Best linear unbiased prediction (BLUP) has been used to estimate the fixed effects and random effects of complex traits. Traditionally, genomic relationship matrix-based (GRM) and random marker-based BLUP analyses are prevalent to estimate the genetic values of complex traits. We used three methods: GRM-based prediction (G-BLUP), random marker-based prediction using an identity matrix (so-called single-nucleotide polymorphism [SNP]-BLUP), and SNP-SNP variance-covariance matrix (so-called SNP-GBLUP). We used 35, 675 SNPs and R package ""rrBLUP"" for the BLUP analysis. The SNP-SNP relationship matrix was calculated using the GRM and Sherman-Morrison-Woodbury lemma. The SNP-GBLUP result was very similar to G-BLUP in the prediction of genetic values. However, there were many discrepancies between SNP-BLUP and the other two BLUPs. SNP-GBLUP has the merit to be able to predict genetic values through SNP effects.
Copy number variations (CNVs), important genetic factors for study of human diseases, may have as large of an effect on phenotype as do single nucleotide polymorphisms. Indeed, it is widely accepted that CNVs are associated with differential disease susceptibility. However, the relationships between CNVs and gene expression have not been characterized in the horse. In this study, we investigated the effects of copy number deletion in the blood and muscle transcriptomes of Thoroughbred racing horses. We identified a total of 1, 246 CNVs of deletion polymorphisms using DNA re-sequencing data from 18 Thoroughbred racing horses. To discover the tendencies between CNV status and gene expression levels, we extracted CNVs of four Thoroughbred racing horses of which RNA sequencing was available. We found that 252 pairs of CNVs and genes were associated in the four horse samples. We did not observe a clear and consistent relationship between the deletion status of CNVs and gene expression levels before and after exercise in blood and muscle. However, we found some pairs of CNVs and associated genes that indicated relationships with gene expression levels: a positive relationship with genes responsible for membrane structure or cytoskeleton and a negative relationship with genes involved in disease. This study will lead to conceptual advances in understanding the relationship between CNVs and global gene expression in the horse.
Indigenous (native) breeds of livestock have higher disease resistance and adaptation to the environment due to high genetic diversity. Even though their extinction rate is accelerated due to the increase of commercial breeds, natural disaster, and civil war, there is a lack of well-established databases for the native breeds. Thus, we constructed the native pig and chicken breed database (NPCDB) which integrates available information on the breeds from around the world. It is a nonprofit public database aimed to provide information on the genetic resources of indigenous pig and chicken breeds for their conservation. The NPCDB (http://npcdb.snu.ac.kr/) provides the phenotypic information and population size of each breed as well as its specific habitat. In addition, it provides information on the distribution of genetic resources across the country. The database will contribute to understanding of the breed’s characteristics such as disease resistance and adaptation to environmental changes as well as the conservation of indigenous genetic resources.
Pork is a major source of animal protein for humans. The subcutaneous, intermuscular and the intramuscular fat are the factors responsible for meat quality. RNA-seq is rapidly adopted for the profiling of the transcriptomes in the studies related to gene regulation. The discovery of differentially expressed genes (DEGs) between adult animals of Jeju Native Pig (JNP) and Berkshire breeds are of particular interest for the current study. RNA-seq was used to investigate the transcriptome profiling in the fat tissue. Sequence reads were obtained from Ilumina HiSeq2000 and mapped to the pig genome using Tophat2. Total 153 DEGs were identified and 71 among the annotated genes, have BLAST matches in the non- redundant database. Metabolic, immune response and protein binding are enriched pathways in the fat tissue. In our study, biological adhesion, cellular, developmental and multicellular organismal processes in fat were up-regulated in JNP as compare to Berkshire. Multicellular organismal process, developmental process, embryonic morphogenesis and skeletal system development were the most significantly enriched terms in fat of JNP and Berkshire breeds (p = 1.17E?04, 0.044, 3.47E?04 and 4.48E?04 respectively). COL10A1, COL11A2, PDK4 and PNPLA3 genes responsible for skeletal system morphogenesis and body growth were down regulated in JNP. This study is the first statistical analysis for the detection of DEGs from RNA-seq data generated from fat tissue sample. This analysis can be used as stepping stone to understand the difference in the genetic mechanisms that might influence the identification of novel transcripts, sequence polymorphisms, isoforms and noncoding RNAs.
This study considers a problem of genomic selection (GS) for adjacent genetic markers of Yorkshire pigs which are typically correlated. The GS has been widely used to efficiently estimate target variables such as molecular breeding values using markers across the entire genome. Recently, GS has been applied to animals as well as plants, especially to pigs. For efficient selection of variables with specific traits in pig breeding, it is required that any such variable selection retains some properties: i) it produces a simple model by identifying insignificant variables; ii) it improves the accuracy of the prediction of future data; and iii) it is feasible to handle high-dimensional data in which the number of variables is larger than the number of observations. In this paper, we applied several variable selection methods including least absolute shrinkage and selection operator (LASSO), fused LASSO and elastic net to data with 47K single nucleotide polymorphisms and litter size for 519 observed sows. Based on experiments, we observed that the fused LASSO outperforms other approaches.
