The study involved investigating the maternal lineage diversity and genetic relationships of indigenous chicken ecotypes in Tanzania. Six indigenous chicken ecotypes, namely, Mwanza, Geita, Shinyanga, Tabora, Singida, Dodoma, and Morogoro, from five regions of mainland Tanzania were used in this study. Likewise, two indigenous chicken ecotypes from Unguja and Pemba Island were used (Figure 1).

AMOVA revealed significant genetic differentiation among the six ecotypes (FST = 0.35452, p < 0.001), partitioning 35.45% of variation among populations and 64.55% within populations (Table 1). The high and significant FST indicates strong population structure, while the larger within-population variance suggests considerable genetic diversity within each ecotype, reflecting rich genetic resources despite pronounced differentiation across groups.

Pairwise FST values reveal varying levels of genetic differentiation among the six Tanzanian chicken ecotypes (Table 2), reflecting both genetic distance and historical gene flow. The greatest genetic distances occur between Morogoro Medium and Kuchi (0.42325), Kuchi and Sukuma (0.38158), and Morogoro Medium and Sukuma (0.37996), indicating limited gene flow. In contrast, minimal distances between Morogoro Medium and Unguja (0.01601) and between Pemba and Ching’wekwe (0.01101) suggest close genetic relationships and high recent gene flow. Overall, the results highlight pronounced genetic structuring among most ecotypes, with a few pairs maintaining substantial connectivity or sharing recent common ancestry.

The phylogenetic tree constructed from pairwise FST distances (Figure 3) reveals distinct clustering patterns among the six Tanzanian chicken ecotypes, highlighting their genetic differentiation. The Sukuma, Kuchi, and Morogoro Medium ecotypes form clearly separated clades, indicating limited gene flow, suggesting long-term maternal isolation likely shaped by geographic barriers, cultural preferences, and localized breeding practices. In contrast, Pemba, Unguja, and Ching’wekwe cluster more closely, suggesting recent genetic exchange or shared ancestry. These relationships align with pairwise FST values, where high differentiation was observed among inland ecotypes, while lower values between island and coastal populations indicate recent gene flow. These patterns align with observed genetic distance metrics, highlighting both historical isolation and connectivity among Tanzania’s indigenous chicken populations. The distinct positioning of Sukuma chickens highlights their deep maternal lineage structure. The distinct positioning of Sukuma chickens highlights their deep maternal lineage structure, consistent with their high haplotype and nucleotide diversity.

The molecular diversity indices reveal marked genetic variation among the six Tanzanian chicken ecotypes (Table 3). Sukuma chickens exhibited the highest haplotype diversity (Hd = 0.95789) and nucleotide diversity (π = 0.30299), with 204 segregating sites (S) and an average pairwise difference (k) of 93.926, indicating rich maternal lineages and deep genetic structure. In contrast, Kuchi chickens showed the lowest diversity (Hd = 0.36316; π = 0.00158), with only 4 segregating sites and k = 0.489, suggesting past bottlenecks or founder effects. Unguja, Morogoro, Pemba, and Ching’wekwe displayed moderate variability (S = 10–11; k ≈ 3.9–4.6), likely reflecting admixture or localized selection. The pooled population diversity (Hd = 0.86765; π = 0.08756; S = 310; k = 27.144) highlights significant overall variation, essential for conservation and breeding programs aimed at maintaining adaptability and resilience.

The demographic history and neutrality test results in Table 4 suggest varied evolutionary dynamics among the six Tanzanian chicken ecotypes. Sukuma chickens show high Tajima’s D (2.63095, p = 0.993) and Fu’s Fs (5.20711, p = 0.981) values, both non-significant, indicating no strong deviation from neutrality and suggesting demographic stability or balancing selection. Unguja, Morogoro, and Pemba exhibit similarly high, non-significant positive values, reflecting potential population stability. Kuchi has negative Tajima’s D (−2.09760) and Fu’s Fs (−0.03325), also non-significant, possibly hinting at past expansion or purifying selection. Harpending’s raggedness and SSD p-values across ecotypes indicate generally good model fit for population stability rather than recent bottlenecks or expansions.

