Preprint
Review

This version is not peer-reviewed.

Expression of mRNA Isoforms in Health and Diseases

Submitted:

09 April 2025

Posted:

10 April 2025

You are already at the latest version

Abstract
Cellular gene expression varies in different physiological and pathological conditions. Analysis of differential gene expression enables researchers to understand the cellular changes associated with physiological or pathological conditions. During gene expression analyses, researchers calculate the transcripts expressed from a gene under that gene's name, assuming only a single mRNA is expressed by that gene. However, this assumption is biologically inaccurate, but it is often preferred to avoid the complex analyses of isoforms. Most mammalian genes express more than three mRNAs, which encode various proteins or act as noncoding RNAs. We have previously addressed the molecular basis mRNA isoform formation and detection strategies. In this review article, we have discussed the physiological and pathological roles of mRNA isoforms. Any specific cell may express different isoforms of mRNA from a specific gene depending on its differentiation state. Different isoforms can be expressed from a single gene at various stages of development and during aging. The same cell may also express mRNA isoforms related to pathological conditions. Summarized findings highlight the importance of detecting mRNA isoforms over conventional gene identification.
Keywords: 
;  ;  ;  ;  ;  ;  

1. Introduction

mRNA transcript variants are the diverse RNA isoforms derived from a single gene locus. These isoforms arise due to alternative transcription start sites (TSS), alternative splicing of precursor mRNAs (pre-mRNAs), and alternative transcription termination and alternative polyadenylation sites (APS). Alternative TSS and APS result in variation in the 5’-end and 3’-end of mRNA, respectively; however, alternative splicing can alter any part of the pre-mRNA [1]. Eventually, mRNA isoforms vary in their coding sequencing in the amino-terminal, carboxy-terminal, or other functional domains and encode proteins with diverse functional domains or form noncoding regulatory RNAs [2,3]. Enabling a single gene to encode multiple protein isoforms or non-coding RNAs, the mRNA transcript variants fine-tune cellular signaling, differentiation, and adaptation to environmental cues [4,5]. Tissue cells generate selective mRNA isoforms that help cells adapt to dynamic physiological and pathological conditions [6,7]. This transcriptomic plasticity is essential for developmental programs, tissue-specific functions, and the decline of functions during aging. Thus, dysregulation of mRNA isoform expression may disrupt molecular homeostasis, contributing to various diseases [8,9].
In embryonic development and organogenesis, they facilitate precise spatiotemporal gene expression, impacting heart, brain, and placental development [10]. Tissue-specific splicing events and APS create diverse mRNA molecules with variable 3' untranslated regions (UTRs), influencing mRNA stability, localization, and translation efficiency [11]. In physiological contexts, isoforms orchestrate critical processes such as cell lineage specification, immune response modulation, and neuronal plasticity [12]. Tissue-specific splicing factors and RNA-binding proteins guide the production of isoforms tailored to distinct cellular niches, ensuring precise spatiotemporal control over gene expression [13]. However, perturbations in RNA processing machinery due to mutations in spliceosome components, epigenetic alterations, or aberrant expression of regulatory RNAs can generate pathogenic isoforms [14]. These dysregulated isoforms often exhibit gain-of-function, dominant-negative, or neomorphic properties that subvert normal cellular checkpoints, fostering disease progression [15]. During aging, changes in splicing patterns, increased errors, and alterations in chromatin structure disrupt mRNA isoform production [16,17]. Accelerated transcription and splicing increase the chance of erroneous splicing events, affecting genes involved in DNA repair, apoptosis, and muscle homeostasis, contributing to cellular decline [18]. The activities of retrotransposons and the quality control mechanisms of RNA also influence these changes [19,20].
The pathological influence of mRNA isoforms spans cancer, neurodegenerative disorders, cardiovascular diseases, and metabolic syndromes [21]. Aberrant isoforms may enhance oncogenic signaling, promote protein aggregation, or impair contractile function in tissues, depending on the disease context [22,23]. Emerging evidence also implicates these isoforms in immune evasion, drug resistance, and intercellular communication, underscoring their systemic impact [24]. Critically, advances in long-read sequencing and single-cell transcriptomics have unveiled previously unrecognized isoform-level alterations, redefined molecular classifications of diseases, and revealed novel biomarkers [25]. Thus, studying the mRNA isoforms is essential for advancing our understanding of gene expression and its implications for health and diseases [26]. In the following sections, we have discussed the importance of studying isoforms in normal physiology, disease pathology and the potential for translational research [27]. This process enables a single gene to produce multiple transcript variants, allowing for fine-tuned regulation of cellular processes, including signaling, metabolism, and immune responses. However, dysregulation of mRNA isoforms can disrupt these processes, leading to pathological outcomes across a wide range of diseases [28].

2. Physiological Roles of mRNA Isoforms

Although most mammalian genes express mRNA isoforms, this area has been minimally explored due to the complexity of detecting and characterizing the isoforms. Our recent efforts have been targeted at revisiting this field of molecular biology [9,29,30]. mRNA isoforms diversify the gene’s protein expression and cellular functional capacity. In the following section, we have discussed the physiological importance of mRNA isoforms during development, organogenesis, and aging.

2.1. mRNA Isoforms in Development and Organogenesis

The role of mRNA isoforms in development and organogenesis begins at fertilization, where maternal transcripts deposited in the oocyte guide early embryonic processes [31]. Following fertilization, the maternal-to-zygotic transition (MZT) marks a pivotal shift in gene regulation as zygotic genome activation (ZGA) replaces maternal control [32]. During this transition, alternative splicing generates specific mRNA isoforms critical for embryonic development [33]. In zebrafish embryos, genes like Pou5f1 (Oct4), Sall4, and Dnmt1 express isoforms associated with pluripotency and DNA methylation, essential for ZGA and early cell fate decisions [34]. Similarly, isoform changes in genes like F11r and Magi1 alter coding sequences to facilitate cell-cell interactions during ZGA [35].
In mice, RNA-binding proteins such as CSDE1 undergo isoform switching during ZGA, characterized by exon skipping that impacts maternal transcript clearance [36,37]. Splicing factors like SF3B1 and RBFOX2 also play crucial roles in generating isoforms that regulate pluripotency and lineage specification [38]. These splicing events are tightly coordinated with chromatin remodeling processes mediated by histone variants like H2A.Z, which destabilize nucleosomes to enable transcriptional activation [39,40]. Transcriptome-wide analyses in zebrafish and mouse embryos revealed the dynamic changes in isoforms that regulate tissue-specific gene expression [41]. As the embryo develops through gastrulation and organogenesis, waves of isoform switching correlate with the formation of major organs such as the heart and neural tube [42]. Alternative splicing of genes like RBM20 and NOVA2 generates isoforms essential for cardiac development and neural differentiation [43]. In addition, transcription factors such as SRF influence cardiac-specific gene expression by regulating transcript variants critical for myocardin-mediated developmental pathways (44-46). Variants of transcription factors such as NR5A1, RUNX, and BAD are involved in adrenal and gonadal development [47]. It has been demonstrated that NR5A1 isoforms are expressed in gonadal precursor cells and regulate the differentiation of the adrenal and gonadal tissues. Mutations or dysregulation of NR5A1 can lead to disorders of sex determination and adrenal insufficiency [48,49].
Epigenetic mechanisms further regulate the generation of mRNA isoforms during organogenesis. Histone acetyltransferases (HATs) like p300/CBP deposit H3K27 acetylation marks at active enhancers, facilitating tissue-specific gene activation [50,51]. Conversely, histone deacetylases (HDACs) compact chromatin to repress transcription in specific sites [52]. DNA methylation complements these processes by silencing non-essential genes, while demethylation activates enhancers critical for tissue identity [53,54]. Throughout organogenesis, APS generates mRNA isoforms with variable 3′UTR lengths that impact post-transcriptional regulation [55]. For example, APS of Hmga2 produces shorter isoforms with reduced regulatory complexity but increased translational efficiency, supporting rapid protein synthesis during development [56,57].
As the embryo matures into a fetus, mRNA isoforms continue to undergo complex developmental programs across tissues [58]. Aberrant expression or processing of these isoforms can lead to developmental abnormalities such as neurodevelopmental disorders or congenital defects [59]. Moreover, aberrant splicing events caused by synonymous or intronic variants can activate cryptic splice sites, leading to exon truncation or misregulation of developmental genes [60]. For instance, mutations affecting splicing regulators, such as FOXP4 or frameshift variants in HMGB1, disrupt normal gene expression [58]. The frameshift variants in the HMGB1 protein have been shown to alter phase separation and nucleolar function, resulting in rare syndromes such as brachyphalangy, polydactyly, and tibial aplasia syndrome, underscoring the role of mRNA isoforms in proper organogenesis [58,61,62].

