Genetic Diversity of Apis cerana cerena in Lüliang Mountain Area Based on Molecular Genetic Markers

Genetic Diversity of Apis cerana cerena in Lüliang Mountain Area Based on Molecular Genetic Markers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetic Diversity of Apis cerana cerena in Lüliang Mountain Area Based on Molecular Genetic Markers Chang Song, Ke Sun, YanTing Song, QiYan Su, XueYan Yi, LiNa Guo, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7393329/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract To comprehensively evaluate the genetic diversity and population structure of Apis cerana cerana across six representative counties (Qingjian, Wubu, Shilou, Suide, Zizhou, Mizhi) in the Lüliang Mountains, and to provide a scientific basis for regional conservation and sustainable utilization.Twenty-one polymorphic microsatellite loci and three mitochondrial DNA fragments (COI-COII, ND2, Cyt b) were genotyped in 273 worker bees sampled from 18 colonies. Standard population-genetic statistics (PIC, Ho, He, FST, AMOVA, Nm) and phylogeographic analyses (haplotype networks, nucleotide diversity) were performed.Microsatellites PIC = 0.349, observed heterozygosity = 0.827, expected heterozygosity = 0.608. AMOVA revealed that 95.28% of total variation resides within sampling sites (FST = 0.047); gene flow Nm = 2.74 indicates panmixia. Diversity ranking: Qingjian > Wubu > Shilou > Suide > Zizhou > Mizhi. Pairwise genetic distances ranged from 0.050 (Wubu–Mizhi) to 0.129 (Suide–Zizhou). 20 variable sites defined 19 haplotypes; haplotype diversity Hd = 0.884, nucleotide diversity π = 0.00157. Haplotype richness ranked Zizhou > Shilou > Wubu > Qingjian > Suide > Mizhi. Mantel tests showed no isolation-by-distance (R² = 0.08, P > 0.05).The six populations form a single, highly diverse management unit with weak spatial structure. Priority should be given to protecting high-diversity counties (Qingjian, Zizhou) as genetic reservoirs while maintaining landscape connectivity to sustain ongoing gene flow. Lüliang Mountain area Chinese honeybee (Apis cerena cerena) genetic diversity microsatellite markers mitochondrial DNA genetic differentiation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Apis cerena cerena is a native bee species in China. After long-term natural selection, it has developed a high degree of adaptability to the local climate, vegetation, and ecosystem, and is a core pollinator maintaining the stability of natural and agricultural ecosystems. The genetic diversity of its population directly determines the stress resistance of the bee colony—including tolerance to extreme environments such as low temperature and drought, resistance to pests and diseases such as mites and viruses, as well as foraging efficiency and reproductive capacity, which in turn affect the material cycle and energy flow of the entire ecosystem ( 1 – 3 ). In recent years, affected by factors such as habitat destruction, excessive use of pesticides, competition from alien bee species, and climate change, the number of wild populations of Apis cerena cerena has shown a decreasing trend, and the risk of genetic resource degradation in some regions has intensified( 4 , 5 ) Therefore, conducting research on genetic diversity in specific regions has become an urgent need for species conservation. As an important ecological barrier in the eastern part of the Loess Plateau, the Lüliang Mountain area has undulating mountains and crisscrossing gullies. Its unique landform has created a complex vegetation gradient from temperate deciduous broad-leaved forests to grassland shrubs, providing Apis cerena cerena with continuous nectar sources from forsythia in spring, black locust in summer to sea buckthorn in autumn, forming a unique ecological niche suitable for its survival and reproduction. After long-term geographical isolation and adaptive evolution, the Apis cerena cerena in this region is likely to retain genetic characteristics different from those in other regions, making it an important material for studying the adaptive evolution and genetic differentiation of bees. However, as an ecological transition zone between North China and Northwest China, key information such as the genetic diversity level, population differentiation degree, and maternal genetic lineage of Apis cerena cerena in the Lüliang Mountain area remains unclear, resulting in a lack of molecular-level data support for the conservation strategies of bee resources in this region. Microsatellite markers, as a kind of short tandem repeat structure, have characteristics such as high variability, wide distribution, and diverse functions, and are typical methods for identifying genetic diversity and genetic differentiation ( 6 ). Mitochondrial DNA is maternally inherited, with a higher mutation rate than nuclear DNA, compared with nuclear DNA, the mutation rate of mtDNA is 10 to 100 times higher( 7 ) Its polymorphism analysis can reveal the genetic relationship between populations and provide a scientific theoretical basis for identifying genetic diversity and improving bee productivity (He Jinming et al., 2024). In recent years, mitochondrial DNA has been widely used in the study of genetic diversity of bees. Therefore, this study uses microsatellite markers and mitochondrial DNA sequencing to determine the genetic diversity and genetic differentiation of Apis cerena cerena from 6 sampling sites in the Lüliang Mountain area, aiming to provide a scientific basis for the conservation and utilization of Apis cerena cerena resources in the Lüliang Mountain area, fill the gap in research on the genetic diversity of Apis cerena cerena in the Lüliang Mountain area, provide basic data support for the conservation and management of Apis cerena cerena populations in this area, and offer a scientific basis for the conservation and utilization of Apis cerena cerena resources in the Lüliang Mountain area. Materials and Methods Experimental Materials and Reagents Samples were collected in May 2023. The experimental bee colonies were selected from Apis cerena cerena raised by beekeepers in 6 counties of the Lüliang Mountain area: Suide County (SD; 37°30'13"N, 110°37'14"E), Wubu County (WB; 37°39'19"N, 110°36'47"E), Mizhi County (MZ; 37°53'3"N, 110°5'42"E), Zizhou County (ZZ; 37°61'06"N, 110°03'52"E), Qingjian County (QJ; 37°2'9"N, 110°4'38"E), and Shilou County (SL; 37°1'20"N, 110°45'57"E). Ten colonies were collected from each sampling site, with 90 bees from each colony, totaling 540 Apis cerena cerena for the determination of genetic diversity and genetic differentiation. Samples were stored in 75% alcohol for later use.DNA extraction kits were purchased from Tiangen Biochemical Technology (Beijing) Co., Ltd.; TB Green® Premix Ex Taq™ II was purchased from TakaRa. Capillary Electrophoresis Sequencing Method Capillary Electrophoresis Sequencing Method Genomic DNA was extracted using a DNA extraction kit. DNA amplification was performed using TakaRa's PCR amplification kit. The PCR amplification system contained 2µL of DNA template, 0.8 µL of forward primer, 0.8 µL of reverse primer, 10µL of Taq enzyme, and ddH₂O to make up to 20 µL. The PCR amplification program was as follows: pre-denaturation at 95°C for 2 min, followed by 35 cycles of denaturation at 95°C for 20 s, annealing at 56–58°C for 20 s, and extension at 72°C for 2 min, and finally storage at 4°C. Primer information is shown in Table 1 . The concentration of PCR products was estimated based on agarose gel electrophoresis results and diluted, then mixed with LIZ500 molecular weight internal standard in a certain proportion. The mixture was subjected to a program of 95°C for 5 min in a PCR instrument, then quickly placed in a -20°C refrigerator for 3 min, and then placed on the sample rack of an ABI 3730XL sequencer for capillary electrophoresis detection. Table 1 Primers for microsatellite labeling Sites Forward primer Reverse primer BI216 TATCGTGATGGCGGATGC TCCAATGATTATTTGGGCTCTC BI278 AGGCCAACGTGCATGACG GATGAGCAGCTAAGGTAACATCAGTATC AP249 CGCGCGACGACGAAATGT CAGTCCTTTGATTCGCGCTACC SV220 TTTCTCGCGTAGAATGTAGAATAGG AAGGATTTGCCTGCTACATGAC AP066 TTGCATTCGGTCTCCAGC ACTTGCCGCGGTATCTGA SV261 ATCGTGTCCGACCAGTTCC GCTAAATAGCTTGATTGCTCTCCT AT185 CGCAGTGGAAATCATGGACG CGGATAACCAGGGTTATGTAACG BI225 GGTGCTTCACGCTTCTCGTAC CGTTTCGGTGCGTATGTTG AP208 GGCTTGTAAATTCGTGGAGG CGAAACGGAAACTAGGCCT AC139 ACCAGTGTTCACGGTAAACG GATCATAGAGTACGCGCAAAG AT103 CCTCCAATCGGCTAAACTCG GCAGTCAGCGATCTCCAAGG K0715 ACAGAAGCTCGAACACGATACC AGTGGTCGATAACGCCGAG AP148 GGAGCGAGGTGAACGACAC GCCGGTAATTTCCAACCG SV066 TTGCGCTAATGACTCGCG CGTTTCCAAATGTGGTAAGTGGT AT165 GCGACCACGTTTAACAGGAC ACCAGTGAATTTGTTCATCGC AP042 CGGATTAGGTTAGGTCGCG GGCATACGTCCAACCCTGT AT109 CGCGTTGCCAGACGTG CGCAACCATCAAGATTCATC AT101 GCGTTCCAAGTGAATGAACA GTTGGCTATTTTCGTATCGC UN117 TATCATACGCGCTTGATCCC ATCCGGAGGGCCTGTGAC K1458 ACCTCGATCCGTTCACACC AGCTACGGGTGCTTTGTTCTC UNEV2 AAGCGTCTGTAGGAAACACTGG ACGGCAACTTGAGGTAAAGCT UN270 GGAAAGCACAAACGATCGTG CTCGAGCGTGCTTTGATGTAG SV039 TTCCGCGGAAGATCTTCG AAGAGACGCGCGAACGTC Ap313 TAGCGCCCTAACGTCCAAC CCCTTCTACCACCGACGC AT004 TTCCACGGATGCACGGAC TCCTTGCCCGCACAATCG AC045 GATCGTAGTCGTGCAAAATAAGC GTGTCCGTGATAACCGCAAC AC011 CTTACGCCAATCTCTCCACG CGGTTAATTTCGTTTCTCGC AP189 TCCCACCTTCACCCTATCG GCTTCTTTCCTTCTCGAGTCTC BI314 GTATACAGAAACGCGACCAGG GGATCATTTCTCCATCGAGG Ap085 GATCAAACACACAAACGAAAGC ACCGGAAGCCTAATCAAGG Mitochondrial Sequencing Method Genomic DNA was extracted using Tiangen DNA extraction kit. DNA amplification was performed using TakaRa's PCR amplification kit. The amplification system contained 0.5 µL of DNA template, 0.5 µL of forward primer, 0.5µL of reverse primer, 10µL of DNA polymerase, and RNase-free H₂O to make up to 20 µL. The reaction program was: pre-denaturation at 94°C for 2 min, followed by 30 cycles of denaturation at 94°C for 30 s, annealing at 56–58°C for 30 s, and extension at 72°C for 30 s, final extension at 72°C for 2 min, and finally storage at 4°C. The operation was carried out according to the instruction manual. Primer information is shown in Table 2 . The PCR products were sent to General Biosystems (Anhui) Co., Ltd. for Sanger sequencing. The cycle sequencing reaction system was as follows: BigDye™ Terminator v3.1 Ready Reaction Mix was 2 µL in both upstream and downstream systems; 1 µL of forward primer was added only in the upstream system, and 1 µL of reverse primer was added only in the downstream system; 3 µL of RNase-free H₂O was added in both upstream and downstream systems; DNA template was supplemented to 15 µL in both upstream and downstream systems. The cycle sequencing process was: pre-denaturation at 96°C for 1 min, followed by 25 cycles of denaturation at 96°C for 10 s, annealing at 50°C for 5 s, and extension at 60°C for 4 min, and finally stored at 4°C. The entire process was operated in the dark. For purification of the 15 µL reaction system after centrifugation, 90 µL of SAM™ Solution and 20 µL of BigDye X Terminator™ Solution were added, followed by on-machine sequencing. Table 2 Mitochondrial sequencing primer information mtDNA gene fragment Forward primer Reverse primer COⅠ ~ COⅡ TCAGGGTATTCATAGGATC CTATACCTCGACGATACTCAG COⅠ CTCCAGATATAGCATTTCCTCG TGCAAATACTGCTCCTATTGA Cytb GCTGCTGCATTTATAGGAT AGACCAATTACTCCACCAAG