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.

Cross-species inference of long non-coding RNAs greatly expands the ruminant transcriptome.

BACKGROUND: mRNA-like long non-coding RNAs (lncRNAs) 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. Thus, in many cases lncRNA detection by RNA-sequencing (RNA-seq) is compromised by stochastic sampling. To account for this and create a catalogue of ruminant lncRNAs, we compared de novo assembled lncRNAs derived from large RNA-seq datasets in transcriptional atlas projects for sheep and goats with previous lncRNAs assembled in cattle and human. We then combined the novel lncRNAs with the sheep transcriptional atlas to identify co-regulated sets of protein-coding and non-coding loci. RESULTS: Few lncRNAs 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 lncRNAs that were assembled from pooled RNA-seq data. We combined positional conservation (synteny) with cross-species mapping of candidate lncRNAs to identify a consensus set of ruminant lncRNAs and then used the RNA-seq data to demonstrate detectable and reproducible expression in each species. In sheep, 20 to 30% of lncRNAs were located close to protein-coding genes with which they are strongly co-expressed, which is consistent with the evolutionary origin of some ncRNAs in enhancer sequences. Nevertheless, most of the lncRNAs are not co-expressed with neighbouring protein-coding genes. CONCLUSIONS: 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 lncRNAs in other species.

Integration of quantitated expression estimates from polyA-selected and rRNA-depleted RNA-seq libraries.

BACKGROUND: The availability of fast alignment-free algorithms has greatly reduced the computational burden of RNA-seq processing, especially for relatively poorly assembled genomes. Using these approaches, previous RNA-seq datasets could potentially be processed and integrated with newly sequenced libraries. Confounding factors in such integration include sequencing depth and methods of RNA extraction and selection. Different selection methods (typically, either polyA-selection or rRNA-depletion) omit different RNAs, resulting in different fractions of the transcriptome being sequenced. In particular, rRNA-depleted libraries sample a broader fraction of the transcriptome than polyA-selected libraries. This study aimed to develop a systematic means of accounting for library type that allows data from these two methods to be compared. RESULTS: The method was developed by comparing two RNA-seq datasets from ovine macrophages, identical except for RNA selection method. Gene-level expression estimates were obtained using a two-part process centred on the high-speed transcript quantification tool Kallisto. Firstly, a set of reference transcripts was defined that constitute a standardised RNA space, with expression from both datasets quantified against it. Secondly, a simple ratio-based correction was applied to the rRNA-depleted estimates. The outcome is an almost perfect correlation between gene expression estimates, independent of library type and across the full range of levels of expression. CONCLUSION: A combination of reference transcriptome filtering and a ratio-based correction can create equivalent expression profiles from both polyA-selected and rRNA-depleted libraries. This approach will allow meta-analysis and integration of existing RNA-seq data into transcriptional atlas projects.

Species-Specificity of Transcriptional Regulation and the Response to Lipopolysaccharide in Mammalian Macrophages.

