Transcriptional-Readthrough RNAs Reflect the Phenomenon of "A Gene Contains Gene(s)" or "Gene(s) within a Gene" in the Human Genome, and Thus Are Not Chimeric RNAs

Identification of RAD17 as a candidate cancer predisposition gene in families with histories of pancreatic and breast cancers

BACKGROUND

Among the 10% of pancreatic cancers that occur in a familial context, around a third carry a pathogenic variant in a cancer predisposition gene. Genetic studies of pancreatic cancer predisposition are limited by high mortality rates amongst index patients and other affected family members. The genetic risk for pancreatic cancer is often shared with breast cancer susceptibility genes, most notably BRCA2, PALB2, ATM and BRCA1. Therefore, we hypothesized that additional shared genetic etiologies might be uncovered by studying families presenting with both breast and pancreatic cancer.

METHODS

Focusing on a multigene panel of 276 DNA Damage Repair (DDR) genes, we performed next-generation sequencing in a cohort of 41 families with at least three breast cancer cases and one pancreatic cancer. When the index patient with pancreatic cancer was deceased, close relatives (first or second-degree) affected with breast cancer were tested (39 families).

RESULTS

We identified 27 variants of uncertain significance in DDR genes. A splice site variant (c.1605 + 2T > A) in the RAD17 gene stood out, as a likely loss of function variant. RAD17 is a checkpoint protein that recruits the MRN (MRE11-RAD50-NBS1) complex to initiate DNA signaling, leading to DNA double-strand break repair.

CONCLUSION

Within families with breast and pancreatic cancer, we identified RAD17 as a novel candidate predisposition gene. Further genetic studies are warranted to better understand the potential pathogenic effect of RAD17 variants and in other DDR genes.

Updating mRNA variants of the human RSK4 gene and their expression in different stressed situations

We determined RNA spectrum of the human RSK4 (hRSK4) gene (also called RPS6KA6) and identified 29 novel mRNA variants derived from alternative splicing, which, plus the NCBI-documented ones and the five we reported previously, totaled 50 hRSK4 RNAs that, by our bioinformatics analyses, encode 35 hRSK4 protein isoforms of 35-762 amino acids. Many of the mRNAs are bicistronic or tricistronic for hRSK4. The NCBI-normalized NM_014496.5 and the protein it encodes are designated herein as the Wt-1 mRNA and protein, respectively, whereas the NM_001330512.1 and the long protein it encodes are designated as the Wt-2 mRNA and protein, respectively. Many of the mRNA variants responded differently to different situations of stress, including serum starvation, a febrile temperature, treatment with ethanol or ethanol-extracted clove buds (an herbal medicine), whereas the same stressed situation often caused quite different alterations among different mRNA variants in different cell lines. Mosifloxacin, an antibiotics and also a functional inhibitor of hRSK4, could inhibit the expression of certain hRSK4 mRNA variants. The hRSK4 gene likely uses alternative splicing as a handy tool to adapt to different stressed situations, and the mRNA and protein multiplicities may partly explain the incongruous literature on its expression and comports.

Thioredoxin Domain Containing 5 (TXNDC5): Friend or Foe?

This review focuses on the thioredoxin domain containing 5 (TXNDC5), also known as endoplasmic reticulum protein 46 (ERp46), a member of the protein disulfide isomerase (PDI) family with a dual role in multiple diseases. TXNDC5 is highly expressed in endothelial cells, fibroblasts, pancreatic β-cells, liver cells, and hypoxic tissues, such as cancer endothelial cells and atherosclerotic plaques. TXNDC5 plays a crucial role in regulating cell proliferation, apoptosis, migration, and antioxidative stress. Its potential significance in cancer warrants further investigation, given the altered and highly adaptable metabolism of tumor cells. It has been reported that both high and low levels of TXNDC5 expression are associated with multiple diseases, such as arthritis, cancer, diabetes, brain diseases, and infections, as well as worse prognoses. TXNDC5 has been attributed to both oncogenic and tumor-suppressive features. It has been concluded that in cancer, TXNDC5 acts as a foe and responds to metabolic and cellular stress signals to promote the survival of tumor cells against apoptosis. Conversely, in normal cells, TXNDC5 acts as a friend to safeguard cells against oxidative and endoplasmic reticulum stress. Therefore, TXNDC5 could serve as a viable biomarker or even a potential pharmacological target.