2.2. mRNA Isoforms Regulating Physiological Functions

mRNA isoforms are fundamental to normal physiology after birth, contributing to tissue-specific gene expression, protein diversity, and cellular adaptation to environmental stimuli [63]. Through mechanisms such as alternative splicing and alternative polyadenylation, mRNA isoforms allow a single gene to produce multiple protein variants with distinct functions or regulatory properties [9,64]. By allowing a single gene to generate multiple transcript variants, mRNA isoforms diversify protein functions and regulate cellular processes [65]. This process is essential for maintaining the specialized functions of different tissues and organs [66].
Alternative splicing, a major driver of transcript diversity, dynamically regulates gene expression across tissues. For instance, the CACNA1C gene, which is involved in cardiac function and blood pressure regulation, generates over 10,000 splice variants, with some isoforms specific to smooth muscle and others to cardiac tissue [67,68]. In the nervous system, splice variants of neurotransmitter receptors and ion channels play critical roles in synaptic plasticity and neuronal function [69]. The Drosophila Dscam gene exemplifies the extreme diversity generated by alternative splicing, producing over 38,000 isoforms through the alternative splicing of 95 variable exons that contribute to neural connectivity [70,71]. RNA-binding proteins (RBPs) are key regulators of alternative splicing and other post-transcriptional processes. RBPs such as SRSF1 and hnRNPs influence exon inclusion or exclusion, shaping protein structure and functionality critical for cell growth, differentiation, and metabolism. These proteins also regulate mRNA stability, localization, and translation efficiency, ensuring precise control of cellular processes in response to physiological changes [72]. RNA modifications further enhance regulatory complexity. For example, N6-methyladenosine (m6A) modifications influence mRNA structure, stability, splicing, export, translation, and decay [73,74]. During stress conditions like heat shock, m6A modifications in the 5′ UTR of HSP70 mRNA promote cap-independent translation to support cellular adaptation [75,76].
APS generates mRNA isoforms with variable 3′ UTRs, altering regulatory elements such as microRNA binding sites and RNA-binding protein interactions [77]. This mechanism enables tissue-specific gene expression and modulates protein abundance in response to environmental cues [78]. It has been reported that APS increases protein levels in skeletal and cardiac tissues while reducing neuronal gene expression through intronic cleavage [79]. The generation of mRNA isoforms is controlled by tissue-specific regulation of pre-mRNA processing. TBX20 transcription factor isoforms are expressed selectively in tissues like the aorta, coronary artery, testis, pituitary gland, and heart [72]. Such specificity underscores the significance of mRNA isoforms in regulating gene expression across various organ systems.

2.3. mRNA Isoforms in Aging

The aging process profoundly impacts the generation of mRNA isoforms, driving changes in gene expressions and cellular functions. As organisms age, alternative splicing patterns shift, altering tissue-specific expression and function of critical genes [80]. Nearly 49,869 splicing events have been identified during human aging that can affect DNA repair, apoptosis, and RNA processing [81]. These changes are often accompanied by an imbalance in transcript length, with shorter transcripts linked to inflammation and functional decline, while longer transcripts are associated with increased lifespan [82].
Epigenetic changes play a significant role in altering mRNA isoform expression during aging. The loss of histone H3K36 methylation exposes cryptic promoters, leading to the production of non-canonical transcripts that may disrupt gene regulation and limit lifespan [83,84]. RNA-binding proteins (RBPs), which regulate splicing, mRNA stability, and translation, exhibit declining levels with aging [85]. Proteins like HuR and TIA-1 lose their ability to stabilize stress-response transcripts, weakening cellular repair mechanisms and exacerbating age-related damage [86]. Additionally, specific transcript variants like Cdkn1a variant 2, which encodes the P21CIP1/WAF1 protein, are a specific marker of aging and cellular senescence [87]. The elevated level of this isoform of Cdkn1a was observed in multiple tissues of aging mice, including the liver, adipose tissue, kidney, heart, and lung [88]. Post-transcriptional processes, including transcription elongation and alternative splicing, remain central to the cellular landscape of aging. In the human brain alone, over 1,174 exons exhibit differential expression with age, reflecting decreased alternative splicing across multiple tissues, including blood, skin, muscle, bone, thymus, spleen, and adipose tissue [81]. Accelerated transcription elongation increases splicing and raises the likelihood of erroneous splicing, which is detrimental to cellular functions.
One hallmark of aging is the acceleration of RNA polymerase II (Pol II) elongation speed across species and tissues [89]. This increased transcriptional speed disrupts the fidelity of RNA splicing, leading to reduced unspliced transcripts and elevated circular RNA formation [90,91]. Such changes alter isoform ratios and compromise protein activity, contributing to functional decline [92]. Genes involved in DNA repair and muscle homeostasis are particularly affected, with splicing errors resulting in aberrant isoforms that undergo nonsense-mediated decay [63]. It has been demonstrated that aging alters the splice variants of genes such as ESRRG and TET2 in skeletal muscle, which are essential for type-1 muscle fiber development and myogenic differentiation [92]. Aging also changes the splice variants of genes, which may cause muscle damage [92]. It has been found that lifespan-extending interventions, such as dietary restriction and reduced insulin-IGF signaling, can reverse those transcriptional and splicing alterations in skeletal muscle [93].
Aging also activates retrotransposable elements, increasing genomic instability as these mobile genetic elements generate cDNAs through reverse transcription [19]. This activity can lead to genomic reinsertion and DNA damage, induction of new mRNA variant expression, and exacerbation of cellular dysfunction. Interestingly, lifespan-extending interventions like caloric restriction have been shown to suppress retrotransposon activity in aged mice, highlighting the connection between retrotransposon regulation and longevity [94,95]. Declines in RNA quality control mechanisms further compromise mRNA integrity during aging [96]. In organisms like C. elegans, age-associated reductions in mannosyltransferase ALGN-2 impair nonsense-mediated mRNA decay, allowing harmful splicing errors to accumulate. These breakdowns contribute to cellular dysfunction across aging tissues [97].

3. mRNA Isoforms in Disease Conditions

mRNA isoforms, arising from alternative TSS, alternative splicing, RNA editing, and other post-transcriptional modifications, play a crucial role in systemic diseases by diversifying protein functions and altering cellular processes [98]. These isoforms enable fine-tuned regulation of gene expression, but their dysregulation can disrupt physiological balance and drive disease progression across multiple organs and systems [99]. The generation of mRNA isoforms plays a multifaceted role in disease conditions. Some mRNA isoforms are formed in the host cells in response to the disease, while abnormal mRNA isoforms can be responsible for the disease pathogenesis. For simple understanding, we have described these mRNA isoforms according to the types of human diseases. We have grouped the diseases into infectious and non-infectious diseases. Non-infectious diseases are further sub-grouped into chronic systemic diseases, autoimmune diseases, metabolic diseases, and tumors.

3.1. mRNA Isoforms in Infectious Diseases

mRNA isoforms play a key role in infectious diseases, influencing host-pathogen interactions, immune responses, and disease progression. Interaction between hosts and pathogens modulates cellular mechanisms, leading to alternative splicing and expression of transcript variants in both [100]. This dynamic interplay and expression of mRNA isoforms may result in the inhibition or promotion of the disease. Thus, exploring the transcript variants may help in understanding the molecular mechanisms underlying infectious diseases.
In viral infections, altered splicing often benefits the pathogen by enhancing the replication and survival of the virus. For example, Epstein-Barr virus (EBV) interferes with the host splicing machinery to skip exon 11 in the MPPE1 gene, expressing an MPPE1 isoform that contributes to EBV-related tumorigenesis [101]. Similarly, HIV-1 infection alters splicing in host genes like CCNT1 and RUNX1 [102,103]. Reduced expression of RUNX1b and RUNX1c transcript isoforms that usually inhibit viral replication increase viral titer [104,105]. HIV also promotes exon 7 skipping in CCNT1, suppressing transcriptional activation and maintaining latency in infected CD4+ T cells [102,103]. The Hepatitis B virus (HBV) is known to produce a spliced viral RNA isoform, SP1 RNA, which dampens inflammatory responses in the host to evade immune detection and establish a chronic infection [106,107].
Bacterial infections exploit alternative splicing to manipulate host defenses. Host response to infections also changes the expression of mRNA isoforms to augment immune functions [108]. Mycobacterium tuberculosis (MTB) promotes exon skipping in the RAB8B gene to produce truncated isoforms that impair macrophage autophagy, allowing intracellular bacterial survival [109]. MTB further alters the splicing of the IL-12Rβ mRNA transcript to generate a shorter isoform (IL-12Rβ1ΔTM) that enhances dendritic cell migration and MTB-specific T cell activation, promoting bacterial survival while modulating immune responses [110,111]. Other bacteria, like Listeria monocytogenes, influence the host splicing machinery through toxins like Listeriolysin O [112]. This toxin induces the alternative splicing of the cold-inducible RNA-binding protein (CIRBP), resulting in two isoforms with opposing actions. While CIRBP-201 reduces intracellular bacterial load by promoting immune responses, CIRBP-210 facilitates bacterial survival by supporting stress-related pathways [112,113]. Similarly, during Salmonella typhi infections, alternative splicing of interleukin-15 (IL-15) mRNA produces isoforms that either enhance interferon-gamma production for effective bacterial control or weaken immune responses to allow bacterial proliferation [114].These adaptive changes highlight the dual role of mRNA isoforms in infection-either bolstering host defenses or inadvertently supporting pathogen survival [115].
Parasitic infections also leverage mRNA isoform regulation to disrupt the host cellular functions. In trypanosomiasis, skipping exon 15 of the HDAC7 gene generates isoforms that inhibit host cell cycle pathways, promoting parasite survival and persistence [116,117].

