Association of plasma microRNA expression with age, genetic background and functional traits in dairy cattle

Abstract A number of blood circulating microRNAs (miRNAs) are proven disease biomarkers and have been associated with ageing and longevity in multiple species. However, the role of circulating miRNAs in livestock species has not been fully studied. We hypothesise that plasma miRNA expression profiles are affected by age and genetic background, and associated with health and production traits in dairy cattle. Using PCR arrays, we assessed 306 plasma miRNAs for effects of age (calves vs mature cows) and genetic background (control vs select lines) in 18 animals. We identified miRNAs which were significantly affected by age (26 miRNAs) and genetic line (5 miRNAs). Using RT-qPCR in a larger cow population (n = 73) we successfully validated array data for 12 age-related miRNAs, one genetic line-related miRNA, and utilised expression data to associate their levels in circulation with functional traits in these animals. Plasma miRNA levels were associated with telomere length (ageing/longevity indicator), milk production and composition, milk somatic cell count (mastitis indicator), fertility, lameness, and blood metabolites linked with body energy balance and metabolic stress. In conclusion, circulating miRNAs could provide useful selection markers for dairy cows to help improve health, welfare and production performance

High-throughput profiling of caenorhabditis elegans starvation-responsive microRNAs

MicroRNAs (miRNAs) are non-coding RNAs of ~22 nucleotides in length that regulate gene expression by interfering with the stability and translation of mRNAs. Their expression is regulated during development, under a wide variety of stress conditions and in several pathological processes. In nature, animals often face feast or famine conditions. We observed that subjecting early L4 larvae from Caenorhabditis elegans to a 12-hr starvation period produced worms that are thinner and shorter than well-fed animals, with a decreased lipid accumulation, diminished progeny, reduced gonad size, and an increased lifespan. Our objective was to identify which of the 302 known miRNAs of C. elegans changed their expression under starvation conditions as compared to well-fed worms by means of deep sequencing in early L4 larvae. Our results indicate that 13 miRNAs (miR-34-3p, the family of miR-35-3p to miR-41-3p, miR-39-5p, miR-41-5p, miR-240-5p, miR-246-3p and miR-4813-5p) were upregulated, while 2 miRNAs (let-7-3p and miR-85-5p) were downregulated in 12-hr starved vs. well-fed early L4 larvae. Some of the predicted targets of the miRNAs that changed their expression in starvation conditions are involved in metabolic or developmental process. In particular, miRNAs of the miR-35 family were upregulated 6-20 fold upon starvation. Additionally, we showed that the expression of gld-1, important in oogenesis, a validated target of miR-35-3p, was downregulated when the expression of miR-35-3p was upregulated. The expression of another reported target, the cell cycle regulator lin-23, was unchanged during starvation. This study represents a starting point for a more comprehensive understanding of the role of miRNAs during starvation in C. elegans

Modelling the molecular mechanisms of ageing

This document is the Accepted Manuscript version of a published work that appeared in final form in Bioscience reports. To access the final edited and published work see http://www.bioscirep.org/content/37/1/BSR20160177.The ageing process is driven at the cellular level by random molecular damage which slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the ageing process. The complexity of the ageing process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards, and discusses many specific examples of models which have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field