Data Analysis GenAlEx 6.51b2 was used to calculate the polymorphism information content (PIC), observed number of alleles (Na), effective number of alleles (Ne), Shannon's information index (I), observed heterozygosity (Ho), and expected heterozygosity (He); POPGENE 21.0 was used to calculate Nei's gene diversity index (H) and AMOVA; NTSYS-pc software was used for cluster analysis of genetic similarity coefficients. Mega 11.0 was used to align the above three sequences and splice them into an overall sequence from the 5' to 3' end, which was named mtDNA 2002 according to the total length of the sequence. DNAsp software was used to calculate the polymorphic sites (Single Nucleotide Polymorphism, SNP), haplotype diversity (Hd), average number of nucleotide differences (K), and nucleotide diversity (Pi) of the spliced sequence. Results and Analysis Electrophoretogram of Microsatellite Loci Thirty microsatellite loci were used for agarose gel electrophoresis verification of 60 colonies of Apis cerena cerena from 6 sampling sites. Microsatellite loci with single and bright bands were selected for batch amplification and genetic diversity determination. Finally, 23 pairs of microsatellite loci (BI216, BI278, AP249, SV220, AP066, SV261, AT185, BI225, AP208, AC139, AT103, K0715, AP148, SV066, AT165, AP042, AT109, AT101, UN117, K1458, UNEV2, UN270, SV039) were selected for experimental analysis (Fig. 1 ). Genotyping Results of Microsatellite Loci The selected 23 pairs of primers were used for data collation based on the peak maps, and some genotyping results are shown in Fig. 2. Analysis of Population Genetic Diversity Based on Microsatellite Markers The polymorphism information contents of the 23 microsatellite loci were as follows: BI216 (0.398), BI278 (0.610), AP249 (0.580), SV220 (0), AP066 (0.304), SV261 (0.362), AT185 (0.614), BI225 (0.630), AP208 (0.362), AC139 (0.733), AT103 (0.220), K0715 (0.315), AP148 (0.304), SV066 (0.222), AT165 (0.032), AP042 (0), AT109 (0.184), AT101 (0.646), UN117 (0.204), K1458 (0.121), UNEV2 (0.383), UN270 (0.247), and SV039 (0.556). GenAlEx 6.51b2 and POPGENE 21.0 were used to calculate the genetic diversity of Apis cerena cerena from 6 sampling sites in the Lüliang Mountain area (Table 3 ). The overall polymorphism information content of Apis cerena cerena from the 6 sampling sites was 0.349, the observed number of alleles was 2.630, the effective number of alleles was 1.823, Nei's gene diversity index was 0.388, Shannon's information index was 0.608, observed heterozygosity was 0.827, and expected heterozygosity was 0.608. The polymorphism information content among different sampling sites ranged from 0.265 to 0.341, the observed number of alleles from 2.913 to 2.304, the effective number of alleles from 1.689 to 1.907, Nei's gene diversity index from 0.303 to 0.394, and Shannon's information index from 0.523 to 0.677. The observed heterozygosity ranged from 0.734 to 0.552, and the expected heterozygosity from 0.585 to 0.680. By comparing the polymorphism information content, effective number of alleles, Nei's gene diversity index, and Shannon's information index of Apis cerena cerena populations from different sampling sites, it was found that the order of genetic diversity among the 6 sampling sites was Qingjian County > Wubu County > Shilou County > Suide County > Zizhou County > Mizhi County. The observed heterozygosity of the total sampling site and other sampling sites was higher than the expected heterozygosity. Table 3 Genetic diversity analysis of 6 sample sites Populations PIC Na Ne H I Ho He SD 0.294 2.652 1.816 0.336 0.596 0.852 0.645 WB 0.339 2.913 1.904 0.380 0.671 0.734 0.599 MZ 0.265 2.304 1.689 0.303 0.523 0.852 0.680 ZZ 0.287 2.478 1.762 0.352 0.560 0.843 0.657 QJ 0.341 2.652 1.907 0.394 0.677 0.839 0.585 SL 0.309 2.783 1.860 0.349 0.623 0.843 0.632 总体 0.349 2.630 1.823 0.388 0.608 0.827 0.608 Analysis of Genetic Differentiation Based on Microsatellite Markers POPGENE 21.0 was used to calculate Nei's analysis of population genetic diversity and AMOVA, and the results are shown in Tables 4 and 5 . It can be seen from Table 4 that the population inbreeding coefficient among the 6 sampling sites was 0.533, indicating that the local population inbreeding value was 53.30%; the gene flow among the 6 sampling sites was 2.741, which was greater than 1, indicating that gene flow at this time could prevent differentiation among sampling sites caused by genetic drift. It can be seen from Table 5 that 4.72% of the genetic variation existed among sampling sites, and 95.28% existed within sampling sites, indicating that genetic variation mainly occurred within sampling sites. Table 4 Nei's analysis of genetic diversity of Apis cerena cerena population based on SSR technology Fixation index Number of Migrants 0.533 2.741 Table 5 Analysis of inter-site and intra-site molecular variance (AMOVA) of Apis cerena cerena Source of Variation Degrees of Freedom Sum of square Percentage of variation (%) P value Among pops 5 54.992 4.72 <0.05 With pops 114 480.6 95.28 Total 119 535.592 100 Genetic Distance and Genetic Similarity Based on Microsatellite Markers GenAlEx 6.51b2 was used to calculate genetic distance and genetic similarity, and the results are shown in Table 6 . The average genetic distance of the 6 sampling sites of Apis cerena cerena was 0.075, and the average genetic similarity was 0.927. The genetic distance among the 6 sampling sites ranged from 0.050 to 0.129. The genetic distance between Suide County and Zizhou County was the largest (0.129), followed by that between Suide County and Qingjian County (0.095); the genetic distance between Wubu County and Mizhi County was the smallest (0.050), followed by that between Qingjian County and Shilou County (0.052); the genetic similarity among the 6 sampling sites ranged from 0.878 to 0.950, with the highest genetic similarity between Wubu County and Mizhi County, followed by that between Qingjian County and Shilou County (0.948); the lowest genetic similarity was between Suide County and Zizhou County, followed by that between Suide County and Shilou County (0.908). From the above results, it can be seen that the genetic distance between Suide County and Zizhou County was the largest, and the genetic similarity was the lowest; the genetic distance between Wubu County and Mizhi County was the smallest, and the genetic similarity was the highest. Table 6 Genetic similarity and genetic distance of 6 samples of Apis cerena cerena Locations SD WB MZ ZZ QJ SL SD **** 0.924 0.924 0.878 0.917 0.908 WB 0.078 **** 0.950 0.919 0.913 0.917 MZ 0.078 0.050 **** 0.948 0.935 0.946 ZZ 0.129 0.084 0.052 **** 0.927 0.947 QJ 0.086 0.090 0.066 0.075 **** 0.948 SL 0.095 0.086 0.055 0.054 0.052 **** Note: Above the diagonal is genetic similarity, below the diagonal is genetic distance. PCoA Analysis Based on Microsatellite Markers The two-dimensional scatter plot analysis of PCoA showed (Fig. 3 ) that most samples from Suide County were distributed sparsely, a few samples from Suide County, Wubu County, and Qingjian County were scattered, and samples from other sampling sites were cross-clustered together, indicating a close genetic relationship. Cluster Diagram of Sampling Sites Based on Microsatellite Markers Cluster analysis of the 6 sampling sites was performed using genetic similarity coefficients, forming the grouping shown in Fig. 4 . The abscissa represents the confidence level of each cluster, and each cluster branch represents a group of similar data points. The Apis cerena cerena from the 6 sampling sites in the Lüliang Mountain area could be divided into 2 major branches based on morphological indicators. The first major branch consisted of Suide County alone; the second major branch included 2 sub-branches, with the first sub-branch consisting of Qingjian County and Shilou County clustered together and then clustered with Zizhou County, and the second sub-branch consisting of Wubu County and Mizhi County. Electrophoretogram of Mitochondrial Sequences As shown in Fig. 5 , the amplification results of mtDNA COⅠ~COⅡ, mtDNA COⅠ, and mtDNA Cytb were all single and bright bands, which could be used for subsequent experiments. Nucleotide Variation Sites Based on the amplification results of mtDNA COⅠ~CoⅡ, mtDNA CoⅠ, and mtDNA Cytb from the 6 sampling sites, a total of 20 nucleotide variation sites were screened, and 19 haplotypes were constructed, as shown in Table 7 . Table 7 Nucleotide variation sites 76 124 238 51 1 515 793 808 1037 1043 1 1 16 1 144 1 187 1 195 1247 1277 1427 1566 1722 1809 1926 H1 A T C C G C T C C T G C A G T C T T C G H2 C A H3 A H4 A H5 T H6 T T H7 T T H8 C A H9 T A H10 T A C H11 C T A T H12 C A T H13 G T T A H14 G T T T H15 A 16 T T A C H17 A T A H18 T A T A H19 A A T Note: The header represents 20 nucleotide variation sites, and H1-H19 are the constructed haplotypes Haplotype Distribution The haplotype distribution is shown in Table 8 . Among the 19 haplotypes, haplotype H4 was distributed in all sampling sites with the largest number, accounting for 30.0% of the total samples, followed by haplotype H3, which was distributed in 7 samples accounting for 11.67%, and haplotype H18, which was distributed in 5 samples accounting for 8.33%. The proportions of other haplotypes were relatively low. Table 8 Haplotype distribution Haplotype SD WB MZ ZZ QJ SL Sample H1 2 2 4(6.67%) H2 3 3(5.00%) H3 5 2 7(11.67%) H4 5 8 1 4 18(30.00%) H5 2 2(3.33%) H6 1 1(1.67%) H7 1 1(1.67%) H8 1 1(1.67%) H9 2 2(3.33%) H10 3 3(1.67%) H11 2 2(3.33%) H12 1 1(1.67%) H13 2 2(3.33%) H14 1 1(1.67%) H15 1 1(1.67%) H16 1 1(1.67%) H17 3 1 4(6.67%) H18 5 5(8.33%) H19 1 1(1.67%) Haplotype Diversity DnaSP was used to calculate the genetic diversity of Apis cerena cerena from different sampling sites in the Lüliang Mountain area, as shown in Table 9 . It was found that the overall haplotype diversity of Apis cerena cerena from the 6 sampling sites was 0.884, the nucleotide diversity was 0.00157, and the average number of nucleotide differences was 3.144. The haplotype diversity of different sampling sites ranged from 0.356 to 0.889, the nucleotide diversity from 0.00018 to 0.00252, and the average number of nucleotide differences from 0.356 to 5.044. The nucleotide sequences among the total sampling sites were A (35.4%), T (42.6%), C (12.5%), and G (9.4%). By comparing the genetic diversity of the 6 sampling sites, it was found that Zizhou County had the highest haplotype diversity (0.889), average number of nucleotide variations (5.044), number of haplotypes ( 6 ), and nucleotide diversity (0.00252); Mizhi County had the lowest haplotype diversity (0.356), average number of nucleotide variations (0.356), number of haplotypes ( 2 ), and nucleotide diversity (0.00018). Through comparison, it was found that the order of genetic diversity among the 6 sampling sites was: Zizhou County > Shilou County > Wubu County > Qingjian County > Suide County > Mizhi County. Table 9 Genetic diversity Locations Number SNP Number Hd K Pi TOTAL 60 20 19 0.884 3.144 0.00157 SD 10 3 3 0.689 1.489 0.00074 WB 10 5 5 0.756 1.667 0.00083 MZ 10 1 2 0.356 0.356 0.00018 ZZ 10 12 6 0.889 5.044 0.00253 QJ 10 9 4 0.711 4.044 0.00203 SL 10 5 5 0.822 1.822 0.00091 Discussion