3.2. mRNA Isoforms in Non-Infectious Diseases

mRNA isoforms also play a critical role in the pathogenesis and prognosis of non-infectious diseases. While pathogenic transcript variants cause certain diseases, others are associated with the progression of diseases and the response to conventional or targeted therapies. In the following section, we have discussed the role of mRNA transcript variants in autoimmune diseases, systemic and metabolic diseases, and tumors.

3.2.1. mRNA Isoforms in Autoimmune Diseases

Studies have shown that mRNA isoforms play a significant role in autoimmune diseases. Alternative protein isoforms profoundly impact immune signaling, antigen presentation, and inflammatory responses [118,119]. This process can also disrupt immune tolerance and contribute to tissue damage in autoimmune diseases [118,119]. In the following section, we discuss several autoimmune diseases, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), Sjögren's syndrome, multiple sclerosis (MS), Graves' disease, inflammatory bowel diseases (IBD), and type 1 diabetes mellitus (T1DM).
In SLE, alternative splicing is dysregulated, particularly affecting the genes crucial for immune regulation. Genome-wide studies have revealed widespread intron retention and exon skipping in immune-related genes in SLE patients, underscoring the impact of splicing dysregulation [120]. Splicing changes in IRF5 transcript that encode transcription factors involved in interferon signaling generate isoforms that amplify pro-inflammatory cytokine production, exacerbating the chronic inflammation in SLE [121,122]. Similarly, variants in the CTLA4 gene produce isoforms that modulate T-cell activation differently, increasing susceptibility to SLE [123,124]. The exact mechanism can also play a causative role in other autoimmune conditions, such as RA and T1DM [123,124]. In RA, the alternative splicing of the CD44 gene, which encodes a cell surface receptor involved in leukocyte migration and inflammation, results in the production of multiple isoforms [125,126]. Altered splicing of the TNFRSF1B transcript, which encodes the tumor necrosis factor receptor 2 (TNFR2) protein, a soluble isoform of the receptor that modulates TNF signaling and perpetuates chronic inflammation in RA [127]. While increased expression of IRAK1 isoforms enhances the interferon signaling in SLE, an elevated level of non-functional SIGLEC10 isoforms impairs the anti-inflammatory activity in RA (128-130). Another autoimmune disease, Sjögren's disease, can occur by itself or alongside other autoimmune diseases like SLE and RA. Studies have shown that transcript variants of several genes involved in immunity are dysregulated. A genetic variant (rs10774671) alters the splicing of OAS1, resulting in the production of alternative isoforms, such as p42, p48, and p44, rather than the p46 isoform [131]. The isoforms impair responsiveness to IFN stimulation and contribute to the production of autoantibodies, leading to chronic inflammation (132-134). Studies have shown that dysregulated isoforms in genes like STAT4 and IRF5 influence inflammation and fibrosis in another autoimmune disease known as scleroderma [135,136]. Increased expression of NBPF family transcripts in dermal fibroblasts drives abnormal tissue remodeling, while splicing alterations in TGF-β signaling pathways further amplify fibrotic processes [137].
In MS, dysregulation of RNA splicing leads to the expression of autoantigens from the genes that generally maintain myelination of axons [138]. These alterations exacerbate immune-mediated damage to the central nervous system, contributing to the pathogenesis of MS [139]. Splicing changes in the MOG gene generate isoforms targeted by autoantibodies, while defects in the PLP gene contribute to demyelination and neurodegeneration [140]. Myasthenia gravis (MG) is a chronic autoimmune disorder that causes muscle weakness and fatigue. In MG, alternative splicing impairs neuromuscular signaling and the host immune system mistakenly attacks the connection between the nerves and muscles. It has been shown that the isoforms of the CHRNA1 gene disrupt acetylcholine receptor assembly, thereby weakening neuromuscular communication and leading to muscle weakness [141].
Graves’ disease, an autoimmune thyroid disease, highlights the role of alternative splicing in thyroid dysfunction. The TSH receptor (TSHR) gene produces truncated isoforms, such as ST4 and ST5, that impair central tolerance by allowing autoreactive T cells to target the TSHR [142,143]. The production of autoantibodies against the TSHR affects TSH-signaling and leads to hyperthyroidism. Altered splicing of other thyroid function-related genes, like thyroid peroxidase (TPO), further enhances autoantigenicity [142,144].
Pathogenesis of inflammatory bowel diseases (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), are also impacted by alternative isoform generation [145]. Splicing of the STAT3 gene produces isoforms with distinct immune regulatory functions [146]. Dysregulated splicing of MLCK generates variants, such as MLCK2, which increases intestinal permeability and promotes bacterial invasion, thereby worsening inflammation [147,148]. Splice variants of the glycoprotein 2 (GP2) gene also function as autoantigens, targeted by autoantibodies, which enhance bacterial adhesion to the intestinal epithelium and drive disease progression in IBD [149]. In Crohn’s disease, altered splicing of NOD2 transcript impairs bacterial sensing. LACC1 transcript variants expressed from alternative promoters inhibit the differentiation of regulatory T cells, thereby increasing inflammation. Isoforms of IL-23R alter the IL-23/IL-17 axis, a critical pathway in Crohn’s disease pathogenesis (150-152). In ulcerative colitis, splicing changes in genes like PTPRS produce isoforms that alter receptor function, disrupting immune signaling and mucosal repair [153]. For instance, the loss of exon 9 in PTPRS affects ligand recognition and dimerization, contributing to colitis progression [154].
In T1DM, splicing changes in autoantigen-encoding genes play a pivotal role [155]. The IA-2 gene produces alternatively spliced isoforms that alter its immunogenicity, influencing how autoreactive T cells target pancreatic beta cells. As mentioned above, alternative splicing of CTLA4 generates soluble isoforms that disrupt T-cell regulation, exacerbating the autoimmune attack on insulin-producing cells and accelerating disease progression (156-158).
Sarcoidosis is a chronic inflammatory disease that affects the lungs, skin, or lymph nodes. It is not a typical autoimmune disease, but its pathogenesis shares similarities with those of other autoimmune diseases. Sarcoidosis has mRNA isoforms that contribute to inflammation and the formation of granulomas. Aberrant expression of THE1B fusion isoforms correlates with disease activity, whereas splice variants such as SIRPB1-SIRPD activate NF-κB pathways in granuloma-associated macrophages. Isoforms of IGF-1 contribute to fibrotic changes that worsen the progression of sarcoidosis [159,160].

