Challenges in detecting and quantifying intron retention from next generation sequencing data

Alternative splicing fine-tunes prey shift of Coccinellini lady beetles to non-target insect

BACKGROUND

Coccinellini lady beetles have been applied as biological control agent of aphids, however, not all of these species are obligately aphidophagous. Thus, a comprehensive understanding of the molecular mechanisms behind predaceous specificity of Coccinellini lady beetles can provide important clues for evaluating their performance and ecological risk assessment in biological control. Post-transcriptional regulations act a key role in shaping organisms' rapid adaptation to changing environment, yet, little is known about their role in the acclimation of Coccinellini lady beetles to non-target preys.

RESULTS

In this study, we conducted a genome-wide investigation to alternative splicing (AS) dynamics in three Coccinellini species Propylea japonica, Coccinella septempunctata and Harmonia axyridis in response to feeding shift from natural prey bean aphids (Megoura japonica) to non-target insect citrus mealybugs (Planococcus citri). Compared to aphid-feeding, all three lady beetles were subject to substantial splicing changes when preying on mealybugs. Most of these differentially spliced genes (DSGs) were not differentially expressed, and regulated different pathways from differentially expressed genes, indicating the functionally nonredundant role of AS. The DSGs were primarily associated with energy derivation, organ formation and development, chemosensation and immune responses, which may promote tolerance of lady beetles to nutrient deprivation and pathogen challenges induced by prey shift. The lady beetles feeding on mealybugs moreover downregulated the generation of splicing products containing premature termination codons (PTCs) for the genes involved in energy derivation and stimulus responses, to fine-tune their protein expression and rationalize energy allocation.

CONCLUSION

These findings unraveled the functional significance of AS reprogramming in modulating acclimation of Coccinellini lady beetles to prey shift from aphids to non-target insects and provided new genetic clues for evaluating their ecological safety as biological control agents.

Differential quantification of alternative splicing events on spliced pangenome graphs

Pangenomes are becoming a powerful framework to perform many bioinformatics analyses taking into account the genetic variability of a population, thus reducing the bias introduced by a single reference genome. With the wider diffusion of pangenomes, integrating genetic variability with transcriptome diversity is becoming a natural extension that demands specific methods for its exploration. In this work, we extend the notion of spliced pangenomes to that of annotated spliced pangenomes; this allows us to introduce a formal definition of Alternative Splicing (AS) events on a graph structure. To investigate the usage of graph pangenomes for the quantification of AS events across conditions, we developed pantas, the first pangenomic method for the detection and differential analysis of AS events from short RNA-Seq reads. A comparison with state-of-the-art linear reference-based approaches proves that pantas achieves competitive accuracy, making spliced pangenomes effective for conducting AS events quantification and opening future directions for the analysis of population-based transcriptomes.

Intronic RNA secondary structural information captured for the human MYC pre-mRNA

To address the lack of intronic reads in secondary structure probing data for the human MYC pre-mRNA, we developed a method that combines spliceosomal inhibition with RNA probing and sequencing. Here, the SIRP-seq method was applied to study the secondary structure of human MYC RNAs by chemically probing HeLa cells with dimethyl sulfate in the presence of the small molecule spliceosome inhibitor pladienolide B. Pladienolide B binds to the SF3B complex of the spliceosome to inhibit intron removal during splicing, resulting in retained intronic sequences. This method was used to increase the read coverage over intronic regions of MYC. The purpose for increasing coverage across introns was to generate complete reactivity profiles for intronic sequences via the DMS-MaPseq approach. Notably, depth was sufficient for analysis by the program DRACO, which was able to deduce distinct reactivity profiles and predict multiple secondary structural conformations as well as their suggested stoichiometric abundances. The results presented here provide a new method for intronic RNA secondary structural analyses, as well as specific structural insights relevant to MYC RNA splicing regulation and therapeutic targeting.

Prediction of tumor-specific splicing from somatic mutations as a source of neoantigen candidates

Motivation

Neoantigens are promising targets for cancer immunotherapies and might arise from alternative splicing. However, detecting tumor-specific splicing is challenging because many non-canonical splice junctions identified in tumors also appear in healthy tissues. To increase tumor-specificity, we focused on splicing caused by somatic mutations as a source for neoantigen candidates in individual patients.

