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Korean Society for Biochemistry and Molecular Biology (생화학분자생물학회)
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BcSNPdb: Bovine Coding Region Single Nucleotide Polymorphisms Located Proximal to Quantitative Trait Loci

  • Moon, Sun-Jin (Laboratory of Bioinformatics and Population Genetics, School of Agricultural Biotechnology, Seoul National University) ;
  • Shin, Hyoung-Doo (Department of Genetic Epidemiology, SNP Genetics Inc.) ;
  • Cheong, Hyun-Sub (Department of Genetic Epidemiology, SNP Genetics Inc.) ;
  • Cho, Hye-Young (Department of Genetic Epidemiology, SNP Genetics Inc.) ;
  • NamGoong, Sohg (Department of Genetic Epidemiology, SNP Genetics Inc.) ;
  • Kim, Eun-Mi (Department of Genetic Epidemiology, SNP Genetics Inc.) ;
  • Han, Chang-Su (Department of Genetic Epidemiology, SNP Genetics Inc.) ;
  • Sung, Sam-Sun (Laboratory of Bioinformatics and Population Genetics, School of Agricultural Biotechnology, Seoul National University) ;
  • Kim, Hee-Bal (Laboratory of Bioinformatics and Population Genetics, School of Agricultural Biotechnology, Seoul National University)
  • Published : 2007.01.31
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Abstract

Bovine coding region single nucleotide polymorphisms located proximal to quantitative trait loci were identified to facilitate bovine QTL fine mapping research. A total of 692,763 bovine SNPs was extracted from 39,432 UniGene clusters, and 53,446 candidate SNPs were found to be a depth >3. In order to validate the in silico SNPs experimentally, 186 animals representing 14 breeds and 100 mixed breeds were analyzed. Genotyping of 40 randomly selected candidate SNPs revealed that 43% of these SNPs ranged in frequency from 0.009 to 0.498. To identify non-synonymous SNPs and to correct for possible frameshift errors in the ESTs at the predicted SNP positions, we designed a program that determines coding regions by protein-sequence referencing, and identified 17,735 nsSNPs. The SNPs and bovine quantitative traits loci informations were integrated into a bovine SNP data: BcSNPdb (http://snugenome.snu.ac.kr/BtcSNP/). Currently there are 43 different kinds of quantitative traits available. Thus, these SNPs would serve as valuable resources for exploiting genomic variation that influence economically and agriculturally important traits in cows.

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