Abstract
In the present study, thirty autosomal insertion and deletion polymorphic loci were simultaneously amplified and genotyped in a multiplex system, and their allelic frequencies as well as several forensic parameters were obtained in a sample of 236 unrelated healthy Tujia individuals. All the loci were in Hardy-Weinberg equilibrium after applying a Bonferroni correction and all pair-wise loci showed no significant linkage disequilibrium. These loci were observed to be relatively informative and discriminating, quite efficient for forensic applications. Allelic frequencies of 30 loci were compared between the Tujia group and other reference populations, and the results of analysis of molecular variance indicated the Tujia group showed the least significant differences with the Shanghai Han at one locus, and the most with Central Spanish population at 22 loci. We analyzed the population genetic structure by the principal component analysis, the clustering of STRUCTURE program and a Neighbor-Joining tree, and then evaluated the genetic relationships among Tujia and other 15 populations.
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Introduction
Short tandem repeats (STRs) have become popular DNA markers in forensic DNA labs for more than 20 years and have been proved to possess several benefits, which make them especially suitable to identify victims, perpetrators, missing persons, and for kinship testing and population genetic analysis7,8, which were useful for forensic DNA applications (Supplementary method for STR applications), population genetics9,19. About 0.5–1.0 ng genomic DNA was used for amplification with a 25 ul reaction volume. PCR amplification for 30 InDel loci and Amelogenin locus was performed in a single multiplex reaction using the DIPplex Investigator reagent (Qiagen, Hilden, Germany), which was prepared on a GeneAmp® PCR System 9700 thermal cycler (Applied Biosystems, Foster City, CA, USA) under the recommended reaction condition. PCR products of all loci were separated and detected by capillary electrophoresis on the ABI 3500 Genetic Analyzer (Applied Biosystems). Genoty** of InDel loci was analyzed using the BTO 550 (Qiagen) as internal lane standard and by GeneMapper® ID software v3.2 (Applied Biosystems). Experiments were carried out according to the kit control and the ISO 17025 standard in this study.
Statistical analyses
Hardy-Weinberg equilibrium (HWE), allelic frequencies and forensic statistical parameters of 30 InDels were calculated by the modified powerstat (version1.2) spreadsheet (Promega, Madison, WI, USA). Linkage disequilibrium (LD) analysis for all pair-wise InDel loci was performed using the SNPAnalyzer v2.0 (Istech, South Korea)20. Fst and p values for pairwise interpopulation comparisons were calculated based on allele frequencies of 30 InDels by analysis of molecular variance (AMOVA) performed with ARLEQUIN version 3.1 software (http://cmpg.unibe.ch/software/arlequin3). Principal component analysis (PCA) in two forms and phylogenetic reconstruction were employed in MATLAB 2007a (MathWorks Inc., USA), R statistical software v3.0.221 and genetic distance and phylogenetic analysis (DISPAN) program (http://pritch.bsd.uchicago.edu), respectively. The detailed population genetic structure was performed with the STRUCTURE program v2.2 (http://pritch.bsd.uchicago.edu.) to analyze the structure of Tujia and the other populations previously published based on the same 30 InDels.
Results and Discussion
Allele diversities within group
Probability values for Hardy-Weinberg equilibrium tests for 29 InDel loci ranged from 0.0669 (HLD40) to 0.9987 (HLD97), and p < 0.05 was only observed at the HLD88 locus (p = 0.0382). P values were adjusted after applying a Bonferroni correction for all 30 InDel loci analyzed and P > 0.00167 was considered statistically insignificant. Then, the genotype frequency data for all loci showed no deviations from HWE expectations in the sample of Tujia group. Allelic frequencies and forensic statistical parameters of 30 InDels based on the raw genotype (shown in Supplementary Table 1) were shown in Table 1. Allelic frequencies of deletion allele at the 30 InDel loci ranged from 0.0445 to 0.9089 in the group, with a mean value of 0.4939. The observed (HO) and expected heterozygosities (HE) ranged from 0.0890 (HLD118) to 0.5381(HLD92); and 0.0850 (HLD118) to 0.4985(HLD136), with a mean value of 0.4028 and 0.4073, respectively. Twenty-four InDel loci had power of discrimination (PD) values greater than 0.5, except the six loci: HLD39, HLD64, HLD81, HLD99, HLD111, and HLD118 loci. The values of the power of exclusion (PE), the matching probability (MP), the typical paternity index (TPI), and the polymorphic information content (PIC) ranged from 0.0067 to 0.2231, 0.3524 to 0.8379, 0.5488 to 1.0826 and 0.0814 to 0.3742, respectively. The lowest HO, HE, PIC, TPI, PD and PE were observed at HLD 118 locus, and this locus was also found with the lowest polymorphism in other previously studied groups25, Central Spanish26, Basque26, and Hungarian populations27. Pairwise populations had small genetic distances, which indicated that they had close genetic relationships or shared a recent common ancestor.
InDel diversities among populations
Population differentiations for 30 InDels were compared between the Tujia group and other populations previously published based on AMOVA method (p < 0.05). As shown in Table 3, the AMOVA comparison results showed significant differences between the Tujia group and Shanghai Han, Bei**g Han, Guangdong Han, She, **be, South Korean, Tibetan, Yi, Uigur, Kazak, Uruguayan, Hungarian, Basque, Dane, Central Spanish populations at 1, 3, 3, 4, 5, 7, 8, 9, 14, 14, 20, 20, 20, 21 and 22 loci, respectively. The present results demonstrated that the HLD125, HLD99, HLD67, HLD118 loci had relatively high level of genetic variation, with the significant differentiation between Tujia group and other 9, 10, 10 and 11 populations, respectively; while the least differentiation was obtained at the HLD92, HLD101, HLD124 loci with only one pair-wise population. Therefore, allele frequency data obtained at 30 InDels are very important and necessary for forensic application research of different populations.
