Abstract
Little is known about polymorphic distribution of telomere-length related genes among ethnicities, which play important roles in the progression of high-altitude pulmonary edema (HAPE). We genotyped 45 single nucleotide polymorphism (SNP) in 300 unrelated healthy volunteers from the following three Chinese ethnic populations: Han (n = 100), Tibetan (n = 100) and Sherpa (n = 100). We used χ2 test, pairwise FST values, and structure clustering analyses to investigate the genetic differences between these populations. Our results first indicated that rs12615793 (ACYP2), rs10936599 (TERC), rs10069690 (TERT) and rs6010620, rs4809324 (RTEL1) showed the greatest number of significant differences between Han and Tibetan, Sherpa and 11 HapMap populations. Meanwhile, we found that rs1056654 and rs1056629 (MPHOSPH6), rs2320615 (NAF1), rs6010621 (RTEL1), rs8105767 and rs2188972 (ZNF208) genotype frequencies showed considerable divergence among Tibetan and Sherpa. Besides, pairwise FST values and structure clustering analyses revealed that Han exhibited a close genetic affinity with CHD and CHB, but revealed a great genetic heterogeneity with YRI and MKK. This work greatly expanded our understanding of the distribution of telomere-length related genes in Chinese populations and may be helpful to forensic applications and population genetic studies.
Keywords: Single nucleotide polymorphism (SNP), telomere-length related gene, ethnic difference
Introduction
Telomeres are nucleoprotein complexes composed of noncoding TTAGGG repeats at the ends of chromosomes in eukaryotic cells that are crucial in maintaining chromosome integrity and genomic stability through prohibiting nucleolytic degradation, chromosomal end-to-end fusion and irregular recombination [1-3].Telomere length is determined by the balance of processes that shorten and lengthen the telomere [4]. The average telomere length ranges from 10 to 15 kb in human somatic cells, and they shorten by 50-200 bp with each cell division [5]. During somatic-cell replication, telomere length progressively shortens due to the inability of DNA polymerase to fully replicate the 3’end of the DNA. In general, a critically short telomere length can trigger cell to enter replicative senescence with a result of cell death [6]. Therefore, telomere length acts as a mitotic clock that defines the lifespan of somatic cells [7,8].
Recently, several genome-wide association studies (GWAS) have identified genetic variants in the ACYP2, MPHOSPH6, NAF1, OBFC1, RTEL1, TERC, TERT and ZNF208 that were associated with the telomere length [9-11]. Furthermore, we explored the association between the eight telomere length-related genes and the risk of high-altitude pulmonary edema (HAPE) in the Chinese Han population and found that the polymorphisms of ACYP2 and RTEL1 were significantly associated with the risk of HAPE, while others several gene polymorphisms were not significantly associated with HAPE risk. Two articles have been published in the Journal of Gene Medicine [12] and Medicine [13], respectively. In addition, an article is being decided.
HAPE is a hypoxia-inducedpulmonary edema characterized by exaggerated pulmonary hypertension caused by stress failure [14]. It may develop in otherwise healthy individuals when first quickly ascended and exposed to altitude above 2500 m. Nevertheless, whether there are differences in different populations have not been unknown.
As we all know, there are 56 ethnic groups in China. The majority of the ethnic people are known as the Han Chinese, which is the most population group (91.59%). Lantian is a county of Xi’an which located in the southern part of the Guanzhong Plain. Tibetan population is a major minority ethnic group, who mostly lives in compact communities located in highlands and mountainous regions, is geographically isolated from other ethnic groups in the region and rarely intermarries with other Chinese ethnic groups. Sherpa refers to a minority ethnic population that has resided for almost 500 years in the Himalayan region, who mostly lives in the border areas with a long life expectancy, where the elevation ranges from 1600 to 4000 m. There are very diverse genetic backgrounds, unique lifestyle, distinct dietary habits, variouscultures and different resident geographical environments between these populations.Previous researches also showed that the incidence of high altitude sickness [15], hypoxic adaptation [16,17], oxygen free radical metabolism [18] are different between Han and Tibetan populations.Genetic susceptibility might have different results from Han population.
We presumed that there might be different genetic information of some telomere-length associated genes in different populations. Therefore, the main aim of this study was toinvestigate the genotypes frequencies of polymorphisms of these genes in distinct ethnic groups. Our results may be helpful to forensic applications and population genetic studies.
Materials and methods
Ethics statement
The study protocol was approved by the Ethics Committee of Northwest University and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all subjects before participation in the study.
Study subjects
A total of 300 volunteers from three distinct ethnic groups in China including 100 Han, 100 Tibetan and 100 Sherpa individuals were recruited for the present study. The participants gave a detailed medical history after carefully interviewed and underwent a physical examination prior to the study. The inclusion criteria were as follows: (1) All individuals had at least three generations of paternal ancestry in their ethnic group without history of intermarried with any other ethnic groups; (2) There was no genetic relationship among all participants; (3) All participants were healthy and had no hereditary disease.
