Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM)

Molecular Profiling Defines Evolutionarily Conserved Transcription Factor Signatures of Major Vestibulospinal Neuron Groups

Vestibulospinal neurons are organized into discrete groups projecting from brainstem to spinal cord, enabling vertebrates to maintain proper balance and posture. The two largest groups are the lateral vestibulospinal tract (LVST) group and the contralateral medial vestibulospinal tract (cMVST) group, with different projection lateralities and functional roles. In search of a molecular basis for these differences, we performed RNA sequencing on LVST and cMVST neurons from mouse and chicken embryos followed by immunohistofluorescence validation. Focusing on transcription factor (TF)-encoding genes, we identified TF signatures that uniquely distinguish the LVST from the cMVST group and further parse different rhombomere-derived portions comprising the cMVST group. Immunohistofluorescence assessment of the CNS from spinal cord to cortex demonstrated that these TF signatures are restricted to the respective vestibulospinal groups and some neurons in their immediate vicinity. Collectively, these results link the combinatorial expression of TFs to developmental and functional subdivisions within the vestibulospinal system.

Gain-of-function mutation of microRNA-140 in human skeletal dysplasia

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression. Heterozygous loss-of-function point mutations of miRNA genes are associated with several human congenital disorders^1-5, but neomorphic (gain-of-new-function) mutations in miRNAs due to nucleotide substitutions have not been reported. Here we describe a neomorphic seed region mutation in the chondrocyte-specific, super-enhancer-associated MIR140 gene encoding microRNA-140 (miR-140) in a novel autosomal dominant human skeletal dysplasia. Mice with the corresponding single nucleotide substitution show skeletal abnormalities similar to those of the patients but distinct from those of miR-140-null mice⁶. This mutant miRNA gene yields abundant mutant miR-140-5p expression without miRNA-processing defects. In chondrocytes, the mutation causes widespread derepression of wild-type miR-140-5p targets and repression of mutant miR-140-5p targets, indicating that the mutation produces both loss-of-function and gain-of-function effects. Furthermore, the mutant miR-140-5p seed competes with the conserved RNA-binding protein Ybx1 for overlapping binding sites. This finding may explain the potent target repression and robust in vivo effect by this mutant miRNA even in the absence of evolutionary selection of miRNA-target RNA interactions, which contributes to the strong regulatory effects of conserved miRNAs^7,8. Our study presents the first case of a pathogenic gain-of-function miRNA mutation and provides molecular insight into neomorphic actions of emerging and/or mutant miRNAs.

pblat: a multithread blat algorithm speeding up aligning sequences to genomes

Background

The blat is a widely used sequence alignment tool. It is especially useful for aligning long sequences and gapped mapping, which cannot be performed properly by other fast sequence mappers designed for short reads. However, the blat tool is single threaded and when used to map whole genome or whole transcriptome sequences to reference genomes this program can take days to finish, making it unsuitable for large scale sequencing projects and iterative analysis. Here, we present pblat (parallel blat), a parallelized blat algorithm with multithread and cluster computing support, which functions to rapidly fine map large scale DNA/RNA sequences against genomes.

Results

The pblat algorithm takes advantage of modern multicore processors and significantly reduces the run time with the number of threads used. pblat utilizes almost equal amount of memory as when running blat. The results generated by pblat are identical with those generated by blat. The pblat tool is easy to install and can run on Linux and Mac OS systems. In addition, we provide a cluster version of pblat (pblat-cluster) running on computing clusters with MPI support.

Conclusion

pblat is open source and free available for non-commercial users. It is easy to install and easy to use. pblat and pblat-cluster would facilitate the high-throughput mapping of large scale genomic and transcript sequences to reference genomes with both high speed and high precision.

Fundamentals of RNA Analysis on Biobanked Specimens

Compared to DNA, analysis of RNA is one step closer on the central dogma of biology to assessing cellular function. This makes it an extremely valuable target for research and clinical testing in nearly all areas of molecular biology. Most RNA molecules are ephemeral by nature. They exist as temporary intermediates, ostensibly enabling data transfer between the genome and the organism. Their ribose backbone renders them sensitive to simple degradation over time and they are the target molecule for numerous and abundant ribonucleases which have evolved to chop them to pieces with extreme efficiency. At the biochemical level, this means that they degrade rapidly in most physiological and laboratory conditions and are thus challenging to study. When considering specimen banking, it is critical to keep this reality in mind, as some commonly used banking modalities will not adequately preserve the relevant RNA molecules in a measureable state.In this chapter, we explore the broad range of RNA testing methodologies in current use, with particular focus on how specimen preparation impacts analysis. Following an overview in the introduction, Subheading 2 covers the major specimen types amenable to RNA analysis in the context of biobanking. Subheading 3 discusses the applications of various RNA analysis modalities to research and clinical testing.

HOS15 Interacts with the Histone Deacetylase HDA9 and the Evening Complex to Epigenetically Regulate the Floral Activator GIGANTEA

In plants, seasonal inputs such as photoperiod and temperature modulate the plant's internal genetic program to regulate the timing of the developmental transition from vegetative to reproductive growth. This regulation of the floral transition involves chromatin remodeling, including covalent modification of histones. Here, we report that HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENE 15 (HOS15), a WD40 repeat protein, associates with a histone deacetylase complex to repress transcription of the GIGANTEA (GI)-mediated photoperiodic flowering pathway in Arabidopsis (Arabidopsis thaliana). Loss of function of HOS15 confers early flowering under long-day conditions because elevated GI expression. LUX ARRHYTHMO (LUX), a DNA binding transcription factor and component of the Evening Complex (EC), is important for the binding of HOS15 to the GI promoter. In wild type, HOS15 associates with the EC components LUX, EARLY FLOWERING 3 (ELF3), and ELF4 and the histone deacetylase HDA9 at the GI promoter, resulting in histone deacetylation and reduced GI expression. In the hos15-2 mutant, the levels of histone acetylation are elevated at the GI promoter, resulting in increased GI expression. Our data suggest that the HOS15-EC-HDA9 histone-modifying complex regulates photoperiodic flowering via the transcriptional repression of GI.

Specialized Plastids Trigger Tissue-Specific Signaling for Systemic Stress Response in Plants

Plastids comprise a complex set of organelles in plants that can undergo distinctive patterns of differentiation and redifferentiation during their lifespan. Plastids localized to the epidermis and vascular parenchyma are distinctive in size, structural features, and functions. These plastids are termed "sensory" plastids, and here we show their proteome to be distinct from chloroplasts, with specialized stress-associated features. The distinctive sensory plastid proteome in Arabidopsis (Arabidopsis thaliana) derives from spatiotemporal regulation of nuclear genes encoding plastid-targeted proteins. Perturbation caused by depletion of the sensory plastid-specific protein MutS HOMOLOG1 conditioned local, programmed changes in gene networks controlling chromatin, stress-related phytohormone, and circadian clock behavior and producing a global, systemic stress response in the plant. We posit that the sensory plastid participates in sensing environmental stress, integrating this sensory function with epigenetic and gene expression circuitry to condition heritable stress memory.

Aberrant splicing and defective mRNA production induced by somatic spliceosome mutations in myelodysplasia

Spliceosome mutations are frequently found in myelodysplasia. Splicing alterations induced by these mutations, their precise targets, and the effect at the transcript level have not been fully elucidated. Here we report transcriptomic analyses of 265 bone marrow samples from myelodysplasia patients, followed by a validation using CRISPR/Cas9-mediated gene editing and an assessment of nonsense-mediated decay susceptibility. Small but widespread reduction of intron-retaining isoforms is the most frequent splicing alteration in SF3B1-mutated samples. SF3B1 mutation is also associated with 3′ splice site alterations, leading to the most pronounced reduction of canonical transcripts. Target genes include tumor suppressors and genes of mitochondrial iron metabolism or heme biosynthesis. Alternative exon usage is predominant in SRSF2- and U2AF1-mutated samples. Usage of an EZH2 cryptic exon harboring a premature termination codon is increased in both SRSF2- and U2AF1-mutated samples. Our study reveals a landscape of splicing alterations and precise targets of various spliceosome mutations.