Versatile RNA: overlooked gems of the transcriptome

The critical role of RNA, its use and targetability concerning different aspects of human health are gaining more attention because our understanding of the versatility of RNA has dramatically evolved over the last decades. We now appreciate that RNA is far more critical than a messenger molecule and possesses many complicated functions. As a multifunctional molecule with its sequence, flexible structures and enzymatic abilities, RNA is genuinely powerful. Mammalian transcriptomes consist of a dynamically regulated plethora of coding and noncoding RNA types. However, some aspects of RNA metabolism remain to be explored. In this Viewpoint, we focus on the transcriptome's unconventional and possibly overlooked aspects to emphasize the importance of RNA in mammalian systems.

The status of the human gene catalogue

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.

Expression of the readthrough transcript CiDRE in alveolar macrophages boosts SARS-CoV-2 susceptibility and promotes COVID-19 severity

Lung infection during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via the angiotensin-I-converting enzyme 2 (ACE2) receptor induces a cytokine storm. However, the precise mechanisms involved in severe COVID-19 pneumonia are unknown. Here, we showed that interleukin-10 (IL-10) induced the expression of ACE2 in normal alveolar macrophages, causing them to become vectors for SARS-CoV-2. The inhibition of this system in hamster models attenuated SARS-CoV-2 pathogenicity. Genome-wide association and quantitative trait locus analyses identified a IFNAR2-IL10RB readthrough transcript, COVID-19 infectivity-enhancing dual receptor (CiDRE), which was highly expressed in patients harboring COVID-19 risk variants at the IFNAR2 locus. We showed that CiDRE exerted synergistic effects via the IL-10-ACE2 axis in alveolar macrophages and functioned as a decoy receptor for type I interferons. Collectively, our data show that high IL-10 and CiDRE expression are potential risk factors for severe COVID-19. Thus, IL-10R and CiDRE inhibitors might be useful COVID-19 therapies.

Dysregulation of murine long noncoding single-cell transcriptome in nonalcoholic steatohepatitis and liver fibrosis

LncRNAs comprise a heterogeneous class of RNA-encoding genes typified by low expression, nuclear enrichment, high tissue-specificity, and functional diversity, but the vast majority remain uncharacterized. Here, we assembled the mouse liver noncoding transcriptome from >2000 bulk RNA-seq samples and discovered 48,261 liver-expressed lncRNAs, a majority novel. Using these lncRNAs as a single-cell transcriptomic reference set, we elucidated lncRNA dysregulation in mouse models of high fat diet-induced nonalcoholic steatohepatitis and carbon tetrachloride-induced liver fibrosis. Trajectory inference analysis revealed lncRNA zonation patterns across the liver lobule in each major liver cell population. Perturbations in lncRNA expression and zonation were common in several disease-associated liver cell types, including nonalcoholic steatohepatitis-associated macrophages, a hallmark of fatty liver disease progression, and collagen-producing myofibroblasts, a central feature of liver fibrosis. Single-cell-based gene regulatory network analysis using bigSCale2 linked individual lncRNAs to specific biological pathways, and network-essential regulatory lncRNAs with disease-associated functions were identified by their high network centrality metrics. For a subset of these lncRNAs, promoter sequences of the network-defined lncRNA target genes were significantly enriched for lncRNA triplex formation, providing independent mechanistic support for the lncRNA-target gene linkages predicted by the gene regulatory networks. These findings elucidate liver lncRNA cell-type specificities, spatial zonation patterns, associated regulatory networks, and temporal patterns of dysregulation during hepatic disease progression. A subset of the liver disease-associated regulatory lncRNAs identified have human orthologs and are promising candidates for biomarkers and therapeutic targets.