3.2.2. mRNA Isoforms in Chronic Systemic Diseases

mRNA isoforms, produced through alternative pre-mRNA processing and the use of alternative TSS, play a significant role in various disease conditions [161]. Disruption of the normal isoform versus pathogenic variants balance contributes to pathological mechanisms [161]. Among the systemic diseases, neurological disorders are the most common chronic diseases that result from pathogenic transcript variants. Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia (FTD) are deeply intertwined with the dysregulation of mRNA isoform generation.
In Alzheimer’s disease, changes in the ratio of amyloid precursor protein (APP) isoforms are linked to plaque formation and neuronal damage [162]. Splicing changes in MAPT generate tau isoforms that aggregate into neurofibrillary tangles, a hallmark of AD [162,163]. A recent study has identified read-through transcripts, such as TOMM40-APOE, at Alzheimer’s susceptibility loci, which are linked to disease risk. Similarly, neuropsychiatric disorders involve novel mRNA isoforms of ATG13 and GATAD2A genes, which alter the protein domains and play a pathogenic role [164]. In PD, variants of the SNCA gene alter the alpha-synuclein expression, leading to toxic Lewy body formation [165]. It has been found that mutations in the TARDBP gene impair splicing regulation, leading to the production of abnormal protein isoforms that drive motor neuron degeneration in ALS [166,167]. ALS and FTD involve mutations in genes like C9ORF72, which produce RNA sites that disrupt splicing regulation. These mutations lead to mis-spliced TDP-43 aggregates in the cytoplasm, damaging neurons [168,169]. Similarly, in Huntington’s disease-like 2 (HDL2), splicing defects in the JPH3 gene lead to toxic RNA gain-of-function effects that disrupt ion channel activity [170,171]. Retinal degeneration further underscores the significance of isoform-specific functions of the CRB1 gene, which is essential for photoreceptor cell integrity, and the loss of CRB1 function results in increased cell death [172,173]. Retinitis pigmentosa also exemplifies the consequences of splicing-related mutations; alterations in genes such as PRPF31 and PRPF8 impair mRNA processing, leading to photoreceptor degeneration and progressive vision loss [174,175]. Beyond neurological conditions, isoform dysregulation impacts neuromuscular diseases such as muscular dystrophy. Mutations in the DMD gene disrupt dystrophin isoforms critical for maintaining muscle integrity and brain function, with the loss of neuronal isoforms, such as DP427, leading to cognitive impairments alongside muscle degeneration [129,176]. Fibromyalgia shows how mRNA isoform dysregulation affects systemic pain sensitivity. Isoforms of the SCN9A sodium channel gene influence nerve excitability, while serotonin receptor polymorphisms, such as 5-HT2A, are linked to widespread chronic pain in fibromyalgia [177,178].
Cardiovascular diseases are another domain where mRNA isoforms play a pivotal role. In heart failure, splicing changes in sarcomeric genes like TTN produce isoforms that affect myocardial stiffness and contraction [179]. Similarly, alternative splicing of TNNT2 and MYH7 alters proteins essential for cardiac muscle function. During myocardial infarction, spliced isoforms promote cell survival and repair mechanisms, while circular RNAs derived from spliced transcripts regulate gene expression by acting as microRNA sponges [180]. In cardiac hypertrophy, splicing factors like RBM20 control isoform changes that adapt the heart’s mechanical properties under stress [181,182]. Hypertension also highlights the role of mRNA isoforms in systemic diseases. Variants in genes like KLF4 and KLF5 affect vascular smooth muscle cell (VSMC) behavior, contributing to blood pressure regulation and vascular remodeling [183]. For instance, the KLF5 variant rs9573096 promotes VSMC dysfunction, increasing hypertension risk, while elevated KLF4 mRNA levels drive VSMC proliferation and worsen vascular injury [183,184].In atherosclerosis, transcript length variations in genes like MIA3 reduce VSMC proliferation and impair plaque stability, increasing cardiovascular risk [185,186].
Chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD) also exhibit significant mRNA isoform dysregulation [187]. In asthma, alternative splicing of the ADAM33 gene generates variants that lack catalytic domains required for metalloprotease activity, thereby affecting airway remodeling. Variants of TGFBR1 and SMAD3, key regulators of TGF-β signaling, contribute to airway inflammation and fibrosis by altering immune cell regulation [188,189]. COPD is characterized by frequent exon skipping and reduced intron retention in severe cases, resulting in protein-coding isoforms that impact lung tissue remodeling and inflammation [190]. For instance, spliced variants of the SERPINA1 gene reduce alpha-1 antitrypsin levels, leading to tissue damage and emphysema [191,192].
Other systemic diseases, such as osteoporosis and cataracts, are also influenced by mRNA isoform dysregulation. Cataracts arise from abnormal protein aggregation caused by mutations in the lens-specific CRYBB2 gene [193]. The variant CRYBB2:c.62T>A affects protein folding and induces cellular stress, leading to lens opacity [194,195]. In osteoporosis, variants in genes such as LRP5 impair WNT signaling pathways, which are critical for osteoblast activity and bone formation [196].

3.2.3. mRNA Isoforms in Tumors

Numerous studies have demonstrated that mRNA isoforms play a crucial role in tumor biology by diversifying the transcriptome. Dysregulation of the mechanisms for expressing normal mRNA isoforms may result in the expression of growth-promoting transcript variants. Differential expression of such mRNA isoforms may be characteristic of benign from malignant tumors [197]. It has been demonstrated that aberrant splicing is linked to tumor progression, metastasis, and resistance to chemotherapy or radiotherapy [198,199]. It has been reported that splicing events in BCl2L1 produce anti-apoptotic BCL-XL isoforms that protect cancer cells from programmed cell death [200]. Similarly, aberrant splicing of caspase genes generates isoforms that suppress apoptosis, ensuring tumor survival. These changes are often driven by dysregulated oncogenic signaling pathways such as RAS/RAF/ERK or PI3K/AKT/mTOR, which modify splicing factor activity at transcriptional or post-translational levels [201,202].
A tumor-specific variant of the epidermal growth factor receptor (EGFR) gene, EGFRvIII, is expressed in glioblastoma [203]. EGFRvIII alters signaling pathways to promote proliferation and resistance to targeted therapies. Notably absent in normal tissues, this isoform represents a promising therapeutic target due to its specificity for malignant cells [204,205]. In glioblastoma, RNA editing creates protein isoforms that evade immune responses while activating oncogenic pathways. These post-transcriptional modifications contribute to therapeutic resistance and tumor growth [206]. Similarly, in prostate cancer, the TMPRSS2-ERG fusion transcript exemplifies the oncogenic potential of an mRNA isoform [207]. This fusion is induced by androgen signaling and leads to the expression of the ERG proto-oncogene, which enhances tumor invasion and angiogenesis, contributing to aggressive disease phenotypes [208,209]. In thyroid cancer, microarray analyses have identified transcriptomic differences between subtypes, with differential expression of isoforms in malignant cells [210]. Similar findings in breast cancer also revealed overexpression of tumor-specific isoforms that correlate with enhanced proliferation and resistance to chemotherapeutics [211]. Long-read sequencing has uncovered thousands of novel isoforms in breast cancer, many of which affect protein function and localization [29]. Alternative splicing also plays an important role in metabolic reprogramming and immune evasion in cancer [212].
Variations in UTRs influence mRNA stability and translation by altering interactions with microRNAs or various RNA-binding proteins (RBPs). These changes can upregulate oncogenes or downregulate tumor suppressors, contributing to cancer progression [213]. For example, germline variants in the 3′ UTR of the CDKN2A gene, such as 500C>G and 540C>T, have been associated with increased melanoma risk and poorer prognosis by disrupting RBP binding and destabilizing mRNAs [214].

4. Translational Relevance of mRNA Isoforms

Advances in RNA sequencing have further enhanced our ability to detect these variants, revealing previously unannotated transcripts that refine our understanding of gene regulation and disease mechanisms [29,215]. It has been demonstrated that identifying isoforms enables the knowledge of how genes are expressed under physiological conditions and their contribution to disease [216]. The mRNA isoforms expressed from these genes have diverse roles in development, organogenesis, aging, and disease pathogenesis, making them critical targets for clinical applications. Recent studies on mRNA isoforms have revolutionized translational research by uncovering the intricate regulatory mechanisms underlying disease pathogenesis [217]. For example, germline mutations 3′ UTR of CDKN2A disrupt RBP binding, destabilizing mRNA and increasing the risk of melanoma [218].
In diagnostics, transcript variants have proven invaluable for distinguishing disease states. For example, specific isoforms, such as CLU2, in thyroid cancer can differentiate between malignant and benign tumors, enabling more accurate diagnoses and guiding preoperative decisions [197]. Transcriptomic profiling in breast cancer has also identified isoforms overexpressed in malignant cells, providing biomarkers for predicting disease progression and developing therapeutic strategies [219].
Therapeutically, targeting mRNA transcript variants has emerged as a promising approach for addressing genetic disorders and certain types of cancer. Splice-site-directed oligonucleotides and antisense therapies are developed to correct aberrant splicing and inhibit expression of pathogenic transcripts [220]. Recently, spliceosome modulators targeting SF3B1 mutations have been utilized in the treatment of hematological malignancies and solid tumors. FDA-approved therapies utilize these technologies to modulate RNA stability and translation, offering precision medicine (221-223). Large-scale transcript variants, identified through advanced techniques like full-length ribosome–nascent chain complex sequencing, have revealed novel neoepitopes derived from unannotated proteins [224]. These neoepitopes expand the repertoire of potential targets for personalized cancer vaccines, offering hope for more effective treatments across diverse tumor types [225,226]. Beyond diagnostics and therapeutics, transcript variants are reshaping the landscape of immunotherapy.
Transcript variants also play a crucial role in pharmacogenomics, influencing drug metabolism and response. Variations in UTRs can alter mRNA stability and translation efficiency through interactions with microRNAs or RBPs, impacting how the body processes drugs [227]. Variations in drug-metabolizing enzymes like CYP3A4 affect statin dose requirements, underscoring the importance of transcript variant analysis in optimizing therapeutic outcomes [228].

