郭晓媛^,1,2, 孙昌春^1,2, 薛思瑶^1,2, 赵慧², 江丽^,2, 李彩霞^,1,2 1. 山西医科大学,太原 030001
2. 公安部物证鉴定中心,法医遗传学公安部重点实验室,现场物证溯源技术国家工程实验室,北京 100038

49AISNP: a study on the ancestry inference of the three ethnic groups in the north of East Asia

Xiaoyuan Guo^,1,2, Changchun Sun^1,2, Siyao Xue^1,2, Hui Zhao², Li Jiang^,2, Caixia Li^,1,2 1. Shanxi Medical University, Taiyuan 030001, China
2. Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China

通讯作者: 江丽,博士,副主任法医师,研究方向：法医遗传学。E-mail:jl@mail.bnu.edu.cn;李彩霞,博士,主任法医师,研究方向：法医遗传学。E-mail:licaixia@tsinghua.org.cn

编委: 朱波峰
收稿日期:2021-02-25修回日期:2021-05-31

基金资助:

国家自然科学基金项目资助编号.81772027

Received:2021-02-25Revised:2021-05-31

Fund supported:

Supported by the National Natural Science Foundation of China No.81772027

作者简介 About authors
郭晓媛,在读硕士研究生,专业方向：法医学。E-mail:827633812@qq.com








摘要
样本的族群来源推断在法医调查中可发挥重要作用,一个理想的推断体系是用一组较少的遗传标记实现较高的族群推断准确性。本研究调研搜集了区分东亚北方三个族群北方汉族、日本人和韩国人的428个祖先信息SNP (ancestry informative SNP, AISNP),获取了其在三个族群307份样本中的分型,通过位点Fst值及等位基因频率聚类等信息进一步精简位点,最终得到了一组49AISNP组合。基于307份样本利用留一法对49AISNP进行推断准确性验证,结果表明其在北方汉族、日本和韩国族群中的推断准确性均高于99%。49AISNP组合将有助于东亚地区亚族群的进一步区分。
关键词： 法医遗传学;祖先信息SNP;族群推断;Fst;东亚北方族群

Abstract
The ancestry inference of unknown samples plays an important role in forensic investigations. An ideal panel is a set of few markers with high ancestry inference accuracy. We collected 428 AISNP (ancestry informative SNP) that can distinguish the three ethnic groups in north of East Asia, including northern Han, Japanese and Korean. The genotypes of 428 AISNP in 307 samples from these three ethnic groups were obtained. Based on the information of Fst value and clustering by allele frequency, the panel was further refined into 49AISNP smart panel. Inference accuracy of the 49AISNP was verified by the leave-one-out method with 307 samples, and the results showed that its accuracy was higher than 99% in the northern Han, Japanese and Korean ethnic groups. This panel can also be helpful to further distinguish the ethnic sub-groups in East Asia.
Keywords：forensic genetics;AISNP;ancestry inference;Fst;ethnic groups in north of East Asia


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本文引用格式
郭晓媛, 孙昌春, 薛思瑶, 赵慧, 江丽, 李彩霞. 49AISNP：东亚北方三个族群遗传来源推断. 遗传[J], 2021, 43(9): 880-889 doi:10.16288/j.yczz.21-073
Xiaoyuan Guo. 49AISNP: a study on the ancestry inference of the three ethnic groups in the north of East Asia. Hereditas(Beijing)[J], 2021, 43(9): 880-889 doi:10.16288/j.yczz.21-073


单核苷酸多态性(single nucleotide polymorphisms, SNPs)是指基因组中单个碱基的变异形成的多态性,多数SNP表现为基因座上二等位基因的变化^[1]。SNP在人类基因组中分布广泛,突变率低,具有较高的遗传稳定性。在不同族群之间频率分布差异大的SNP标记可用于预测族群来源,被称为祖先信息SNP (ancestry informative SNP, AISNP)^[2,3,4]。利用一组AISNP即可判断个体的族源信息。目前已报道了大量洲际族群区分的AISNP体系^[5,6,7,8],在洲际内部进行进一步细分的二级族群推断体系也有报道^[9,10,11],例如可区分东亚、南亚、北亚的74-plex SNP等^[9]。然而对东亚内部的区分推断仍有待进一步深入研究。

东亚人口众多^[12,13],有研究表明东亚地区存在从南到北的遗传差异^[14,15],且已发表不同的AISNP体系对其内部不同族群进行区分^[11,16,17],这为研究东亚内部族群进化和遗传多样性奠定了基础。在东亚北方地区,北方汉族、日本人和韩国人有着相似的外貌特征,如黄皮肤、黑眼睛、鼻子短而扁平等;语言也有相似之处,如韩语和日语在结构、元音以及缺乏连词方面有着显著的共同特点^[18]、汉字早在公元5世纪传入日本^[19]。基于线粒体DNA (mitochondrial DNA, mtDNA)^[20,21]、Y染色体^[18]和短串联重复序列^[22]的研究也表明三个族群间存在密切的遗传关系。最近有研究发现基于全基因组水平可区分汉族、日本和韩国族群^[17,23],也有研究建立了包含142、98、59及36个AISNP的四组嵌套体系,可实现汉族、日本和韩国族群的区分,但是随着位点数目的减少,区分准确率会下降至90%^[16]。对法医学应用而言,需筛选一组精简高效的AISNP,用于目标族群的推断区分,同时又可满足现场微量样本的检验需求。本研究从已发表文献中收集了东亚北方三个族群的428个AISNP及307份样本中的分型数据集,筛选了一组适用于法医学应用的AISNP,使其在这些族群中具有良好的区分度,以进一步提高族群推断技术在东亚北方的分辨率。

1 材料与方法

1.1 样本

参考数据库、测试样本群体信息见表1。参考数据库307份样本包括：来自千人基因组计划的103份北方汉族样本和104份日本样本^[24],以及亚洲多样性计划 (分型基于affymetrix genome-wide human SNP array 6.0芯片)^[17]的100份韩国样本。测试样本包括来自2个族群的38份样本：来自人类基因组多样性计划的10份北方汉族样本以及来自人类基因组多样性计划和西蒙斯基因组多样性计划的28份日本族群样本^[25]。

1.2 SNP位点来源

通过文献调研,从以下几个方面收集了428个AISNP位点：(1)中国科学院上海生命科学研究院徐书华课题组的203个AISNP^[17],用于北方汉族、日本和韩国族群的两两区分;(2)中国科学院北京基因组研究所陈华课题组的142个AISNP^[16],用于区分中国、日本和韩国族群的体系;(3)本课题组前期筛选的88个AISNP^{[26,27,28,29]},针对北方汉族与日本族群以及东亚南北方族群区分的位点。具体信息见附表1。

Table 1
表1
表1样本信息
Table 1Sample information

族群简称	族群信息	样本量	样本来源
CHB	中国北京的汉族人	103	千人基因组计划
JPT	东京的日本人	104	千人基因组计划
KOR	朝鲜人	100	亚洲多样性计划
CHB-C	中国北方汉族人	10	人类基因组多样性计划
JPT-C	日本人	28	人类基因组多样性计划、西蒙斯基因组多样性计划

测试样本以斜体表示,其余为参考数据库样本信息。

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1.3 质量控制

去除分型缺失率超过10%的样本和AISNP位点。使用Haploview v4.1软件计算总族群中AISNP的连锁不平衡值^[30],去除连锁不平衡(r²>0.2)的位点^[31,32]。

