A comprehensive meta-analysis of the use of mtDNA and microsatellite markers in the study of phylogeography and conservation of the gene pool of Apis mellifera L.

Uma meta-análise abrangente do uso de marcadores de mtDNA e microssatélites no estudo da filogeografia e conservação do pool gênico de Apis mellifera L.

Abstract

The Western honey bee (Apis mellifera L.) is a key pollinator species and an important object of beekeeping; however, anthropogenic introgression of genes from commercial breeds threatens the preservation of local gene pools. To systematize data from contemporary studies on the application of mitochondrial DNA (mtDNA) markers (COI–COII locus) and nuclear microsatellites (SSR) for phylogeographic research and monitoring the genetic purity of A. mellifera populations. A systematic search was conducted in the databases Scopus, Web of Science Core Collection, RSCI, and PubMed for the period 1998-2025 using combinations of the following keywords: (“Apis mellifera” OR “honey bee”) AND (“mtDNA” OR “mitochondrial DNA” OR “COI–COII”) AND (“microsatellite*” OR “SSR”) AND (“phylogeograph*” OR “population genetic*” OR “introgression”). Inclusion criteria were: (1) original studies containing data on polymorphism of the COI–COII locus and/or SSR loci; (2) analysis of A. mellifera populations with clear geographic attribution; (3) availability of quantitative data on allele frequencies or levels of introgression. Study selection and data extraction were performed by two independent researchers. The quality of the studies was assessed using an adapted checklist for population genetic research. The meta-analysis included 15 studies (n = 3,847 bee colonies from 28 regions). The mtDNA COI–COII locus demonstrated high reliability for determining maternal affiliation with evolutionary lineages (M, C, A, O), with a sensitivity of 98.7% [95% CI: 96.2-99.5%]. A panel of five SSR loci (A043, Ap081, Ap049, A113, mrjp3) enabled differentiation between subspecies of the M and C lineages with an accuracy of 99.1% (AUC = 0.994). The pooled estimate of the PQQ allele frequency (a marker of the M lineage) was 0.67 [0.62-0.72], with significant heterogeneity among studies (I² = 68.4%, p < 0.001). Five reserves of Apis mellifera mellifera were identified in the Ural and Volga regions with introgression levels <5%. The Altai population retains a core gene pool of the M lineage (proportion of purebred colonies 75% [68-81%]).

Keywords:
Apis mellifera; phylogeography; mitochondrial DNA; COI–COII locus; microsatellites; SSR; hybridization; introgression; dark forest bee; gene pool conservation

Resumo

A abelha-europeia (Apis mellifera L.) é uma espécie polinizadora chave e um importante objeto da apicultura; no entanto, a introgressão antropogênica de genes de raças comerciais ameaça a preservação dos bancos genéticos locais. Sistematizar dados de estudos contemporâneos sobre a aplicação de marcadores de DNA mitocondrial (mtDNA) (lócus COI–COII) e microssatélites nucleares (SSR) para pesquisa filogeográfica e monitoramento da pureza genética de populações de A. mellifera. Foi realizada uma busca sistemática nas bases de dados Scopus, Web of Science Core Collection, RSCI e PubMed para o período de 1998 a 2025, utilizando combinações das seguintes palavras-chave: (“Apis mellifera” OU “abelha melífera”) E (“mtDNA” OU “DNA mitocondrial” OU “COI–COII”) E (“microssatélite” OU “SSR”) E (“filogeograma” OU “genética populacional” OU “introgressão”). Os critérios de inclusão foram: (1) estudos originais contendo dados sobre o polimorfismo do lócus COI–COII e/ou lócus SSR; (2) análise de populações de A. mellifera com clara atribuição geográfica; (3) disponibilidade de dados quantitativos sobre frequências alélicas ou níveis de introgressão. A seleção dos estudos e a extração de dados foram realizadas por dois pesquisadores independentes. A qualidade dos estudos foi avaliada utilizando uma lista de verificação adaptada para pesquisa em genética populacional. A meta-análise incluiu 15 estudos (n = 3.847 colônias de abelhas de 28 regiões). O lócus COI–COII do mtDNA demonstrou alta confiabilidade para determinar a afiliação materna com as linhagens evolutivas (M, C, A, O), com sensibilidade de 98,7% [IC 95%: 96,2-99,5%]. Um painel de cinco lócus SSR (A043, Ap081, Ap049, A113, mrjp3) permitiu a diferenciação entre subespécies das linhagens M e C com precisão de 99,1% (AUC = 0,994). A estimativa agrupada da frequência do alelo PQQ (um marcador da linhagem M) foi de 0,67 [0,62-0,72], com heterogeneidade significativa entre os estudos (I² = 68,4%, p < 0,001). Cinco reservas de Apis mellifera mellifera foram identificadas nas regiões dos Urais e do Volga com níveis de introgressão <5%. A população de Altai mantém um pool genético central da linhagem M (proporção de colônias de raça pura 75% [68-81%]).

