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Article

Distribution of Killer-Cell Immunoglobulin-Like Receptor Genes and Combinations of Their Human Leucocyte Antigen Ligands in 11 Ethnic Populations in China

by
Yufeng Yao
,
Lei Shi
,
Jiankun Yu
,
Shuyuan Liu
,
Yufen Tao
and
Li Shi
*
Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming 650118, China
*
Author to whom correspondence should be addressed.
Cells 2019, 8(7), 711; https://doi.org/10.3390/cells8070711
Submission received: 31 May 2019 / Revised: 8 July 2019 / Accepted: 9 July 2019 / Published: 12 July 2019
(This article belongs to the Special Issue Major Histocompatibility Complex (MHC) in Health and Disease)
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Abstract

:
The aim of this study was to analyze the distribution of killer-cell immunoglobulin-like receptor (KIR) genes and their human leucocyte antigen (HLA) ligand combinations in different original ethnic populations in China, and thus, to provide relevant genomic diversity data for the future study of viral infections, autoimmune diseases, and reproductive fitness. A total of 1119 unrelated individuals from 11 ethnic populations—including Hani, Jinuo, Lisu, Nu, Bulang, Wa, Dai, Maonan, Zhuang, Tu, and Yugu—from four original groups, were included. The presence/absence of the 16 KIR loci were detected, and the KIR gene’s phenotype, genotype, and haplotype A and B frequencies, as well as KIR ligand’s HLA allotype and KIR–HLA pairs for each population, were calculated. Principal component analysis and phylogenetic trees were constructed to compare the characteristics of the KIR and KIR–HLA pair distributions of these 11 populations. In total, 92 KIR genotypes were identified, including six new genotypes. The KIR and its HLA ligands had a distributed diversity in 11 ethnic populations in China, and each group had its specific KIR and KIR–HLA pair profile. The difference among the KIR–HLA pairs between northern and southern groups, but not among the four original groups, may reflect strong pressure from previous or ongoing infectious diseases, which have a significant impact on KIR and its HLA combination repertoires.

1. Introduction

Segregated in different chromosomes, 6p21 and 19q13.4, human leucocyte antigen (HLA) and killer-cell immunoglobulin-like receptor (KIR) genes, respectively, exhibit diverse polymorphisms and their molecular expressions interact with each other as receptor ligands to ensure the proper role of nature killer (NK) cells in modulating an immune response [1,2]. Several studies on the coinheritance of these two genetic systems have indicated that carrying the appropriate KIR–HLA combination is important for human survival [3,4]. During human migration outward from Africa and the successive colonization worldwide, the cooperative KIR haplotypes and activating KIR–HLA pairs are important for humans to adapt to quickly changing environments and to increase population reproduction [5,6].
HLA polymorphism has been well studied in worldwide populations, which makes it a genetic marker for tracing a population’s origin, migration, and admixture [7,8]. Compared to HLA, KIR genes show polymorphisms, both at content and allelic levels. Among 16 identified KIR genes, 2DL1, 2DL2, 2DL3, 2DL5, 3DL1, 3DL2, and 3DL3 belong to inhibitory KIR genes, while 2DS1, 2DS2, 2DS3, 2DS4, KIR2DS5, and 3DS1 belong to activating KIR genes, and KIR2DL4 has both inhibitory and activating capacities [9]. Four framework KIR genes—3DL3, 3DP1, 2DL4, and 3DL2—which are located from the centromeric to the telomeric region, respectively, are observed consistently in almost all individuals [10]. On the basis of gene content, KIRs are divided into two haplotype groups: A and B. The A haplotype has a fixed gene content (3DL3-2DL3-2DL1-3DP1-2DL4-3DL1-2DS4-3DL2) and an activating 2DS4. Four inhibitory KIRs (2DL1, 2DL3, 3DL1, and 3DL2) are specific for four major HLA class I ligands (C2, C1, Bw4, and A3/A11, respectively) [11]. In contrast, haplotype B is variable both in the numbers and combinations of KIR genes and comprises several genes (2DL2, 2DL5, 2DS1, 2DS2, 2DS3, 2DS5, and 3DS1) that do not exist in the A haplotype. Among them, 2DS1 binds to HLA-C2 but with a low affinity; 3DS1 may bind to the HLA-Bw4 allotype, especially for Bw4-80T; and 2DS2 may bind to HLA-A11 [12,13,14]. KIR genes, genotypes, haplotypes, and KIR–HLA pairs show a diverse distribution in different populations worldwide. Examination of KIR and ethnic populations may permit analysis of the evolutionary basis for KIR variation, allowing insight into the role of these receptors in health and disease.
The 55 officially recognized ethnic populations of China, which contribute to about 8% of the overall Chinese population, provide abundant genetic resources for KIR–HLA studies. The ethnic groups living in the south and southwest of China can be traced back to three major ancient groups: Di-Qiang, Bai-Pu, and Bai-Yue [15]. According to historical records, the ancient Di-Qiang tribe migrated from northern to southern China before the Qin dynasty in 206 BC and formed several ethnic populations who spoke the language of Tibeto-Burman, which belongs to the Sino-Tibetan linguistic family [15,16]. The ancient Baipu tribe settled down in the south and southwest of Yunnan Province in China and developed into the major Mon-Khmer speaking populations of the Austo-Asiatic linguistic family. Most of the Mon-Khmer ancient tribes migrated to the Indochina Peninsula by the end of 2000 BC, whereas others remained in the Yunnan Province [15,16]. The ancient Baiyue tribe, which was widely distributed along the southeast coast of China, migrated to Yunnan Province and the northern part of Southeast Asia 2000–3000 years ago and then later on migrated to Northern Thailand and contributed to the ancestral gene pool of the Thais [15]. They formed ethnic populations who spoke a language of Daic, part of the Sino-Tibetan linguistic family [17]. There are several ethnic populations in northwestern China, such as the Tu and Yugu. It has been suggested that the Tu population originated from an ancient Xian-Bei tribe, who constructed the Kingdom of Tuguhun in 400 AD, and most of them live in Qinhai and Gansu Provinces. The Yugu originated from Hui-Hu in 600 AD and live only in Gansu Province now. Both the Tu and Yugu integrated with Mongolian and Han populations during the following centuries; moreover, both speak a language of Mongolian belonging to the Altaic linguistic family [15,17].
In the present study, 11 ethnic populations—Hani, Jinuo, Lisu, and Nu, speaking Tibeto-Burman; Bulang and Wa, speaking Mon-Khmer; Dai, Maonan, and Zhuang, speaking Daic; and Tu and Yugu, speaking Mongolian—were selected for HLA and KIR genotyping. The KIR gene’s distribution in Bulang, Nu, Yugu, and Zhuang has been reported previously [18]. The presence/absence of the 16 KIR loci were detected and the KIR gene’s phenotype, genotype, and A and B haplotype frequencies, as well as the KIR ligand’s HLA allotype and KIR–HLA pairs, are reported. Principal component analysis (PCA) and phylogenetic trees were constructed to compare the characteristics of the KIR and KIR–HLA pair distributions in the 11 populations.

