation is also at risk due to focus on some performing lines and less application of wild genetic bases (Lind et al., 2019; Geletu and Zhao, 2022). In addition, introgressive hybridization and translocation admixture are able to compromise the genetic integrity of wild and domesticated populations (Tibihika et al., 2024). Gene tracking and regulation of gene flow and maintenance of genetic diversity still pose high challenges to sustainable breeding (Avallone et al., 2020; Tibihika et al., 2024).

2.3 Analysis of heritability and selection response potential of phenotypic traits

Heritability for traits such as growth rate and yield in tilapia is medium to high and is in favor of the success of selective breeding programs (Herkenhoff et al., 2020; Barría et al., 2023). Genomics have identified many regions and candidate genes, including those associated with the growth hormone/insulin-like growth factor axis, that are associated with enhanced growth performance (Herkenhoff et al., 2020; Etherington et al., 2022). The application of molecular markers and genomic tools increases the selection response by more accurate monitoring of desirable traits and greater genetic improvement (Avallone et al., 2020; Herkenhoff et al., 2020; Etherington et al., 2022; Barría et al., 2023). But full expression of selection response is cut short by genetic bottlenecks and absence of diversity in cultured stocks (Geletu and Zhao, 2022; Tibihika et al., 2024).

3 Development of Molecular Markers and Association Analysis Strategies

The further development of molecular marker technologies and association analysis strategies transformed genetic improvement programs for fast-growth traits and high-yield tilapia cultures. The MOD method permits the genotyping of massive SNP across the genome and allowed carrying out comprehensive genome-wide association studies for a robust foundation in marker-assisted selection, identifying genetic loci that may become associated with economically important traits that can help build superior tilapia breeds (Han, 2024)..

3.1 Common types of molecular markers and their applicability

Due to their frequent occurrence, stability, and amenability to platforms appropriate for high-throughput genotyping, they are the most frequent molecular markers used in current genetic studies. It has been possible to successfully capture most of the common SNPs either directly or indirectly by using linkage disequilibrium, and hence they are highly informative for applications like GWAS and genetic mapping. Analytical strategies involving single-marker and haplotype-based tests have been found to detect a higher proportion of genetic variation, with haplotype-based strategies often detecting a higher proportion of phenotypic variance compared to single-marker tests. The two-pronged strategy improves the ability to find associations and accuracy in marker-assisted selection (Zhang et al., 2021; Du et al., 2024).

3.2 Population construction and accurate phenotypic trait measurement methods

Successful association analysis depends on populations and phenotypic data being well structured and exact. Populations are generally built by subdividing genetic resources into groups according to genotype information that serves to control for population structure and prevent spurious associations. Phenotypic trait measurement is exact through standardized protocol, replicated trials, and multi-environment testing, which provides linkage of genotype and phenotype that is trustworthy. Marker selection methods based on linkage disequilibrium and haplotype information allow for the optimization of marker sets, reducing genotyping effort while retaining most of the genetic information. Sample sizes of 50~100 individuals are often sufficient for initial marker selection and population structure analysis, providing consistent and reliable results (Abdoli-Nasab and Rahimi, 2020).

3.3 Phenotype-genotype association analysis and candidate gene discovery

Association analysis combines the phenotypic and genotypic data to detect markers associated with the traits of interest. Mixed Linear Models (MLM) are highly adopted while ignoring population structure and kinship for the purpose of reducing false positives and enhancing the accuracy of marker-trait associations. The haplotype-based methods could identify more loci and explain a greater proportion of phenotypic variance than the single-marker tests to aid in discovering candidate genes. Marker selection analysis based on linkage disequilibrium and haplotype data also increases the effectiveness and power of association analysis to aid identification of genetically important regions for marker-assisted selection (Abdoli-Nasab and Rahimi, 2020).