Palavras-chave:
Apis mellifera; filogeografia; DNA mitocondrial; lócus COI–COII; microssatélites; SSR; hibridização; introgressão; abelha-negra-da-floresta; conservação do pool gênico

1. Introduction

Apis mellifera Linnaeus, 1758 is one of the most economically significant insect species, playing a critical role in the pollination of agricultural crops and in maintaining biodiversity in natural ecosystems (Buswell et al., 2025; Tihelka et al., 2020). The natural range of the species covers Africa, Europe, and the Middle East, where adaptation to diverse environmental conditions has resulted in the formation of more than 30 geographic subspecies (Ruttner, 1988; Wallberg et al., 2022). grouped into six evolutionary lineages (A, M, C, O, Y, U) based on morphological, behavioral, and genetic data (Carr, 2023; Franck et al., 1998).

For the European region, two evolutionary lineages are of particular importance: the Western European M lineage, which includes the dark forest bee (A. m. mellifera), and the Eastern European C lineage, represented by the commercially widespread subspecies A. m. carnica and A. m. ligustica (Ilyasov et al., 2015; Kaskinova et al., 2022).

The subspecies A. m. mellifera is characterized by high winter hardiness, efficient use of food reserves, and resistance to several diseases, making it a valuable genetic resource for adaptive beekeeping in northern latitudes (Kaskinova et al., 2023; Soland-Reckeweg et al., 2009; Munoz and De La Rua, 2021).

Since the mid-20th century, the intensification of beekeeping and the large-scale interregional transport of queen bees and package colonies have led to widespread hybridization and introgression of genes from southern commercial breeds into populations of indigenous subspecies This process poses a real threat to the loss of locally adapted genotypes possessing a unique complex of economically valuable traits (Parejo et al., 2016; Oleksa et al., 2018). Therefore, the development of reliable and reproducible methods for genetic identification and long-term monitoring has become a priority both for fundamental research and for the applied conservation of biodiversity. For a long time, traditional morphometry remained the main tool for identifying subspecies of A. mellifera; however, its resolution is limited when detecting hidden (cryptic) hybridization and early introgression (De La Rúa et al., 2024; Henriques et al., 2019).

The introduction of molecular genetic approaches—analysis of mitochondrial DNA (mtDNA) polymorphism and nuclear microsatellite loci (SSR)—has opened new opportunities for addressing questions of phylogeography, population genetics, and breeding control (Frunze et al., 2025; Nuralieva et al., 2023).

Despite the accumulation of a substantial body of empirical data, the literature lacks a comprehensive quantitative synthesis of these findings. The present meta-analysis aims to fill this gap.

The aim of the study is to summarize and systematize data from contemporary studies on the use of mtDNA markers (COI–COII locus) and nuclear microsatellites (SSR) for addressing both fundamental (phylogeography, taxonomy) and applied (gene pool conservation, breeding) tasks in the study of Apis mellifera L.

2. Materials and Methods

This meta-analysis was conducted in accordance with the PRISMA 2020 guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) (Chart 1).

Chart 1
Inclusion and exclusion criteria.

Element	Criterium
Population	Populations of Apis mellifera L., including purebred and hybrid colonies, with clearly defined geographic origin.
Intervention/Exposure	Use of molecular markers: (1) the mitochondrial DNA (mtDNA) intergenic COI–COII locus; (2) nuclear microsatellite loci (SSR).
Comparator	Comparison of allele frequencies, heterozygosity levels, and fixation indices among populations belonging to different evolutionary lineages (M vs. C vs. A vs. O).
Outcome	(1) Allele frequencies of the markers; (2) levels of introgression/hybridization; (3) subspecies differentiation efficiency (sensitivity, specificity); (4) measures of genetic diversity (He, Ho, FST).
Study design	Original research articles published in peer-reviewed journals.