SNPs selection and genotyping
We selected 45 single-nucleotide polymorphisms (SNPs) which located in eight telomere-length associated genes for genotyping. And the minor allele frequencies (MAF) of all of the SNPs were > 5% in the HapMap Han Chinese population. Peripheral blood (5 ml) was collected from each subject in vacutainer tubes containing ethylene diaminetetraacetic acid (EDTA). Genomic DNA was extracted using a GoldMag-Mini Whole Blood Genomic DNA Purification Kit (GoldMag Co. Ltd., Xi’an, China) according to the manufacturer’s protocol. DNA concentration and purity were measured by a NanoDrop 2000 (Thermo Scientific, Waltham, Massachusetts, USA). Polymerase chain reaction (PCR) and extension primers for these SNPs were designed using the Sequenom MassARRAY Assay Design 3.0 software (Sequenom, San Diego, California, USA), presented in Table S1. SNPs genotyping was performed utilizing the Sequenom MassARRAY RS1000 recommended by the manufacturer. Sequenom Typer 4.0 Software was performed to manage and analysis data.
Statistical analysis
Statistical analyses were performed using Microsoft Excel (Redmond, WA, USA) and SPSS 19.0 statistical package (SPSS, Chicago, IL, USA). We calculated and compared the genotype frequencies of the selected 45 variants in Han with Tibetan, Sherpa and the other 11 populations, including African ancestry in the southwestern USA (ASW); a northwestern European population (CEU); the Han Chinese in Beijing, China (CHB); a Chinese population of metropolitan Denver, Colorado, USA (CHD); the Gujarati Indians in Houston, Texas, USA (GIH); the Japanese population in Tokyo, Japan (JPT); the Luhya people in Webuye, Kenya (LWK); people of Mexican ancestry living in Los Angeles, California, USA (MEX); the Maasai people in Kinyawa, Kenya (MKK); the Tuscan people of Italy (TSI) and the Yoruba in Ibadan, Nigeria (YRI) (data were from the second phase of HapMap: http://hapmap.ncbi.nlm.nih.gov) separately, using chi-square test. Meanwhile, we also calculated and compared the genetic heterogeneity between Tibetan and Sherpa using χ2 test. All p values in this study were two-sided, and P ≤ 0.05 after Bonferroni correction was considered to be statistically significant.
We used Haploview software package (version 4.2) to perform the analysis of the linkage disequilibrium (LD), constructed haplotype and genetic association at significant polymorphism loci in Lantian Han, Tibetan and Sherpa. The Pairwise Fst values, Slatkins linearized Fst values and coancestry coefficients among all of the populations were calculated in programArlequin v3.5.1.3 (Institute of Ecology and Evolution, University of Bern, Switzerland) using genotype data. We applied the Structure (version 2.3.4) software to analysis population genetic structure comparisons which works well on small number of loci.
Results
The basic information about the 45 selected SNPs are displayed in Table 1, including the gene name, chromosome number and position, minor allele frequencies and genotypic counts in the Han, Tibetan and Sherpa populations. We used χ2 test to evaluate the polymorphic distribution of the variants between Han, Tibetan and Sherpa populations (Table 1). We found that four polymorphisms (rs11125529, rs12615793, rs11896604 and rs17045754) in ACYP2 and two polymorphisms (rs1056675 and rs11859599) in MPHOSPH6 (P = 0.003, 0.003, 0.004, 0.005, 0.014 and 0.012, respectively) were significantly different between the Han and Tibetan population. Meanwhile, twenty genetic variants in ACYP2 (rs6713088, rs11125529, rs12615793, rs843711, rs11896604, rs843706 and rs17045754), MPHOSPH6 (rs1056654, rs1056629, rs11859599 and rs2967361), OBFC1 (rs9325507, rs3814220, rs12765878 and rs11191865), TERC (rs10936599) and ZNF208 (rs2188972, rs2188971, rs8103163 and rs7248488) showed considerable divergence among Han and Sherpa (P < 0.05). Additionally, we also found that rs1056654 and rs1056629 (MPHOSPH6), rs2320615 (NAF1), rs6010621 (RTEL1), rs8105767 and rs2188972 (ZNF208) (P = 0.020, 0.025, 0.039, 0.040, 0.012 and 0.016, respectively) were significant genetic divergences between the Tibetan and Sherpa population.
Table 1.
