The reconstruction of transcriptional regulatory networks (TRNs) is a long-standing challenge in human genetics. Numerous computational methods have been developed to infer regulatory interactions between human transcriptional factors (TFs) and target genes from high-throughput data, and their performance evaluation requires gold-standard interactions. Here we present a database of literature-curated human TF-target interactions, TRRUST (transcriptional regulatory relationships unravelled by sentence-based text-mining, http://www.grnpedia.org/trrust), which currently contains 8,015 interactions between 748 TF genes and 1,975 non-TF genes. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 20 million Medline abstracts. To the best of our knowledge, TRRUST is the largest publicly available database of literature-curated human TF-target interactions to date. TRRUST also has several useful features: i) information about the mode-of-regulation; ii) tests for target modularity of a query TF; iii) tests for TF cooperativity of a query target; iv) inferences about cooperating TFs of a query TF; and v) prioritizing associated pathways and diseases with a query TF. We observed high enrichment of TF-target pairs in TRRUST for top-scored interactions inferred from high-throughput data, which suggests that TRRUST provides a reliable benchmark for the computational reconstruction of human TRNs.

The importance of probiotics in swine production is widely acknowledged as crucial. However, gaps still remain in the exact roles played by probiotics in modulation of gut microbiota and immune response. This study determined the roles of probiotic Lactobacillus plantarum strain JDFM LP11in gut microbiota modulation and immune response in weaned piglets. L. plantarum JDFM LP11 increased the population of lactic acid bacteria in feces and enhanced the development of villi in the small intestine. Metagenome analysis showed that microbial diversity and richness (Simpson, Shannon, ACE, Chao1) and the relative abundance of the Firmicutes were higher in weaned piglets fed probiotics. Five bacterial families were different in the relative abundance, especially; Prevotellaceae occupied the largest part of microbial community showed the most difference between two groups. Transcriptome analysis identified 25 differentially expressed genes using RNAsequencing data of the ileum. Further gene ontology and immune DB analysis determined 8 genes associated with innate defense response and cytokine production. BPI, RSAD2, SLPI, LUM, OLFM4, DMBT1 and C6 genes were down-regulated by probiotic supplementation except PLA2G2A. PICRUSt analysis predicting functional profiling of microbial communities indicated branched amino acid biosynthesis and butyrate metabolism promoting gut development and health were increased by probiotics. Altogether, our data suggest that L. plantarum JDFM LP11 increases the diversity and richness in the microbial community, and attenuates the ileal immune gene expression towards gut inflammation, promoting intestinal development in weaned piglets.

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BackgroundCopy 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.ResultsIllumina 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.ConclusionsThis study provides useful information for assessing the impact of CNVs on cattle traits using NGS at the population level.

Since being domesticated about 10,000–12,000 years ago, domestic pigs (Sus scrofa domesticus) have been selected for traits of economic importance, in particular large body size. However, Yucatan miniature pigs have been selected for small body size to withstand high temperature environment and for laboratory use. This renders the Yucatan miniature pig a valuable model for understanding the evolution of body size. We investigate the genetic signature for selection of body size in the Yucatan miniature pig. Phylogenetic distance of Yucatan miniature pig was compared to other large swine breeds (Yorkshire, Landrace, Duroc and wild boar). By estimating the XP-EHH statistic using re-sequencing data derived from 70 pigs, we were able to unravel the signatures of selection of body size. We found that both selections at the level of organism, and at the cellular level have occurred. Selection at the higher levels include feed intake, regulation of body weight and increase in mass while selection at the molecular level includes cell cycle and cell proliferation. Positively selected genes probed by XP-EHH may provide insight into the docile character and innate immunity as well as body size of Yucatan miniature pig.

