International Journal of Aquaculture, 2025, Vol.15, No.5, 240-247 http://www.aquapublisher.com/index.php/ija 242 2.3 Impact of hybridization and introgression on phylogenetic resolution Introgression and hybridization occur frequently in both wild and captive tilapia populations as a result of deliberate introduction for aquaculture and accidental escapes. Ancient gene flow contributed to diversification of the genus, whereas modern hybridization, especially between introduced and native species, poses a threat to the genetic integrity of wild populations. Introgression obscures phylogenetic relationships, creating mito-nuclear discordance and impeding species identification. In some, hybridization has resulted in new species or strains with new adaptive traits, but hybridization may also homogenize unique genetic lineages and undermine conservation plans (Ford et al., 2019; Mojekwu et al., 2020; Etherington et al., 2022; Yu et al., 2022; Ciezarek et al., 2023). 3 Mitochondrial Data Construction and Phylogenetic Analysis Methods 3.1 Sampling of tilapia specimens and strategies for mtDNA extraction and sequencing Tilapia samples are usually collected from heterogeneous populations and tissue or blood samples are preserved for DNA extraction. Methods applied to the extraction rely on commercial kits such as Quik-gDNATM miniPrep or Aqualex extraction kits to recover high-quality mitochondrial DNA (mtDNA) for downstream use. Both Sanger and next-generation sequencing (NGS) technology are used for the purpose of sequencing, with NGS (i.e., Illumina platforms) enabling the assembly of complete mitogenomes and production of large genetic data ready for application in phylogenetic studies (Ekerette et al., 2018; Nyaku, et al., 2023). 3.2 Alignment and quality control of mitochondrial genes After sequencing, chromatograms are examined and edited using software such as BioEdit for sequence quality. Multiple sequence alignment is done using software such as MEGA, which allows polymorphic, monomorphic, and parsimony-informative sites to be identified. Quality control includes removal of low-quality reads and use of specialized pipelines (e.g., Mitopore, mtGrasp) to enhance data reliability and standardization to enable strong downstream phylogenetic analysis (Ekerette et al., 2018). 3.3 Phylogenetic tree construction and model selection Phylogenetic distances are estimated using numerous varied methods such as Neighbor-Joining (NJ), Maximum Likelihood (ML), and Maximum Parsimony (MP). Software such as MEGA is utilized for these analyses in which model selection is chosen based on data best representing. BI and machine learning-based approaches can be used with more advanced datasets in order to increase trees accuracy and support values. Method choice is determined by sequence diversity, data set size, and study objective (Ekerette et al., 2018; Gamage et al., 2020). 3.4 Genetic distance calculation and topological analysis of phylogenetic relationships Genetic distances between populations or species are quantified with models such as Kimura 2-parameter, providing quantitative divergence estimates. Molecular variance analysis (AMOVA) is used to decompose genetic variation within and between populations. Phylogenetic networks and trees are interpreted to assess clustering, monophyly, and the presence of differentiated lineages, to support conclusions about evolutionary relationships and population structure (Ikpeme et al., 2019; Nyaku, et al., 2023; Kwikiriza et al., 2025) (Figure2). 4 Phylogenetic Relationships and Divergence Signals in Tilapias 4.1 Sequence variation and inter-specific differentiation based on mtDNA Mitochondrial DNA (mtDNA) sequence polymorphism is a potent tool for assessing evolutionary history and inter-species differentiation. It has been found that while ancient mitochondrial markers (e.g., COI, CYTB, D-loop) continue to be favorites, analyses based on full mtDNA sequences make more robust and secure phylogenetic inferences than the ones based on short gene fragment sequences. This further confirms the importance of marker choice for successful differentiation of species and evolutionary information. 4.2 Phylogenetic relationships and lineage divergence among geographic populations Phylogenetic analyses using mtDNA often reveal deep intraspecific divergence and clearly defined lineages that are geographic locality-specific. Such patterns are suggestive of complex evolutionary histories, with genetic divergence among populations shaped by historical biogeography and limited gene flow. In some taxa,
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