Alternative splicing, a mechanism of post-transcriptional RNA processing whereby a single gene can encode multiple distinct transcripts, has been proposed to underlie morphological innovations in multicellular organisms. Genes with developmental functions are enriched for alternative splicing events, suggestive of a contribution of alternative splicing to developmental programmes. The role of alternative splicing as a source of transcript diversification has previously been compared to that of gene duplication, with the relationship between the two extensively explored. Alternative splicing is reduced following gene duplication with the retention of duplicate copies higher for genes which were alternatively spliced prior to duplication. Furthermore, and unlike the case for overall gene number, the proportion of alternatively spliced genes has also increased in line with the evolutionary diversification of cell types, suggesting alternative splicing may contribute to the complexity of developmental programmes. Together these observations suggest a prominent role for alternative splicing as a source of functional innovation. However, it is unknown whether the proliferation of alternative splicing events indeed reflects a functional expansion of the transcriptome or instead results from weaker selection acting on larger species, which tend to have a higher number of cell types and lower population sizes. This article is part of the themed issue ‘Evo-devo in the genomics era, and the origins of morphological diversity’.

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. Sheep 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 growth rate and health and fitness traits including disease resilience. 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.

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.

What at the genomic level underlies organism complexity? Although several genomic features have been associated with organism complexity, in the case of alternative splicing, which has long been proposed to explain the variation in complexity, no such link has been established. Here, we analyzed over 39 million expressed sequence tags available for 47 eukaryotic species with fully sequenced genomes to obtain a comparable index of alternative splicing estimates, which corrects for the distorting effect of a variable number of transcripts per species—an important obstacle for comparative studies of alternative splicing. We find that alternative splicing has steadily increased over the last 1,400 My of eukaryotic evolution and is strongly associated with organism complexity, assayed as the number of cell types. Importantly, this association is not explained as a by-product of covariance between alternative splicing with other variables previously linked to complexity including gene content, protein length, proteome disorder, and protein interactivity. In addition, we found no evidence to suggest that the relationship of alternative splicing to cell type number is explained by drift due to reduced N_e in more complex species. Taken together, our results firmly establish alternative splicing as a significant predictor of organism complexity and are, in principle, consistent with an important role of transcript diversification through alternative splicing as a means of determining a genome’s functional information capacity.

We have produced Csf1r-deficient rats by homologous recombination in embryonic stem cells. Consistent with the role of Csf1r in macrophage differentiation, there was a loss of peripheral blood monocytes, microglia in the brain, epidermal Langerhans cells, splenic marginal zone macrophages, bone-associated macrophages and osteoclasts, and peritoneal macrophages. Macrophages of splenic red pulp, liver, lung, and gut were less affected. The pleiotropic impacts of the loss of macrophages on development of multiple organ systems in rats were distinct from those reported in mice. Csf1r^−/− rats survived well into adulthood with postnatal growth retardation, distinct skeletal and bone marrow abnormalities, infertility, and loss of visceral adipose tissue. Gene expression analysis in spleen revealed selective loss of transcripts associated with the marginal zone and, in brain regions, the loss of known and candidate novel microglia-associated transcripts. Despite the complete absence of microglia, there was little overt phenotype in brain, aside from reduced myelination and increased expression of dopamine receptor-associated transcripts in striatum. The results highlight the redundant and nonredundant functions of CSF1R signaling and of macrophages in development, organogenesis, and homeostasis.

Accurately identifying single-nucleotide polymorphisms (SNPs) from bacterial sequencing data is an essential requirement for using genomics to track transmission and predict important phenotypes such as antimicrobial resistance. However, most previous performance evaluations of SNP calling have been restricted to eukaryotic (human) data. Additionally, bacterial SNP calling requires choosing an appropriate reference genome to align reads to, which, together with the bioinformatic pipeline, affects the accuracy and completeness of a set of SNP calls obtained. This study evaluates the performance of 209 SNP-calling pipelines using a combination of simulated data from 254 strains of 10 clinically common bacteria and real data from environmentally sourced and genomically diverse isolates within the genera Citrobacter, Enterobacter, Escherichia, and Klebsiella. We evaluated the performance of 209 SNP-calling pipelines, aligning reads to genomes of the same or a divergent strain. Irrespective of pipeline, a principal determinant of reliable SNP calling was reference genome selection. Across multiple taxa, there was a strong inverse relationship between pipeline sensitivity and precision, and the Mash distance (a proxy for average nucleotide divergence) between reads and reference genome. The effect was especially pronounced for diverse, recombinogenic bacteria such as Escherichia coli but less dominant for clonal species such as Mycobacterium tuberculosis. The accuracy of SNP calling for a given species is compromised by increasing intra-species diversity. When reads were aligned to the same genome from which they were sequenced, among the highest-performing pipelines was Novoalign/GATK. By contrast, when reads were aligned to particularly divergent genomes, the highest-performing pipelines often used the aligners NextGenMap or SMALT, and/or the variant callers LoFreq, mpileup, or Strelka.