2. Material and Methods

2.1. Subject and Samples

A total of 1119 unrelated individuals were recruited from 11 Chinese ethnic populations in China. The geographic location, sample size of each population, the language family to which they belong, and the original ancient groups they are from are listed in Figure 1 and Supplementary Table S1. These populations are descended from four ancient Chinese groups and belong to four different language subfamilies as mentioned in the introduction. The geographic origin, nationalities, and pedigree (unrelated through at least three generations) of each individual were ascertained before sampling. The present study has been approved by the Committee on the Ethics of Institute of Medical Biology, Chinese Academy of Medical Sciences, the batch number is YIKESHENGLUNZI [2012]12. All the individuals are healthy and gave written informed consent in accordance with the Declaration of Helsinki.
Genomic DNA was extracted from peripheral lymphocytes using a QIAamp Blood Kit (Qiagen, Hilden, Germany), in accordance with the manufacturer’s protocol. DNA samples were quantified with a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, WI, USA) and adjusted to a concentration of 20 ng/μL.

2.2. KIR Genotyping

The 16 KIR genes were genotyped using the Luminex MultiAnalyte Profiling System (xMAP) with a One Lambda KIR typing kit (One Lambda, Canoga Park, CA, USA), as previously reported [18]. Briefly, three separate PCR products were amplified: exon 3, exon 5, and exons 7–9. The PCR products were run on 2% agarose gel to confirm the specificity and efficiency of the reactions. Then, the PCR amplicons were denatured and hybridized with complementary 81-nucleotide oligonucleotide probes that had been immobilized on fluorescent-coated microsphere beads. At the same time, the biotinylated PCR products were labeled with phycoerythrin-conjugated streptavidin and immediately examined with the Luminex 200 system (Luminex, Austin, TX, USA). Genotype determination and data analysis were performed automatically using the LABScan 100 platform (One Lambda, Canoga Park, CA, USA) in accordance with the manufacturer’s instructions.

2.3. Statistical Analysis

Hardy–Weinberg’s equilibrium for each of the alleles was assessed using the Guo and Thompson method [19]. For KIR genes, the observed frequency for each KIR gene was determined via direct counting and corresponded to the ratio of the number within the population that carried the gene to the total population number. KIR locus gene frequencies (KLFs) were estimated by using the formula KLF = 1 − 1 − f , where f is the observed frequency of a particular KIR sequence in a population. The genotypes were defined by referring to the Allele Frequencies website (http://www.allelefrequencies.net). Each genotype was named in accordance with the genotype number. The genotypes that could not be found in the database were named as unknown. Group A and B haplotypes and frequencies were predicted on the basis of a previous study [20].
HLA genotyping of 11 ethnic populations has been reported previously [21,22,23,24,25], and the allelic frequencies are summarized in Supplementary Table S2. The frequencies of HLA-C1/C2 allotype, HLA-Bw4 (Bw4-80I and Bw4-80T)/Bw6 allotype, and HLA-A11, -A3 were calculated using direct counting. The HLA-C1 and HLA-C2, HLA-A11 and HLA-A3, and HLA-Bw4/Bw6 groups were used to analyze KIR–HLA combinations. The observed frequencies of KIR–HLA matched pairs were calculated using direct counting. The significance of the correlations of KIR and HLA frequencies among populations were estimated using the correlation coefficient (r) and the t-test was used to establish whether the correlation coefficient was significant using SPSS 16.0 [26]. The chord distance of Nei (Da distances among the populations were calculated based on 11 KIR gene (2DL1, 2DL2, 2DL3, 3DL1, 2DS1, 2DS2, 2DS3, 2DS4, 2DS5, 3DS1, and 2DL5) frequencies; HLA-A, HLA-B, and HLA-C allele frequencies; or HLA–KIR combinations. A neighbor-joining (NJ) tree was constructed using Mega 7.0 software based on the DA distance [27]. Principal component analysis (PCA) was also performed based either on KIR genes, HLA alleles, or KIR–HLA combination frequencies using SPSS 16.0 software [26]. Significant differences in KIR and KIR–HLA pair frequencies between two populations were determined using a contingency test. The difference between the northern and southern groups were detected using a t-test with SPSS 16.0 software [26]. A value of p < 0.05 was considered to be statistically significant. The observed 11 KIR gene (2DL1, 2DL2, 2DL3, 3DL1, 2DS1, 2DS2, 2DS3, 2DS4, 2DS5, 3DS1, and 2DL5) frequencies of 47 other populations were from previous studies and the DA distance among 58 populations were calculated (Supplementary Tables S5 and S6). The phylogenetic tree was constructed based on the DA distance using the minimum evolution method from Mega 7.0 software [28].

