Stature is affected by many polymorphisms of small effect in humans . In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP-seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.

Long non-coding RNA (lncRNA) have been implicated in diverse biological roles including gene regulation and genomic imprinting. Identifying lncRNA in bovine across many differing tissue would contribute to the current repertoire of bovine lncRNA, and help further improve our understanding of the evolutionary importance and constraints of these transcripts. Additionally, it could aid in identifying sites in the genome outside of protein coding genes where mutations could contribute to variation in complex traits. This is particularly important in bovine as genomic predictions are increasingly used in genetic improvement for milk and meat production. Our aim was to identify and annotate novel long non coding RNA transcripts in the bovine genome captured from RNA Sequencing (RNA-Seq) data across 18 tissues, sampled in triplicate from a single cow. To address the main challenge in identifying lncRNA, namely distinguishing lncRNA transcripts from unannotated genes and protein coding genes, a lncRNA identification pipeline with a number of filtering steps was developed. A total of 9,778 transcripts passed the filtering pipeline. The bovine lncRNA catalogue includes MALAT1 and HOTAIR, both of which have been well described in human and mouse genomes. We attempted to validate the lncRNA in libraries from three additional cows. 726 (87.47%) liver and 1,668 (55.27%) blood class 3 lncRNA were validated with stranded liver and blood libraries respectively. Additionally, this study identified a large number of novel unknown transcripts in the bovine genome with high protein coding potential, illustrating a clear need for better annotations of protein coding genes.

Heat stress in dairy cattle leads to reduction in feed intake and milk production as well as the induction of many physiological stress responses. The genes implicated in the response to heat stress in vivo are not well characterised. With the aim of identifying such genes, an experiment was conducted to perform differential gene expression in peripheral white blood cells and milk somatic cells in vivo in 6 Holstein Friesian cows in thermoneutral conditions and in 6 Holstein Friesian cows exposed to a short-term moderate heat challenge. RNA sequences from peripheral white blood cells and milk somatic cells were used to quantify full transcriptome gene expression. Genes commonly differentially expressed (DE) in both the peripheral white blood cells and in milk somatic cells were associated with the cellular stress response, apoptosis, oxidative stress and glucose metabolism. Genes DE in peripheral white blood cells of cows exposed to the heat challenge compared to the thermoneutral control were related to inflammation, lipid metabolism, carbohydrate metabolism and the cardiovascular system. Genes DE in milk somatic cells compared to the thermoneutral control were involved in the response to stress, thermoregulation and vasodilation. These findings provide new insights into the cellular adaptations induced during the response to short term moderate heat stress in dairy cattle and identify potential candidate genes (BDKRB1 and SNORA19) for future research.