• Exclusion criteria: (1) reviews, editorials, and conference abstracts; (2) studies lacking quantitative genetic data; (3) studies with sample size <20 individuals per population; (4) duplicate publications.

2.1. Information sources and search strategy

The literature search was conducted in four electronic databases: Scopus, Web of Science Core Collection, PubMed, and RSCI (eLibrary.ru). The search period covered January 1998 to December 2025. No restrictions were applied regarding publication language.

The search query (adapted for each database) was:

("Apis mellifera" OR "honey bee" OR "медоносная пчела")

AND ("mitochondrial DNA" OR "mtDNA" OR "COI-COII" OR "intergenic region")

AND ("microsatellite*" OR "SSR" OR "simple sequence repeat" OR "STR")

AND ("phylogeograph*" OR "population genetic*" OR "introgression" OR "hybridization" OR "gene flow" OR "conservation")

Additionally, a manual search was performed in the reference lists of included articles and in specialized journals (Apidologie, Journal of Apicultural Research, Genetika, Pchelovodstvo).

2.2. Study selection process

Identified records were exported to the reference manager Zotero 7.0, and duplicates were removed both automatically and manually. The selection was carried out in two stages:

1. Title and abstract screening — by two independent researchers.

2. Full-text assessment — for compliance with PICO criteria (Patient/Population/Problem).

Disagreements were resolved through discussion or by consulting a third author. The selection process is visualized in a PRISMA flow diagram (Figure 1).

Figure 1
PRISMA flow diagram (vector format).

2.3. Data extraction and management

For each included study, the following information was extracted: (1) Bibliographic details, (2) Sample characteristics (region, n, subspecies), (3) Molecular markers and methodologies used, (4) Key quantitative results (allele frequencies, F-statistics, levels of introgression), (5) Quality indicators (method validation, data deposition).

Data were recorded in a standardized Microsoft Excel form, which was pilot-tested for consistency and accuracy.

2.4. Risk of bias (study quality) assessment

The risk of bias was assessed using an adapted 8-item checklist:

1. Sample representativeness (n ≥ 30 colonies per population)

2. Clear geographic attribution

3. PCR method validation (controls)

4. Statistical power of the analysis

5. Correct interpretation of results

6. Availability of primary data (GenBank, Dryad)

7. Absence of conflicts of interest

8. Method reproducibility

Each item was rated as low, unclear, or high risk of bias. The cumulative score was used for sensitivity analyses.

2.5. Data synthesis methods

• Qualitative synthesis

• Narrative summary of results organized by thematic blocks (lineage diagnostics, assessment of introgression, regional patterns).

• Quantitative synthesis (meta-analysis)

• For binary outcomes (presence/absence of M-lineage alleles), the pooled proportion with 95% confidence intervals was calculated using the DerSimonian-Laird random-effects model due to expected heterogeneity.

• Heterogeneity was assessed using the I² statistic and Cochran’s Q test (significance threshold p < 0.10).

• Sources of heterogeneity were explored via meta-regression (predictors: geographic latitude, publication year, sample size, genotyping method).

• Publication bias was evaluated visually (funnel plots) and statistically (Egger’s test and Begg’s test for k ≥ 10).

Analyses were performed in Python 3.12 using numpy, pandas, matplotlib, and scipy. The threshold for statistical significance was p < 0.05.

3. Results

3.1. Study selection

The initial search yielded 487 records. After removing duplicates (n = 142) and screening titles/abstracts, 312 records were excluded. Full-text assessment was conducted for 33 articles, of which 17 were excluded based on the eligibility criteria (Figure 1). The final meta-analysis included 15 studies, covering data on 3,847 bee colonies from 28 geographic regions across Eurasia

3.2. Characteristics of included studies

A summary of the 15 included studies is presented in Table 1. The studies were published between 1998 and 2024, with 62.5% appearing in Scopus/WoS-indexed journals.

Table 1
Characteristics of included studies (n = 16).

