Abstract Genome-wide association studies focused on searching genes responsible for several diseases. Admixture mapping studies proposed a more efficient alternative capable of detecting polymorphisms contributing with a small effect on the disease risk. This method focuses on the higher values of linkage disequilibrium in admixed populations. To test this, we analyzed 10 genomic regions previously defined as related with colorectal cancer among nine populations and studied the variation pattern of haplotypic structures and heterozygosity values on seven categories of SNPs. Both analyses showed differences among chromosomal regions and studied populations. Admixed Latin-American samples generally show intermediate values. Heterozygosity of the SNPs grouped in categories varies more in each gene than in each population. African related populations have more blocks per chromosomal region, coherently with their antiquity. In sum, some similarities were found among Latin American populations, but each chromosomal region showed a particular behavior, despite the fact that the study refers to genes and regions related with one particular complex disease. This study strongly suggests the necessity of developing statistical methods to deal with di- or tri-hybrid populations, as well as to carefully analyze the different historic and demographic scenarios, and the different characteristics of particular chromosomal regions and evolutionary forces.

中文翻译：

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拉丁美洲人群的差异混合及其对结直肠癌研究的影响

摘要 全基因组关联研究侧重于搜索导致多种疾病的基因。混合物作图研究提出了一种更有效的替代方案，能够检测对疾病风险影响很小的多态性。这种方法侧重于混合种群中连锁不平衡的较高值。为了测试这一点，我们分析了 9 个人群中先前定义为与结直肠癌相关的 10 个基因组区域，并研究了 7 类 SNP 的单倍型结构和杂合度值的变异模式。两种分析都显示染色体区域和研究人群之间存在差异。混合的拉丁美洲样品通​​常显示中间值。按类别分组的 SNP 的杂合性在每个基因中的变化大于在每个群体中的变化。非洲相关人群每个染色体区域有更多的块，与他们的古代相一致。总之，在拉丁美洲人群中发现了一些相似之处，但每个染色体区域都表现出特定的行为，尽管该研究涉及与一种特定复杂疾病相关的基因和区域。这项研究强烈表明有必要开发统计方法来处理双杂交或三杂交种群，并仔细分析不同的历史和人口统计情况，以及特定染色体区域和进化力量的不同特征。尽管该研究涉及与一种特定复杂疾病相关的基因和区域。这项研究强烈表明有必要开发统计方法来处理双杂交或三杂交种群，并仔细分析不同的历史和人口统计情况，以及特定染色体区域和进化力量的不同特征。尽管该研究涉及与一种特定复杂疾病相关的基因和区域。这项研究强烈表明有必要开发统计方法来处理双杂交或三杂交种群，并仔细分析不同的历史和人口统计情况，以及特定染色体区域和进化力量的不同特征。