The CRTC1-SIK1 pathway regulates entrainment of the circadian clock.

Retinal photoreceptors entrain the circadian system to the solar day. This photic resetting involves cAMP response element binding protein (CREB)-mediated upregulation of Per genes within individual cells of the suprachiasmatic nuclei (SCN). Our detailed understanding of this pathway is poor, and it remains unclear why entrainment to a new time zone takes several days. By analyzing the light-regulated transcriptome of the SCN, we have identified a key role for salt inducible kinase 1 (SIK1) and CREB-regulated transcription coactivator 1 (CRTC1) in clock re-setting. An entrainment stimulus causes CRTC1 to coactivate CREB, inducing the expression of Per1 and Sik1. SIK1 then inhibits further shifts of the clock by phosphorylation and deactivation of CRTC1. Knockdown of Sik1 within the SCN results in increased behavioral phase shifts and rapid re-entrainment following experimental jet lag. Thus SIK1 provides negative feedback, acting to suppress the effects of light on the clock. This pathway provides a potential target for the regulation of circadian rhythms.

Identifying and avoiding off-target effects of RNase H-dependent antisense oligonucleotides in mice.

Antisense oligonucleotides that are dependent on RNase H for cleavage and subsequent degradation of complementary RNA are being developed as therapeutics. Besides the intended RNA target, such oligonucleotides may also cause degradation of unintended RNA off-targets by binding to partially complementary target sites. Here, we characterized the global effects on the mouse liver transcriptome of four oligonucleotides designed as gapmers, two targeting Apob and two targeting Pcsk9, all in different regions on their respective intended targets. This study design allowed separation of intended- and off-target effects on the transcriptome for each gapmer. Next, we used sequence analysis to identify possible partially complementary binding sites among the potential off-targets, and validated these by measurements of melting temperature and RNase H-cleavage rates. Generally, our observations were as expected in that fewer mismatches or bulges in the gapmer/transcript duplexes resulted in a higher chance of those duplexes being effective substrates for RNase H. Follow-up experiments in mice and cells show, that off-target effects can be mitigated by ensuring that gapmers have minimal sequence complementarity to any RNA besides the intended target, and that they do not have exaggerated binding affinity to the intended target.

The genomic organization and expression pattern of the low-affinity Fc gamma receptors (FcγR) in the Göttingen minipig.

Safety and efficacy of therapeutic antibodies are often dependent on their interaction with Fc receptors for IgG (FcγRs). The Göttingen minipig represents a valuable species for biomedical research but its use in preclinical studies with therapeutic antibodies is hampered by the lack of knowledge about the porcine FcγRs. Genome analysis and sequencing now enabled the localization of the previously described FcγRIIIa in the orthologous location to human FCGR3A. In addition, we identified nearby the gene coding for the hitherto undescribed putative porcine FcγRIIa. The 1'241 bp long FCGR2A cDNA translates to a 274aa transmembrane protein containing an extracellular region with high similarity to human and cattle FcγRIIa. Like in cattle, the intracellular part does not contain an immunoreceptor tyrosine-based activation motif (ITAM) as in human FcγRIIa. Flow cytometry of the whole blood and single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) of Göttingen minipigs revealed the expression profile of all porcine FcγRs which is compared to human and mouse. The new FcγRIIa is mainly expressed on platelets making the minipig a good model to study IgG-mediated platelet activation and aggregation. In contrast to humans, minipig blood monocytes were found to express inhibitory FcγRIIb that could lead to the underestimation of FcγR-mediated effects of monocytes observed in minipig studies with therapeutic antibodies.

Rewriting the (tran)script: Application to spinal muscular atrophy.

Targeting RNA drastically expands our target space to therapeutically modulate numerous cellular processes implicated in human diseases. Of particular interest, drugging pre-mRNA splicing appears a very viable strategy; to control levels of splicing product by promoting the inclusion or exclusion of exons. After describing the concept of "splicing modulation", this chapter will cover the outstanding progress achieved in this field, by highlighting the breakthrough accomplished recently for the treatment of spinal muscular atrophy using two therapeutic modalities: splice switching oligonucleotides and small molecules. This review discusses the vital but feasible requirement for such drugs to deliver selectivity, and critical safety aspects are highlighted. Transformational medicines such as those developed to treat SMA are likely just the beginning of this story.