3. Results

3.1. KIR Gene, Genotype, and Haplotype Frequencies

The observed KIR frequencies and the estimated gene frequencies for each locus in the 11 populations are listed in Table 1. The four framework loci (KIR3DL3, 3DP1, 2DL4, and 3DL2) were exhibited in all individuals in 10 populations, except one individual in Yugu, for whom 2DL4 and 3DP1 were not observed. The non-framework pseudogene 2DP1 was observed in all individuals in Hani, Nu, Dai, Zhuang, and Tu, but not in all other populations, with frequencies of 94.8%–99.1%. The frequencies of 3DL1, 2DL1, and 2DS4 were about 90%–100% in 11 populations, with the exception in Jinuo and Bulang, which showed frequencies of 88% and 81% at 3DL1 and 88% and 79% at 2DS4, respectively. Other activating KIRs, including 3DS1, 2DS1, 2DS3, and 2DS5, as well as inhibitory KIRs, including 2DL2 and 2DL5, exhibited diverse distributions in different populations. Bulang was different compared with the other 10 populations at 3DS1 and 2DS1 (p < 0.05), 9 other populations except Zhuang at 2DS3, and 9 other populations except Jinuo at 2DS4. The following difference was among Nu and others. For all populations, the most diverse was at 2DS3 (Supplementary Table S3).
In total, 92 KIR genotypes were identified, including 6 new genotypes: 3 in Tu, 2 in Jinuo, and 1 in Wa (Table 2). Genotypes 1, 2, 4, and 8 were observed in all the populations but showed diverse frequencies. Genotype 1 was predominant in all populations except in Bulang. On the contrary, the predominant genotypes in Bulang were genotype 8 followed by genotypes 1, 2, and 75, as previously reported [18]. Originating from the same Baipu ancient group, Wa did not show a distribution similar to Bulang, with genotype 1 being the most predominant, followed by genotypes 2 and 4. The frequencies of genotype 1 were as high as 0.679 in Nu, 0.510 in Hani, 0.469 in Yugu, 0.465 in Lisu, 0.432 in Zhuang, and 0.425 in Wa.
The frequencies of the group A and B haplotypes in the 11 populations were deduced from the genotype data (Figure 2). As with most populations worldwide, the A haplotype was predominant. The frequencies of the A haplotype were around 0.657–0.830 in Nu, Hani, Wa, Lisu, Zhuang, Maonan, and Yugu, while they were around 0.576–0.593 in Tu, Jinuo, and Dai. In Bulang, the frequencies of the A and B haplotypes were almost equal (0.491 vs. 0.509). Haplotype differences were identified among Nu and 10 other populations except Jinuo; among Bulang and Hai, Lisu, Nu, Wa, Maonan, Zhuang, and Yugu; and between Hani and Jinuo, and Dai and Tu (Supplementary Table S3). The distributions of KIR genes, genotypes, and haplotypes did not show any consistency among their original ancient group or linguistic subfamily.

3.2. HLA Allotype Frequencies

The frequencies of HLA-A11/A3, HLA-Bw4 (Bw4-80I and Bw4-80T), and HLA-C1 and HLA-C2 were calculated from the HLA-A, HLA-B, and HLA-C allele genotyping results (Table 3). HLA-A11/A3 were predominant in all the populations living in southern China, with frequencies higher than 0.556, and they accounted for around 80% of HLA-A alleles in Bulang, Wa, and Hani. On the contrary, HLA-A11/A3 were around 40% in Tu and Yugu living in northern China. HLA-Bw4 existed commonly in Tu and Yugu, with frequencies of 0.700 and 0.688, but only with frequencies of 0.283 in Bulang. HLA-C1 was observed in all individuals in Jinuo, Lisu, Maonan, and Zhuang, with frequencies around >95% in other southern Chinese populations, but with frequencies of 0.914 and 0.833 in Tu and Yugu, respectively, from northern China. On the contrary, the frequencies of HLA-C2 were around 50% in Tu and Yugu but was only 0.073 in Maonan. This HLA characteristic reflected the northern and southern Chinese original difference, which has been confirmed in previous studies. Therefore, we divided the present study populations into two groups: the southern group, which included Hani, Jinuo, Lisu, Nu, Bulang, Wa, Dai, Maonan, and Zhuang, and the northern group, which included Tu and Yugu. Differences between the northern and southern groups were observed (data not shown).