Mutations to the splicing machinery may have an important role in myelodysplasia. Here, the authors describe splicing factor gene mutations in myelodysplasia and report tumor suppressor, epigenetic, iron metabolism and heme biosynthesis genes as their targets.

When one becomes many-Alternative splicing in β-cell function and failure

Pancreatic β-cell dysfunction and death are determinant events in type 1 diabetes (T1D), but the molecular mechanisms behind β-cell fate remain poorly understood. Alternative splicing is a post-transcriptional mechanism by which a single gene generates different mRNA and protein isoforms, expanding the transcriptome complexity and enhancing protein diversity. Neuron-specific and certain serine/arginine-rich RNA binding proteins (RBP) are enriched in β-cells, playing crucial roles in the regulation of insulin secretion and β-cell survival. Moreover, alternative exon networks, regulated by inflammation or diabetes susceptibility genes, control key pathways and processes for the correct function and survival of β-cells. The challenge ahead of us is to understand the precise role of alternative splicing regulators and splice variants on β-cell function, dysfunction and death and develop tools to modulate it.

Indel detection from RNA-seq data: tool evaluation and strategies for accurate detection of actionable mutations

Driver somatic mutations are a hallmark of a tumor that can be used for diagnosis and targeted therapy. Mutations are primarily detected from tumor DNA. As dynamic molecules of gene activities, transcriptome profiling by RNA sequence (RNA-seq) is becoming increasingly popular, which not only measures gene expression but also structural variations such as mutations and fusion transcripts. Although single-nucleotide variants (SNVs) can be easily identified from RNA-seq, intermediate long insertions/deletions (indels  > 2 bases and less than sequence reads) cause significant challenges and are ignored by most RNA-seq analysis tools. This study evaluates commonly used RNA-seq analysis programs along with variant and somatic mutation callers in a series of data sets with simulated and known indels. The aim is to develop strategies for accurate indel detection. Our results show that the RNA-seq alignment is the most important step for indel identification and the evaluated programs have a wide range of sensitivity to map sequence reads with indels, from not at all to decently sensitive. The sensitivity is impacted by sequence read lengths. Most variant calling programs rely on hard evidence indels marked in the alignment and the programs with realignment may use soft-clipped reads for indel inferencing. Based on the observations, we have provided practical recommendations for indel detection when different RNA-seq aligners are used and demonstrated the best option with highly reliable results. With careful customization of bioinformatics algorithms, RNA-seq can be reliably used for both SNV and indel mutation detection that can be used for clinical decision-making.

iMapSplice: Alleviating reference bias through personalized RNA-seq alignment

Genomic variants in both coding and non-coding sequences can have functionally important and sometimes deleterious effects on exon splicing of gene transcripts. For transcriptome profiling using RNA-seq, the accurate alignment of reads across exon junctions is a critical step. Existing algorithms that utilize a standard reference genome as a template sometimes have difficulty in mapping reads that carry genomic variants. These problems can lead to allelic ratio biases and the failure to detect splice variants created by splice site polymorphisms. To improve RNA-seq read alignment, we have developed a novel approach called iMapSplice that enables personalized mRNA transcriptome profiling. The algorithm makes use of personal genomic information and performs an unbiased alignment towards genome indices carrying both reference and alternative bases. Importantly, this breaks the dependency on reference genome splice site dinucleotide motifs and enables iMapSplice to discover personal splice junctions created through splice site polymorphisms. We report comparative analyses using a number of simulated and real datasets. Besides general improvements in read alignment and splice junction discovery, iMapSplice greatly alleviates allelic ratio biases and unravels many previously uncharacterized splice junctions created by splice site polymorphisms, with minimal overhead in computation time and storage. Software download URL: https://github.com/LiuBioinfo/iMapSplice.

Detection and benchmarking of somatic mutations in cancer genomes using RNA-seq data

To detect functional somatic mutations in tumor samples, whole-exome sequencing (WES) is often used for its reliability and relative low cost. RNA-seq, while generally used to measure gene expression, can potentially also be used for identification of somatic mutations. However there has been little systematic evaluation of the utility of RNA-seq for identifying somatic mutations. Here, we develop and evaluate a pipeline for processing RNA-seq data from glioblastoma multiforme (GBM) tumors in order to identify somatic mutations. The pipeline entails the use of the STAR aligner 2-pass procedure jointly with MuTect2 from genome analysis toolkit (GATK) to detect somatic variants. Variants identified from RNA-seq data were evaluated by comparison against the COSMIC and dbSNP databases, and also compared to somatic variants identified by exome sequencing. We also estimated the putative functional impact of coding variants in the most frequently mutated genes in GBM. Interestingly, variants identified by RNA-seq alone showed better representation of GBM-related mutations cataloged by COSMIC. RNA-seq-only data substantially outperformed the ability of WES to reveal potentially new somatic mutations in known GBM-related pathways, and allowed us to build a high-quality set of somatic mutations common to exome and RNA-seq calls. Using RNA-seq data in parallel with WES data to detect somatic mutations in cancer genomes can thus broaden the scope of discoveries and lend additional support to somatic variants identified by exome sequencing alone.

Transcriptional profiling reveals extraordinary diversity among skeletal muscle tissues

Skeletal muscle comprises a family of diverse tissues with highly specialized functions. Many acquired diseases, including HIV and COPD, affect specific muscles while sparing others. Even monogenic muscular dystrophies selectively affect certain muscle groups. These observations suggest that factors intrinsic to muscle tissues influence their resistance to disease. Nevertheless, most studies have not addressed transcriptional diversity among skeletal muscles. Here we use RNAseq to profile mRNA expression in skeletal, smooth, and cardiac muscle tissues from mice and rats. Our data set, MuscleDB, reveals extensive transcriptional diversity, with greater than 50% of transcripts differentially expressed among skeletal muscle tissues. We detect mRNA expression of hundreds of putative myokines that may underlie the endocrine functions of skeletal muscle. We identify candidate genes that may drive tissue specialization, including Smarca4, Vegfa, and Myostatin. By demonstrating the intrinsic diversity of skeletal muscles, these data provide a resource for studying the mechanisms of tissue specialization.

About 40% of our weight is formed of skeletal muscles, the hundreds of muscles in our bodies that can be voluntarily controlled by our nervous system. At the moment, the research community largely sees all these muscles as a single group whose tissues are virtually interchangeable.

Yet, skeletal muscles have highly diverse origins, shapes and roles. For example, our diaphragm is a long muscle that contracts slowly and rhythmically so we can draw breaths, while tiny muscles in our eyes generate the short and precise movements of our eyeballs. Different skeletal muscles also respond in distinct ways to injuries, drugs and diseases. This suggests that these muscles may be diverse at the genetic level.

While all the cells in our body have the same genetic information, exactly which genes are turned on and off (or ‘expressed’) changes between types of cells. On top of this ‘on or off’ regulation, the level of expression of a gene – how active it is – can also differ. However, the studies that examine the differences in gene expression between tissues usually overlook skeletal muscles.

Here, Terry et al. use genetic techniques to measure how genes are expressed in over 20 types of muscle in mice and rats. The results show that the expression levels of over 50% of all the animals’ genes vary between muscles. In fact, any two types of muscles express on average 13% of their genes differently from each other. The analyses yield further unexpected findings. For example, the expression levels in a muscle in the foot that helps to flex the rodents’ toes are more similar to those found in eye muscles than to the ones observed in limb muscles. These conclusions indicate that skeletal muscles are a widely diverse family of tissues.

The research community will be able to use the data collected by Terry et al. to explore further the origins and the consequences of the differences between skeletal muscles. This could help researchers to understand why specific groups of muscles are more susceptible to disease, or react differently to a drug. This knowledge could also be exploited to refine approaches in tissue engineering, which aims to replace damaged muscles in the body.