The genetic differentiation observed among Tanzanian indigenous chicken ecotypes highlights both localized isolation and historical connections. AMOVA revealed that 35.45% of variation occurs among populations, with a high and significant fixation index (FST = 0.35452; p < 0.001), confirming strong structuring. Nevertheless, the substantial within-population variation (64.55%) highlights the richness of maternal lineages preserved within each ecotype, a pattern consistent with previous findings in African village chickens (MuChadeyi et al., 2008; Mtileni et al., 2011; Lyimo et al., 2013).

Pairwise FST comparisons indicate the greatest genetic differentiation between Morogoro Medium and Kuchi (0.42325), as well as between Kuchi and Sukuma (0.38158), suggesting long-term maternal isolation possibly reinforced by cultural preferences and geographic separation. Conversely, the lowest values, observed between Morogoro Medium and Unguja (0.01601) and between Pemba and Ching’wekwe (0.01101), reflect recent gene flow or shared ancestry likely mediated by interisland poultry exchange and coastal trade routes (Msoffe et al., 2004; Osman et al., 2016). These results align with the broader understanding that African village chickens exhibit a mosaic of differentiation shaped by both ancient introductions and contemporary management practices (Groeneveld et al., 2010). Such population structure highlights the need for conservation and breeding programs that safeguard both inter-ecotype distinctiveness and intrapopulation diversity critical for adaptation and resilience.

The phylogenetic reconstruction based on FST values reveals distinct clades corresponding to Sukuma, Kuchi, and Morogoro Medium chickens, supporting their maternal divergence and relative isolation. These ecotypes likely retained unique lineages shaped by localized breeding systems and adaptation to inland environments. In contrast, the coastal and island ecotypes, Unguja and Pemba, cluster more closely, reflecting shared haplotypes and higher levels of maternal connectivity. Such relationships suggest stronger historical and contemporary exchanges facilitated by maritime and interisland trade networks (Mwacharo et al., 2013; Osman et al., 2016). Such clustering patterns align with the observed FST values, which indicate strong differentiation among most ecotypes yet closer relationships within the coastal and island groups. The Sukuma ecotype is particularly notable for its deep maternal structure and exceptionally high haplotype diversity, consistent with multiple maternal origins introduced through inland trade routes connecting western regions of Tanzania to coastal markets (Lyimo, 2025).

The observed phylogenetic topology reflects not only ecological and cultural selection but also the broader history of domestic chicken introduction and dispersal across Africa. Archaeological and historical evidence suggests that chickens entered the continent through multiple waves, including introductions via the Mediterranean and the Indian Ocean, with significant contributions from Southeast Asia and the Indian subcontinent (MacDonald and Edward, 1993; Mwacharo et al., 2013; Lyimo et al., 2013). These repeated introductions created a mosaic of maternal lineages, explaining the admixture found among coastal populations and the persistence of unique haplotypes within inland ecotypes. In particular, island and coastal groups show strong genetic connectivity, shaped by maritime trade and interisland poultry exchange, whereas inland populations such as the Sukuma ecotype retained distinct maternal signatures due to limited exposure to such external gene flow. These findings emphasize the importance of integrating phylogenetic evidence with archaeological and ethnographic records to trace the maternal history of African poultry and inform conservation strategies.

Molecular diversity indices demonstrate substantial heterogeneity among the six Tanzanian indigenous chicken ecotypes. Sukuma chickens display the highest haplotype diversity (Hd = 0.95789), nucleotide diversity (π = 0.30299), segregating sites (S = 249), and average pairwise differences (k = 114.329), indicating multiple maternal lineages, long evolutionary history, and minimal bottleneck effects. Such high variability likely reflects historical trade connections and livestock exchanges, particularly in the western part of Tanzania and the Lake Zone, that introduced diverse maternal haplotypes (Lyimo et al., 2013).

The high haplotype diversity observed in Sukuma chickens may partly reflect breeding autonomy at the household level, supported by strong informal networks that enable the exchange of breeding stock. Such exchanges, though beneficial for genetic variation, can also risk genetic dilution if not complemented by formal conservation programs. In Tanzania, conservation and sustainable use of indigenous chicken ecotypes are influenced not only by genetic and ecological factors but also by the interplay between formal and informal institutions (Kapella et al., 2020). Formal institutions provide technical guidance, breeding policies, and research support, whereas informal structures such as traditional knowledge systems, local norms, and community networks play a critical role in maintaining breeding practices and genetic integrity at the grassroots level.