3.3. KIR–HLA Combination

The frequencies of KIR3DL2 and HLA-A11/A3 were calculated first. Since the interaction of KIR2DS4 and KIR2DS2 with HLA-A11 has been demonstrated, their combinations have also been calculated [14,29]. The frequencies of KIR3DL2+A11/A3 and KIR2DS4+A11/A3 were from 0.417 to 0.879, while the frequencies of KIR2DS2+A11 were lower, with frequencies from 0.038 to 0.299 (Table 4). In Nu, the frequency of KIR2DS2+A11 was only 0.038, though HLA-A*11:01 was predominant, with a frequency of 0.411(Table 4).
The individuals carrying either KIR3DL1 or KIR3DS1 and its HLA-Bw4 ligands, or carrying both KIR3DL1 and KIR3DS1 together with its HLA-Bw4 ligands, were counted for the KIR–HLA combination (Table 5). KIR3DL1/3DS1+Bw4 was commonly exhibited in all populations, with frequencies of 0.383–0.700, except in Bulang. The total frequency of the KIR3DL1/3DS1+Bw4 combination was 0.283, and the frequency of either KIR3DL1+Bw4 or KIR3DS1+Bw4 pairs was 0.057. The frequencies of 3DL1+3DS1+Bw4 were predominant in Bulang, and 3DL1+3DS1+Bw4 and 3DL1+Bw4 were almost similar in Jinuo; however, KIR3DL1+Bw4 was predominant in other 9 populations. In Hani and Wa, all individuals carried either 3DL1+Bw4 or 3DL1+3DS1+Bw4 together, and no one carrying only 3DS1+Bw4 was observed.
Further analysis of KIR with the presence of isoleucine at position 80(Bw4-80I) as well as with the presence of threonine at position 80(Bw4-80T) was performed. One individual in Dai and Jinuo with HLA-Bw4 were unable to have their KIR ligands identified, two individuals in Lisu were not able to have their KIR ligands identified, while all the other individuals with KIR-Bw4 ligands were identified. For the 3DL1/3DS1+Bw4 pair, the frequencies of 80I3DL1+Bw4 80I were higher than 3DS1+Bw4 80I. Moreover, in Hani, Nu, Wa, and Maonan, no individuals who only carried 3DS1+Bw4 80I were observed. There were more individuals only carrying KIR3DL1+Bw4-80I than those only carrying KIR3DL1+Bw4-80T in Hani, Lisu, Bulang, and Yugu, while there were fewer in Jinuo, Dai, and Maonan, and there was no difference in Nu, Wa, Zhuang, and Tu. There was a similar finding for the KIR3DL1+Bw4-80T and KIR3DS1+Bw4-80T pairs. Further analysis of the southern and northern groups indicated that the frequencies of KIR3DL1+Bw4 were lower in the southern group than in the northern group (0.451 ± 0.120 vs. 0.659 ± 0.018, p = 0.001).
KIR2DL2/2DL3 and its ligand HLA-C1 specifically control NK cell response. Its combination commonly exists in all the populations, but the frequencies were higher in the southern group (0.978 ± 0.006, 95% CI: 0.966–0.988) than in the northern group (0.860 ± 0.020, 95% CI: 0.833–0.886) (p = 0.00005). KIR2DL1 and KIR2DS2 had a similar binding specificity for HLA-C2. The frequencies of 2DL1+HLA-C2 were lower in the southern group (0.211 ± 0.026, 95% CI: 0.162–0.264) than in the northern group (0.472 ± 0.021, 95% CI: 0.443–0.500) (p = 0.003). However, there was no difference in frequencies of 2DS1+HLA-C2 combinations between the southern and northern groups (Table 6).
The comparison between the two populations indicated that Yugu and Tu did not show any difference in any of the KIR–HLA pairs, while the other populations all showed differences of between 1 and 15 pairs (Supplementary Table S4). The 2DL2/3+HLA-C1, 2DL1+HLA-C2, and 2DS1+HLA-C2 pairs showed clear differences between the northern and southern groups. For other HLA-Bw or HLA-A11/A3 pairs, the difference between the two populations was extensive. For example, Wa showed differences with: every other population except Lisu and Nu for carrying both KIR3DL1+Bw4 and KIR3DS1+Bw4 pairs; every other population except Jinuo, Nu, and Maonan for carrying both KIR3DL1+Bw4-80I and KIR3DS1+Bw4-80I pairs; and Hani, Lisu, Nu, Bulang, Dai, and Yugu for carrying KIR3DL1+Bw4-80T and KIR3DS1+Bw4-80T. For carrying KIR3DL1+Bw4, Bulang showed differences with every population except Jinuo, and Jinuo, Wa, Zhuang, Tu, and Yugu showed differences with at least five populations. The differences at KIR3DL1+Bw4-80I and KIR3DL1+Bw4-80T between the populations were not same as for KIR3DL1+Bw4. The differences in carrying KIR3DL2+A11/A3 or KIR2DS4+A11/A3 among the populations were similar, and Hani, Bulang, Wa, Tu, and Yugu showed differences with at least five populations.

3.4. HLA/KIR Correlation

The correlations of each KIR–HLA receptor and ligand pair were analyzed. The observed frequencies for KIR2DL3 and HLA-C1 ligands showed a significant correlation (r = 0.637, p = 0.035). Positive correlations were also observed in KIR3DL1+HLA-Bw4, KIR3DL1+HLA-Bw4 80I, KIR3DL1+HLA-Bw4 80T, KIR2DL2+HLA-C1, KIR2DS1+HLA-C2, and KIR2DS2+HLA-C1 pairs, but they were not significant. Negative correlations between KIR3DS1 and HLA-Bw4, and KIR2DL1 and HLA-C2 were observed, but they were not significant neither (Figure 3 and Supplementary Figure S1).

3.5. Phylogenetic Analysis

Both principal component analysis (PCA) and phylogenetic trees using KIR, HLA, and KIR–HLA combination frequencies were employed. For PCA based on 11 KIR (3DL1, 2DL1, 2DL3, 2DS4, 2DL2, 2DL5, 3DS1, 2DS1, 2DS2, 2DS3, and 2DS5) plots, Bulang showed distance from the other 10 populations (Figure 4a), and the other 10 populations did not cluster with their linguistic family as based on HLA-A, -B, and -C (Figure 4b), which agreed with previous studies. On the PCA plots based on KIR–HLA pairs, Yugu and Nu from northern China clustered together and showed distance from the other nine populations from southern China (Figure 4c).
On the phylogenetic tree based on KIRs, for the trees constructed either by all 11 KIR genes (Figure 5a), or by the inhibitor KIR genes or by the activating KIR genes (data not shown) had no clear clustering among the populations. For the NJ tree constructed using HLA genes, Tu and Yugu clustered together as one major branch. Bulang and Wa of Khmer clustered together, and Maonao, Zhuang, and Dai of Daic clustered together with Jinuo (Figure 5b). When 58 populations were compared on the phylogenetic tree using 11 KIRs frequencies, most populations clustered together according to their geographic location of Asian, European, African, and American (Figure 6). However, the closeness were not displayed clearly as in the NJ tree constructed by the HLA genes, in which the populations clustered according to their evolutional relationship [25]. In the Asian branch, on one hand, most Han populations in northern China clustered with Japanese and Korean, but also together with Nu, Yi, and Hani ethnic populations living in southern China. On the other hand, Yugu and Tu living in Northern China clustered with Southern Hans living in Guangdong, Hong Kong, together with Maonan, Bulang, Jinuo, etc., ethnic populations in southern China. The 11 ethnic populations in the present study still did not show a clear origin or linguistic clustering trend.

