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RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics.

Orthology assignment is a key step of comparative genomic studies, for which many bioinformatic tools have been developed. However, all gene clustering pipelines are based on the analysis of protein distances, which are subject to many artifacts. In this article, we introduce Broccoli, a user-friendly pipeline designed to infer, with high precision, orthologous groups, and pairs of proteins using a phylogeny-based approach. Briefly, Broccoli performs ultrafast phylogenetic analyses on most proteins and builds a network of orthologous relationships. Orthologous groups are then identified from the network using a parameter-free machine learning algorithm. Broccoli is also able to detect chimeric proteins resulting from gene-fusion events and to assign these proteins to the corresponding orthologous groups. Tested on two benchmark data sets, Broccoli outperforms current orthology pipelines. In addition, Broccoli is scalable, with runtimes similar to those of recent distance-based pipelines. Given its high level of performance and efficiency, this new pipeline represents a suitable choice for comparative genomic studies. Broccoli is freely available at https://github.com/rderelle/Broccoli.

Glioblastoma (GBM) is the most common type of glioma and is uniformly fatal. Currently, tumour heterogeneity and mutation acquisition are major impedances for tailoring personalized therapy. We collected blood and tumour tissue samples from 25 GBM patients and 25 blood samples from healthy controls. Cell‐free DNA (cfDNA) was extracted from the plasma of GBM patients and from healthy controls. Tumour DNA was extracted from fresh tumour samples. Extracted DNA was sequenced using a whole‐genome sequencing procedure. We also collected 180 tumour DNA datasets from GBM patients publicly available at the TCGA/PANCANCER project. These data were analysed for mutations and gene–gene fusions that could be potential druggable targets. We found that plasma cfDNA concentrations in GBM patients were significantly elevated (22.6 ± 5 ng·mL−1), as compared to healthy controls (1.4 ± 0.4 ng·mL−1) of the same average age. We identified unique mutations in the cfDNA and tumour DNA of each GBM patient, including some of the most frequently mutated genes in GBM according to the COSMIC database (TP53, 18.75%; EGFR, 37.5%; NF1, 12.5%; LRP1B, 25%; IRS4, 25%). Using our gene–gene fusion database, ChiTaRS 5.0, we identified gene–gene fusions in cfDNA and tumour DNA, such as KDR–PDGFRA and NCDN–PDGFRA, which correspond to previously reported alterations of PDGFRA in GBM (44% of all samples). Interestingly, the PDGFRA protein fusions can be targeted by tyrosine kinase inhibitors such as imatinib, sunitinib, and sorafenib. Moreover, we identified BCR–ABL1 (in 8% of patients), COL1A1–PDGFB (8%), NIN–PDGFRB (8%), and FGFR1–BCR (4%) in cfDNA of patients, which can be targeted by analogues of imatinib. ROS1 fusions (CEP85L–ROS1 and GOPC–ROS1), identified in 8% of patient cfDNA, might be targeted by crizotinib, entrectinib, or larotrectinib. Thus, our study suggests that integrated analysis of cfDNA plasma concentration, gene mutations, and gene–gene fusions can serve as a diagnostic modality for distinguishing GBM patients who may benefit from targeted therapy. These results open new avenues for precision medicine in GBM, using noninvasive liquid biopsy diagnostics to assess personalized patient profiles. Moreover, repeated detection of druggable targets over the course of the disease may provide real‐time information on the evolving molecular landscape of the tumour. Personalized therapy of patients with glioblastoma (GBM) is challenging owing to tumour heterogeneity. Here, we extracted and sequenced cell‐free DNA (cfDNA) from the plasma of 25 GBM patients and tumour DNA from fresh tumour samples. We found that cfDNA concentrations in the plasma of GBM patients were significantly elevated, as compared to healthy controls. Moreover, we identified unique mutations and gene–gene fusions in the cfDNA and tumour DNA of GBM patients, some of which could be therapeutically targeted by tyrosine kinase inhibitors.

