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Letter to the Editor| Volume 7, ISSUE 1, e9-e14, January 2013

Allele frequencies of 15 STRs in five ethnic groups (Han, Gelao, Jing, Shui and Zhuang) in South China

Published:November 01, 2012DOI:https://doi.org/10.1016/j.fsigen.2012.10.009
      Dear Editor,
      Chinese consists of 56 ethnic groups, including a largest ethnic group of Han, and other 55 minor ethnic groups. Among these groups, there are significant differences in language, culture, custom and history. Some studies have been carried out on the genetic relationships among the different ethnic groups [
      • Wu W.
      • Pan L.
      • Hao H.
      • Zheng X.
      • Lin J.
      • Lu D.
      Population genetics of 17 Y-STR loci in a large Chinese Han population from Zhejiang Province, Eastern China.
      ,
      • Li C.
      • Li L.
      • Zhao Z.
      • Lin Y.
      • Que T.
      • Liu Y.
      • Xue J.
      Genetic polymorphism of 17 STR loci for forensic use in Chinese population from Shanghai in East China.
      ,
      • Zhu Y.
      • Lu S.
      • Xie Z.
      • Chen Y.
      • You J.
      Genetic analysis of 15 STR loci in the population of Zhejiang Province (Southeast China).
      ].
      Ethnic minorities Gelao, Jing, Shui and Zhuang are the major ethnic groups in South China. Gelao ethnic group, an aboriginal population residing in Southwest China, has a population of 579 thousand. The Jing is the smallest Chinese ethnic minority with about 21 thousand population, mostly the people of Jing inhabits in the Guangxi Province. Shui ethnic group has a population of 400 thousand living in the Sandu Shui Autonomous County of Guizhou Province. The populations of Gelao, Jing and Shui are living in relatively isolated environments, and seldom contact with other nationalities. Zhuang ethnic group, the second largest official ethnic group in China, currently has a population of nearly 17 million mainly living in Guangxi, Guangdong and Yunnan Provinces of South China. This paper reports the genetic relationships among the five ethnic groups based on the data of STRs.
      The blood samples of 2022 unrelated individuals from five ethnic groups were collected. They include Han (N = 1000), Gelao (N = 316), Jing (N = 312), Shui (N = 204) and Zhuang (N = 190) from the provinces of Guangxi and Guangdong of South China. The locations of the two provinces are shown in the map of China (Fig. 1).
      Figure thumbnail gr1
      Fig. 1Geographic distribution of the focused populations in South China. Guangdong (shadow on the right side): Han; Guangxi (shadow on the left side): Gelao, Jing, Shui and Zhuang.
      Genomic DNA was extracted from each of the blood samples by Chelex-100 method (Bio-rad Company) as described by Walsh et al. [
      • Walsh P.S.
      • Metzger D.A.
      • Higuchi R.
      Chelex 100 as a medium for simple extraction of DNA for PCR-based typing from forensic material.
      ]. DNA samples were amplified using AmpFISTR®.
      IdentifilerTM commercial kits (Applied Biosystems) [
      • Mitra S.
      On Nei and Roychoudhury's sampling variances of heterozygosity and genetic distance.
      ]. PCR amplifications were carried out according to the manufacturer's instructions. Amplified products were carried out on an ABIPRISM 3100 Genetic Analyzer (Applied Biosystems) according to the manufacturer's recommendations.
      Fragment size determination was carried out using Genescan v3.7 software. The observed heterozygosity (Ho), expected heterozygosity (He) and p-values of exact test for Hardy–Weinberg equilibrium (p) were calculated using Genepop v3.4 software [
      • Raymond M.
      • Rousset F.
      GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism.
      ]. Polymorphism information content (PIC), power of discrimination (PD) and power of exclusion (PE) were calculated using Powerstats v1.2 software (Promega Corp.) (http://www.promega.com/genetici-dtools/pow erstats/). Two methods which include analysis of molecular variance (AMOVA) and population pairwise genetic distances (Fst) were performed with Arlequin v3.1 software [
      • Excoffier L.
      • Laval G.
      • Schneider S.
      Arlequin (version 3.0): an integrated software package for population genetics data analysis.
      ]. Neighbor-joining tree was built from Nei genetic distance matrix using the R software [
      • Nei M.
      • Roychoudhury A.K.