Intergenic transcription in in vivo developed bovine oocytes and pre-implantation embryos

Background

Intergenic transcription, either failure to terminate at the transcription end site (TES), or transcription initiation at other intergenic regions, is present in cultured cells and enhanced in the presence of stressors such as viral infection. Transcription termination failure has not been characterized in natural biological samples such as pre-implantation embryos which express more than 10,000 genes and undergo drastic changes in DNA methylation.

Results

Using Automatic Readthrough Transcription Detection (ARTDeco) and data of in vivo developed bovine oocytes and embryos, we found abundant intergenic transcripts that we termed as read-outs (transcribed from 5 to 15 kb after TES) and read-ins (transcribed 1 kb up-stream of reference genes, extending up to 15 kb up-stream). Read-throughs (continued transcription from TES of expressed reference genes, 4-15 kb in length), however, were much fewer. For example, the numbers of read-outs and read-ins ranged from 3,084 to 6,565 or 33.36-66.67% of expressed reference genes at different stages of embryo development. The less copious read-throughs were at an average of 10% and significantly correlated with reference gene expression (P < 0.05). Interestingly, intergenic transcription did not seem to be random because many intergenic transcripts (1,504 read-outs, 1,045 read-ins, and 1,021 read-throughs) were associated with common reference genes across all stages of pre-implantation development. Their expression also seemed to be regulated by developmental stages because many were differentially expressed (log2 fold change ≥ 2, P < 0.05). Additionally, while gradual but un-patterned decreases in DNA methylation densities 10 kb both up- and down-stream of the intergenic transcribed regions were observed, the correlation between intergenic transcription and DNA methylation was insignificant. Finally, transcription factor binding motifs and polyadenylation signals were found in 27.2% and 12.15% of intergenic transcripts, respectively, suggesting considerable novel transcription initiation and RNA processing.

Conclusion

In summary, in vivo developed oocytes and pre-implantation embryos express large numbers of intergenic transcripts, which are not related to the overall DNA methylation profiles either up- or down-stream.

The status of the human gene catalogue

Scientists have been trying to identify all of the genes in the human genome since the initial draft of the genome was published in 2001. Over the intervening years, much progress has been made in identifying protein-coding genes, and the estimated number has shrunk to fewer than 20,000, although the number of distinct protein-coding isoforms has expanded dramatically. The invention of high-throughput RNA sequencing and other technological breakthroughs have led to an explosion in the number of reported non-coding RNA genes, although most of them do not yet have any known function. A combination of recent advances offers a path forward to identifying these functions and towards eventually completing the human gene catalogue. However, much work remains to be done before we have a universal annotation standard that includes all medically significant genes, maintains their relationships with different reference genomes, and describes clinically relevant genetic variants.

Unscrambling cancer genomes via integrated analysis of structural variation and copy number

Complex somatic genomic rearrangements and copy number alterations are hallmarks of nearly all cancers. We have developed an algorithm, LINX, to aid interpretation of structural variant and copy number data derived from short-read, whole-genome sequencing. LINX classifies raw structural variant calls into distinct events and predicts their effect on the local structure of the derivative chromosome and the functional impact on affected genes. Visualizations facilitate further investigation of complex rearrangements. LINX allows insights into a diverse range of structural variation events and can reliably detect pathogenic rearrangements, including gene fusions, immunoglobulin enhancer rearrangements, intragenic deletions, and duplications. Uniquely, LINX also predicts chained fusions that we demonstrate account for 13% of clinically relevant oncogenic fusions. LINX also reports a class of inactivation events that we term homozygous disruptions that may be a driver mutation in up to 9% of tumors and may frequently affect PTEN, TP53, and RB1.

Discovery of clinically relevant fusions in pediatric cancer

Background

Pediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions.

Results

Our Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a “known fusion list” prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient’s medical record, both known and novel fusions provided medically meaningful information.