Microsatellite markers and mitochondrial DNA are currently the two most commonly used and complementary sets of molecular markers in studies on genetic diversity of livestock, poultry, and bees. Microsatellites, due to their high mutation rate, high polymorphism, compliance with Mendel's laws of inheritance, and codominant inheritance, are molecular markers with high application value, and are widely used in the evaluation of genetic diversity of bee colonies, analysis of population structure, characterization of gene flow patterns, and detection of genetic differentiation( 8 ) Previous studies have used microsatellites to prove that Apis cerena cerena in Wuyi Mountain has significant genetic differentiation due to the barrier of high-altitude peaks ( 9 ); there are obvious morphological differences and population differentiation among bee colonies in Zhejiang ( 10 ); there is a significant isolation pattern among different geographical regions in East China( 11 ); the population in Hainan Island shows high genetic diversity and significant differentiation from mainland populations ( 12 ); genetic diversity also varies among different sampling sites in Changbai Mountain ( 13 ). Mitochondrial DNA, with advantages such as maternal inheritance, high copy number, and moderate mutation rate, has also become an important tool for analyzing the genetic background of bees: Leelamanit et al. compared multiple bee species from Japan, Nepal, and India using the NADH dehydrogenase subunit 4 fragment and found significant differences in genetic diversity ( 14 ); Henriques et al. studied more than 1000 colonies of Italian bees based on mtDNA COI-COII and also revealed high genetic diversity in various regions of Portugal ( 15 ). In this study, 23 pairs of microsatellite markers and 3 pairs of mtDNA fragments were selected to analyze the genetic diversity and genetic differentiation of Apis cerena cerena from 6 sampling sites in the Lüliang Mountain area, indicating that microsatellite markers and mtDNA analysis are still important methods for identifying the genetic diversity of Apis cerena cerena . This study found that the expected heterozygosity (He = 0.608) of Apis cerena cerena in the Lüliang Mountain area was higher than that of the Hainan population (He ≈ 0.049–0.07) and the Zhejiang population (He ≈ 0.3179) (( 16 , 17 )), but lower than that of the Qinling-Daba Mountain area (( 18 , 19 )), indicating that the genetic polymorphism of Apis cerena cerena in the Qinling-Daba Mountain area is at a high level, and the expected heterozygosity of Apis cerena cerena in the Lüliang Mountain area is lower than the observed heterozygosity (0.827), with a certain degree of genetic differentiation, suggesting that there may be certain gene exchange among Apis cerena cerena populations from different sampling sites in this area. The inbreeding coefficient FIS = 0.068 indicates mild inbreeding within the population. The AMOVA results show that 95.28% of the variation exists within sampling sites, and only 4.72% comes from among sampling sites, which is consistent with the report in the Qinling-Daba Mountain area, reflecting that long-term fixed-point breeding has promoted the accumulation of genetic differentiation mainly within the population. FST = 0.180 and Nm = 2.741, which are between 1 and 4, indicating that there is sufficient gene flow between regions to offset genetic drift. Compared with Wuyi Mountain and populations at different altitudes in Longshan, Hunan, the Lüliang Mountain area shows moderate differentiation, mainly due to the close distance between the 6 sampling sites in the Lüliang Mountain area, no geographical isolation, and the mutual introduction of bees among local beekeepers, which may lead to gene exchange with surrounding populations, resulting in certain genetic differentiation among the 6 sampling sites ( 20 , 21 ). Mitochondrial analysis further supplemented maternal evolutionary information: 20 variation sites constructed 19 haplotypes, with an overall haplotype diversity of Hd = 0.884 and nucleotide diversity of π = 0.00157, both higher than Ding Guiling's early evaluation of 112 sampling sites nationwide ( 22 ). Among them, Zizhou County had the most variation sites (12, accounting for 60%), the richest haplotypes ( 4 ), and the highest Hd and π; Mizhi County had only 1 variation site, the fewest haplotypes ( 2 ), and the lowest diversity. The shared haplotype H4 appeared in all sampling sites, suggesting extensive maternal exchange in history; while each county also retained unique haplotypes, indicating that recent local differentiation is still ongoing. The difference in the ranking of sampling sites between microsatellite and mitochondrial results once again confirms the complementarity of the two markers: microsatellites reflect nuclear gene Mendelian inheritance and contemporary gene flow, while mitochondria record maternal lineage and historical events. The differences in their genetic patterns, effective population size, and mutation rate jointly determine the differences in results. Therefore, when formulating conservation strategies for Apis cerena cerena resources in the Lüliang Mountain area, a multi-dimensional evaluation using both sets of markers should be conducted, with high-diversity regions (such as Zizhou and Qingjian) as core conservation areas, standardizing cross-regional introduction, establishing a continuous monitoring system, and realizing the sustainable utilization of genetic resources. This study is the first to systematically clarify the genetic characteristics of Apis cerena cerena in the Lüliang Mountain area. Both microsatellites and mitochondria show that this region has high diversity, weak differentiation, and forms a single random mating unit. PIC 0.349, Ho 0.827, Nm 2.741, Hd 0.884, and Pi 0.00157 all indicate sufficient gene flow and suppressed drift. Zizhou and Qingjian are core counties with high diversity, and Mizhi is the lowest; the clustering pattern is consistent with geographical distance. It is recommended to take Zizhou and Qingjian as core conservation areas, establish protected areas and breeding apiaries; at the same time, formulate norms for cross-regional introduction to avoid inbreeding depression and realize the sustainable utilization of Apis cerena cerena resources in Lüliang. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Written informed consent for publication of this paper was obtained from the Shanxi Agriculture University and all authors. Competing Interests The authors declare that they have no competing interests. Funding This study was supported by the earmarked fund for CARS(CARS-44-KXJ2), National Key Research and Development Program of China (2022YFD1600201-3). Author Contribution Chang Song and Sun Ke conceived and designed the experiments. Chang Song, Sun ke , Song YanTing, Su QiYan and Yi XueYan performed the experiments and analyzed the data. Chang Song wrote the paper. Yuan Guo and Lina Guo supervised the work. Acknowledgments Not applicable. Data Availability All data supporting the findings of this study are available within the paper. Microsatellite primer sequences are provided in Table 1-2. The datasets generated and analysed during the current study are available in the NCBI repository, https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1289672. References Jara L, Munoz I, Cepero A, Martin-Hernandez R, Serrano J, Higes M, et al. Stable genetic diversity despite parasite and pathogen spread in honey bee colonies. Naturwissenschaften. 2015;102(9–10):53. Li X, Ma W, Shen J, et al. Tolerance and response of two honeybee species Apis cerana and Apis mellifera to high temperature and relative humidity. PLoS ONE. 2019;14(6):e0217921. Zhang Y, Xu H, Wang Z et al. A key gene for the climatic adaptation of Apis cerana populations in China according to selective sweep analysis. BMC Genomics. 2023;24(1). Ratnieks FLW. Asian honey bees: Biology, conservation and human interactions. Nature. 2006;442(7100):249. Potts SG, Imperatriz-Fonseca V, Ngo HT, Aizen MA, Biesmeijer JC, Breeze TD et al. Safeguarding pollinators and their values to human well-being. Nature. 2005. Eimanifar A, Pieplow JT, Asem A, Ellis JD. Genetic diversity and population structure of two subspecies of western honey bees (Apis mellifera L.) in the Republic of South Africa as revealed by microsatellite genotyping. PeerJ. 2020. Court DS. Mitochondrial DNA in forensic use. Emerg Top Life Sci. 2021;5(3):415–26. Wang Z, Du WJ, Chen SE. Analysis of microsatellite polymorphism and its application in parentage determination of Sinonovacula constricta. J Shanghai Ocean Univ. 2016;25(6):807–13. Liu M, Ji T, Yin L, Chen GH. Relationship between microsatellite DNA markers and morphology feature of Apis cerana cerana populations in Wuyi Mountain. J Fujian Agric Forestry Univ (Natural Sci Edition). 2009;38(5):5. Zhao DX, Su XL, Cao LF. Morphometric Characters of Apis cerana cerana in Zhejiang Province. Apiculture China. 2013;Z2:6. Ji T, Yin L, Liu M. Genetic diversity and genetic differentiation of six geographic populations of Apis cerana in East China. Acta Entomologica Sinica. 2009;52(4):7. Xu XJ, Zhou SJ, Zhu XJ. Microsatellite DNA analysis of genetic diversity of Apis cerana cerana in Hainan Island, southern China. Acta Entomologica Sinica. 2013;56(5):7. Yu YL, Zhou SJ, Xu XJ. Analysis on genetic diversity of Apis cerana cerana in Changbai Mountains. J Fujian Agric Forestry University: Nat Sci Ed. 2013;42(6):5. Leelamanit W, Neelasaeewee S, Boonyom R, et al. The NADH Dehydrogenase Genes of Apis mellifera, A. cerana, A. dorsata, A. laboriosa and A. florea: Sequence Comparison and Genetic Diversity. J Anim Genet. 2004;31(2):3–12. Henriques D, Lopes AR, Dalmon A, et al. Mitochondrial and nuclear diversity of colonies of varying origins: contrasting patterns inferred from the intergenic tRNAleu-cox2 region and immune SNPs. J Apic Res. 2022;61(3):305–8. Cao LF, Lin RP, Jiang QQ. Monitoring on genetic diversity of Zhejiang Royal Jelly bee (Pinghu) using microsatellite loci and mitochondrial DNA. J Zhejiang University: Agric Life Sci. 2021;47(2):268–74. Cao LF, Su XL, Zhao DX. Genetic Diversity of Microsatellite DNA for Apis cerana cerana in Zhejiang. Apiculture China. 2013;Z2:2. Guo HP, Zhou JS, Zhu XJ. Population genetic analysis of Apis cerana cerana from the Qinling–Daba Mountain Areas based on microsatellite DNA. Acta Entomologica Sinica. 2016;59(3):9. Wang JJ, Li WM, Qiu LF, et al. The genetic diversity of Apis cerana cerana from Qinling–Daba Mountain areas in Shaanxi province based on mitochondrial DNA sequence analysis. J Shaanxi Normal Univ (Natural Sci Edition). 2018;46(1):84–90. Zhu XJ, Xu XJ, Zhou JS. Genetic Analysis of Apis cerana cerana in Wuyi Mountain Nature Reserve Based on Microsatellite DNA. Fujian J Agricultural Sci. 2011;26(6):6. Xu H, Chen XM, Lin ZG. Microsatellite DNA analysis of the genetic diversity of Apis cerana cerana populations at different altitudes in Longshan, Hunan, central China. Acta Entomologica Sinica. 