Retained introns in long RNA-seq reads are not reliably detected in sample-matched short reads

Full-length isoform concatenation sequencing to resolve cancer transcriptome complexity

BACKGROUND

Cancers exhibit complex transcriptomes with aberrant splicing that induces isoform-level differential expression compared to non-diseased tissues. Transcriptomic profiling using short-read sequencing has utility in providing a cost-effective approach for evaluating isoform expression, although short-read assembly displays limitations in the accurate inference of full-length transcripts. Long-read RNA sequencing (Iso-Seq), using the Pacific Biosciences (PacBio) platform, can overcome such limitations by providing full-length isoform sequence resolution which requires no read assembly and represents native expressed transcripts. A constraint of the Iso-Seq protocol is due to fewer reads output per instrument run, which, as an example, can consequently affect the detection of lowly expressed transcripts. To address these deficiencies, we developed a concatenation workflow, PacBio Full-Length Isoform Concatemer Sequencing (PB_FLIC-Seq), designed to increase the number of unique, sequenced PacBio long-reads thereby improving overall detection of unique isoforms. In addition, we anticipate that the increase in read depth will help improve the detection of moderate to low-level expressed isoforms.

RESULTS

In sequencing a commercial reference (Spike-In RNA Variants; SIRV) with known isoform complexity we demonstrated a 3.4-fold increase in read output per run and improved SIRV recall when using the PB_FLIC-Seq method compared to the same samples processed with the Iso-Seq protocol. We applied this protocol to a translational cancer case, also demonstrating the utility of the PB_FLIC-Seq method for identifying differential full-length isoform expression in a pediatric diffuse midline glioma compared to its adjacent non-malignant tissue. Our data analysis revealed increased expression of extracellular matrix (ECM) genes within the tumor sample, including an isoform of the Secreted Protein Acidic and Cysteine Rich (SPARC) gene that was expressed 11,676-fold higher than in the adjacent non-malignant tissue. Finally, by using the PB_FLIC-Seq method, we detected several cancer-specific novel isoforms.

CONCLUSION

This work describes a concatenation-based methodology for increasing the number of sequenced full-length isoform reads on the PacBio platform, yielding improved discovery of expressed isoforms. We applied this workflow to profile the transcriptome of a pediatric diffuse midline glioma and adjacent non-malignant tissue. Our findings of cancer-specific novel isoform expression further highlight the importance of long-read sequencing for characterization of complex tumor transcriptomes.

Single-cell long-read sequencing in human cerebral organoids uncovers cell-type-specific and autism-associated exons

Dysregulation of alternative splicing has been repeatedly associated with neurodevelopmental disorders, but the extent of cell-type-specific splicing in human neural development remains largely uncharted. Here, single-cell long-read sequencing in induced pluripotent stem cell (iPSC)-derived cerebral organoids identifies over 31,000 uncatalogued isoforms and 4,531 cell-type-specific splicing events. Long reads uncover coordinated splicing and cell-type-specific intron retention events, which are challenging to study with short reads. Retained neuronal introns are enriched in RNA splicing regulators, showing shorter lengths, higher GC contents, and weaker 5' splice sites. We use this dataset to explore the biological processes underlying neurological disorders, focusing on autism. In comparison with prior transcriptomic data, we find that the splicing program in autistic brains is closer to the progenitor state than differentiated neurons. Furthermore, cell-type-specific exons harbor significantly more de novo mutations in autism probands than in siblings. Overall, these results highlight the importance of cell-type-specific splicing in autism and neuronal gene regulation.

Comprehensive analysis of alternative splicing across multiple transcriptomic cohorts reveals prognostic signatures in prostate cancer

BACKGROUND

Alternative splicing (AS) plays a crucial role in transcriptomic diversity and is a hallmark of cancer that profoundly influences the development and progression of prostate cancer (PCa), a prevalent and potentially life-limiting cancer among men. Accumulating evidence has highlighted the association between AS dysregulation and the onset and progression of PCa. However, a comprehensive and integrative analysis of AS profiles at the event level, utilising data from multiple high-throughput cohorts and evaluating the prognosis of PCa progression, remains lacking and calls for thorough exploration.

