Literature DB >> 23690203

Population genetics of 30 INDELs in populations of Poland and Taiwan.

Witold Pepinski1, Monica Abreu-Glowacka, Malgorzata Koralewska-Kordel, Eliza Michalak, Krzysztof Kordel, Anna Niemcunowicz-Janica, Michal Szeremeta, Magdalena Konarzewska.   

Abstract

The Investigator DIPplex(®) kit (Qiagen) contain components for the simultaneous amplification and analysis of 30 biallelic autosomal INDELs and amelogenin. The objective of this study was to estimate the diversity of the 30 markers in Polish (N P = 122) and Taiwanese (N T = 126) population samples and to evaluate their usefulness in forensic genetics. All amplicon lengths were shorter than 160 base pairs. The DIPplex genotype distributions showed no significant deviation from Hardy-Weinberg rule expectations (Bonferroni corrected) except for DLH39 in the Taiwanese population. Among the Poles and the Taiwanese the mean observed heterozygosity values are 0.4385 and 0.4079, and the combined matching probability values are 7.98 × 10(-14) and 1.22 × 10(-11), respectively. The investigated marker set has been confirmed as a potential extension to standard short tandem repeat-based kits or a separate informative system for individual identification and kinship analysis. Eight INDELs have been selected as possible ancestry informative single-nucleotide polymorphisms for further analyses.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23690203      PMCID: PMC3685699          DOI: 10.1007/s11033-013-2521-7

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


Introduction

INDELs (insertion–deletion) or DIPs (deletion–insertion polymorphisms) are short length diallelic polymorphisms, consisting of the presence or absence of short sequences (typically 1–50 bp). They are relatively common throughout the human genome representing 15–20 % of all polymorphisms [1] with the total number estimated at about 2 million [2]. Short amplicon size (50–150 bp), low mutation rate (<2 × 10−8), and capacity to multiplex (30–40 markers) and type using a single multiplexed PCR with fluorescently labeled primers followed by capillary electrophoresis (a current technology for human identification) [3-5] are the main advantages that make INDELs useful in forensic genetics applications including individual identification, kinship testing, population studies and ancient DNA analysis [6-8]. The Investigator DIPplex® kit (Qiagen) contain components for the simultaneous amplification and analysis of 30 biallelic autosomal INDELs and amelogenin. The INDELs are distributed over 19 autosomes at the minimum distance of 10 Mbp to routinely used STR and SNP markers. The allele length variations of the INDELs are between 4 and 22 bp, and all amplicons are shorter than 160 bp.

DNA extraction

Buccal swabs were anonymized and collected from unrelated volunteers along with information on the birthplace and ethnicity of the donor. Signed informed consents were obtained from all the participants and this study complied with the protocol approved by the Ethical Committee of Poznan University of Medical Sciences (Ref: 139/13). The population sample sizes were: Poles (N P = 122), and Taiwanese (N T = 126). The extraction of genomic DNA was carried out using QIAamp® DNA Mini Kit (Qiagen). The quantitation was performed using Quantifiler™ Human DNA Quantification Kit on a 7500 Real-Time PCR System (Applied Biosystems) according to the manufacturer’s specifications. The samples were then normalized to 100 pg/μl and stored at −20 °C until amplification.

Amplification and genotyping

PCR conditions were applied according to the protocol recommended by the manufacturer of the Investigator DIPplex Kit (Qiagen) in PCR System 9700 (Applied Biosystems, USA) with a total reaction volume adjusted to 5 μl containing 1.8 μl nuclease-free water, 1.0 μl reaction mix A, 1.0 μl primer mix, 0.2 μl MultiTaq2 polymerase, and 100 pg DNA template. Control DNA XY5 was used to test performance of the DIPplex Kit. The amplification was performed with 30 PCR cycles. Electrophoresis and typing were performed in 3130 Genetic Analyzer (Applied Biosystems, USA) using a 36 cm capillary array and a denaturing polymer POP-4. BTO 550 (Qiagen) was used as the internal lane standard spanning fragments from 60 to 550 bps. Prior to the analysis, a five dye matrix standard (BT5) was established with the fluorescent labels dyes 6-FAM, BTG, BTY, BTR, and BTO under the Any5Dye virtual filter. Samples were injected for 10 s at 3 kV and electrophoresed for 1000 s at 15 kV at a run temperature of 60 °C. The data were collected using Data Collection v3.0 software. GeneMapper® ID-X v1.1.1 software was used for the INDELs classification.