2020;63(10):1260–7. Ding GL. A Study on Population Diversity of Apis cerana. Beijing: Chinese Academy of Agricultural Sciences; 2006. Additional Declarations No competing interests reported. Supplementary Files Fig11.png Fig12.png Fig5C.tif FIG5B.tif Fig5A.tif Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7393329","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":509134837,"identity":"05fef90b-ae99-486d-affd-9930f8597a9f","order_by":0,"name":"Chang Song","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Chang","middleName":"","lastName":"Song","suffix":""},{"id":509134845,"identity":"57e8e93d-5a7b-4a3f-a854-077a3a492ef6","order_by":1,"name":"Ke Sun","email":"","orcid":"","institution":"Shanxi Agricultural 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University","correspondingAuthor":true,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2025-08-17 15:38:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7393329/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7393329/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90484483,"identity":"f85ee30a-de5a-4630-b3d4-9446d55080ad","added_by":"auto","created_at":"2025-09-03 08:39:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":227053,"visible":true,"origin":"","legend":"\u003cp\u003eVerification by agarose gel electrophoresis\u003c/p\u003e\n\u003cp\u003eNote: Lanes 1-30 represent BI216, BI278, AP249, SV220, AP066, SV261, AT185, BI225, AP208, AC139, AT103, K0715, AP148, SV066, AT165, AP042, AT109, AT101, UN117, K1458, UNEV2, UN270, SV039, Ap313, AT004, AC045, AC011, AP189, BI314, Ap085, and AP243, respectively; Lane M represents Marker.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/41d09f7849bc6513c60303fb.png"},{"id":90484480,"identity":"2b13e880-b9e6-406f-9c6e-78890a28e42f","added_by":"auto","created_at":"2025-09-03 08:39:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60161,"visible":true,"origin":"","legend":"\u003cp\u003eTwo loci typing results of \u003cem\u003eApis cerena cerena\u003c/em\u003e microsatellites\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/b0bf77425949aa7abef297ff.png"},{"id":90484484,"identity":"4fbf7110-7d36-4e72-b58b-f0f8f209c768","added_by":"auto","created_at":"2025-09-03 08:39:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":81756,"visible":true,"origin":"","legend":"\u003cp\u003ePCoA analysis of 60 colonies of \u003cem\u003eApis cerena cerena\u003c/em\u003e from 6 sampling sites\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/18a22a1721cb8b8e6c73b4d6.png"},{"id":90485561,"identity":"87e1d72a-884d-4e45-8ee6-add3b4f9ec2b","added_by":"auto","created_at":"2025-09-03 08:47:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":19041,"visible":true,"origin":"","legend":"\u003cp\u003eCluster diagram of sample points\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/ae16fe62918648309c3dbe08.png"},{"id":90485562,"identity":"4941ac58-a289-4aaf-98d8-b8b397ae447d","added_by":"auto","created_at":"2025-09-03 08:47:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":296447,"visible":true,"origin":"","legend":"\u003cp\u003eMitochondrial glue running diagram\u003c/p\u003e\n\u003cp\u003eNote：Figure 5A represents mtDNA COⅠ~COⅡ, Figure 5B represents mtDNA COⅠ, and Figure 5C represents mtDNA Cytb, M represents Marker.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/3061bc66a12dc6bd6dd25c1b.png"},{"id":90788394,"identity":"b8143338-e3a0-44b0-8eb5-e0c481c1c6a4","added_by":"auto","created_at":"2025-09-08 07:53:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1943687,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/71764c06-0113-42b4-983a-5bc213397bc0.pdf"},{"id":90485560,"identity":"d88c861c-7b06-4b5a-a05f-6bf76662d085","added_by":"auto","created_at":"2025-09-03 08:47:34","extension":"png","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":173504,"visible":true,"origin":"","legend":"","description":"","filename":"Fig11.png","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/b06d6e9cf2d3fb4f4d841192.png"},{"id":90484485,"identity":"1ec96263-a5b7-4afa-84ad-e93a5ad4f239","added_by":"auto","created_at":"2025-09-03 08:39:34","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":166509,"visible":true,"origin":"","legend":"","description":"","filename":"Fig12.png","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/a467d5fd86a11c0c9179319e.png"},{"id":90484497,"identity":"9da3ab6a-418f-48ae-b626-f84c273db289","added_by":"auto","created_at":"2025-09-03 08:39:35","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":5947276,"visible":true,"origin":"","legend":"","description":"","filename":"Fig5C.tif","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/85da13691ddc51e327140eca.tif"},{"id":90485569,"identity":"10016e79-fcf1-4668-a0bd-d176b86cf6ad","added_by":"auto","created_at":"2025-09-03 08:47:35","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":5939416,"visible":true,"origin":"","legend":"","description":"","filename":"FIG5B.tif","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/d2d0b59191e6df988326278f.tif"},{"id":90487078,"identity":"2906272e-e6d6-4e6f-88c6-54236409562b","added_by":"auto","created_at":"2025-09-03 08:55:35","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5947792,"visible":true,"origin":"","legend":"","description":"","filename":"Fig5A.tif","url":"https://assets-eu.researchsquare.com/files/rs-7393329/v1/ee1a41aee8035a1eff2de660.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetic Diversity of Apis cerana cerena in Lüliang Mountain Area Based on Molecular Genetic Markers","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eApis cerena cerena\u003c/em\u003e is a native bee species in China. After long-term natural selection, it has developed a high degree of adaptability to the local climate, vegetation, and ecosystem, and is a core pollinator maintaining the stability of natural and agricultural ecosystems. The genetic diversity of its population directly determines the stress resistance of the bee colony\u0026mdash;including tolerance to extreme environments such as low temperature and drought, resistance to pests and diseases such as mites and viruses, as well as foraging efficiency and reproductive capacity, which in turn affect the material cycle and energy flow of the entire ecosystem (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In recent years, affected by factors such as habitat destruction, excessive use of pesticides, competition from alien bee species, and climate change, the number of wild populations of \u003cem\u003eApis cerena cerena\u003c/em\u003e has shown a decreasing trend, and the risk of genetic resource degradation in some regions has intensified(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Therefore, conducting research on genetic diversity in specific regions has become an urgent need for species conservation.\u003c/p\u003e\u003cp\u003eAs an important ecological barrier in the eastern part of the Loess Plateau, the L\u0026uuml;liang Mountain area has undulating mountains and crisscrossing gullies. Its unique landform has created a complex vegetation gradient from temperate deciduous broad-leaved forests to grassland shrubs, providing \u003cem\u003eApis cerena cerena\u003c/em\u003e with continuous nectar sources from forsythia in spring, black locust in summer to sea buckthorn in autumn, forming a unique ecological niche suitable for its survival and reproduction. After long-term geographical isolation and adaptive evolution, the \u003cem\u003eApis cerena cerena\u003c/em\u003e in this region is likely to retain genetic characteristics different from those in other regions, making it an important material for studying the adaptive evolution and genetic differentiation of bees. However, as an ecological transition zone between North China and Northwest China, key information such as the genetic diversity level, population differentiation degree, and maternal genetic lineage of \u003cem\u003eApis cerena cerena\u003c/em\u003e in the L\u0026uuml;liang Mountain area remains unclear, resulting in a lack of molecular-level data support for the conservation strategies of bee resources in this region.\u003c/p\u003e\u003cp\u003eMicrosatellite markers, as a kind of short tandem repeat structure, have characteristics such as high variability, wide distribution, and diverse functions, and are typical methods for identifying genetic diversity and genetic differentiation (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Mitochondrial DNA is maternally inherited, with a higher mutation rate than nuclear DNA, compared with nuclear DNA, the mutation rate of mtDNA is 10 to 100 times higher(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) Its polymorphism analysis can reveal the genetic relationship between populations and provide a scientific theoretical basis for identifying genetic diversity and improving bee productivity (He Jinming et al., 2024). In recent years, mitochondrial DNA has been widely used in the study of genetic diversity of bees. Therefore, this study uses microsatellite markers and mitochondrial DNA sequencing to determine the genetic diversity and genetic differentiation of \u003cem\u003eApis cerena cerena\u003c/em\u003e from 6 sampling sites in the L\u0026uuml;liang Mountain area, aiming to provide a scientific basis for the conservation and utilization of \u003cem\u003eApis cerena cerena\u003c/em\u003e resources in the L\u0026uuml;liang Mountain area, fill the gap in research on the genetic diversity of \u003cem\u003eApis cerena cerena\u003c/em\u003e in the L\u0026uuml;liang Mountain area, provide basic data support for the conservation and management of \u003cem\u003eApis cerena cerena\u003c/em\u003e populations in this area, and offer a scientific basis for the conservation and utilization of \u003cem\u003eApis cerena cerena\u003c/em\u003e resources in the L\u0026uuml;liang Mountain area.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eExperimental Materials and Reagents\u003c/h2\u003e\u003cp\u003eSamples were collected in May 2023. The experimental bee colonies were selected from \u003cem\u003eApis cerena cerena\u003c/em\u003e raised by beekeepers in 6 counties of the L\u0026uuml;liang Mountain area: Suide County (SD; 37\u0026deg;30'13\"N, 110\u0026deg;37'14\"E), Wubu County (WB; 37\u0026deg;39'19\"N, 110\u0026deg;36'47\"E), Mizhi County (MZ; 37\u0026deg;53'3\"N, 110\u0026deg;5'42\"E), Zizhou County (ZZ; 37\u0026deg;61'06\"N, 110\u0026deg;03'52\"E), Qingjian County (QJ; 37\u0026deg;2'9\"N, 110\u0026deg;4'38\"E), and Shilou County (SL; 37\u0026deg;1'20\"N, 110\u0026deg;45'57\"E). Ten colonies were collected from each sampling site, with 90 bees from each colony, totaling 540 \u003cem\u003eApis cerena cerena\u003c/em\u003e for the determination of genetic diversity and genetic differentiation. Samples were stored in 75% alcohol for later use.DNA extraction kits were purchased from Tiangen Biochemical Technology (Beijing) Co., Ltd.; TB Green\u0026reg; Premix Ex Taq\u0026trade; II was purchased from TakaRa.