The objective of this study was to determine the physicochemical and sensory properties of cooked emulsion sausages containing different levels of lotus rhizome powder (0, 1, 2, and 3%, based on total weight). Lotus rhizome powder had no significant (p>0.05) impact on pH, moisture, protein, or ash content of sausage. However, fat content was slightly but significantly (p<0.05) decreased when the level of lotus rhizome powder was increased in the sausages. The addition of lotus rhizome powder to sausages at over 1% resulted in significantly (p<0.05) darker and less red color of cooked sausage compared to control. Increase in lotus rhizome level slightly improved the emulsion stability and apparent viscosity. Significant (p<0.05) reduction in cooking loss was observed when more than 1% of lotus rhizome powder was added to sausages. The textural properties of sausages were unaffected by the inclusion of lotus rhizome except for springiness and chewiness. On the manufacture day, control sausage had significantly (p<0.05) higher TBARS value than treatments. Regarding sensory characteristics, increased levels of lotus rhizome powder decreased (p<0.05) color and juiciness scores. However, cooked sausages exhibited similar overall acceptability regardless of the level of lotus rhizome powder added to sausages. Therefore, lotus rhizome powder, an antioxidant dietary fiber, could be used as an effective natural ingredient in meat products for the development of healthier and functional food.

Background In this study, we assessed the accuracy of genomic prediction for carcass weight (CWT), marbling score (MS), eye muscle area (EMA) and back fat thickness (BFT) in Hanwoo cattle when using genomic best linear unbiased prediction (GBLUP), weighted GBLUP (wGBLUP), and a BayesR model. For these models, we investigated the potential gain from using pre-selected single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on imputed sequence data and from gene expression information. We used data on 13,717 animals with carcass phenotypes and imputed sequence genotypes that were split in an independent GWAS discovery set of varying size and a remaining set for validation of prediction. Expression data were used from a Hanwoo gene expression experiment based on 45 animals. Results Using a larger number of animals in the reference set increased the accuracy of genomic prediction whereas a larger independent GWAS discovery dataset improved identification of predictive SNPs. Using pre-selected SNPs from GWAS in GBLUP improved accuracy of prediction by 0.02 for EMA and up to 0.05 for BFT, CWT, and MS, compared to a 50 k standard SNP array that gave accuracies of 0.50, 0.47, 0.58, and 0.47, respectively. Accuracy of prediction of BFT and CWT increased when BayesR was applied with the 50 k SNP array (0.02 and 0.03, respectively) and was further improved by combining the 50 k array with the top-SNPs (0.06 and 0.04, respectively). By contrast, using BayesR resulted in limited improvement for EMA and MS. wGBLUP did not improve accuracy but increased prediction bias. Based on the RNA-seq experiment, we identified informative expression quantitative trait loci, which, when used in GBLUP, improved the accuracy of prediction slightly, i.e. between 0.01 and 0.02. SNPs that were located in genes, the expression of which was associated with differences in trait phenotype, did not contribute to a higher prediction accuracy. Conclusions Our results show that, in Hanwoo beef cattle, when SNPs are pre-selected from GWAS on imputed sequence data, the accuracy of prediction improves only slightly whereas the contribution of SNPs that are selected based on gene expression is not significant. The benefit of statistical models to prioritize selected SNPs for estimating genomic breeding values is trait-specific and depends on the genetic architecture of each trait.

Linkage disequilibrium between markers or genetic variants underlying interesting traits affects many genomic methodologies. In many genomic methodologies, the effective population size (Ne) is important to assess the genetic diversity of animal populations. In this study, dairy cattle were genotyped using the Illumina BovineHD Genotyping BeadChips for over 777,000 SNPs located across all autosomes, mitochondria and sex chromosomes, and 70,000 autosomal SNPs were selected randomly for the final analysis. We characterized more accurate linkage disequilibrium in a sample of 96 dairy cattle producing milk in Korea. Estimated linkage disequilibrium was relatively high between closely linked markers (>0.6 at 10 kb) and decreased with increasing distance. Using formulae that related the expected linkage disequilibrium to Ne, and assuming a constant actual population size, Ne was estimated to be approximately 122 in this population. Historical Ne, calculated assuming linear population growth, was suggestive of a rapid increase Ne over the past 10 generations, and increased slowly thereafter. Additionally, we corrected the genomic relationship structure per chromosome in calculating r2 and estimated Ne. The observed Ne based on r2 corrected by genomics relationship structure can be rationalized using current knowledge of the history of the dairy cattle breeds producing milk in Korea.