Results

We developed the tool splice2neo with multiple functionalities to integrate predicted splice effects from somatic mutations with splice junctions detected in tumor RNA-seq and to annotate the resulting transcript and peptide sequences. Additionally, we provide the tool EasyQuant for targeted RNA-seq read mapping to candidate splice junctions. Using a stringent detection rule, we predicted 1.7 splice junctions per patient as splice targets with a false discovery rate below 5% in a melanoma cohort. We confirmed tumor-specificity using independent, healthy tissue samples. Furthermore, using tumor-derived RNA, we confirmed individual exon-skipping events experimentally. Most target splice junctions encoded neoepitope candidates with predicted major histocompatibility complex (MHC)-I or MHC-II binding. Compared to neoepitope candidates from non-synonymous point mutations, the splicing-derived MHC-I neoepitope candidates had lower self-similarity to corresponding wild-type peptides. In conclusion, we demonstrate that identifying mutation-derived, tumor-specific splice junctions can lead to additional neoantigen candidates to expand the target repertoire for cancer immunotherapies.

Availability and implementation

The R package splice2neo and the python package EasyQuant are available at https://github.com/TRON-Bioinformatics/splice2neo and https://github.com/TRON-Bioinformatics/easyquant, respectively.

Serine/arginine-rich splicing factor 7 promotes the type I interferon response by activating Irf7 transcription

Tight regulation of macrophage immune gene expression is required to fight infection without risking harmful inflammation. The contribution of RNA-binding proteins (RBPs) to shaping the macrophage response to pathogens remains poorly understood. Transcriptomic analysis reveals that a member of the serine/arginine-rich (SR) family of mRNA processing factors, SRSF7, is required for optimal expression of a cohort of interferon-stimulated genes in macrophages. Using genetic and biochemical assays, we discover that in addition to its canonical role in regulating alternative splicing, SRSF7 drives transcription of interferon regulatory transcription factor 7 (IRF7) to promote antiviral immunity. At the Irf7 promoter, SRSF7 maximizes STAT1 transcription factor binding and RNA polymerase II elongation via cooperation with the H4K20me1 histone methyltransferase KMT5a (SET8). These studies define a role for an SR protein in activating transcription and reveal an RBP-chromatin network that orchestrates macrophage antiviral gene expression.

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.

Identification of Splice Variants and Isoforms in Transcriptomics and Proteomics

Alternative splicing is pivotal to the regulation of gene expression and protein diversity in eukaryotic cells. The detection of alternative splicing events requires specific omics technologies. Although short-read RNA sequencing has successfully supported a plethora of investigations on alternative splicing, the emerging technologies of long-read RNA sequencing and top-down mass spectrometry open new opportunities to identify alternative splicing and protein isoforms with less ambiguity. Here, we summarize improvements in short-read RNA sequencing for alternative splicing analysis, including percent splicing index estimation and differential analysis. We also review the computational methods used in top-down proteomics analysis regarding proteoform identification, including the construction of databases of protein isoforms and statistical analyses of search results. While many improvements in sequencing and computational methods will result from emerging technologies, there should be future endeavors to increase the effectiveness, integration, and proteome coverage of alternative splicing events.

MARVEL: an integrated alternative splicing analysis platform for single-cell RNA sequencing data

Alternative splicing is an important source of heterogeneity underlying gene expression between individual cells but remains an understudied area due to the paucity of computational tools to analyze splicing dynamics at single-cell resolution. Here, we present MARVEL, a comprehensive R package for single-cell splicing analysis applicable to RNA sequencing generated from the plate- and droplet-based methods. We performed extensive benchmarking of MARVEL against available tools and demonstrated its utility by analyzing multiple publicly available datasets in diverse cell types, including in disease. MARVEL enables systematic and integrated splicing and gene expression analysis of single cells to characterize the splicing landscape and reveal biological insights.

mTOR Contributes to the Proteome Diversity through Transcriptome-Wide Alternative Splicing