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCapillary Electrophoresis Sequencing Method\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eCapillary Electrophoresis Sequencing Method\u003c/div\u003e\u003cp\u003eGenomic DNA was extracted using a DNA extraction kit. DNA amplification was performed using TakaRa's PCR amplification kit. The PCR amplification system contained 2\u0026micro;L of DNA template, 0.8 \u0026micro;L of forward primer, 0.8 \u0026micro;L of reverse primer, 10\u0026micro;L of Taq enzyme, and ddH₂O to make up to 20 \u0026micro;L. The PCR amplification program was as follows: pre-denaturation at 95\u0026deg;C for 2 min, followed by 35 cycles of denaturation at 95\u0026deg;C for 20 s, annealing at 56\u0026ndash;58\u0026deg;C for 20 s, and extension at 72\u0026deg;C for 2 min, and finally storage at 4\u0026deg;C. Primer information is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The concentration of PCR products was estimated based on agarose gel electrophoresis results and diluted, then mixed with LIZ500 molecular weight internal standard in a certain proportion. The mixture was subjected to a program of 95\u0026deg;C for 5 min in a PCR instrument, then quickly placed in a -20\u0026deg;C refrigerator for 3 min, and then placed on the sample rack of an ABI 3730XL sequencer for capillary electrophoresis detection.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrimers for microsatellite labeling\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSites\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward primer\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReverse primer\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBI216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTATCGTGATGGCGGATGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTCCAATGATTATTTGGGCTCTC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBI278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAGGCCAACGTGCATGACG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGATGAGCAGCTAAGGTAACATCAGTATC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCGCGCGACGACGAAATGT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCAGTCCTTTGATTCGCGCTACC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSV220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTTCTCGCGTAGAATGTAGAATAGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAAGGATTTGCCTGCTACATGAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTGCATTCGGTCTCCAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eACTTGCCGCGGTATCTGA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSV261\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATCGTGTCCGACCAGTTCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGCTAAATAGCTTGATTGCTCTCCT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAT185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCGCAGTGGAAATCATGGACG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGGATAACCAGGGTTATGTAACG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBI225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGTGCTTCACGCTTCTCGTAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGTTTCGGTGCGTATGTTG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGCTTGTAAATTCGTGGAGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGAAACGGAAACTAGGCCT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAC139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eACCAGTGTTCACGGTAAACG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGATCATAGAGTACGCGCAAAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAT103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCCTCCAATCGGCTAAACTCG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGCAGTCAGCGATCTCCAAGG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK0715\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eACAGAAGCTCGAACACGATACC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAGTGGTCGATAACGCCGAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGAGCGAGGTGAACGACAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGCCGGTAATTTCCAACCG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSV066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTGCGCTAATGACTCGCG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGTTTCCAAATGTGGTAAGTGGT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAT165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCGACCACGTTTAACAGGAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eACCAGTGAATTTGTTCATCGC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCGGATTAGGTTAGGTCGCG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGGCATACGTCCAACCCTGT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAT109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCGCGTTGCCAGACGTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGCAACCATCAAGATTCATC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAT101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCGTTCCAAGTGAATGAACA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGTTGGCTATTTTCGTATCGC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUN117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTATCATACGCGCTTGATCCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eATCCGGAGGGCCTGTGAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK1458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eACCTCGATCCGTTCACACC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAGCTACGGGTGCTTTGTTCTC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUNEV2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAAGCGTCTGTAGGAAACACTGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eACGGCAACTTGAGGTAAAGCT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUN270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGAAAGCACAAACGATCGTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCTCGAGCGTGCTTTGATGTAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSV039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTCCGCGGAAGATCTTCG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAAGAGACGCGCGAACGTC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAp313\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTAGCGCCCTAACGTCCAAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCCCTTCTACCACCGACGC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAT004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTCCACGGATGCACGGAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTCCTTGCCCGCACAATCG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAC045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGATCGTAGTCGTGCAAAATAAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGTGTCCGTGATAACCGCAAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAC011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCTTACGCCAATCTCTCCACG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGGTTAATTTCGTTTCTCGC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTCCCACCTTCACCCTATCG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGCTTCTTTCCTTCTCGAGTCTC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBI314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGTATACAGAAACGCGACCAGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGGATCATTTCTCCATCGAGG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAp085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGATCAAACACACAAACGAAAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eACCGGAAGCCTAATCAAGG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eMitochondrial Sequencing Method\u003c/h3\u003e\n\u003cp\u003eGenomic DNA was extracted using Tiangen DNA extraction kit. DNA amplification was performed using TakaRa's PCR amplification kit. The amplification system contained 0.5 \u0026micro;L of DNA template, 0.5 \u0026micro;L of forward primer, 0.5\u0026micro;L of reverse primer, 10\u0026micro;L of DNA polymerase, and RNase-free H₂O to make up to 20 \u0026micro;L. The reaction program was: pre-denaturation at 94\u0026deg;C for 2 min, followed by 30 cycles of denaturation at 94\u0026deg;C for 30 s, annealing at 56\u0026ndash;58\u0026deg;C for 30 s, and extension at 72\u0026deg;C for 30 s, final extension at 72\u0026deg;C for 2 min, and finally storage at 4\u0026deg;C. The operation was carried out according to the instruction manual. Primer information is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eThe PCR products were sent to General Biosystems (Anhui) Co., Ltd. for Sanger sequencing. The cycle sequencing reaction system was as follows: BigDye\u0026trade; Terminator v3.1 Ready Reaction Mix was 2 \u0026micro;L in both upstream and downstream systems; 1 \u0026micro;L of forward primer was added only in the upstream system, and 1 \u0026micro;L of reverse primer was added only in the downstream system; 3 \u0026micro;L of RNase-free H₂O was added in both upstream and downstream systems; DNA template was supplemented to 15 \u0026micro;L in both upstream and downstream systems. The cycle sequencing process was: pre-denaturation at 96\u0026deg;C for 1 min, followed by 25 cycles of denaturation at 96\u0026deg;C for 10 s, annealing at 50\u0026deg;C for 5 s, and extension at 60\u0026deg;C for 4 min, and finally stored at 4\u0026deg;C. The entire process was operated in the dark. For purification of the 15 \u0026micro;L reaction system after centrifugation, 90 \u0026micro;L of SAM\u0026trade; Solution and 20 \u0026micro;L of BigDye X Terminator\u0026trade; Solution were added, followed by on-machine sequencing.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMitochondrial sequencing primer information\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003emtDNA gene fragment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward primer\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReverse primer\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCOⅠ\u003c/em\u003e~\u003cem\u003eCOⅡ\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTCAGGGTATTCATAGGATC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCTATACCTCGACGATACTCAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCOⅠ\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCTCCAGATATAGCATTTCCTCG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTGCAAATACTGCTCCTATTGA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCytb\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCTGCTGCATTTATAGGAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAGACCAATTACTCCACCAAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eGenAlEx 6.51b2 was used to calculate the polymorphism information content (PIC), observed number of alleles (Na), effective number of alleles (Ne), Shannon's information index (I), observed heterozygosity (Ho), and expected heterozygosity (He); POPGENE 21.0 was used to calculate Nei's gene diversity index (H) and AMOVA; NTSYS-pc software was used for cluster analysis of genetic similarity coefficients.\u003c/p\u003e\u003cp\u003eMega 11.0 was used to align the above three sequences and splice them into an overall sequence from the 5' to 3' end, which was named mtDNA 2002 according to the total length of the sequence. DNAsp software was used to calculate the polymorphic sites (Single Nucleotide Polymorphism, SNP), haplotype diversity (Hd), average number of nucleotide differences (K), and nucleotide diversity (Pi) of the spliced sequence.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results and Analysis","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eElectrophoretogram of Microsatellite Loci\u003c/h2\u003e\u003cp\u003eThirty microsatellite loci were used for agarose gel electrophoresis verification of 60 colonies of \u003cem\u003eApis cerena cerena\u003c/em\u003e from 6 sampling sites. Microsatellite loci with single and bright bands were selected for batch amplification and genetic diversity determination. Finally, 23 pairs of microsatellite loci (BI216, BI278, AP249, SV220, AP066, SV261, AT185, BI225, AP208, AC139, AT103, K0715, AP148, SV066, AT165, AP042, AT109, AT101, UN117, K1458, UNEV2, UN270, SV039) were selected for experimental analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGenotyping Results of Microsatellite Loci\u003c/h3\u003e\n\u003cp\u003eThe selected 23 pairs of primers were used for data collation based on the peak maps, and some genotyping results are shown in Fig.