4. Discussion

The extensive diversity of HLA and KIR genes and their interactive roles in the immune response make these genes coevolve in genotypic combination. Disease and population studies have confirmed that they evolved together as specific KIR–HLA pairs to regulate NK cell function and play a vital role in the innate defense against pathogens and early placentation [30,31,32]. KIR–HLA combination studies have been performed in different populations worldwide; however, previous studies in China were limited to the Han population [4,33,34,35,36,37,38]. In the present study, we analyzed KIR and its HLA pairs in 11 ethnic populations from northern and southern China covering four different linguistic language families that represent the major origins of Chinese ethnic populations. This study not only provides useful genomic diversity data for the future study of viral infections, autoimmune diseases, and reproductive fitness among these populations, but also reveals clues about HLA and KIR interaction and coevolution under the diverse change of pathogen infections.
The coevolution of HLA and KIR has been proved by several population studies worldwide, and different KIR–HLA pair correlations were identified in different populations. In 2006, Single et al. studied the distribution of KIR and its HLA ligands in 30 populations worldwide and observed that a balancing selection acted on the negative correlation between KIR3DS1 and HLA-Bw4-80I pairs [30]. In 2013, Hollenbach et al. compared KIR–HLA pairs in 105 populations worldwide and revealed a significant correlation between KIR2DL3 and HLA-C ligands. However, the correlation for KIR3DL1 and HLA-Bw4 pairs was not significant [39]. In the Italian population, a correlation between KIR and HLA-C ligands was not observed; instead, a correlation between KIR3DL1 and HLA-Bw4 ligands, as well as KIR3DL2 and HLA-A3 and HLA-A11 ligands, was observed [40]. In the present study, the observed frequencies for KIR2DL3 and HLA-C1 ligands showed a correlation (r = 0.637, p = 0.035) that agreed with Hollenbach et al.’s study, as well as Gendzekhadze’s study in the Yucpa og South Amerindian [4]. The association of KIR2DL3 and HLA-C1 has also been investigated regarding the Hepatitis C virus and Malaria infection [41,42]. In Hirayasu et al.’s study, they found KIR2DL3+HLA-C1, but no other KIR–HLA pairs were associated with cerebral malaria, and the frequency of combination was significant lower in malaria high-endemic populations. This result suggested that natural selection has reduced the KIR2DL3+HLA-C1 frequencies in malaria high-endemic populations to favor the development of malaria [41]. Thus, KIR–HLA coevolution may be driven by microbial pathogens, resulting in specific distributions of KIR–HLA pairs in different populations.
The genetic difference between southern and northern Chinese has been confirmed in studies of HLA [35,43], as well as immunoglobulins [44], microsatellites [45], and Y-chromosome single-nucleotide polymorphisms [46]. Furthermore, population migration from northern to southern China has frequently happened throughout Chinese history [15,16,17]. In the present study, KIR2DL2/3+HLA-C1, KIR2DL1+HLA-C2, and KIR2DS1+HLA-C2 pairs showed clear differences between the northern and southern groups. The frequencies of KIR2DL2/3+HLA-C1 pairs were significantly higher in the southern group than in the northern group (0.978 vs. 0.860, p = 0.00005). This difference has also been investigated in Han population. The frequencies of KIR2DL2/3+HLA-C1 pairs were higher in two southern Chinese Han, namely Guangdong Han and Yunnan Han, than in the northern ethnic group, with frequencies of 0.981 and 0.950, respectively. In contrast, the frequencies of KIR2DL1+HLA-C2 and KIR2DS1+HLA-C2 pairs were lower than in the northern group, with frequencies of 0.294 and 0.351 for KIR2DL1+HLA-C2, and 0.100 and 0.155 for KIR2DS1+HLA-C2 in Guangdong Han and Yunnan Han, respectively [36,38]. Furthermore, the Tu and Yugu formed a cluster and showed a distance from other ethnic populations in southern China in the PCA plot constructed using KIR–HLA pair frequencies. According to historical records, northern and southern China underwent different pathogenic pressures. Regarding malaria (a serious infectious disease prevalent in China since 2700 BC), its epidemic area was focused in southern China, whereas northern China was malaria free or had a very low incidence rate [47,48]. Historically, Yunnan Province has been the most high-risk malaria area, especially along the China–Myanmar border [49,50]. In the present study, Tu and Yugu are from northern China, while the other populations are all in southern China, the most high-risk malaria areas. Therefore, we deduced that the different distribution between the northern and southern groups in China may have been caused by severe infectious disease epidemics, such as malaria.
Except for KIR+HLA-C pairs, KIR+HLA-Bw and KIR+HLA-A3/A11 pair differences were diverse in different populations. When considering KIR genes, genotypes, and haplotypes, more diversity was exhibited. It is interesting to note that the HLA gene distributions were in accordance with the population linguistic group and their origins. Both in the PCA plot and neighbor-joining tree constructed using HLA allele frequencies, the same linguistic origin populations clustered together. However, there were no clear cluster trends to distinguish the populations according to their origin or linguistic classification using either KIR, activated KIR, or KIR genotype frequencies among 11 ethnic populations. Moreover, in the phylogenetic tree constructed using 11 KIRs frequencies of 58 populations worldwide, there was a geographic closeness among Asians, Africans, Europeans, and Americans, while the 11 ethnic populations in the present study still did not show a clear origin or linguistic clustering trend. Compared with HLA genes, KIR genes have experienced a rapid evolution through a combination of gene duplication and nonhomologous recombination [1]. The extensive diversity of KIR genes in different populations worldwide indicates that distinct diseases have recently acted or are still acting to select on KIR repertoires [2]. This evolution was thought to be driven by the selective pressure of pathogen invasion, as well as reproduction. Moreover, haplotypes A and B are thought to have maintained a balance selection in human beings. The A haplotypes are associated with an improved response to pathogens, while B haplotypes are associated with reproductive fitness [51,52]. Previous studies have indicated that the populations are related to their geographic distribution based on KIR haplotype B but do not show a correlation based on haplotype A [53]. Moreover, it has been reported that B haplotypes are more prevalent in Australian Aborigines and Asian Indians, where the possible reason is due to these populations maybe being under strong pressure from infectious diseases [2]. In the present study, the frequencies of haplotypes A and B were almost similar to each other in Bulang, which showed a difference from other Asian populations. On the contrary, in Nu, haplotype A was as high as 0.830, which showed a significant difference from the other 10 populations. This extensive range of haplotype A in the present study, from 0.491 in Bulang to 0.830 in Nu, together with the diverse frequencies worldwide, may be the result of a founder effect, genetic drift, or natural selection [5,31]. Therefore, the distribution of KIR profiles among the present study populations could not be interpreted as a phylogenetic tree.
In conclusion, the distribution of KIR and its HLA ligands in 11 ethnic populations in China exhibited diverse characteristics, where each group had its specific KIR and KIR–HLA pair profile. The difference of KIR–HLA pairs between the northern and southern groups, but not among the four original groups, may reflect the strong pressure from previous or ongoing infectious diseases that have had a significant impact on KIR and its HLA combination repertoires.

