Cellular heterogeneity of the developing worker honey bee (Apis mellifera) pupa: a single cell transcriptomics analysis.

It is estimated that animals pollinate 87.5% of flowering plants worldwide and that managed honey bees (Apis mellifera) account for 30-50% of this ecosystem service to agriculture. In addition to their important role as pollinators, honey bees are well-established insect models for studying learning and memory, behavior, caste differentiation, epigenetic mechanisms, olfactory biology, sex determination, and eusociality. Despite their importance to agriculture, knowledge of honey bee biology lags behind many other livestock species. In this study, we have used scRNA-Seq to map cell types to different developmental stages of the worker honey bee (prepupa at day 11 and pupa at day 15) and sought to determine their gene expression signatures. To identify cell-type populations, we examined the cell-to-cell network based on the similarity of the single-cells transcriptomic profiles. Grouping similar cells together we identified 63 different cell clusters of which 17 clusters were identifiable at both stages. To determine genes associated with specific cell populations or with a particular biological process involved in honey bee development, we used gene coexpression analysis. We combined this analysis with literature mining, the honey bee protein atlas, and gene ontology analysis to determine cell cluster identity. Of the cell clusters identified, 17 were related to the nervous system and sensory organs, 7 to the fat body, 19 to the cuticle, 5 to muscle, 4 to compound eye, 2 to midgut, 2 to hemocytes, and 1 to malpighian tubule/pericardial nephrocyte. To our knowledge, this is the first whole single-cell atlas of honey bees at any stage of development and demonstrates the potential for further work to investigate their biology at the cellular level.

When One's Not Enough: Colony Pool-Seq Outperforms Individual-Based Methods for Assessing Introgression in Apis mellifera mellifera.

The human management of honey bees (Apis mellifera) has resulted in the widespread introduction of subspecies outside of their native ranges. One well known example of this is Apis mellifera mellifera, native to Northern Europe, which has now been significantly introgressed by the introduction of C lineage honey bees. Introgression has consequences for species in terms of future adaptive potential and long-term viability. However, estimating introgression in colony-living haplodiploid species is challenging. Previous studies have estimated introgression using individual workers, individual drones, multiple drones, and pooled workers. Here, we compare introgression estimates via three genetic approaches: SNP array, individual RAD-seq, and pooled colony RAD-seq. We also compare two statistical approaches: a maximum likelihood cluster program (ADMIXTURE) and an incomplete lineage sorting model (ABBA BABA). Overall, individual approaches resulted in lower introgression estimates than pooled colonies when using ADMIXTURE. However, the pooled colony ABBA BABA approach resulted in generally lower introgression estimates than all three ADMIXTURE estimates. These results highlight that sometimes one individual is not enough to assess colony-level introgression, and future studies that do use colony pools should not be solely dependent on clustering programs for introgression estimates.

The transcriptional signature associated with human motile cilia.

Cilia are complex microtubule-based organelles essential to a range of processes associated with embryogenesis and tissue homeostasis. Mutations in components of these organelles or those involved in their assembly may result in a diverse set of diseases collectively known as ciliopathies. Accordingly, many cilia-associated proteins have been described, while those distinguishing cilia subtypes are poorly defined. Here we set out to define genes associated with motile cilia in humans based on their transcriptional signature. To define the signature, we performed network deconvolution of transcriptomics data derived from tissues possessing motile ciliated cell populations. For each tissue, genes coexpressed with the motile cilia-associated transcriptional factor, FOXJ1, were identified. The consensus across tissues provided a transcriptional signature of 248 genes. To validate these, we examined the literature, databases (CilDB, CentrosomeDB, CiliaCarta and SysCilia), single cell RNA-Seq data, and the localisation of mRNA and proteins in motile ciliated cells. In the case of six poorly characterised signature genes, we performed new localisation experiments on ARMC3, EFCAB6, FAM183A, MYCBPAP, RIBC2 and VWA3A. In summary, we report a set of motile cilia-associated genes that helps shape our understanding of these complex cellular organelles.

Transcriptomics Analysis of Porcine Caudal Dorsal Root Ganglia in Tail Amputated Pigs Shows Long-Term Effects on Many Pain-Associated Genes.