Mammalian macrophages differ in their basal gene expression profiles and response to the toll-like receptor 4 (TLR4) agonist, lipopolysaccharide (LPS). In human macrophages, LPS elicits a temporal cascade of transient gene expression including feed forward activators and feedback regulators that limit the response. Here we present a transcriptional network analysis of the response of sheep bone marrow-derived macrophages (BMDM) to LPS based upon RNA-seq at 0, 2, 4, 7, and 24 h post-stimulation. The analysis reveals a conserved transcription factor network with humans, and rapid induction of feedback regulators that constrain the response at every level. The gene expression profiles of sheep BMDM at 0 and 7 h post LPS addition were compared to similar data obtained from goat, cow, water buffalo, horse, pig, mouse and rat BMDM. This comparison was based upon identification of 8,200 genes annotated in all species and detected at >10TPM in at least one sample. Analysis of expression of transcription factors revealed a conserved transcriptional millieu associated with macrophage differentiation and LPS response. The largest co-expression clusters, including genes encoding cell surface receptors, endosome-lysosome components and secretory activity, were also expressed in all species and the combined dataset defines a macrophage functional transcriptome. All of the large animals differed from rodents in lacking inducible expression of genes involved in arginine metabolism and nitric oxide production. Instead, they expressed inducible transporters and enzymes of tryptophan and kynurenine metabolism. BMDM from all species expressed high levels of transcripts encoding transporters and enzymes involved in glutamine metabolism suggesting that glutamine is a major metabolic fuel. We identify and discuss transcripts that were uniquely expressed or regulated in rodents compared to large animals including ACOD1, CXC and CC chemokines, CD163, CLEC4E, CPM, CSF1, CSF2, CTSK, MARCO, MMP9, SLC2A3, SLC7A7, and SUCNR1. Conversely, the data confirm the conserved regulation of multiple transcripts for which there is limited functional data from mouse models and knockouts. The data provide a resource for functional annotation and interpretation of loci involved in susceptibility to infectious and inflammatory disease in humans and large animal species.

Elimination of Reference Mapping Bias Reveals Robust Immune Related Allele-Specific Expression in Crossbred Sheep.

Pervasive allelic variation at both gene and single nucleotide level (SNV) between individuals is commonly associated with complex traits in humans and animals. Allele-specific expression (ASE) analysis, using RNA-Seq, can provide a detailed annotation of allelic imbalance and infer the existence of cis-acting transcriptional regulation. However, variant detection in RNA-Seq data is compromised by biased mapping of reads to the reference DNA sequence. In this manuscript, we describe an unbiased standardized computational pipeline for allele-specific expression analysis using RNA-Seq data, which we have adapted and developed using tools available under open license. The analysis pipeline we present is designed to minimize reference bias while providing accurate profiling of allele-specific expression across tissues and cell types. Using this methodology, we were able to profile pervasive allelic imbalance across tissues and cell types, at both the gene and SNV level, in Texel×Scottish Blackface sheep, using the sheep gene expression atlas data set. ASE profiles were pervasive in each sheep and across all tissue types investigated. However, ASE profiles shared across tissues were limited, and instead, they tended to be highly tissue-specific. These tissue-specific ASE profiles may underlie the expression of economically important traits and could be utilized as weighted SNVs, for example, to improve the accuracy of genomic selection in breeding programs for sheep. An additional benefit of the pipeline is that it does not require parental genotypes and can therefore be applied to other RNA-Seq data sets for livestock, including those available on the Functional Annotation of Animal Genomes (FAANG) data portal. This study is the first global characterization of moderate to extreme ASE in tissues and cell types from sheep. We have applied a robust methodology for ASE profiling to provide both a novel analysis of the multi-dimensional sheep gene expression atlas data set and a foundation for identifying the regulatory and expressed elements of the genome that are driving complex traits in livestock.

A Mini-Atlas of Gene Expression for the Domestic Goat (Capra hircus).

Goats (Capra hircus) are an economically important livestock species providing meat and milk across the globe. They are of particular importance in tropical agri-systems contributing to sustainable agriculture, alleviation of poverty, social cohesion, and utilisation of marginal grazing. There are excellent genetic and genomic resources available for goats, including a highly contiguous reference genome (ARS1). However, gene expression information is limited in comparison to other ruminants. To support functional annotation of the genome and comparative transcriptomics, we created a mini-atlas of gene expression for the domestic goat. RNA-Seq analysis of 17 transcriptionally rich tissues and 3 cell-types detected the majority (90%) of predicted protein-coding transcripts and assigned informative gene names to more than 1000 previously unannotated protein-coding genes in the current reference genome for goat (ARS1). Using network-based cluster analysis, we grouped genes according to their expression patterns and assigned those groups of coexpressed genes to specific cell populations or pathways. We describe clusters of genes expressed in the gastro-intestinal tract and provide the expression profiles across tissues of a subset of genes associated with functional traits. Comparative analysis of the goat atlas with the larger sheep gene expression atlas dataset revealed transcriptional similarities between macrophage associated signatures in the sheep and goats sampled in this study. The goat transcriptomic resource complements the large gene expression dataset we have generated for sheep and contributes to the available genomic resources for interpretation of the relationship between genotype and phenotype in small ruminants.

