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Genome-Wide Identification of Discriminative Genetic Variations in Beef and Dairy Cattle via an Information-Theoretic Approach

by Soo-Jin Kim 1, Jung-Woo Ha 2 and Heebal Kim 1,3,4,*
1
Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea
2
Clova AI Research, NAVER Corp., Seongnam 13561, Korea
3
Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea
4
C&K Genomics, Seoul 05836, Korea
*
Author to whom correspondence should be addressed.
Genes 2020, 11(6), 678; https://doi.org/10.3390/genes11060678
Received: 26 May 2020 / Revised: 19 June 2020 / Accepted: 19 June 2020 / Published: 22 June 2020
(This article belongs to the Section Animal Genetics and Genomics)
Analyzing the associations between genotypic changes and phenotypic traits on a genome-wide scale can contribute to understanding the functional roles of distinct genetic variations during breed development. We performed a whole-genome analysis of Angus and Jersey cattle breeds using conditional mutual information, which is an information-theoretic method estimating the conditional independency among multiple factor variables. The proposed conditional mutual information-based approach allows breed-discriminative genetic variations to be explicitly identified from tens of millions of SNP (single nucleotide polymorphism) positions on a genome-wide scale while minimizing the usage of prior knowledge. Using this data-driven approach, we identified biologically relevant functional genes, including breed-specific variants for cattle traits such as beef and dairy production. The identified lipid-related genes were shown to be significantly associated with lipid and triglyceride metabolism, fat cell differentiation, and muscle development. In addition, we confirmed that milk-related genes are involved in mammary gland development, lactation, and mastitis-associated processes. Our results provide the distinct properties of Angus and Jersey cattle at a genome-wide level. Moreover, this study offers important insights into discovering unrevealed genetic variants for breed-specific traits and the identification of genetic signatures of diverse cattle breeds with respect to target breed-specific properties. View Full-Text
Keywords: cattle genome-wide analysis; conditional mutual information; Angus and Jersey cattle; genetic variations; single nucleotide polymorphisms cattle genome-wide analysis; conditional mutual information; Angus and Jersey cattle; genetic variations; single nucleotide polymorphisms
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    Description: Figure S1: Projection of 20 Angus and Jersey individuals plotted on the top two principal components, Figure S2: Ratio of the identified SNPs to all the SNPs on each chromosome and the number of genes including the identified SNPs, Figure S3: Distributions of the ratio of the identified SNPs on each chromosome, Figure S4: Distribution of 858 SNPs for heterozygosity in the identified lipid/intramuscular fat-related genes in Angus versus Jersey cattle, Figure S5: Distribution of 852 SNPs for heterozygosity in the identified milk production-related genes in Angus versus Jersey cattle, Figure S6: 33 SNPs on the mitochondrial genome plotted with negative log-scaled p-values, Figure S7: Significant GO terms for ND1, ND2 and COX1 on the mitochondrial genome, Figure S8: Genotype profiles for each SNP locus on the mitochondrial genome of Angus and Jersey breeds, Table S1: Summary of sequencing data, Table S2: Chromosomal distributions of the number of SNPs, Table S3: Chromosomal distributions of the number of SNPs identified by CMI, Table S4: The 75 identified lipid/intramuscular fat-related genes and the number of identified SNPs, Table S5: The 90 identified mammary gland/milk production-related genes and the number of identified SNPs, Table S6: Significant GO terms in the 75 identified lipid/intramuscular fat-related genes, Table S7: Significant GO terms in the 90 identified mammary gland/milk production-related genes, Table S8: Summary of XP-CLR, Table S9: Summary of XP-EHH, Table S10: 40 genes in the intersection of XP-CLR, XP-EHH and conditional mutual information for Angus, Table S11: 55 genes in the intersection of XP-CLR, XP-EHH and conditional mutual information for Jersey.
MDPI and ACS Style

Kim, S.-J.; Ha, J.-W.; Kim, H. Genome-Wide Identification of Discriminative Genetic Variations in Beef and Dairy Cattle via an Information-Theoretic Approach. Genes 2020, 11, 678.

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