High ambient temperature has multiple potential effects on the organism such as hyperthermia, endotoxemia, and/or systemic inflammation. However, it is often difficult to discriminate between cause and consequence of phenotypic effects, such as the indirect influence of heat stress via reduced food intake. Lactating dairy cows are a particularly sensitive model to examine the effects of heat stress due to their intensive metabolic heat production and small surface:volume ratio. Results from this model show heat stress directly induced a so-far unknown infiltration of yet uncategorized cells into the mucosa and submucosa of the jejunum. Due to a pair-feeding design, we can exclude this effect being a consequence of the concurrent heat-induced reduction in feed intake. Isolation and characterization of the infiltrating cells using laser capture microdissection and RNA sequencing indicated a myeloic origin and macrophage-like phenotype. Furthermore, targeted transcriptome analyses provided evidence of activated immune- and phagocytosis-related pathways with LPS and cytokines as upstream regulators directly associated with heat stress. Finally, we obtained indication that heat stress may directly alter jejunal tight junction proteins suggesting an impaired intestinal barrier. The penetration of toxic and bacterial compounds during heat stress may have triggered a modulated immune repertoire and induced an antioxidative defense mechanism to maintain homeostasis between commensal bacteria and the jejunal immune system. Our bovine model indicates direct effects of heat stress on the jejunum of mammals already at moderately elevated ambient temperature. These results need to be considered when developing concepts to combat the negative consequences of heat stress.
The study of selection signatures helps to find genomic regions that have been under selective pressure and might host genes or variants that modulate important phenotypes. Such knowledge improves our understanding of how breeding programmes have shaped the genomes of livestock. In this study, 942 stallions were included from four, exemplarily chosen, German warmblood breeds with divergent historical and recent selection focus and different crossbreeding policies: Trakehner (N = 44), Holsteiner (N = 358), Hanoverian (N = 319) and Oldenburger (N = 221). Those breeds are nowadays bred for athletic performance and aptitude for show-jumping, dressage or eventing, with a particular focus of Holsteiner on the first discipline. Blood samples were collected during the health exams of the stallion preselections before licensing and were genotyped with the Illumina EquineSNP50 BeadChip. Autosomal markers were used for a multi-method search for signals of positive selection. Analyses within and across breeds were conducted by using the integrated Haplotype Score (iHS), cross-population Extended Haplotype Homozygosity (xpEHH) and Runs of Homozygosity (ROH). Oldenburger and Hanoverian showed very similar iHS signatures, but breed specificities were detected on multiple chromosomes with the xpEHH. The Trakehner clustered as a distinct group in a principal component analysis and also showed the highest number of ROHs, which reflects their historical bottleneck. Beside breed specific differences, we found shared selection signals in an across breed iHS analysis on chromosomes 1, 4 and 7. After investigation of these iHS signals and shared ROH for potential functional candidate genes and affected pathways including enrichment analyses, we suggest that genes affecting muscle functionality ( TPM1 , TMOD2-3 , MYO5A , MYO5C ), energy metabolism and growth ( AEBP1 , RALGAPA2 , IGFBP1 , IGFBP3-4 ), embryonic development ( HOXB -complex) and fertility ( THEGL , ZPBP1-2 , TEX14 , ZP1 , SUN3 and CFAP61 ) have been targeted by selection in all breeds. Our findings also indicate selection pressure on KITLG , which is well-documented for influencing pigmentation.