Long-Term Persistence of Exhausted CD8 T Cells in Chronic Infection Is Regulated by MicroRNA-155

Persistent viral infections and tumors drive development of exhausted T (TEX) cells. In these settings, TEX cells establish an important host-pathogen or host-tumor stalemate. However, TEX cells erode over time, leading to loss of pathogen or cancer containment. We identified microRNA (miR)-155 as a key regulator of sustained TEX cell responses during chronic lymphocytic choriomeningitis virus (LCMV) infection. Genetic deficiency of miR-155 ablated CD8 T cell responses during chronic infection. Conversely, enhanced miR-155 expression promoted expansion and long-term persistence of TEX cells. However, rather than strictly antagonizing exhaustion, miR-155 promoted a terminal TEX cell subset. Transcriptional profiling identified coordinated control of cell signaling and transcription factor pathways, including the key AP-1 family member Fosl2. Overexpression of Fosl2 reversed the miR-155 effects, identifying a link between miR-155 and the AP-1 transcriptional program in regulating TEX cells. Thus, we identify a mechanism of miR-155 regulation of TEX cells and a key role for Fosl2 in T cell exhaustion.

Subepithelial telocytes are an important source of Wnts that supports intestinal crypts

Tissues that undergo rapid cellular turnover, such as the mammalian haematopoietic system or the intestinal epithelium, are dependent on stem and progenitor cells that proliferate to provide differentiated cells to maintain organismal health. Stem and progenitor cells, in turn, are thought to rely on signals and growth factors provided by local niche cells to support their function and self-renewal. Several cell types have been hypothesized to provide the signals required for the proliferation and differentiation of the intestinal stem cells in intestinal crypts^1-6. Here we identify subepithelial telocytes as an important source of Wnt proteins, without which intestinal stem cells cannot proliferate and support epithelial renewal. Telocytes are large but rare mesenchymal cells that are marked by expression of FOXL1 and form a subepithelial plexus that extends from the stomach to the colon. While supporting the entire epithelium, FOXL1⁺ telocytes compartmentalize the production of Wnt ligands and inhibitors to enable localized pathway activation. Conditional genetic ablation of porcupine (Porcn), which is required for functional maturation of all Wnt proteins, in mouse FOXL1⁺ telocytes causes rapid cessation of Wnt signalling to intestinal crypts, followed by loss of proliferation of stem and transit amplifying cells and impaired epithelial renewal. Thus, FOXL1⁺ telocytes are an important source of niche signals to intestinal stem cells.

Subepithelial telocytes are an important source of Wnts that supports intestinal crypts

Tissues with rapid cellular turnover, such as the mammalian hematopoietic system or the intestinal epithelium, are dependent upon stem and progenitor cells, which through proliferation provide differentiated cells to maintain organismal health. Stem and progenitor cells, in turn, are thought to rely upon signals and growth factors provided by local niche cells to support their function and self-renewal. Several cell types have been proposed to provide the signals required for the proliferation and differentiation of the ISC in the crypt^1–6. Here, we identify subepithelial telocytes as an important source of Wnt proteins, without which intestinal stem cells cannot proliferate and support epithelial renewal. Telocytes are large but rare mesenchymal cells that are marked by Foxl1 and PDGFRα expression and form a subepithelial plexus that extends from the stomach to the colon. While supporting the entire epithelium, Foxl1⁺ telocytes compartmentalize the production of Wnt ligands and inhibitors to enable localized pathway activation. Conditional gene ablation of Porcupine (Porcn), which is required for functional maturation of all Wnt proteins, in Foxl1⁺ telocytes causes rapid cessation of Wnt signaling to intestinal crypts, followed by loss of stem and transit amplifying cell proliferation and impaired epithelial renewal. Thus, Foxl1⁺ telocytes are an important source of niche signals to intestinal stem cells.

Outlier detection for improved differential splicing quantification from RNA-Seq experiments with replicates

Motivation

A key component in many RNA-Seq-based studies is contrasting multiple replicates from different experimental conditions. In this setup, replicates play a key role as they allow to capture underlying biological variability inherent to the compared conditions, as well as experimental variability. However, what constitutes a 'bad' replicate is not necessarily well defined. Consequently, researchers might discard valuable data or downstream analysis may be hampered by failed experiments.

Results

Here we develop a probability model to weigh a given RNA-Seq sample as a representative of an experimental condition when performing alternative splicing analysis. We demonstrate that this model detects outlier samples which are consistently and significantly different compared with other samples from the same condition. Moreover, we show that instead of discarding such samples the proposed weighting scheme can be used to downweight samples and specific splicing variations suspected as outliers, gaining statistical power. These weights can then be used for differential splicing (DS) analysis, where the resulting algorithm offers a generalization of the MAJIQ algorithm. Using both synthetic and real-life data, we perform an extensive evaluation of the improved MAJIQ algorithm in different scenarios involving perturbed samples, mislabeled samples, same condition groups, and different levels of coverage, showing it compares favorably to other tools. Overall, this work offers an outlier detection algorithm that can be combined with any splicing pipeline, a generalized and improved version of MAJIQ for DS detection, and evaluation metrics with matching code and data for DS algorithms.

Availability and implementation

Software and data are accessible via majiq.biociphers.org/norton_et_al_2017/.

Contact

yosephb@upenn.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

TRAP-seq identifies cystine/glutamate antiporter as a driver of recovery from liver injury

Understanding the molecular basis of the regenerative response following hepatic injury holds promise for improved treatment of liver diseases. Here, we report an innovative method to profile gene expression specifically in the hepatocytes that regenerate the liver following toxic injury. We used the Fah-/- mouse, a model of hereditary tyrosinemia, which conditionally undergoes severe liver injury unless fumarylacetoacetate hydrolase (FAH) expression is reconstituted ectopically. We used translating ribosome affinity purification followed by high-throughput RNA sequencing (TRAP-seq) to isolate mRNAs specific to repopulating hepatocytes. We uncovered upstream regulators and important signaling pathways that are highly enriched in genes changed in regenerating hepatocytes. Specifically, we found that glutathione metabolism, particularly the gene Slc7a11 encoding the cystine/glutamate antiporter (xCT), is massively upregulated during liver regeneration. Furthermore, we show that Slc7a11 overexpression in hepatocytes enhances, and its suppression inhibits, repopulation following toxic injury. TRAP-seq allows cell type-specific expression profiling in repopulating hepatocytes and identified xCT, a factor that supports antioxidant responses during liver regeneration. xCT has potential as a therapeutic target for enhancing liver regeneration in response to liver injury.

Bayesian nonparametric discovery of isoforms and individual specific quantification

Most human protein-coding genes can be transcribed into multiple distinct mRNA isoforms. These alternative splicing patterns encourage molecular diversity, and dysregulation of isoform expression plays an important role in disease etiology. However, isoforms are difficult to characterize from short-read RNA-seq data because they share identical subsequences and occur in different frequencies across tissues and samples. Here, we develop biisq, a Bayesian nonparametric model for isoform discovery and individual specific quantification from short-read RNA-seq data. biisq does not require isoform reference sequences but instead estimates an isoform catalog shared across samples. We use stochastic variational inference for efficient posterior estimates and demonstrate superior precision and recall for simulations compared to state-of-the-art isoform reconstruction methods. biisq shows the most gains for low abundance isoforms, with 36% more isoforms correctly inferred at low coverage versus a multi-sample method and 170% more versus single-sample methods. We estimate isoforms in the GEUVADIS RNA-seq data and validate inferred isoforms by associating genetic variants with isoform ratios.

Alternative splicing leads to transcript isoform diversity. Here, Aguiar et al. develop biisq, a Bayesian nonparametric approach to discover and quantify isoforms from RNA-seq data.