Principal component analyses
On the basis of the allelic frequencies at the same 30 InDels, PCA figures were constructed by MATLAB 2007a (MathWorks Inc., USA) and R statistical software v3.0.221 among the Tujia group and other 15 reference populations. As shown in Fig. 1a, the variance ratio contribution of the first principal component (PC) was about 77.87% of the total variation and the second accounted for 5.74%. In the PCA diagram, the 16 populations were divided into three relatively independent areas inconsistency with their languages family. Ethnic groups with similar language family basically spread closer. The results indicated that there were close relationships between the Tujia group and Chinese Han populations from different regions, as well as She and South Korean groups. Ya et al. studied the haplotypes of 17 Y-STR loci and preformed the multidimensional scaling plot which also showed the close relationship between Tujia and Han population28; and the similar result was observed in the PCA plot based on the allelic frequencies of HLA-DRB1 locus29. The relatively far genetic relationships between Tujia group and Kazak or Uigur group were observed in the PCA map constructed by mtDNA haplogroup frequencies30 and in the abovementioned HLA-DRB1 PCA plot29, respectively.
A PCA plot showing the genetic relationships.
(a) Tujia group and other 15 reference populations. (b) Tujia, central Asian, western Eurasian and other eastern Eurasian populations were analyzed at individual level.
The genetic relationships among Tujia, central Asian (Uigur and Kazak populations), western Eurasians (Hungarian, Dane, Basque and Central Spanish populations) and other eastern Eurasians (Shanghai Han, Bei**g Han, Guangdong Han, She, **be, South Korean, Tibetan, and Yi populations) were also discerned with the aid of abovementioned InDel datasets at the individual level. Results of individual PCA were presented by the plots of the first two PCs (shown in Fig. 1b), which together accounted for 38.82% of the total variation in these populations. The first PC revealed an east-west geographic division within Eurasians. In concrete terms, all eastern Eurasians tended to cluster on the left of PCA plots, whereas western Eurasians formed a separate cluster on the right. The Tujia people were expectedly clustered within eastern Asian group.
Neighbor-joining phylogenetic reconstruction
We constructed a neighbor-joining (N-J) phylogenetic tree (shown in Fig. 2). The branch in the upper-left corner contained the nine East Asian populations including Tujia group; whereas in the other branch, Dane, Basque, Central Spanish, Uruguayan, and Hungarian populations were found in the lower-left corner. The Kazak and Uigur groups were in the middle of the above two branches. In previous study, the close relationship between Tujia group and Han population was observed in the N-J dendrogram based on the allelic frequencies of HLA-A locus31. The language of Tujia belongs to Tibeto-Burman language system, without written script. Tujias lived with other nationalities like Miao and Han, and many of them can speak Mandarin Chinese and write the Chinese characters. The tight genetic relationship between the Tujia and Han population in Hubei provience was observed based on fifteen STRs, and the present and previous studies indicated that broad genetic exchanges had occurred among them in history32.
A neighbor-joining phylogenetic tree constructed to analyze phylogenetic relationships from Tujia group and 15 reference populations.
Population STRUCTURE analyses
The STRUCTURE program was used to evaluate the genetic structure of Tujia and other 15 populations. As shown in Fig. 3, at K = 2, three clusters were highly visible and easily distinguishable basically by red, green and mixture of the two. When K = 2–7 (in Supplementary Fig. 2), the STRUCTURE analyses revealed three major clusters: the first subpopulation of Dane, Basque, Central Spanish, Uruguayan, and Hungarian populations, the second of Kazak and Uigur; the last one of nine East Asian populations including Tujia group. The results presented here were similar to that of the PCA plot and N-J tree. With the increase of K values, no further population structures were obtained. We should, just as a precaution, study more ancestry informative InDels in the future in order to subdivide the genetic structure of different ethnic groups in China, and to infer the population origin and ancestral components of an unknown individual.
Population STRUCTURE analysis of 16 populations at K = 2, which revealed three major clusters.
Conclusion
In summary, the population data here indicated the 30 InDels had high diversities within the studied group and genetic differentiations among different populations; and could be a useful supplement to the routine detection of autosomal STRs in forensic cases. The PCA plot, N-J tree and STRUCTURE analyses suggested the close relationships between Tujia and Han population in different regions. More ancestry informative InDels and SNPs should be selected and validated to clarify the Tujia ancestral origin.
Additional Information
How to cite this article: Shen, C. et al. A 30-InDel Assay for Genetic Variation and Population Structure Analysis of Chinese Tujia Group. Sci. Rep. 6, 36842; doi: 10.1038/srep36842 (2016).
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Acknowledgements
This project was supported by the National Natural Science Foundation of China (NSFC, No. 81471824, 81525015, 81373248), and Shaanxi Science and Technology Co-ordination and Innovation Project (2015KTCL03-03). Thank Professor Shaoqing Wen for hel** us to draw the Figure 1b.
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C.S. and B.Z. performed the data acquisition and wrote the main manuscript text, X.B. designed the research, T.Y., Z.L., Y.Z., B.W. and X.B. did the data processing and the manuscript modification, J.Y., F.T. and B.Z. prepared the figures. All authors reviewed the manuscript. All authors read and approved the final manuscript.
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Shen, C., Zhu, B., Yao, T. et al. A 30-InDel Assay for Genetic Variation and Population Structure Analysis of Chinese Tujia Group. Sci Rep 6, 36842 (2016). https://doi.org/10.1038/srep36842
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DOI: https://doi.org/10.1038/srep36842
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