The names of Spain: a study of the isonymy structure of Spain

In order to estimate the isonymy structure of Spain, we studied surname distribution in 283 Spanish towns based on 3.625 million telephone users selected from 6.328 million users, downloaded from a commercial CD-ROM which contains all 13 million users in the country. Since in Spain the surname is made by the paternal and the maternal surname, it was possible to classify surnames according to parental origin. Two matrices of isonymy distances, one for paternal and one for maternal surnames, were constructed and tested for correlation with geographic distance. For the whole of Spain, Euclidean distance was significantly but weakly correlated with geographic distance both for paternal and maternal surnames, with r = 0.205 +/- 0.013 and r = 0.263 +/- 0.012, respectively. Two dendrograms of the 283 sampled towns were built from the two matrices of Euclidean distance. They are largely colinear. Four main clusters identified by the dendrograms are correlated with geography. Given the surname structure of Spain, we were able to calculate from isonymy and for each town 1). total or expressed inbreeding, 2). random or expected inbreeding, and 3). local inbreeding. Total inbreeding, F(IT), was highest in the North Atlantic regions and lowest along the Mediterranean Coast. The lowest levels were found in Andalusia, Catalunyia, Valencia, and Navarra. Random inbreeding, F(ST), had a similar geographical pattern. Local inbreeding, F(IS), was relatively uniform in the whole of Spain. In towns, random inbreeding dominates over local inbreeding. From the analysis, it emerges that the northwestern area of Spain is the most inbred.     

曲阜地区孔姓人群17个Y-STR基因座遗传多态性分析

应用AmpFLSTR~Y-filer~(TM)PCR Amplification Kit荧光标记复合扩增试剂盒(ABI公司),对曲阜地区11 18名孔姓男性个体血样DNA进行PCR,扩增,统计分析17个Y-STR基因座的遗传学参数。实验结果显示,17个基因座除DYS385a/b基因座检出51个单倍型外,其余基因座上分别检出4~11种等位基因,等位基因频率分布在0.0009~0.8265之间。由17个基因座组成的YH单倍型系统共检出206种单倍型。根据Y-STR单倍型推断了Y-SNP单倍群,发现曲阜孔姓有3种高频单倍群:C3、Q1a1和O3,前两者有着明显的单祖先扩散结构,最可能是孔子类型。本实验通过对曲阜地区孔姓人群群体17个Y染色体短串联重复序列基因座遗传多态性的调查,记录、保存孔姓人群遗传学数据。     

中国人姓氏群体遗传Ⅱ. 姓氏传递的稳定性与地域人群的亲缘关系

分析了比较了宋朝、明朝和当代姓氏的分布曲线,同姓率（ｉｓｏｎｙｍｙ）和地域人群间的亲缘关系。３个历史时期的姓氏分布反映了２个重要的现象;第一,中国人姓氏在历史上是连续的和稳定的。它揭示了姓氏所表现的血缘文化的痕迹与生命遗传物质,尤其是Ｙ染色体的进化具有基本相同的和平行的表现,第二,中国人的姓氏存在２种状态,常见姓氏和非常见姓氏。仅占总姓氏上５％的１００个常见姓氏集中了８５％以上的人口,而占总姓氏量     

深圳无偿献血人群中李姓、王姓和张姓无关男性个体Y-STR单倍型遗传多态性

为研究姓氏群体Y染色体特异STR单倍型的遗传多态性, 采用PCR复合扩增和ABI PrismTM 3100基因测序仪荧光检测方法对DYS426等9个Y-STR基因座进行基因分型, 检测深圳地区李姓无关男性个体血样139份、王姓无关男性个体118份、张姓无关男性个体119份。结果在139份李姓群体中, 共检出126种单倍型, 其中118种单倍型仅出现1次, 检出频率最高的1种单倍型出现6次, 单倍型多样性为0.9974; 118份王姓无关男性样本中, 共检出105种单倍型, 其中94种单倍型仅出现1次, 检出频率最高的1种单倍型出现4次, 单倍型多样性为0.9953; 张姓无关男性样本中, 共检出101种单倍型, 其中88种单倍型仅出现1次, 检出频率最高的1种单倍型出现4次, 单倍型多样性为0.9964。结果表明: 深圳地区李、王、张姓氏无关男性个体Y-STR单倍型的遗传多态性丰富, 与以往的汉族无关男性群体遗传资料相比较, 差异不显著。     

中国人姓氏群体遗传──Ⅰ.姓氏频率分布与人群遗传分化

分析了明朝中国人姓氏分布特征和1000年中影响姓氏分布的因数。通过对1000年来3个不同历史时期的α和ν值的分析,较为清楚地看到了中国人姓氏分布的规律,中国普遍存在同姓人群,尤其在中原地区相对隔离的同源Y染色体的群体（同姓人群）种类不同于其他地区,特别是比南方地区相对要多,姓氏种类也多。假设每一种同姓人群携带某一种特定类型的Y-DNA单倍型,那么,姓氏分布的特征可能提示在中国姓氏起源的中心—中原地区的省份中应存在着较为丰富的Y-染色体单倍型类型。利用首次获得的预测中国人姓氏种类的公式,估计当今正在使用的汉族姓氏为3100余种。     