Modeling the Effects of Severe Metabolic Disease by Genome Editing of hPSC-Derived Endothelial Cells Reveals an Inflammatory Phenotype.

The kinase AKT2 (PKB) is an important mediator of insulin signaling, for which loss-of-function knockout (KO) mutants lead to early onset diabetes mellitus, and dominant active mutations lead to early development of obesity and endothelial cell (EC) dysfunction. To model EC dysfunction, we used edited human pluripotent stem cells (hPSCs) that carried either a homozygous deletion of AKT2 (AKT2 KO) or a dominant active mutation (AKT2 E17K), which, along with the parental wild type (WT), were differentiated into ECs. Profiling of EC lines indicated an increase in proinflammatory and a reduction in anti-inflammatory fatty acids, an increase in inflammatory chemokines in cell supernatants, increased expression of proinflammatory genes, and increased binding to the EC monolayer in a functional leukocyte adhesion assay for both AKT2 KO and AKT2 E17K. Collectively, these findings suggest that vascular endothelial inflammation that results from dysregulated insulin signaling (homeostasis) may contribute to coronary artery disease, and that either downregulation or upregulation of the insulin pathway may lead to inflammation of endothelial cells. This suggests that the standard of care for patients must be expanded from control of metabolic parameters to include control of inflammation, such that endothelial dysfunction and cardiovascular disorders can ultimately be prevented.

Correction to: Detect tissue heterogeneity in gene expression data with BioQC.

After the publication of this work [1], a mistake was noticed in the Eq. 1. Given an m × n expression matrix with m genes and samples of n tissues, the correct definition of the Gini index for gene i is.

First Infusion Reactions are Mediated by FcγRIIIb and Neutrophils.

PURPOSE: Administration of therapeutic monoclonal antibodies (mAbs) is frequently accompanied by severe first infusion reactions (FIR). The mechanism driving FIR is still unclear. This study aimed to investigate the cellular and molecular mechanisms causing FIR in humanized mouse models and their potential for evaluating FIR risk in patients. METHODS: Mice humanized for Fc gamma receptors (FcγRs) were generated by recombination-mediated genomic replacement. Body temperature, cytokine release and reactive oxygen species (ROS) were measured to assess FIR to mAbs. RESULTS: Infusion of human mAb specific for mouse transferrin receptor (HamTfR) into FcγR-humanized mice, produced marked transient hypothermia accompanied by an increase in inflammatory cytokines KC and MIP-2, and ROS. FIR were dependent on administration route and Fc-triggered effector functions mediated by neutrophils. Human neutrophils also induced FIR in wild type mice infused with HamTfR. Specific knock-in mice demonstrated that human FcγRIIIb on neutrophils was both necessary and sufficient to cause FIR. FcγRIIIb-mediated FIR was abolished by depleting neutrophils or blocking FcγRIIIb with CD11b antibodies. CONCLUSIONS: Human FcγRIIIb and neutrophils are primarily responsible for triggering FIR. Clinical strategies to prevent FIR in patients should focus on this pathway and may include transient depletion of neutrophils or blocking FcγRIIIb with specific mAbs.

Detect tissue heterogeneity in gene expression data with BioQC.

BACKGROUND: Gene expression data can be compromised by cells originating from other tissues than the target tissue of profiling. Failures in detecting such tissue heterogeneity have profound implications on data interpretation and reproducibility. A computational tool explicitly addressing the issue is warranted. RESULTS: We introduce BioQC, a R/Bioconductor software package to detect tissue heterogeneity in gene expression data. To this end BioQC implements a computationally efficient Wilcoxon-Mann-Whitney test and provides more than 150 signatures of tissue-enriched genes derived from large-scale transcriptomics studies. Simulation experiments show that BioQC is both fast and sensitive in detecting tissue heterogeneity. In a case study with whole-organ profiling data, BioQC predicted contamination events that are confirmed by quantitative RT-PCR. Applied to transcriptomics data of the Genotype-Tissue Expression (GTEx) project, BioQC reveals clustering of samples and suggests that some samples likely suffer from tissue heterogeneity. CONCLUSIONS: Our experience with gene expression data indicates a prevalence of tissue heterogeneity that often goes unnoticed. BioQC addresses the issue by integrating prior knowledge with a scalable algorithm. We propose BioQC as a first-line tool to ensure quality and reproducibility of gene expression data.