The mammalian target of rapamycin (mTOR) pathway is crucial in energy metabolism and cell proliferation. Previously, we reported transcriptome-wide 3′-untranslated region (UTR) shortening by alternative polyadenylation upon mTOR activation and its impact on the proteome. Here, we further interrogated the mTOR-activated transcriptome and found that hyperactivation of mTOR promotes transcriptome-wide exon skipping/exclusion, producing short isoform transcripts from genes. This widespread exon skipping confers multifarious regulations in the mTOR-controlled functional proteomics: AS in coding regions widely affects the protein length and functional domains. They also alter the half-life of proteins and affect the regulatory post-translational modifications. Among the RNA processing factors differentially regulated by mTOR signaling, we found that SRSF3 mechanistically facilitates exon skipping in the mTOR-activated transcriptome. This study reveals a role of mTOR in AS regulation and demonstrates that widespread AS is a multifaceted modulator of the mTOR-regulated functional proteome.

GTFtools: a software package for analyzing various features of gene models

MOTIVATION

Gene-centric bioinformatics studies frequently involve calculation or extraction of various features of genes such as splice sites, promoters, independent introns, and untranslated regions (UTRs) through manipulation of gene models. Gene models are often annotated in gene transfer format (GTF) files. The features are essential for subsequent analysis such as intron retention detection, DNA-binding site identification, and computing splicing strength of splice sites. Some features such as independent introns and splice sites are not provided in existing resources including the commonly used BioMart database. A package that implements and integrates functions to analyze various features of genes will greatly ease routine analysis for related bioinformatics studies. However, to the best of our knowledge, such a package is not available yet.

RESULTS

In this work, we introduce GTFtools, a stand-alone command-line software that provides a set of functions to calculate various gene features, including splice sites, independent introns, transcription start sites (TSS)-flanking regions, UTRs, isoform coordination and length, different types of gene lengths, etc. It takes the ENSEMBL or GENCODE GTF files as input, and can be applied to both human and non-human gene models like the lab mouse. We compare the utilities of GTFtools with those of two related tools: Bedtools and BioMart. GTFtools is implemented in Python and not dependent on any third-party software, making it very easy to install and use.

AVAILABILITY

GTFtools is freely available at www.genemine.org/gtftools.php as well as pyPI and Bioconda.

Practical Considerations for Single-Cell Genomics

The single-cell revolution in the field of genomics is in full bloom, with clever new molecular biology tricks appearing regularly that allow researchers to explore new modalities or scale up their projects to millions of cells and beyond. Techniques abound to measure RNA expression, DNA alterations, protein abundance, chromatin accessibility, and more, all with single-cell resolution and often in combination. Despite such a rapidly changing technology landscape, there are several fundamental principles that are applicable to the majority of experimental workflows to help users avoid pitfalls and exploit the advantages of the chosen platform. In this overview article, we describe a variety of popular single-cell genomics technologies and address some common questions pertaining to study design, sample preparation, quality control, and sequencing strategy. As the majority of relevant publications currently revolve around single-cell RNA-seq, we will prioritize this genomics modality in our discussion. © 2022 Wiley Periodicals LLC.

Differential fates of introns in gene expression due to global alternative splicing

The discovery of introns over four decades ago revealed a new vision of genes and their interrupted arrangement. Throughout the years, it has appeared that introns play essential roles in the regulation of gene expression. Unique processing of excised introns through the formation of lariats suggests a widespread role for these molecules in the structure and function of cells. In addition to rapid destruction, these lariats may linger on in the nucleus or may even be exported to the cytoplasm, where they remain stable circular RNAs (circRNAs). Alternative splicing (AS) is a source of diversity in mature transcripts harboring retained introns (RI-mRNAs). Such RNAs may contain one or more entire retained intron(s) (RIs), but they may also have intron fragments resulting from sequential excision of smaller subfragments via recursive splicing (RS), which is characteristic of long introns. There are many potential fates of RI-mRNAs, including their downregulation via nuclear and cytoplasmic surveillance systems and the generation of new protein isoforms with potentially different functions. Various reports have linked the presence of such unprocessed transcripts in mammals to important roles in normal development and in disease-related conditions. In certain human neurological-neuromuscular disorders, including myotonic dystrophy type 2 (DM2), frontotemporal dementia/amyotrophic lateral sclerosis (FTD/ALS) and Duchenne muscular dystrophy (DMD), peculiar processing of long introns has been identified and is associated with their pathogenic effects. In this review, we discuss different mechanisms involved in the processing of introns during AS and the functions of these large sections of the genome in our biology.