Statistical analysis

Estimates for genetic diversity (allele frequencies, heterozygosity), conformance to expectations of the Hardy–Weinberg equilibrium (HWE) and for independence (Linkage Disequilibrium, LD) were obtained using GDA v1.0 software [9]. For multiple comparisons, the original significance levels achieved (P values) were transformed by the Bonferroni correction procedure [10], i.e. 30 markers per database yield an actual significance level of 0.0016667. Forensic informativeness was estimated by calculating discrimination power (DP), match probability (MP), polymorphic information content (PIC), typical paternity index (TPI), and power of paternity exclusion (PE) using Powerstats v1.2 spreadsheet (Promega) [11]. Comparison of allele frequency distributions was performed by means of a pairwise population comparison test (R × C contingency test; G. Carmody, Ottawa, Canada). AMOVA and population differentiation exact test were calculated with the Arlequin v.3.5 software [12].

Results and discussion

A representative DIPplex profile obtained from amplification of 100 pg DNA template is presented in Fig. 1. In the Polish population sample the INDELs frequency distributions showed no deviations from HWE (Bonferroni corrected, 0.0025 < P < 1.0000) evaluated by randomization procedure (10,000 cycles). Pairwise comparison using the exact test disequilibrium analysis with 16,000 permutation steps yielded departures from independence for 93 out of 435 pairs of INDELs under the analysis (0.0019 < P < 0.0480) (data not shown). The departures appeared statistically insignificant when the Bonferroni correction was used for the number of analysed loci. Observed heterozygosity for all the systems ranged 0.3525–0.5164, with an average of 0.4385, which is slightly lower than the values reported for Czech [6], German [13], Danish [14], Finnish [15], Central Spain, and the Basque Country populations [16]. In the Taiwanese population sample the INDELs frequency distributions showed no deviations from HWE (0.0032 < P < 1.0000) except for DLH39 (P = 0.0005). There were no statistically significant departures from independence between any pair-wise combination of INDELs (0.0018 < P < 0.0597) (data not shown). Observed heterozygosity for all the systems ranged 0.1270–0.6191, with an average of 0.4079, which corresponds to the values reported for Asian-Americans, and African-Americans [17]. The highest DP loci were HLD114 (DP = 0.660) for Poles and HLD118 (DP = 0.656) for Taiwanese. Based on data of the 30 INDELs the combined MP value among Poles amounts 7.98 × 10−14 which is more than two orders of magnitude lower than the value calculated for the Taiwanese population (1.22 × 10−11). Both parameters however, indicate a favourable value of a random match comparable with that of AmpFlSTR SGM kit [18, 19]. The combined values of PE are 0.9900 versus 0.9884, correspondingly (Table 1).
Fig. 1

Representative DIPplex profile obtained from amplification of 100 pg DNA template

Table 1

Population data and forensic efficiency parameters for 30 DIPplex INDELs in Polish (N P = 122) and Taiwanese (N T = 126) population samples