Cathepsin S Cleavage of Protease-Activated Receptor-2 on Endothelial Cells Promotes Microvascular Diabetes Complications.

Endothelial dysfunction is a central pathomechanism in diabetes-associated complications. We hypothesized a pathogenic role in this dysfunction of cathepsin S (Cat-S), a cysteine protease that degrades elastic fibers and activates the protease-activated receptor-2 (PAR2) on endothelial cells. We found that injection of mice with recombinant Cat-S induced albuminuria and glomerular endothelial cell injury in a PAR2-dependent manner. In vivo microscopy confirmed a role for intrinsic Cat-S/PAR2 in ischemia-induced microvascular permeability. In vitro transcriptome analysis and experiments using siRNA or specific Cat-S and PAR2 antagonists revealed that Cat-S specifically impaired the integrity and barrier function of glomerular endothelial cells selectively through PAR2. In human and mouse type 2 diabetic nephropathy, only CD68(+) intrarenal monocytes expressed Cat-S mRNA, whereas Cat-S protein was present along endothelial cells and inside proximal tubular epithelial cells also. In contrast, the cysteine protease inhibitor cystatin C was expressed only in tubules. Delayed treatment of type 2 diabetic db/db mice with Cat-S or PAR2 inhibitors attenuated albuminuria and glomerulosclerosis (indicators of diabetic nephropathy) and attenuated albumin leakage into the retina and other structural markers of diabetic retinopathy. These data identify Cat-S as a monocyte/macrophage-derived circulating PAR2 agonist and mediator of endothelial dysfunction-related microvascular diabetes complications. Thus, Cat-S or PAR2 inhibition might be a novel strategy to prevent microvascular disease in diabetes and other diseases.

Boolean regulatory network reconstruction using literature based knowledge with a genetic algorithm optimization method.

BACKGROUND: Prior knowledge networks (PKNs) provide a framework for the development of computational biological models, including Boolean models of regulatory networks which are the focus of this work. PKNs are created by a painstaking process of literature curation, and generally describe all relevant regulatory interactions identified using a variety of experimental conditions and systems, such as specific cell types or tissues. Certain of these regulatory interactions may not occur in all biological contexts of interest, and their presence may dramatically change the dynamical behaviour of the resulting computational model, hindering the elucidation of the underlying mechanisms and reducing the usefulness of model predictions. Methods are therefore required to generate optimized contextual network models from generic PKNs. RESULTS: We developed a new approach to generate and optimize Boolean networks, based on a given PKN. Using a genetic algorithm, a model network is built as a sub-network of the PKN and trained against experimental data to reproduce the experimentally observed behaviour in terms of attractors and the transitions that occur between them under specific perturbations. The resulting model network is therefore contextualized to the experimental conditions and constitutes a dynamical Boolean model closer to the observed biological process used to train the model than the original PKN. Such a model can then be interrogated to simulate response under perturbation, to detect stable states and their properties, to get insights into the underlying mechanisms and to generate new testable hypotheses. CONCLUSIONS: Generic PKNs attempt to synthesize knowledge of all interactions occurring in a biological process of interest, irrespective of the specific biological context. This limits their usefulness as a basis for the development of context-specific, predictive dynamical Boolean models. The optimization method presented in this article produces specific, contextualized models from generic PKNs. These contextualized models have improved utility for hypothesis generation and experimental design. The general applicability of this methodological approach makes it suitable for a variety of biological systems and of general interest for biological and medical research. Our method was implemented in the software optimusqual, available online at http://www.vital-it.ch/software/optimusqual/ .

Pathway reporter genes define molecular phenotypes of human cells.