Conclusions

The EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08094-z.

Acyl-Coenzyme A: Cholesterol Acyltransferase (ACAT) in Cholesterol Metabolism: From Its Discovery to Clinical Trials and the Genomics Era

The purification and cloning of the acyl-coenzyme A: cholesterol acyltransferase (ACAT) enzymes and the sterol O-acyltransferase (SOAT) genes has opened new areas of interest in cholesterol metabolism given their profound effects on foam cell biology and intestinal lipid absorption. The generation of mouse models deficient in Soat1 or Soat2 confirmed the importance of their gene products on cholesterol esterification and lipoprotein physiology. Although these studies supported clinical trials which used non-selective ACAT inhibitors, these trials did not report benefits, and one showed an increased risk. Early genetic studies have implicated common variants in both genes with human traits, including lipoprotein levels, coronary artery disease, and Alzheimer’s disease; however, modern genome-wide association studies have not replicated these associations. In contrast, the common SOAT1 variants are most reproducibly associated with testosterone levels.

At elevated temperatures, heat shock protein genes show altered ratios of different RNAs and expression of new RNAs, including several novel HSPB1 mRNAs encoding HSP27 protein isoforms

Heat shock proteins (HSP) serve as chaperones to maintain the physiological conformation and function of numerous cellular proteins when the ambient temperature is increased. To determine how accurate the general assumption that HSP gene expression is increased in febrile situations is, the RNA levels of the HSF1 (heat shock transcription factor 1) gene and certain HSP genes were determined in three cell lines cultured at 37˚C or 39˚C for three days. At 39˚C, the expression of HSF1, HSPB1, HSP90AA1 and HSP70A1L genes demonstrated complex changes in the ratios of expression levels between different RNA variants of the same gene. Several older versions of the RNAs of certain HSP genes that have been replaced by a newer version in the National Center for Biotechnology Information database were also detected, indicating that the older versions are actually RNA variants of these genes. The present study cloned four new RNA variants of the HSP27-encoding HSPB1 gene, which together encode three short HSP27 peptides. Reanalysis of the proteomics data from our previous studies also demonstrated that proteins from certain HSP genes could be detected simultaneously at multiple positions using SDS-PAGE, suggesting that these genes may engender multiple protein isoforms. These results collectively suggested that, besides increasing their expression, certain HSP and associated genes also use alternative transcription start sites to produce multiple RNA transcripts and use alternative splicing of a transcript to produce multiple mature RNAs, as important mechanisms for responding to an increased ambient temperature in vitro.

Interstitial Deletions Generating Fusion Genes

A fusion gene is the physical juxtaposition of two different genes resulting in a structure consisting of the head of one gene and the tail of the other. Gene fusion is often a primary neoplasia-inducing event in leukemias, lymphomas, solid malignancies as well as benign tumors. Knowledge about fusion genes is crucial not only for our understanding of tumorigenesis, but also for the diagnosis, prognostication, and treatment of cancer. Balanced chromosomal rearrangements, in particular translocations and inversions, are the most frequent genetic events leading to the generation of fusion genes. In the present review, we summarize the existing knowledge on chromosome deletions as a mechanism for fusion gene formation. Such deletions are mostly submicroscopic and, hence, not detected by cytogenetic analyses but by array comparative genome hybridization (aCGH) and/or high throughput sequencing (HTS). They are found across the genome in a variety of neoplasias. As tumors are increasingly analyzed using aCGH and HTS, it is likely that more interstitial deletions giving rise to fusion genes will be found, significantly impacting our understanding and treatment of cancer.

annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions

BACKGROUND

Gene fusion events are significant sources of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy.

RESULTS

We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions.

CONCLUSIONS

annoFuse provides standardized filtering and annotation for gene fusion calls from STAR-Fusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.

