Paoli G, Franceschi M G, Tofanelli S, Stanyon R
Dipartimento di Scienze del Comportamento Animale e dell'Uomo, Università di Pisa, Italy.
Hum Biol. 1997 Feb;69(1):11-29.
The genetic structure and interrelationships of six populations of the Garfagnana valley (Tuscany, Italy) were examined using chromosomal heteromorphisms concurrently with blood group system, red cell isozyme, and serum protein polymorphisms, secretor status, and surname frequency data. We aimed to evaluate the relationship of cytogenetic polymorphisms to more classical sources of gene frequency data in a population with a well-known demographic scenario. The R matrix technique (Harpending and Jenkins 1973) was used to estimate kinship coefficients, and the Harpending-Ward model (1982) and its extensions for quantitative traits (Relethford and Blangero 1990) were used to detect differential systematic pressure among population subdivisions. Mantel statistics were used to assess the significance of the correlations between cytogenetic, genetic, isonymy, geographic, and migration matrices. The analyses consistently gave similar results for the DA/DAPI cytogenetic heteromorphism and most gene frequency data. Both sets of results depend on migration patterns and on geographic distance among population subdivisions. However, C cytogenetic heteromorphism and some separately analyzed genetic markers did not fit the demogeographic pattern. Overall, it appears that data from different levels of the genetic hierarchy (namely, DNA regions encoding for classical biochemical markers and the noncoding highly variable cytogenetic bands of heterochromatin) can be treated and compared using the same analytical tools.
利用染色体异态性,同时结合血型系统、红细胞同工酶、血清蛋白多态性、分泌型状态和姓氏频率数据,对意大利托斯卡纳加尔法尼亚纳山谷六个群体的遗传结构和相互关系进行了研究。我们旨在评估在一个人口统计学情况已知的群体中,细胞遗传学多态性与更经典的基因频率数据来源之间的关系。采用R矩阵技术(哈彭丁和詹金斯,1973年)来估计亲属系数,并使用哈彭丁 - 沃德模型(1982年)及其对数量性状的扩展模型(雷尔思福德和布兰杰罗,1990年)来检测群体细分之间的差异系统压力。使用曼特尔统计量来评估细胞遗传学、遗传学、姓氏学、地理和迁移矩阵之间相关性的显著性。对于DA/DAPI细胞遗传学异态性和大多数基因频率数据,分析结果始终相似。两组结果均取决于迁移模式以及群体细分之间的地理距离。然而,C细胞遗传学异态性和一些单独分析的遗传标记并不符合人口地理模式。总体而言,不同遗传层次水平的数据(即编码经典生化标记的DNA区域和异染色质的非编码高变细胞遗传学带)似乎可以使用相同的分析工具进行处理和比较。