Tail amputation by tail docking or as an extreme consequence of tail biting in commercial pig production potentially has serious implications for animal welfare. Tail amputation causes peripheral nerve injury that might be associated with lasting chronic pain. The aim of this study was to investigate the short- and long-term effects of tail amputation in pigs on caudal DRG gene expression at different stages of development, particularly in relation to genes associated with nociception and pain. Microarrays were used to analyse whole DRG transcriptomes from tail amputated and sham-treated pigs 1, 8, and 16 weeks following tail treatment at either 3 or 63 days of age (8 pigs/treatment/age/time after treatment; n = 96). Tail amputation induced marked changes in gene expression (up and down) compared to sham-treated intact controls for all treatment ages and time points after tail treatment. Sustained changes in gene expression in tail amputated pigs were still evident 4 months after tail injury. Gene correlation network analysis revealed two co-expression clusters associated with amputation: Cluster A (759 down-regulated) and Cluster B (273 up-regulated) genes. Gene ontology (GO) enrichment analysis identified 124 genes in Cluster A and 61 genes in Cluster B associated with both "inflammatory pain" and "neuropathic pain." In Cluster A, gene family members of ion channels e.g., voltage-gated potassium channels (VGPC) and receptors e.g., GABA receptors, were significantly down-regulated compared to shams, both of which are linked to increased peripheral nerve excitability after axotomy. Up-regulated gene families in Cluster B were linked to transcriptional regulation, inflammation, tissue remodeling, and regulatory neuropeptide activity. These findings, demonstrate that tail amputation causes sustained transcriptomic expression changes in caudal DRG cells involved in inflammatory and neuropathic pain pathways.

Visualization and analysis of RNA-Seq assembly graphs.

RNA-Seq is a powerful transcriptome profiling technology enabling transcript discovery and quantification. Whilst most commonly used for gene-level quantification, the data can be used for the analysis of transcript isoforms. However, when the underlying transcript assemblies are complex, current visualization approaches can be limiting, with splicing events a challenge to interpret. Here, we report on the development of a graph-based visualization method as a complementary approach to understanding transcript diversity from short-read RNA-Seq data. Following the mapping of reads to a reference genome, a read-to-read comparison is performed on all reads mapping to a given gene, producing a weighted similarity matrix between reads. This is used to produce an RNA assembly graph, where nodes represent reads and edges similarity scores between them. The resulting graphs are visualized in 3D space to better appreciate their sometimes large and complex topology, with other information being overlaid on to nodes, e.g. transcript models. Here we demonstrate the utility of this approach, including the unusual structure of these graphs and how they can be used to identify issues in assembly, repetitive sequences within transcripts and splice variants. We believe this approach has the potential to significantly improve our understanding of transcript complexity.

Assembly of a parts list of the human mitotic cell cycle machinery.

The set of proteins required for mitotic division remains poorly characterized. Here, an extensive series of correlation analyses of human and mouse transcriptomics data were performed to identify genes strongly and reproducibly associated with cells undergoing S/G2-M phases of the cell cycle. In so doing, 701 cell cycle-associated genes were defined and while it was shown that many are only expressed during these phases, the expression of others is also driven by alternative promoters. Of this list, 496 genes have known cell cycle functions, whereas 205 were assigned as putative cell cycle genes, 53 of which are functionally uncharacterized. Among these, 27 were screened for subcellular localization revealing many to be nuclear localized and at least three to be novel centrosomal proteins. Furthermore, 10 others inhibited cell proliferation upon siRNA knockdown. This study presents the first comprehensive list of human cell cycle proteins, identifying many new candidate proteins.

Characterisation of the British honey bee metagenome.

The European honey bee (Apis mellifera) plays a major role in pollination and food production. Honey bee health is a complex product of the environment, host genetics and associated microbes (commensal, opportunistic and pathogenic). Improved understanding of these factors will help manage modern challenges to bee health. Here we used DNA sequencing to characterise the genomes and metagenomes of 19 honey bee colonies from across Britain. Low heterozygosity was observed in many Scottish colonies which had high similarity to the native dark bee. Colonies exhibited high diversity in composition and relative abundance of individual microbiome taxa. Most non-bee sequences were derived from known honey bee commensal bacteria or pathogens. However, DNA was also detected from additional fungal, protozoan and metazoan species. To classify cobionts lacking genomic information, we developed a novel network analysis approach for clustering orphan DNA contigs. Our analyses shed light on microbial communities associated with honey bees and demonstrate the power of high-throughput, directed metagenomics for identifying novel biological threats in agroecosystems.

High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool.