Background The plant immune system is innate and encoded in the germline. Using it efficiently, plants are capable of recognizing a diverse range of rapidly evolving pathogens. A recently described phenomenon shows that plant immune receptors are able to recognize pathogen effectors through the acquisition of exogenous protein domains from other plant genes. Results We show that plant immune receptors with integrated domains are distributed unevenly across their phylogeny in grasses. Using phylogenetic analysis, we uncover a major integration clade, whose members underwent repeated independent integration events producing diverse fusions. This clade is ancestral in grasses with members often found on syntenic chromosomes. Analyses of these fusion events reveals that homologous receptors can be fused to diverse domains. Furthermore, we discover a 43 amino acid long motif associated with this dominant integration clade which is located immediately upstream of the fusion site. Sequence analysis reveals that DNA transposition and/or ectopic recombination are the most likely mechanisms of formation for nucleotide binding leucine rich repeat proteins with integrated domains. Conclusions The identification of this subclass of plant immune receptors that is naturally adapted to new domain integration will inform biotechnological approaches for generating synthetic receptors with novel pathogen “baits.”

Background Plants deploy immune receptors to detect pathogen-derived molecules and initiate defense responses. Intracellular plant immune receptors called nucleotide-binding leucine-rich repeat (NLR) proteins contain a central nucleotide-binding (NB) domain followed by a series of leucine-rich repeats (LRRs), and are key initiators of plant defense responses. However, recent studies demonstrated that NLRs with non-canonical domain architectures play an important role in plant immunity. These composite immune receptors are thought to arise from fusions between NLRs and additional domains that serve as “baits” for the pathogen-derived effector proteins, thus enabling pathogen recognition. Several names have been proposed to describe these proteins, including “integrated decoys” and “integrated sensors”. We adopt and argue for “integrated domains” or NLR-IDs, which describes the product of the fusion without assigning a universal mode of action. Results We have scanned available plant genome sequences for the full spectrum of NLR-IDs to evaluate the diversity of integrations of potential sensor/decoy domains across flowering plants, including 19 crop species. We manually curated wheat and brassicas and experimentally validated a subset of NLR-IDs in wild and cultivated wheat varieties. We have examined NLR fusions that occur in multiple plant families and identified that some domains show re-occurring integration across lineages. Domains fused to NLRs overlap with previously identified pathogen targets confirming that they act as baits for the pathogen. While some of the integrated domains have been previously implicated in disease resistance, others provide new targets for engineering durable resistance to plant pathogens. Conclusions We have built a robust reproducible pipeline for detecting variable domain architectures in plant immune receptors across species. We hypothesize that NLR-IDs that we revealed provide clues to the host proteins targeted by pathogens, and that this information can be deployed to discover new sources of disease resistance.

The treatment scenario of metastatic colorectal cancer (mCRC) has been rapidly enriched with new chemotherapy combinations and biological agents that lead to a remarkable improvement in patients’ outcome. Kinase gene fusions account for less than 1% of mCRC overall but are enriched in patients with high microsatellite instability, RAS/BRAF wild-type colorectal cancer. mCRC patients harboring such alterations show a poor prognosis with standard treatments that could be reversed by adopting novel therapeutic strategies. Moving forward to a positive selection of mCRC patients suitable for targeted therapy in the era of personalized medicine, actionable gene fusions, although rare, represent a peculiar opportunity to disrupt a tumor alteration to achieve therapeutic goal. Here we summarize the current knowledge on potentially actionable gene fusions in colorectal cancer available from retrospective experiences and promising preliminary results of new basket trials.