Supplementary Materials

The Supplementary Materials are available online at https://www.mdpi.com/2073-4409/8/7/711/s1.

Author Contributions

Conceived and designed the experiments: L.S.; Sample collection: L.S. and J.Y.; Sample Genotyping: Y.Y., L.S., and Y.T.; Data Analysis: Y.Y. and S.L.; Manuscript writing: L.S.

Funding

This research was found by the National Natural Science Foundation of China (81573206) and the Special Funds for High-Level Health Talents of Yunnan Province (D-201669 and L-201615). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest. The sponsors had no role in the design, execution, interpretation, or writing of the study.

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Figure 1. The geographic locations of the 11 ethnic populations in China. dq: Di-Qiang ancient group; bp: Baipu ancient group; by: Baiyue ancient group; m: Mongolian group; TB: Tibeto-Burman sublanguage family; MK: Mon-Khmer sublanguage family; D: Daic sublanguage family; M: Mongolian sublanguage family.
Figure 1. The geographic locations of the 11 ethnic populations in China. dq: Di-Qiang ancient group; bp: Baipu ancient group; by: Baiyue ancient group; m: Mongolian group; TB: Tibeto-Burman sublanguage family; MK: Mon-Khmer sublanguage family; D: Daic sublanguage family; M: Mongolian sublanguage family.
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Figure 2. Haplotypes A and B frequencies in 11 ethnic populations in China.
Figure 2. Haplotypes A and B frequencies in 11 ethnic populations in China.
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Figure 3. Correlation of KIR2DL3 and HLA-C1.
Figure 3. Correlation of KIR2DL3 and HLA-C1.
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Figure 4. Principal component analysis. (a) PCA based on 11 KIR genes. Contributions of the first and second components were 60.10% and 17.49%, respectively. (b) PCA based on HLA-A, -B, and -C allele frequencies. Contributions of first and second components were 31.47% and 27.02%, respectively. (c) PCA based on KIR–HLA pairs. Contributions of first and second components were 55.72% and 30.09%, respectively.
Figure 4. Principal component analysis. (a) PCA based on 11 KIR genes. Contributions of the first and second components were 60.10% and 17.49%, respectively. (b) PCA based on HLA-A, -B, and -C allele frequencies. Contributions of first and second components were 31.47% and 27.02%, respectively. (c) PCA based on KIR–HLA pairs. Contributions of first and second components were 55.72% and 30.09%, respectively.
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Figure 5. Neighbor-joining tree. (a) Neighbor-joining tree based on DA genetic distance from 11 KIR gene frequencies. The optimal tree was one with the sum of branch length = 1.166. (b) Neighbor-joining tree based on DA genetic distance from HLA-A, -B, and -C allele frequencies. The optimal tree was one with the sum of branch length = 0.875.
Figure 5. Neighbor-joining tree. (a) Neighbor-joining tree based on DA genetic distance from 11 KIR gene frequencies. The optimal tree was one with the sum of branch length = 1.166. (b) Neighbor-joining tree based on DA genetic distance from HLA-A, -B, and -C allele frequencies. The optimal tree was one with the sum of branch length = 0.875.
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Figure 6. Neighbor-joining tree constructed using 11 KIR genes frequencies of 58 populations worldwide. The optimal tree was one with the sum of branch length = 0.159.
Figure 6. Neighbor-joining tree constructed using 11 KIR genes frequencies of 58 populations worldwide. The optimal tree was one with the sum of branch length = 0.159.
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Table
Table 1. The observed KIR frequencies and the estimated gene frequencies for each locus in 11 ethnic populations.
Table 1. The observed KIR frequencies and the estimated gene frequencies for each locus in 11 ethnic populations.
Hani (n = 145)Jinuo (n = 94)Lisu (n = 99)Nu (n = 106)Bulang (n = 106)Wa (n = 107)Dai (n = 112)Maonan (n = 89)Zhuang (n = 95)Tu (n = 70)Yugu (n = 96)
OF (%)GFOF (%)GFOF (%)GFOF (%)GFOF (%)GFOF (%)GFOF (%)GFOF (%)GFOF (%)GFOF (%)GFOF (%)GF
3DL1990.917880.658920.716980.863810.566980.863910.701990.894940.749960.793940.750
2DL11001.0001001.000990.8991001.000980.8631001.000970.836990.8941001.0001001.000950.772
2DL3970.834950.769980.8581001.000960.806970.832960.811940.763980.855930.733930.730
2DS4990.917880.658920.716980.863790.544980.863900.687990.894940.749970.831920.711
2DL2270.145270.143330.184100.053160.084320.176410.232390.221290.160330.181270.146