5. Conclusions

Multiple mRNA isoforms can be expressed from a single gene, which varies in their 5’ end, 3’ end, or internal coding sequences. Thus, a single gene can express multiple proteins with diverse functional domains. The transcript variants may be expressed in varying quantities in different cell types or within the same cell type under different physiological or pathological conditions. The mRNA isoforms and the transcript variants can play diverse roles in cell differentiation, organogenesis, and aging processes. Recent studies suggest that the expression of alternative transcript variants is linked to disease pathogenesis and can impact disease progression or response to therapeutics. This article discusses published reports on the physiological and pathological roles of mRNA transcript variants. These studies emphasize the importance of examining mRNA transcript variants rather than focusing solely on a single mRNA isoform expressed from a gene. Nowadays, long-read RNA sequencing can accurately identify mRNA isoforms. However, future developments in proteomic techniques will be necessary to identify the corresponding protein isoforms.

Author Contributions

M.A.K.R. conceptualization, supervision, and writing; S.S. and E.B. wrote the original manuscript and prepared the figures; K.V., V.D., and P.E.F. contributed to the reviewing and editing the manuscript. All authors have read and agreed on the contents of the manuscript.

Funding

No institutional funding was provided to prepare the manuscript.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

  1. Lisowiec, J.; Magner, D.; Kierzek, E.; Lenartowicz, E.; Kierzek, R. Structural determinants for alternative splicing regulation of the MAPT pre-mRNA. RNA biology 2015, 12, 330–42. [Google Scholar] [CrossRef]
  2. Dhamija, S.; Menon, M.B. Non-coding transcript variants of protein-coding genes – what are they good for? RNA Biol. 2018, 15, 1–7. [Google Scholar] [CrossRef]
  3. Vo, K.; Sharma, Y.; Paul, A.; Mohamadi, R.; Mohamadi, A.; Fields, P.E.; Rumi, M.A.K. Importance of Transcript Variants in Transcriptome Analyses. Cells 2024, 13, 1502. [Google Scholar] [CrossRef]
  4. Ray, T.A.; Cochran, K.; Kozlowski, C.; Wang, J.; Alexander, G.; Cady, M.A.; Spencer, W.J.; Ruzycki, P.A.; Clark, B.S.; Laeremans, A.; et al. Comprehensive identification of mRNA isoforms reveals the diversity of neural cell-surface molecules with roles in retinal development and disease. Nat. Commun. 2020, 11, 1–20. [Google Scholar] [CrossRef]
  5. Pai, A.A.; Luca, F. Environmental influences on RNA processing: Biochemical, molecular and genetic regulators of cellular response. Wiley Interdiscip. Rev. RNA 2019, 10. [Google Scholar] [CrossRef]
  6. You, N.; Liu, C.; Gu, Y.; Wang, R.; Jia, H.; Zhang, T.; Jiang, S.; Shi, J.; Chen, M.; Guan, M.-X.; et al. SpliceTransformer predicts tissue-specific splicing linked to human diseases. Nat. Commun. 2024, 15, 1–18. [Google Scholar] [CrossRef]
  7. Wang, E.T.; Sandberg, R.; Luo, S.; Khrebtukova, I.; Zhang, L.; Mayr, C.; Kingsmore, S.F.; Schroth, G.P.; Burge, C.B. Alternative isoform regulation in human tissue transcriptomes. Nature 2008, 456, 470–476. [Google Scholar] [CrossRef]
  8. Park, C.-W.; Lee, S.-M.; Yoon, K.-J. Epitranscriptomic regulation of transcriptome plasticity in development and diseases of the brain. BMB Rep. 2020, 53, 551–564. [Google Scholar] [CrossRef]
  9. Sharma, Y.; Vo, K.; Shila, S.; Paul, A.; Dahiya, V.; Fields, P.E.; Rumi, M.A.K. mRNA Transcript Variants Expressed in Mammalian Cells. Int. J. Mol. Sci. 2025, 26, 1052. [Google Scholar] [CrossRef]
  10. Revil, T.; Gaffney, D.; Dias, C.; Majewski, J.; A Jerome-Majewska, L. Alternative splicing is frequent during early embryonic development in mouse. BMC Genom. 2010, 11, 1–17. [Google Scholar] [CrossRef]
  11. Badr, E.; ElHefnawi, M.; Heath, L.S. Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data. PLOS ONE 2016, 11, e0166978. [Google Scholar] [CrossRef] [PubMed]
  12. Gao, C.; Wang, Y. mRNA Metabolism in Cardiac Development and Disease: Life After Transcription. Physiol. Rev. 2020, 100, 673–694. [Google Scholar] [CrossRef]
  13. Kasprzak, A.; Szaflarski, W. Role of Alternatively Spliced Messenger RNA (mRNA) Isoforms of the Insulin-Like Growth Factor 1 (IGF1) in Selected Human Tumors. Int. J. Mol. Sci. 2020, 21, 6995. [Google Scholar] [CrossRef]
  14. Cooper, T.A.; Wan, L.; Dreyfuss, G. RNA and Disease. Cell 2009, 136, 777–793. [Google Scholar] [CrossRef]
  15. Giacomelli, AO. Systematic Interrogation of Cancer Driver Gene Function: Harvard University; 2019.
  16. Mariotti M, Kerepesi C, Oliveros W, Mele M, Gladyshev VN. Deterioration of the human transcriptome with age due to increasing intron retention and spurious splicing. bioRxiv. 2022:2022.03.14.484341. [CrossRef]
  17. García-Ruiz, S.; Zhang, D.; Gustavsson, E.K.; Rocamora-Perez, G.; Grant-Peters, M.; Fairbrother-Browne, A.; Reynolds, R.H.; Brenton, J.W.; Gil-Martínez, A.L.; Chen, Z.; et al. Splicing accuracy varies across human introns, tissues, age and disease. Nat. Commun. 2025, 16, 1–22. [Google Scholar] [CrossRef]
  18. Baralle, M.; Romano, M. Age-Related Alternative Splicing: Driver or Passenger in the Aging Process? Cells 2023, 12, 2819. [Google Scholar] [CrossRef]
  19. Gorbunova, V.; Seluanov, A.; Mita, P.; McKerrow, W.; Fenyö, D.; Boeke, J.D.; Linker, S.B.; Gage, F.H.; Kreiling, J.A.; Petrashen, A.P.; et al. The role of retrotransposable elements in ageing and age-associated diseases. Nature 2021, 596, 43–53. [Google Scholar] [CrossRef]
  20. Patterson, M.N.; Scannapieco, A.E.; Au, P.H.; Dorsey, S.; Royer, C.A.; Maxwell, P.H. Preferential retrotransposition in aging yeast mother cells is correlated with increased genome instability. DNA Repair 2015, 34, 18–27. [Google Scholar] [CrossRef]
  21. Irizar, P.A.; Schäuble, S.; Esser, D.; Groth, M.; Frahm, C.; Priebe, S.; Baumgart, M.; Hartmann, N.; Marthandan, S.; Menzel, U.; et al. Transcriptomic alterations during ageing reflect the shift from cancer to degenerative diseases in the elderly. Nat. Commun. 2018, 9, 327. [Google Scholar] [CrossRef]
  22. Yosudjai, J.; Wongkham, S.; Jirawatnotai, S.; Kaewkong, W. Aberrant mRNA splicing generates oncogenic RNA isoforms and contributes to the development and progression of cholangiocarcinoma (Review). Biomed. Rep. 2019, 10, 147–155. [Google Scholar] [CrossRef]
  23. Ben Mrid, R.; El Guendouzi, S.; Mineo, M.; El Fatimy, R. The emerging roles of aberrant alternative splicing in glioma. Cell Death Discov. 2025, 11, 1–11. [Google Scholar] [CrossRef]