Recurrent gene fusions are a prevalent class of mutations arising from the juxtaposition of 2 distinct regions, which can generate novel functional transcripts that could serve as valuable therapeutic targets in cancer. Therefore, we aim to establish a sensitive, high-throughput methodology to comprehensively catalog functional gene fusions in cancer by evaluating a paired-end transcriptome sequencing strategy. Not only did a paired-end approach provide a greater dynamic range in comparison with single read based approaches, but it clearly distinguished the high-level \"driving\" gene fusions, such as BCR-ABL1 and TMPRSS2-ERG, from potential lower level \"passenger\" gene fusions. Also, the comprehensiveness of a paired-end approach enabled the discovery of 12 previously undescribed gene fusions in 4 commonly used cell lines that eluded previous approaches. Using the paired-end transcriptome sequencing approach, we observed read-through mRNA chimeras, tissue-type restricted chimeras, converging transcripts, diverging transcripts, and overlapping mRNA transcripts. Last, we successfully used paired-end transcriptome sequencing to detect previously undescribed ETS gene fusions in prostate tumors. Together, this study establishes a highly specific and sensitive approach for accurately and comprehensively cataloguing chimeras within a sample using paired-end transcriptome sequencing.

Matthew Meyerson and colleagues report exome sequencing of solitary fibrous tumor (SFT), a rare mesenchymal tumor. They identify a NAB2 - STAT6 fusion in 55% of cases. Solitary fibrous tumors (SFTs) are rare mesenchymal tumors. Here, we describe the identification of a NAB2-STAT6 fusion from whole-exome sequencing of 17 SFTs. Analysis in 53 tumors confirmed the presence of 7 variants of this fusion transcript in 29 tumors (55%), representing a lower bound for fusion frequency at this locus and suggesting that the NAB2-STAT6 fusion is a distinct molecular feature of SFTs.

Arul Chinnaiyan and colleagues identify NAB2 - STAT6 fusions in 52 of 52 solitary fibrous tumor cases. Overexpression of this fusion induced cell proliferation, which could be suppressed by knockdown of EGR1 . A 44-year old woman with recurrent solitary fibrous tumor (SFT)/hemangiopericytoma was enrolled in a clinical sequencing program including whole-exome and transcriptome sequencing. A gene fusion of the transcriptional repressor NAB2 with the transcriptional activator STAT6 was detected. Transcriptome sequencing of 27 additional SFTs identified the presence of a NAB2 - STAT6 gene fusion in all tumors. Using RT-PCR and sequencing, we detected this fusion in all 51 SFTs, indicating high levels of recurrence. Expression of NAB2-STAT6 fusion proteins was confirmed in SFT, and the predicted fusion products harbor the early growth response (EGR)-binding domain of NAB2 fused to the activation domain of STAT6. Overexpression of the NAB2 - STAT6 gene fusion induced proliferation in cultured cells and activated the expression of EGR-responsive genes. These studies establish NAB2 - STAT6 as the defining driver mutation of SFT and provide an example of how neoplasia can be initiated by converting a transcriptional repressor of mitogenic pathways into a transcriptional activator.

Background Gene fusions are an important driver of cancer and require rapid and accurate detection to guide clinical decisions. However, the performance characteristics of whole transcriptome sequencing (WTS) for the detection of gene fusions have not been thoroughly investigated. Methods We developed a novel WTS-based assay for the detection of gene fusions, MET exon 14 skipping and EGFR VIII alterations in clinical samples. Results We defined a DV200 value ≥ 30% as the threshold for RNA degradation, RNA input, fusion expression and number of mapped reads greater than 100 ng, 40 copies/ng and 80 Mb for optimal sensitivity of the WTS assay. Our assay successfully identified 62 out of 63 known gene fusions, achieving a sensitivity of 98.4%. The specificity of the assay was 100%, as no fusions were detected in the 21 fusion-negative samples. Good repeatability and reproducibility were observed in replicates, except for the TPM3::NTRK1 fusion, which was expressed below the threshold. Of all fusions identified in 101 NSCLC samples, 68.9% (20/29) were potentially actionable, compared to 20% in pan-cancer samples. In addition to actionable fusions, we also identified many fusions with potential diagnostic and prognostic value in pan-cancer. Conclusions We have developed a novel WTS assay with high sensitivity, specificity, repeatability and reproducibility. This assay can identify potentially actionable gene fusions and provides valuable insights into the fusion landscape in various cancers, which may help guide treatment decisions and aid in diagnosis and prognosis.