The natural distribution of the honeybee (Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera, is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A. m. mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation of introgression levels to more effectively monitor and manage A. m. mellifera conservatories.

Effects of anti-inflammatory drugs on the expression of tryptophan-metabolism genes by human macrophages.

Several lines of evidence link macrophage activation and inflammation with (monoaminergic) nervous systems in the etiology of depression. IFN treatment is associated with depressive symptoms, whereas anti-TNFα therapies elicit positive mood. This study describes the actions of 2 monoaminergic antidepressants (escitalopram, nortriptyline) and 3 anti-inflammatory drugs (indomethacin, prednisolone, and anti-TNFα antibody) on the response of human monocyte-derived macrophages (MDMs) from 6 individuals to LPS or IFN-α. Expression profiling revealed robust changes in the MDM transcriptome (3294 genes at P < 0.001) following LPS challenge, whereas a more limited subset of genes (499) responded to IFNα. Contrary to published reports, administered at nontoxic doses, neither monoaminergic antidepressant significantly modulated the transcriptional response to either inflammatory challenge. Each anti-inflammatory drug had a distinct impact on the expression of inflammatory cytokines and on the profile of inducible gene expression-notably on the regulation of enzymes involved in metabolism of tryptophan. Inter alia, the effect of anti-TNFα antibody confirmed a predicted autocrine stimulatory loop in human macrophages. The transcriptional changes were predictive of tryptophan availability and kynurenine synthesis, as analyzed by targeted metabolomic studies on cellular supernatants. We suggest that inflammatory processes in the brain or periphery could impact on depression by altering the availability of tryptophan for serotonin synthesis and/or by increasing production of neurotoxic kynurenine.

Modelling the Structure and Dynamics of Biological Pathways.

There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologist-friendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system's dynamics. We present example pathway models that illustrate of the power of approach to depict a diverse range of systems.

Analysis of the transcriptional networks underpinning the activation of murine macrophages by inflammatory mediators.

Macrophages respond to the TLR4 agonist LPS with a sequential transcriptional cascade controlled by a complex regulatory network of signaling pathways and transcription factors. At least two distinct pathways are currently known to be engaged by TLR4 and are distinguished by their dependence on the adaptor molecule MyD88. We have used gene expression microarrays to define the effects of each of three variables--LPS dose, LPS versus IFN-ß and -γ, and genetic background--on the transcriptional response of mouse BMDMs. Analysis of correlation networks generated from the data has identified subnetworks or modules within the macrophage transcriptional network that are activated selectively by these variables. We have identified mouse strain-specific signatures, including a module enriched for SLE susceptibility candidates. In the modules of genes unique to different treatments, we found a module of genes induced by type-I IFN but not by LPS treatment, suggesting another layer of complexity in the LPS-TLR4 signaling feedback control. We also observe that the activation of the complement system, in common with the known activation of MHC class 2 genes, is reliant on IFN-γ signaling. Taken together, these data further highlight the exquisite nature of the regulatory systems that control macrophage activation, their likely relevance to disease resistance/susceptibility, and the appropriate response of these cells to proinflammatory stimuli.

A gene expression atlas of the domestic pig.

BACKGROUND: This work describes the first genome-wide analysis of the transcriptional landscape of the pig. A new porcine Affymetrix expression array was designed in order to provide comprehensive coverage of the known pig transcriptome. The new array was used to generate a genome-wide expression atlas of pig tissues derived from 62 tissue/cell types. These data were subjected to network correlation analysis and clustering. RESULTS: The analysis presented here provides a detailed functional clustering of the pig transcriptome where transcripts are grouped according to their expression pattern, so one can infer the function of an uncharacterized gene from the company it keeps and the locations in which it is expressed. We describe the overall transcriptional signatures present in the tissue atlas, where possible assigning those signatures to specific cell populations or pathways. In particular, we discuss the expression signatures associated with the gastrointestinal tract, an organ that was sampled at 15 sites along its length and whose biology in the pig is similar to human. We identify sets of genes that define specialized cellular compartments and region-specific digestive functions. Finally, we performed a network analysis of the transcription factors expressed in the gastrointestinal tract and demonstrate how they sub-divide into functional groups that may control cellular gastrointestinal development. CONCLUSIONS: As an important livestock animal with a physiology that is more similar than mouse to man, we provide a major new resource for understanding gene expression with respect to the known physiology of mammalian tissues and cells. The data and analyses are available on the websites http://biogps.org and http://www.macrophages.com/pig-atlas.