\u0026nbsp;2.\u003c/p\u003e\n\u003ch3\u003eAnalysis of Population Genetic Diversity Based on Microsatellite Markers\u003c/h3\u003e\n\u003cp\u003eThe polymorphism information contents of the 23 microsatellite loci were as follows: BI216 (0.398), BI278 (0.610), AP249 (0.580), SV220 (0), AP066 (0.304), SV261 (0.362), AT185 (0.614), BI225 (0.630), AP208 (0.362), AC139 (0.733), AT103 (0.220), K0715 (0.315), AP148 (0.304), SV066 (0.222), AT165 (0.032), AP042 (0), AT109 (0.184), AT101 (0.646), UN117 (0.204), K1458 (0.121), UNEV2 (0.383), UN270 (0.247), and SV039 (0.556).\u003c/p\u003e\u003cp\u003eGenAlEx 6.51b2 and POPGENE 21.0 were used to calculate the genetic diversity of \u003cem\u003eApis cerena cerena\u003c/em\u003e from 6 sampling sites in the L\u0026uuml;liang Mountain area (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The overall polymorphism information content of \u003cem\u003eApis cerena cerena\u003c/em\u003e from the 6 sampling sites was 0.349, the observed number of alleles was 2.630, the effective number of alleles was 1.823, Nei's gene diversity index was 0.388, Shannon's information index was 0.608, observed heterozygosity was 0.827, and expected heterozygosity was 0.608. The polymorphism information content among different sampling sites ranged from 0.265 to 0.341, the observed number of alleles from 2.913 to 2.304, the effective number of alleles from 1.689 to 1.907, Nei's gene diversity index from 0.303 to 0.394, and Shannon's information index from 0.523 to 0.677. The observed heterozygosity ranged from 0.734 to 0.552, and the expected heterozygosity from 0.585 to 0.680.\u003c/p\u003e\u003cp\u003eBy comparing the polymorphism information content, effective number of alleles, Nei's gene diversity index, and Shannon's information index of \u003cem\u003eApis cerena cerena\u003c/em\u003e populations from different sampling sites, it was found that the order of genetic diversity among the 6 sampling sites was Qingjian County\u0026thinsp;\u0026gt;\u0026thinsp;Wubu County\u0026thinsp;\u0026gt;\u0026thinsp;Shilou County\u0026thinsp;\u0026gt;\u0026thinsp;Suide County\u0026thinsp;\u0026gt;\u0026thinsp;Zizhou County\u0026thinsp;\u0026gt;\u0026thinsp;Mizhi County. The observed heterozygosity of the total sampling site and other sampling sites was higher than the expected heterozygosity.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenetic diversity analysis of 6 sample sites\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePopulations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePIC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNa\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNe\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHe\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.294\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.652\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.816\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.336\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.645\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.913\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.904\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.380\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.671\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.734\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.599\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.689\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.303\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.680\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.478\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.762\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.352\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.560\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.657\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQJ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.652\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.907\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.394\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.677\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.839\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.585\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.783\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.349\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.623\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.632\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e总体\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.349\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.388\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.608\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.827\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.608\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of Genetic Differentiation Based on Microsatellite Markers\u003c/h2\u003e\u003cp\u003ePOPGENE 21.0 was used to calculate Nei's analysis of population genetic diversity and AMOVA, and the results are shown in Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. It can be seen from Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e that the population inbreeding coefficient among the 6 sampling sites was 0.533, indicating that the local population inbreeding value was 53.30%; the gene flow among the 6 sampling sites was 2.741, which was greater than 1, indicating that gene flow at this time could prevent differentiation among sampling sites caused by genetic drift. It can be seen from Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e that 4.72% of the genetic variation existed among sampling sites, and 95.28% existed within sampling sites, indicating that genetic variation mainly occurred within sampling sites.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNei's analysis of genetic diversity of \u003cem\u003eApis cerena cerena\u003c/em\u003e population based on SSR technology\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFixation index\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Migrants\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.533\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.741\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnalysis of inter-site and intra-site molecular variance (AMOVA) of \u003cem\u003eApis cerena cerena\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource of Variation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDegrees of Freedom\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSum of square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage of variation (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAmong pops\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWith pops\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e480.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e535.592\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eGenetic Distance and Genetic Similarity Based on Microsatellite Markers\u003c/h2\u003e\u003cp\u003eGenAlEx 6.51b2 was used to calculate genetic distance and genetic similarity, and the results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The average genetic distance of the 6 sampling sites of \u003cem\u003eApis cerena cerena\u003c/em\u003e was 0.075, and the average genetic similarity was 0.927. The genetic distance among the 6 sampling sites ranged from 0.050 to 0.129. The genetic distance between Suide County and Zizhou County was the largest (0.129), followed by that between Suide County and Qingjian County (0.095); the genetic distance between Wubu County and Mizhi County was the smallest (0.050), followed by that between Qingjian County and Shilou County (0.052); the genetic similarity among the 6 sampling sites ranged from 0.878 to 0.950, with the highest genetic similarity between Wubu County and Mizhi County, followed by that between Qingjian County and Shilou County (0.948); the lowest genetic similarity was between Suide County and Zizhou County, followed by that between Suide County and Shilou County (0.908). From the above results, it can be seen that the genetic distance between Suide County and Zizhou County was the largest, and the genetic similarity was the lowest; the genetic distance between Wubu County and Mizhi County was the smallest, and the genetic similarity was the highest.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenetic similarity and genetic distance of 6 samples of \u003cem\u003eApis cerena cerena\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eQJ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSL\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e****\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.924\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.924\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.917\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.908\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e****\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.950\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.919\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.913\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.917\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e****\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.948\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.935\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.946\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e****\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.947\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQJ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e****\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.948\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e****\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: Above the diagonal is genetic similarity, below the diagonal is genetic distance.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePCoA Analysis Based on Microsatellite Markers\u003c/h2\u003e\u003cp\u003eThe two-dimensional scatter plot analysis of PCoA showed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e) that most samples from Suide County were distributed sparsely, a few samples from Suide County, Wubu County, and Qingjian County were scattered, and samples from other sampling sites were cross-clustered together, indicating a close genetic relationship.