1.4 位点筛选及评估

在法医学应用中,具有相似信息量同时包含较少位点的组合最为实用。为了实现这个目标,需要剔除信息量较少或冗余的SNP以获得更为精简的体系。Fst值是群体遗传学中衡量群体间分化程度的一个重要指标,其范围是0~1,值越大表明群体间的遗传分化程度越大^[33]。在族群推断应用方面,可以衡量一组AISNP位点的信息含量。使用Genepop v4.7.5软件计算每个位点在三个族群中总的Fst值以及等位基因频率^[34],基于Fst值,以0.01为单位取不同范围的AISNP组合进行分析,确保优化后的AISNP组合提供与全部AISNP相似的族群推断信息量。

使用R v3.3.2软件基于等位基因频率绘制热图并进行主成分分析(principal components analysis, PCA),使用R v4.0.2软件基于每个AISNP位点对PCA中样本聚类结果的贡献度值(Cos2值)进行可视化展示。基于热图聚类结果删除Fst值较小的位点来减少冗余信息^[9]。使用Snipper网站(http://mathgene.usc.es/snipper/)的交叉验证选项计算人群特异分化值(population-specific divergence, PSD)^[35],通过比较其数值大小可以衡量这组位点在不同人群之间的区分平衡度^[5]。

1.5 推断方法准确性验证

使用DNA族群推断系统软件(DNA ancestry analyzer version1.0, DAA v1.0)^[36]计算三个族群307份样本的群体匹配概率(population assignment match probability, AMP)和似然比(likelihood ratio, LR),并进行族群聚类分析,参数设置为K=3,运行20次,统计每个样本的AMP和LR值。通过样本数据库的留一法验证,对筛选的AISNP进行准确性评估,即依次从数据库取出一份样本作为未知族群来源的样本,其余作为参考数据库进行分析,以此类推,直到所有样本均被测试一次为止。基于留一法验证的族群推断结果有3种情况：(1)一致性结论,AMP排名第一位的人族群与样本信息来源一致且LR大于10;(2)不排除结论,LR小于或等于10表明不排除AMP排名前两位的族群;(3)错误结论,AMP排名第一位的族群与样本信息来源不一致且LR大于10。根据样本推断族群来源结果与其实际所属族群的一致与否,统计推断结果的准确性。

测试样本准确性验证：以307份样本为参考数据库,38份测试集样本为未知族群来源的样本,计算每个测试集的AMP和LR值,并对推断结果的准确性进行统计。

1.6 位点的对比评估

为了验证本筛选方法的有效性,使用R v4.0.2软件中的sample函数进行随机抽样,从质控后的位点组合中随机抽取两组与最终组合数目相同的位点组合,并对其进行留一法准确性验证,与本研究所筛选的位点组合的准确性进行对比。

2 结果与分析

2.1 位点筛选及评估

307份样本的分型缺失率均小于10%,在428AISNP中25个位点的分型缺失率大于10%,去除后得到403个AISNP。基于三个族群307份样本在403个AISNP上的分型,在三个族群中总Fst值见附表1。连锁不平衡分析结果如附图1所示,共有70个SNP位点分别位于24个单体型块中,每个单体型块代表着位点之间存在高度连锁。附表2列出了相互连锁位点间的r²值,统计各个单体型块中位点的Fst值,仅留下每个单体型块中Fst值最大的AISNP位点,共得到357个AISNP。

Table 2
表2
表249AISNP位点信息
Table 2Information of the 49AISNP

序号	rs号	染色体	第37版序列位置	等位基因	Fst	序号	rs号	染色体	第37版序列位置	等位基因	Fst
1	rs10088365	8	10097398	G/A	0.2709	26	rs2622637	8	106505971	G/A/T	0.0951
2	rs10489744	1	165380623	G/A	0.0690	27	rs2642066	17	65639014	G/T	0.0910
3	rs10521076	9	108878562	C/T	0.0775	28	rs2838408	21	45246422	A/G	0.0750
4	rs10894724	11	133547942	T/A/G	0.0812	29	rs2976396	8	143764001	G/A	0.1521
5	rs10973829	9	38446392	C/T	0.0781	30	rs3111745	3	21827159	G/T	0.0751
6	rs11034709	11	38428289	A/G	0.1083	31	rs3217805	12	4388084	C/A/G/T	0.0844
7	rs11841589	13	73814891	G/T	0.0862	32	rs374722	2	147839830	G/A	0.0740
8	rs11846710	14	58343352	G/A	0.0768	33	rs3923736	7	155060730	A/C/G/T	0.0714
9	rs11959012	5	167668843	C/T	0.0694	34	rs4353835	3	32446775	C/T	0.0849
10	rs12006467	9	35090720	T/C	0.0993	35	rs4372441	11	7657259	C/T	0.0787
11	rs12039715	1	242801261	G/C	0.1726	36	rs4718412	7	66286867	T/C	0.0751
12	rs12483769	22	47790072	T/C	0.0870	37	rs5022079	18	76478188	A/G	0.0931
13	rs1256519	14	65736324	G/A	0.1027	38	rs6123723	20	37082145	C/T	0.0891
14	rs1322944	13	53683163	A/G	0.0740	39	rs6436971	2	231582797	T/C	0.0815
15	rs1333099	13	73691236	G/A	0.0715	40	rs6576127	14	106194763	C/T	0.1076
16	rs1678537	12	57900341	G/A	0.0885	41	rs7655849	4	161867415	T/A	0.0759
17	rs17121800	10	108710873	C/T	0.1007	42	rs928844	21	37999799	C/T	0.0846
18	rs17207681	5	138168527	A/G	0.0823	43	rs929115	1	171591189	T/G	0.0757
19	rs17451739	5	144030993	C/T	0.0732	44	rs9321180	6	130102959	C/T	0.0866
20	rs174520	14	88006776	T/G	0.0899	45	rs9549212	13	41022093	C/T	0.0708
21	rs17599827	5	89518433	A/C	0.0810	46	rs9896443	17	47125982	T/C	0.0738
22	rs17631488	5	18777746	A/G	0.1030	47	rs2770310	6	70165296	C/A/T	0.0924
23	rs1981370	18	74070815	A/G	0.0722	48	rs3027238	17	8135061	T/C	0.9803
24	rs2269275	5	83261405	A/G	0.0688	49	rs4578397	11	131832284	G/T	0.0737
25	rs229562	22	37599065	G/T	0.0827

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基于357个AISNP在三个族群中等位基因频率绘制的热图见附图2。在热图中,颜色的深浅代表了AISNP位点的基因频率在不同群体中的相似性和差异性,颜色越红表示基因频率越高,越浅表示基因频率越低,且具有相似频率分布的AISNP通常处于聚类树的同一分枝中。去除信息含量较少及冗余的位点以获得具有相似信息量的较小的体系,例如图中红色标记位点处,rs11104947与rs229562处于同一聚类小枝中且颜色相似,而rs11104947的Fst值(0.0782)低于rs229562的Fst值(0.0827),所以可删除rs11104947位点。经过多轮测试,最终获得了一组49个AISNP(以下简称49AISNP),表2列出了49AISNP的详细信息,三个族群的总Fst值介于0.0688~0.9803,平均值为0.1083。图1显示基于49AISNP在三个族群中的等位基因频率热图。

图1

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图1基于49AISNP的三个族群等位基因频率热图

Fig. 1Heatmap of 49AISNP based on the allele frequencies in three ethnic groups



表3显示了49个位点在各族群中的累计PSD值。可以看到三个族群之间的累计PSD值差异在1.4左右,说明该49AISNP在这三个族群之间的区分平衡度较好。

Table 3
表3
表349AISNP在每个族群中的累计PSD值
Table 3The cumulative PSD value of 49AISNP in each ethnic group