Basic characteristic of the selected variants in Han, Tibetan and Sherpa
| SNP-ID | Genes | Chr | Position | Alleles | MAF (%) | Han (count) | Tibetan | Sherpa | P value | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
| |||||||||||||||||||
| A/B | Han | Tibetan | Sherpa | AA | AB | BB | AA | AB | BB | AA | AB | BB | Han vs. Tibetan | Han vs. Sherpa | Tibetan vs. Sherpa | ||||
| rs6713088 | ACYP2 | 2 | 54198973 | C/G | 54.0 | 60.0 | 70.9 | 36 | 42 | 22 | 34 | 52 | 14 | 47 | 45 | 6 | 0.235 | 0.005 | 0.056 |
| rs12621038 | ACYP2 | 2 | 54244617 | C/T | 54.0 | 49.5 | 43.9 | 32 | 44 | 24 | 24 | 51 | 25 | 20 | 47 | 32 | 0.432 | 0.135 | 0.501 |
| rs1682111 | ACYP2 | 2 | 54281483 | A/T | 30.0 | 24.0 | 29.8 | 9 | 42 | 49 | 4 | 40 | 56 | 8 | 43 | 48 | 0.295 | 0.963 | 0.358 |
| rs843752 | ACYP2 | 2 | 54300091 | G/T | 73.5 | 68.5 | 71.2 | 54 | 39 | 7 | 46 | 45 | 9 | 50 | 41 | 8 | 0.517 | 0.876 | 0.816 |
| rs10439478 | ACYP2 | 2 | 54312954 | A/C | 56.5 | 55.7 | 58.2 | 32 | 49 | 19 | 29 | 49 | 18 | 34 | 46 | 18 | 0.955 | 0.922 | 0.79 |
| rs843645 | ACYP2 | 2 | 54328168 | G/T | 74.0 | 68.5 | 71.2 | 54 | 40 | 6 | 46 | 45 | 9 | 50 | 41 | 8 | 0.464 | 0.800 | 0.816 |
| rs11125529 | ACYP2 | 2 | 54329370 | A/C | 75.0 | 85.0 | 91.0 | 54 | 42 | 4 | 75 | 20 | 5 | 82 | 18 | 0 | 0.003 | 0.000 | 0.067 |
| rs12615793 | ACYP2 | 2 | 54329418 | A/G | 75.3 | 85.5 | 91.2 | 54 | 41 | 4 | 76 | 19 | 5 | 80 | 17 | 0 | 0.003 | 0.000 | 0.075 |
| rs843711 | ACYP2 | 2 | 54332621 | C/T | 49.0 | 52.5 | 62.0 | 21 | 56 | 23 | 26 | 53 | 21 | 37 | 50 | 13 | 0.703 | 0.023 | 0.143 |
| rs11896604 | ACYP2 | 2 | 54332703 | C/G | 74.5 | 84.5 | 90.5 | 53 | 43 | 4 | 74 | 21 | 5 | 81 | 19 | 0 | 0.004 | 0.000 | 0.067 |
| rs843706 | ACYP2 | 2 | 54333873 | A/C | 49.5 | 52.5 | 61.5 | 22 | 55 | 23 | 26 | 53 | 21 | 36 | 51 | 13 | 0.794 | 0.043 | 0.171 |
| rs17045754 | ACYP2 | 2 | 54350261 | C/G | 77.0 | 85.5 | 90.5 | 57 | 40 | 3 | 76 | 19 | 5 | 81 | 19 | 0 | 0.005 | 0.001 | 0.076 |
| rs843720 | ACYP2 | 2 | 54364164 | G/T | 62.0 | 67.5 | 71.5 | 38 | 48 | 14 | 46 | 43 | 11 | 52 | 39 | 9 | 0.497 | 0.123 | 0.683 |
| rs1056675 | MPHOSPH6 | 16 | 80739435 | C/T | 55.1 | 69.2 | 63.5 | 33 | 43 | 23 | 47 | 43 | 9 | 40 | 47 | 13 | 0.014 | 0.164 | 0.481 |
| rs1056654 | MPHOSPH6 | 16 | 80739512 | A/G | 69.0 | 68.5 | 81.0 | 50 | 38 | 12 | 51 | 35 | 14 | 66 | 30 | 4 | 0.866 | 0.028 | 0.02 |
| rs1056629 | MPHOSPH6 | 16 | 80739605 | C/T | 69.0 | 68.5 | 80.6 | 50 | 38 | 12 | 51 | 35 | 14 | 64 | 30 | 4 | 0.866 | 0.036 | 0.025 |
| rs3751862 | MPHOSPH6 | 16 | 80739730 | A/C | 95.5 | 95.0 | 95.9 | 92 | 7 | 1 | 90 | 10 | 0 | 89 | 8 | 0 | 0.460 | 0.585 | - |
| rs11859599 | MPHOSPH6 | 16 | 80740333 | C/G | 19.0 | 32.5 | 40.5 | 4 | 30 | 66 | 12 | 41 | 47 | 13 | 55 | 32 | 0.012 | 0.000 | 0.085 |
| rs2967361 | MPHOSPH6 | 16 | 80761004 | G/T | 20.7 | 31.5 | 35.5 | 7 | 27 | 65 | 12 | 39 | 49 | 14 | 43 | 43 | 0.057 | 0.005 | 0.691 |
| rs3792792 | TNIP1 | 5 | 150420699 | C/T | 95.0 | 98.5 | 99.0 | 90 | 10 | 0 | 97 | 3 | 0 | 96 | 2 | 0 | - | - | - |