HLDChromosomal locationGenBank SNP IDPolesTaiwanese
-/DIP/ P HoHePICMPPETPI-/DIP/ P HoHePICMPPETPI
1777q31.1rs16110480.42210.08590.40980.48990.370.3520.1150.840.50790.59710.47620.50190.370.3640.1680.95
2452q31.1rs23079590.46720.70440.47540.49990.370.3660.1670.950.32530.04170.52380.44080.340.4490.2091.05
31317q36.2rs16110010.38110.68750.45080.47670.360.3820.1480.910.70630.83100.42860.41650.330.4320.1320.88
4706q16.1rs23076520.50000.11130.42620.50210.380.3460.1310.870.34130.23550.39680.45140.350.3900.1120.83
5616q13rs16109050.45090.00250.36070.49720.370.3400.0960.790.47620.47290.53970.50090.370.3980.2251.09
611117p11.2rs13050470.47540.01810.39340.50080.370.3400.1100.820.83330.10960.23810.27890.240.5690.0410.66
7585q14.1rs16109370.57381.00000.49180.49110.370.3820.1800.980.56350.58660.52380.49390.370.3960.2091.05
8564q25rs23082920.33200.69440.42620.44810.350.4010.1250.860.38101.00000.47620.47350.360.3920.1680.95
911820p11.1rs164380.59020.09750.40980.48570.370.3590.1250.860.09530.01390.12700.17300.160.7250.0130.57
109211q22.2rs171744760.58200.18440.42620.48860.370.3600.1310.870.53170.14940.42860.50000.370.3490.1320.88
119312q22rs23075700.46311.00000.50000.49930.370.3780.1881.000.42060.46640.52380.48930.370.4000.2091.05
129914q23.1rs23081630.40571.00000.48360.48420.370.3850.1740.970.15870.00320.19050.26810.230.5970.0270.62
13889q22.32rs81905700.56970.36780.45080.49230.370.3640.1480.910.45240.03010.39680.49740.370.3440.1120.83
1410115q26.1rs23074330.41800.58560.45900.48860.370.3700.1540.920.53970.28040.44440.49780.370.3600.1430.90
15675q33.2rs13050560.39340.04500.38520.47750.360.3610.1100.820.34130.69110.42860.45140.350.3970.1320.88
16838p22rs23080720.52870.85190.51640.50040.370.3850.2021.030.57940.14570.55560.48930.370.4200.2411.13
1711417p13.3rs23075810.68850.39000.39340.43070.340.4100.1100.820.71431.00000.41270.40980.320.4350.1220.85
18482q11.2rs283699420.43850.19880.43440.49450.370.3560.1360.880.66671.00000.44440.44620.350.4070.1430.90
1912422q12.3rs64810.36060.43280.42620.46310.350.3850.1310.870.46410.28310.55560.50150.370.4080.2411.13
2012221q22.11rs81785240.54510.71060.51640.49800.370.3880.2021.030.83330.74860.26980.27890.240.5620.0520.68
2112522q11.23rs163880.57790.85250.47540.48860.370.3790.1740.970.52380.59900.47620.50090.370.3650.1680.95
22645q12.3rs16109350.46310.13750.42620.49870.370.3470.1250.860.14291.00000.25400.24590.210.5980.0460.67
23817q21.3rs178799360.55740.46970.45900.49540.370.3640.1540.920.27780.00690.30160.40280.320.4340.0640.72
2413622q13.1rs163630.53281.00000.49180.49990.370.3730.1800.980.56350.00620.61910.49390.370.4640.3141.31
251333p22.1rs20672350.48770.14630.43440.50180.370.3490.1360.880.64291.00000.46030.46100.350.3980.1550.93
269713q12.3rs172388920.50410.07280.41800.50200.370.3640.1480.910.61110.71000.46030.47720.360.3820.1550.93
27401p32.3rs23079560.49590.21060.44260.50210.370.3530.1450.900.35710.12500.39680.46100.350.3880.1160.84
281281q31.3rs23079240.54510.01750.38520.49800.370.3410.1070.820.65080.07750.38100.45630.350.3800.1060.82
29391p22.1rs178784440.58200.00590.35250.48420.370.3470.0830.760.8254 0.0005 0.19050.28940.250.5760.0270.62
30848q24.12rs30814000.46310.15500.43440.50120.370.3640.1480.910.26980.03900.31750.39560.320.4400.0710.73

-/DIP/ frequency of deletion allele, P probability value for HWE, H observed heterozygosity, H expected heterozygosity, PIC polymorphic information content, MP match probability, PE power of exclusion, TPI typical paternity index

Representative DIPplex profile obtained from amplification of 100 pg DNA template Population data and forensic efficiency parameters for 30 DIPplex INDELs in Polish (N P = 122) and Taiwanese (N T = 126) population samples -/DIP/ frequency of deletion allele, P probability value for HWE, H observed heterozygosity, H expected heterozygosity, PIC polymorphic information content, MP match probability, PE power of exclusion, TPI typical paternity index A pairwise testing for heterogeneity using the χ2-test was applied to compare allelic distributions. Minor or no significant differences were found between the Polish sample and Czech [6], Danish [14], Finnish [15], and American-Caucasian [17] data sets. Correspondingly, the comparison between the Taiwanese sample and Asian-Americans [17] yielded no significant differences (0.032 < P < 1.000). On the other hand, among differences revealed between the Poles and the Taiwanese at 14 INDELs (P < 0.05), these at HLD131, HLD111, HLD118, HLD99, HLD48, HLD122, HLD64, HLD81, HLD39, and HLD84 remained significant after the critical value was corrected for multiple testing (Table 2). It is noteworthy that the same loci significantly accounted for diversity between Caucasian and Asian samples, based on North American datasets published elsewhere [17].
Table 2

P values of population differentiation tested by an exact test and population specific F ST indices per polymorphic locus (absolute values)