Systematic review of next-generation sequencing simulators: computational tools, features and perspectives

High-throughput next-generation sequencing (NGS) technologies have rapidly generated a large volume of genomic data. To aid the development and evaluation of new statistical models and computational methods, NGS-based simulators have been proposed to construct better experimental workflows. However, the comparative performance of these NGS simulators remains unclear. In this review, we conducted a comprehensive investigation of NGS simulators for various sequencing techniques, including DNA sequencing, metagenomic sequencing, RNA-seq, ChIP-seq and bisulfite sequencing for methylation.

Transcriptional profiling of synovium in a porcine model of early post-traumatic osteoarthritis

To determine the transcriptional profile of synovium during the molecular phase of post-traumatic osteoarthritis, anterior cruciate ligament transections (ACL) were performed in 36 Yucatan minipigs. Equal numbers were randomly assigned to no further treatment, ACL reconstruction or repair. Perimeniscal synovium for histopathology and RNA-sequencing was harvested at 1 and 4 weeks post-operatively and from six healthy control animals. Microscopic synovitis scores significantly worsened at 1 (p < 0.001) and 4 weeks (p = 0.003) post-surgery relative to controls, and were driven by intimal hyperplasia and increased stromal cellularity without inflammatory infiltrates. Synovitis scores were similar between no treatment, reconstruction, and repair groups (p ≥ 0.668). Relative to no treatment at 1 week, 88 and 367 genes were differentially expressed in the reconstruction and repair groups, respectively (227 and 277 at 4 weeks). Relative to controls and with the treatment groups pooled, 1,683 transcripts were concordantly differentially expressed throughout the post-surgery time-course. Affected pathways included, proteolysis_connective tissue degradation (including upregulations of protease-encoding MMP1, MMP13, and ADAMTS4), and development_cartilage development (including upregulations of ACAN, SOX9, and RUNX2), among others. Using linear regression, significant associations of post-surgery synovial expression levels of 20 genes with the articular cartilage glycosaminoglycan loss were identified. These genes were predominantly related to embryonic skeletal system development and included RUNX2. In conclusion, this study confirmed an increased synovial expression of genes that may serve as targets to prevent cartilage degradation, including MMP1, MMP13, and ADAMTS4, in knees with microscopic synovitis and cartilage proteoglycan loss. Attractive novel targets include regulators of embryonic developmental processes in synovium. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

FuSpot: a web-based tool for visual evaluation of fusion candidates

BACKGROUND

Gene fusions often occur in cancer cells and in some cases are the main driver of oncogenesis. Correct identification of oncogenic gene fusions thus has implications for targeted cancer therapy. Recognition of this potential has led to the development of a myriad of sequencing-based fusion detection tools. However, given the same input, many of these detectors will find different fusion points or claim different sets of supporting data. Furthermore, the rate at which these tools falsely detect fusion events in data varies greatly. This discrepancy between tools underscores the fact that computation algorithms still cannot perfectly evaluate evidence; especially when provided with small amounts of supporting data as is typical in fusion detection. We assert that when evidence is provided in an easily digestible form, humans are more proficient in identifying true positives from false positives.

RESULTS

We have developed a web tool that, given the genomic coordinates of a candidate fusion breakpoint, will extract fusion and non-fusion reads adjacent to the fusion point from partner transcripts, and color code reads by transcript origin and read orientation for ease of intuitive inspection by the user. Fusion partner transcript read alignments are performed using a novel variant of the Smith-Waterman algorithm.

CONCLUSIONS

Combined with dynamic filtering parameters, the visualization provided by our tool introduces a powerful new investigative step that allows researchers to comprehensively evaluate fusion evidence. Additionally, this allows quick identification of false positives that may deceive most fusion detectors, thus eliminating unnecessary gene fusion validation. We apply our visualization tool to publicly available datasets and provide examples of true as well as false positives reported by open source fusion detection tools.

DART: a fast and accurate RNA-seq mapper with a partitioning strategy

MOTIVATION

In recent years, the massively parallel cDNA sequencing (RNA-Seq) technologies have become a powerful tool to provide high resolution measurement of expression and high sensitivity in detecting low abundance transcripts. However, RNA-seq data requires a huge amount of computational efforts. The very fundamental and critical step is to align each sequence fragment against the reference genome. Various de novo spliced RNA aligners have been developed in recent years. Though these aligners can handle spliced alignment and detect splice junctions, some challenges still remain to be solved. With the advances in sequencing technologies and the ongoing collection of sequencing data in the ENCODE project, more efficient alignment algorithms are highly demanded. Most read mappers follow the conventional seed-and-extend strategy to deal with inexact matches for sequence alignment. However, the extension is much more time consuming than the seeding step.

RESULTS

We proposed a novel RNA-seq de novo mapping algorithm, call DART, which adopts a partitioning strategy to avoid the extension step. The experiment results on synthetic datasets and real NGS datasets showed that DART is a highly efficient aligner that yields the highest or comparable sensitivity and accuracy compared to most state-of-the-art aligners, and more importantly, it spends the least amount of time among the selected aligners.

AVAILABILITY AND IMPLEMENTATION

https://github.com/hsinnan75/DART.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Prospective Advances in Circular RNA Investigation

circRNAs have emerged as one of the key regulators in many cellular mechanisms and pathogenesis of diseases. However, with the limited knowledge and current technologies for circRNA investigations, there are several challenges that need to be addressed for. These include challenges in understanding the regulation of circRNA biogenesis, experimental designs, and sample preparations to characterize the circRNAs in diseases as well as the bioinformatics pipelines and algorithms. In this chapter, we discussed the above challenges and possible strategies to overcome those limitations. We also addressed the differences between the existing applications and technologies to study the circRNAs in diseases. By addressing these challenges, further understanding of circRNAs roles and regulations as well as the discovery of novel circRNAs could be achieved.

Current and Future Methods for mRNA Analysis: A Drive Toward Single Molecule Sequencing

The transcriptome encompasses a range of species including messenger RNA, and other noncoding RNA such as rRNA, tRNA, and short and long noncoding RNAs. Due to the huge role played by mRNA in development and disease, several methods have been developed to sequence and characterize mRNA, with RNA sequencing (RNA-Seq) emerging as the current method of choice particularly for large high-throughput studies. Short-read RNA-Seq which involves sequencing of short cDNA fragments and computationally assembling them to reconstruct the transcriptome, or aligning them to a reference is the most widely used approach. However, due to inherent limitations of this approach in de novo transcriptome assembly and isoform quantification, long-read RNA-Seq approaches, which also happen to be single molecule sequencing approaches, are increasingly becoming the standard for de novo transcriptome assembly and isoform quantification. In this chapter, we review the technical aspects of the current methods of RNA-Seq, both short and long-read approaches, and data analysis methods available. We discuss recent advances in single-cell RNA-Seq and direct RNA-Seq approaches, which perhaps will dominate the future of RNA-Seq.

Transcriptional profiling of articular cartilage in a porcine model of early post-traumatic osteoarthritis

To identify the molecular pathophysiology present in early post-traumatic osteoarthritis (PTOA), the transcriptional profile of articular cartilage and its response to surgical PTOA induction were determined. Thirty six Yucatan minipigs underwent anterior cruciate ligament (ACL) transection and were randomly assigned in equal numbers to no further treatment, reconstruction or ligament repair. Cartilage was harvested at 1 and 4 weeks post-operatively and histology and RNA-sequencing were performed and compared to controls. Microscopic cartilage scores significantly worsened at 1 (p = 0.028) and 4 weeks (p = 0.001) post-surgery relative to controls, but did not differ between untreated, reconstruction or repair groups. Gene expression after ACL reconstruction and ACL transection were similar, with only 0.03% (including SERPINB7 and CR2) and 0.2% of transcripts (including INHBA) differentially expressed at 1 and 4 weeks respectively. COL2A1, COMP, SPARC, CHAD, and EF1ALPHA were the most highly expressed non ribosomal, non mitochondrial genes in the controls and remained abundant after surgery. A total of 1,275 genes were differentially expressed between 1 and 4 weeks post-surgery. With the treatment groups pooled, 682 genes were differentially expressed at both time-points, with the most significant changes observed in MMP1, COCH, POSTN, CYTL1, and PTGFR. This study confirmed the development of a microscopic PTOA stage after ACL surgery in the porcine model. Upregulation of multiple proteases (including MMP1 and ADAMTS4) were found; however, the level of expression remained orders of magnitude below that of extracellular matrix protein-coding genes (including COL2A1 and ACAN). In summary, genes with established roles in PTOA as well as novel targets for specific intervention were identified. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:318-329, 2018.