      Sampling variances of heterozygosity and genetic distance.
      ]. A new principal component analysis method (multiple co-inertia analysis) was performed among the ethnic groups using the R software adegent package [
      • Jombart T.
      Adegenet: a R package for the multivariate analysis of genetic markers.
      ].
      The allele frequencies and six statistic parameters for the 15 STR loci of the five ethnic groups in South China were shown in Table 1. The Nei genetic distances between the populations of the five ethnic groups were shown in Table 2A, Table 2B. Two other ethnic groups from references (Tujia ethnic group [
      • Deng S.X.
      Genetic polymorphism of 15 STR loci in Chongqing Tujia population.
      ] and Monggol ethnic group [
      • Wang Z.H.
      • Lu B.
      Genetic polymorphism of 15 STR loci in Qinghai Monggol population.
      ]) had been added in the neighbor-joining phylogenetic tree (Fig. 2) for comparisons. The principal components and synthetic variables were shown in Table 3A, Table 3B, and the principal component analysis diagram was shown (Fig. 3).
      Table 1Allele frequencies and six parameters of 15 STR.
      AlleleD8S1179D21S11D7S820CSF1POD3S1358TH01D13S317D16S539D2S1338D19S433vWATPOXD18S51D5S818FGA
      In Han group (N = 1000)
      60.09670.002
      70.00250.00450.27710.00150.00150.0335
      80.00150.14330.00250.06960.30000.00300.54200.0035
      90.00050.06860.03560.47400.14550.25600.11150.0696
      9.30.0321
      100.13650.17230.24150.00050.05010.14050.12500.02700.2147
      110.10300.33470.23250.00050.23650.26350.00300.29150.00500.3073
      120.12350.22650.38980.00050.13700.23450.05100.02300.04380.2392
      12.20.0050
      130.19400.04960.08070.00150.03100.10550.27800.00200.00150.16750.1221
      13.20.00250.0400
      140.18500.01050.04200.00800.01250.25250.27500.21230.0100
      14.20.0910
      150.16600.00250.34350.07000.02850.1816
      15.20.1525
      160.07900.31650.01500.01450.17800.13580.0010
      16.20.0370
      170.01100.23650.06860.00100.21400.09160.0020
      17.20.0045
      180.05400.10160.19650.05180.0280
      190.00500.19370.09250.03970.0596
      200.12010.01350.02210.0455
      210.03350.01660.1271
      21.20.0025
      220.05260.01960.1662
      22.20.0050
      230.18470.00760.2242
      23.20.0085
      240.16270.00500.1582
      24.20.0095
      250.05910.0911
      25.20.0035
      260.00850.0420
      26.20.0030
      270.00300.0170
      280.04600.0060
      28.20.0085
      290.2590
      29.20.0020
      300.2685
      30.20.0100
      310.0980
      31.20.0670
      320.0365
      32.20.1460
      330.0045
      33.20.0435
      34.20.0075
      Ho0.85200.80100.78300.72100.70500.70500.71100.81400.84600.82800.79400.61200.85900.76600.8640
      He0.85200.81900.77100.73600.72600.67200.79200.78500.86500.81500.80000.60600.86200.78200.8620
      P0.61090.19390.34120.07520.75600.42750.11430.06080.20700.46170.08490.29360.09690.75250.4892
      PD0.95800.94700.91700.88200.87500.85100.92400.91600.96600.94100.92900.78000.96300.92000.9670
      PE0.69900.60100.56800.46100.43600.43600.62000.62500.69400.65200.58800.30600.71300.53800.7230
      PIC0.83000.80000.75000.68000.67000.64000.76000.75000.85000.79000.77000.55000.84000.75000.8500
      In Gelao group (N = 316)
      60.0696
      70.04110.27530.00320.0190
      80.19300.05700.36710.5411
      90.03800.00630.54750.11390.17410.08230.0728
      9.2
      9.30.0317
      100.20890.18040.25000.01900.15820.11080.00320.2025
      110.11710.41770.24050.18670.26580.35130.3006
      120.07280.15190.38610.12980.20890.02530.02220.02240.2722
      12.20.00000.0190
      130.16460.01900.06650.04110.19940.25630.17950.1298
      13.20.00000.0506