Computational Detection of Known Pathogenic Gene Fusions in a Normal Tissue Database and Implications for Genetic Disease Research

Several recent studies have demonstrated the utility of RNA-Seq in the diagnosis of rare inherited disease. Diagnostic rates 35% higher than those previously achievable with DNA-Seq alone have been attained. These studies have primarily profiled gene expression and splicing defects, however, some have also shown that fusion transcripts are diagnostic or phenotypically relevant in patients with constitutional disorders. Fusion transcripts have traditionally been studied as oncogenic phenomena, with relevance only to cancer testing. Consequently, fusion detection algorithms were biased toward the detection of well-known oncogenic fusions, hindering their application to rare Mendelian genetic disease studies. A recent methodology published by the authors successfully tailored a traditional algorithm to the detection of pathogenic fusion events in inherited disease. A key mechanism of decreasing false positive or biologically benign events was comparison to a database of events detected in normal tissues. This approach is akin to population frequency-based filtering of genetic variants. It is predicated on the idea that pathogenic fusion transcripts are absent from normal tissue. We report on an analysis of RNA-Seq data from the genotype-tissue expression (GTEx) project in which known pathogenic fusions are computationally detected at low levels in normal tissues unassociated with the disease phenotype. Examples include archetypal cancer fusion transcripts, as well as fusions responsible for rare inherited disease. We consider potential explanations for the detectability of such transcripts and discuss the bearing such results have on the future profiling of genetic disease patients for pathogenic gene fusions.

About three-fourths of mouse proteins unexpectedly appear at a low position of SDS-PAGE, often as additional isoforms, questioning whether all protein isoforms have been eliminated in gene-knockout cells or organisms

Most genes in evolutionarily complex genomes are expressed to multiple protein isoforms, but there is not yet any simple high-throughput approach to identify these isoforms. Using an oversimplified top-down LC-MS/MS strategy, we detected, around the 26-kD position of SDS-PAGE, proteins produced from 782 genes in a Cdk4-/- mouse embryonic fibroblast cell line. Interestingly, only 213 (27.24%, about one-fourth) of these 782 genes have their proteins with a theoretical molecular mass (TMM) 10% smaller or larger than 26 kD, that is, between 23 and 29 kD, the range set as allowed variation in SDS-PAGE. These 213 proteins are considered as the wild type (WT). The remaining three-fourths includes proteins from 66 (9.44%) genes with a TMM smaller than 23 kD and proteins from 503 (64.32%, nearly two-thirds) genes with a TMM larger than 29 kD; these proteins are categorized into a larger-group or a smaller-group, respectively, for their appearance at a higher or lower position of SDS-PAGE. For instance, at this 26-kD position we detected proteins from the Rps27a, Snrpf, Hist1h4a, and Rps25 genes whose proteins' TMM is 8.6, 9.7, 11.4, and 13.7 kD, respectively, and detected proteins from the Plelc1 and Prkdc genes, whose largest isoform is 533.9 and 471.1 kD, respectively. We extrapolate that many of those proteins migrating unexpectedly in SDS-PAGE may be isoforms besides the WT protein. Moreover, we also detected a Cdk4 protein in this Cdk4-/- cell line, thus wondering whether some of other gene-knockout cells or organisms show similar incompleteness of the knockout.

A tailored approach to fusion transcript identification increases diagnosis of rare inherited disease

BACKGROUND

RNA sequencing has been proposed as a means of increasing diagnostic rates in studies of undiagnosed rare inherited disease. Recent studies have reported diagnostic improvements in the range of 7.5-35% by profiling splicing, gene expression quantification and allele specific expression. To-date however, no study has systematically assessed the presence of gene-fusion transcripts in cases of germline disease. Fusion transcripts are routinely identified in cancer studies and are increasingly recognized as having diagnostic, prognostic or therapeutic relevance. Isolated reports exist of fusion transcripts being detected in cases of developmental and neurological phenotypes, and thus, systematic application of fusion detection to germline conditions may further increase diagnostic rates. However, current fusion detection methods are unsuited to the investigation of germline disease due to performance biases arising from their development using tumor, cell-line or in-silico data.

