Quality assessment and control of tissue specific RNA-seq libraries of Drosophila transgenic RNAi models

Analysis of asymptomatic Drosophila models for ALS and SMA reveals convergent impact on functional protein complexes linked to neuro-muscular degeneration

BACKGROUND

Spinal Muscular Atrophy (SMA) and Amyotrophic Lateral Sclerosis (ALS) share phenotypic and molecular commonalities, including the fact that they can be caused by mutations in ubiquitous proteins involved in RNA metabolism, namely SMN, TDP-43 and FUS. Although this suggests the existence of common disease mechanisms, there is currently no model to explain the resulting motor neuron dysfunction. In this work we generated a parallel set of Drosophila models for adult-onset RNAi and tagged neuronal expression of the fly orthologues of the three human proteins, named Smn, TBPH and Caz, respectively. We profiled nuclear and cytoplasmic bound mRNAs using a RIP-seq approach and characterized the transcriptome of the RNAi models by RNA-seq. To unravel the mechanisms underlying the common functional impact of these proteins on neuronal cells, we devised a computational approach based on the construction of a tissue-specific library of protein functional modules, selected by an overall impact score measuring the estimated extent of perturbation caused by each gene knockdown.

RESULTS

Transcriptome analysis revealed that the three proteins do not bind to the same RNA molecules and that only a limited set of functionally unrelated transcripts is commonly affected by their knock-down. However, through our integrative approach we were able to identify a concerted effect on protein functional modules, albeit acting through distinct targets. Most strikingly, functional annotation revealed that these modules are involved in critical cellular pathways for motor neurons, including neuromuscular junction function. Furthermore, selected modules were found to be significantly enriched in orthologues of human neuronal disease genes.

CONCLUSIONS

The results presented here show that SMA and ALS disease-associated genes linked to RNA metabolism functionally converge on neuronal protein complexes, providing a new hypothesis to explain the common motor neuron phenotype. The functional modules identified represent promising biomarkers and therapeutic targets, namely given their alteration in asymptomatic settings.

DIS3L2 knockdown impairs key oncogenic properties of colorectal cancer cells via the mTOR signaling pathway

DIS3L2 degrades different types of RNAs in an exosome-independent manner including mRNAs and several types of non-coding RNAs. DIS3L2-mediated degradation is preceded by the addition of nontemplated uridines at the 3'end of its targets by the terminal uridylyl transferases 4 and 7. Most of the literature that concerns DIS3L2 characterizes its involvement in several RNA degradation pathways, however, there is some evidence that its dysregulated activity may contribute to cancer development. In the present study, we characterize the role of DIS3L2 in human colorectal cancer (CRC). Using the public RNA datasets from The Cancer Genome Atlas (TCGA), we found higher DIS3L2 mRNA levels in CRC tissues versus normal colonic samples as well as worse prognosis in patients with high DIS3L2 expression. In addition, our RNA deep-sequencing data revealed that knockdown (KD) of DIS3L2 induces a strong transcriptomic disturbance in SW480 CRC cells. Moreover, gene ontology (GO) analysis of significant upregulated transcripts displays enrichment in mRNAs encoding proteins involved in cell cycle regulation and cancer-related pathways, which guided us to evaluate which specific hallmarks of cancer are differentially regulated by DIS3L2. To do so, we employed four CRC cell lines (HCT116, SW480, Caco-2 and HT-29) differing in their mutational background and oncogenicity. We demonstrate that depletion of DIS3L2 results in reduced cell viability of highly oncogenic SW480 and HCT116 CRC cells, but had little or no impact in the more differentiated Caco-2 and HT-29 cells. Remarkably, the mTOR signaling pathway, crucial for cell survival and growth, is downregulated after DIS3L2 KD, whereas AZGP1, an mTOR pathway inhibitor, is upregulated. Furthermore, our results indicate that depletion of DIS3L2 disturbs metastasis-associated properties, such as cell migration and invasion, only in highly oncogenic CRC cells. Our work reveals for the first time a role for DIS3L2 in sustaining CRC cell proliferation and provides evidence that this ribonuclease is required to support the viability and invasive behavior of dedifferentiated CRC cells.

Mutation-class dependent signatures outweigh disease-associated processes in cystic fibrosis cells

BACKGROUND

The phenotypic heterogeneity observed in Cystic Fibrosis (CF) patients suggests the involvement of other genes, besides CFTR. Here, we combined transcriptome and proteome analysis to understand the global gene expression patterns associated with five prototypical CFTR mutations.