| rs4958881 | TNIP1 | 5 | 150430429 | C/T | 94.5 | 97.0 | 98.0 | 89 | 11 | 0 | 94 | 6 | 0 | 94 | 4 | 0 | - | - | - |
| rs7708392 | TNIP1 | 5 | 150437678 | C/G | 30.5 | 32.5 | 33.7 | 8 | 45 | 47 | 11 | 43 | 46 | 9 | 48 | 41 | 0.767 | 0.762 | 0.69 |
| rs10036748 | TNIP1 | 5 | 150438339 | C/T | 30.0 | 32.5 | 33.3 | 7 | 46 | 47 | 11 | 43 | 46 | 9 | 48 | 42 | 0.606 | 0.753 | 0.722 |
| rs960709 | TNIP1 | 5 | 150441242 | A/G | 29.9 | 32.0 | 34.2 | 7 | 44 | 46 | 10 | 44 | 46 | 9 | 49 | 40 | 0.785 | 0.627 | 0.698 |
| rs2320615 | NAF1 | 4 | 164289399 | A/G | 22.0 | 18.0 | 27.3 | 6 | 32 | 62 | 1 | 34 | 65 | 7 | 39 | 51 | 0.157 | 0.408 | 0.039 |
| rs9420907 | OBFC1 | 10 | 105666455 | A/C | 0.0 | 2.5 | 3.1 | 0 | 0 | 100 | 1 | 3 | 96 | 0 | 6 | 92 | 0.130 | - | 0.356 |
| rs9325507 | OBFC1 | 10 | 105635612 | C/T | 66.0 | 60.5 | 53.5 | 41 | 50 | 9 | 36 | 49 | 15 | 26 | 54 | 19 | 0.400 | 0.029 | 0.313 |
| rs3814220 | OBFC1 | 10 | 105637290 | A/G | 66.0 | 60.5 | 53.5 | 41 | 50 | 9 | 36 | 49 | 15 | 26 | 55 | 19 | 0.400 | 0.028 | 0.297 |
| rs12765878 | OBFC1 | 10 | 105659612 | C/T | 66.0 | 60.5 | 53.5 | 41 | 50 | 9 | 36 | 49 | 15 | 26 | 55 | 19 | 0.400 | 0.028 | 0.297 |
| rs11191865 | OBFC1 | 10 | 105662832 | A/G | 66.0 | 61.3 | 53.0 | 41 | 50 | 9 | 36 | 47 | 14 | 25 | 55 | 19 | 0.482 | 0.021 | 0.187 |
| rs6089953 | RTEL1 | 20 | 61761452 | A/G | 72.5 | 80.0 | 68.0 | 53 | 39 | 8 | 66 | 28 | 6 | 47 | 42 | 11 | 0.173 | 0.624 | 0.024 |
| rs6010620 | RTEL1 | 20 | 61780283 | A/G | 71.5 | 80.0 | 70.2 | 51 | 41 | 8 | 65 | 30 | 5 | 50 | 39 | 10 | 0.130 | 0.871 | 0.091 |
| rs6010621 | RTEL1 | 20 | 61781316 | G/T | 73.0 | 79.5 | 68.2 | 54 | 38 | 8 | 65 | 29 | 6 | 47 | 41 | 11 | 0.285 | 0.586 | 0.04 |
| rs4809324 | RTEL1 | 20 | 61788664 | C/T | 90.5 | 90.5 | 88.0 | 83 | 15 | 2 | 83 | 15 | 2 | 79 | 18 | 3 | 1.000 | 0.751 | 0.751 |
| rs2297441 | RTEL1 | 20 | 61798026 | A/G | 67.0 | 71.5 | 70.0 | 49 | 36 | 15 | 50 | 43 | 7 | 49 | 42 | 9 | 0.170 | 0.375 | 0.873 |
| rs10936599 | TERC | - | - | - | 47.0 | 40.5 | 35.9 | 28 | 38 | 34 | 17 | 47 | 36 | 11 | 49 | 39 | 0.157 | 0.010 | 0.486 |
| rs10069690 | TERT | 5 | 1332790 | C/T | 89.9 | 82.8 | 88.5 | 80 | 18 | 1 | 70 | 24 | 5 | 80 | 17 | 3 | 0.123 | 0.599 | 0.308 |
| rs2242652 | TERT | 5 | 1333028 | A/G | 88.5 | 81.5 | 88.8 | 77 | 23 | 0 | 68 | 27 | 5 | 78 | 18 | 2 | 0.053 | 0.273 | 0.153 |
| rs2853677 | TERT | 5 | 1340194 | A/G | 34.5 | 33.5 | 33.8 | 8 | 53 | 39 | 12 | 43 | 45 | 12 | 43 | 44 | 0.321 | 0.343 | 0.997 |
| rs2853676 | TERT | 5 | 1341547 | C/T | 14.0 | 23.0 | 15.5 | 2 | 24 | 74 | 8 | 30 | 62 | 1 | 29 | 70 | 0.070 | 0.633 | 0.051 |
| rs8105767 | ZNF208 | - | - | - | 71.2 | 75.0 | 61.5 | 50 | 41 | 8 | 55 | 40 | 5 | 36 | 51 | 13 | 0.626 | 0.103 | 0.012 |
| rs2188972 | ZNF208 | 19 | 21941298 | A/G | 47.0 | 57.5 | 70.5 | 21 | 52 | 27 | 32 | 51 | 17 | 52 | 37 | 11 | 0.102 | 0.000 | 0.016 |
| rs2188971 | ZNF208 | 19 | 21944022 | C/T | 29.5 | 38.0 | 41.3 | 9 | 41 | 50 | 16 | 44 | 40 | 23 | 35 | 40 | 0.204 | 0.021 | 0.323 |