METHODS

We describe a tailored approach to fusion candidate identification and prioritization in a cohort of 47 undiagnosed, suspected inherited disease patients. We modify an existing fusion transcript detection algorithm by eliminating its cell line-derived filtering steps, and instead, prioritize candidates using a custom workflow that integrates genomic and transcriptomic sequence alignment, biological and technical annotations, customized categorization logic, and phenotypic prioritization.

RESULTS

We demonstrate that our approach to fusion transcript identification and prioritization detects genuine fusion events excluded by standard analyses and efficiently removes phenotypically unimportant candidates and false positive events, resulting in a reduced candidate list enriched for events with potential phenotypic relevance. We describe the successful genetic resolution of two previously undiagnosed disease cases through the detection of pathogenic fusion transcripts. Furthermore, we report the experimental validation of five additional cases of fusion transcripts with potential phenotypic relevance.

CONCLUSIONS

The approach we describe can be implemented to enable the detection of phenotypically relevant fusion transcripts in studies of rare inherited disease. Fusion transcript detection has the potential to increase diagnostic rates in rare inherited disease and should be included in RNA-based analytical pipelines aimed at genetic diagnosis.

The Protein-Coding Human Genome: Annotating High-Hanging Fruits

The major transcript variants of human protein-coding genes are annotated to a certain degree of accuracy combining manual curation, transcript data, and proteomics evidence. However, there is considerable disagreement on the annotation of about 2000 genes-they can be protein-coding, noncoding, or pseudogenes-and on the annotation of most of the predicted alternative transcripts. Pure transcriptome mapping approaches seem to be limited in discriminating functional expression from noise. These limitations have partially been overcome by dedicated algorithms to detect alternative spliced micro-exons and wobble splice variants. Recently, knowledge about splice mechanism and protein structure are incorporated into an algorithm to predict neighboring homologous exons, often spliced in a mutually exclusive manner. Predicted exons are evaluated by transcript data, structural compatibility, and evolutionary conservation, revealing hundreds of novel coding exons and splice mechanism re-assignments. The emerging human pan-genome is necessitating distinctive annotations incorporating differences between individuals and between populations.

MROH7-TTC4 read-through lncRNA suppresses vascular endothelial cell apoptosis and is upregulated by inhibition of ANXA7 GTPase activity

Apoptosis of vascular endothelial cells (VEC) is the main form of vascular injury that is closely linked to numerous cardiovascular diseases. Therefore, it is important to find new factors that can suppress VEC apoptosis. By using long noncoding RNA (lncRNA) microarray analysis, we found a new read-through lncRNA, MROH7-TTC4, which acted as an apoptosis inhibitor in VECs. Furthermore, by using the inhibitor (ABO) of annexin A7 (ANXA7) GTPase, we discovered that ANXA7 translocated into nucleus and interacted with 5'→3' exoribonuclease (XRN2). The decreased XRN2 phosphorylation induced by ANXA7 GTPase activity inhibition, promoted MROH7-TTC4 expression. Moreover, T-cell intracellular antigen-1 (TIA1), a binding protein of MROH7-TTC4, processed it into MROH7 and TTC4 that could inhibit VEC apoptosis. Here, we conclude that inhibiting ANXA7 GTPase activity promotes the interaction of ANXA7 and XRN2 in nucleus, which regulates the read-through transcription of MROH7-TTC4, and TIA1 is responsible for the process of MROH7-TTC4 that inhibits apoptosis through MROH7 and TTC4.