BACKGROUND: The phenotype of a living cell is determined by its pattern of active signaling networks, giving rise to a "molecular phenotype" associated with differential gene expression. Digital amplicon based RNA quantification by sequencing is a useful technology for molecular phenotyping as a novel tool to characterize the state of biological systems. RESULTS: We show here that the activity of signaling networks can be assessed based on a set of established key regulators and expression targets rather than the entire transcriptome. We compiled a panel of 917 human pathway reporter genes, representing 154 human signaling and metabolic networks for integrated knowledge- and data-driven understanding of biological processes. The reporter genes are significantly enriched for regulators and effectors covering a wide range of biological processes, and faithfully capture gene-level and pathway-level changes. We apply the approach to iPSC derived cardiomyocytes and primary human hepatocytes to describe changes in molecular phenotype during development or drug response. The reporter genes deliver an accurate pathway-centric view of the biological system under study, and identify known and novel modulation of signaling networks consistent with literature or experimental data. CONCLUSIONS: A panel of 917 pathway reporter genes is sufficient to describe changes in the molecular phenotype defined by 154 signaling cascades in various human cell types. AmpliSeq-RNA based digital transcript imaging enables simultaneous monitoring of the entire pathway reporter gene panel in up to 150 samples. We propose molecular phenotyping as a useful approach to understand diseases and drug action at the network level.

Functional analysis and transcriptional output of the Göttingen minipig genome.

BACKGROUND: In the past decade the Göttingen minipig has gained increasing recognition as animal model in pharmaceutical and safety research because it recapitulates many aspects of human physiology and metabolism. Genome-based comparison of drug targets together with quantitative tissue expression analysis allows rational prediction of pharmacology and cross-reactivity of human drugs in animal models thereby improving drug attrition which is an important challenge in the process of drug development. RESULTS: Here we present a new chromosome level based version of the Göttingen minipig genome together with a comparative transcriptional analysis of tissues with pharmaceutical relevance as basis for translational research. We relied on mapping and assembly of WGS (whole-genome-shotgun sequencing) derived reads to the reference genome of the Duroc pig and predict 19,228 human orthologous protein-coding genes. Genome-based prediction of the sequence of human drug targets enables the prediction of drug cross-reactivity based on conservation of binding sites. We further support the finding that the genome of Sus scrofa contains about ten-times less pseudogenized genes compared to other vertebrates. Among the functional human orthologs of these minipig pseudogenes we found HEPN1, a putative tumor suppressor gene. The genomes of Sus scrofa, the Tibetan boar, the African Bushpig, and the Warthog show sequence conservation of all inactivating HEPN1 mutations suggesting disruption before the evolutionary split of these pig species. We identify 133 Sus scrofa specific, conserved long non-coding RNAs (lncRNAs) in the minipig genome and show that these transcripts are highly conserved in the African pigs and the Tibetan boar suggesting functional significance. Using a new minipig specific microarray we show high conservation of gene expression signatures in 13 tissues with biomedical relevance between humans and adult minipigs. We underline this relationship for minipig and human liver where we could demonstrate similar expression levels for most phase I drug-metabolizing enzymes. Higher expression levels and metabolic activities were found for FMO1, AKR/CRs and for phase II drug metabolizing enzymes in minipig as compared to human. The variability of gene expression in equivalent human and minipig tissues is considerably higher in minipig organs, which is important for study design in case a human target belongs to this variable category in the minipig. The first analysis of gene expression in multiple tissues during development from young to adult shows that the majority of transcriptional programs are concluded four weeks after birth. This finding is in line with the advanced state of human postnatal organ development at comparative age categories and further supports the minipig as model for pediatric drug safety studies. CONCLUSIONS: Genome based assessment of sequence conservation combined with gene expression data in several tissues improves the translational value of the minipig for human drug development. The genome and gene expression data presented here are important resources for researchers using the minipig as model for biomedical research or commercial breeding. Potential impact of our data for comparative genomics, translational research, and experimental medicine are discussed.

Expanding the Imine Reductase Toolbox by Exploring the Bacterial Protein-Sequence Space.