      140.17410.00950.02530.02530.24370.26900.22120.0032
      14.20.00000.1203
      150.17720.35760.01580.10130.03480.1667
      15.20.00000.1487
      160.06650.29430.01900.00320.21840.16990.0032
      16.20.00000.0127
      170.00950.21840.04750.14560.0545
      17.20.0190
      180.00950.07600.05700.17720.04810.0158
      18.2
      190.02850.18990.08230.08010.1171
      200.07600.06960.04810.0918
      210.04750.00320.1203
      21.20.0032
      220.01900.00320.1962
      22.20.0190
      230.31650.1203
      240.14870.00640.1772
      24.20.0317
      250.05700.0601
      260.00950.0095
      270.01270.0348
      27.2
      280.0063
      290.2911
      300.2468
      30.20.0253
      310.0791
      31.20.1171
      320.0506
      32.20.0981
      33.20.0538
      34.20.0317
      Ho0.86100.79100.72200.66500.76600.58200.72200.79700.86100.78500.83500.54400.86500.77200.9370
      He0.84700.82000.73300.72700.73300.61700.77600.80500.82700.82700.81700.57800.84000.77400.8750
      P0.57540.07200.16280.15130.45020.1062*0.01120.34170.71680.14690.26860.30870.77300.66790.6297
      PD0.95000.94000.88200.88300.87100.80100.91300.92700.94500.94300.93100.74800.95400.90700.9630
      PE0.71600.58300.46200.37600.53700.27000.46200.59400.71600.57100.66600.22900.72500.54800.8710
      PIC0.82000.80000.69000.68000.68000.56000.74000.77000.80000.80000.79000.50000.83000.74000.8600
      In Jing group (N = 312)
      60.12500.0032
      70.00640.32690.0545
      80.20830.00320.02560.30450.5513
      90.02240.04810.02560.42310.10580.26600.00960.18910.0449
      9.30.0417
      100.16350.14420.17310.05770.14740.09300.01920.1923
      110.16350.33330.32370.30130.30770.22760.3237
      120.12180.20510.37180.09300.20190.02560.01280.08650.2276
      12.20.00960.0000
      130.08650.06090.08010.04170.08970.22440.14100.1346
      13.20.05130.0000
      140.14740.00320.02240.00640.04170.14420.27240.20510.0128
      14.20.10900.0000
      150.21470.01280.23080.10260.02890.24680.0064
      15.20.1827
      160.04170.36860.00960.06730.15710.15710.0032
      16.20.0737
      170.02240.33650.06090.24680.0609
      180.01600.03530.07370.21150.01600.0289
      190.00320.16670.06090.05130.1763
      200.00320.15710.02240.0321
      210.05770.01600.0032
      21.20.00000.1090
      220.01600.01280.0096
      22.20.2212
      230.16670.00640.0032
      23.20.1474
      240.21150.1410
      24.20.0224
      250.08010.0513
      25.20.0064
      260.0192
      26.20.0064
      270.0064
      280.07050.0128
      290.1955
      300.2276
      30.20.0160
      310.1058
      31.20.0962
      320.0289
      32.20.2083
      330.0032
      33.20.0385
      34.20.0096
      Ho0.89100.80100.78200.71200.74400.72400.75000.79500.83300.80800.71800.57100.83300.75600.8780
      He0.85600.84100.77900.72200.69800.69500.77600.77800.85900.86200.79300.61000.84100.78600.8640
      P0.78150.52180.09370.65500.74130.21370.07320.69200.07670.11160.08540.37280.06460.30070.8142
      PD0.95600.95200.86000.87800.83200.84400.91400.91000.95800.96100.92500.78900.94500.92000.9600
      PE0.77700.60100.35000.46200.49900.46700.51000.59000.66200.61300.45700.25700.66200.52100.7510
      PIC0.84000.82000.64000.68000.64000.64000.74000.74000.84000.84000.76000.55000.82000.75000.8500
      In Shui group (N = 204)
      60.1618
      70.01470.29410.0196
      80.18140.02940.39220.3971
      90.06860.00490.42160.10780.36770.11770.0098
      9.30.0441
      100.09310.11770.23040.04900.17160.03430.00980.2108
      110.10780.41180.25000.24510.26470.35780.2892
      120.21080.18140.39220.04900.24510.02940.11770.03430.3137
      130.31860.03920.09310.02940.08330.37750.05880.1569
      13.20.0245
      140.06860.01470.04410.00490.00490.12750.25000.2451
      14.20.00000.0539
