Biology subjects

Clark, E. L.

Publications and source records attributed to Clark, E. L..

3 recordsLinked to original sources

bioRxiv2018

Comprehensive transcriptional profiling of the gastrointestinal tract of ruminants from birth to adulthood reveals strong developmental stage specific gene expression

One of the most significant physiological challenges to neonatal and juvenile ruminants is the development and establishment of the rumen. Using a subset of RNA-Seq data from our high-resolution atlas of gene expression in sheep (Ovis aries) we have provided the first comprehensive characterisation of transcription of the entire the gastrointestinal (GI) tract during the transition from pre-ruminant to ruminant. The dataset comprises 168 tissue samples from sheep at four different time points (birth, one week, 8 weeks and adult). Using network cluster analysis we illustrate how the complexity of the GI tract is reflected in tissue- and developmental stage-specific differences in gene expression. The most significant transcriptional differences between neonatal and adult sheep were observed in the rumen complex. Differences in transcription between neonatal and adult sheep were particularly evident in macrophage specific signatures indicating they might be driving the observed developmental stage-specific differences. Comparative analysis of gene expression in three GI tract tissues from age-matched sheep and goats revealed species-specific differences in genes involved in immunity and metabolism. This study improves our understanding of the transcriptomic mechanisms involved in the transition from pre-ruminant to ruminant. It highlights key genes involved in immunity, microbe recognition, metabolism and cellular differentiation in the GI tract. The results form a basis for future studies linking gene expression with microbial colonisation of the developing GI tract and will contribute towards identifying genes that underlie immunity in early development, which could be utilised to improve ruminant efficiency and productivity.\n\nReference Numbers for Data in the Public RepositoriesThe raw RNA-Sequencing data are deposited in the European Nucleotide Archive (ENA) under study accessions PRJEB19199 (sheep) and PRJEB23196 (goat). Metadata for all samples is deposited in the EBI BioSamples database under group identifiers SAMEG317052 (sheep) and SAMEG330351 (goat).

genomics↗

bioRxiv2018

Assembly and validation of conserved long non-coding RNAs in the ruminant transcriptome

mRNA-like long non-coding RNAs (lncRNA) are a significant component of mammalian transcriptomes, although most are expressed only at low levels, with high tissue-specificity and/or at specific developmental stages. In many cases, therefore, lncRNA detection by RNA-sequencing (RNA-seq) is compromised by stochastic sampling. To account for this and create a catalogue of ruminant lncRNA, we compared de novo assembled lncRNA derived from large RNA-seq datasets in transcriptional atlas projects for sheep and goats with previous lncRNA assembled in cattle and human. Few lncRNA could be reproducibly assembled from a single dataset, even with deep sequencing of the same tissues from multiple animals. Furthermore, there was little sequence overlap between lncRNA assembled from pooled RNA-seq data. We combined positional conservation (synteny) with cross-species mapping of candidate lncRNA to identify a consensus set of ruminant lncRNA and then used the RNA-seq data to demonstrate detectable and reproducible expression in each species. The majority of lncRNA were encoded by single exons, and expressed at < 1 TPM. In sheep, 20-30% of lncRNA had expression profiles significantly correlated with neighbouring protein-coding genes, suggesting association with enhancers. Alongside substantially expanding the ruminant lncRNA repertoire, the outcomes of our analysis demonstrate that stochastic sampling can be partly overcome by combining RNA-seq datasets from related species. This has practical implications for the future discovery of lncRNA in other species.

genomics↗

bioRxiv2017

A High Resolution Atlas Of Gene Expression In The Domestic Sheep (Ovis aries)

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of guilt by association was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.\n\nAuthor SummarySheep are ruminant mammals kept as livestock for the production of meat, milk and wool in agricultural industries across the globe. Genetic and genomic information can be used to improve production traits such as disease resiliance. The sheep genome is however missing important information relating to gene function and many genes, which may be important for productivity, have no informative gene name. This can be remedied using RNA-Sequencing to generate a global expression profile of all protein-coding genes, across multiple organ systems and developmental stages. Clustering genes based on their expression profile across tissues and cells allows us to assign function to those genes. If for example a gene with no informative gene name is expressed in macrophages and is found within a cluster of known macrophage related genes it is likely to be involved in macrophage function and play a role in innate immunity. This information improves the quality of the reference genome and provides insight into biological processes underlying the complex traits that influence the productivity of sheep and other livestock species.

genomics↗