Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data

Chromosome-level Genome Assembly of Korean Long-tailed Chicken and Pangenome of 40 Gallus gallus Assemblies

This study presents the first chromosome-level genome assembly of the Korean long-tailed chicken (KLC), a unique breed of Gallus gallus known as Ginkkoridak. Our assembly achieved a super contig N50 of 5.7 Mbp and a scaffold N50 exceeding 90 Mb, with a genome completeness of 96.3% as assessed by BUSCO using the aves_odb10 set. We also constructed a comprehensive pangenome graph, incorporating 40 Gallus gallus assemblies, including the KLC genome. This graph comprises 87,934,214 nodes, 121,720,974 edges, and a total sequence length of 1,709,850,352 bp. Notably, our KLC assembly contributed 1,919,925 bp of new sequences to the pangenome, underscoring the unique genetic makeup of this breed. Furthermore, in comparison with the pangenome, we identified 36,818 structural variants in KLC, which included 2,529 insertions, 27,743 deletions, and 6,546 of either insertions or deletions shorter than 1 kb. We also successfully identified pan-genome wide non-reference sequences. Our KLC assembly and pangenome graph provide valuable genomic resources for studying G. gallus populations.

Architects and Partners: The Dual Roles of Non-coding RNAs in Gene Fusion Events

Extensive research into gene fusions in cancer and other diseases has led to the discovery of novel biomarkers and therapeutic targets. Concurrently, various bioinformatics tools have been developed for fusion detection in RNA sequencing data, which, in the age of increasing affordability of sequencing, have delivered a large-scale identification of transcriptomic abnormalities. Historically, the focus of fusion transcript research was predominantly on coding RNAs and their resultant proteins, often overlooking non-coding RNAs (ncRNAs). This chapter discusses how ncRNAs are integral players in the landscape of gene fusions, detailing their contributions to the formation of gene fusions and their presence in chimeric transcripts. We delve into both linear and the more recently identified circular fusion RNAs, providing a comprehensive overview of the computational methodologies used to detect ncRNA-involved gene fusions. Additionally, we examine the inherent biases and limitations of these bioinformatics approaches, offering insights into the challenges and future directions in this dynamic field.

Recent advances in the investigation of fusion RNAs and their role in molecular pathology of cancer

Gene fusions have had a significant role in the development of various types of cancer, oftentimes involved in oncogenic activities through dysregulation of gene expression or signalling pathways. Some cancer-associated chromosomal translocations can undergo backsplicing, resulting in fusion-circular RNAs, a more stable isoform immune to RNase degradation. This stability makes fusion circular RNAs a promising diagnostic biomarker for cancer. While the detection of linear fusion RNAs and their function in certain cancers have been described in literature, fusion circular RNAs lag behind due to their low abundance in cancer cells. This review highlights current literature on the role of linear and circular fusion transcripts in cancer, tools currently available for detecting of these chimeric RNAs and their function and how they play a role in tumorigenesis.

Large-scale single-virus genomics uncovers hidden diversity of river water viruses and diversified gene profiles

Environmental viruses (primarily bacteriophages) are widely recognized as playing an important role in ecosystem homeostasis through the infection of host cells. However, the majority of environmental viruses are still unknown as their mosaic structure and frequent mutations in their sequences hinder genome construction in current metagenomics. To enable the large-scale acquisition of environmental viral genomes, we developed a new single-viral genome sequencing platform with microfluidic-generated gel beads. Amplification of individual DNA viral genomes in mass-produced gel beads allows high-throughput genome sequencing compared to conventional single-virus genomics. The sequencing analysis of river water samples yielded 1431 diverse viral single-amplified genomes, whereas viral metagenomics recovered 100 viral metagenome-assembled genomes at the comparable sequence depth. The 99.5% of viral single-amplified genomes were determined novel at the species level, most of which could not be recovered by a metagenomic assembly. The large-scale acquisition of diverse viral genomes identified protein clusters commonly detected in different viral strains, allowing the gene transfer to be tracked. Moreover, comparative genomics within the same viral species revealed that the profiles of various methyltransferase subtypes were diverse, suggesting an enhanced escape from host bacterial internal defense mechanisms. Our use of gel bead-based single-virus genomics will contribute to exploring the nature of viruses by accelerating the accumulation of draft genomes of environmental DNA viruses.