| rs8103163 | ZNF208 | 19 | 21966592 | A/C | 29.5 | 38.0 | 40.5 | 9 | 41 | 50 | 16 | 44 | 40 | 23 | 35 | 42 | 0.204 | 0.026 | 0.312 |
| rs7248488 | ZNF208 | 19 | 21980549 | A/C | 29.5 | 38.0 | 40.5 | 9 | 41 | 50 | 16 | 44 | 40 | 23 | 35 | 42 | 0.204 | 0.026 | 0.312 |
SNP: Single nucleotide polymorphism; Chr: Chromosome; vs.: versus. P < 0.05 indicates statistical significance.
Furthermore, we also used chi-square test to compare the genotypic frequencies of the tested variants between Han and other 11 HapMap populations (Table 2). There were 20, 20, 3, 16, 9, 21, 16, 27, 23 and 29 variants that differed in frequency in the Han population compared to the ASW, CEU, CHB, GIH, JPT, LWK, MEX, MKK, TSI and YRI populations, respectively. However, we didn’t find any polymorphism in Han different from CHD. The rs10936599 (TERC) and rs12615793 (ACYP2) showed the greatest number of significant differences between Han and the other 11 populations, while the rs2320615 (NAF1) has no significant genetic differences between Han and the 11 HapMap populations. The genotype counts of 45 loci in 11 HapMap populations listed in Table S2.
Table 2.
Han compared with 11 HapMap populations after Bonferroni’s multiple adjustments
| SNP-ID | ASW | CEU | CHB | CHD | GIH | JPT | LWK | MEX | MKK | TSI | YRI |
|---|---|---|---|---|---|---|---|---|---|---|---|
| rs6713088 | - | - | 0.532 | - | - | 0.083 | - | - | - | - | 0.549 |
| rs12621038 | 0.000 | 0.000 | 0.943 | 0.722 | 0.000 | 0.066 | 0.000 | 0.001 | 0.000 | 0.000 | 0.000 |
| rs1682111 | - | - | 0.858 | - | - | 0.052 | - | - | - | - | 0.012 |
| rs843752 | - | - | 0.707 | - | - | 0.893 | - | - | - | - | 0.000 |
| rs10439478 | - | - | 0.915 | - | - | 0.072 | - | - | - | - | 0.000 |
| rs843645 | 0.779 | 0.779 | 0.333 | 0.821 | 0.000 | 0.348 | 0.001 | 0.091 | 0.000 | 0.169 | 0.001 |
| rs11125529 | 0.018 | 0.018 | 0.517 | 0.054 | 0.000 | 0.016 | 0.214 | 0.006 | 0.001 | 0.001 | 0.106 |
| rs12615793 | 0.000 | 0.000 | 0.631 | 0.366 | 0.000 | 0.023 | 0.047 | 0.009 | 0.000 | 0.001 | 0.001 |
| rs843711 | 0.029 | 0.029 | 0.092 | 0.201 | 0.067 | 0.035 | 0.039 | 0.000 | 0.002 | 0.006 | 0.001 |
| rs11896604 | 0.016 | 0.016 | 0.461 | 0.162 | 0.711 | 0.021 | 0.219 | 0.004 | 0.003 | 0.000 | 0.178 |
| rs843706 | 0.365 | 0.365 | 0.128 | 0.320 | 0.066 | 0.049 | 0.083 | 0.000 | 0.006 | 0.004 | 0.050 |
| rs17045754 | - | - | 0.294 | - | - | 0.182 | - | - | - | - | 0.574 |
| rs843720 | 0.001 | 0.001 | 0.704 | 0.299 | 0.392 | 0.431 | 0.000 | 0.001 | 0.000 | 0.013 | 0.000 |
| rs1056675 | - | - | 0.341 | - | - | 0.570 | - | - | - | - | 0.000 |
| rs1056654 | 0.000 | 0.000 | 0.974 | 0.082 | 0.405 | 0.594 | 0.000 | 0.743 | 0.000 | 0.001 | 0.000 |
| rs1056629 | 0.000 | 0.000 | 0.878 | 0.085 | 0.405 | 0.851 | 0.000 | 0.829 | 0.000 | 0.000 | 0.000 |
| rs3751862 | 0.000 | 0.000 | 0.935 | 0.457 | 0.214 | 0.003 | 0.000 | 0.761 | 0.000 | 0.199 | 0.000 |
| rs11859599 | - | - | 0.182 | - | - | 0.380 | - | - | - | - | 0.059 |
| rs2967361 | 0.000 | 0.000 | 0.674 | 0.447 | 0.002 | 0.113 | 0.000 | 0.252 | 0.000 | 0.034 | 0.000 |