Involvement of Innate Immune System in Late Stages of Inherited Photoreceptor Degeneration

Retinitis pigmentosa (RP) is a group of inherited retinal degenerations that lead to progressive vision loss. Many mutations in 60 different genes have been shown to cause RP. Given the diversity of genes and mutations that cause RP, corrective gene therapy approaches currently in development may prove both time-consuming and cost-prohibitive for treatment of all forms of RP. An alternative approach is to find common biological pathways that cause retinal degeneration in various forms of RP, and identify new molecular targets. With this goal, we analyzed the retinal transcriptome of two non-allelic forms of RP in dogs, rcd1 and xlpra2, at clinically relevant advanced stages of the two diseases. Both diseases showed very similar trends in changes in gene expression compared to control normal dogs. Pathway analysis revealed upregulation of various components of the innate immune system in both diseases, including inflammasome and complement pathways. Our results show that the retinal transcriptome at advanced stages of RP is very similar to that of other retinal degenerative diseases such as age-related macular degeneration and diabetic retinopathy. Thus, drugs and therapeutics already in development for targeting these retinopathies may also prove useful for the treatment of many forms of RP.

Rail-RNA: scalable analysis of RNA-seq splicing and coverage

MOTIVATION

RNA sequencing (RNA-seq) experiments now span hundreds to thousands of samples. Current spliced alignment software is designed to analyze each sample separately. Consequently, no information is gained from analyzing multiple samples together, and it requires extra work to obtain analysis products that incorporate data from across samples.

RESULTS

We describe Rail-RNA, a cloud-enabled spliced aligner that analyzes many samples at once. Rail-RNA eliminates redundant work across samples, making it more efficient as samples are added. For many samples, Rail-RNA is more accurate than annotation-assisted aligners. We use Rail-RNA to align 667 RNA-seq samples from the GEUVADIS project on Amazon Web Services in under 16 h for US$0.91 per sample. Rail-RNA outputs alignments in SAM/BAM format; but it also outputs (i) base-level coverage bigWigs for each sample; (ii) coverage bigWigs encoding normalized mean and median coverages at each base across samples analyzed; and (iii) exon-exon splice junctions and indels (features) in columnar formats that juxtapose coverages in samples in which a given feature is found. Supplementary outputs are ready for use with downstream packages for reproducible statistical analysis. We use Rail-RNA to identify expressed regions in the GEUVADIS samples and show that both annotated and unannotated (novel) expressed regions exhibit consistent patterns of variation across populations and with respect to known confounding variables.

AVAILABILITY AND IMPLEMENTATION

Rail-RNA is open-source software available at http://rail.bio.

CONTACTS

anellore@gmail.com or langmea@cs.jhu.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Gene expression and risk of leukemic transformation in myelodysplasia

Through a comprehensive transcriptomic analysis, we discovered 2 major subgroups of myelodysplasia defined by gene expression profiles. The gene expression–based subgroups had independent prognostic value, which was validated in an external cohort.

Pancreatic Inflammation Redirects Acinar to β Cell Reprogramming

Using a transgenic mouse model to express MafA, Pdx1, and Neurog3 (3TF) in a pancreatic acinar cell- and doxycycline-dependent manner, we discovered that the outcome of transcription factor-mediated acinar to β-like cellular reprogramming is dependent on both the magnitude of 3TF expression and on reprogramming-induced inflammation. Overly robust 3TF expression causes acinar cell necrosis, resulting in marked inflammation and acinar-to-ductal metaplasia. Generation of new β-like cells requires limiting reprogramming-induced inflammation, either by reducing 3TF expression or by eliminating macrophages. The new β-like cells were able to reverse streptozotocin-induced diabetes 6 days after inducing 3TF expression but failed to sustain their function after removal of the reprogramming factors.

The combinatorial control of alternative splicing in C. elegans

Normal development requires the right splice variants to be made in the right tissues at the right time. The core splicing machinery is engaged in all splicing events, but which precise splice variant is made requires the choice between alternative splice sites—for this to occur, a set of splicing factors (SFs) must recognize and bind to short RNA motifs in the pre-mRNA. In C. elegans, there is known to be extensive variation in splicing patterns across development, but little is known about the targets of each SF or how multiple SFs combine to regulate splicing. Here we combine RNA-seq with in vitro binding assays to study how 4 different C. elegans SFs, ASD-1, FOX-1, MEC-8, and EXC-7, regulate splicing. The 4 SFs chosen all have well-characterised biology and well-studied loss-of-function genetic alleles, and all contain RRM domains. Intriguingly, while the SFs we examined have varied roles in C. elegans development, they show an unexpectedly high overlap in their targets. We also find that binding sites for these SFs occur on the same pre-mRNAs more frequently than expected suggesting extensive combinatorial control of splicing. We confirm that regulation of splicing by multiple SFs is often combinatorial and show that this is functionally significant. We also find that SFs appear to combine to affect splicing in two modes—they either bind in close proximity within the same intron or they appear to bind to separate regions of the intron in a conserved order. Finally, we find that the genes whose splicing are regulated by multiple SFs are highly enriched for genes involved in the cytoskeleton and in ion channels that are key for neurotransmission. Together, this shows that specific classes of genes have complex combinatorial regulation of splicing and that this combinatorial regulation is critical for normal development to occur.

Alternative splicing (AS) is a highly regulated process that is crucial for normal development. It requires the core splicing machinery, but the specific choice of splice site during AS is controlled by splicing factors (SFs) such as ELAV or RBFOX proteins that bind to specific sequences in pre-mRNAs to regulate usage of different splice sites. AS varies across the C. elegans life cycle and here we study how diverse SFs combine to regulate AS during C. elegans development. We selected 4 RRM-containing SFs that are all well studied and that have well-characterised loss-of-function genetic alleles. We find that these SFs regulate many of the same targets, and that combinatorial interactions between these SFs affect both individual splicing events and organism-level phenotypes including specific effects on the neuromuscular system. We further show that SFs combine to regulate splicing of an individual pre-mRNA in two distinct modes—either by binding in close proximity or by binding in a defined order on the pre-mRNA. Finally, we find that the genes whose splicing are most likely to be regulated by multiple SFs are genes that are required for the proper function of the neuromuscular system. These genes are also most likely to have changing AS patterns across development, suggesting that their splicing regulation is highly complex and developmentally regulated. Taken together, our data show that the precise splice variant expressed at any point in development is often the outcome of regulation by multiple SFs.

ESRP1 Mutations Cause Hearing Loss due to Defects in Alternative Splicing that Disrupt Cochlear Development

Alternative splicing contributes to gene expression dynamics in many tissues, yet its role in auditory development remains unclear. We performed whole-exome sequencing in individuals with sensorineural hearing loss (SNHL) and identified pathogenic mutations in Epithelial Splicing-Regulatory Protein 1 (ESRP1). Patient-derived induced pluripotent stem cells showed alternative splicing defects that were restored upon repair of an ESRP1 mutant allele. To determine how ESRP1 mutations cause hearing loss, we evaluated Esrp1-/- mouse embryos and uncovered alterations in cochlear morphogenesis, auditory hair cell differentiation, and cell fate specification. Transcriptome analysis revealed impaired expression and splicing of genes with essential roles in cochlea development and auditory function. Aberrant splicing of Fgfr2 blocked stria vascularis formation due to erroneous ligand usage, which was corrected by reducing Fgf9 gene dosage. These findings implicate mutations in ESRP1 as a cause of SNHL and demonstrate the complex interplay between alternative splicing, inner ear development, and auditory function.