HLD P value F ST Poles F ST TaiwaneseAverage F ST
770.2020.01080.01070.0107
450.0430.03710.03760.0373
131 0.000 0.18930.18970.1895
700.0220.04630.04680.0466
60.771−0.0027−0.0028−0.0028
111 0.000 0.24500.24680.2459
580.8870.03310.03310.0331
560.4600.00130.00110.0012
118 0.000 0.42600.42820.4271
920.4770.00110.00100.0011
930.569−0.0004−0.0003−0.0004
99 0.000 0.13610.13810.1371
880.1200.02320.02320.0232
1010.0890.02530.02520.0253
670.4630.00170.00190.0018
830.4770.00110.00120.0012
1140.758−0.0026−0.0024−0.0025
48 0.001 0.09620.09660.0964
1240.1510.04400.04370.0439
122 0.000 0.17320.17510.1741
1250.3940.00190.00180.0019
64 0.000 0.21320.21540.2143
81 0.000 0.14520.14590.1455
1360.670−0.0022−0.0021−0.0021
1330.0320.04380.04410.0440
970.1180.01890.01910.0190
400.0460.03460.03490.0347
1280.1130.01890.01920.0190
39 0.000 0.12870.13050.1296
84 0.000 0.07330.07420.0737

Italicised significant differentiation test P values, after Bonferroni correction

P values of population differentiation tested by an exact test and population specific F ST indices per polymorphic locus (absolute values) Italicised significant differentiation test P values, after Bonferroni correction Wright’s F ST was analysed to measure population substructure effects [20]. AMOVA results revealed that most of the molecular variation was due to variation within the analysed populations (92.54 %) rather than among them, with average fixation index values of 0.0743 and 0.0749 (Poles and Taiwanese, respectively). Our findings correspond to those presented by other authors who used AMOVA to compare the allelic frequencies for each DIPplex locus in populations of Europe, Africa, Asia and North America [16, 17]. Moreover, in our analysis individual INDELs displayed noticeable disparities in fixation index spanning from −0.0004 to −0.0003 (HLD93) to 0.4260 and 0.4282 (HLD118) for Poles and Taiwanese, respectively (Table 2). The individual mutation rate of a locus is one of the factors that may explain the observed discrepancy [21]. However, when compared with mutation rates of 10−3–10−5 for STRs [22, 23], SNPs have essentially mutation rates estimated at as low as 10−8 [24]. From the point of view of forensic genetics, markers with high heterozygosity and very low F ST are potentially advantageous due to relatively high discrimination efficiency irrespective of population of origin [24, 25]. High heterozygosity enhances the polymorphism information at each SNP and low F ST diminishes the chance of interpopulation effects. Some SNPs are reported to have remarkably little variation in allele frequency around the world [26]. On the other hand, ancestry informative single-nucleotide polymorphisms (AISNPs) are required to show low heterozygosity and high allele frequency divergence between different ancestral or geographically distant populations (F ST values). These genetic markers are especially useful in establishing the high probability of an individual’s biogeographical ancestry [27, 28]. We have selected eight INDELs (HLD131, HLD111, HLD118, HLD99, HLD122, HLD64, HLD81, HLD39) with F ST higher than 0.1 between Poles and Taiwanese as potential AISNPs for further analyses. Other sets of population data are needed to verify the robustness of these loci.
  22 in total

1.  Estimate of the mutation rate per nucleotide in humans.

Authors:  M W Nachman; S L Crowell
Journal:  Genetics       Date:  2000-09       Impact factor: 4.562

2.  STR data for the AmpFlSTR SGM Plus and Profiler loci from Taiwan.

Authors:  Chih-Wei Wang; Ding-Ping Chen; Chi-Yuan Chen; Shu-Chuan Lu; Chien-Feng Sun
Journal:  Forensic Sci Int       Date:  2003-12-17       Impact factor: 2.395

Review 3.  Small insertions and deletions (INDELs) in human genomes.