| rs3792792 | - | - | - | - | - | - | - | - | - | - | - |
| rs4958881 | 0.000 | 0.000 | - | - | - | - | 0.000 | - | 0.000 | 0.074 | 0.000 |
| rs7708392 | - | - | 0.518 | - | - | 0.351 | - | - | - | - | - |
| rs10036748 | 0.131 | 0.131 | 0.577 | 0.878 | 0.000 | 0.842 | 0.007 | 0.001 | 0.180 | 0.000 | 0.000 |
| rs960709 | 0.236 | 0.236 | 0.614 | 0.872 | 0.000 | 0.878 | 0.013 | 0.000 | 0.091 | 0.000 | 0.000 |
| rs2320615 | 0.243 | 0.243 | 0.869 | 0.852 | 0.303 | 0.234 | 0.385 | 0.299 | 0.717 | 0.057 | 0.149 |
| rs9420907 | 0.000 | 0.000 | - | - | - | - | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| rs9325507 | 0.688 | 0.688 | 0.514 | 0.505 | 0.294 | 0.582 | 0.944 | 0.341 | 0.013 | 0.000 | 0.128 |
| rs3814220 | - | - | 0.383 | - | - | 0.964 | - | - | - | - | 0.028 |
| rs12765878 | 0.843 | 0.843 | 0.514 | 0.519 | 0.341 | 0.582 | 0.953 | 0.482 | 0.016 | 0.000 | 0.142 |
| rs11191865 | 0.531 | 0.531 | 0.564 | 0.447 | 0.419 | 0.545 | 0.969 | 0.337 | 0.013 | 0.000 | 0.142 |
| rs6089953 | 0.000 | 0.000 | 0.818 | 0.998 | 0.000 | 0.843 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| rs6010620 | 0.000 | 0.000 | 0.758 | 0.626 | 0.000 | 0.816 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| rs6010621 | - | - | 0.278 | - | - | 0.352 | - | - | - | - | 0.000 |
| rs4809324 | 0.126 | 0.126 | 0.473 | 0.875 | 0.672 | 0.133 | 0.001 | 0.000 | 0.041 | 0.409 | 0.003 |
| rs2297441 | 0.000 | 0.000 | 0.263 | 0.055 | 0.000 | 0.296 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| rs10936599 | 0.000 | 0.000 | 0.017 | 0.341 | 0.000 | 0.003 | 0.000 | 0.001 | 0.000 | 0.000 | 0.000 |
| rs10069690 | 0.000 | 0.000 | 0.016 | 0.190 | 0.000 | 0.011 | 0.000 | 0.024 | 0.000 | 0.003 | 0.000 |
| rs2242652 | - | - | - | - | - | 0.030 | - | - | - | - | - |
| rs2853677 | 0.251 | 0.251 | 0.520 | 0.153 | 0.000 | 0.098 | 0.648 | 0.414 | 0.008 | 0.103 | 0.008 |
| rs2853676 | 0.109 | 0.109 | 0.970 | 0.868 | 0.000 | 0.385 | 0.070 | 0.284 | 0.000 | 0.001 | 0.211 |
| rs8105767 | 0.000 | 0.000 | 0.532 | 0.639 | 0.052 | 0.710 | 0.000 | 0.954 | 0.003 | 0.568 | 0.000 |
| rs2188972 | 0.000 | 0.000 | 0.248 | 0.767 | 0.000 | 0.213 | 0.000 | 0.131 | 0.000 | 0.145 | 0.000 |
| rs2188971 | 0.005 | 0.005 | 0.298 | 0.809 | 0.000 | 0.419 | 0.967 | 0.423 | 0.604 | 0.007 | 0.684 |
| rs8103163 | - | - | 0.033 | - | - | 0.097 | - | - | - | - | 0.073 |
| rs7248488 | - | - | 0.153 | - | - | 0.318 | - | - | - | - | 0.178 |
ASW: African ancestry in the southwestern USA; CEU: a northwestern European population; CHB: the Han Chinese in Beijing, China; CHD: a Chinese population of metropolitan Denver, Colorado, USA; GIH: the Gujarati Indians in Houston, Texas, USA; JPT: the Japanese population in Tokyo, Japan; LWK: the Luhya people in Webuye, Kenya; MEX: people of Mexican ancestry living in Los Angeles, California, USA; MKK: the Maasai people in Kinyawa, Kenya; TSI: the Tuscan people of Italy; YRI: the Yoruba in Ibadan, Nigeria. P < 0.05 indicates statistical significance.