49AISNP	北方汉族	日本	韩国
累计PSD值	3.24566	3.96998	2.53635

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2.2 基于49AISNP的群体遗传结构

基于49AISNP的三个族群STRUCTURE聚类分析在K=3时的结果见图2,可观察到北方汉族、日本和韩国三个族群间明显的遗传差异。群体水平的祖先成分见饼状图,各颜色的比例代表该族群的祖先成分比例。如图所示,黄色、绿色和蓝色分别代表韩国、北方汉族和日本的祖先成分,其中,北方汉族族群中绿色成分占0.95;日本族群中蓝色成分占0.95;韩国族群中黄色成分占0.96。个体水平祖先成分见柱状图,其中每个柱形表示为一个样本,每种颜色代表一个祖先成分,每个条中各颜色的长度对应各样本的祖先成分比例。各颜色代表的祖先成分与饼状图相同。其中似然值最高的聚类结果显示：北方汉族族群样本的北方汉族成分中位数为0.98 (95%置信区间为0.94~0.97);日本族群样本的日本成分中位数为0.98 (95%置信区间为0.93~0.97);韩国族群样本的韩国成分中位数为0.98 (95%置信区间为0.95~0.98)。

主成分分析(PCA)可反映个体水平上的族群结构,不同的颜色代表不同的族群,样本的聚类情况可反映族群间的遗传关系,同时根据不同的主成分可进行族群的区分。图3A展示了基于49AISNP的主成分分析图,前2个主成分占变异的23.36%。第一主成分(PC1)占变异的12.96%,可将北方汉族与日本和韩国族群区分开;第二主成分(PC2)占变异的10.40%,可将日本族群与其他两族群区分开。图3B展示了基于每个AISNP位点对PCA中样本聚类结果的Cos2值分析,图中颜色由绿色到红色以及箭头的长短均代表Cos2值的大小,图中只展示Cos2值排名前18个AISNP的名称,其余位点的Cos2值参照箭头长短及颜色变化。结合Fst值来看,每个位点对样本聚类的贡献值大小排序也对应该位点的Fst值大小排序。

图2

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图249AISNP在K=3时的三个族群STRUCTURE分析结果(Ln P(D)=-12,331.7)

Fig. 2The STRUCTURE analysis for three ethnic groups at K = 3 of 49AISNP(Ln P(D)= -12,331.7)

图3

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图3主成分分析及Cos2值分析

A：基于三个族群在49AISNP的等位基因频率进行主成分分析;B：基于每个AISNP位点对PCA中样本聚类结果的Cos2值分析。
Fig. 3Principal component analysis and Cos2 value analysis

2.3 留一法准确性验证

基于49AISNP的留一法准确性验证结果见表4,北方汉族、韩国样本族群推断结果一致性为100%;日本样本族群推断结果一致性为99.04%,错误率为0.96%,1例错判样本信息见表5。

Table 4
表4
表4基于49AISNP的参考数据库族群推断结果统计
Table 4Statistic of sample assignment in reference ethnic groups using 49AISNP

族群	北方汉族	日本	韩国	总计
北方汉族	103(0)			103
日本	1(0)	103(0)		104
韩国			100(0)	100

每格数字代表归到该组的样本数目,括号中的数字代表其中LR值小于10的样本数目。

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Table 5
表5
表5基于参考数据库的错判样本信息
Table 5Information of misjudged sample in reference ethnic groups

样本来源	样本编号	族群	群体匹配概率	似然比	祖先成分
日本	NA18976	北方汉族	1.96E-15		0.75
		日本	8.10E-17	2.43E+01	0.16
		韩国	1.83E-19	1.07E+04	0.09

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2.4 测试样本验证

基于49AISNP的测试集准确性验证结果见表6,北方汉族族群推断结果一致性为80%,不排除结论为20%,错误率为0;日本样本族群推断结果一致性占82.15%,不排除结论占10.71%,错误率占7.14%。

Table 6
表6
表6基于49AISNP的测试集族群推断结果统计
Table 6Statistic of sample assignment in test ethnic groups using 49AISNP

族群	北方汉族	日本	韩国	总计
北方汉族	9(1)		1(1)	10
日本	2(2)	24(1)	2(0)	28

每格数字代表归到该组的样本数目,括号中的数字代表其中LR值小于10的样本数目。

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2.5 49AISNP对比评估

附图3显示了基于三个族群307份样本在357AISNP下的STRUCTURE聚类结果,在K=3时,可观察到三个族群明显的遗传差异,基于群体水平的祖先成分图显示北方汉族族群中绿色成分占0.97;日本族群中蓝色成分占0.96;韩国族群中黄色成分占0.98。基于个体水平祖先成分柱状图显示北方汉族族群样本的北方汉族成分中位数为0.99(95%置信区间为0.94~0.97);日本族群样本的日本成分中位数为0.99 (95%置信区间为0.93~0.97);韩国族群样本的韩国成分中位数为0.99 (95%置信区间为0.95~ 0.98)。同时利用主成分分析来评估357AISNP在个体水平上的族群结构,结果如附图4所示,前2个主成分占变异的9.03%。第一主成分(PC1)占变异的5.42%,可区分北方汉族和其他两族群;第二主成分(PC2)占变异的3.61%,可将韩国族群与其他两族群区分开。对比49AISNP与357AISNP的结果,两组AISNP均表现出良好的族群聚类能力,具有相似的族群推断准确性,且49AISNP的PC1和PC2总比例相较于357AISNP有所上升,证明通过一系列的筛选,我们成功地获得了一组具有相似信息量且位点数较少的组合。

图4

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图449AISNP与两组不同的、随机49AISNP在三个族群中的族群推断一致性和错误率比较

A：49AISNP与两组不同的、随机49AISNP在三个族群中的族群推断一致性比较;B：49AISNP与两组不同的、随机49AISNP在三个族群中的族群推断错误率比较。
Fig. 4Comparison of ancestry inference accuracy and error rate for the 49 AISNP with two different, random samplings of 49AISNP in the three ethnic groups



从357AISNP中用随机抽样的方法抽取的两组49AISNP,分别编为49AISNP-Random1和49AISNP- Random2。这两组的族群推断一致性和错误率与49AISNP的结果对比分别见图4A和图4B。结果显示两组随机49AISNP在三大族群中的族群推断一致性均比通过Fst值以及热图筛选出的49AISNP的低,且推断错误率较高,进一步说明我们的位点筛选方法是有效的。

3 讨论

汉族人口约占中国总人口的91.6%^[37],是世界上最大的遗传群体,有研究表明汉族与韩国人或日本人间的遗传关系比与中国的少数民族间的关系更为密切^[22]。现代日本人有双重血统,源于绳纹文化的狩猎采集者与弥生文化的移民之间的混合,他们从中国南部的长江口通过韩国带来了稻谷农业^[38]。这种历史迁徙造成了如今汉族、日本与韩国之间的遗传差异,而近年来随着中、日、韩三国之间社会经济的频繁交流,大量人口离开其出生地,旅居他国,融入当地社会。使用遗传标记进行样本的族群来源推断在法医实践应用中起着关键作用。随着测序技术的发展,高密度遗传标记越来越多地被应用在族群推断上,因其能够获到高分辨率的区分度^[39],然而,在实际应用中,高密度遗传标记并不适用于微量或降解检材的分型检测,位点数目少但信息量高的族群推断位点组合,对于法医学应用是最实用的。因此,我们需要在高密度遗传标记中剔除冗余的标记,本研究利用较高的Fst值筛选出了一组具有较高信息量且位点数较少的位点组合,为后续的体系构建及进一步验证奠定基础。