IRFinder-S: a comprehensive suite to discover and explore intron retention

Accurate quantification and detection of intron retention levels require specialized software. Building on our previous software, we create a suite of tools called IRFinder-S, to analyze and explore intron retention events in multiple samples. Specifically, IRFinder-S allows a better identification of true intron retention events using a convolutional neural network, allows the sharing of intron retention results between labs, integrates a dynamic database to explore and contrast available samples, and provides a tested method to detect differential levels of intron retention.

Implications of Antigen Selection on T Cell-Based Immunotherapy

Many immunotherapies rely on CD8+ effector T cells to recognize and kill cognate tumor cells. These T cell-based immunotherapies include adoptive cell therapy, such as CAR T cells or transgenic TCR T cells, and anti-cancer vaccines which expand endogenous T cell populations. Tumor mutation burden and the choice of antigen are among the most important aspects of T cell-based immunotherapies. Here, we highlight various classes of cancer antigens, including self, neojunction-derived, human endogenous retrovirus (HERV)-derived, and somatic nucleotide variant (SNV)-derived antigens, and consider their utility in T cell-based immunotherapies. We further discuss the respective anti-tumor/anti-self-properties that influence both the degree of immunotolerance and potential off-target effects associated with each antigen class.

A second hit somatic (p.R905W) and a novel germline intron-mutation of TSC2 gene is found in intestinal lymphangioleiomyomatosis: a case report with literature review

BACKGROUND

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder characterized by hamartomas in multiple organs associated with germline mutations in TSC1 and TSC2, including exonic, intronic, or mosaic mutations. Gastrointestinal (GI) tract Lymphangioleiomyomatosis (LAM) is an extremely rare manifestation of TSC, with few reported cases. Herein, we aimed to determine the driver mutation, pathogenesis, and relationship of germline and somatic mutations of LAM through whole-genome sequencing (WGS) of the tumor and blood samples and whole transcriptome sequencing (WTS) analysis.

CASE PRESENTATION

A nine-year-old girl with a full-blown TSC presented with abdominal masses detected during a routine check-up. Resected intestinal masses were diagnosed as LAM by thorough pathological examination. Interestingly, the LAM presented a somatic TSC2 gene mutation in exon 24 (p.R905W, c.C2713T), and the patient had intron retention by a novel germline mutation in the intron region of TSC2 (chr16:2126489, C > G).

CONCLUSION

Our case suggests that intron retention by a single nucleotide intronic mutation of TSC2 is sufficient to develop severe manifestations of TSC, but the development of LAM requires an additional somatic oncogenic mutation of TSC2.

Reactive astrocytes in ALS display diminished intron retention

Reactive astrocytes are implicated in amyotrophic lateral sclerosis (ALS), although the mechanisms controlling reactive transformation are unknown. We show that decreased intron retention (IR) is common to human-induced pluripotent stem cell (hiPSC)-derived astrocytes carrying ALS-causing mutations in VCP, SOD1 and C9orf72. Notably, transcripts with decreased IR and increased expression are overrepresented in reactivity processes including cell adhesion, stress response and immune activation. This was recapitulated in public-datasets for (i) hiPSC-derived astrocytes stimulated with cytokines to undergo reactive transformation and (ii) in vivo astrocytes following selective deletion of TDP-43. We also re-examined public translatome sequencing (TRAP-seq) of astrocytes from a SOD1 mouse model, which revealed that transcripts upregulated in translation significantly overlap with transcripts exhibiting decreased IR. Using nucleocytoplasmic fractionation of VCP mutant astrocytes coupled with mRNA sequencing and proteomics, we identify that decreased IR in nuclear transcripts is associated with enhanced nonsense mediated decay and increased cytoplasmic expression of transcripts and proteins regulating reactive transformation. These findings are consistent with a molecular model for reactive transformation in astrocytes whereby poised nuclear reactivity-related IR transcripts are spliced, undergo nuclear-to-cytoplasmic translocation and translation. Our study therefore provides new insights into the molecular regulation of reactive transformation in astrocytes.