2DL5300.165350.194340.190260.142700.451240.126530.312350.193460.267330.181450.257
3DS1340.186500.293300.165250.131730.477310.170410.232350.193410.232530.313350.196
2DS1340.191440.249380.215230.120730.477340.187430.244300.165370.205390.216410.229
2DS2270.145270.143330.184100.053160.084320.176410.232390.221290.160330.181270.146
2DS3340.191290.15680.04180.038480.280110.058280.150310.172370.205130.066210.110
2DS590.046390.221290.159160.084410.229370.205330.182200.107150.077430.244310.171
2DL41001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.000990.898
3DL21001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.000
3DL31001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.000
2DP11001.000990.897990.8991001.000980.863990.9031001.000990.8941001.0001001.000950.772
3DP11001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.0001001.000990.898
OF: Observed Frequencies, GF: estimated Gene frequencies.
Table
Table 2. KIR genotypes identified in 11 ethnic populations.
Table 2. KIR genotypes identified in 11 ethnic populations.
Hapl GroupGeno GroupGenotype ID3DL12DL12DL32DS42DL22DL53DS12DS12DS22DS32DS52DL43DL23DL32DP13DP1HaniJinuoLisuNuBulangWaDaiMaonanZhuangTuYugu
Fre.Fre.Fre.Fre.Fre.Fre.Fre.Fre.Fre.Fre.Fre.
AAAA11111 111110.510 0.287 0.465 0.679 0.2080.425 0.2860.393 0.4320.271 0.469
AAAA18011 1 111110.007 0.021 0.010 0.014
AAAA2031111 111 1 0.009
AAAA3321 11 11111 0.009
BxAB21111 111 1111110.034 0.117 0.101 0.113 0.1700.113 0.0800.056 0.0740.143 0.094
BxAB3111111111 1111110.007 0.021 0.040 0.009 0.0280.009 0.063 0.0210.043 0.021
BxAB411111 1 111110.069 0.074 0.091 0.057 0.0280.085 0.1070.135 0.0950.143 0.052
BxAB5111111 11 111110.007 0.011 0.020 0.0190.019 0.0630.022 0.042 0.021
BxAB611111111111111110.021 0.011 0.009 0.0180.067 0.011 0.042
BxAB71111111111 111110.055 0.011 0.030 0.0280.009 0.009 0.0630.014
BxAB81111 111 1 111110.076 0.053 0.010 0.057 0.2550.019 0.0630.101 0.1370.057 0.083
BxAB9111111 11 1111110.007 0.030 0.009 0.038 0.0090.011 0.042
BxAB11111111 111 111110.021 0.009 0.018
BxAB121111 1111 111111 0.009
BxAB131111111 11 111110.034 0.010 0.0090.022 0.0320.014
BxAB141111 1 11111 0.032 0.020 0.0180.022 0.0110.014
BxAB151111 1 111110.007 0.010 0.009
BxAB171111 11 111111 0.014
BxAB1911111 11111 0.009
BxAB231111 111111 0.011 0.019 0.009 0.014
BxAB25111111 11111111 0.009
BxAB271111 11 1 11111 0.009
BxAB301111 1 1 11111 0.009 0.0090.011 0.010
BxAB31111111 1 11111 0.021
BxAB331111 111 111110.007
BxAB351111 1 1 111111 0.011 0.009 0.009
BxAB4111111 1 11 11111 0.011 0.011
BxAB4411111 1 1111110.007 0.038 0.011
BxAB571111 11111 11111 0.009
BxAB6211111 11 11111 0.021 0.011
BxAB6311111 111 111111 0.011 0.028
BxBB68 11 11111 111111 0.030 0.009 0.009 0.0090.011
BxBB69 11 111 111111 0.011 0.020 0.009 0.0380.009 0.027 0.031
BxBB70 11 111111111111 0.011 0.010 0.009 0.018 0.011
BxBB7111 111 11 111110.014 0.011 0.011 0.021 0.010
BxBB721 11 1 111 1 0.009 0.010
BxBB7311 1111111111111 0.018
BxBB75 11 111 11111110.007 0.053 0.104 0.032 0.010
BxBB761 111111 1111 1 0.021
BxBB79111 111 111111 0.010
BxBB80111 11111 111111 0.009 0.010
BxBB81 1 111111111111 0.010
BxBB86 11111111 111111 0.014
BxBB8911 11 1 11111 0.022
BxBB971 111 111 111 1 0.011 0.010
BxBB1041 11 1 11111 0.009
BxBB1061 111 11 1111 1 0.010
BxBB11311 111 111 111110.007 0.009
BxBB117 11 111 1 11111 0.011 0.019 0.009 0.021
BxBB151 111111111 11111 0.011
BxBB154 111 111 111111 0.009
BxBB164 11 11 11 111111 0.010
BxAB18811111 1 1 11111 0.009
BxAB19211111 11 11111 0.030 0.019
BxBB194 11 11 1 11 0.010
BxAB2021111 11 111111 0.074 0.020 0.0190.028 0.0090.011 0.057
BxAB2051111 1 1 11111 0.010
BxAB23311111 1111 111110.014 0.009 0.014
BxBB243 1 11111 111111 0.009
BxBB24711 1 n11 1 111nn 0.009
BxAB2601111 1 11111 0.011
BxAB2641111 1 1 111110.007 0.011 0.019 0.014
BxAB26811111 11111111 0.009
BxBB280 11 1 1111111111 0.011
BxBB28911 1 11 111111 0.009
BxBB2931 111 1 11111 0.009
BxBB31711 11 11 11111 0.021 0.014
BxAB31911111 1111111111 0.011 0.011
BxBB320 1111111111 1 0.009
BxBB32511 111111111111 0.009
BxBB331111 111 1 11111 0.009
BxAB37011111 11 111111 0.010 0.009 0.014
BxAB3721111 11 1 111110.076 0.011 0.0090.009
BxBB375 11 1 111111 0.011
BxBB37911 11 111 111111 0.014
BxAB381111111111 11111 0.010
BxAB382111111 1111111110.007 0.009
BxBB390 11 1 1 111111 0.010 0.009
BxBB39411 1 111 111111 0.014
BxAB40011111 1 1 111111 0.011 0.019 0.011 0.029 0.010
BxBB402 11 11 111111 0.014
BxAB4331111 11 11111 0.038 0.010
BxBB46611 1 111 1 11111 0.011
BxAB57011111 1 11111111 0.009
BxBB578111 11 111111 0.009
BxAB5871111111 1 11111 0.009
BxABn1*1111 1 111111 0.029