  24. Karlstaedt, A.; Moslehi, J.; de Boer, R.A. Cardio-onco-metabolism: metabolic remodelling in cardiovascular disease and cancer. Nat. Rev. Cardiol. 2022, 19, 414–425. [Google Scholar] [CrossRef]
  25. Liu S, Yu Y-P, Ren B-G, Ben-Yehezkel T, Obert C, Smith M, et al. Long-read single-cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells. eLife Sciences Publications, Ltd; 2023.
  26. Emilsson, V.; Thorleifsson, G.; Zhang, B.; Leonardson, A.S.; Zink, F.; Zhu, J.; Carlson, S.; Helgason, A.; Walters, G.B.; Gunnarsdottir, S.; et al. Genetics of gene expression and its effect on disease. Nature 2008, 452, 423–428. [Google Scholar] [CrossRef]
  27. Schoch, K.; Tan, Q.K.-G.; Stong, N.; Deak, K.L.; McConkie-Rosell, A.; McDonald, M.T.; Goldstein, D.B.; Jiang, Y.-H.; Shashi, V. Alternative transcripts in variant interpretation: the potential for missed diagnoses and misdiagnoses. Anesthesia Analg. 2020, 22, 1269–1275. [Google Scholar] [CrossRef]
  28. Le Quesne, J.P.; A Spriggs, K.; Bushell, M.; E Willis, A. Dysregulation of protein synthesis and disease. J. Pathol. 2009, 220, 140–151. [Google Scholar] [CrossRef]
  29. Vo, K.; Shila, S.; Sharma, Y.; Pei, G.J.; Rosales, C.Y.; Dahiya, V.; Fields, P.E.; Rumi, M.A.K. Detection of mRNA Transcript Variants. Genes 2025, 16, 343. [Google Scholar] [CrossRef]
  30. Vo, K.; Sharma, Y.; Paul, A.; Mohamadi, R.; Mohamadi, A.; Fields, P.E.; Rumi, M.A.K. Importance of Transcript Variants in Transcriptome Analyses. Cells 2024, 13, 1502. [Google Scholar] [CrossRef]
  31. Farley BM, Ryder SP. Regulation of maternal mRNAs in early development. Critical reviews in biochemistry and molecular biology. 2008;43(2):135-62.
  32. Schulz, K.N.; Harrison, M.M. Mechanisms regulating zygotic genome activation. Nat. Rev. Genet. 2018, 20, 221–234. [Google Scholar] [CrossRef]
  33. Singh, P.; Ahi, E.P. The importance of alternative splicing in adaptive evolution. Mol. Ecol. 2022, 31, 1928–1938. [Google Scholar] [CrossRef]
  34. Onichtchouk, D. Pou5f1/oct4 in pluripotency control: insights from zebrafish. genesis. 2012;50(2):75-85.
  35. Aanes, H.; Østrup, O.; Andersen, I.S.; Moen, L.F.; Mathavan, S.; Collas, P.; Alestrom, P. Differential transcript isoform usage pre- and post-zygotic genome activation in zebrafish. BMC Genom. 2013, 14, 1–15. [Google Scholar] [CrossRef]
  36. Li, F.; Karimi, N.; Wang, S.; Pan, T.; Dong, J.; Wang, X.; Ma, S.; Shan, Q.; Liu, C.; Zhang, Y.; et al. mRNA isoform switches during mouse zygotic genome activation. Cell Prolif. 2024, 57, e13655. [Google Scholar] [CrossRef]
  37. Lee, H.J.; Bartsch, D.; Xiao, C.; Guerrero, S.; Ahuja, G.; Schindler, C.; Moresco, J.J.; Yates, J.R.; Gebauer, F.; Bazzi, H.; et al. A post-transcriptional program coordinated by CSDE1 prevents intrinsic neural differentiation of human embryonic stem cells. Nat. Commun. 2017, 8, 1456–1456. [Google Scholar] [CrossRef]
  38. Maurin, M.; Ranjouri, M.; Megino-Luque, C.; Newberg, J.Y.; Du, D.; Martin, K.; Miner, R.E.; Prater, M.S.; Wee, D.K.B.; Centeno, B.; et al. RBFOX2 deregulation promotes pancreatic cancer progression and metastasis through alternative splicing. Nat. Commun. 2023, 14, 1–18. [Google Scholar] [CrossRef]
  39. Tao, Y.; Zhang, Q.; Wang, H.; Yang, X.; Mu, H. Alternative splicing and related RNA binding proteins in human health and disease. Signal Transduct. Target. Ther. 2024, 9, 1–33. [Google Scholar] [CrossRef]
  40. Colino-Sanguino Y, Clark SJ, Valdes-Mora F. The H2A. Z-nucleosome code in mammals: emerging functions. Trends in Genetics. 2022;38(3):273-89.
  41. Liu, Z.; Wang, W.; Li, X.; Zhao, X.; Zhao, H.; Yang, W.; Zuo, Y.; Cai, L.; Xing, Y. Temporal Dynamic Analysis of Alternative Splicing During Embryonic Development in Zebrafish. Front. Cell Dev. Biol. 2022, 10, 879795. [Google Scholar] [CrossRef]
  42. Tan, C.M.J.; Lewandowski, A.J. The Transitional Heart: From Early Embryonic and Fetal Development to Neonatal Life. Fetal Diagn. Ther. 2019, 47, 373–386. [Google Scholar] [CrossRef]
  43. Fochi, S.; Lorenzi, P.; Galasso, M.; Stefani, C.; Trabetti, E.; Zipeto, D.; Romanelli, M.G. The Emerging Role of the RBM20 and PTBP1 Ribonucleoproteins in Heart Development and Cardiovascular Diseases. Genes 2020, 11, 402. [Google Scholar] [CrossRef]
  44. Deshpande, A.; Shetty, P.M.V.; Frey, N.; Rangrez, A.Y. SRF: a seriously responsible factor in cardiac development and disease. J. Biomed. Sci. 2022, 29, 1–21. [Google Scholar] [CrossRef]
  45. Mengmeng, X.; Yuejuan, X.; Sun, C.; Yanan, L.; Fen, L.; Kun, S. Novel mutations of the SRF gene in Chinese sporadic conotruncal heart defect patients. BMC Med Genet. 2020, 21, 1–10. [Google Scholar] [CrossRef]
  46. Mokalled, M.H.; Carroll, K.J.; Cenik, B.K.; Chen, B.; Liu, N.; Olson, E.N.; Bassel-Duby, R. Myocardin-related transcription factors are required for cardiac development and function. Dev. Biol. 2015, 406, 109–116. [Google Scholar] [CrossRef]
  47. Yan, Y.-L.; Titus, T.; Desvignes, T.; BreMiller, R.; Batzel, P.; Sydes, J.; Farnsworth, D.; Dillon, D.; Wegner, J.; Phillips, J.B.; et al. A fish with no sex: gonadal and adrenal functions partition between zebrafishNR5A1co-orthologs. Genetics 2021, 217. [Google Scholar] [CrossRef]
  48. Ruggiero, C.; Doghman, M.; Lalli, E. How genomic studies have improved our understanding of the mechanisms of transcriptional regulation by NR5A nuclear receptors. Mol. Cell. Endocrinol. 2015, 408, 138–144. [Google Scholar] [CrossRef]
  49. Tagami, A.; Ikeda, Y.; Ishizuka, K.; Maekawa, M. Conditional disruption of Nr5a1 directed by Sox9-Cre impairs adrenal development. Sci. Rep. 2024, 14, 1–12. [Google Scholar] [CrossRef]
  50. Narita, T.; Higashijima, Y.; Kilic, S.; Liebner, T.; Walter, J.; Choudhary, C. Acetylation of histone H2B marks active enhancers and predicts CBP/p300 target genes. Nat. Genet. 2023, 55, 679–692. [Google Scholar] [CrossRef]
  51. Haberland, M.; Montgomery, R.L.; Olson, E.N. The many roles of histone deacetylases in development and physiology: implications for disease and therapy. Nat. Rev. Genet. 2009, 10, 32–42. [Google Scholar] [CrossRef]
  52. Ning, L.; Rui, X.; Bo, W.; Qing, G. The critical roles of histone deacetylase 3 in the pathogenesis of solid organ injury. Cell Death Dis. 2021, 12, 1–13. [Google Scholar] [CrossRef]
  53. Carim, S. Regulating enhancer activation. Nat. Cell Biol. 2023, 25, 372–372. [Google Scholar] [CrossRef]
  54. Jansz, N. DNA methylation dynamics at transposable elements in mammals. Essays Biochem. 2019, 63, 677–689. [Google Scholar] [CrossRef]