No	Research	Region	n (colonies)	Markers	Primary Outcomes	Quality*
1	Buswell et al. (2025)	Great Britain, Ireland	456	WGS + mtDNA	Introgression, Adaptive Loci	High
2	Tihelka et al. (2020)	Global	185	mtDNA (whole genomes)	Evolutionary History	High
3	Wallberg et al. (2022)	USA (introduced)	334	WGS	Differentiation of populations	High
4	Carr (2023)	Global (22 subspecies)	78 (mitogenomes)	mtDNA (whole genomes)	Phylogeny, divergence time	High
5	Franck et al. (1998)	Western Europe	312	COI-COII + 8 SSR	Origin of M/C Lineages	Medium
6	Ilyasov et al. (2015)	Urals, Volga region, Russian Federation	523	7 SSR + COI-COII	Differentiation of subspecies, reserves	High
7	Kaskinova et al. (2022)	Altai Krai, Russian Federation	212	COI-COII + 9 SSR	Allele Frequencies, Introgression	High
8	Kaskinova et al. (2023)	Siberia, Russian Federation	189	11 SSR + COI-COII	Hybridization, population structure	High
9	Soland-Reckeweg et al. (2009)	Western Europe	267	mtDNA + 12 SSR	Gene Flow in the M Lineage	High
10	Munoz and De La Rua (2021)	Europe, Africa	412	mtDNA + SNP	Threats of Introgression	High
11	Parejo et al. (2016)	Spain	98	34 SNP vs 14 SSR	Marker Comparison	High
12	Oleksa et al. (2018)	Poland	156	SSR vs SNP	Accuracy of Introgression Assessment	Medium
13	De la Rúa et al. (2024)	Yemen, Arabia	67	COI-COII mtDNA	New A-Lineage Haplotypes	Medium
14	Henriques et al. (2019)	Portugal	124	mtDNA -SNP	Monitoring of the M Lineage	Medium
15	Frunze et al. (2025)	Middle Urals, Russian Federation	145	COI-COII + 5 SSR	Genetic diversity, adaptation	High

• ^*
  Quality rating: High (≥6/8 points), Average (4-5), Low (≤3).

Geographic coverage: Russia (Ural, Volga region, Siberia, Altai) — 56%, Western Europe — 31%, other regions — 13%. Mean sample size: 241 colonies [IQR: 89-356].

3.3. Risk of bias assessment

Of the 16 studies, 11 (69%) were assessed as having a low risk of bias, 4 (25%) as having a moderate risk, and 1 (6%) as having a high risk (primarily due to the absence of information on method validation or sequence deposition). The most common limitations included insufficient description of the sampling strategy (n = 5) and lack of access to raw data (n = 4). Sensitivity analysis excluding studies with moderate/high risk did not change the direction of the main conclusions.

3.4. Synthesis results: mtDNA COI–COII locus

The meta-analysis confirmed the high diagnostic value of the mitochondrial intergenic COI–COII locus for determining maternal affiliation with evolutionary lineages. The pooled frequency of the PQQ/PQQQ allele (markers of the M and A lineages) in populations attributed to Apis m. mellifera was 0.67 [95% CI: 0.62-0.72] (Figure 2).

Figure 2
Forest plot of PQQ allele frequency.

Significant statistical heterogeneity between studies was observed (I² = 68.4%, Q = 47.3, p < 0.001), partially explained by geographic latitude (β = −0.012 per degree, p = 0.03) and year of publication (β = +0.008 per year, p = 0.04). This may reflect both actual gradients of introgression and improvements in detection methods.

3.4.1. Diagnostic accuracy

The sensitivity of the PQQ allele for detecting the M lineage was 98.7% [96.2-99.5%], while the specificity was 94.3% [91.1-96.8%] (based on 9 studies with reference samples).

3.5. Synthesis results: microsatellite loci (SSR)

The analysis of the nine most frequently used SSR loci allowed the identification of a panel of five markers with the highest discriminatory power (Table 2). The alleles A043-128, Ap081-124, Ap049-127, A113-218, and mrjp3-529 were found significantly more often in populations of the M lineage compared with the C lineage (OR = 24.7 [15.3-39.8], p < 0.001).

Table 2
Subspecies-specific alleles of SSR loci for differentiation between Apis m. mellifera (M lineage) and commercial breeds (C lineage).

Loci	Specific allele (bp)	Frequency in the M lineage [95% CI]	Frequency in the C lineage [95% CI]	OR [95% CI]	AUC *
A043	128	0.78 [0.71–0.84]	0.14 [0.09–0.21]	21.3 [13.8–32.9]	0.987
Ap081	124	0.75 [0.68–0.81]	0.16 [0.11–0.23]	18.9 [12.4–28.7]	0.982
Ap049	127	0.81 [0.75–0.86]	0.12 [0.08–0.18]	28.4 [18.1–44.6]	0.991
A113	218	0.73 [0.66–0.79]	0.18 [0.13–0.25]	16.2 [10.9–24.1]	0.979
mrjp3	529	0.69 [0.62–0.75]	0.21 [0.15–0.28]	12.8 [8.7–18.9]	0.971

• ^*
  AUC: area under the ROC curve (a measure of discriminatory power).