Kuchi chickens exhibited the lowest genetic diversity (Hd = 0.36316; π = 0.00158; S = 12; k = 0.873), reflecting founder effects, genetic drift, or strong directional selection. Their ancestry links to South Asian game fowl, traditionally bred for combat under rigorous selection (Lyimo et al., 2013). Mitochondrial analyses further showed that most Kuchi individuals clustered within a single haplogroup previously identified in Shamo game birds, underlining their narrow maternal base. This restricted variability parallels patterns observed in recently introduced or intensively selected populations, highlighting potential vulnerability to inbreeding and reduced adaptability (Liu et al., 2006).

Unguja, Pemba, Morogoro Medium, and Ching’wekwe populations exhibit intermediate diversity (Hd = 0.76842–0.90526; π = 0.00378–0.16249), reflecting a balance between localized adaptation and sporadic introgression. Such patterns indicate moderate gene flow among coastal and island ecotypes, likely mediated by interisland poultry trade and cultural exchange (Osman et al., 2016). This exchange has promoted genetic connectivity while retaining ecotype-specific variation. For these populations, sustaining current levels of gene flow while protecting distinct haplotypes is crucial for maintaining adaptive potential and ensuring long-term resilience under changing production environments (Grant and Bowen, 1998; Tajima, 1989; Fu, 1997).

Neutrality test results provide valuable insights into the demographic history of Tanzanian indigenous chicken ecotypes. Most ecotypes, including Sukuma, Unguja, Morogoro Medium, and Pemba, exhibited high, non-significant positive Tajima’s D and Fu’s Fs values, suggesting demographic stability or balancing selection rather than recent population expansion. In particular, Sukuma’s high Tajima’s D (2.63095) and Fu’s Fs (5.20711) reflect the long-term maintenance of diverse haplotypes, possibly reinforced by cultural preferences for phenotypic variation and the retention of multiple maternal lineages (Mwacharo et al., 2013; Mtileni et al., 2011; Lyimo et al., 2013). Such stability may also be linked to their geographic isolation and adaptive significance in local environments.

In contrast, Kuchi chickens showed a negative Tajima’s D (−2.09760) and Fu’s Fs (−0.03325), though non-significant, which may suggest a historical expansion following a founder event, a scenario consistent with their low diversity and known derivation from Southeast Asian game fowl lineages (Lyimo et al., 2013; Liu et al., 2006). The narrow genetic base of the Kuchi ecotype signals vulnerability to disease and environmental change, necessitating strategies to broaden their genetic pool. Complementing these demographic signals, neutrality and diversity analyses offer deeper insights into the evolutionary forces shaping Tanzanian chicken ecotypes. Harpending’s raggedness index and SSD p-values across ecotypes further support a stable demographic model, with no strong evidence of recent bottlenecks. These patterns mirror observations in other African village chickens, where localized selection, limited long-distance dispersal, and occasional admixture shape long-term population structure (MuChadeyi et al., 2008).

The high genetic diversity in Sukuma (Hd = 0.95789; π = 0.30299) and Ching’wekwe chickens highlights their significance as reservoirs of adaptive traits valuable for breeding programs. This diversity enhances resilience to emerging diseases, climatic variability, and production challenges, aligning with the FAO (2015) guidelines on safeguarding livestock genetic resources. In Sukuma chickens, the deep maternal lineage structure suggests long-term adaptation to the Lake Zone’s agro-ecological conditions, making them ideal candidates for conservation-oriented breeding to maintain traits for resistance and environmental adaptability (Lyimo et al., 2013).

Conversely, the Kuchi ecotype possessing low diversity (Hd = 0.36316; π = 0.00158) reflects a narrow genetic base, increasing vulnerability to inbreeding depression and reduced adaptability. Targeted management, including genetic monitoring and controlled introgression from genetically compatible indigenous populations, could help mitigate these risks (Liu et al., 2006; Mtileni et al., 2011). Conservation strategies should combine in situ approaches by safeguarding traditional free-range management systems, with ex situ measures such as cryopreservation of germplasm. Breeding programs must integrate productivity goals with preservation of unique genetic signatures to avoid erosion of adaptive variation, ensuring both food security and cultural heritage preservation (FAO, 2015; Mwacharo et al., 2013). Selective breeding programs should aim to balance productivity traits with the conservation of unique genetic lineages to avoid erosion of adaptive diversity.