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The origin and evolution of variable number tandem repeat of CLEC4M gene in the global human population.

Hui Li | Jia-Xin Wang | Dong-Dong Wu | Hua-Wei Wang | Nelson Leung-Sang Tang | Ya-Ping Zhang
PloS one | 2012

CLEC4M is a C-type lectin gene serving as cell adhesion receptor and pathogen recognition receptor. It recognizes several pathogens of important public health concern. In particular, a highly polymorphic variable number tandem repeat (VNTR) at the neck-region of CLEC4M had been associated with genetic predisposition to some infectious diseases. To gain insight into the origin and evolution of this VNTR in CLEC4M, we studied 21 Africans, 20 Middle Easterns, 35 Europeans, 38 Asians, 13 Oceania, and 18 Americans (a total of 290 chromosomes) from the (Human Genome Diversity Panel) HGDP-CEPH panel; these samples covered most of alleles of this VNTR locus present in human populations. We identified a limited number of haplotypes among the basic repeat subunits that is 69 base pairs in length. Only 8 haplotypes were found. Their sequence identities were determined in the 290 chromosomes. VNTR alleles of different repeat length (from 4 to 9 repeats) were analyzed for composition and orientation of these subunits. Our results showed that the subunit configuration of the same repeat number of VNTR locus from different populations were, in fact, virtually identical. It implies that most of the VNTR alleles existed before dispersion of modern humans outside Africa. Further analyses indicate that the present diversity profile of this locus in worldwide populations is generated from the effect of migration of different tribes and neutral evolution. Our findings do not support the hypothesis that the origin of the VNTR alleles were arisen by independent (separate) mutation events and caused by differential allele advantage and natural selection as suggested by previous report based on SNP data.

Pubmed ID: 22279577

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ARLEQUIN (tool)

RRID:SCR_009051

An exploratory population genetics software environment able to handle large samples of molecular data (RFLPs, DNA sequences, microsatellites), while retaining the capacity of analyzing conventional genetic data (standard multi-locus data or mere allele frequency data). (entry from Genetic Analysis Software)

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