ExpressionDB: An open source platform for distributing genome-scale datasets

RNA-sequencing (RNA-seq) and microarrays are methods for measuring gene expression across the entire transcriptome. Recent advances have made these techniques practical and affordable for essentially any laboratory with experience in molecular biology. A variety of computational methods have been developed to decrease the amount of bioinformatics expertise necessary to analyze these data. Nevertheless, many barriers persist which discourage new labs from using functional genomics approaches. Since high-quality gene expression studies have enduring value as resources to the entire research community, it is of particular importance that small labs have the capacity to share their analyzed datasets with the research community. Here we introduce ExpressionDB, an open source platform for visualizing RNA-seq and microarray data accommodating virtually any number of different samples. ExpressionDB is based on Shiny, a customizable web application which allows data sharing locally and online with customizable code written in R. ExpressionDB allows intuitive searches based on gene symbols, descriptions, or gene ontology terms, and it includes tools for dynamically filtering results based on expression level, fold change, and false-discovery rates. Built-in visualization tools include heatmaps, volcano plots, and principal component analysis, ensuring streamlined and consistent visualization to all users. All of the scripts for building an ExpressionDB with user-supplied data are freely available on GitHub, and the Creative Commons license allows fully open customization by end-users. We estimate that a demo database can be created in under one hour with minimal programming experience, and that a new database with user-supplied expression data can be completed and online in less than one day.

Single-cell analysis identifies cellular markers of the HIV permissive cell

Cellular permissiveness to HIV infection is highly heterogeneous across individuals. Heterogeneity is also found across CD4+ T cells from the same individual, where only a fraction of cells gets infected. To explore the basis of permissiveness, we performed single-cell RNA-seq analysis of non-infected CD4+ T cells from high and low permissive individuals. Transcriptional heterogeneity translated in a continuum of cell states, driven by T-cell receptor-mediated cell activation and was strongly linked to permissiveness. Proteins expressed at the cell surface and displaying the highest correlation with T cell activation were tested as biomarkers of cellular permissiveness to HIV. FACS sorting using antibodies against several biomarkers of permissiveness led to an increase of HIV cellular infection rates. Top candidate biomarkers included CD25, a canonical activation marker. The combination of CD25 high expression with other candidate biomarkers led to the identification of CD298, CD63 and CD317 as the best biomarkers for permissiveness. CD25highCD298highCD63highCD317high cell population showed an enrichment of HIV-infection of up to 28 fold as compared to the unsorted cell population. The purified hyper-permissive cell subpopulation was characterized by a downregulation of interferon-induced genes and several known restriction factors. Single-cell RNA-seq analysis coupled with functional characterization of cell biomarkers provides signatures of the "HIV-permissive cell".

Transcriptomes and neurotransmitter profiles of classes of gustatory and somatosensory neurons in the geniculate ganglion

Taste buds are innervated by neurons whose cell bodies reside in cranial sensory ganglia. Studies on the functional properties and connectivity of these neurons are hindered by the lack of markers to define their molecular identities and classes. The mouse geniculate ganglion contains chemosensory neurons innervating lingual and palatal taste buds and somatosensory neurons innervating the pinna. Here, we report single cell RNA sequencing of geniculate ganglion neurons. Using unbiased transcriptome analyses, we show a pronounced separation between two major clusters which, by anterograde labeling, correspond to gustatory and somatosensory neurons. Among the gustatory neurons, three subclusters are present, each with its own complement of transcription factors and neurotransmitter response profiles. The smallest subcluster expresses both gustatory- and mechanosensory-related genes, suggesting a novel type of sensory neuron. We identify several markers to help dissect the functional distinctions among gustatory neurons and address questions regarding target interactions and taste coding.Characterization of gustatory neural pathways has suffered due to a lack of molecular markers. Here, the authors report single cell RNA sequencing and unbiased transcriptome analyses to reveal major distinctions between gustatory and somatosensory neurons and subclusters of gustatory neurons with unique molecular and functional profiles.

Transcriptomes and neurotransmitter profiles of classes of gustatory and somatosensory neurons in the geniculate ganglion

Taste buds are innervated by neurons whose cell bodies reside in cranial sensory ganglia. Studies on the functional properties and connectivity of these neurons are hindered by the lack of markers to define their molecular identities and classes. The mouse geniculate ganglion contains chemosensory neurons innervating lingual and palatal taste buds and somatosensory neurons innervating the pinna. Here, we report single cell RNA sequencing of geniculate ganglion neurons. Using unbiased transcriptome analyses, we show a pronounced separation between two major clusters which, by anterograde labeling, correspond to gustatory and somatosensory neurons. Among the gustatory neurons, three subclusters are present, each with its own complement of transcription factors and neurotransmitter response profiles. The smallest subcluster expresses both gustatory- and mechanosensory-related genes, suggesting a novel type of sensory neuron. We identify several markers to help dissect the functional distinctions among gustatory neurons and address questions regarding target interactions and taste coding.

Characterization of gustatory neural pathways has suffered due to a lack of molecular markers. Here, the authors report single cell RNA sequencing and unbiased transcriptome analyses to reveal major distinctions between gustatory and somatosensory neurons and subclusters of gustatory neurons with unique molecular and functional profiles.

DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates

Motivation

High-throughput mRNA sequencing (RNA-Seq) is a powerful tool for quantifying gene expression. Identification of transcript isoforms that are differentially expressed in different conditions, such as in patients and healthy subjects, can provide insights into the molecular basis of diseases. Current transcript quantification approaches, however, do not take advantage of the shared information in the biological replicates, potentially decreasing sensitivity and accuracy.

Results

We present a novel hierarchical Bayesian model called Differentially Expressed Isoform detection from Multiple biological replicates (DEIsoM) for identifying differentially expressed (DE) isoforms from multiple biological replicates representing two conditions, e.g. multiple samples from healthy and diseased subjects. DEIsoM first estimates isoform expression within each condition by (1) capturing common patterns from sample replicates while allowing individual differences, and (2) modeling the uncertainty introduced by ambiguous read mapping in each replicate. Specifically, we introduce a Dirichlet prior distribution to capture the common expression pattern of replicates from the same condition, and treat the isoform expression of individual replicates as samples from this distribution. Ambiguous read mapping is modeled as a multinomial distribution, and ambiguous reads are assigned to the most probable isoform in each replicate. Additionally, DEIsoM couples an efficient variational inference and a post-analysis method to improve the accuracy and speed of identification of DE isoforms over alternative methods. Application of DEIsoM to an hepatocellular carcinoma (HCC) dataset identifies biologically relevant DE isoforms. The relevance of these genes/isoforms to HCC are supported by principal component analysis (PCA), read coverage visualization, and the biological literature.

Availability and implementation

The software is available at https://github.com/hao-peng/DEIsoM

Supplementary information

Supplementary data are available at Bioinformatics online.

RNA sequencing in post-mortem human brains of neuropsychiatric disorders

RNA sequencing (RNA-Seq), a revolutionary tool for transcriptome profiling, is becoming increasingly important for neuroscientists in studying the transcriptional landscape of the human brain. Studies using this next-generation sequencing technique have already revealed novel insights into the complexity of neurons in the human brain and pathogenesis of complex neurological diseases. In clinical neuroscience, RNA-Seq provides exciting opportunities for improving diagnosis and treatment of neurological diseases by facilitating the development of pharmacotherapies able to modulate gene expression. Furthermore, integrative whole genome sequencing and transcriptome sequencing can provide additional information for the functional role of mutated genes, prioritization of variants, and intron/exon splicing. This review describes the current state of RNA-Seq studies in neuropsychiatric disorders using post-mortem human brains, a brief survey of best practices for experimental design and sequencing data analysis, and the challenges associated with its application in the human brain.