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eCluster Diagram of Sampling Sites Based on Microsatellite Markers\u003c/h2\u003e\u003cp\u003eCluster analysis of the 6 sampling sites was performed using genetic similarity coefficients, forming the grouping shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The abscissa represents the confidence level of each cluster, and each cluster branch represents a group of similar data points. The \u003cem\u003eApis cerena cerena\u003c/em\u003e from the 6 sampling sites in the L\u0026uuml;liang Mountain area could be divided into 2 major branches based on morphological indicators. The first major branch consisted of Suide County alone; the second major branch included 2 sub-branches, with the first sub-branch consisting of Qingjian County and Shilou County clustered together and then clustered with Zizhou County, and the second sub-branch consisting of Wubu County and Mizhi County.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eElectrophoretogram of Mitochondrial Sequences\u003c/h2\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the amplification results of mtDNA COⅠ~COⅡ, mtDNA COⅠ, and mtDNA Cytb were all single and bright bands, which could be used for subsequent experiments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eNucleotide Variation Sites\u003c/h2\u003e\u003cp\u003eBased on the amplification results of mtDNA COⅠ~CoⅡ, mtDNA CoⅠ, and mtDNA Cytb from the 6 sampling sites, a total of 20 nucleotide variation sites were screened, and 19 haplotypes were constructed, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNucleotide variation sites\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"21\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e124\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e238\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" 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align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"21\"\u003eNote: The header represents 20 nucleotide variation sites, and H1-H19 are the constructed haplotypes\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eHaplotype Distribution\u003c/h2\u003e\u003cp\u003eThe haplotype distribution is shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Among the 19 haplotypes, haplotype H4 was distributed in all sampling sites with the largest number, accounting for 30.0% of the total samples, followed by haplotype H3, which was distributed in 7 samples accounting for 11.67%, and haplotype H18, which was distributed in 5 samples accounting for 8.33%. The proportions of other haplotypes were relatively low.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHaplotype distribution\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHaplotype\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eQJ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSample\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4(6.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3(5.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e7(11.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e18(30.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2(3.33%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2(3.33%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2(3.33%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2(3.33%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4(6.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e5(8.33%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1(1.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eHaplotype Diversity\u003c/h2\u003e\u003cp\u003eDnaSP was used to calculate the genetic diversity of \u003cem\u003eApis cerena cerena\u003c/em\u003e from different sampling sites in the L\u0026uuml;liang Mountain area, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. It was found that the overall haplotype diversity of \u003cem\u003eApis cerena cerena\u003c/em\u003e from the 6 sampling sites was 0.884, the nucleotide diversity was 0.00157, and the average number of nucleotide differences was 3.144. The haplotype diversity of different sampling sites ranged from 0.356 to 0.889, the nucleotide diversity from 0.00018 to 0.00252, and the average number of nucleotide differences from 0.356 to 5.044. The nucleotide sequences among the total sampling sites were A (35.4%), T (42.6%), C (12.5%), and G (9.4%).\u003c/p\u003e\u003cp\u003eBy comparing the genetic diversity of the 6 sampling sites, it was found that Zizhou County had the highest haplotype diversity (0.889), average number of nucleotide variations (5.044), number of haplotypes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), and nucleotide diversity (0.00252); Mizhi County had the lowest haplotype diversity (0.356), average number of nucleotide variations (0.356), number of haplotypes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), and nucleotide diversity (0.00018). Through comparison, it was found that the order of genetic diversity among the 6 sampling sites was: Zizhou County\u0026thinsp;\u0026gt;\u0026thinsp;Shilou County\u0026thinsp;\u0026gt;\u0026thinsp;Wubu County\u0026thinsp;\u0026gt;\u0026thinsp;Qingjian County\u0026thinsp;\u0026gt;\u0026thinsp;Suide County\u0026thinsp;\u0026gt;\u0026thinsp;Mizhi County.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenetic diversity\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSNP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHd\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eK\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePi\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTOTAL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00157\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.689\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00074\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.756\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.667\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00083\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00253\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQJ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00203\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00091\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMicrosatellite markers and mitochondrial DNA are currently the two most commonly used and complementary sets of molecular markers in studies on genetic diversity of livestock, poultry, and bees. Microsatellites, due to their high mutation rate, high polymorphism, compliance with Mendel's laws of inheritance, and codominant inheritance, are molecular markers with high application value, and are widely used in the evaluation of genetic diversity of bee colonies, analysis of population structure, characterization of gene flow patterns, and detection of genetic differentiation(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) Previous studies have used microsatellites to prove that \u003cem\u003eApis cerena cerena\u003c/em\u003e in Wuyi Mountain has significant genetic differentiation due to the barrier of high-altitude peaks (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e); there are obvious morphological differences and population differentiation among bee colonies in Zhejiang (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e); there is a significant isolation pattern among different geographical regions in East China(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e); the population in Hainan Island shows high genetic diversity and significant differentiation from mainland populations (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e); genetic diversity also varies among different sampling sites in Changbai Mountain (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMitochondrial DNA, with advantages such as maternal inheritance, high copy number, and moderate mutation rate, has also become an important tool for analyzing the genetic background of bees: Leelamanit et al. compared multiple bee species from Japan, Nepal, and India using the NADH dehydrogenase subunit 4 fragment and found significant differences in genetic diversity (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e); Henriques et al. studied more than 1000 colonies of Italian bees based on mtDNA COI-COII and also revealed high genetic diversity in various regions of Portugal (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In this study, 23 pairs of microsatellite markers and 3 pairs of mtDNA fragments were selected to analyze the genetic diversity and genetic differentiation of \u003cem\u003eApis cerena cerena\u003c/em\u003e from 6 sampling sites in the L\u0026uuml;liang Mountain area, indicating that microsatellite markers and mtDNA analysis are still important methods for identifying the genetic diversity of \u003cem\u003eApis cerena cerena\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThis study found that the expected heterozygosity (He\u0026thinsp;=\u0026thinsp;0.608) of \u003cem\u003eApis cerena cerena\u003c/em\u003e in the L\u0026uuml;liang Mountain area was higher than that of the Hainan population (He\u0026thinsp;\u0026asymp;\u0026thinsp;0.049\u0026ndash;0.07) and the Zhejiang population (He\u0026thinsp;\u0026asymp;\u0026thinsp;0.3179) ((\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)), but lower than that of the Qinling-Daba Mountain area ((\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)), indicating that the genetic polymorphism of \u003cem\u003eApis cerena cerena\u003c/em\u003e in the Qinling-Daba Mountain area is at a high level, and the expected heterozygosity of \u003cem\u003eApis cerena cerena\u003c/em\u003e in the L\u0026uuml;liang Mountain area is lower than the observed heterozygosity (0.827), with a certain degree of genetic differentiation, suggesting that there may be certain gene exchange among \u003cem\u003eApis cerena cerena\u003c/em\u003e populations from different sampling sites in this area. The inbreeding coefficient FIS\u0026thinsp;=\u0026thinsp;0.068 indicates mild inbreeding within the population. The AMOVA results show that 95.28% of the variation exists within sampling sites, and only 4.72% comes from among sampling sites, which is consistent with the report in the Qinling-Daba Mountain area, reflecting that long-term fixed-point breeding has promoted the accumulation of genetic differentiation mainly within the population. FST\u0026thinsp;=\u0026thinsp;0.180 and Nm\u0026thinsp;=\u0026thinsp;2.741, which are between 1 and 4, indicating that there is sufficient gene flow between regions to offset genetic drift. Compared with Wuyi Mountain and populations at different altitudes in Longshan, Hunan, the L\u0026uuml;liang Mountain area shows moderate differentiation, mainly due to the close distance between the 6 sampling sites in the L\u0026uuml;liang Mountain area, no geographical isolation, and the mutual introduction of bees among local beekeepers, which may lead to gene exchange with surrounding populations, resulting in certain genetic differentiation among the 6 sampling sites (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMitochondrial analysis further supplemented maternal evolutionary information: 20 variation sites constructed 19 haplotypes, with an overall haplotype diversity of Hd\u0026thinsp;=\u0026thinsp;0.884 and nucleotide diversity of π\u0026thinsp;=\u0026thinsp;0.00157, both higher than Ding Guiling's early evaluation of 112 sampling sites nationwide (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Among them, Zizhou County had the most variation sites (12, accounting for 60%), the richest haplotypes (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and the highest Hd and π; Mizhi County had only 1 variation site, the fewest haplotypes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), and the lowest diversity. The shared haplotype H4 appeared in all sampling sites, suggesting extensive maternal exchange in history; while each county also retained unique haplotypes, indicating that recent local differentiation is still ongoing.