      150.14220.29900.05880.05390.1961
      15.20.00000.2745
      160.02940.33330.00490.10780.1961
      170.02940.25490.07840.05390.21080.1177
      180.04900.05390.19120.04900.0735
      190.01960.19120.10290.01960.0343
      200.09310.06860.06370.0294
      210.03920.01470.1716
      220.05390.1912
      22.20.0098
      230.16670.01470.1128
      23.20.0049
      240.24510.0588
      24.20.0147
      250.02450.1422
      260.04900.1275
      270.00490.0294
      280.0245
      290.2206
      300.1520
      30.20.0098
      310.2010
      31.20.0980
      320.0098
      32.20.1569
      33.20.1029
      34.20.0245
      Ho0.77500.82400.74500.75500.75500.61800.72000.67600.87300.70600.83300.69600.81400.72500.8630
      He0.81100.84600.74800.72500.73300.70800.74700.73000.85500.75900.83100.69000.84200.75200.8770
      P0.25610.67930.53110.27770.05290.16720.17700.84370.33760.15120.70020.56390.41320.45390.2649
      PD0.93300.95100.89400.85500.86500.86600.89500.88500.95100.90400.92600.81900.95000.88800.9630
      PE0.55300.64300.50100.62500.51800.31300.46400.39300.66200.43700.82000.23400.62500.46900.7200
      PIC0.78000.82000.71000.67000.68000.66000.71000.68000.83000.72000.80000.63000.82000.70000.8600
      In Zhuang group (N = 190)
      60.0684
      70.00530.01580.27900.01050.00530.0263
      80.11580.06320.27900.5632
      90.08420.02110.43160.16840.22110.10530.0474
      9.20.0053
      9.30.0526
      100.17370.18950.23160.10530.15790.10530.03160.1632
      110.17370.41050.24210.23680.27900.28420.00530.3790
      120.12630.15260.41580.10530.26320.03680.01050.07900.2421
      12.20.0105
      130.12630.03160.04740.04210.12630.28950.07900.1316
      13.20.0211
      140.16320.00530.02630.01600.00530.21050.31050.21580.0105
      14.20.1053
      150.16840.28190.06320.03160.2632
      15.20.1526
      160.04210.38300.00530.02110.13160.1316
      16.20.0790
      170.01580.24470.07370.19470.0895
      17.20.0105
      180.01050.06380.08950.20000.04210.0211
      190.01060.24210.11580.03680.0579
      200.07900.01050.03160.0421
      210.03160.00530.01050.1263
      220.05790.00530.1947
      22.20.0158
      230.18420.00530.1368
      240.16320.00530.2000
      24.20.0158
      250.05790.1053
      25.20.0105
      260.01580.0368
      26.20.0053
      270.0211
      280.04740.0105
      290.2684
      300.2737
      30.20.0263
      310.0947
      31.20.0632
      320.0526
      32.20.1421
      330.0053
      33.20.0211
      34.20.0053
      Ho0.84200.76800.78900.76800.64900.78900.76800.76800.86300.80000.78900.59300.85300.69500.8000
      He0.85500.81800.75500.71500.71300.71700.80400.78100.85800.82900.79800.57900.84600.75500.8730
      P0.66240.16690.17260.45150.84820.14840.22730.92100.39580.84570.73450.47060.35810.58440.1787
      PD0.95300.93300.89400.85900.86800.84700.92600.91200.95600.94800.92400.77300.94900.90000.9620
      PE0.67900.54200.58000.54200.35400.58000.54200.54200.72100.59900.58000.26600.70000.42000.5990
      PIC0.83000.79000.72000.66000.66000.67000.77000.74000.84000.80000.76000.53000.82000.71000.8500
      Ho: observed heterozygosity; He: expected heterozygosity; PIC: polymorphism information content; PD: power of discrimination; PE: power of exclusion; P: the p-values of exact test of Hardy–Weinberg equilibrium.
      Table 2AThe information of the five ethnic groups in South China.
      Ethnic groupsHanGelaoJingShuiZhuang
      RegionGuangdongGuangxiGuangxiGuangxiGuangxi
      The number of population1000316312204190
      Combined power of exclusion0.9999980.9999980.9999980.9999950.999996
      Combined matching probability7.93E−185.83E−173.94E−171.44E−164.74E−17
      Table 2BPairwise Nei genetic distance coefficients between the five ethnic groups.