3.4 Statistical methods for qtl mapping and functional region identification

Several statistical methods are employed for the purpose of QTL mapping and identification of functional genomic regions. Single marker and multi-marker approaches are utilized; however, the multi-marker and haplotype-based techniques such as principal components along with variance components models have shown a higher detection power for association, especially in cases where complex traits are influenced by a locus. Tournament-based marker selection strategies along with Bayesian approaches have helped in the reduction of problems such as high dimensionality and multicollinearity, thus increasing the precision of genomic prediction and decreasing spurious associations. Specific applications where significant power is available at the gene or regional level for detecting associations are for gene or region-based tests, which support the identification of functionally relevant regions responsible for target traits (Filho et al., 2019).

4 QTL and Candidate Gene Studies Related to Rapid Growth and High Yield Traits

4.1 QTL identification and stability evaluation for growth-related traits

New technology in QTL mapping has made it possible to map many loci that correspond to growth traits across several species. Field testing on a large scale and genetic mapping through high-density genotyping have made it possible to identify stable QTLs for plant height, biomass, and plant yield. For instance, doubled haploid population and near-isogenic line research found confirmatory evidence of high-effect QTLs on many single chromosome arms, effects of individual shoots on growth characteristics and yield (Li et al., 2018; Liu et al., 2020; Kumar et al., 2022). The QTLs also locate on already characterized loci, reflecting stability and versatility in alternative genetic backgrounds and across varying environments. Meta-QTL analysis is also utilized to narrow these intervals, reducing confidence intervals and precision of QTL detection for marker-assisted selection (Li et al., 2018; Zhang et al., 2021).

4.2 QTL mapping for high-yield traits

QTL mapping for high-yielding characteristics has revealed clusters of loci that affect various components of yield. Grain number, kernel weight, and protein content yield characteristics have been recognized for QTL cluster strategies. Multi-environment and population data have been combined; this revealed the presence of QTL clusters with positive correlations among the various yield characteristics, which have been strongly advocated for use in breeding programs. Meta-analyses have merged these hundreds of primary QTLs into fewer, more stable meta-QTLs, which are in many cases validated by genome-wide association studies. The meta-QTLs frequently harbor candidate genes with established functions in yield determination, offering attractive targets for genetic improvement (Zhang et al., 2021; Du et al., 2024).

4.3 Functional annotation and expression validation of candidate genes

Prioritization of candidate genes in QTL regions is increasingly best done through integrated multi-omics approaches, integrating sequence variation, gene expression, gene ontology, and protein-protein interaction data. This provides a drastic reduction of possible candidates, often by more than twenty fold. Functional annotation frequently highlights transcription factors and regulatory proteins, such as MADS-box, WRKY, and cytochrome P450 families, as key players in growth and yield traits (Kumar et al., 2023; Keerthi et al., 2024). Further validation of expression is done with contrasting genotypes and RNA-seq data, and several of the studies have been able to show differential expression of candidate genes in high- versus low-yielding lines (Su et al., 2020; Zhang et al., 2021; Kumar et al., 2022).

4.4 Analysis of QTL expression consistency and marker universality across different families

Stability of QTL expression and universality of related markers in different genetic backgrounds are essential requirements for their application in breeding. Empirical studies have documented that several QTLs and related markers are stable in different populations and environments and justify application of such markers for marker-assisted selection. Meta-QTL and QTL breeding research have mapped loci that are expressed similarly in different distinct genetic backgrounds (Kumar et al., 2023; Du et al., 2024). Further, confirmation of candidate genes and QTLs in various families and environments ensures their universal use and consistency for improving accelerated growth and high-yielding characters (Li et al., 2018; Liu et al., 2020; Zhang et al., 2021).