Tracking pre-mRNA maturation across subcellular compartments identifies developmental gene regulation through intron retention and nuclear anchoring

Steps of mRNA maturation are important gene regulatory events that occur in distinct cellular locations. However, transcriptomic analyses often lose information on the subcellular distribution of processed and unprocessed transcripts. We generated extensive RNA-seq data sets to track mRNA maturation across subcellular locations in mouse embryonic stem cells, neuronal progenitor cells, and postmitotic neurons. We find disparate patterns of RNA enrichment between the cytoplasmic, nucleoplasmic, and chromatin fractions, with some genes maintaining more polyadenylated RNA in chromatin than in the cytoplasm. We bioinformatically defined four regulatory groups for intron retention, including complete cotranscriptional splicing, complete intron retention in the cytoplasmic RNA, and two intron groups present in nuclear and chromatin transcripts but fully excised in cytoplasm. We found that introns switch their regulatory group between cell types, including neuronally excised introns repressed by polypyrimidine track binding protein 1 (PTBP1). Transcripts for the neuronal gamma-aminobutyric acid (GABA) B receptor, 1 (Gabbr1) are highly expressed in mESCs but are absent from the cytoplasm. Instead, incompletely spliced Gabbr1 RNA remains sequestered on chromatin, where it is bound by PTBP1, similar to certain long noncoding RNAs. Upon neuronal differentiation, Gabbr1 RNA becomes fully processed and exported for translation. Thus, splicing repression and chromatin anchoring of RNA combine to allow posttranscriptional regulation of Gabbr1 over development. For this and other genes, polyadenylated RNA abundance does not indicate functional gene expression. Our data sets provide a rich resource for analyzing many other aspects of mRNA maturation in subcellular locations and across development.

The genetics of mitochondrial disease: dissecting mitochondrial pathology using multi-omic pipelines

Mitochondria play essential roles in numerous metabolic pathways including the synthesis of adenosine triphosphate through oxidative phosphorylation. Clinically, mitochondrial diseases occur when there is mitochondrial dysfunction – manifesting at any age and affecting any organ system; tissues with high energy requirements, such as muscle and the brain, are often affected. The clinical heterogeneity is parallel to the degree of genetic heterogeneity associated with mitochondrial dysfunction. Around 10% of human genes are predicted to have a mitochondrial function, and defects in over 300 genes are reported to cause mitochondrial disease. Some involve the mitochondrial genome (mtDNA), but the vast majority occur within the nuclear genome. Except for a few specific genetic defects, there remains no cure for mitochondrial diseases, which means that a genetic diagnosis is imperative for genetic counselling and the provision of reproductive options for at‐risk families. Next‐generation sequencing strategies, particularly exome and whole‐genome sequencing, have revolutionised mitochondrial diagnostics such that the traditional muscle biopsy has largely been replaced with a minimally‐invasive blood sample for an unbiased approach to genetic diagnosis. Where these genomic approaches have not identified a causative defect, or where there is insufficient support for pathogenicity, additional functional investigations are required. The application of supplementary ‘omics’ technologies, including transcriptomics, proteomics, and metabolomics, has the potential to greatly improve diagnostic strategies. This review aims to demonstrate that whilst a molecular diagnosis can be achieved for many cases through next‐generation sequencing of blood DNA, the use of patient tissues and an integrated, multidisciplinary multi‐omics approach is pivotal for the diagnosis of more challenging cases. Moreover, the analysis of clinically relevant tissues from affected individuals remains crucial for understanding the molecular mechanisms underlying mitochondrial pathology. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

TALC: Transcript-level Aware Long-read Correction

MOTIVATION

Long-read sequencing technologies are invaluable for determining complex RNA transcript architectures but are error-prone. Numerous 'hybrid correction' algorithms have been developed for genomic data that correct long reads by exploiting the accuracy and depth of short reads sequenced from the same sample. These algorithms are not suited for correcting more complex transcriptome sequencing data.