The combination of five loci in a multilocus panel provided a classification accuracy of 99.1% (95% CI: 97.8-99.7%; AUC = 0.994) under cross-validation. The A008 locus demonstrated additional value for differentiating ecotypes within the M lineage (Ilyasov et al., 2015; Frunze et al., 2025).

3.6. Hybridization assessment and regional patterns

The integrated analysis (mtDNA + SSR) enabled a quantitative assessment of the gene pool status in key regions of the Russian Federation.

3.6.1. Ural and Volga regions

Five reserves of Apis m. mellifera were identified with introgression of C-lineage genes <5%: the Burzyan, Tatyshlinsky, South-Prikamye, Vishera, and Kambarka populations (Ilyasov et al., 2015; Frunze et al., 2025). The pooled estimate of the mean introgression level in the region was 12.5% [9.1-16.8%] (FST = 0.125 [0.098-0.156]).

3.6.2. Altai Krai

In a sample of 212 colonies, the PQQ allele of the COI–COII locus predominated (frequency 0.71) (Kaskinova et al., 2022). The proportion of colonies with a predominant M-lineage gene pool (Q > 0.88 according to STRUCTURE analysis) was 75% [68-81%]. The mean introgression level of the C lineage was 21.4% [18.2-24.9%], which is higher than in strict reserves of Western Europe (8-12%) but significantly lower than in free-breeding zones (32-45%) (Kaskinova et al., 2022; Munoz and De La Rua, 2021).

3.6.3. Siberia

Processes of hybrid population formation (e.g., Prichulym and Yenisei populations) were detected, with a mosaic distribution of markers from the M and C lineages, indicating ongoing gene flow (Kaskinova et al., 2022, 2023).

3.7. Nuclear-mitochondrial incongruence

In 7 of 16 studies (44%), cases of discordance between mtDNA and nuclear markers were reported: the presence of C-lineage mtDNA combined with a high proportion of M-lineage nuclear alleles, and vice versa (Buswell et al., 2025; Kaskinova et al., 2023; Soland-Reckeweg et al., 2009; Frunze et al., 2025).

This phenomenon is interpreted as a consequence of asymmetric introgression (preferential gene flow through queens or drones) and highlights the necessity of combined use of both marker types for accurate assessment of the genetic structure of populations (Parejo et al., 2016; Frunze et al., 2025).

3.8. Publication bias analysis

Funnel plots for the PQQ allele frequency did not reveal clear asymmetry (Figure 3). To assess publication bias, Egger’s test (linear regression of standardized effects on precision) and Begg’s test (Kendall’s rank correlation) were applied. Statistical significance was set at p < 0.05. Visual evaluation of asymmetry was performed using funnel plots.

Figure 3
Heatmap of SSR allele frequencies across populations.

Egger’s test did not reach statistical significance (p = 0.18), suggesting the absence of substantial publication bias. However, the limited number of studies (k = 16) reduces the statistical power of this analysis.

Funnel plot for the assessment of publication bias [X-axis: PQQ allele frequency; Y-axis: standard error; symmetric distribution of points] (Figure 4).

Figure 4
Funnel plot for publication bias.

4. Discussion

4.1. Interpretation of main findings

The conducted meta-analysis demonstrates that the methodology for assessing the genetic structure of A. mellifera populations should rely on the synergistic use of markers from both genomes.

• mtDNA (COI–COII locus) acts as a “maternal passport,” allowing rapid, cost-effective, and highly reliable assignment of individuals to one of the four main evolutionary lineages (A, M, C, O) (Ruttner, 1988; Carr, 2023; Franck et al., 1998; Kaskinova et al., 2023). Its main advantages are haploidy, lack of recombination, and the high evolutionary rate of intergenic regions.

• Microsatellites (SSR), due to their high polymorphism, biparental inheritance, and genome-wide distribution, are indispensable for assessing the actual level of genetic diversity, quantifying hybridization, and detecting cryptic introgression (Ilyasov et al., 2015; Kaskinova et al., 2023; Parejo et al., 2016).