RESULTS

We identified a differentially expressed retained intron event in ZWINT across three distinct cohorts, encompassing an original array-based dataset profiled by us previously and two RNA sequencing (RNA-seq) datasets. Subsequent in-depth analyses of these RNA-seq datasets revealed  141 altered events, of which 21 demonstrated a significant association with patients' biochemical recurrence-free survival (BCRFS). We formulated an AS event-based prognostic signature, capturing six pivotal events in genes CYP4F12, NFATC4, PIGO, CYP3A5, ALS2CL, and FXYD3. This signature effectively differentiated  high-risk patients diagnosed with PCa, who experienced shorter BCRFS, from their low-risk counterparts. Notably, the signature's predictive power surpassed traditional clinicopathological markers in forecasting 5-year BCRFS, demonstrating robust performance in both internal and external validation sets. Lastly, we constructed a novel nomogram that integrates patients' Gleason scores with pathological tumour stages, demonstrating improved prognostication of BCRFS.

CONCLUSIONS

Prediction of clinical progression remains elusive in PCa. This research uncovers novel splicing events associated with BCRFS, augmenting existing prognostic tools, thus potentially refining clinical decision-making.

Splicing defects in rare diseases: transcriptomics and machine learning strategies towards genetic diagnosis

Genomic variants affecting pre-messenger RNA splicing and its regulation are known to underlie many rare genetic diseases. However, common workflows for genetic diagnosis and clinical variant interpretation frequently overlook splice-altering variants. To better serve patient populations and advance biomedical knowledge, it has become increasingly important to develop and refine approaches for detecting and interpreting pathogenic splicing variants. In this review, we will summarize a few recent developments and challenges in using RNA sequencing technologies for rare disease investigation. Moreover, we will discuss how recent computational splicing prediction tools have emerged as complementary approaches for revealing disease-causing variants underlying splicing defects. We speculate that continuous improvements to sequencing technologies and predictive modeling will not only expand our understanding of splicing regulation but also bring us closer to filling the diagnostic gap for rare disease patients.

Global Analysis of Dark- and Heat-Regulated Alternative Splicing in Arabidopsis

Alternative splicing (AS) is one of the major post-transcriptional regulation mechanisms that contributes to plant responses to various environmental perturbations. Darkness and heat are two common abiotic factors affecting plant growth, yet the involvement and regulation of AS in the plant responses to these signals remain insufficiently examined. In this study, we subjected Arabidopsis seedlings to 6 h of darkness or heat stress and analyzed their transcriptome through short-read RNA sequencing. We revealed that both treatments altered the transcription and AS of a subset of genes yet with different mechanisms. Dark-regulated AS events were found enriched in photosynthesis and light signaling pathways, while heat-regulated AS events were enriched in responses to abiotic stresses but not in heat-responsive genes, which responded primarily through transcriptional regulation. The AS of splicing-related genes (SRGs) was susceptible to both treatments; while dark treatment mostly regulated the AS of these genes, heat had a strong effect on both their transcription and AS. PCR analysis showed that the AS of the Serine/Arginine-rich family gene SR30 was reversely regulated by dark and heat, and heat induced the upregulation of multiple minor SR30 isoforms with intron retention. Our results suggest that AS participates in plant responses to these two abiotic signals and reveal the regulation of splicing regulators during these processes.

Retained introns in long RNA-seq reads are not reliably detected in sample-matched short reads

BACKGROUND

There is growing interest in retained introns in a variety of disease contexts including cancer and aging. Many software tools have been developed to detect retained introns from short RNA-seq reads, but reliable detection is complicated by overlapping genes and transcripts as well as the presence of unprocessed or partially processed RNAs.

RESULTS

We compared introns detected by 8 tools using short RNA-seq reads with introns observed in long RNA-seq reads from the same biological specimens. We found significant disagreement among tools (Fleiss' [Formula: see text]) such that 47.7% of all detected intron retentions were not called by more than one tool. We also observed poor performance of all tools, with none achieving an F1-score greater than 0.26, and qualitatively different behaviors between general-purpose alternative splicing detection tools and tools confined to retained intron detection.

CONCLUSIONS

Short-read tools detect intron retention with poor recall and precision, calling into question the completeness and validity of a large percentage of putatively retained introns called by commonly used methods.