We found two LD blocks for ACYP2 in the Han, Tibetan and Sherpa populations, while the block 1 (rs843752, rs10439478 and rs843645) in the Han and Tibetan was different from the block 1 in the Sherpa population which included four loci (rs168211, rs843752, rs10439478 and rs843645). In addition, each pair of variants in the second block in the Han population had a stronger linkage than the Tibetan and Sherpa. We also found one LD block for MPHOSPH6 in the three populations, rs3751862 and rs11859599 was complete recombination in the Han and was not linkage in the Sherpa population, whereas the pair of loci was partial linkage in the Tibetan (Figure 1).
Figure 1.
Linkage disequilibrium analysis of the ACYP2/MPHOSPH6 in the Liantian Han, Tibetan and Sherpa. LD is displayed by standard color schemes with bright red for very strong LD (LOD > 2, D’ = 1), pink red (LOD > 2, D’ < 1) and blue (LOD < 2, D’ = 1) for partial linkage, and white (LOD < 2, D’ < 1) for complete recombination. A: LD blocks of ACYP2 in Liantian Han. B: LD blocks of ACYP2 in Tibetan. C: LD blocks of ACYP2 in Sherpa. D: LD blocks of MPHOSPH6 in Liantian Han. E: LD blocks of MPHOSPH6 in Tibetan. F: LD blocks of MPHOSPH6 in Sherpa.
We estimated the magnitude of differentiation among geographic populations using pairwise FST values, which less than 0.15 indicating no significant genetic divergences between the two populations. And pairwise FST values between the Han population and Tibetan, Sherpa and the other 11 HapMap populations ranged from 0.001 to 0.277 (Table 3). Comparing other populations, the lowest level of differentiation was observed between the Han and CHD populations (FST = 0.001), followed by the CHB (FST = 0.002), whereas the greatest divergence was found in the YRI population (FST = 0.277). This finding was also supported by Slatkin linearized FST and co-ancestry coefficients (Tables S3 and S4).
Table 3.
Distribution of pairwise Fst distances among the among the 14 populations
| Han | Tibetan | Sherpa | ASW | CEU | CHB | CHD | GIH | JPT | LWK | MEX | MKK | TSI | YRI | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Han | 0.000 | |||||||||||||
| Tibetan | 0.005 | 0.000 | ||||||||||||
| Sherpa | 0.024 | 0.009 | 0.000 | |||||||||||
| ASW | 0.189 | 0.198 | 0.185 | 0.000 | ||||||||||
| CEU | 0.113 | 0.124 | 0.113 | 0.099 | 0.000 | |||||||||
| CHB | 0.002 | 0.008 | 0.029 | 0.192 | 0.123 | 0.000 | ||||||||
| CHD | 0.001 | 0.000 | 0.012 | 0.186 | 0.113 | 0.001 | 0.000 | |||||||
| GIH | 0.148 | 0.151 | 0.145 | 0.086 | 0.040 | 0.159 | 0.146 | 0.000 | ||||||
| JPT | 0.007 | 0.005 | 0.017 | 0.158 | 0.111 | 0.006 | 0.002 | 0.144 | 0.000 | |||||
| LWK | 0.243 | 0.258 | 0.245 | 0.013 | 0.158 | 0.245 | 0.243 | 0.151 | 0.211 | 0.000 | ||||
| MEX | 0.099 | 0.111 | 0.101 | 0.086 | 0.031 | 0.102 | 0.094 | 0.071 | 0.076 | 0.129 | 0.000 | |||
| MKK | 0.209 | 0.221 | 0.209 | 0.015 | 0.100 | 0.207 | 0.209 | 0.093 | 0.175 | 0.028 | 0.081 | 0.000 | ||
| TSI | 0.140 | 0.147 | 0.129 | 0.099 | 0.004 | 0.149 | 0.136 | 0.050 | 0.129 | 0.155 | 0.025 | 0.100 | 0.000 | |
| YRI | 0.277 | 0.293 | 0.279 | 0.025 | 0.198 | 0.277 | 0.279 | 0.192 | 0.241 | 0.009 | 0.163 | 0.036 | 0.199 | 0.000 |
ASW: African ancestry in the southwestern USA; CEU: a northwestern European population; CHB: the Han Chinese in Beijing, China; CHD: a Chinese population of metropolitan Denver, Colorado, USA; GIH: the Gujarati Indians in Houston, Texas, USA; JPT: the Japanese population in Tokyo, Japan; LWK: the Luhya people in Webuye, Kenya; MEX: people of Mexican ancestry living in Los Angeles, California, USA; MKK: the Maasai people in Kinyawa, Kenya; TSI: the Tuscan people of Italy; YRI: the Yoruba in Ibadan, Nigeria.