SimBA: A methodology and tools for evaluating the performance of RNA-Seq bioinformatic pipelines

Background

The evolution of next-generation sequencing (NGS) technologies has led to increased focus on RNA-Seq. Many bioinformatic tools have been developed for RNA-Seq analysis, each with unique performance characteristics and configuration parameters. Users face an increasingly complex task in understanding which bioinformatic tools are best for their specific needs and how they should be configured. In order to provide some answers to these questions, we investigate the performance of leading bioinformatic tools designed for RNA-Seq analysis and propose a methodology for systematic evaluation and comparison of performance to help users make well informed choices.

Results

To evaluate RNA-Seq pipelines, we developed a suite of two benchmarking tools. SimCT generates simulated datasets that get as close as possible to specific real biological conditions accompanied by the list of genomic incidents and mutations that have been inserted. BenchCT then compares the output of any bioinformatics pipeline that has been run against a SimCT dataset with the simulated genomic and transcriptional variations it contains to give an accurate performance evaluation in addressing specific biological question. We used these tools to simulate a real-world genomic medicine question s involving the comparison of healthy and cancerous cells. Results revealed that performance in addressing a particular biological context varied significantly depending on the choice of tools and settings used. We also found that by combining the output of certain pipelines, substantial performance improvements could be achieved.

Conclusion

Our research emphasizes the importance of selecting and configuring bioinformatic tools for the specific biological question being investigated to obtain optimal results. Pipeline designers, developers and users should include benchmarking in the context of their biological question as part of their design and quality control process. Our SimBA suite of benchmarking tools provides a reliable basis for comparing the performance of RNA-Seq bioinformatics pipelines in addressing a specific biological question. We would like to see the creation of a reference corpus of data-sets that would allow accurate comparison between benchmarks performed by different groups and the publication of more benchmarks based on this public corpus. SimBA software and data-set are available at http://cractools.gforge.inria.fr/softwares/simba/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1831-5) contains supplementary material, which is available to authorized users.

A comparison of Illumina and Ion Torrent sequencing platforms in the context of differential gene expression

Background

Though Illumina has largely dominated the RNA-Seq field, the simultaneous availability of Ion Torrent has left scientists wondering which platform is most effective for differential gene expression (DGE) analysis. Previous investigations of this question have typically used reference samples derived from cell lines and brain tissue, and do not involve biological variability. While these comparisons might inform studies of tissue-specific expression, marked by large-scale transcriptional differences, this is not the common use case.

Results

Here we employ a standard treatment/control experimental design, which enables us to evaluate these platforms in the context of the expression differences common in differential gene expression experiments. Specifically, we assessed the hepatic inflammatory response of mice by assaying liver RNA from control and IL-1β treated animals with both the Illumina HiSeq and the Ion Torrent Proton sequencing platforms. We found the greatest difference between the platforms at the level of read alignment, a moderate level of concordance at the level of DGE analysis, and nearly identical results at the level of differentially affected pathways. Interestingly, we also observed a strong interaction between sequencing platform and choice of aligner. By aligning both real and simulated Illumina and Ion Torrent data with the twelve most commonly-cited aligners in the literature, we observed that different aligner and platform combinations were better suited to probing different genomic features; for example, disentangling the source of expression in gene-pseudogene pairs.

Conclusions

Taken together, our results indicate that while Illumina and Ion Torrent have similar capacities to detect changes in biology from a treatment/control experiment, these platforms may be tailored to interrogate different transcriptional phenomena through careful selection of alignment software.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4011-0) contains supplementary material, which is available to authorized users.

C. elegans SUP-46, an HNRNPM family RNA-binding protein that prevents paternally-mediated epigenetic sterility

BACKGROUND

In addition to DNA, gametes contribute epigenetic information in the form of histones and non-coding RNA. Epigenetic programs often respond to stressful environmental conditions and provide a heritable history of ancestral stress that allows for adaptation and propagation of the species. In the nematode C. elegans, defective epigenetic transmission often manifests as progressive germline mortality. We previously isolated sup-46 in a screen for suppressors of the hexosamine pathway gene mutant, gna-2(qa705). In this study, we examine the role of SUP-46 in stress resistance and progressive germline mortality.

RESULTS

We identified SUP-46 as an HNRNPM family RNA-binding protein, and uncovered a highly novel role for SUP-46 in preventing paternally-mediated progressive germline mortality following mating. Proximity biotinylation profiling of human homologs (HNRNPM, MYEF2) identified proteins of ribonucleoprotein complexes previously shown to contain non-coding RNA. Like HNRNPM and MYEF2, SUP-46 was associated with multiple RNA granules, including stress granules, and also formed granules on active chromatin. SUP-46 depletion disrupted germ RNA granules and caused ectopic sperm, increased sperm transcripts, and chronic heat stress sensitivity. SUP-46 was also required for resistance to acute heat stress, and a conserved "MYEF2" motif was identified that was needed for stress resistance.

CONCLUSIONS

In mammals, non-coding RNA from the sperm of stressed males has been shown to recapitulate paternal stress phenotypes in the offspring. Our results suggest that HNRNPM family proteins enable stress resistance and paternally-mediated epigenetic transmission that may be conserved across species.

Gene expression profiles of brain endothelial cells during embryonic development at bulk and single-cell levels

The blood-brain barrier is a dynamic interface that separates the brain from the circulatory system, and it is formed by highly specialized endothelial cells. To explore the molecular mechanisms defining the unique nature of vascular development and differentiation in the brain, we generated high-resolution gene expression profiles of mouse embryonic brain endothelial cells using translating ribosome affinity purification and single-cell RNA sequencing. We compared the brain vascular translatome with the vascular translatomes of other organs and analyzed the vascular translatomes of the brain at different time points during embryonic development. Because canonical Wnt signaling is implicated in the formation of the blood-brain barrier, we also compared the brain endothelial translatome of wild-type mice with that of mice lacking the transcriptional cofactor β-catenin (Ctnnb1). Our analysis revealed extensive molecular changes during the embryonic development of the brain endothelium. We identified genes encoding brain endothelium-specific transcription factors (Foxf2, Foxl2, Foxq1, Lef1, Ppard, Zfp551, and Zic3) that are associated with maturation of the blood-brain barrier and act downstream of the Wnt-β-catenin signaling pathway. Profiling of individual brain endothelial cells revealed substantial heterogeneity in the population. Nevertheless, the high abundance of Foxf2, Foxq1, Ppard, or Zic3 transcripts correlated with the increased expression of genes encoding markers of brain endothelial cell differentiation. Expression of Foxf2 and Zic3 in human umbilical vein endothelial cells induced the production of blood-brain barrier differentiation markers. This comprehensive data set may help to improve the engineering of in vitro blood-brain barrier models.

Immediate Administration of Intraarticular Triamcinolone Acetonide After Joint Injury Modulates Molecular Outcomes Associated With Early Synovitis

OBJECTIVE

To test whether intraarticular corticosteroid injection mitigates injury-induced synovitis and collagen degradation after anterior cruciate ligament transection (ACLT) and to characterize the synovial response using a functional genomics approach in a preclinical model of posttraumatic osteoarthritis.

METHODS

Yorkshire pigs underwent unilateral ACLT without subsequent corticosteroid injection (the ACLT group; n = 6) or ACLT with immediate injection of 20 mg triamcinolone acetonide (the steroid group; n = 6). A control group of pigs (the intact group; n = 6) did not undergo surgery. Total synovial membrane cellularity and synovial fluid concentration of C1,2C neoepitope-bearing collagen fragments 14 days after injury were primary end points and were compared between the ACLT, steroid, and intact groups. Cells were differentiated by histologic phenotype and counted, while RNA sequencing was used to quantify transcriptome-wide gene expression and monocyte, macrophage, and lymphocyte markers.