RESULTS

Evaluation of differentially expressed genes and proteins unveiled common and mutation-specific changes revealing functional signatures that are much more associated with the specific molecular defects associated with each mutation than to the CFTR loss-of-function phenotype. The combination of both datasets revealed that mutation-specific detected translated-transcripts (Dtt) have a high level of consistency.

CONCLUSIONS

This is the first combined transcriptomic and proteomic study focusing on prototypical CFTR mutations. Analysis of Dtt provides novel insight into the pathophysiology of CF, and the mechanisms through which each mutation class causes disease and will likely contribute to the identification of new therapeutic targets and/or biomarkers for CF.

Transcriptome analysis of chloride intracellular channel knockdown in Drosophila identifies oxidation-reduction function as possible mechanism of altered sensitivity to ethanol sedation

Chloride intracellular channels (CLICs) are a unique family of evolutionarily conserved metamorphic proteins, switching between stable conformations based on redox conditions. CLICs have been implicated in a wide variety biological processes including ion channel activity, apoptosis, membrane trafficking, and enzymatic oxidoreductase activity. Understanding the molecular mechanisms by which CLICs engage in these activities is an area of active research. Here, the sole Drosophila melanogaster ortholog, Clic, was targeted for RNAi knockdown to identify genes and biological processes associated with Clic expression. Clic knockdown had a substantial impact on global transcription, altering expression of over 7% of transcribed Drosophila genes. Overrepresentation analysis of differentially expressed genes identified enrichment of Gene Ontology terms including Cytoplasmic Translation, Oxidation-Reduction Process, Heme Binding, Membrane, Cell Junction, and Nucleolus. The top term, Cytoplasmic Translation, was enriched almost exclusively with downregulated genes. Drosophila Clic and vertebrate ortholog Clic4 have previously been tied to ethanol sensitivity and ethanol-regulated expression. Clic knockdown-responsive genes from the present study were found to overlap significantly with gene sets from 4 independently published studies related to ethanol exposure and sensitivity in Drosophila. Bioinformatic analysis of genes shared between these studies revealed an enrichment of genes related to amino acid metabolism, protein processing, oxidation-reduction processes, and lipid particles among others. To determine whether the modulation of ethanol sensitivity by Clic may be related to co-regulated oxidation-reduction processes, we evaluated the effect of hyperoxia on ethanol sedation in Clic knockdown flies. Consistent with previous findings, Clic knockdown reduced acute ethanol sedation sensitivity in flies housed under normoxia. However, this effect was reversed by exposure to hyperoxia, suggesting a common set of molecular-genetic mechanism may modulate each of these processes. This study suggests that Drosophila Clic has a major influence on regulation of oxidative stress signaling and that this function overlaps with the molecular mechanisms of acute ethanol sensitivity in the fly.

Cloudy with a Chance of Insights: Context Dependent Gene Regulation and Implications for Evolutionary Studies

Research in various fields of evolutionary biology has shown that divergence in gene expression is a key driver for phenotypic evolution. An exceptional contribution of cis-regulatory divergence has been found to contribute to morphological diversification. In the light of these findings, the analysis of genome-wide expression data has become one of the central tools to link genotype and phenotype information on a more mechanistic level. However, in many studies, especially if general conclusions are drawn from such data, a key feature of gene regulation is often neglected. With our article, we want to raise awareness that gene regulation and thus gene expression is highly context dependent. Genes show tissue- and stage-specific expression. We argue that the regulatory context must be considered in comparative expression studies.

Networks of mRNA Processing and Alternative Splicing Regulation in Health and Disease

mRNA processing events introduce an intricate layer of complexity into gene expression processes, supporting a tremendous level of diversification of the genome's coding and regulatory potential, particularly in vertebrate species. The recent development of massive parallel sequencing methods and their adaptation to the identification and quantification of different RNA species and the dynamics of mRNA metabolism and processing has generated an unprecedented view over the regulatory networks that are established at this level, which contribute to sustain developmental, tissue specific or disease specific gene expression programs. In this chapter, we provide an overview of the recent evolution of transcriptome profiling methods and the surprising insights that have emerged in recent years regarding distinct mRNA processing events - from the 5' end to the 3' end of the molecule.