RESULTS

We have created a novel reference-free algorithm called Transcript-level Aware Long-Read Correction (TALC) which models changes in RNA expression and isoform representation in a weighted De Bruijn graph to correct long reads from transcriptome studies. We show that transcript-level aware correction by TALC improves the accuracy of the whole spectrum of downstream RNA-seq applications and is thus necessary for transcriptome analyses that use long read technology.

AVAILABILITY AND IMPLEMENTATION

TALC is implemented in C++ and available at https://github.com/lbroseus/TALC.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Intron retention and its impact on gene expression and protein diversity: A review and a practical guide

Intron retention (IR) occurs when a complete and unspliced intron remains in mature mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions, including several that impact human health and disease. Although experimental technologies used to study other forms of mRNA splicing can also be used to investigate IR, a specialized downstream computational analysis is optimal for IR discovery and analysis. Here we provide a review of IR and its biological implications, as well as a practical guide for how to detect and analyze it. Several methods, including long read third generation direct RNA sequencing, are described. We have developed an R package, FakIR, to facilitate the execution of the bioinformatic tasks recommended in this review and a tutorial on how to fit them to users aims. Additionally, we provide guidelines and experimental protocols to validate IR discovery and to evaluate the potential impact of IR on gene expression and protein output. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Regulation/Alternative Splicing RNA Methods > RNA Analyses in vitro and In Silico.

Relative and Absolute Quantification of Aberrant and Normal Splice Variants in HBBIVSI-110 (G > A) β-Thalassemia

The β-thalassemias are an increasing challenge to health systems worldwide, caused by absent or reduced β-globin (HBB) production. Of particular frequency in many Western countries is HBBIVSI-110(G > A) β-thalassemia (HGVS name: HBB:c.93-21G > A). Its underlying mutation creates an abnormal splice acceptor site in the HBB gene, and while partially retaining normal splicing of HBB, it severely reduces HBB protein expression from the mutant locus and HBB loci in trans. For the assessment of the underlying mechanisms and of therapies targeting β-thalassemia, accurate quantification of aberrant and normal HBB mRNA is essential, but to date, has only been performed by approximate methods. To address this shortcoming, we have developed an accurate, duplex reverse-transcription quantitative PCR assay for the assessment of the ratio and absolute quantities of normal and aberrant mRNA species as a tool for basic and translational research of HBBIVSI-110(G > A) β-thalassemia. The method was employed here to determine mRNA ratios and quantities in blood and primary cell culture samples and correlate them with HBB protein levels. Moreover, with its immediate utility for β-thalassemia and the mutation in hand, the approach can readily be adopted for analysis of alternative splicing or for quantitative assays of any disease-causing mutation that interferes with normal splicing.

Alternative splicing and cancer: insights, opportunities, and challenges from an expanding view of the transcriptome

Over the past decade there has been increased awareness of the potential role of alternative splicing in the etiology of cancer. In particular, advances in RNA-Sequencing technology and analysis has led to a wave of discoveries in the last few years regarding the causes and functional relevance of alternative splicing in cancer. Here we discuss the current understanding of the connections between splicing and cancer, with a focus on the most recent findings. We also discuss remaining questions and challenges that must be addressed in order to use our knowledge of splicing to guide the diagnosis and treatment of cancer.

Intron Retention as a Mode for RNA-Seq Data Analysis

Intron retention (IR) is an alternative splicing mode whereby introns, rather than being spliced out as usual, are retained in mature mRNAs. It was previously considered a consequence of mis-splicing and received very limited attention. Only recently has IR become of interest for transcriptomic data analysis owing to its recognized roles in gene expression regulation and associations with complex diseases. In this article, we first review the function of IR in regulating gene expression in a number of biological processes, such as neuron differentiation and activation of CD4⁺ T cells. Next, we briefly review its association with diseases, such as Alzheimer's disease and cancers. Then, we describe state-of-the-art methods for IR detection, including RNA-seq analysis tools IRFinder and iREAD, highlighting their underlying principles and discussing their advantages and limitations. Finally, we discuss the challenges for IR detection and potential ways in which IR detection methods could be improved.