5 Practical Application of Marker-Assisted Selection in Tilapia Breeding

5.1 Design of MAS breeding workflow and construction of selection systems

Marker-Assisted Selection (MAS) pipeline development for tilapia breeding starts with marker identification and validation of molecular markers associated with key traits like disease resistance, sex determination, and growth. Microsatellite markers for association with disease resistance have, for instance, been developed in tilapia lines and can predict offspring survival before challenge by pathogens, thereby enabling non-lethal and effective selection (Chen et al., 2021). In sex control, operations use sex-linked DNA markers to detect and select YY supermales or genetic male tilapia, whose multiplex PCR and high-throughput genotyping platforms are utilized to genotype broodstock rapidly and build stable selection systems (Figure 2) (Chen et al., 2018; Sultana et al., 2020; Wu et al., 2021; Tao et al., 2022). These types of systems are so advanced that information about markers is included in breeding choices to an extent that only individuals with a positive genotype are promoted in the breeding plan (Chen et al., 2021; Wang and Chen, 2024).

5.2 Validation of marker effects and evaluation of selection efficiency

Marker effects are confirmed through controlled crossing tests and progeny testing to ascertain that the selected markers are linked to the target characters. For instance, MAS-selected YY supermales have been reported to sire offspring with male proportions of over 94% and significantly increased growth rates, and MAS for disease resistance has resulted in offspring with mortality levels of less than 1% compared to over 70% in susceptible lines (Chen et al., 2018; Vela-Avitúa et al., 2023). MAS effectiveness is further observed by the ability to predict offspring performance for properties from parental genotypes and by obtaining high concordance when validated markers are applied between populations and environments (Sultana et al., 2020; Chen et al., 2021; Curzon et al., 2021; Tao et al., 2022).

5.3 Integrated application strategies of mas and conventional family selection

Blending MAS with conventional family selection methods maximizes genetic gain without losing genetic diversity. MAS is utilized early and accurately to select individuals with desirable alleles, whereas conventional family selection techniques are utilized to induce overall performance and versatility (Sultana et al., 2020; Curzon et al., 2021; Tao et al., 2022). This combined approach is particularly valuable for polygenic traits regulated by numerous genes since it applies phenotypic and molecular data together to increase the precision and efficacy of selection. Use. of MAS in Charm. with family selection has also been found to be effective in the production of all-male and disease-resistant tilapia and has thereby established its usefulness for commercial breeding (Chen et al., 2018; Curzon et al., 2021; Wu et al., 2021; Tao et al., 2022).

5.4 Trait improvement performance in advanced generations and industrial promotion prospects

MAS-bred tilapia lines have exhibited higher growth rates, higher yields, better disease resistance, and better sex control in later generations than traditionally bred counterparts. Such improvements are equivalent to improved production efficiency and less reliance on hormone treatments, which enable the development of robust, high-performing strains for diverse aquaculture conditions. The effective application of MAS across different tilapia species and strains suggests that it has the promise to be applied on an industrial scale and significantly impact the world tilapia industry to promote sustainable and profitable tilapia aquaculture (Chen et al., 2018;2021; Wu et al., 2021; Vela-Avitúa et al., 2023).

6 Challenges and Future Prospects in Molecular Breeding

6.1 Stability of marker-trait associations and environmental interaction issues

One of the central challenges of molecular breeding is to achieve marker-trait association stability across a number of environments. The utility of markers can be undermined by genotype-environment interactions that have the potential to change the expression of target traits and decrease the predictive power of markers in alternative environments. This is of utmost significance for multi-gene and polygenic complex traits, where marker-phenotype associations in the continuous validation of multi-location and multi-year tests become a prerequisite to guarantee valid selection gains (Luo et al., 2023; Chen, 2024).

6.2 Marker combination strategies for multi-trait selection

Multi-trait selection involves the development and use of marker combination programs such as gene pyramiding and multiplexed marker panel application. The strategies simplify the breeding of favorable yield, quality, and stress tolerance alleles but also complicate the breeding programs. The combination of high-throughput genotyping and high-performance bioinformatics software has enabled handling of large-scale data and correct selection of individuals with the best multi-trait profiles, though it is not simple to balance trade-offs between traits without compromising genetic diversity (Luo et al., 2023; Chen, 2024).

