• Molecular & Cellular Toxicology
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• v.5 no.4
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• pp.291-297
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• 2009

Kawasaki disease (KD) is believed to be infectious but etiology and the mechanism of development remain elusive. The aim of this study was to investigate the association between transmembrane channel-like 1 (TMC1) gene and KD. One hundred nine KD patients and 424 normal controls were enrolled. Of all KD patients, 34 developed coronary artery lesions (CALs). Eleven single nucleotide polymorphisms (SNPs) within TMC1 gene were selected and SNP genotyping was performed by the direct sequencing. Genotype frequencies were analyzed with the SNPAnalyzer, Helixtree, and SNPStats programs. In the present study, six SNPs (rs7851577, rs10781105, rs2589615, rs1663743, rs1373628, and rs1373626) were significantly associated with the risk of KD. In further haplotype analysis, one haplotype (CGGACCCT) showed a significant association between KD and control groups. These results suggest that TMC1 gene may be a susceptibility gene for KD in Korean population.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.1
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• pp.36-42
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• 2016

Milk-related traits (milk yield, fat and protein) have been crucial to selection of Holstein. It is essential to find the current selection trends of Holstein. Despite this, uncovering the current trends of selection have been ignored in previous studies. We suggest a new formula to detect the current selection trends based on single nucleotide polymorphisms (SNP). This suggestion is based on the best linear unbiased prediction (BLUP) and the Fisher's fundamental theorem of natural selection both of which are trait-dependent. Fisher's theorem links the additive genetic variance to the selection coefficient. For Holstein milk production traits, we estimated the additive genetic variance using SNP effect from BLUP and selection coefficients based on genetic variance to search highly selective SNPs. Through these processes, we identified significantly selective SNPs. The number of genes containing highly selective SNPs with p-value <0.01 (nearly top 1% SNPs) in all traits and p-value <0.001 (nearly top 0.1%) in any traits was 14. They are phosphodiesterase 4B (PDE4B), serine/threonine kinase 40 (STK40), collagen, type XI, alpha 1 (COL11A1), ephrin-A1 (EFNA1), netrin 4 (NTN4), neuron specific gene family member 1 (NSG1), estrogen receptor 1 (ESR1), neurexin 3 (NRXN3), spectrin, beta, non-erythrocytic 1 (SPTBN1), ADP-ribosylation factor interacting protein 1 (ARFIP1), mutL homolog 1 (MLH1), transmembrane channel-like 7 (TMC7), carboxypeptidase X, member 2 (CPXM2) and ADAM metallopeptidase domain 12 (ADAM12). These genes may be important for future artificial selection trends. Also, we found that the SNP effect predicted from BLUP was the key factor to determine the expected current selection coefficient of SNP. Under Hardy-Weinberg equilibrium of SNP markers in current generation, the selection coefficient is equivalent to $2^*SNP$ effect.