  55. E Mittleman, B.; Pott, S.; Warland, S.; Zeng, T.; Mu, Z.; Kaur, M.; Gilad, Y.; Li, Y.; Genetics; Genomics; et al. Alternative polyadenylation mediates genetic regulation of gene expression. eLife 2020, 9. [Google Scholar] [CrossRef]
  56. Cesana, M.; Guo, M.H.; Cacchiarelli, D.; Wahlster, L.; Barragan, J.; Doulatov, S.; Vo, L.T.; Salvatori, B.; Trapnell, C.; Clement, K.; et al. A CLK3-HMGA2 Alternative Splicing Axis Impacts Human Hematopoietic Stem Cell Molecular Identity throughout Development. Cell Stem Cell 2018, 22, 575–588.e7. [Google Scholar] [CrossRef]
  57. Cleynen I, Van de Ven WJ. The HMGA proteins: a myriad of functions. International journal of oncology. 2008;32(2):289-305.
  58. Blok, L.S.; Vino, A.; Hoed, J.D.; Underhill, H.R.; Monteil, D.; Li, H.; Santos, F.J.R.; Chung, W.K.; Amaral, M.D.; Schnur, R.E.; et al. Heterozygous variants that disturb the transcriptional repressor activity of FOXP4 cause a developmental disorder with speech/language delays and multiple congenital abnormalities. Anesthesia Analg. 2021, 23, 534–542. [Google Scholar] [CrossRef]
  59. Yamamoto, T. Genomic Aberrations Associated with the Pathophysiological Mechanisms of Neurodevelopmental Disorders. Cells 2021, 10, 2317. [Google Scholar] [CrossRef]
  60. Wang, R.; Helbig, I.; Edmondson, A.C.; Lin, L.; Xing, Y. Splicing defects in rare diseases: transcriptomics and machine learning strategies towards genetic diagnosis. Briefings Bioinform. 2023, 24. [Google Scholar] [CrossRef]
  61. Mensah, M.A.; Niskanen, H.; Magalhaes, A.P.; Basu, S.; Kircher, M.; Sczakiel, H.L.; Reiter, A.M.V.; Elsner, J.; Meinecke, P.; Biskup, S.; et al. Aberrant phase separation and nucleolar dysfunction in rare genetic diseases. Nature 2023, 614, 564–571. [Google Scholar] [CrossRef]
  62. Roychowdhury, S.; Chattopadhyay, K. A tale of (disordered) tail. Commun. Biol. 2023, 6, 1–2. [Google Scholar] [CrossRef]
  63. Imbriano, C.; Molinari, S. Alternative Splicing of Transcription Factors Genes in Muscle Physiology and Pathology. Genes 2018, 9, 107. [Google Scholar] [CrossRef]
  64. Barrie, E.S.; Smith, R.M.; Sanford, J.C.; Sadee, W. mRNA Transcript Diversity Creates New Opportunities for Pharmacological Intervention. Mol. Pharmacol. 2012, 81, 620–630. [Google Scholar] [CrossRef]
  65. Kwan, T.; Benovoy, D.; Dias, C.; Gurd, S.; Provencher, C.; Beaulieu, P.; Hudson, T.J.; Sladek, R.; Majewski, J. Genome-wide analysis of transcript isoform variation in humans. Nat. Genet. 2008, 40, 225–231. [Google Scholar] [CrossRef]
  66. Breitbart RE, Andreadis A, Nadal-Ginard B. Alternative splicing: a ubiquitous mechanism for the generation of multiple protein isoforms from single genes. Annual review of biochemistry. 1987;56(1):467-95.
  67. Rodriguez, J.M.; Pozo, F.; di Domenico, T.; Vazquez, J.; Tress, M.L. An analysis of tissue-specific alternative splicing at the protein level. PLOS Comput. Biol. 2020, 16, e1008287. [Google Scholar] [CrossRef]
  68. Beitelshees AL, Navare H, Wang D, Gong Y, Wessel J, Moss JI, et al. CACNA1C gene polymorphisms, cardiovascular disease outcomes, and treatment response. Circulation: Cardiovascular Genetics. 2009;2(4):362-70.
  69. Su, C.-H.; D, D.; Tarn, W.-Y. Alternative Splicing in Neurogenesis and Brain Development. Front. Mol. Biosci. 2018, 5, 12. [Google Scholar] [CrossRef]
  70. Celotto, A.M.; Graveley, B.R. Alternative Splicing of the DrosophilaDscamPre-mRNA Is Both Temporally and Spatially Regulated. Genetics 2001, 159, 599–608. [Google Scholar] [CrossRef] [PubMed]
  71. Smith, PH. Dscam gene expression in invertebrate immunity: alternative splicing in response to diverse pathogens. 2012.
  72. Chen, Y.; Xiao, D.; Zhang, L.; Cai, C.-L.; Li, B.-Y.; Liu, Y. The Role of Tbx20 in Cardiovascular Development and Function. Front. Cell Dev. Biol. 2021, 9. [Google Scholar] [CrossRef] [PubMed]
  73. Feng, Q.; Zhao, H.; Xu, L.; Xie, Z. N6-Methyladenosine Modification and Its Regulation of Respiratory Viruses. Front. Cell Dev. Biol. 2021, 9, 699997. [Google Scholar] [CrossRef] [PubMed]
  74. Jiang, X.; Liu, B.; Nie, Z.; Duan, L.; Xiong, Q.; Jin, Z.; Yang, C.; Chen, Y. The role of m6A modification in the biological functions and diseases. Signal Transduct. Target. Ther. 2021, 6, 1–16. [Google Scholar] [CrossRef]
  75. Cai, T.; Atteh, L.L.; Zhang, X.; Huang, C.; Bai, M.; Ma, H.; Zhang, C.; Fu, W.; Gao, L.; Lin, Y.; et al. The N6-Methyladenosine Modification and Its Role in mRNA Metabolism and Gastrointestinal Tract Disease. Front. Surg. 2022, 9, 819335. [Google Scholar] [CrossRef]
  76. Zhou, J.; Wan, J.; Gao, X.; Zhang, X.; Jaffrey, S.R.; Qian, S.-B. Dynamic m6A mRNA methylation directs translational control of heat shock response. Nature 2015, 526, 591–594. [Google Scholar] [CrossRef]
  77. Di Giammartino, D.C.; Nishida, K.; Manley, J.L. Mechanisms and Consequences of Alternative Polyadenylation. Mol. Cell 2011, 43, 853–866. [Google Scholar] [CrossRef]
  78. Mitschka, S.; Mayr, C. Context-specific regulation and function of mRNA alternative polyadenylation. Nat. Rev. Mol. Cell Biol. 2022, 23, 779–796. [Google Scholar] [CrossRef]
  79. Cao, J.; Kuyumcu-Martinez, M.N. Alternative polyadenylation regulation in cardiac development and cardiovascular disease. Cardiovasc. Res. 2023, 119, 1324–1335. [Google Scholar] [CrossRef]
  80. Marasco LE, Kornblihtt AR. The physiology of alternative splicing. Nature Reviews Molecular Cell Biology. 2023;24(4):242-54.
  81. Wang, K.; Wu, D.; Zhang, H.; Das, A.; Basu, M.; Malin, J.; Cao, K.; Hannenhalli, S. Comprehensive map of age-associated splicing changes across human tissues and their contributions to age-associated diseases. Sci. Rep. 2018, 8, 1–12. [Google Scholar] [CrossRef]
  82. Bhadra, M.; Howell, P.; Dutta, S.; Heintz, C.; Mair, W.B. Alternative splicing in aging and longevity. Hum. Genet. 2019, 139, 357–369. [Google Scholar] [CrossRef] [PubMed]
  83. Pal, S.; Tyler, J.K. Epigenetics and aging. Sci. Adv. 2016, 2, e1600584. [Google Scholar] [CrossRef] [PubMed]
  84. Sen, P.; Dang, W.; Donahue, G.; Dai, J.; Dorsey, J.; Cao, X.; Liu, W.; Cao, K.; Perry, R.; Lee, J.Y.; et al. H3K36 methylation promotes longevity by enhancing transcriptional fidelity. Genes Dev. 2015, 29, 1362–1376. [Google Scholar] [CrossRef] [PubMed]
  85. Masuda, K.; Marasa, B.; Martindale, J.L.; Halushka, M.K.; Gorospe, M. Tissue- and age-dependent expression of RNA-binding proteins that influence mRNA turnover and translation. Aging 2009, 1, 681–698. [Google Scholar] [CrossRef]
  86. Fernández-Gómez, A.; Izquierdo, J.M. The Multifunctional Faces of T-Cell Intracellular Antigen 1 in Health and Disease. Int. J. Mol. Sci. 2022, 23, 1400. [Google Scholar] [CrossRef]