We used Bayesian-based Structure 2.3.4 that provided complementary methods for visualizing patterns of genetic similarity and differentiation to analyze genetic structure difference between Han population and the other 13 populations in the current study. The results of cluster analysis indicated that the 45 selected variants could distinguish the 14 populations genetic structure when K = 2 or 3. From Figure 2, the bar graph revealed that the genetic structure of Han population was near to cluster of CHB and CHD populations.
Figure 2.
Comparison of genetic structure among 14 populations assessed by structure based on 45 telomere length related SNPs. K = 2 and K = 3. K is the number of parental populations. Each individual is represented by a vertical column partitioned into different color segments.
Discussion
In this study, we evaluated the polymorphic distribution of 45 variants in telomere-length related genes in different populations. We found that the genotype frequencies of variants exhibited great variation among different populations and there were 6, 20, 20, 20, 3, 0, 16, 9, 21, 16, 27, 23 and 29 variants that differed in frequency Han compared to the other populations. Comprehensive analysis of all the results indicated that Han population exhibited closely genetic affinity with the CHD and CHB but differ significantly from those in the YRI and MKK. We found some significantly different polymorphisms among the 14 populations, rs10936599 (TERC), rs10069690, rs2853676 (TERT) and rs6010620, rs4809324 (RTEL1), as well as some others. These results suggested that genotype data from one group or subgroup should not be overly generalized and applied to genetically distinct groups.
TERC is located on chromosome 3q26.2 that is an essential element of telomerase, serving as a template for telomere elongation [19]. Even moderate changes in TERC activity could profoundly affect telomere homeostasis [11]. The SNP (rs10936599) is one of the variants of the TERC. According to the analysis of data from 37669 European ancestry participants showed that the allele “T” of rs10936599 were associated with the mean leukocyte telomere length. One study found that the effect of the T allele of this SNP to be equivalent to 3.91 years of age-related telomere attrition [11]. Our results showed that rs10936599 was significantly different in the three groups, may cause the average life is different. In addition, the SNP is significantly associated with colorectal cancer [20], high-grade glioma [21] and coronary heart disease risk [22]. Further studies to determine the mechanism of rs10936599 should be considered.
Recent study revealed that rs10069690 located in intron 4 of the TERT, which encodes the catalytic subunit of telomerase reverse transcriptase, a complex with an integral role in telomere maintenance [23], at chromosome 5p15 was not significantly correlated with breast cancer in the Chinese Henan Han women [24]. The findings were inconsistent with other studies in European and African-American populations [25,26]. Interestingly, previous research has shown that rs2853676 genotype “AG” was associated with an increased risk ofglioma in Xi’an [27] that was not inconsistent with Shanghai [28] and United States participants [29]. The RTEL1 locates in 20q13.3, including 40 exons. It is an essential DNA helicase thathas been shown to have critical roles in setting telomere length, maintaining telomere integrity and disassembling a variety of DNA secondary structures to facilitate 3R (replication, repair, and recombination) processes in mice. Its loss is associated with shortened telomere length, chromosome breaks and translocations [30-32]. Previous report showed that rs6010620 (RTEL1) was significantly correlated with the risk of glioma in the German cohort and Han Chinese population, but the French population [28,33,34]. Furthermore, rs4809324 (RTEL1) was significantly associated with the risk of high grade glioma in the American, while itwas not correlated with the risk of glioma in Han Chinese [28,34]. These phenomena also showed that the variationmay be lead to the occurrence of diseases are different in distinct groups.
It should be mentioned that this is the first study to explore the polymorphic distribution of variants in the telomere-length related genes in the three China distinct ethnic groups and the other 11 HapMap populations to our knowledge. However, the sample size of the Han, Tibetan and Sherpa population in our study was relative small, and further investigation with larger cohort is necessary to determine the generalizability of our results and focus on determining the biological functions of these SNPs.
The present study is the first to present genetic polymorphisms in the telomere-length related genes of the Han people compare with the distinct ethnic groups (Tibetan, Sherpa and other 11HapMap populations). We also compared these polymorphisms in the Tibetan with the Sherpa population. Results indicated that the Han people are most similar to CHD and six polymorphisms in the Tibetan differ from the Sherpa. The results also confirmed that there are important interethnic differences in the distribution of telomere-length related genes variants, which may be related to different efficacy on the telomere length related genes.
Acknowledgements
We are grateful to the all individuals for their participation in the study. We also thank the clinicians and hospital staff who contributed to sample and data collection for this study.
Disclosure of conflict of interest
None.
Supporting Information
References
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