Molecular diagnostic tools for the World Health Organization (WHO) 2021 classification of gliomas, glioneuronal and neuronal tumors; an EANO guideline

In the 5th edition of the WHO CNS tumor classification (CNS5, 2021), multiple molecular characteristics became essential diagnostic criteria for many additional CNS tumor types. For those tumors, an integrated, "histomolecular" diagnosis is required. A variety of approaches exists for determining the status of the underlying molecular markers. The present guideline focuses on the methods that can be used for assessment of the currently most informative diagnostic and prognostic molecular markers for the diagnosis of gliomas, glioneuronal and neuronal tumors. The main characteristics of the molecular methods are systematically discussed, followed by recommendations and information on available evidence levels for diagnostic measures. The recommendations cover DNA and RNA next-generation-sequencing, methylome profiling, and select assays for single/limited target analyses, including immunohistochemistry. Additionally, because of its importance as a predictive marker in IDH-wildtype glioblastomas, tools for the analysis of MGMT promoter methylation status are covered. A structured overview of the different assays with their characteristics, especially their advantages and limitations, is provided, and requirements for input material and reporting of results are clarified. General aspects of molecular diagnostic testing regarding clinical relevance, accessibility, cost, implementation, regulatory, and ethical aspects are discussed as well. Finally, we provide an outlook on new developments in the landscape of molecular testing technologies in neuro-oncology.

Disruption of regulatory domains and novel transcripts as disease-causing mechanisms

Deletions, duplications, insertions, inversions, and translocations, collectively called structural variations (SVs), affect more base pairs of the genome than any other sequence variant. The recent technological advancements in genome sequencing have enabled the discovery of tens of thousands of SVs per human genome. These SVs primarily affect non-coding DNA sequences, but the difficulties in interpreting their impact limit our understanding of human disease etiology. The functional annotation of non-coding DNA sequences and methodologies to characterize their three-dimensional (3D) organization in the nucleus have greatly expanded our understanding of the basic mechanisms underlying gene regulation, thereby improving the interpretation of SVs for their pathogenic impact. Here, we discuss the various mechanisms by which SVs can result in altered gene regulation and how these mechanisms can result in rare genetic disorders. Beyond changing gene expression, SVs can produce novel gene-intergenic fusion transcripts at the SV breakpoints.

Outlier Expression of Isoforms by Targeted or Total RNA Sequencing Identifies Clinically Significant Genomic Variants in Hematolymphoid Tumors

Recognition of aberrant gene isoforms due to DNA events can impact risk stratification and molecular classification of hematolymphoid tumors. In myelodysplastic syndromes, KMT2A partial tandem duplication (PTD) was one of the top adverse predictors in the International Prognostic Scoring System-Molecular study. In B-cell acute lymphoblastic leukemia (B-ALL), ERG isoforms have been proposed as markers of favorable-risk DUX4 rearrangements, whereas deletion-mediated IKZF1 isoforms are associated with adverse prognosis and have been extended to the high-risk IKZF1plus signature defined by codeletions, including PAX5. In this limited study, outlier expression of isoforms as markers of IKZF1 intragenic or 3' deletions, DUX4 rearrangements, or PAX5 intragenic deletions were 92.3% (48/52), 90% (9/10), or 100% (9/9) sensitive, respectively, and 98.7% (368/373), 100% (35/35), or 97.1% (102/105) specific, respectively, by targeted RNA sequencing, and 84.0% (21/25), 85.7% (6/7), or 81.8% (9/11) sensitive, respectively, and 98.2% (109/111), 98.4% (127/129), or 98.7% (78/79) specific, respectively, by total RNA sequencing. Comprehensive split-read analysis identified expressed DNA breakpoints, cryptic splice sites associated with IKZF1 3' deletions, PTD of IKZF1 exon 5 spanning N159Y in B-ALL with mutated IKZF1 N159Y, and truncated KMT2A-PTD isoforms. Outlier isoforms were also effective targeted RNA markers for PAX5 intragenic amplifications (B-ALL), KMT2A-PTD (myeloid malignant cancers), and rare NOTCH1 intragenic deletions (T-cell acute lymphoblastic leukemia). These findings support the use of outlier isoform analysis as a robust strategy for detecting clinically significant DNA events.