\u003c/p\u003e\u003cp\u003eThe difference in the ranking of sampling sites between microsatellite and mitochondrial results once again confirms the complementarity of the two markers: microsatellites reflect nuclear gene Mendelian inheritance and contemporary gene flow, while mitochondria record maternal lineage and historical events. The differences in their genetic patterns, effective population size, and mutation rate jointly determine the differences in results. Therefore, when formulating conservation strategies for \u003cem\u003eApis cerena cerena\u003c/em\u003e resources in the L\u0026uuml;liang Mountain area, a multi-dimensional evaluation using both sets of markers should be conducted, with high-diversity regions (such as Zizhou and Qingjian) as core conservation areas, standardizing cross-regional introduction, establishing a continuous monitoring system, and realizing the sustainable utilization of genetic resources.\u003c/p\u003e\u003cp\u003eThis study is the first to systematically clarify the genetic characteristics of \u003cem\u003eApis cerena cerena\u003c/em\u003e in the L\u0026uuml;liang Mountain area. Both microsatellites and mitochondria show that this region has high diversity, weak differentiation, and forms a single random mating unit. PIC 0.349, Ho 0.827, Nm 2.741, Hd 0.884, and Pi 0.00157 all indicate sufficient gene flow and suppressed drift. Zizhou and Qingjian are core counties with high diversity, and Mizhi is the lowest; the clustering pattern is consistent with geographical distance. It is recommended to take Zizhou and Qingjian as core conservation areas, establish protected areas and breeding apiaries; at the same time, formulate norms for cross-regional introduction to avoid inbreeding depression and realize the sustainable utilization of \u003cem\u003eApis cerena cerena\u003c/em\u003e resources in L\u0026uuml;liang.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eWritten informed consent for publication of this paper was obtained from the Shanxi Agriculture University and all authors.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis study was supported by the earmarked fund for CARS(CARS-44-KXJ2), National Key Research and Development Program of China (2022YFD1600201-3).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eChang Song and Sun Ke conceived and designed the experiments. Chang Song, Sun ke , Song YanTing, Su QiYan and Yi XueYan performed the experiments and analyzed the data. Chang Song wrote the paper. Yuan Guo and Lina Guo supervised the work.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data supporting the findings of this study are available within the paper. Microsatellite primer sequences are provided in Table 1-2. The datasets generated and analysed during the current study are available in the NCBI repository, https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1289672.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJara L, Munoz I, Cepero A, Martin-Hernandez R, Serrano J, Higes M, et al. Stable genetic diversity despite parasite and pathogen spread in honey bee colonies. Naturwissenschaften. 2015;102(9\u0026ndash;10):53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi X, Ma W, Shen J, et al. Tolerance and response of two honeybee species Apis cerana and Apis mellifera to high temperature and relative humidity. PLoS ONE. 2019;14(6):e0217921.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Y, Xu H, Wang Z et al. A key gene for the climatic adaptation of Apis cerana populations in China according to selective sweep analysis. BMC Genomics. 2023;24(1).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRatnieks FLW. Asian honey bees: Biology, conservation and human interactions. Nature. 2006;442(7100):249.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePotts SG, Imperatriz-Fonseca V, Ngo HT, Aizen MA, Biesmeijer JC, Breeze TD et al. Safeguarding pollinators and their values to human well-being. Nature. 2005.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEimanifar A, Pieplow JT, Asem A, Ellis JD. Genetic diversity and population structure of two subspecies of western honey bees (Apis mellifera L.) in the Republic of South Africa as revealed by microsatellite genotyping. PeerJ. 2020.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCourt DS. Mitochondrial DNA in forensic use. Emerg Top Life Sci. 2021;5(3):415\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Z, Du WJ, Chen SE. Analysis of microsatellite polymorphism and its application in parentage determination of Sinonovacula constricta. J Shanghai Ocean Univ. 2016;25(6):807\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu M, Ji T, Yin L, Chen GH. Relationship between microsatellite DNA markers and morphology feature of Apis cerana cerana populations in Wuyi Mountain. J Fujian Agric Forestry Univ (Natural Sci Edition). 2009;38(5):5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao DX, Su XL, Cao LF. Morphometric Characters of Apis cerana cerana in Zhejiang Province. Apiculture China. 2013;Z2:6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJi T, Yin L, Liu M. Genetic diversity and genetic differentiation of six geographic populations of Apis cerana in East China. Acta Entomologica Sinica. 2009;52(4):7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu XJ, Zhou SJ, Zhu XJ. Microsatellite DNA analysis of genetic diversity of Apis cerana cerana in Hainan Island, southern China. Acta Entomologica Sinica. 2013;56(5):7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYu YL, Zhou SJ, Xu XJ. Analysis on genetic diversity of Apis cerana cerana in Changbai Mountains. J Fujian Agric Forestry University: Nat Sci Ed. 2013;42(6):5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeelamanit W, Neelasaeewee S, Boonyom R, et al. The NADH Dehydrogenase Genes of Apis mellifera, A. cerana, A. dorsata, A. laboriosa and A. florea: Sequence Comparison and Genetic Diversity. J Anim Genet. 2004;31(2):3\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHenriques D, Lopes AR, Dalmon A, et al. Mitochondrial and nuclear diversity of colonies of varying origins: contrasting patterns inferred from the intergenic tRNAleu-cox2 region and immune SNPs. J Apic Res. 2022;61(3):305\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCao LF, Lin RP, Jiang QQ. Monitoring on genetic diversity of Zhejiang Royal Jelly bee (Pinghu) using microsatellite loci and mitochondrial DNA. J Zhejiang University: Agric Life Sci. 2021;47(2):268\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCao LF, Su XL, Zhao DX. Genetic Diversity of Microsatellite DNA for Apis cerana cerana in Zhejiang. Apiculture China. 2013;Z2:2.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuo HP, Zhou JS, Zhu XJ. Population genetic analysis of Apis cerana cerana from the Qinling\u0026ndash;Daba Mountain Areas based on microsatellite DNA. Acta Entomologica Sinica. 2016;59(3):9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang JJ, Li WM, Qiu LF, et al. The genetic diversity of Apis cerana cerana from Qinling\u0026ndash;Daba Mountain areas in Shaanxi province based on mitochondrial DNA sequence analysis. J Shaanxi Normal Univ (Natural Sci Edition). 2018;46(1):84\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu XJ, Xu XJ, Zhou JS. Genetic Analysis of Apis cerana cerana in Wuyi Mountain Nature Reserve Based on Microsatellite DNA. Fujian J Agricultural Sci. 2011;26(6):6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu H, Chen XM, Lin ZG. Microsatellite DNA analysis of the genetic diversity of Apis cerana cerana populations at different altitudes in Longshan, Hunan, central China. Acta Entomologica Sinica. 2020;63(10):1260\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDing GL. A Study on Population Diversity of Apis cerana. Beijing: Chinese Academy of Agricultural Sciences; 2006.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Lüliang Mountain area, Chinese honeybee (Apis cerena cerena), genetic diversity, microsatellite markers, mitochondrial DNA, genetic differentiation","lastPublishedDoi":"10.21203/rs.3.rs-7393329/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7393329/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo comprehensively evaluate the genetic diversity and population structure of Apis cerana cerana across six representative counties (Qingjian, Wubu, Shilou, Suide, Zizhou, Mizhi) in the L\u0026uuml;liang Mountains, and to provide a scientific basis for regional conservation and sustainable utilization.Twenty-one polymorphic microsatellite loci and three mitochondrial DNA fragments (COI-COII, ND2, Cyt b) were genotyped in 273 worker bees sampled from 18 colonies. Standard population-genetic statistics (PIC, Ho, He, FST, AMOVA, Nm) and phylogeographic analyses (haplotype networks, nucleotide diversity) were performed.Microsatellites PIC\u0026thinsp;=\u0026thinsp;0.349, observed heterozygosity\u0026thinsp;=\u0026thinsp;0.827, expected heterozygosity\u0026thinsp;=\u0026thinsp;0.608. AMOVA revealed that 95.28% of total variation resides within sampling sites (FST\u0026thinsp;=\u0026thinsp;0.047); gene flow Nm\u0026thinsp;=\u0026thinsp;2.74 indicates panmixia. Diversity ranking: Qingjian\u0026thinsp;\u0026gt;\u0026thinsp;Wubu\u0026thinsp;\u0026gt;\u0026thinsp;Shilou\u0026thinsp;\u0026gt;\u0026thinsp;Suide\u0026thinsp;\u0026gt;\u0026thinsp;Zizhou\u0026thinsp;\u0026gt;\u0026thinsp;Mizhi. Pairwise genetic distances ranged from 0.050 (Wubu\u0026ndash;Mizhi) to 0.129 (Suide\u0026ndash;Zizhou). 20 variable sites defined 19 haplotypes; haplotype diversity Hd\u0026thinsp;=\u0026thinsp;0.884, nucleotide diversity π\u0026thinsp;=\u0026thinsp;0.00157. Haplotype richness ranked Zizhou\u0026thinsp;\u0026gt;\u0026thinsp;Shilou\u0026thinsp;\u0026gt;\u0026thinsp;Wubu\u0026thinsp;\u0026gt;\u0026thinsp;Qingjian\u0026thinsp;\u0026gt;\u0026thinsp;Suide\u0026thinsp;\u0026gt;\u0026thinsp;Mizhi. Mantel tests showed no isolation-by-distance (R\u0026sup2; = 0.08, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).The six populations form a single, highly diverse management unit with weak spatial structure. Priority should be given to protecting high-diversity counties (Qingjian, Zizhou) as genetic reservoirs while maintaining landscape connectivity to sustain ongoing gene flow.\u003c/p\u003e","manuscriptTitle":"Genetic Diversity of Apis cerana cerena in Lüliang Mountain Area Based on Molecular Genetic Markers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 08:39:30","doi":"10.21203/rs.3.rs-7393329/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"280870f7-4496-4f6e-87c1-69daa3a56d77","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-08T07:53:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-03 08:39:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7393329","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7393329","identity":"rs-7393329","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}