在体系的测试评估方面,一般用以下几种方法评估族群推断的准确性：一是用随机抽样的方式,将现有数据库以一定比例划分为训练集和测试集,用训练集内样本数据进行位点筛选,用测试集内样本对筛选结果进行准确性验证^[40];二是在应用现有数据库进行位点筛选后,新采集一部分样本,用新的测试集进行验证^[41];三是用交叉验证的方法评估数据库的准确性^[40],当样本量较大时,用十折交叉验证的方法,当样本量较少时,选择留一法评估数据库的准确性。但是将所有数据均用于训练集和测试集,容易造成筛选体系的过拟合,即最终模型在训练集上效果好;在测试集上效果差。为了避免过拟合的出现,一般可以重采样来评价模型效能,或者采用多次交叉验证的方法,求其均值估计算法准确性。由于本文中样本量较少,故未采用随机抽样的方法划分训练集和测试集,而是采用了留一法来逐一抽取测试样本,可以最大程度避免由于训练集样本量过少造成的偏差,同时另收集一部分样本做为测试集,以验证筛选体系的准确性。

在分析样本的族群来源时,应综合分析AMP、LR和族群成分^[7,32,41],AMP值是在三个族群中AISNP组合的等位基因频率计算所得,AMP值最高的族群并不一定是真正的来源族群,当两个族群间AMP值的比值即似然比LR大于10时,可以认为AMP值第一位的族群是该样本来源族群,当似然比小于10时,要结合族群成分进行综合分析^[41]。在49AISNP中,参考数据库族群来源推断错误的样本来自于日本族群中的NA18976,该样本的北方汉族和日本的似然比LR值计算结果为2.43E+01,其北方汉族、日本和韩国的族群成分分别为：0.75、0.16和0.09,该样本被推断为北方汉族。分析可能的原因如下：一是有可能推断错误,未来还需增加针对日本族群的特异性位点以达到更高的族群推断准确性;二是样本采样标签错误,或者由于历史或社会等原因,样本本身可能也不知道自己的族群来源^[9]。

从测试集的验证结果来看,利用49AISNP基于307份参考数据库上的测试集族群推断一致性结论占81.58%,不排除结论占13.16%,错误率仅5.26%。证明我们筛选的49AISNP可以有效地区分东亚的这三个族群。综上所述,本研究获得了一组49AISNP可以进行东亚北方三个族群的区分,且具有高鉴别能力和区分平衡度。该组合将有助于东亚地区二级族群推断体系的发展,进一步提升东亚族群的内部区分力。但是本研究中涉及的样本量较少,未来可增加样本量,进一步验证该组合在北方汉族、日本和韩国族群中的推断能力。

附录：

附加材料详见文章电子版 www.chinagene.cn。

Supplementary Table 1
附表1
附表1428AISNP位点信息
Supplementary Table 1Information of the 428AISNP