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 characterization of transcription of the entire gastrointestinal (GI) tract during the transition from pre-ruminant to ruminant. The dataset comprises 164 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. 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 by identifying key genes involved in immunity, microbe recognition and metabolism. The results form a basis for future studies linking gene expression with microbial colonization of the developing GI tract and provide a foundation to improve ruminant efficiency and productivity through identifying potential targets for novel therapeutics and gene editing.

Species-Specific Transcriptional Regulation of Genes Involved in Nitric Oxide Production and Arginine Metabolism in Macrophages.

Activated mouse macrophages metabolize arginine via NO synthase (NOS2) to produce NO as an antimicrobial effector. Published gene expression datasets provide little support for the activation of this pathway in human macrophages. Generation of NO requires the coordinated regulation of multiple genes. We have generated RNA-sequencing data from bone marrow-derived macrophages from representative rodent (rat), monogastric (pig and horse), and ruminant (sheep, goat, cattle, and water buffalo) species, and analyzed the expression of genes involved in arginine metabolism in response to stimulation with LPS. In rats, as in mice, LPS strongly induced Nos2, the arginine transporter Slc7a2, arginase 1 (Arg1), GTP cyclohydrolase (Gch1), and argininosuccinate synthase (Ass1). None of these responses was conserved across species. Only cattle and water buffalo showed substantial NOS2 induction. The species studied also differed in expression and regulation of arginase (ARG2, rather than ARG1), and amino acid transporters. Variation between species was associated with rapid promoter evolution. Differential induction of NOS2 and ARG2 between the ruminant species was associated with insertions of the Bov-A2 retrotransposon in the promoter region. Bov-A2 was shown to possess LPS-inducible enhancer activity in transfected RAW264.7 macrophages. Consistent with a function in innate immunity, NO production and arginine metabolism vary greatly between species and differences may contribute to pathogen host restriction.

ADGRE1 (EMR1, F4/80) Is a Rapidly-Evolving Gene Expressed in Mammalian Monocyte-Macrophages.

The F4/80 antigen, encoded by the Adgre1 locus, has been widely-used as a monocyte-macrophage marker in mice, but its value as a macrophage marker in other species is unclear, and has even been questioned. ADGRE1 is a seven transmembrane G protein-coupled receptor with an extracellular domain containing repeated Epidermal Growth Factor (EGF)-like calcium binding domains. Using a new monoclonal antibody, we demonstrated that ADGRE1 is a myeloid differentiation marker in pigs, absent from progenitors in bone marrow, highly-expressed in mature granulocytes, monocytes, and tissue macrophages and induced by macrophage colony-stimulating factor (CSF1) treatment in vivo. Based upon these observations, we utilized RNA-Seq to assess the expression of ADGRE1 mRNA in bone marrow or monocyte-derived macrophages (MDM) and alveolar macrophages from 8 mammalian species including pig, human, rat, sheep, goat, cow, water buffalo, and horse. ADGRE1 mRNA was expressed by macrophages in each species, with inter-species variation both in expression level and response to lipopolysaccharide (LPS) stimulation. Analysis of the RNA-Seq data also revealed additional exons in several species compared to current Ensembl annotations. The ruminant species and horses appear to encode a complete duplication of the 7 EGF-like domains. In every species, Sashimi plots revealed evidence of exon skipping of the EGF-like domains, which are highly-variable between species and polymorphic in humans. Consistent with these expression patterns, key elements of the promoter and a putative enhancer are also conserved across all species. The rapid evolution of this molecule and related ADGRE family members suggests immune selection and a role in pathogen recognition.