6.3 Potential of integrating gene editing and omics technologies in future tilapia breeding

The integration of gene editing technologies, such as CRISPR-Cas9, and omics technologies (genomics, transcriptomics, proteomics, and metabolomics) holds large potential to accelerate tilapia improvement for desired traits. With these technologies, it is possible to edit directly the target genes and investigate extensively the biological pathways of the complex traits. Gene editing integrated with omics decreases breeding cycles, improves the efficiency of introgression of qualities, and can create tilapia lines with augmented yield, disease resistance, and environmental tolerance. Ethical, regulative, and technical barriers must be addressed in an attempt to enjoy such gains (Singh et al., 2020; Chen, 2024).

6.4 Key directions for advancing MAS toward precision breeding systems

In order to propel MAS towards precision breeding, the research work in the future needs to involve the development of cost-cutting high-throughput genotyping platforms, improving the predictability of quantitative traits, and the integration of multi-layer omics data for indirectly decomposing traits. The application of automatic genotyping technologies as well as artificial intelligence in predictive breeding will further enhance selection efficiency and enable the quick release of cultivars with desired traits. Further studies and collaboration are required to overcome the current challenges and facilitate the widespread and sustainable application of precision molecular breeding in tilapia and other aquaculture species (Singh et al., 2020; Chen, 2024).

7 Concluding Remarks

There have been impressive recent achievements in the elucidation of the molecular foundation of tilapia high-yield and rapid-growth traits. Genome-wide association studies (GWAS) have identified major quantitative trait loci (QTLs) associated with body weight, growth rate, and fillet yield, which has a solid genetic foundation for trait enhancement. Polymorphisms in important genes, such as the myogenic regulatory factors (MRFs) gene family, have been highly associated with enhanced muscle growth and enhancement of growth. Meanwhile, gene editing technologies, including CRISPR/Cas9, have enabled functional verification of such candidate genes, with effective knockout of the myostatin (mstn) gene promoting enhanced muscle weight and growth performance enhancement in Nile tilapia. These findings collectively provide not only molecular insight into growth and yield traits, but also practicable targets for genetic improvement by marker-assisted selection (MAS).

MAS is very useful in accelerating genetic progress, precision in selection, and reduction of improvement time in tilapia breeding. Technology allows early identification of those with favorable alleles and therefore improves selection efficiency compared to phenotypic selection. In practice, breeding programs such as GenoMar have recorded consistent progress in key production traits by generations through MAS. The strategy has also been at the heart of hormone-free production of Genetically Male Tilapia (GMT), a strategy that is concordant with environmental sustainability and consumer safety standards. Such applied effects demonstrate MAS to be a scientifically proven and industry-relevant strategy that contributes directly to profitability and robustness in modern aquaculture operations.

In the future, there should again be an attempt made to link large-scale breeding programs with molecular tools to further enhance the efficiency of MAS in tilapia breeding. Genomic Selection (GS) based on genome-wide marker data to predict breeding values can be employed as an adjunct to MAS to consider the cumulative effect of many small-effect loci contributing to complex traits. High-throughput genotyping technologies such as SNP arrays and next-generation sequencing would have to be embraced in order to facilitate fast and cost-effective screening of the markers in large populations. CRISPR gene editing technologies will also be utilized strategically to facilitate efficient manipulation of the target genes, resulting in the quick generation of improved strains. The integration of breeding platforms that conjoin pedigree-based selection with MAS, GS, and gene editing will be decisive to the future of genetic improvement. Combined methodologies will allow the breeders to address multigenic breeding objectives more satisfactorily and thus drive tilapia aquaculture towards increased precision, productivity, and responsiveness to world concerns.

Acknowledgments

The authors thank the two anonymous reviewers for their feedback on the manuscript of this study. Their thorough review and constructive suggestions contributed to the improvement of the manuscript.

Conflict of Interest Disclosure

The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

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