Genomic prediction is an effective way to estimate the genomic breeding values from genetic information based on statistical methods such as best linear unbiased prediction (BLUP). The used of haplotype, clusters of linked single nucleotide polymorphism (SNP) as markers instead of individual SNPs can improve the accuracy of genomic prediction. Since the probability of a quantitative trait loci to be in strong linkage disequilibrium (LD) with a cluster of markers is higher compared to an individual marker. To make haplotypes efficient in genomic prediction, finding optimal ways to define haplotypes is essential. In this study, 770K or 50K SNP chip data was collected from Hanwoo (Korean cattle) population consisted of 3,498 cattle. Using SNP chip data, haplotype was defined in three different ways based on 1) the number of SNPs included, 2) length of haplotypes (bp), and 3) agglomerative hierarchical clustering based on LD. To compare the methods in parallel, haplotypes defined by all methods were set to have comparable sizes; 5, 10, 20 or 50 SNPs on average per haplotype. A linear mixed model using haplotype to calculated the covariance matrix was applied for testing the prediction accuracy of each haplotype size. Also, conventional SNP-based linear mixed model was tested to evaluate the performance of the haplotype sets on genomic prediction. Carcass weight (CWT), eye muscle area (EMA) and backfat thickness (BFT) were used as the phenotypes. This study reveals that using haplotypes generally showed increased accuracy compared to conventional SNP-based model for CWT and EMA, but found to be small or no increase in accuracy for BFT. LD clustering-based haplotypes specifically the five SNPs size showed the highest prediction accuracy for CWT and EMA. Meanwhile, the highest accuracy was obtained when length-based haplotypes with five SNPs were used for BFT. The maximum gain in accuracy was 1.3% from cross-validation and 4.6% from forward validation for EMA, suggesting that genomic prediction accuracy can be increased by using haplotypes. However, the improvement from using haplotypes may depend on the trait of interest. In addition, when the number of alleles generated by each haplotype defining methods was compared, clustering by LD generated the least number of alleles, thereby reducing computational costs. Therefore, finding optimal ways to define haplotypes and using the haplotype alleles as markers can improve the accuracy of genomic prediction.

ObjectiveThe aim of this study is to identify single nucleotide polymorphisms (SNPs) and genes related to pig IMF and estimate the heritability of intramuscular fat content (IMF).MethodsGenome-wide association study (GWAS) on 704 inbred Berkshires was performed for IMF. To consider the inbreeding among samples, associations of the SNPs with IMF were tested as random effects in a mixed linear model using the genetic relationship matrix by GEMMA. Significant genes were compared with reported pig IMF quantitative trait loci (QTL) regions and functional classification of the identified genes were also performed. Heritability of IMF was estimated by GCTA tool.ResultsTotal 365 SNPs were found to be significant from a cutoff of p-value <0.01 and the 365 significant SNPs were annotated across 120 genes. Twenty five genes were on pig IMF QTL regions. Bone morphogenetic protein-binding endothelial cell precursor-derived regulator, forkhead box protein O1, ectodysplasin A receptor, ring finger protein 149, cluster of differentiation, tyrosine-protein phosphatase non-receptor type 1, SRY (sex determining region Y)-box 9 (SOX9), MYC proto-oncogene, and macrophage migration inhibitory factor were related to mitogen-activated protein kinase pathway, which regulates the differentiation to adipocytes. These genes and the genes mapped on QTLs could be the candidate genes affecting IMF. Heritability of IMF was estimated as 0.52, which was relatively high, suggesting that a considerable portion of the total variance of IMF is explained by the SNP information.ConclusionOur results can contribute to breeding pigs with better IMF and therefore, producing pork with better sensory qualities.

Background Many short-read genome assemblies have been found to be incomplete and contain mis-assemblies. The Vertebrate Genomes Project has been producing new reference genome assemblies with an emphasis on being as complete and error-free as possible, which requires utilizing long reads, long-range scaffolding data, new assembly algorithms, and manual curation. A more thorough evaluation of the recent references relative to prior assemblies can provide a detailed overview of the types and magnitude of improvements. Results Here we evaluate new vertebrate genome references relative to the previous assemblies for the same species and, in two cases, the same individuals, including a mammal (platypus), two birds (zebra finch, Anna’s hummingbird), and a fish (climbing perch). We find that up to 11% of genomic sequence is entirely missing in the previous assemblies. In the Vertebrate Genomes Project zebra finch assembly, we identify eight new GC- and repeat-rich micro-chromosomes with high gene density. The impact of missing sequences is biased towards GC-rich 5′-proximal promoters and 5′ exon regions of protein-coding genes and long non-coding RNAs. Between 26 and 60% of genes include structural or sequence errors that could lead to misunderstanding of their function when using the previous genome assemblies. Conclusions Our findings reveal novel regulatory landscapes and protein coding sequences that have been greatly underestimated in previous assemblies and are now present in the Vertebrate Genomes Project reference genomes.

Many genome assemblies have been found to be incomplete and contain mis-assemblies. The Vertebrate Genomes Project (VGP) has been producing assemblies with an emphasis on being as complete and error-free as possible, utilizing long reads, long-range scaffolding data, new assembly algorithms, and manual curation. Here we evaluate these new vertebrate genome assemblies relative to the previous references for the same species, including a mammal (platypus), two birds (zebra finch, Anna's hummingbird), and a fish (climbing perch). We found that 3 to 11% of genomic sequence was entirely missing in the previous reference assemblies, which included nearly entire GC-rich and repeat-rich microchromosomes with high gene density. Genome-wide, between 25 to 60% of the genes were either completely or partially missing in the previous assemblies, and this was in part due to a bias in GC-rich 5'-proximal promoters and 5' exon regions. Our findings reveal novel regulatory landscapes and protein coding sequences that have been greatly underestimated in previous assemblies and are now present in the VGP assemblies.

Hanwoo, is the most popular native beef cattle in South Korea. Due to its extensive popularity, research is ongoing to enhance its carcass quality and marbling traits. In this study we conducted a haplotype-based genome-wide association study (GWAS) by constructing haplotype blocks by three methods: number of single nucleotide polymorphisms (SNPs) in a haplotype block (nsnp), length of genomic region in kb (Len) and linkage disequilibrium (LD). Significant haplotype blocks and genes associated with them were identified for carcass traits such as BFT (back fat thickness), EMA (eye Muscle area), CWT (carcass weight) and MS (marbling score). Gene-set enrichment analysis and functional annotation of genes in the significantly-associated loci revealed candidate genes, including PLCB1 and PLCB4 present on BTA13, coding for phospholipases, which might be important candidates for increasing fat deposition due to their role in lipid metabolism and adipogenesis. CEL (carboxyl ester lipase), a bile-salt activated lipase, responsible for lipid catabolic process was also identified within the significantly-associated haplotype block on BTA11. The results were validated in a different Hanwoo population. The genes and pathways identified in this study may serve as good candidates for improving carcass traits in Hanwoo cattle.