序号	rs号	染色体	第37版序列位置	等位基因	Fst值	序号	rs号	染色体	第37版序列位置	等位基因	Fst值
1	rs10018432	4	189437086	C/A	0.0460	40	rs10957985	8	81789921	G/A	0.0645
2	rs10058739	5	144074365	G/A	0.0297	41	rs10972006	9	3430684	T/C	0.0266
3	rs10088365	8	10097398	G/A	0.2709	42	rs10973829	9	38446392	C/T	0.0781
4	rs1009544	22	42239348	G/C	0.0430	43	rs10991718	9	93716118	T/C	0.0048
5	rs10107492	8	80568935	T/A/C	0.0503	44	rs11012716	10	21762267	A/G	0.0302
6	rs10110194	8	119479124	G/C/T	0.0585	45	rs11023463	11	15209506	A/C	0.0052
7	rs10132336	14	74869017	A/G	0.0327	46	rs11032331	11	33678161	G/T	0.0519
8	rs10132483	14	102299420	T/C	0.0519	47	rs11034709	11	38428289	A/G	0.1083
9	rs10134903	14	95229777	G/A	0.0360	48	rs11042911	11	10678785	T/C	0.0432
10	rs10139575	14	57087118	A/C/G	0.0342	49	rs11058961	12	127544998	G/A	0.0438
11	rs10166397	2	44372909	G/T	0.0490	50	rs11086012	19	16032643	A/C	0.0537
12	rs10171891	2	195971878	C/T	0.0431	51	rs11104947	12	88942980	G/A	0.0782
13	rs10177273	2	122239287	C/G	0.0782	52	rs1111212	2	159312733	C/G/T	-0.0007
14	rs1026975	4	113971374	T/G	0.0229	53	rs11128125	3	69389614	T/A/C/G	0.0035
15	rs10277413	7	55238464	T/A/G	0.0294	54	rs11133144	4	177229719	A/C/T	0.0446
16	rs10431079	11	116440678	A/G	0.0728	55	rs11151527	18	67347133	A/G	0.0506
17	rs10459664	15	35064934	C/T	0.0505	56	rs11159882	14	89525994	G/T	0.0479
18	rs10483991	14	88682616	G/A	0.0607	57	rs11161614	1	85898160	T/G	0.0299
19	rs10486260	7	8859616	C/T	0.0210	58	rs11164354	1	102439329	G/A	0.0436
20	rs10489744	1	165380623	G/A	0.0690	59	rs11174261	12	62362843	C/T	0.0473
21	rs10506294	12	51070554	T/C	0.0019	60	rs11177698	12	69906287	A/G	0.0534
22	rs10506725	12	77449514	T/C	0.0444	61	rs11222851	11	131831335	G/A	0.0683
23	rs10521076	9	108878562	C/T	0.0775	62	rs11223550	11	133532372	A/G	0.0527
24	rs10756234	9	11316481	C/T	-0.0004	63	rs11224765	11	101310590	C/T	0.0981
25	rs10768017	11	33681025	G/T	0.0571	64	rs11257349	10	6260717	T/G	0.0065
26	rs10771923	12	32320912	C/T	0.0332	65	rs1125832	16	52421140	T/A	0.0337
27	rs10778125	12	101962634	C/A	0.0513	66	rs11466640	4	38778903	G/A/T	0.0090
28	rs10806975	6	23766367	A/G/T	0.0372	67	rs11611033	12	63771136	C/T	0.0488
29	rs10819066	9	101356091	C/G	0.0262	68	rs11621121	14	65822493	C/T	0.0990
30	rs10833071	11	19209050	T/C	0.0328	69	rs11625485	14	80242132	T/C	0.0538
31	rs10836092	11	33676946	G/A/C	0.0515	70	rs11625876	14	35248467	C/T	0.0559
32	rs10836093	11	33678526	A/G	0.0530	71	rs11680024	2	49535856	A/C	-0.0040
33	rs10847616	12	128910954	A/C/T	0.0308	72	rs1178148	7	18778113	A/C	0.0795
34	rs10849181	12	638166	C/T	0.0525	73	rs11841589	13	73814891	G/T	0.0862
35	rs10858883	12	89893348	T/C	-0.0004	74	rs11846710	14	58343352	G/A	0.0768
36	rs10883736	10	104320029	G/T	0.0365	75	rs11847263	14	65775695	T/A/G	0.0635
37	rs10890510	1	48334490	A/C	0.0495	76	rs11874960	18	1948608	A/C/G/T	0.0049
38	rs10894034	11	129255618	C/T	0.0521	77	rs11959012	5	167668843	C/T	0.0694
39	rs10894724	11	133547942	T/A/G	0.0812	78	rs12006467	9	35090720	T/C	0.0993
79	rs12039715	1	242801261	G/C	0.1726	119	rs1391099	4	143373910	A/G/T	0.0025
80	rs12045644	1	40084488	G/T	0.0393	120	rs1420288	16	54477881	T/C	0.0519
81	rs12095503	1	171653329	C/T	0.0346	121	rs1420528	16	52417241	C/G	0.0374
82	rs12134013	1	164459913	C/T	0.0586	122	rs1420638	3	181497374	G/A	0.0407
83	rs12141436	1	68463212	G/A	0.0418	123	rs1422931	5	167397540	C/T	0.0462
84	rs12151767	2	198274929	G/A	0.0548	124	rs1428150	5	132490807	A/G	0.0666
85	rs12231617	12	124930127	C/G	0.0458	125	rs1442502	1	166548317	G/A	0.0277
86	rs12351269	9	16806521	T/C	0.0558	126	rs1453054	2	181359907	T/C/G	0.0119
87	rs12459941	19	10666112	G/A	0.0631	127	rs1465306	7	66699784	T/C	0.0672
88	rs12483769	22	47790072	T/C	0.0870	128	rs1465759	2	142576915	T/C	0.0365
89	rs12488690	3	150490463	G/A	0.0502	129	rs1488485	3	7951364	T/C	0.0125
90	rs12522710	5	65051804	G/A	0.0125	130	rs1522340	3	70369504	G/A	0.0320
91	rs1256519	14	65736324	G/A	0.1027	131	rs1524930	21	40968460	A/G	0.0649
92	rs1256520	14	65737193	C/A	0.0958	132	rs1537523	9	3649097	A/C	0.0512
93	rs12567990	1	207681685	C/T	-0.0038	133	rs1538374	10	72718336	G/A	0.0663
94	rs12571942	10	127954919	G/A	0.0056	134	rs1551653	8	34324240	A/G	0.0084
95	rs12586912	14	34023334	G/T	0.0422	135	rs155872	3	1454063	C/T	0.0227
96	rs12588061	14	50481926	T/C	0.0703	136	rs1561201	18	38205375	G/A	0.0330
97	rs12589835	14	30848932	C/T	0.0615	137	rs1566857	4	46048880	A/T	0.0468
98	rs12598852	16	13329469	G/A	0.0500	138	rs160539	16	63353953	C/G	0.0641
99	rs12630087	3	80935171	T/C	0.0429	139	rs1609763	5	142018424	T/G	0.0232
100	rs12632233	3	94033744	G/T	0.0334	140	rs1613215	3	77738317	T/C	0.0509
101	rs12676684	8	118857704	G/C/T	0.0584	141	rs1652519	15	58612113	G/A/C	0.0219
102	rs12691557	2	141469911	G/A/T	0.0461	142	rs1678537	12	57900341	G/A	0.0885
103	rs12768145	10	17610277	G/A	0.0532	143	rs16834705	2	193385209	A/G	0.0168
104	rs12776442	10	59297413	A/G	0.0075	144	rs16850913	2	166421763	A/G	0.0450
105	rs1284605	12	57921188	C/T	0.0863	145	rs16862627	3	150114701	G/A	-0.0022
106	rs13076655	3	80920612	C/T	0.0412	146	rs16893074	5	24074021	T/A	0.0042
107	rs13094402	3	80710455	A/G	0.0467	147	rs16895073	5	65596821	T/C	0.0302
108	rs13160399	5	165711426	G/A	0.0550	148	rs16944149	17	10938783	T/G	0.0223
109	rs1317548	10	12245520	G/A	0.0575	149	rs16951472	13	97073977	C/T	0.0503
110	rs131864	22	47271217	T/G	0.0450	150	rs16986850	20	41048928	T/C	0.0307
111	rs1322944	13	53683163	A/G	0.0740	151	rs16991180	20	10148468	G/A	0.0655
112	rs13249584	8	9710943	A/G	0.0786	152	rs16997770	4	124693346	T/C	0.0611
113	rs1325192	1	199244248	G/C/T	0.0625	153	rs17002737	22	42282012	C/T	0.0454
114	rs1333099	13	73691236	G/A	0.0715	154	rs17016175	4	143391299	A/G	0.0018
115	rs13419695	2	7347211	A/T	0.0808	155	rs17029405	3	32451697	C/A	0.0508
116	rs1362553	16	52438954	C/G	0.0329	156	rs17034099	3	11220006	C/A	0.0412
117	rs1371566	2	119738187	T/G	0.0337	157	rs17072984	18	62051788	G/A	0.0312
118	rs1378365	4	61775645	G/A	0.0587	158	rs17076328	5	173143508	G/A	0.0164
159	rs17121800	10	108710873	C/T	0.1007	199	rs2175743	1	70295901	C/T	0.0413
160	rs17129041	1	66996037	T/C	0.0529	200	rs2194757	2	21706029	G/A	0.0108
161	rs17207681	5	138168527	A/G	0.0823	201	rs2195856	1	187922876	A/C	0.0548
162	rs17239258	4	183263055	A/G	0.0500	202	rs2253974	21	23231832	C/T	0.0187
163	rs17372695	4	155060317	A/G	-0.0030	203	rs2255957	22	42241372	G/A/T	0.0440
164	rs17377643	22	42152988	A/C	0.0565	204	rs2269275	5	83261405	A/G	0.0688
165	rs17451739	5	144030993	C/T	0.0732	205	rs2269658	22	42280618	T/C	0.0375
166	rs174520	14	88006776	T/G	0.0899	206	rs2278339	18	50866195	T/G	0.0298
167	rs174534	11	61549458	A/G	-0.0023	207	rs229562	22	37599065	G/T	0.0827
168	rs174583	11	61609750	C/T	-0.0046	208	rs2295756	11	35241229	T/C	0.0000
169	rs17469810	3	80807568	G/A	0.0390	209	rs2313427	16	8815000	G/A	0.0470
170	rs17582830	4	38867427	A/G	0.0004	210	rs2330015	22	22536956	C/T	0.0678
171	rs17583068	4	38908616	G/C/T	0.0558	211	rs2333656	17	58184540	T/C	0.0576
172	rs17599827	5	89518433	A/C	0.0810	212	rs2349093	12	128520953	T/A	0.0004
173	rs17631488	5	18777746	A/G	0.1030	213	rs2352181	10	87653766	G/A	0.0257
174	rs17717717	3	71404405	G/A	0.0320	214	rs2353686	16	86354605	T/C	0.0566
175	rs17766621	14	71262932	T/C	0.0349	215	rs2377962	18	9101722	G/T	0.0522
176	rs17823795	14	63384260	G/A	0.0411	216	rs2430184	1	187786661	G/T	0.0482
177	rs1794072	11	61303803	C/T	0.0446	217	rs2526371	17	56443545	G/A	0.0501
178	rs1795704	12	58739693	C/A	0.0502	218	rs2547353	19	58582797	G/C/T	0.0666
179	rs1835298	11	112057620	G/A	0.0428	219	rs255630	5	127677188	T/C	0.0133
180	rs1841305	18	50163950	A/T	0.0556	220	rs258728	7	81663275	C/A	0.0337
181	rs1861693	12	107603157	C/T	0.0471	221	rs2587694	2	120213497	A/G	0.0026
182	rs1864307	18	57332158	T/G	0.0440	222	rs2589787	5	38260303	G/A	0.0374
183	rs1875174	10	2971488	C/G/T	0.0806	223	rs2622637	8	106505971	G/A/T	0.0951
184	rs1877696	8	9712822	C/G/T	0.0956	224	rs2642066	17	65639014	G/T	0.0910
185	rs189062	2	137349278	G/A	0.0429	225	rs2645645	4	77859067	A/G/T	0.0469