Recent investigations on imine reductases (IREDs) have enriched the toolbox of potential catalysts for accessing chiral amines, which are important building blocks for the pharmaceutical industry. Herein, we describe the characterization of 20 new IREDs. A C-terminal domain clustering of the bacterial protein-sequence space was performed to identify the novel IRED candidates. Each of the identified enzymes was characterized against a set of nine cyclic imine model substrates. A refined clustering towards putative active-site residues was performed and was consistent both with our screening and previously reported results. Finally, preparative scale experiments on a 100 mg scale with two purified IREDs, IR_20 from Streptomyces tsukubaensis and IR_23 from Streptomyces vidiochromogenes, were carried out to provide (R)-2-methylpiperidine in 98% ee (71% yield) and (R)-1-methyl-1,2,3,4-tetrahydroisoquinoline in >98% ee (82% yield).

The immunogenicity of antibody aggregates in a novel transgenic mouse model.

PURPOSE: Protein aggregates have been discussed as a potential risk factor related to immunogenicity. Here we developed a novel human IgG transgenic (tg) mouse system expressing a mini-repertoire of human IgG1 antibodies (Abs) for the assessment of immunogenic properties of human mAb preparations. METHODS: Transgenic mice were generated using germline versions of the human Ig heavy chain γ1 (IgH-γ1), and the human Ig light chain (IgL) κ and λ genes. Only the soluble form of human IgH-γ1 was used to avoid expression of the membrane Ig-H chain and concomitant allelic exclusion of endogenous murine Ig genes. IgG1 aggregates were generated by different stress conditions such as process-related, low pH and exposure to artificial light. RESULTS: The expression of human Ig proteins induced immunological tolerance to a broad range of human IgG1 molecules in the tg mice. Immunization with IgG1 aggregates demonstrated that soluble oligomers induced by significant light-exposure and carrying neo-epitopes induced a strong immune response in tg mice. In contrast, Ab aggregates alone and monomers with neo-epitopes were not immunogenic. CONCLUSION: This mouse model is able to recognize immunogenic modifications of human IgG1. While the degree of stress-induced aggregation varies for different mAbs, our findings using a particular mAb (mAb1) demonstrate that non-covalently modified aggregates do not break tolerance, contrary to widely held opinion. The immunogenic potential of soluble aggregates of human IgG strongly depends on the presence of neo-epitopes resulting from harsh stress conditions, i.e. extensive exposure to artificial light.

Development of a 5-plex SILAC method tuned for the quantitation of tyrosine phosphorylation dynamics.

The propagation of phosphorylation downstream of receptor tyrosine kinases is a key dynamic cellular event involved in signal transduction, which is often deregulated in disease states such as cancer. Probing phosphorylation dynamics is therefore crucial for understanding receptor tyrosine kinases' function and finding ways to inhibit their effects. MS methods combined with metabolic labeling such as stable isotope labeling with amino acids in cell culture (SILAC) have already proven successful in deciphering temporal phosphotyrosine perturbations. However, they are limited in terms of multiplexing, and they also are time consuming, because several experiments need to be performed separately. Here, we introduce an innovative approach based on 5-plex SILAC that allows monitoring of phosphotyrosine signaling perturbations induced by a drug treatment in one single experiment. Using this new labeling strategy specifically tailored for phosphotyrosines, it was possible to generate the time profiles for 318 unique phosphopeptides belonging to 215 proteins from an erlotinib-treated breast cancer cell line model. Hierarchical clustering of the time profiles followed by pathway enrichment analysis highlighted epidermal growth factor receptor (EGFR or ErbB1) and ErbB2 signaling as the major pathways affected by erlotinib, thereby validating the method. Moreover, based on the similarity of its time profile to those of other proteins in the ErbB pathways, the phosphorylation at Tyr453 of protein FAM59A, a recently described adaptor of EGFR, was confirmed as tightly involved in the signaling cascade. The present investigation also demonstrates the remote effect of EGFR inhibition on ErbB3 phosphorylation sites such as Tyr1289 and Tyr1328, as well as a potential feedback effect on Tyr877 of ErbB2. Overall, the 5-plex SILAC is a straightforward approach that extends sample multiplexing and builds up the arsenal of methods for tyrosine phosphorylation dynamics.

Highly sensitive amplicon-based transcript quantification by semiconductor sequencing.