      HanGelaoZhuangJingShui
      Han0.0000
      Gelao0.01860.0000
      Zhuang0.01020.02010.0000
      Jing0.03930.04970.04140.0000
      Shui0.03010.03760.03390.06450.0000
      Figure thumbnail gr2
      Fig. 2Neighbor-joining tree based on Nei genetic distance calculated between five populations (A) and seven populations (B).
      Table 3AThe five principal components for the 15 STR loci.
      PC1PC2PC3PC4PC5
      D8S11790.49700.18800.02380.04800.0001
      D21S110.59640.29530.05760.01170.0001
      D7S8200.17340.21290.23150.04100.0001
      CSF1PO0.15970.21630.10780.08320.0005
      D3S13580.21710.06610.07930.02560.0001
      TH010.54930.11040.11440.01260.0006
      D13S3170.35410.41960.10400.01320.0000
      D16S5390.73620.10030.08130.03070.0001
      D2S13380.43900.19880.22080.02510.0000
      D19S4330.57110.22730.08470.01910.0000
      vWA0.38160.29170.20700.02020.0011
      TPOX0.42110.41330.01520.00020.0004
      D18S510.29620.32900.08110.06650.0000
      D5S8180.29330.22680.14710.01560.0002
      FGA0.17040.47630.03800.03920.0087
      PC: principal component.
      Table 3BThe synthetic variables for the five ethnic groups.
      SynVar1SynVar2SynVar3SynVar4SynVar5
      Han−0.48820.06150.2541−1.92180.0024
      Gelao−1.2109−1.0447−1.00200.66210.2931
      Zhuang−0.45960.42631.68630.8737−2.1221
      Jing0.46541.6141−1.03820.31650.5181
      Shui1.6933−1.05730.09980.0695−0.3776
      Figure thumbnail gr3
      Fig. 3Principal component analysis based on the allele frequencies for 15 STRs.
      All the STR loci analyzed reach the Hardy–Weinberg equilibrium (p > 0.05) in this study except for the D13S317 (p = 0.0112) locus in Gelao ethnic group. For the five ethnic groups, the combined power of discrimination and the combined power of exclusion for the 15 STR loci were higher than 0.99999 (Table 2A). Based on heterozygosity (He) and polymorphic informative content (PIC), FGA may be the most informative locus.
      Nei genetic distances were calculated based on the gene frequencies for 15 STRs to find out the genetic relationships among the five ethnic groups. The result (Table 2A, Table 2B) showed an obvious separation between (Shui), (Jing) groups and (Zhuang, Han, Gelao) groups. The Nei's genetic distances between populations of Han, Jing and Shui were more than 0.03 and Nei's genetic distances between populations of Han, Zhuang and Gelao were less than 0.02. Originally, it was found that Zhuang was closer to Han than other groups (Fig. 2A). After adding two other ethnic groups (Monggol and Tujia), it was found that Zhuang and Tujia were closer to Han than any other groups (Fig. 2B). The principal component analysis showed that the 15 STR loci of five components contribute to the variation. The first two components account for 82.39% of the total sample variation (Table 3A). As shown in Fig. 2A, Zhuang was found to be closer to Han population than other three populations (Gelao, Jing, Shui). The first principal axis of the analysis differentiates the three groups (Han, Zhuang, Gelao) and the other two groups (Jing, Shui) from the five STRs (D16S539, D21S11, D19S433, TH01, and D8S1179), while the second principal component differentiates the Han, Zhuang two groups and Gelao group from the four STRs (FGA, D13S317, TPOX and D18S51). This result also supported the conclusion above.
      This paper follows the ISFG recommendations [
      • Olaisen B.
      • Bär W.
      • Brinkmann B.
      • Budowle B.
      • Carracedo A.
      • Gill P.
      • Lincoln P.
      • Mayr W.R.
      • Rand S.
      DNA recommendations 1997 of the International Society for Forensic Genetics.
      ] and the guidelines for publication of population data requested by the journal [
      • Carracedo A.
      • Butler J.M.
      • Gusmao L.
      • Parson W.
      • Roewer L.
      • Schneider P.M.
      Publication of population data for forensic purposes.
      ].

      Acknowledgment

      This work was supported by National Natural Science Foundation of China (No. 91130009).

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