한우의 유전체 표지인자 활용 개체 혈연관계 추정
Prediction of Genomic Relationship Matrices using Single Nucleotide Polymorphisms in Hanwoo
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초록
한우의 유전체 전장의 정보를 Illumina BeadArrayTM Bovine SNP50 assay를 이용하여 단일염기다형 현상을 조사한 결과, 유전적 다양성을 보이는 좌위가 약 32,567 좌위 이상에서 다양성을 보이고 있었으며 약 5,554 좌위에서 다양성이 조사되지 않았다. 이는 조사된 자료의 가계집단의 수가 크게 제한되었기 때문에 기인될 수 있으며 또 다른 원인으로는 한우 종축집단의 크기가 작을 수 있다는 현상을 반증한다고 사료된다. 유전분석의 기초가 되는 혈통기록에 의한 개체간 혈연관계를 유전체 정보에 의한 혈연관계와 비교하여 본 결과, 유전체 정보에 의한 혈연관계의 크기가 혈통기록에 의한 혈연관계보다 좀 더 정확하게 추정될 수 있다는 장점이 있으며 혈통기록상의 오류로 그릇된 혈연관계의 크기를 유전체 정보를 통하여 보완할 수 있다는 장점이 있다. 이러한 장점을 활용하면 유전체정보를 이용한 유전능력 평가의 정확성을 크게 향상시킬 수 있을 것으로 사료되었다.
Abstract
The emergence of next-generation sequencing technologies has lead to application of new computational and statistical methodologies that allow incorporating genetic information from entire genomes of many individuals composing the population. For example, using single-nucleotide polymorphisms(SNP) obtained from whole genome amplification platforms such as the Ilummina BovineSNP50 chip, many researchers are actively engaged in the genetic evaluation of cattle livestock using whole genome relationship analyses. In this study, we estimated the genomic relationship matrix(GRM) and compared it with one computed using a pedigree relationship matrix(PRM) using a population of Hanwoo. This project is a preliminary study that will eventually include future work on genomic selection and prediction. Data used in this study were obtained from 187 blood samples consisting of the progeny of 20 young bulls collected after parentage testing from the Hanwoo improvement center, National Agriculture Cooperative Federation as well as 103 blood samples from the progeny of 12 proven bulls collected from farms around the Kyong-buk area in South Korea. The data set was divided into two cases for analysis. In the first case missing genotypes were included. In the second case missing genotypes were excluded. The effect of missing genotypes on the accuracy of genomic relationship estimation was investigated. Estimation of relationships using genomic information was also carried out chromosome by chromosome for whole genomic SNP markers based on the regression method using allele frequencies across loci. The average correlation coefficient and standard deviation between relationships using pedigree information and chromosomal genomic information using data which was verified using a parentage test andeliminated missing genotypes was 0.81±0.04 and their correlation coefficient when using whole genomic information was 0.98, which was higher. Variation in relationships between non-inbred half sibs was 0.22±0.17 on chromosomal and 0.22±0.04 on whole genomic SNP markers. The variations were larger and unusual values were observed when non-parentage test data were included. So, relationship matrix by genomic information can be useful for genetic evaluation of animal breeding.
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