A study of surnames in China through isonymy

The isonymy structure of 1.28 billion people registered in China's National Citizen Identity Information System was studied at the provincial, prefectural, and county administrative division levels. The isonymy was 0.026 for China as a whole. The average value of isonymy was 0.033 for the 30 provinces, 0.035 for the 334 prefectures, and 0.040 for the 2811 counties. The isonymy in China was much higher than in other countries. This finding may be partly explained by the low number of surnames in the Chinese language. Two regional features can be identified from the geographic distributions of isonymy. One feature is that the middle and lower reaches of the Yangtze River had the lowest values of isonymy at both the provincial and county levels. The second feature is that most counties with the highest values of isonymy were distributed in the provinces with high proportions of ethnic minorities. According to the dendrogram of surname distances, several clusters could be identified. Most provinces in a cluster were conterminous with one another. The one exception could be explained by demic migration called "braving the journey to the northeast of China." Isolation by distance could be detected because the correlation coefficients between Nei's distance and the geographic distances at the provincial, prefectural, and county levels were 0.64, 0.43, and 0.37, respectively. Human behaviors in Chinese history that may have caused these results have been discussed, including cultural origin, migration, residential patterns, and ethnic distribution.     

上海郊区姓氏和通婚分析

上海郊区本地人的来源多种多样,通过对13个分布于各区县的乡镇随机抽样统计姓氏,并作各地之间的相关分析和主成分分析,发现嘉定,浦 东,南汇,奉贤东部组成东北部一类,金山,松江,青浦,崇明组成相对一类,南翔姓氏来源复杂,马桥,金汇也是独特的一类。家谱中记载的姓氏与现代的姓氏有明显对应关系,并且东北部的姓氏主要来源于长江以北,而西南部姓氏来源于长江以南,这说明两地人群来源可能不同,东北部晚近成陆地区的居民来源于北方地区,而西南部居民来源于南方其他地区,马桥;金汇等冈身地带居民与远古马桥文化有传承关系,其姓氏成因多样,对金汇镇20世纪不同时期通婚范围的研究发现,70代以平,因媒约习俗而使通婚半径固定于5公里左右的两个乡镇之内,70,80年代自由恋爱使通婚半径缩为3公里左右的同一个乡内,90年代以后由于社会发展迅速而通婚半径扩展到近年的国内各省,金汇镇的通婚范围和血缘自然扩散状况可以代表上海及南方多数地区,相领乡镇之间在媒妁习俗时需2000多年同化时间,在自由恋爱时需7000多年同化时间,可见自然扩散对基因交流的作用是很弱的,移民混居才是主要因素,上海各来源群体的邻居历史远远短于同化时间,所以其间几乎是没有混血的,南方其他地区的情况也会较相似。     

Surnames in Argentina: a population study through isonymy

In order to study the isonymic structure of Argentina, the surname distributions of 22.6 million electors registered for the year 2001 were analyzed in the 24 districts (distritos) and 541 municipalities (municipios) of the country. The number of different surnames found was 414,441. Matrices of isonymic distances between districts were constructed and tested for correlation with the geographic distance between the capital towns of the districts. We found that, for the whole of Argentina, Euclidean distance was correlated with the log of geographic distance (r=0.480+/- 0.067). A dendrogram of the 24 regions was built from the matrix of Euclidean distances, using the UPGMA method. The clusters identified by the dendrogram are coincident with conterminous geographical regions of the country. Random inbreeding calculated from isonymy, F(ST), was highest in La Rioja, Corrientes, and Santiago del Estero. It was lowest in the area of Buenos Aires and in the north-central region of Santa Fé. Average Fisher's alpha for municipalities was 358; for districts, it was 422; and for Argentina as a unit, it was 602. The geographical distribution of alpha in 541 municipalities, high in the east and lower in the west of the country, is compatible with the settlement in the 20th century of subsequent waves of immigrants moving from the North Atlantic coast toward the foot of the Andes and toward the south. The present structure of Argentina indicates that migration dominates over drift.     

Genetic genealogy comes of age: Perspectives on the use of deep‐rooted pedigrees in human population genetics

In this article, we promote the implementation of extensive genealogical data in population genetic studies. Genealogical records can provide valuable information on the origin of DNA donors in a population genetic study, going beyond the commonly collected data such as residence, birthplace, language, and self‐reported ethnicity. Recent studies demonstrated that extended genealogical data added to surname analysis can be crucial to detect signals of (past) population stratification and to interpret the population structure in a more objective manner. Moreover, when in‐depth pedigree data are combined with haploid markers, it is even possible to disentangle signals of temporal differentiation within a population genetic structure during the last centuries. Obtaining genealogical data for all DNA donors in a population genetic study is a labor‐intensive task but the vastly growing (genetic) genealogical databases, due to the broad interest of the public, are making this job more time‐efficient if there is a guarantee for sufficient data quality. At the end, we discuss the advantages and pitfalls of using genealogy within sampling campaigns and we provide guidelines for future population genetic studies. Am J Phys Anthropol 150:505–511, 2013. © 2013 Wiley Periodicals, Inc.