Identification of novel direct targets of Drosophila Sine oculis and Eyes absent by integration of genome-wide data sets

Drosophila eye development is a complex process that involves many transcription factors (TFs) and interactions with their cofactors and targets. The TF Sine oculis (So) and its cofactor Eyes absent (Eya) are highly conserved and are both necessary and sufficient for eye development. Despite their many important roles during development, the direct targets of So are still largely unknown. Therefore the So-dependent regulatory network governing eye determination and differentiation is poorly understood. In this study, we intersected gene expression profiles of so or eya mutant eye tissue prepared from three different developmental stages and identified 1731 differentially expressed genes across the Drosophila genome. A combination of co-expression analyses and motif discovery identified a set of twelve putative direct So targets, including three known and nine novel targets. We also used our previous So ChIP-seq data to assess motif predictions for So and identified a canonical So binding motif. Finally, we performed in vivo enhancer reporter assays to test predicted enhancers from six candidate target genes and find that at least one enhancer from each gene is expressed in the developing eye disc and that their expression patterns overlap with that of So. We furthermore confirmed that the expression level of predicted direct So targets, for which antibodies are available, are reduced in so or eya post-mitotic knockout eye discs. In summary, we expand the set of putative So targets and show for the first time that the combined use of expression profiling of so with its cofactor eya is an effective method to identify novel So targets. Moreover, since So is highly conserved throughout the metazoa, our results provide the basis for future functional studies in a wide variety of organisms.

Trimming of sequence reads alters RNA-Seq gene expression estimates

BACKGROUND

High-throughput RNA-Sequencing (RNA-Seq) has become the preferred technique for studying gene expression differences between biological samples and for discovering novel isoforms, though the techniques to analyze the resulting data are still immature. One pre-processing step that is widely but heterogeneously applied is trimming, in which low quality bases, identified by the probability that they are called incorrectly, are removed. However, the impact of trimming on subsequent alignment to a genome could influence downstream analyses including gene expression estimation; we hypothesized that this might occur in an inconsistent manner across different genes, resulting in differential bias.

RESULTS

To assess the effects of trimming on gene expression, we generated RNA-Seq data sets from four samples of larval Drosophila melanogaster sensory neurons, and used three trimming algorithms--SolexaQA, Trimmomatic, and ConDeTri-to perform quality-based trimming across a wide range of stringencies. After aligning the reads to the D. melanogaster genome with TopHat2, we used Cuffdiff2 to compare the original, untrimmed gene expression estimates to those following trimming. With the most aggressive trimming parameters, over ten percent of genes had significant changes in their estimated expression levels. This trend was seen with two additional RNA-Seq data sets and with alternative differential expression analysis pipelines. We found that the majority of the expression changes could be mitigated by imposing a minimum length filter following trimming, suggesting that the differential gene expression was primarily being driven by spurious mapping of short reads. Slight differences with the untrimmed data set remained after length filtering, which were associated with genes with low exon numbers and high GC content. Finally, an analysis of paired RNA-seq/microarray data sets suggests that no or modest trimming results in the most biologically accurate gene expression estimates.

CONCLUSIONS

We find that aggressive quality-based trimming has a large impact on the apparent makeup of RNA-Seq-based gene expression estimates, and that short reads can have a particularly strong impact. We conclude that implementation of trimming in RNA-Seq analysis workflows warrants caution, and if used, should be used in conjunction with a minimum read length filter to minimize the introduction of unpredictable changes in expression estimates.

Using mixtures of biological samples as process controls for RNA-sequencing experiments

Background

Genome-scale “-omics” measurements are challenging to benchmark due to the enormous variety of unique biological molecules involved. Mixtures of previously-characterized samples can be used to benchmark repeatability and reproducibility using component proportions as truth for the measurement. We describe and evaluate experiments characterizing the performance of RNA-sequencing (RNA-Seq) measurements, and discuss cases where mixtures can serve as effective process controls.

Results

We apply a linear model to total RNA mixture samples in RNA-seq experiments. This model provides a context for performance benchmarking. The parameters of the model fit to experimental results can be evaluated to assess bias and variability of the measurement of a mixture. A linear model describes the behavior of mixture expression measures and provides a context for performance benchmarking. Residuals from fitting the model to experimental data can be used as a metric for evaluating the effect that an individual step in an experimental process has on the linear response function and precision of the underlying measurement while identifying signals affected by interference from other sources. Effective benchmarking requires well-defined mixtures, which for RNA-Seq requires knowledge of the post-enrichment ‘target RNA’ content of the individual total RNA components. We demonstrate and evaluate an experimental method suitable for use in genome-scale process control and lay out a method utilizing spike-in controls to determine enriched RNA content of total RNA in samples.

Conclusions

Genome-scale process controls can be derived from mixtures. These controls relate prior knowledge of individual components to a complex mixture, allowing assessment of measurement performance. The target RNA fraction accounts for differential selection of RNA out of variable total RNA samples. Spike-in controls can be utilized to measure this relationship between target RNA content and input total RNA. Our mixture analysis method also enables estimation of the proportions of an unknown mixture, even when component-specific markers are not previously known, whenever pure components are measured alongside the mixture.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1912-7) contains supplementary material, which is available to authorized users.