186	rs1898227	16	63282080	A/G/T	0.0546	226	rs26461	5	11202649	C/T	0.0211
187	rs1901786	3	130021945	G/A	0.0411	227	rs27061	5	1362793	T/C	0.0761
188	rs1944975	18	57276748	T/C	0.0369	228	rs2770310	6	70165296	C/A/T	0.0924
189	rs1981370	18	74070815	A/G	0.0722	229	rs2793438	6	24461427	G/C	0.0382
190	rs198464	11	61521621	G/A	-0.0050	230	rs2836749	21	40287238	A/C/T	0.0548
191	rs2008819	7	39662268	C/T	0.0459	231	rs2837352	21	41363778	C/T	0.0312
192	rs2011071	5	88741077	A/G	0.0583	232	rs2838408	21	45246422	A/G	0.0750
193	rs2035023	4	137753683	T/C	0.0549	233	rs2853668	5	1300025	G/T	0.0580
194	rs2047297	4	121511851	G/C/T	0.0271	234	rs2901142	2	124764392	C/T	0.0727
195	rs2068746	17	11389480	T/C	0.0464	235	rs2945733	8	134615750	T/G	0.0602
196	rs2099563	3	80740366	G/A	0.0447	236	rs2972336	5	76504150	G/C	-0.0028
197	rs2160913	18	8716090	A/C/G	0.0216	237	rs2976396	8	143764001	G/A	0.1521
198	rs2174739	6	79659170	A/G	0.0042	238	rs3027238	17	8135061	T/C	0.9803
239	rs3104517	15	27940339	A/G	0.0288	279	rs4690508	4	178295766	G/T	0.0504
240	rs3111745	3	21827159	G/T	0.0751	280	rs4718412	7	66286867	T/C	0.0751
241	rs315808	5	169750158	G/T	0.0626	281	rs475235	18	10029988	G/A/T	0.0289
242	rs3217805	12	4388084	C/A/G/T	0.0844	282	rs4756305	11	36292065	T/A/C	0.0532
243	rs321967	7	78314549	G/A/C	0.0454	283	rs4790409	17	1243941	C/T	0.0600
244	rs34052939	3	80765431	C/G/T	0.0447	284	rs480631	6	138406328	C/A/T	0.0620
245	rs34254286	4	164411734	A/G	0	285	rs4820428	22	41537589	A/G	0.0762
246	rs374722	2	147839830	G/A	0.0740	286	rs4834226	4	128986874	C/T	-0.0008
247	rs3757419	7	66029429	C/T	0.0718	287	rs4839523	1	116800016	T/C	0.0284
248	rs3757425	7	150067640	A/C	0.0706	288	rs4846992	1	230137518	A/G	0.0426
249	rs3758229	9	95078852	C/A/G	0.0574	289	rs4865142	4	57549583	C/T	0.0372
250	rs3775539	4	99304600	A/G	0.0452	290	rs4865290	4	53278689	G/A	0.0307
251	rs3910142	20	12921966	T/C	0.0613	291	rs4883926	13	73843655	T/C	0.0583
252	rs3923084	2	227948726	A/G/T	0.0586	292	rs4902391	14	65815979	G/T	0.0929
253	rs3923736	7	155060730	A/C/G/T	0.0714	293	rs4903754	14	40865770	G/A	0.0492
254	rs3924308	9	130185385	C/A	0.0129	294	rs4912933	5	143038150	G/A/C/T	-0.0034
255	rs4133446	5	86155113	T/C	0.0645	295	rs4918000	10	94837743	C/T	0.0399
256	rs4144800	4	38006916	G/A	0.0228	296	rs4922234	8	16639271	G/A/C/T	0.0433
257	rs4254643	3	792207	G/A	0.0307	297	rs4938285	11	116440011	T/C	0.0697
258	rs4263026	18	73309989	G/C	0.0466	298	rs5022079	18	76478188	A/G	0.0931
259	rs4280278	16	29439227	C/G	0.0841	299	rs5030883	10	70480868	A/C/T	0.0759
260	rs4325622	17	28526475	T/C	0.3617	300	rs520605	1	184795779	C/T	0.0581
261	rs4328700	20	23709545	A/G	0.0344	301	rs536430	10	79001643	C/T	0.0107
262	rs4353835	3	32446775	C/T	0.0849	302	rs5770018	22	49595560	C/T	0.0411
263	rs4355871	9	29653331	G/A/C	0.0665	303	rs5996064	22	42172080	C/T	0.0476
264	rs4372441	11	7657259	C/T	0.0787	304	rs6000401	22	37149336	C/T	0.0426
265	rs4393669	18	67296561	T/C	0.0330	305	rs6007756	22	48282309	G/A/C	0.0571
266	rs4414069	1	200391561	T/C	0.0478	306	rs6016226	20	38661387	C/T	0.0181
267	rs4466495	9	17496114	C/A/T	0.0489	307	rs6030932	20	42146320	T/G	0.0659
268	rs4486887	16	50677571	C/T	0.0579	308	rs6031579	20	43015108	C/G	0.0654
269	rs4491175	11	90956214	T/C	0.0485	309	rs6049064	20	23727145	C/T	0.0360
270	rs4533076	12	56069231	C/A	0.0410	310	rs6074520	20	12905188	T/A/C	0.0559
271	rs4543050	3	74954560	A/C/T	0.0194	311	rs6117562	20	753310	G/A	-0.0011
272	rs4578397	11	131832284	G/T	0.0737	312	rs6123723	20	37082145	C/T	0.0891
273	rs4603782	2	102735809	T/A	0.0642	313	rs6137010	20	2090118	C/T	0.0110
274	rs4668680	2	10529961	A/G	0.0199	314	rs6138046	20	23704388	G/C/T	0.0342
275	rs4674759	2	224068666	G/A	0.0059	315	rs616022	3	80711349	G/C/T	0.0253
276	rs4677399	3	74519384	T/C	0.0307	316	rs6436971	2	231582797	T/C	0.0815
277	rs4678169	3	124543103	C/A	0.0557	317	rs6450876	5	31925423	A/G	-0.0024
278	rs4681869	3	58573534	C/T	0.0583	318	rs6465469	7	95179593	G/A	0.0611
319	rs6478966	9	101776125	G/A	0.0192	359	rs760873	20	45393072	T/G	0.0582
320	rs6502840	17	4989857	C/T	0.0515	360	rs7630111	3	114165901	C/A	0.0499
321	rs6549596	3	74507710	T/C	0.0271	361	rs7642488	3	84688723	C/T	0.0406
322	rs6549601	3	74525187	C/T	0.0307	362	rs7655849	4	161867415	T/A	0.0759
323	rs6559935	9	89140339	G/A	0.0425	363	rs7666030	4	24728480	G/A	0.0492
324	rs6561294	13	46695350	T/C	0.0215	364	rs7674135	4	84577025	T/C	0.0399
325	rs6576127	14	106194763	C/T	0.1076	365	rs769411	2	171693639	C/G/T	0.0537
326	rs6589072	11	109322914	C/G	0.0501	366	rs7698051	4	60278484	A/G	0.0445
327	rs6599390	4	956047	A/G	0.0584	367	rs770576	11	99884272	A/G	0.0565
328	rs6707773	2	191344132	C/T	0.0279	368	rs7802058	7	81697666	A/C	0.0512
329	rs6717406	2	187743228	T/G	0.0326	369	rs7845383	8	88289450	G/T	0.0361
330	rs6738590	2	65059603	A/G	0.0429	370	rs789378	3	154079645	C/T	0.0205
331	rs6743998	2	196676489	T/A/C/G	0.0612	371	rs8014475	14	65811537	T/C	0.0937
332	rs6760967	2	4669324	C/T	0.0400	372	rs8015594	14	40942142	C/G	0.0688
333	rs6767410	3	80699208	C/T	0.0505	373	rs8049660	16	89857700	A/G	0.0398
334	rs6768622	3	74508075	C/T	0.0271	374	rs8050932	16	50687673	C/T	0.0545
335	rs6833150	4	61659236	A/G	0.0235	375	rs8060207	16	82273372	G/A	0.0287
336	rs6898653	5	115975656	A/G	0.0654	376	rs807959	19	22115835	A/G	0.0561
337	rs6924957	6	96853579	G/T	0.0527	377	rs8084884	18	75513922	A/T	0.0597
338	rs6955018	7	125115418	A/G	0.0474	378	rs8107011	19	30841000	A/C	0.0341
339	rs7006443	8	9290753	T/C	0.0383	379	rs827287	10	72708276	A/T	0.0435
340	rs7022178	9	29780195	G/A	0.0720	380	rs883433	19	39206288	C/T	0.0580
341	rs7032231	9	117025771	C/A	0.0706	381	rs928844	21	37999799	C/T	0.0846
342	rs7038964	9	104423907	C/T	0.0419	382	rs929115	1	171591189	T/G	0.0757
343	rs7097617	10	77504287	A/G	0.0447	383	rs9302550	16	52405521	C/T	0.0374
344	rs7117447	11	101351383	G/A	0.1118	384	rs9303660	17	31420730	C/T	0.0614
345	rs712645	5	110585627	C/T	0.0604	385	rs9321180	6	130102959	C/T	0.0866
346	rs713278	11	133563491	G/A	0.0619	386	rs933199	6	26112893	T/C	0.0107
347	rs7173716	15	70123826	T/G	0.0723	387	rs9384981	6	116803328	T/C	0.0259
348	rs7173982	15	36685718	C/A/T	-0.0013	388	rs9398434	6	116787017	T/G	0.0229
349	rs7193505	16	52401477	C/G	0.0394	389	rs943327	9	113599422	T/C	0.0695
350	rs7195477	16	29288634	T/C	0.0020	390	rs9532080	13	38126537	G/A	0.0395
351	rs7211426	17	53654548	G/A/C	0.0037	391	rs9549212	13	41022093	C/T	0.0708
352	rs7268940	20	9961532	C/T	0.0461	392	rs9590216	13	95905305	T/C	-0.0035
353	rs7271913	20	39263421	C/A	0.0155	393	rs9663367	10	19776910	A/C/T	0.0370
354	rs7317643	13	108536028	C/T	0.1665	394	rs978605	10	94903693	A/G	0.0208
355	rs738745	22	48246398	A/G	0.0255	395	rs9825713	3	100936248	C/A	0.0450
356	rs741245	12	4227248	G/A	0.0535	396	rs9826148	3	114464858	C/A/T	0.0677
357	rs7555405	1	31183486	C/T	0.0420	397	rs9852677	3	50291617	G/A/T	0.0412
358	rs758219	19	40294953	T/C	0.0461	398	rs9857773	3	149344615	C/A	0.0547
399	rs9860483	3	138730737	C/T	0.0985	414	rs1991955	6	29884066	A/C	0.0938
400	rs9896443	17	47125982	T/C	0.0738	415	rs2182268	13	113170683	G/A	0.0573
401	rs9941426	18	487281	T/G	0.0689	416	rs2261033	6	31603591	A/G	0.1538
402	rs9947737	18	455128	A/G	0.0477	417	rs2524095	6	31266117	A/C	0.0456
403	rs9979724	21	22447717	A/G	0.0383	418	rs284784	4	100335874	C/A	0.0255
404	rs10901244	9	136079463	C/T	0.0077	419	rs3015224	9	72728388	A/G	0.1419
405	rs11078951	17	38831415	T/A/G	0.1249	420	rs3130688	6	31210216	C/A/T	0.0991
406	rs11673276	19	55347963	C/T	0.0264	421	rs3135402	6	33024654	A/C	0.1028
407	rs12896399	14	92773663	G/T	0.0615	422	rs376877	6	33024606	C/G	0.0902
408	rs1414241	9	21744392	G/A/T	0.0756	423	rs4800105	18	19651982	C/G/T	0.0906
409	rs1431403	6	33047031	T/C	-0.0048	424	rs5758649	22	42605548	C/T	0.0059
410	rs1496279	5	18680420	A/T	-	425	rs6062275	20	61146909	C/G/T	0.1420
411	rs1500127	5	165739982	C/T	0.0416	426	rs7207346	17	75668619	C/A/G/T	0.0105
412	rs174592	11	61618608	A/G	-0.0049	427	rs8074124	17	36531565	C/T	0.0457
413	rs1927568	13	99740117	T/C	0.0137	428	rs901134	3	84688173	G/A	0.0574