USP18 restricts PRRSV growth through alteration of nuclear translocation of NF-κB p65 and p50 in MARC-145 cells.

Although the functions of porcine respiratory and reproductive syndrome virus (PRRSV) proteins are increasingly understood, the roles of host factors in modifying infection are less well understood. Growing evidence places deubiquitination at the core of a multitude of regulatory processes, ranging from cell growth to innate immune response and health, such as cancer, degenerative and infectious diseases. This report provides further information on the functional role of the porcine ubiquitin-specific peptidase 18 (USP18) during innate immune responses to PRRSV. We have shown that constitutive overexpression of the porcine USP18 in MARC-145 cells restricts PRRSV growth, at least in part via early activation of NF-κB. Viral growth of PRRSV may be perturbed by increasing and decreasing nuclear translocation of p65 and p50, respectively. Our data highlight USP18 as a host restriction factor during innate immune response to PRRSV.

Somatic retrotransposition alters the genetic landscape of the human brain.

Retrotransposons are mobile genetic elements that use a germline 'copy-and-paste' mechanism to spread throughout metazoan genomes. At least 50 per cent of the human genome is derived from retrotransposons, with three active families (L1, Alu and SVA) associated with insertional mutagenesis and disease. Epigenetic and post-transcriptional suppression block retrotransposition in somatic cells, excluding early embryo development and some malignancies. Recent reports of L1 expression and copy number variation in the human brain suggest that L1 mobilization may also occur during later development. However, the corresponding integration sites have not been mapped. Here we apply a high-throughput method to identify numerous L1, Alu and SVA germline mutations, as well as 7,743 putative somatic L1 insertions, in the hippocampus and caudate nucleus of three individuals. Surprisingly, we also found 13,692 somatic Alu insertions and 1,350 SVA insertions. Our results demonstrate that retrotransposons mobilize to protein-coding genes differentially expressed and active in the brain. Thus, somatic genome mosaicism driven by retrotransposition may reshape the genetic circuitry that underpins normal and abnormal neurobiological processes.

Involvement of protein kinase A in patterning of the mouse somatosensory cortex.

Patterning of the mouse somatosensory cortex is unusually evident because of the presence of a "barrel field." Presynaptic serotonin and postsynaptic glutamate receptors regulate barrel formation, but little is known of the intracellular signaling pathways through which they act. To determine whether protein kinase A (PKA) plays a role in the development of the barrel field, we examined five viable PKA subunit-specific knock-out (KO) mouse lines for barrel field abnormalities. Barrels are present in these mice, but those lacking the RIIbeta subunit display significantly reduced contrast between the cell densities of barrel hollows and sides compared with wild-type animals. Thalamocortical afferent segregation in the posterior medial barrel subfield appeared normal, suggesting a postsynaptic site of gene action for the RIIbeta protein. Immunoelectron microscopy confirmed that RIIbeta was selectively localized to dendrites and dendritic spines. Mice lacking RIIbeta show reduced glutamate receptor A (GluRA) subunit insertion into the postsynaptic density in postnatal day 7 somatosensory cortex; however, GluRA KO mice developed normal barrels. Our results clearly demonstrate a role for postsynaptic PKA signaling pathways in barrel differentiation. They also demonstrate a clear dissociation between the regulation of GluRA trafficking by PKA and its role in barrel formation. Finally, although a role for PKA downstream of cAMP cannot be ruled out, these data suggest that PKA may not be the principle downstream target because none of the mutants showed a barrelless phenotype similar to that observed in adenylate cyclase type 1 KO mice. These results give insight into activity-dependent mechanisms that regulate barrel formation.

Synaptic Ras GTPase activating protein regulates pattern formation in the trigeminal system of mice.