BACKGROUND: In clinical and basic research custom panels for transcript profiling are gaining importance because only project specific informative genes are interrogated. This approach reduces costs and complexity of data analysis and allows multiplexing of samples. Polymerase-chain-reaction (PCR) based TaqMan assays have high sensitivity but suffer from a limited dynamic range and sample throughput. Hence, there is a gap for a technology able to measure expression of large gene sets in multiple samples. RESULTS: We have adapted a commercially available mRNA quantification assay (AmpliSeq-RNA) that measures mRNA abundance based on the frequency of PCR amplicons determined by high-throughput semiconductor sequencing. This approach allows for parallel, accurate quantification of about 1000 transcripts in multiple samples covering a dynamic range of five orders of magnitude. Using samples derived from a well-characterized stem cell differentiation model, we obtained a good correlation (r = 0.78) of transcript levels measured by AmpliSeq-RNA and DNA-microarrays. A significant portion of low abundant transcripts escapes detection by microarrays due to limited sensitivity. Standard quantitative RNA sequencing of the same samples confirms expression of low abundant genes with an overall correlation coefficient of r = 0.87. Based on digital AmpliSeq-RNA imaging we show switches of signaling cascades at four time points during differentiation of stem cells into cardiomyocytes. CONCLUSIONS: The AmpliSeq-RNA technology adapted to high-throughput semiconductor sequencing allows robust transcript quantification based on amplicon frequency. Multiplexing of at least 900 parallel PCR reactions is feasible because sequencing-based quantification eliminates artefacts coming from off-target amplification. Using this approach, RNA quantification and detection of genetic variations can be performed in the same experiment.

Genome-based analysis of the nonhuman primate Macaca fascicularis as a model for drug safety assessment.

The long-tailed macaque, also referred to as cynomolgus monkey (Macaca fascicularis), is one of the most important nonhuman primate animal models in basic and applied biomedical research. To improve the predictive power of primate experiments for humans, we determined the genome sequence of a Macaca fascicularis female of Mauritian origin using a whole-genome shotgun sequencing approach. We applied a template switch strategy that uses either the rhesus or the human genome to assemble sequence reads. The sixfold sequence coverage of the draft genome sequence enabled discovery of about 2.1 million potential single-nucleotide polymorphisms based on occurrence of a dimorphic nucleotide at a given position in the genome sequence. Homology-based annotation allowed us to identify 17,387 orthologs of human protein-coding genes in the M. fascicularis draft genome, and the predicted transcripts enabled the design of a M. fascicularis-specific gene expression microarray. Using liver samples from 36 individuals of different geographic origin we identified 718 genes with highly variable expression in liver, whereas the majority of the transcriptome shows relatively stable and comparable expression. Knowledge of the M. fascicularis draft genome is an important contribution to both the use of this animal in disease models and the safety assessment of drugs and their metabolites. In particular, this information allows high-resolution genotyping and microarray-based gene-expression profiling for animal stratification, thereby allowing the use of well-characterized animals for safety testing. Finally, the genome sequence presented here is a significant contribution to the global "3R" animal welfare initiative, which has the goal to reduce, refine, and replace animal experiments.

Detection of attractors of large Boolean networks via exhaustive enumeration of appropriate subspaces of the state space.

BACKGROUND: Boolean models are increasingly used to study biological signaling networks. In a Boolean network, nodes represent biological entities such as genes, proteins or protein complexes, and edges indicate activating or inhibiting influences of one node towards another. Depending on the input of activators or inhibitors, Boolean networks categorize nodes as either active or inactive. The formalism is appealing because for many biological relationships, we lack quantitative information about binding constants or kinetic parameters and can only rely on a qualitative description of the type "A activates (or inhibits) B". A central aim of Boolean network analysis is the determination of attractors (steady states and/or cycles). This problem is known to be computationally complex, its most important parameter being the number of network nodes. Various algorithms tackle it with considerable success. In this paper we present an algorithm, which extends the size of analyzable networks thanks to simple and intuitive arguments. RESULTS: We present lnet, a software package which, in fully asynchronous updating mode and without any network reduction, detects the fixed states of Boolean networks with up to 150 nodes and a good part of any present cycles for networks with up to half the above number of nodes. The algorithm goes through a complete enumeration of the states of appropriately selected subspaces of the entire network state space. The size of these relevant subspaces is small compared to the full network state space, allowing the analysis of large networks. The subspaces scanned for the analyses of cycles are larger, reducing the size of accessible networks. Importantly, inherent in cycle detection is a classification scheme based on the number of non-frozen nodes of the cycle member states, with cycles characterized by fewer non-frozen nodes being easier to detect. It is further argued that these detectable cycles are also the biologically more important ones. Furthermore, lnet also provides standard Boolean analysis features such as node loop detection. CONCLUSIONS: lnet is a software package that facilitates the analysis of large Boolean networks. Its intuitive approach helps to better understand the network in question.