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Supplementary Table 2
附表2
附表2成对连锁不平衡位点间的r²值
Supplementary Table 2r² of AISNP between paired LD

Block	rs号-1	rs号-2	r2值	Block	rs号-1	rs号-2	r2值
Block1	rs2853668	rs27061	0.243		rs5996064	rs2255957	0.869
Block2	rs13249584	rs1877696	0.885		rs5996064	rs2269658	0.695
Block3	rs6074520	rs3910142	0.771		rs5996064	rs17002737	0.574
Block4	rs6138046	rs4328700	1		rs1009544	rs2255957	0.991
	rs6138046	rs6049064	0.993		rs1009544	rs2269658	0.795
	rs4328700	rs6049064	0.993		rs1009544	rs17002737	0.679
Block5	rs4355871	rs7022178	0.221		rs2255957	rs2269658	0.802
Block6	rs10836092	rs11032331	0.98		rs2255957	rs17002737	0.686
	rs10836092	rs10836093	0.987		rs2269658	rs17002737	0.816
	rs10836092	rs10768017	0.906	Block10	rs4486887	rs8050932	0.371
	rs11032331	rs10836093	0.981	Block11	rs7193505	rs9302550	0.959
	rs11032331	rs10768017	0.899		rs7193505	rs1420528	0.959
	rs10836093	rs10768017	0.919		rs7193505	rs1125832	0.93
Block7	rs11466640	rs17582830	0.449		rs7193505	rs1362553	0.911
Block8	rs4903754	rs8015594	0.285		rs9302550	rs1420528	1
Block9	rs17377643	rs5996064	0.849		rs9302550	rs1125832	0.95
	rs17377643	rs1009544	0.735		rs9302550	rs1362553	0.912
	rs17377643	rs2255957	0.742		rs1420528	rs1125832	0.95
	rs17377643	rs2269658	0.62		rs1420528	rs1362553	0.912
	rs17377643	rs17002737	0.66		rs1125832	rs1362553	0.961
	rs5996064	rs1009544	0.861	Block12	rs1678537	rs1284605	0.965
Block13	rs198464	rs174534	0.388		rs6767410	rs34052939	0.96
Block14	rs6833150	rs1378365	0.278		rs6767410	rs17469810	0.944
Block15	rs1898227	rs160539	0.326		rs6767410	rs13076655	0.898
Block16	rs1256519	rs1256520	0.898		rs6767410	rs12630087	0.905
	rs1256519	rs11847263	0.565		rs13094402	rs616022	0.468
	rs1256519	rs8014475	0.61		rs13094402	rs2099563	0.992
	rs1256519	rs4902391	0.61		rs13094402	rs34052939	0.992
	rs1256519	rs11621121	0.606		rs13094402	rs17469810	0.976
	rs1256520	rs11847263	0.528		rs13094402	rs13076655	0.929
	rs1256520	rs8014475	0.596		rs13094402	rs12630087	0.937
	rs1256520	rs4902391	0.575		rs616022	rs2099563	0.472
	rs1256520	rs11621121	0.572		rs616022	rs34052939	0.472
	rs11847263	rs8014475	0.814		rs616022	rs17469810	0.466
	rs11847263	rs4902391	0.791		rs616022	rs13076655	0.468
	rs11847263	rs11621121	0.791		rs616022	rs12630087	0.476
	rs8014475	rs4902391	0.95		rs2099563	rs34052939	1
	rs8014475	rs11621121	0.925		rs2099563	rs17469810	0.984
	rs4902391	rs11621121	0.975		rs2099563	rs13076655	0.937
Block17	rs3757419	rs4718412	0.312		rs2099563	rs12630087	0.944
Block18	rs827287	rs1538374	0.258		rs34052939	rs17469810	0.984
Block19	rs6549596	rs6768622	1		rs34052939	rs13076655	0.937
	rs6549596	rs4677399	0.923		rs34052939	rs12630087	0.944
	rs6549596	rs6549601	0.975		rs17469810	rs13076655	0.921
	rs6768622	rs4677399	0.923		rs17469810	rs12630087	0.929
	rs6768622	rs6549601	0.975		rs13076655	rs12630087	0.992
	rs4677399	rs6549601	0.916	Block21	rs11224765	rs7117447	0.442
Block20	rs6767410	rs13094402	0.952	Block22	rs4938285	rs10431079	0.876
	rs6767410	rs616022	0.468	Block23	rs9398434	rs9384981	0.949
	rs6767410	rs2099563	0.96	Block24	rs1391099	rs17016175	0.593