Authors:  Julienne M Mullaney; Ryan E Mills; W Stephen Pittard; Scott E Devine
Journal:  Hum Mol Genet       Date:  2010-09-21       Impact factor: 6.150

4.  Developing a SNP panel for forensic identification of individuals.

Authors:  Kenneth K Kidd; Andrew J Pakstis; William C Speed; Elena L Grigorenko; Sylvester L B Kajuna; Nganyirwa J Karoma; Selemani Kungulilo; Jong-Jin Kim; Ru-Band Lu; Adekunle Odunsi; Friday Okonofua; Josef Parnas; Leslie O Schulz; Olga V Zhukova; Judith R Kidd
Journal:  Forensic Sci Int       Date:  2005-12-19       Impact factor: 2.395

5.  Candidate SNPs for a universal individual identification panel.

Authors:  Andrew J Pakstis; William C Speed; Judith R Kidd; Kenneth K Kidd
Journal:  Hum Genet       Date:  2007-02-27       Impact factor: 4.132

6.  Typing of 30 insertion/deletions in Danes using the first commercial indel kit--Mentype® DIPplex.

Authors:  Susanne Lunøe Friis; Claus Børsting; Eszter Rockenbauer; Lena Poulsen; Stine Frisk Fredslund; Carmen Tomas; Niels Morling
Journal:  Forensic Sci Int Genet       Date:  2011-09-07       Impact factor: 4.882

7.  Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

Authors:  Laurent Excoffier; Heidi E L Lischer
Journal:  Mol Ecol Resour       Date:  2010-03-01       Impact factor: 7.090

8.  ESTIMATING F-STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE.

Authors:  B S Weir; C Clark Cockerham
Journal:  Evolution       Date:  1984-11       Impact factor: 3.694

Review 9.  Forensically relevant SNP classes.

Authors:  Bruce Budowle; Angela van Daal
Journal:  Biotechniques       Date:  2008-04       Impact factor: 1.993

10.  Y-chromosomal microsatellite mutation rates: differences in mutation rate between and within loci.

Authors:  B Myhre Dupuy; M Stenersen; T Egeland; B Olaisen
Journal:  Hum Mutat       Date:  2004-02       Impact factor: 4.878

View more
  6 in total

1.  Evaluation of a 49 InDel Marker HID panel in two specific populations of South America and one population of Northern Africa.

Authors:  R S Moura-Neto; R Silva; I C Mello; T Nogueira; A A Al-Deib; B LaRue; J King; B Budowle
Journal:  Int J Legal Med       Date:  2014-12-17       Impact factor: 2.686

2.  Study of InDel genetic markers with forensic and ancestry informative interest in PALOP's immigrant populations in Lisboa.

Authors:  Ana Inácio; Heloísa Afonso Costa; Cláudia Vieira da Silva; Teresa Ribeiro; Maria João Porto; Jorge Costa Santos; Gilberto Igrejas; António Amorim
Journal:  Int J Legal Med       Date:  2016-10-29       Impact factor: 2.686

3.  Population genetic data and forensic parameters of 30 autosomal InDel markers in Santa Catarina State population, Southern Brazil.

Authors:  Sandra Regina Rachadel Torres; Clineu Julien Seki Uehara; Ana Frederica Sutter-Latorre; Bibiana Sgorla de Almeida; Tania Streck Sauerbier; Yara Costa Netto Muniz; Andrea Rita Marrero; Ilíada Rainha de Souza
Journal:  Mol Biol Rep       Date:  2014-06-12       Impact factor: 2.316

4.  Genetic variation and forensic efficiency of autosomal insertion/deletion polymorphisms in Chinese Bai ethnic group: phylogenetic analysis to other populations.

Authors:  Chun-Hua Yang; Cai-Yong Yin; Chun-Mei Shen; Yu-Xin Guo; Qian Dong; Jiang-Wei Yan; Hong-Dan Wang; Yu-Dang Zhang; Hao-Tian Meng; Rui Jin; Feng Chen; Bo-Feng Zhu
Journal:  Oncotarget       Date:  2017-06-13

5.  Genetic diversity and phylogenetic analysis of Chinese Han and Li ethnic populations from Hainan Island by 30 autosomal insertion/deletion polymorphisms.

Authors:  Jing Liu; Ziwei Ye; Zheng Wang; Xing Zou; Guanglin He; Mengge Wang; Shouyu Wang; Yiping Hou
Journal:  Forensic Sci Res       Date:  2019-12-13

6.  Population genetic structure analysis and forensic evaluation of Xinjiang Uigur ethnic group on genomic deletion and insertion polymorphisms.

Authors:  Ting Mei; Chun-Mei Shen; Bo-Feng Zhu; Li-Ping Zhang; Yao-Shun Liu; Hao-Tian Meng; Yu-Dang Zhang; Yu-Xin Guo; Qian Dong; Xin-Xin Wang; Jiang-Wei Yan
Journal:  Springerplus       Date:  2016-07-15
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.