Novel gene-intergenic fusion involving ubiquitin E3 ligase UBE3C causes distal hereditary motor neuropathy

Distal hereditary motor neuropathies (dHMNs) are a group of inherited diseases involving the progressive, length-dependent axonal degeneration of the lower motor neurons. There are currently 29 reported causative genes and four disease loci implicated in dHMN. Despite the high genetic heterogeneity, mutations in the known genes account for less than 20% of dHMN cases, with the mutations identified predominantly being point mutations or indels. We have expanded the spectrum of dHMN mutations with the identification of a 1.35 Mb complex structural variation (SV) causing a form of autosomal dominant dHMN (DHMN1 OMIM %182906). Given the complex nature of SV mutations and the importance of studying pathogenic mechanisms in a neuronal setting, we generated a patient-derived DHMN1 motor neuron model harbouring the 1.35 Mb complex insertion. The DHMN1 complex insertion creates a duplicated copy of the first 10 exons of the ubiquitin-protein E3 ligase gene (UBE3C) and forms a novel gene-intergenic fusion sense transcript by incorporating a terminal pseudo-exon from intergenic sequence within the DHMN1 locus. The UBE3C intergenic fusion (UBE3C-IF) transcript does not undergo nonsense-mediated decay and results in a significant reduction of wild-type full-length UBE3C (UBE3C-WT) protein levels in DHMN1 iPSC-derived motor neurons. An engineered transgenic Caenorhabditis elegans model expressing the UBE3C-IF transcript in GABA-ergic motor neurons shows neuronal synaptic transmission deficits. Furthermore, the transgenic animals are susceptible to heat stress, which may implicate defective protein homeostasis underlying DHMN1 pathogenesis. Identification of the novel UBE3C-IF gene-intergenic fusion transcript in motor neurons highlights a potential new disease mechanism underlying axonal and motor neuron degeneration. These complementary models serve as a powerful paradigm for studying the DHMN1 complex SV and an invaluable tool for defining therapeutic targets for DHMN1.

The Transition from Cancer "omics" to "epi-omics" through Next- and Third-Generation Sequencing

Deciphering cancer etiopathogenesis has proven to be an especially challenging task since the mechanisms that drive tumor development and progression are far from simple. An astonishing amount of research has revealed a wide spectrum of defects, including genomic abnormalities, epigenomic alterations, disturbance of gene transcription, as well as post-translational protein modifications, which cooperatively promote carcinogenesis. These findings suggest that the adoption of a multidimensional approach can provide a much more precise and comprehensive picture of the tumor landscape, hence serving as a powerful tool in cancer research and precision oncology. The introduction of next- and third-generation sequencing technologies paved the way for the decoding of genetic information and the elucidation of cancer-related cellular compounds and mechanisms. In the present review, we discuss the current and emerging applications of both generations of sequencing technologies, also referred to as massive parallel sequencing (MPS), in the fields of cancer genomics, transcriptomics and proteomics, as well as in the progressing realms of epi-omics. Finally, we provide a brief insight into the expanding scope of sequencing applications in personalized cancer medicine and pharmacogenomics.

CRISPRs in the human genome are differentially expressed between malignant and normal adjacent to tumor tissue

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) have been identified in bacteria, archaea and mitochondria of plants, but not in eukaryotes. Here, we report the discovery of 12,572 putative CRISPRs randomly distributed across the human chromosomes, which we termed hCRISPRs. By using available transcriptome datasets, we demonstrate that hCRISPRs are distinctively expressed as small non-coding RNAs (sncRNAs) in cell lines and human tissues. Moreover, expression patterns thereof enabled us to distinguish normal from malignant tissues. In prostate cancer, we confirmed the differential hCRISPR expression between normal adjacent and malignant primary prostate tissue by RT-qPCR and demonstrate that the SHERLOCK and DETECTR dipstick tools are suitable to detect these sncRNAs. We anticipate that the discovery of CRISPRs in the human genome can be further exploited for diagnostic purposes in cancer and other medical conditions, which certainly will lead to the development of point-of-care tests based on the differential expression of the hCRISPRs.

Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data

BACKGROUND

Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non-poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints.

RESULTS

We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA-minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG-positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq.

CONCLUSION

By using the full potential of non-poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects.