通过对59个法国人类多态性研究中心(CEPH)家系进行分离分析确定的杀伤细胞免疫球蛋白样受体(KIR)单倍型。
KIR haplotypes defined by segregation analysis in 59 Centre d'Etude Polymorphisme Humain (CEPH) families.
作者信息
Martin M P, Single R M, Wilson M J, Trowsdale J, Carrington M
机构信息
Cancer and Inflammation Program, Laboratory of Experimental Immunology, SAIC-Frederick, Inc, NCI-Frederick, Frederick, MD, 21702, USA.
出版信息
Immunogenetics. 2008 Dec;60(12):767-74. doi: 10.1007/s00251-008-0334-y. Epub 2008 Oct 30.
The killer cell immunoglobulin-like receptor (KIR) gene cluster exhibits extensive allelic and haplotypic diversity. Variation at the locus is associated with an increasing number of human diseases, reminiscent of the HLA loci. Characterization of diversity at the KIR locus has progressed over the past several years, particularly since the sequence of entire KIR haplotypes have become available. To determine the extent of KIR haplotypic variability among individuals of northern European descent, we genotyped 59 CEPH families for presence/absence of all KIR genes and performed limited allelic subtyping at several KIR loci. A total of 20 unique haplotypes differing in gene content were identified, the most common of which was the previously defined A haplotype (f = 0.52). Several unusual haplotypes that probably arose as a consequence of unequal crossing over events were also identified. Linkage disequilibrium (LD) analysis indicated strong negative and positive LD between several pairs of genes, values that may be useful in determining haplotypic structure when family data are not available. These data provide a resource to aid in the interpretation of disease association data involving individuals of European descent.
杀伤细胞免疫球蛋白样受体(KIR)基因簇表现出广泛的等位基因和单倍型多样性。该基因座的变异与越来越多的人类疾病相关,这与HLA基因座类似。在过去几年中,KIR基因座多样性的特征研究取得了进展,特别是自从完整的KIR单倍型序列可用以来。为了确定北欧血统个体中KIR单倍型变异的程度,我们对59个CEPH家族进行了所有KIR基因存在/缺失的基因分型,并在几个KIR基因座进行了有限的等位基因亚型分析。共鉴定出20种基因含量不同的独特单倍型,其中最常见的是先前定义的A单倍型(f = 0.52)。还鉴定出了几种可能由于不等交换事件而产生的异常单倍型。连锁不平衡(LD)分析表明,几对基因之间存在强烈的负向和正向LD,当没有家族数据时,这些值可能有助于确定单倍型结构。这些数据为解释涉及欧洲血统个体的疾病关联数据提供了资源。
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