The development of ordered connections or "maps" within the nervous system is a common feature of sensory systems and is crucial for their normal function. NMDA receptors are known to play a key role in the formation of these maps; however, the intracellular signaling pathways that mediate the effects of glutamate are poorly understood. Here, we demonstrate that SynGAP, a synaptic Ras GTPase activating protein, is essential for the anatomical development of whisker-related patterns in the developing somatosensory pathways in rodent forebrain. Mice lacking SynGAP show only partial segregation of barreloids in the thalamus, and thalamocortical axons segregate into rows but do not form whisker-related patches. In cortex, layer 4 cells do not aggregate to form barrels. In Syngap(+/-) animals, barreloids develop normally, and thalamocortical afferents segregate in layer 4, but cell segregation is retarded. SynGAP is not necessary for the development of whisker-related patterns in the brainstem. Immunoelectron microscopy for SynGAP from layer 4 revealed a postsynaptic localization with labeling in developing postsynaptic densities (PSDs). Biochemically, SynGAP associates with the PSD in a PSD-95-independent manner, and Psd-95(-/-) animals develop normal barrels. These data demonstrate an essential role for SynGAP signaling in the activity-dependent development of whisker-related maps selectively in forebrain structures indicating that the intracellular pathways by which NMDA receptor activation mediates map formation differ between brain regions and developmental stage.

X-epilectin: a novel epidermal fucolectin regulated by BMP signalling.

This paper reports the cloning and characterisation of a new posterior epidermal marker, X-epilectin, in Xenopus laevis. This gene encodes for a fucolectin, which belongs to the lectin superfamily of carbohydrate binding proteins and specifically binds fucose residues. RT-PCR and in situ hybridisation show that the expression of this gene is switched on during gastrulation and up-regulated during neurula stages and found expressed ubiquitously throughout the epidermis. From tailbud stages, the expression is limited to the dorsal posterior region of the embryo, suggesting that X-epilectin expression is regulated along anteroposterior and dorsoventral gradients during development. In the adult, X-epilectin is mainly expressed in intestinal components, kidney, spinal cord and skin. The effects of growth factors on the regulation of X-epilectin were studied. Change of the fate of animal caps into cement gland or dorsal mesoderm induces a down-regulation of X-epilectin expression in explants treated respectively with ammonium chloride and activin A. We also show that X-epilectin expression is down-regulated by Noggin and tBR and that this effect is inhibited by BMP4 over-expression, suggesting X-epilectin expression is mediated by the BMP signalling pathway.

Isolation and growth factor inducibility of the Xenopus laevis Lmx1b gene.

This paper reports the cloning of the full length Xenopus laevis Lmx1b gene, Xlmx1b. Xlmx1b is a LIM homeodomain protein with high conservation to homologues identified in human, mouse, hamster and chick. In situ hybridisation and RT-PCR analysis showed that Xlmx1b has a specific temporal expression pattern which can be separated into three main spatial domains. An Xlmx1b probe hybridized to regions of the nervous system from stage 13 onwards; these regions included the placodes and otic vesicles, the eye and specific sets of neurons. Sectioning of in situ hybridised embryos confirmed the location of transcripts as discreet regions of staining in ventrolateral regions of the neural tube. From stage 27, transcripts could be detected in the capsule of pronephric glomus. Finally, transcripts were detected by Northern blot analysis in the developing fore and hind limbs. Xlmx1b transcripts were also detected by Northern blot analysis in eye, brain, muscle and mesonephros tissue in metamorphosing tadpoles. RT-PCR analysis showed that zygotic expression of Xlmx1b is initiated at stage 10.5 and the temporal sequence of Xlmx1b expression is identical in both neural and presumptive pronephros regions. The effects of the growth factors activin A, retinoic acid (RA) and basic fibroblast growth factor (bFGF) on the regulation of Xlmx1b were also studied. Xlmx1b was found to be upregulated by activin A and RA inhibited this upregulation in a concentration dependant manner. In contrast, bFGF had no effect on the regulation of Xlmx1b.

Signalling by glial cell line-derived neurotrophic factor (GDNF) requires heparan sulphate glycosaminoglycan.

Glial cell line-derived neurotrophic factor, GDNF, is vital to the development and maintenance of neural tissues; it promotes survival of sympathetic, parasympathetic and spinal motor neurons during development, protects midbrain dopaminergic neurons from apoptosis well enough to be a promising treatment for Parkinson's disease, and controls renal and testicular development. Understanding how GDNF interacts with its target cells is therefore a priority in several fields. Here we show that GDNF requires glycosaminoglycans as well as the already-known components of its receptor complex, c-Ret and GFRalpha-1. Without glycosaminoglcyans, specifically heparan sulphate, c-Ret phosphorylation fails and GDNF cannot induce axonogenesis in neurons, in PC-12 cells, or scatter of epithelial cells. Furthermore, exogenous heparan sulphate inhibits rather than assists GDNF signalling. The involvement of heparan sulphates in GDNF signalling raises the possibility that modulation of heparan expression may modulate signalling by GDNF in vivo.