BxABn2*1111 1 11111 1 0.011
BxBBn3*11 11 1 1 111111 0.014
BxBBn4* 11 1 111111 0.014
BxBBn5* 11 1 1111111 0.011
BxBBn6* 1 11 111111 0.009
Fre.: Frequency. *n1–n6: unknown genotype ID.
Table
Table 3. HLA allotype frequencies in 11 ethnic populations.
Table 3. HLA allotype frequencies in 11 ethnic populations.
TitleHani (n = 145)Jinuo (n = 94) *Lisu
(n = 99)		Nu
(n = 106)		Bulang
(n = 106)		Wa
(n = 107)		Dai
(n = 112)		Maonan
(n = 89)*		Zhuang
(n = 95)		Tu
(n = 70)		Yugu
(n = 96)
A11/A30.8210.5850.5560.6420.7920.8790.6430.6970.5790.4430.417
Bw40.4620.3940.5050.4720.2830.3930.6070.5960.6530.7000.688
Bw4-80I0.4000.0740.3940.1980.1790.1960.3210.1350.4000.4000.448
Bw4-80T0.0620.3300.1620.2830.1040.2150.4110.4940.3050.3860.333
HLA-C10.9861.0001.0000.9810.9430.9910.9821.0001.0000.9140.833
HLA-C20.1450.2580.1620.2080.4060.2620.1790.0730.2210.4430.542
C1/C10.8550.7420.8380.7920.5940.7380.8210.9270.7790.5570.458
C1/C20.1310.2580.1620.1890.3490.2520.1610.0730.2210.3570.375
C2/C20.0140.0000.0000.0190.0570.0090.0180.0000.0000.0860.167
* The numbers for HLA-C1 and HLA-C2 was 89 in Jinuo and was 82 in Maonan.
Table
Table 4. Distribution of KIR and HLA-A11/A3 pairs in 11 ethnic populations.
Table 4. Distribution of KIR and HLA-A11/A3 pairs in 11 ethnic populations.
Title3DL2+A11/A32DS4+A11/A32DS2+A11
CountsFre.CountsFre.CountsFre.
Hani (n = 145)1190.8211190.821310.214
Jinuo (n = 94)550.585460.489120.128
Lisu(n = 99)550.556500.505210.212
Nu (n = 106)680.642680.64240.038
Bulang (n = 106)840.792650.613150.142
Wa (n = 107)940.879920.860320.299
Dai (n = 112)720.643660.589300.268
Maonan (n = 89)620.697580.652240.270
Zhuang (n = 95)550.579490.516160.168
Tu (n = 70)310.443300.429110.157
Yugu (n = 96)400.417380.396100.104
Fre.: Frequency.
Table
Table 5. Distributions of KIR and HLA-B pairs in 11 ethnic populations.
Table 5. Distributions of KIR and HLA-B pairs in 11 ethnic populations.
3DL1+3DS1+Bw43DL1+Bw43DS1+Bw43DL1+3DS1+BW4 80I3DL1+BW4 80I3DS1+BW4 80I3DL1+3DS1+BW4 80T3DL1+BW4 80T3DS1+BW4 80T
CountsFre.CountsFre.CountsFre.CountsFre.CountsFre.CountsFre.CountsFre.CountsFre.CountsFre.
Hani (n = 145)230.159440.30300.000210.145370.25500.00020.01490.06200.000
Jinuo (n = 94)150.160170.18140.04300.00060.06410.011150.160130.13820.021
Lisu (n = 99)130.131320.32340.040120.121240.24220.02020.020110.11120.020
Nu (n = 106)110.104380.35810.00970.066200.18900.00040.038260.24510.009
Bulang (n = 106)180.17060.05760.057100.09450.04730.02850.04730.02830.028
Wa (n = 107)70.065350.32700.00020.019190.17800.00050.047180.16800.000
Dai (n = 112)210.188380.33980.071140.125190.17020.018140.125240.21480.071
Maonan (n = 89)230.258290.32610.01150.05670.07900.000200.225230.25810.011
Zhuang (n = 95)190.200390.41140.042100.105230.24230.032100.105220.23220.021
Tu (n = 70)200.286270.38620.029100.143130.18620.029120.171150.21400.000
Yugu (n = 96)160.167460.47940.04290.094320.33320.021100.104200.20820.021
Fre.: Frequency.
Table
Table 6. Distributions of KIR and HLA-C pairs in 11 ethnic populations.
Table 6. Distributions of KIR and HLA-C pairs in 11 ethnic populations.
2DL2/3+HLA-C12DL1+HLA-C22DS1+HLA-C22DS2+HLA-C1
CountsFre.CountsFre.CountsFre.CountsFre.
Hani (n = 145)1420.979210.145100.069420.290
Jinuo (n = 89)870.978230.25890.101240.270
Lisu (n = 99)980.990160.16250.051330.333
Nu (n = 106)1040.981220.20840.038110.104
Bulang (n = 106)990.934410.387310.292170.160
Wa (n = 107)1040.972280.262100.093340.318
Dai (n = 112)1100.982200.179100.089440.393
Maonan (n = 82)810.98860.07320.024350.427
Zhuang (n = 95)951.000210.221110.116280.295
Tu (n = 70)620.886310.443110.157220.314
Yugu (n = 96)800.833480.500230.240220.229
Fre.: Frequency.

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Yao, Y.; Shi, L.; Yu, J.; Liu, S.; Tao, Y.; Shi, L. Distribution of Killer-Cell Immunoglobulin-Like Receptor Genes and Combinations of Their Human Leucocyte Antigen Ligands in 11 Ethnic Populations in China. Cells 2019, 8, 711. https://doi.org/10.3390/cells8070711

AMA Style

Yao Y, Shi L, Yu J, Liu S, Tao Y, Shi L. Distribution of Killer-Cell Immunoglobulin-Like Receptor Genes and Combinations of Their Human Leucocyte Antigen Ligands in 11 Ethnic Populations in China. Cells. 2019; 8(7):711. https://doi.org/10.3390/cells8070711

Chicago/Turabian Style

Yao, Yufeng, Lei Shi, Jiankun Yu, Shuyuan Liu, Yufen Tao, and Li Shi. 2019. "Distribution of Killer-Cell Immunoglobulin-Like Receptor Genes and Combinations of Their Human Leucocyte Antigen Ligands in 11 Ethnic Populations in China" Cells 8, no. 7: 711. https://doi.org/10.3390/cells8070711

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