Dataset Information

Effective Population Size and Signatures of Selection Using Bovine 50K SNP Chips in Korean Native Cattle (Hanwoo).

ABSTRACT: Inferring the effective population size and the pattern of selection signatures is of interest both from an evolutionary perspective and to improve models for mapping of quantitative trait genes. We used DNA samples of 61 sires and 486 progeny of the Hanwoo, genotyped by the Illumina Bovine SNP50 BeadChip, to analyze the genetic structure. Our study showed a persistent decline in effective population size throughout the period considered, but suggested a marked decline at one distinctive time point (100th generation) and two sharp decline intervals (50th-25th generation and 25th-10th generation). This pattern can be explained by Hanwoo formation and the modern breeding program. Our results revealed 95 regions exhibiting the footprint of recent positive selection at a threshold level of 0.01. We found an overlap of the 11 core regions presenting top P-values and those that had previously been identified as harboring quantitative trait loci from other breeds. The information generated from this study can be used to better understand the mechanism of selection in Hanwoo breeding, and provide important implications for the design and application of association studies in the Hanwoo population.

SUBMITTER: Li Y

PROVIDER: S-EPMC4498654 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Effective Population Size and Signatures of Selection Using Bovine 50K SNP Chips in Korean Native Cattle (Hanwoo).

Li Yi Y Kim Jong-Joo JJ

Evolutionary bioinformatics online 20150708

Inferring the effective population size and the pattern of selection signatures is of interest both from an evolutionary perspective and to improve models for mapping of quantitative trait genes. We used DNA samples of 61 sires and 486 progeny of the Hanwoo, genotyped by the Illumina Bovine SNP50 BeadChip, to analyze the genetic structure. Our study showed a persistent decline in effective population size throughout the period considered, but suggested a marked decline at one distinctive time po ...[more]

PMID: 26244003

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Project description:Hanwoo cattle are a Korean breed renowned for their cultural significance and high-quality beef, characterized by low cholesterol and high unsaturated fat ratio. Growth is divided into a growing phase focused on development and a fattening phase for marbling. Proper feed management, considering genetic and environmental factors, is vital for maximizing growth potential. The rumen plays a crucial role in digestion and gene expression regulation, with rumen fermentation being central to nutrient absorption and cattle health. In this study, we conduct transcriptome analysis of the rumen at eight timepoints. Our goal is to identify genetic factors that influence the growth of Hanwoo steers to enhance our understanding of the rumen’s functions and roles during their growth. In this RNA-sequencing analysis of Hanwoo steer rumen, differential gene expression was examined over eight timepoints, highlighting significant genetic changes, particularly between 12 and 26 months. Weighted gene co-expression network analysis identified and organized as three modules: turquoise, blue, and yellow. The turquoise module, linked to immune response, showed down-regulation in genes at 30 months. The blue module, associated with steroid metabolism, was notably up-regulated at 26 months. The yellow module’s genes showed a consistent increase in expression with growth. These modules and their functional annotations provide a deeper understanding of the biological processes during Hanwoo growth, highlighting the intricate relationship between gene expression and cattle development. The growth stages of Hanwoo steers were explored in our investigation utilizing rumen transcriptome data. The rumen plays critical role in their development, particularly during the growing and fattening phases. Proper feed management, considering the rumen’s function, is essential for optimal growth. Transcriptome analysis helps identify genes associated with growth and provides insights for cattle breeding and management practices. Understanding the complex connection between gene expression and Hanwoo development is essential for maximizing productivity and health.

Project description:Whole-genome sequence (WGS) data are increasingly being applied into genomic predictions, offering a higher predictive ability by including causal mutations or single-nucleotide polymorphisms (SNPs) putatively in strong linkage disequilibrium with causal mutations affecting the trait. This study aimed to improve the predictive performance of the customized Hanwoo 50 k SNP panel for four carcass traits in commercial Hanwoo population by adding highly predictive variants from sequence data. A total of 16,892 Hanwoo cattle with phenotypes (i.e., backfat thickness, carcass weight, longissimus muscle area, and marbling score), 50 k genotypes, and WGS imputed genotypes were used. We partitioned imputed WGS data according to functional annotation [intergenic (IGR), intron (ITR), regulatory (REG), synonymous (SYN), and non-synonymous (NSY)] to characterize the genomic regions that will deliver higher predictive power for the traits investigated. Animals were assigned into two groups, the discovery set (7324 animals) used for predictive variant detection and the cross-validation set for genomic prediction. Genome-wide association studies were performed by trait to every genomic region and entire WGS data for the pre-selection of variants. Each set of pre-selected SNPs with different density (1000, 3000, 5000, or 10,000) were added to the 50 k genotypes separately and the predictive performance of each set of genotypes was assessed using the genomic best linear unbiased prediction (GBLUP). Results showed that the predictive performance of the customized Hanwoo 50 k SNP panel can be improved by the addition of pre-selected variants from the WGS data, particularly 3000 variants from each trait, which is then sufficient to improve the prediction accuracy for all traits. When 12,000 pre-selected variants (3000 variants from each trait) were added to the 50 k genotypes, the prediction accuracies increased by 9.9, 9.2, 6.4, and 4.7% for backfat thickness, carcass weight, longissimus muscle area, and marbling score compared to the regular 50 k SNP panel, respectively. In terms of prediction bias, regression coefficients for all sets of genotypes in all traits were close to 1, indicating an unbiased prediction. The strategy used to select variants based on functional annotation did not show a clear advantage compared to using whole-genome. Nonetheless, such pre-selected SNPs from the IGR region gave the highest improvement in prediction accuracy among genomic regions and the values were close to those obtained using the WGS data for all traits. We concluded that additional gain in prediction accuracy when using pre-selected variants appears to be trait-dependent, and using WGS data remained more accurate compared to using a specific genomic region.

Dataset Information

Effective Population Size and Signatures of Selection Using Bovine 50K SNP Chips in Korean Native Cattle (Hanwoo).

Publications

Effective Population Size and Signatures of Selection Using Bovine 50K SNP Chips in Korean Native Cattle (Hanwoo).

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