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 tissueand 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

Distributed and dynamic intracellular organization of extracellular information

Although cells respond specifically to environments, how environmental identity is encoded intracellularly is not understood. Here, we study this organization of information in budding yeast by estimating the mutual information between environmental transitions and the dynamics of nuclear translocation for 10 transcription factors. Our method of estimation is general, scalable, and based on decoding from single cells. The dynamics of the transcription factors are necessary to encode the highest amounts of extracellular information, and we show that information is transduced through two channels: Generalists (Msn2/4, Tod6 and Dot6, Maf1, and Sfp1) can encode the nature of multiple stresses, but only if stress is high; specialists (Hog1, Yap1, and Mig1/2) encode one particular stress, but do so more quickly and for a wider range of magnitudes. In particular, Dot6 encodes almost as much information as Msn2, the master regulator of the environmental stress response. Each transcription factor reports differently, and it is only their collective behavior that distinguishes between multiple environmental states. Changes in the dynamics of the localization of transcription factors thus constitute a precise, distributed internal representation of extracellular change. We predict that such multidimensional representations are common in cellular decision-making

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

Additional file 3. This file contains all supplementary tables relating to lncRNA identification via the conservation of synteny. Table S3. lncRNAs inferred in one species by the genomic alignment of a transcript assembled with the RNA-seq libraries from a related spdecies. Table S12. Presence of intergenic lncRNAs both in sheep and cattle, in regions of conserved synteny. Table S13. Presence of intergenic lncRNAs both in sheep and goat, in regions of conserved synteny. Table S14. Presence of intergenic lncRNAs both in cattle and goat, in regions of conserved synteny. Table S15. Presence of intergenic lncRNAs both in sheep and humans, in regions of conserved synteny. Table S16. Presence of intergenic lncRNAs both in goat and humans, in regions of conserved synteny. Table S17. Presence of intergenic lncRNAs both in cattle and humans, in regions of conserved synteny. Table S18. High-confidence lncRNA pairs, those conserved across species both sequentially and positionally

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

Analysing and meta-analysing time-series data of microbial growth and gene expression from plate readers

Responding to change is a fundamental property of life, making time-series data invaluable in biology. For microbes, plate readers are a popular, convenient means to measure growth and also gene expression using fluorescent reporters. Nevertheless, the difficulties of analysing the resulting data can be a bottleneck, particularly when combining measurements from different wells and plates. Here we present omniplate, a Python module that corrects and normalises plate-reader data, estimates growth rates and fluorescence per cell as functions of time, calculates errors, exports in different formats, and enables meta-analysis of multiple plates. The software corrects for autofluorescence, the optical density's non-linear dependence on the number of cells, and the effects of the media. We use omniplate to measure the Monod relationship for the growth of budding yeast in raffinose, showing that raffinose is a convenient carbon source for controlling growth rates. Using fluorescent tagging, we study yeast's glucose transport. Our results are consistent with the regulation of the hexose transporter (HXT) genes being approximately bipartite: the medium and high affinity transporters are predominately regulated by both the high affinity glucose sensor Snf3 and the kinase complex SNF1 via the repressors Mth1, Mig1, and Mig2; the low affinity transporters are predominately regulated by the low affinity sensor Rgt2 via the co-repressor Std1. We thus demonstrate that omniplate is a powerful tool for exploiting the advantages offered by time-series data in revealing biological regulation

Distributed and dynamic intracellular organization of extracellular information in yeast

Data from single-cell microscopy experiments for "Distributed and dynamic intracellular organization of extracellular information" by Granados, Pietsch, Cepeda-Humerez, Tkačik and Swain. The data come from a microfluidics-based screening of the dynamics of nuclear translocation for 10 transcription factors (Msn2, Msn4, Dot6, Tod6, Sfp1, Maf1, Mig1, Mig2, Hog1, and Yap1), which are the endpoints of evolutionarily conserved signaling pathways (including protein kinase A (PKA), AMP kinase and TOR kinase pathways). The data set includes single-cell time series describing the response of each factor for environmental transitions from rich media (2% glucose) into three different stresses: carbon stress (low glucose), osmotic stress or oxidative stress. Responses to different magnitudes of each stress are also included.Granados, AA; Pietsch, JMJ; Cepeda-Humerez, SA; Farquhar, I; Tkačik, G; Swain, P. (2017). Distributed and dynamic intracellular organization of extracellular information in yeast, [dataset]. University of Edinburgh. http://dx.doi.org/10.7488/ds/221

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. This dataset demonstrates that few lncRNA are fully captured by biological replicates of the same RNA-seq library. In a transcriptional atlas of the domestic sheep (https://doi.org/10.1371/journal.pgen.1006997), 31 diverse tissues/cell types were sampled in each of 6 individual adults (3 females, 3 males, all unrelated virgin animals approximately 2 years of age). By taking a subset of 31 common tissues per individual, each of the 6 adults (f1, f2, f3, m1, m2, and m3) was represented by ~0.75 billion reads. In a typical lncRNA assembly pipeline, read alignments from all individuals are merged, to maximise the number of candidate gene models (using, for instance, StringTie --merge). With n = 6 adults (and ~0.75 billion reads per adult), there are (2^n)-1 = 63 possible combinations of data for which GTFs can be made with StringTie --merge. This dataset comprises those GTFs.Bush, Stephen; Muriuki, Charity; McCulloch, Mary E. B.; Farquhar, Iseabail L.; Clark, Emily L.; Hume, David A.. (2018). Assembly and validation of conserved long non-coding RNAs in the ruminant transcriptome, [dataset]. Roslin Institute. University of Edinburgh. http://dx.doi.org/10.7488/ds/2284

Comprehensive transcriptional profiling of the gastrointestinal tract of ruminants from birth to adulthood

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 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). Included here are the gene expression estimates as transcripts per million (TPM) for individual sheep (Table S4) and averaged across individuals (Table S1).Bush, Stephen J.; McCulloch, Mary E. B.; Muriuki, Charity; Salavati, Mazdak; Davis, Gemma M.; Farquhar, Iseabail L.; Lisowski, Z. M.; Archibald, Alan L.; Hume, D. A.; Clark, E. L.. (2018). Comprehensive transcriptional profiling of the gastrointestinal tract of ruminants from birth to adulthood, [dataset]. The Roslin Institute. University of Edinburgh