Alternative Transcription at Venom Genes and Its Role as a Complementary Mechanism for the Generation of Venom Complexity in the Common House Spider

The complex composition of venom, a proteinaceous secretion used by diverse animal groups for predation or defense, is typically viewed as being driven by gene duplication in conjunction with positive selection, leading to large families of diversified toxins with selective venom gland expression. Yet, the production of alternative transcripts at venom genes is often overlooked as another potentially important process that could contribute proteins to venom, and requires comprehensive datasets integrating genome and transcriptome sequences together with proteomic characterization of venom to be fully documented. In the common house spider, Parasteatoda tepidariorum, we used RNA sequencing of four tissue types in conjunction with the sequenced genome to provide a comprehensive transcriptome annotation. We also used mass spectrometry to identify a minimum of 99 distinct proteins in P tepidariorum venom, including at least 33 latrotoxins, pore-forming neurotoxins shared with the confamilial black widow. We found that venom proteins are much more likely to come from multiple transcript genes, whose transcripts produced distinct protein sequences. The presence of multiple distinct proteins in venom from transcripts at individual genes was confirmed for eight loci by mass spectrometry, and is possible at 21 others. Alternative transcripts from the same gene, whether encoding or not encoding a protein found in venom, showed a range of expression patterns, but were not necessarily restricted to the venom gland. However, approximately half of venom protein encoding transcripts were found among the 1,318 transcripts with strongly venom gland biased expression. Our findings revealed an important role for alternative transcription in generating venom protein complexity and expanded the traditional model of venom evolution.

Efficient system for upstream mRNA trans-splicing to generate covalent, head-to-tail, protein multimers

We present a plasmid-based system in which upstream trans-splicing efficiently generates mRNAs that encode head-to-tail protein multimers. In this system, trans-splicing occurs between one of two downstream splice donors in the sequence encoding a C-terminal V5 epitope tag and an upstream splice acceptor in the 5′ region of the pCS2(+) host plasmid. Using deletion and fusion constructs of the DUX4 protein as an example, we found that this system produced trans-spliced mRNAs in which coding regions from independent transcripts were fused in phase such that covalent head-to-tail protein multimers were translated. For a cDNA of ~450 bp, about half of the expressed proteins were multimeric, with the efficiency of trans-splicing and extent of multimer expression decreasing as cDNA length increased. This system generated covalent heterodimeric proteins upon co-transfections of plasmids encoding separate proteins and did not require a long complementary binding domain to position mRNAs for trans-splicing. This plasmid-based trans-splicing system is adaptable to multiple gene delivery systems, and it presents new opportunities for investigating molecular mechanisms of trans-splicing, generating covalent protein multimers with novel functions within cells, and producing mRNAs encoding large proteins from split precursors.

Long-read sequencing uncovers a complex transcriptome topology in varicella zoster virus

BACKGROUND

Varicella zoster virus (VZV) is a human pathogenic alphaherpesvirus harboring a relatively large DNA molecule. The VZV transcriptome has already been analyzed by microarray and short-read sequencing analyses. However, both approaches have substantial limitations when used for structural characterization of transcript isoforms, even if supplemented with primer extension or other techniques. Among others, they are inefficient in distinguishing between embedded RNA molecules, transcript isoforms, including splice and length variants, as well as between alternative polycistronic transcripts. It has been demonstrated in several studies that long-read sequencing is able to circumvent these problems.

RESULTS

In this work, we report the analysis of the VZV lytic transcriptome using the Oxford Nanopore Technologies sequencing platform. These investigations have led to the identification of 114 novel transcripts, including mRNAs, non-coding RNAs, polycistronic RNAs and complex transcripts, as well as 10 novel spliced transcripts and 25 novel transcription start site isoforms and transcription end site isoforms. A novel class of transcripts, the nroRNAs are described in this study. These transcripts are encoded by the genomic region located in close vicinity to the viral replication origin. We also show that the ORF63 exhibits a complex structural variation encompassing the splice sites of VZV latency transcripts. Additionally, we have detected RNA editing in a novel non-coding RNA molecule.

CONCLUSIONS

Our investigations disclosed a composite transcriptomic architecture of VZV, including the discovery of novel RNA molecules and transcript isoforms, as well as a complex meshwork of transcriptional read-throughs and overlaps. The results represent a substantial advance in the annotation of the VZV transcriptome and in understanding the molecular biology of the herpesviruses in general.