High throughput transcriptome analysis of lipid metabolism in Syrian hamster liver in absence of an annotated genome.

BACKGROUND: Whole transcriptome analyses are an essential tool for understanding disease mechanisms. Approaches based on next-generation sequencing provide fast and affordable data but rely on the availability of annotated genomes. However, there are many areas in biomedical research that require non-standard animal models for which genome information is not available. This includes the Syrian hamster Mesocricetus auratus as an important model for dyslipidaemia because it mirrors many aspects of human disease and pharmacological responses. We show that complementary use of two independent next generation sequencing technologies combined with mapping to multiple genome databases allows unambiguous transcript annotation and quantitative transcript imaging. We refer to this approach as "triple match sequencing" (TMS). RESULTS: Contigs assembled from a normalized Roche 454 hamster liver library comprising 1.2 million long reads were used to identify 10'800 unique transcripts based on homology to RefSeq database entries from human, mouse, and rat. For mRNA quantification we mapped 82 million SAGE tags (SOLiD) from the same RNA source to the annotated hamster liver transcriptome contigs. We compared the liver transcriptome of hamster with equivalent data from human, rat, minipig, and cynomolgus monkeys to highlight differential gene expression with focus on lipid metabolism. We identify a cluster of five genes functionally related to HDL metabolism that is expressed in human, cynomolgus, minipig, and hamster but lacking in rat as a non-responder species for lipid lowering drugs. CONCLUSIONS: The TMS approach is suited for fast and inexpensive transcript profiling in cells or tissues of species where a fully annotated genome is not available. The continuously growing number of well annotated reference genomes will further empower reliable transcript identification and thereby raise the utility of the method for any species of interest.

Reproductive findings in male animals exposed to selective survival of motor neuron 2 (SMN2) gene splicing-modifying agents.

Risdiplam is a daily, orally dosed, survival of motor neuron 2 (SMN2) mRNA splicing-modifying agent approved for the treatment of spinal muscular atrophy (SMA). RG7800 is a closely related SMN2 mRNA-splicing compound. Effects on secondary mRNA splice targets such as Forkhead Box M1 (FOXM1) and MAP kinase-activating death domain protein (MADD), which have been implicated in cell-cycle regulation, were observed in non-clinical studies with both risdiplam and RG7800. Potential effects of risdiplam on male fertility via FOXM1 and MADD are important as these secondary splice targets exist in humans. This publication reports the findings from 14 in vivo studies that investigated the reproductive tissues of male animals in various stages of development. Exposure to risdiplam or RG7800 induced changes within the germ cells in the testes of male cynomolgus monkeys and rats. Germ-cell changes included both cell-cycle gene changes (alteration of mRNA-splicing variants) and seminiferous tubule degeneration. In monkeys treated with RG7800, there was no evidence of damage to spermatogonia. Observed testicular changes were stage-specific with spermatocytes in the pachytene stage of meiosis and were fully reversible in monkeys following a sufficient recovery period of eight weeks following cessation of RG7800. In rats, seminiferous tubule degeneration was present, and full reversibility of germ-cell degeneration in the testes was observed among half of the rats that were exposed to risdiplam or RG7800 and then allowed to recover. With these results, coupled with histopathological findings, the effects on the male reproductive system are expected to be reversible in humans for these types of SMN2 mRNA-splicing modifiers.