A Gram-positive bacterium, Staphylococcus aureus is known to be one of the major pathogenic bacteria responsible for causing bovine mastitis. Among the various cell wall components of S. aureus, lipoteichoic acid (LTA) and peptidoglycan (PGN) are closely associated with inflammatory responses. However, the role of LTA and PGN derived from S. aureus in bovine mastitis has not been clearly elucidated. In this study, we characterized the gene expression profile of a bovine mammary gland epithelial cell line, MAC-T cells, in the presence of LTA and PGN from S. aureus. LTA plus PGN, but not LTA or PGN alone, activated MAC-T cells. The analysis of transcriptional profiles using an Affymetrix genechip microarray showed that stimulation with LTA plus PGN produced a total of 2019 (fold change >1.2) differentially expressed genes (DEGs), with 801 up-regulated genes and 1218 down-regulated genes. Of the up-regulated genes, 14 inflammatory mediator-related DEGs, 22 intra-cellular signaling molecule-related DEGs, and 15 transcription factor-related DEGs were observed, whereas among the down-regulated DEGs 17 inflammation-related DEGs were found in MAC-T cells. The microarray results were confirmed using real-time RT-PCR of 18 genes with substantial changes in expression (9 each from the up-regulated and down-regulated DEGs). These results provide a comprehensive analysis of gene-expression profiles elicited by S. aureus LTA and PGN in MAC-T cells, contributing to an understanding of the pathogenesis for S. aureus-induced bovine mastitis.
Gene expression profiling of bovine mammary gland epithelial cells stimulated with lipoteichoic acid plus peptidoglycan from Staphylococcus aureus. Available from: https://www.researchgate.net/publication/262423448_Gene_expression_profiling_of_bovine_mammary_gland_epithelial_cells_stimulated_with_lipoteichoic_acid_plus_peptidoglycan_from_Staphylococcus_aureus [accessed Jan 21, 2016]
Holstein is known to provide higher milk yields than most other cattle breeds, and the dominant position of Holstein today is the result of various selection pressures. Holstein cattle have undergone intensive selection for milk production in recent decades, which has left genome-wide footprints of domestication. To further characterize the bovine genome, we performed whole-genome resequencing analysis of 10 Holstein and 11 Hanwoo cattle to identify regions containing genes as outliers in Holstein, including CSN1S1, CSN2, CSN3, and KIT whose products are likely involved in the yield and proteins of milk and their distinctive black-and-white markings. In addition, genes indicative of positive selection were associated with cardiovascular disease, which is related to simultaneous propagation of genetic defects, also known as inbreeding depression in Holstein.
One of the most important traits for both animal science and livestock production is the number of offspring for a species. This study was performed to identify differentially evolved genes and their distinct functions that influence the number of offspring at birth by comparative analysis of eight monotocous mammals and seven polytocous mammals in a number of scopes: specific amino acid substitution with site-wise adaptive evolution, gene expansion and specific orthologous group. The mutually exclusive amino acid substitution among the 16 mammalian species identified five candidate genes. These genes were both directly and indirectly related to ovulation. Furthermore, in monotocous mammals, the EPH gene family was found to have undergone expansion. Previously, the EPHA4 gene was found to positively affect litter size in pigs and supports the possibility of the EPH gene playing a role in determining the number of offspring per birth. The identified genes in this study offer a basis from which the differences between monotocous and polytocous species can be studied. Furthermore, these genes may harbor some clues to the underlying mechanism, which determines litter size and may prove useful for livestock breeding strategies.
The increasing importance of meat quality has implications for animal breeding programs. Research has revealed much about the genetic background of pigs, and many studies have revealed the importance of various genetic factors. Since meat quality is a complex trait which is affected by many factors, consideration of the overall phenotype is very useful to study meat quality. For integrating the phenotypes, we used principle component analysis (PCA). The significant SNPs refer to results of the GRAMMAR method against PC1, PC2 and PC3 of 14 meat quality traits of 181 Duroc pigs. The Genome-wide association study (GWAS) found 26 potential SNPs affecting various meat quality traits. The loci identified are located in or near 23 genes. The SNPs associated with meat quality are in or near five genes (ANK1, BMP6, SHH, PIP4K2A, and FOXN2) and have been reported previously. Twenty-five of the significant SNPs also located in meat quality-related QTL regions, these result supported the QTL effect indirectly. Each single gene typically affects multiple traits. Therefore, it is a useful approach to use integrated traits for the various traits at the same time. This innovative approach using integrated traits could be applied on other GWAS of complex-traits including meat-quality, and the results will contribute to improving meat-quality of pork.
Copy number variation (CNV), a source of genetic diversity in mammals, has been shown to underlie biological functions related to production traits. Notwithstanding, there have been few studies conducted on CNVs using next generation sequencing at the population level.
Illumina NGS data was obtained for ten Holsteins, a dairy cattle, and 22 Hanwoo, a beef cattle. The sequence data for each of the 32 animals varied from 13.58-fold to almost 20-fold coverage. We detected a total of 6, 811 deleted CNVs across the analyzed individuals (average length =?2732.2 bp) corresponding to 0.74% of the cattle genome (18.6 Mbp of variable sequence). By examining the overlap between CNV deletion regions and genes, we selected 30 genes with the highest deletion scores. These genes were found to be related to the nervous system, more specifically with nervous transmission, neuron motion, and neurogenesis. We regarded these genes as having been effected by the domestication process. Further analysis of the CNV genotyping information revealed 94 putative selected CNVs and 954 breed-specific CNVs.
This study provides useful information for assessing the impact of CNVs on cattle traits using NGS at the population level."