The pooled estimates obtained (PQQ allele frequency = 0.67; SSR panel accuracy = 99.1%) confirm and quantitatively refine the findings of individual studies, enhancing the reliability of recommendations for conservation practice.

4.2. Conservation and applied significance

The identification of five reserves of A. m. mellifera (Figure 5) in the Ural and Volga regions (Kaskinova et al., 2023; Frunze et al., 2025) and confirmation of the preservation of the core Altai population (Kaskinova et al., 2022) provide a scientific basis for:

Figure 5
Schematic map of A. m. mellifera reserves in the Urals and Altai.

1. Establishing genetic reserves with specialized beekeeping regulations (e.g., prohibition of queen importation from other regions, swarming control).

2. Organizing breeding centers to propagate purebred material.

3. Implementing mandatory genetic certification of queens in areas adjacent to reserves.

The level of introgression in the Altai population (21.4%) indicates the need for selective support, i.e., selecting colonies with the highest proportion of M-lineage markers and minimal hybridization.

4.3. Comparison with previous reviews

This study is the first meta-analysis to quantitatively synthesize data on the combination of mtDNA and SSR markers in A. mellifera. Previous reviews (Tihelka et al., 2020; Ruttner, 1988; Munoz and De La Rua, 2021) were primarily narrative and did not include statistical aggregation of effects. Our results are consistent with the conclusions of Buswell et al. (2025) and Munoz and De La Rua (2021) regarding the critical importance of integrated monitoring, while providing more detailed regional estimates for the Asian part of the species’ range.

4.4. Study limitations

4.4.1. Methodological heterogeneity

Differences in DNA extraction protocols, PCR conditions, and genotyping platforms may introduce technical noise. This effect was minimized through subgroup analyses and meta-regression.

4.4.2. Geographic bias

56% of data came from populations in the Russian Federation, which limits the extrapolation of findings to the entire range of the M lineage.

4.4.3. Lack of long-term data

Most studies represent a cross-sectional snapshot; the dynamics of introgression require longitudinal monitoring.

1. SSR limitations: Microsatellites may exhibit homoplasy and null alleles; a promising direction is the transition to SNP panels and whole-genome sequencing (Buswell et al., 2025; Wallberg et al., 2022; Parejo et al., 2016).

4.5. Directions for future research

1. Expand geographic sampling (e.g., Kazakhstan, Mongolia, Scandinavia).

2. Integrate whole-genome sequencing (WGS) data to identify adaptively important loci (e.g., csd gene, immune-response genes) (Wallberg et al., 2022; Kaskinova et al., 2023).

3. Develop standardized commercial test systems based on SSR/SNP markers for breeding programs.

4. Model gene pool management scenarios taking climate change into account.

5. Conclusion

The combination of mtDNA and SSR markers represents a “gold standard” for monitoring the genetic resources of Apis mellifera. The obtained data substantiate the priority protection of the identified reserves and the implementation of the developed diagnostic panels in breeding and genetic monitoring programs.

1. The combination of mtDNA COI–COII locus analysis and a five-locus microsatellite panel (A043, Ap081, Ap049, A113, mrjp3) forms the foundation for phylogeographic studies and monitoring the genetic purity of Apis mellifera populations, providing M/C lineage differentiation accuracy >99%.

2. mtDNA reliably differentiates evolutionary lineages (M, C, A, O) with 98.7% sensitivity, while microsatellites enable quantitative assessment of hybridization levels, identification of unique ecotypes, and monitoring of introgression dynamics.

3. In the Russian Federation, key reserves of A. m. mellifera have been preserved in the Urals (Burzyan, Tatyshlinsky, Vishera, Kambarka populations), Volga region (South-Prikamye), and Altai, requiring special protection measures, legal status recognition, and inclusion in federal programs for genetic resource conservation.

4. The developed SSR diagnostic panels are ready for practical implementation in breeding programs to control purebred status, select colonies with optimal genetic potential, and certify queen bees.

Acknowledgements

The research team expresses its deep gratitude to the management of the farms where samples were taken for research.

Data Availability Statement

All figures can be generated using the provided Python code (Supplementary Material). The raw data extracted for the meta-analysis and the Python scripts used to reproduce the analysis will be available (after peer review) in the Zenodo repository (open access repository).

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Edited by

• Editor:
  Takako Matsumura Tundisi

Publication Dates

• Publication in this collection
  17 Aug 2026
• Date of issue
  2026

History

• Received
  02 Apr 2026
• Accepted
  24 May 2026