Background: Genomic regions associated with divergent livestock feed efficiency have been found predominantly outside protein coding sequences. Long non-coding RNAs (lncRNA) can modulate chromatin accessibility, gene expression and act as important metabolic regulators in mammals. By integrating phenotypic, transcriptomic, and metabolomic data with quantitative trait locus data in prioritizing co-expression network analyses, we aimed to identify and functionally characterize lncRNAs with a potential key regulatory role in metabolic efficiency in cattle.Materials and Methods: Crossbred animals (n = 48) of a Charolais x Holstein F2-population were allocated to groups of high or low metabolic efficiency based on residual feed intake in bulls, energy corrected milk in cows and intramuscular fat content in both genders. Tissue samples from jejunum, liver, skeletal muscle and rumen were subjected to global transcriptomic analysis via stranded total RNA sequencing (RNAseq) and blood plasma samples were used for profiling of 640 metabolites. To identify lncRNAs within the indicated tissues, a project-specific transcriptome annotation was established. Subsequently, novel transcripts were categorized for potential lncRNA status, yielding a total of 7,646 predicted lncRNA transcripts belonging to 3,287 loci. A regulatory impact factor approach highlighted 92, 55, 35, and 73 lncRNAs in jejunum, liver, muscle, and rumen, respectively. Their ensuing high regulatory impact factor scores indicated a potential regulatory key function in a gene set comprising loci displaying differential expression, tissue specificity and loci overlapping with quantitative trait locus regions for residual feed intake or milk production. These were subjected to a partial correlation and information theory analysis with the prioritized gene set.Results and Conclusions: Independent, significant and group-specific correlations (|r| > 0.8) were used to build a network for the high and the low metabolic efficiency group resulting in 1,522 and 1,732 nodes, respectively. Eight lncRNAs displayed a particularly high connectivity (>100 nodes). Metabolites and genes from the partial correlation and information theory networks, which each correlated significantly with the respective lncRNA, were included in an enrichment analysis indicating distinct affected pathways for the eight lncRNAs. LncRNAs associated with metabolic efficiency were classified to be functionally involved in hepatic amino acid metabolism and protein synthesis and in calcium signaling and neuronal nitric oxide synthase signaling in skeletal muscle cells.
Long non-coding RNAs (lncRNAs) can influence transcriptional and translational processes in mammalian cells and are associated with various developmental, physiological and phenotypic conditions. However, they remain poorly understood and annotated in livestock species. We combined phenotypic, metabolomics and liver transcriptomic data of bulls divergent for residual feed intake (RFI) and fat accretion. Based on a project-specific transcriptome annotation for the bovine reference genome ARS-UCD.1.2 and multiple-tissue total RNA sequencing data, we predicted 3590 loci to be lncRNAs. To identify lncRNAs with potential regulatory influence on phenotype and gene expression, we applied the regulatory impact factor algorithm on a functionally prioritized set of loci (n = 4666). Applying the algorithm of partial correlation and information theory, significant and independent pairwise correlations were calculated and co-expression networks were established, including plasma metabolites correlated with lncRNAs. The network hub lncRNAs were assessed for potential cis-actions and subjected to biological pathway enrichment analyses. Our results reveal a prevalence of antisense lncRNAs positively correlated with adjacent protein-coding genes and suggest their participation in mitochondrial function, acute phase response signalling, TCA-cycle, fatty acid β-oxidation and presumably gluconeogenesis. These antisense lncRNAs indicate a stabilizing function for their cis-correlated genes and a putative regulatory role in gene expression.
Reliability of genomic predictions is influenced by the size and genetic composition of the reference population. For German Warmblood horses, compilation of a reference population has been enabled through the cooperation of five German breeding associations. In this study, preliminary data from this joint reference population were used to genetically and genomically characterize withers height and to apply single-step methodology for estimating genomic breeding values for withers height. Using data on 2113 mares and their genomic information considering about 62,000 single nucleotide polymorphisms (SNPs), analysis of the genomic relationship revealed substructures reflecting breed origin and different breeding goals of the contributing breeding associations. A genome-wide association study confirmed a known quantitative trait locus (QTL) for withers height on equine chromosome (ECA) 3 close to LCORL and identified a further significant peak on ECA 1. Using a single-step approach with a combined relationship matrix, the estimated heritability for withers height was 0.31 (SE = 0.08) and the corresponding genomic breeding values ranged from − 2.94 to 2.96 cm. A mean reliability of 0.38 was realized for these breeding values. The analyses of withers height showed that compiling a reference population across breeds is a suitable strategy for German Warmblood horses. The single-step method is an appealing approach for practical genomic prediction in horses, because not many genotypes are available yet and animals without genotypes can by this way directly contribute to the estimation system.
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