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附图1

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附图1403AISNP连锁不平衡图

Supplementary Fig. 1Linkage disequilibrium diagram of 403AISNP

附图2

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附图2基于357AISNP的3个族群等位基因频率热图

Supplementary Fig. 2Heatmap of 357AISNP based on the allele frequencies in 3 ethnic groups

附图3

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附图3357AISNP在K=3时的3个族群STRUCTURE分析结果(Ln P(D)=-107,854.6)

Supplementary Fig. 3The STRUCTURE analysis for 3 ethnic groups at K=3 of 357AISNP(Ln P(D)= -107,854.6)

附图4

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附图4基于3个族群在357AISNP的等位基因频率进行主成分分析

Supplementary Fig. 4Principal component analysis of 3 ethnic groups based on allele frequencies of 357AISNP

致谢：

感谢中国科学院上海生命科学研究院计算生物学研究所的徐书华老师在文章数据方面给予的帮助。

(责任编委: 朱波峰)

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[1] Budowle B, van Daal A. Forensically relevant SNP classes
Biotechniques, 2008, 44(5):603-608, 610.
DOI:10.2144/000112806PMID:18474034 [本文引用: 1]
Forensic samples that contain too little template DNA or are too degraded require alternate genetic marker analyses or approaches to what is currently used for routine casework. Single nucleotide polymorphisms (SNPs) offer promise to support forensic DNA analyses because of an abundance of potential markers, amenability to automation, and potential reduction in required fragment length to only 60-80 bp. The SNP markers will serve an important role in analyzing challenging forensic samples, such as those that are very degraded, for augmenting the power of kinship analyses and family reconstructions for missing persons and unidentified human remains, as well as for providing investigative lead value in some cases without a suspect (and no genetic profile match in CODIS). The SNPs for forensic analyses can be divided into four categories: identity-testing SNPs; lineage informative SNPs; ancestry informative SNPs; and phenotype informative SNPs. In addition to discussing the applications of these different types of SNPs, this article provides some discussion on privacy issues so that society and policymakers can be more informed.

[2] Phillips C. Forensic genetic analysis of bio-geographical ancestry
Forensic Sci Int Genet, 2015, 18:49-65.
DOI:10.1016/j.fsigen.2015.05.012URL [本文引用: 1]

[3] Phillips C. Ancestry informative markers
Encycl Forensic Sci, 2013: 323-331.
[本文引用: 1]

[4] Kidd KK, Speed WC, Pakstis AJ, Furtado MR, Fang RX, Madbouly A, Maiers M, Middha M, Friedlaender FR, Kidd JR. Progress toward an efficient panel of SNPs for ancestry inference
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Recent reports have identified a north-south cline in genetic variation in East and South-East Asia, but these studies have not formally explored the basis of these clinical differences. Understanding the origins of these variations may provide valuable insights in tracking down the functional variants in genomic regions identified by genetic association studies. Here we investigate the genetic basis of these differences with genome-wide data from the HapMap, the Human Genome Diversity Project and the Singapore Genome Variation Project. We implemented four bioinformatic measures to discover genomic regions that are considerably differentiated either between two Han Chinese populations in the north and south of China, or across 22 populations in East and South-East Asia. These measures prioritized genomic stretches with: (i) regional differences in the allelic spectrum for SNPs common to the two Han Chinese populations; (ii) differential evidence of positive selection between the two populations as quantified by integrated haplotype score (iHS) and cross-population extended haplotype homozygosity (XP-EHH); (iii) significant correlation between allele frequencies and geographical latitudes of the 22 populations. We also explored the extent of linkage disequilibrium variations in these regions, which is important in combining genetic association studies from North and South Chinese. Two of the regions that emerged are found in HLA class I and II, suggesting that the HLA imputation panel from the HapMap may not be directly applicable to every Chinese sample. This has important implications to autoimmune studies that plan to impute the classical HLA alleles to fine map the SNP association signals.

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We have examined variations of five polymorphic loci (DYS287, DXYS5Y, SRY465, DYS19, and DXYS156Y) on the Y chromosome in samples from a total of 1260 males in eight ethnic groups of East Asia. We found four unique haplotypes constructed from three biallelic markers in these samples of East Asians. The Japanese population was characterized by a relatively high frequency of either the haplotype I-2b (-/Y2/T) or II-1 (+/Y1/C). These dual patterns of the distribution of Y chromosomes (I-2b/II-1) were also found in Korea, although they were present at relatively low frequencies. The haplotype II-1 was present in Northeast Asian populations (Chinese, Japanese, Koreans, and Mongolians) only, except for one male from the Thai population among the Southeast Asian populations (Indonesians, Philippines, Thais, and Vietnamese). The Japanese were revealed to have the highest frequency of this haplotype (27.5%), followed by Koreans (2.9%), Mongolians (2.6%), and mainland Chinese (2.2%). In contrast, the frequency of the haplotype I-2b was found to be 17.1% in the Japanese, 9.5% in Indonesian, 6.3% in Korean, 3.8% in Vietnamese, and 2.7% in Thai samples. These findings suggested that the chromosomes of haplotype I-2b were likely derived from certain areas of Northeast Asia, the region closest to Southeast Asia. Phylogenetic analysis using the neighbor-joining tree also reflected a general distinction between Southeast and Northeast Asian populations. The phylogeny revealed a closer genetic relationship between Japanese and Koreans than to the other surveyed Asian populations. Based on the result of the dual patterns of the haplotype distribution, it is more likely that the population structure of Koreans may not have evolved from a single ancient population derived from Northeast Asians, but through dual infusions of Y chromosomes entering Korea from two different waves of East Asians.

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