RESULTS

In the intact group, total cellularity was 13% (95% confidence interval [95% CI] 9-16) and the C1,2C concentration was 0.24 μg/ml (95% CI 0.08-0.39). In the ACLT group, significant increases were observed in total cellularity (to 21% [95% CI 16-27]) and C1,2C concentration (to 0.49 μg/ml [95% CI 0.39-0.59]). Compared to values in the ACLT group, total cellularity in the steroid group was nonsignificantly decreased to 17% (95% CI 15-18) (P = 0.26) and C1,2C concentration in the steroid group was significantly decreased to 0.29 μg/ml (95% CI 0.23-0.35) (P = 0.04). A total of 255 protein-coding transcripts were differentially expressed between the ACLT group and the intact group. These genes mainly enriched pathways related to cellular immune response, proteolysis, and angiogenesis. Mononuclear leukocytes were the dominant cell type in cell-dense areas. MARCO, SOCS3, CCR1, IL4R, and MMP2 expression was significantly associated with C1,2C levels.

CONCLUSION

Early intraarticular immunosuppression mitigated injury-induced increases in collagen fragments, an outcome better predicted by specific marker expression than by histologic measures of synovitis.

Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review

High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

Generation of a microglial developmental index in mice and in humans reveals a sex difference in maturation and immune reactivity

Evidence suggests many neurological disorders emerge when normal neurodevelopmental trajectories are disrupted, i.e., when circuits or cells do not reach their fully mature state. Microglia play a critical role in normal neurodevelopment and are hypothesized to contribute to brain disease. We used whole transcriptome profiling with Next Generation sequencing of purified developing microglia to identify a microglial developmental gene expression program involving thousands of genes whose expression levels change monotonically (up or down) across development. Importantly, the gene expression program was delayed in males relative to females and exposure of adult male mice to LPS, a potent immune activator, accelerated microglial development in males. Next, a microglial developmental index (MDI) generated from gene expression patterns obtained from purified mouse microglia, was applied to human brain transcriptome datasets to test the hypothesis that variability in microglial development is associated with human diseases such as Alzheimer's and autism where microglia have been suggested to play a role. MDI was significantly increased in both Alzheimer's Disease and in autism, suggesting that accelerated microglial development may contribute to neuropathology. In conclusion, we identified a microglia-specific gene expression program in mice that was used to create a microglia developmental index, which was applied to human datasets containing heterogeneous cell types to reveal differences between healthy and diseased brain samples, and between males and females. This powerful tool has wide ranging applicability to examine microglial development within the context of disease and in response to other variables such as stress and pharmacological treatments.

Detecting circular RNAs: bioinformatic and experimental challenges

The pervasive expression of circular RNAs (circRNAs) is a recently discovered feature of gene expression in highly diverged eukaryotes. Numerous algorithms that are used to detect genome-wide circRNA expression from RNA sequencing (RNA-seq) data have been developed in the past few years, but there is little overlap in their predictions and no clear gold-standard method to assess the accuracy of these algorithms. We review sources of experimental and bioinformatic biases that complicate the accurate discovery of circRNAs and discuss statistical approaches to address these biases. We conclude with a discussion of the current experimental progress on the topic.

Drosophila melanogaster retrotransposon and inverted repeat-derived endogenous siRNAs are differentially processed in distinct cellular locations

BACKGROUND

Endogenous small interfering (esi)RNAs repress mRNA levels and retrotransposon mobility in Drosophila somatic cells by poorly understood mechanisms. 21 nucleotide esiRNAs are primarily generated from retrotransposons and two inverted repeat (hairpin) loci in Drosophila culture cells in a Dicer2 dependent manner. Additionally, proteins involved in 3' end processing, such as Symplekin, CPSF73 and CPSR100, have been recently implicated in the esiRNA pathway.

RESULTS

Here we present evidence of overlap between two essential RNA metabolic pathways: esiRNA biogenesis and mRNA 3' end processing. We have identified a nucleus-specific interaction between the essential esiRNA cleavage enzyme Dicer2 (Dcr2) and Symplekin, a component of the core cleavage complex (CCC) required for 3' end processing of all eukaryotic mRNAs. This interaction is mediated by the N-terminal 271 amino acids of Symplekin; CCC factors CPSF73 and CPSF100 do not contact Dcr2. While Dcr2 binds the CCC, Dcr2 knockdown does not affect mRNA 3' end formation. RNAi-depletion of CCC components Symplekin and CPSF73 causes perturbations in esiRNA abundance that correlate with fluctuations in retrotransposon and hairpin esiRNA precursor levels. We also discovered that esiRNAs generated from retrotransposons and hairpins have distinct physical characteristics including a higher predominance of 22 nucleotide hairpin-derived esiRNAs and differences in 3' and 5' base preference. Additionally, retrotransposon precursors and derived esiRNAs are highly enriched in the nucleus while hairpins and hairpin derived esiRNAs are predominantly cytoplasmic similar to canonical mRNAs. RNAi-depletion of either CPSF73 or Symplekin results in nuclear retention of both hairpin and retrotransposon precursors suggesting that polyadenylation indirectly affects cellular localization of Dcr2 substrates.

CONCLUSIONS

Together, these observations support a novel mechanism in which differences in localization of esiRNA precursors impacts esiRNA biogenesis. Hairpin-derived esiRNAs are generated in the cytoplasm independent of Dcr2-Symplekin interactions, while retrotransposons are processed in the nucleus.

Achilles is a circadian clock-controlled gene that regulates immune function in Drosophila

The circadian clock is a transcriptional/translational feedback loop that drives the rhythmic expression of downstream mRNAs. Termed "clock-controlled genes," these molecular outputs of the circadian clock orchestrate cellular, metabolic, and behavioral rhythms. As part of our on-going work to characterize key upstream regulators of circadian mRNA expression, we have identified a novel clock-controlled gene in Drosophila melanogaster, Achilles (Achl), which is rhythmic at the mRNA level in the brain and which represses expression of antimicrobial peptides in the immune system. Achilles knock-down in neurons dramatically elevates expression of crucial immune response genes, including IM1 (Immune induced molecule 1), Mtk (Metchnikowin), and Drs (Drosomysin). As a result, flies with knocked-down Achilles expression are resistant to bacterial challenges. Meanwhile, no significant change in core clock gene expression and locomotor activity is observed, suggesting that Achilles influences rhythmic mRNA outputs rather than directly regulating the core timekeeping mechanism. Notably, Achilles knock-down in the absence of immune challenge significantly diminishes the fly's overall lifespan, indicating a behavioral or metabolic cost of constitutively activating this pathway. Together, our data demonstrate that (1) Achilles is a novel clock-controlled gene that (2) regulates the immune system, and (3) participates in signaling from neurons to immunological tissues.

Stress-responsive pathways and small RNA changes distinguish variable developmental phenotypes caused by MSH1 loss

BACKGROUND

Proper regulation of nuclear-encoded, organelle-targeted genes is crucial for plastid and mitochondrial function. Among these genes, MutS Homolog 1 (MSH1) is notable for generating an assortment of mutant phenotypes with varying degrees of penetrance and pleiotropy. Stronger phenotypes have been connected to stress tolerance and epigenetic changes, and in Arabidopsis T-DNA mutants, two generations of homozygosity with the msh1 insertion are required before severe phenotypes begin to emerge. These observations prompted us to examine how msh1 mutants contrast according to generation and phenotype by profiling their respective transcriptomes and small RNA populations.

RESULTS

Using RNA-seq, we analyze pathways that are associated with MSH1 loss, including abiotic stresses such as cold response, pathogen defense and immune response, salicylic acid, MAPK signaling, and circadian rhythm. Subtle redox and environment-responsive changes also begin in the first generation, in the absence of strong phenotypes. Using small RNA-seq we further identify miRNA changes, and uncover siRNA trends that indicate modifications at the chromatin organization level. In all cases, the magnitude of changes among protein-coding genes, transposable elements, and small RNAs increases according to generation and phenotypic severity.

CONCLUSION

Loss of MSH1 is sufficient to cause large-scale regulatory changes in pathways that have been individually linked to one another, but rarely described all together within a single mutant background. This study enforces the recognition of organelles as critical integrators of both internal and external cues, and highlights the relationship between organelle and nuclear regulation in fundamental aspects of plant development and stress signaling. Our findings also encourage further investigation into potential connections between organelle state and genome regulation vis-á-vis small RNA feedback.