  87. López-Domínguez, J.A.; Rodríguez-López, S.; Ahumada-Castro, U.; Desprez, P.-Y.; Konovalenko, M.; Laberge, R.-M.; Cárdenas, C.; Villalba, J.M.; Campisi, J. Cdkn1a transcript variant 2 is a marker of aging and cellular senescence. Aging 2021, 13, 13380–13392. [Google Scholar] [CrossRef]
  88. Hudgins, A.D.; Tazearslan, C.; Tare, A.; Zhu, Y.; Huffman, D.; Suh, Y. Age- and Tissue-Specific Expression of Senescence Biomarkers in Mice. Front. Genet. 2018, 9. [Google Scholar] [CrossRef]
  89. Papadakis, A. Aging associated changes of transcriptional elongation speed and transcriptional error rate: Universität zu Köln; 2024.
  90. Debès, C.; Papadakis, A.; Grönke, S.; Karalay, Ö.; Tain, L.S.; Mizi, A.; Nakamura, S.; Hahn, O.; Weigelt, C.; Josipovic, N.; et al. Ageing-associated changes in transcriptional elongation influence longevity. Nature 2023, 616, 814–821. [Google Scholar] [CrossRef]
  91. Gruner, H.; Cortés-López, M.; Cooper, D.A.; Bauer, M.; Miura, P. CircRNA accumulation in the aging mouse brain. Sci. Rep. 2016, 6, 38907. [Google Scholar] [CrossRef]
  92. Tumasian, R.A.; Harish, A.; Kundu, G.; Yang, J.-H.; Ubaida-Mohien, C.; Gonzalez-Freire, M.; Kaileh, M.; Zukley, L.M.; Chia, C.W.; Lyashkov, A.; et al. Skeletal muscle transcriptome in healthy aging. Nat. Commun. 2021, 12, 1–16. [Google Scholar] [CrossRef]
  93. Singh, A.; Kumar, N.; Matai, L.; Jain, V.; Garg, A.; Mukhopadhyay, A. A chromatin modifier integrates insulin/IGF-1 signalling and dietary restriction to regulate longevity. Aging Cell 2016, 15, 694–705. [Google Scholar] [CrossRef] [PubMed]
  94. Testa, G.; Biasi, F.; Poli, G.; Chiarpotto, E. Calorie Restriction and Dietary Restriction Mimetics: A Strategy for Improving Healthy Aging and Longevity. Curr. Pharm. Des. 2014, 20, 2950–2977. [Google Scholar] [CrossRef] [PubMed]
  95. Green, C.L.; Lamming, D.W.; Fontana, L. Molecular mechanisms of dietary restriction promoting health and longevity. Nat. Rev. Mol. Cell Biol. 2021, 23, 56–73. [Google Scholar] [CrossRef]
  96. Schneider, B.K.; Sun, S.; Lee, M.; Li, W.; Skvir, N.; Neretti, N.; Vijg, J.; Secombe, J. Expression of retrotransposons contributes to aging in Drosophila. Genetics 2023, 224. [Google Scholar] [CrossRef]
  97. Kwon, H.C.; Bae, Y.; Lee, S.-J.V. The Role of mRNA Quality Control in the Aging of Caenorhabditis elegans. Mol. Cells 2023, 46, 664–671. [Google Scholar] [CrossRef]
  98. Wright, C.J.; Smith, C.W.J.; Jiggins, C.D. Alternative splicing as a source of phenotypic diversity. Nat. Rev. Genet. 2022, 23, 697–710. [Google Scholar] [CrossRef]
  99. Kim, H.K.; Pham, M.H.C.; Ko, K.S.; Rhee, B.D.; Han, J. Alternative splicing isoforms in health and disease. Pfl?gers Arch. Eur. J. Physiol. 2018, 470, 995–1016. [Google Scholar] [CrossRef]
  100. Li, J.; He, L.; Zhang, Y.; Xue, C.; Cao, Y. A novel method for genome-wide profiling of dynamic host-pathogen interactions using 3′ end enriched RNA-seq. Sci. Rep. 2017, 7, 1–10. [Google Scholar] [CrossRef]
  101. Lyu, M.; Lai, H.; Wang, Y.; Zhou, Y.; Chen, Y.; Wu, D.; Chen, J.; Ying, B. Roles of alternative splicing in infectious diseases: from hosts, pathogens to their interactions. Chin. Med J. 2023, 136, 767–779. [Google Scholar] [CrossRef]
  102. Sehrawat, S.; Garcia-Blanco, M.A. RNA virus infections and their effect on host alternative splicing. Antivir. Res. 2022, 210, 105503–105503. [Google Scholar] [CrossRef]
  103. Evans III, EL. Investigating species-specific blocks to HIV-1 replication and Vif-induced metaphase arrest: The University of Wisconsin-Madison; 2019.
  104. Liu, Y.-H.; Xu, H.-Q.; Zhu, S.-S.; Hong, Y.-F.; Li, X.-W.; Li, H.-X.; Xiong, J.-P.; Xiao, H.; Bu, J.-H.; Zhu, F.; et al. ASVirus: A Comprehensive Knowledgebase for the Viral Alternative Splicing. J. Chem. Inf. Model. 2025, 65, 2722–9. [Google Scholar] [CrossRef] [PubMed]
  105. Amir, N.; Taube, R. Role of long noncoding RNA in regulating HIV infection—a comprehensive review. mBio 2024, 15, e0192523. [Google Scholar] [CrossRef] [PubMed]
  106. Zhao, H.-J.; Hu, Y.-F.; Han, Q.-J.; Zhang, J. Innate and adaptive immune escape mechanisms of hepatitis B virus. World J. Gastroenterol. 2022, 28, 881–896. [Google Scholar] [CrossRef]
  107. Kuipery, A.; Gehring, A.J.; Isogawa, M. Mechanisms of HBV immune evasion. Antivir. Res. 2020, 179, 104816. [Google Scholar] [CrossRef]
  108. Carpenter, S.; Ricci, E.P.; Mercier, B.C.; Moore, M.J.; Fitzgerald, K.A. Post-transcriptional regulation of gene expression in innate immunity. Nat. Rev. Immunol. 2014, 14, 361–376. [Google Scholar] [CrossRef]
  109. Kalam, H.; Fontana, M.F.; Kumar, D. Alternate splicing of transcripts shape macrophage response to Mycobacterium tuberculosis infection. PLOS Pathog. 2017, 13, e1006236. [Google Scholar] [CrossRef] [PubMed]
  110. Hong, W.; Yang, H.; Wang, X.; Shi, J.; Zhang, J.; Xie, J. The Role of mRNA Alternative Splicing in Macrophages Infected with Mycobacterium tuberculosis: A Field Needing to Be Discovered. Molecules 2024, 29, 1798. [Google Scholar] [CrossRef]
  111. Baena, A.; Porcelli, S.A. Evasion and subversion of antigen presentation by Mycobacterium tuberculosis. Tissue Antigens 2009, 74, 189–204. [Google Scholar] [CrossRef]
  112. Corre, M.; Boehm, V.; Besic, V.; Kurowska, A.; Viry, A.; Mohammad, A.; Sénamaud-Beaufort, C.; Thomas-Chollier, M.; Lebreton, A. Alternative splicing induced by bacterial pore-forming toxins sharpens CIRBP-mediated cell response to Listeria infection. Nucleic Acids Res. 2023, 51, 12459–12475. [Google Scholar] [CrossRef]
  113. Corre, M.; Lebreton, A. Regulation of cold-inducible RNA-binding protein (CIRBP) in response to cellular stresses. Biochimie 2023, 217, 3–9. [Google Scholar] [CrossRef]
  114. Nishimura, H.; Yajima, T.; Naiki, Y.; Tsunobuchi, H.; Umemura, M.; Itano, K.; Matsuguchi, T.; Suzuki, M.; Ohashi, P.S.; Yoshikai, Y. Differential Roles of Interleukin 15 mRNA Isoforms Generated by Alternative Splicing in Immune Responses in Vivo. J. Exp. Med. 2000, 191, 157–170. [Google Scholar] [CrossRef] [PubMed]
  115. Yoshikai, Y.; Nishimura, H. The role of interleukin 15 in mounting an immune response against microbial infections. Microbes Infect. 2000, 2, 381–389. [Google Scholar] [CrossRef] [PubMed]
  116. Agosto, L.M.; Mallory, M.J.; Ferretti, M.B.; Blake, D.; Krick, K.S.; Gazzara, M.R.; Garcia, B.A.; Lynch, K.W. Alternative splicing of HDAC7 regulates its interaction with 14-3-3 proteins to alter histone marks and target gene expression. Cell Rep. 2023, 42, 112273–112273. [Google Scholar] [CrossRef] [PubMed]
  117. Kamran, M.; Bhattacharjee, R.; Das, S.; Mukherjee, S.; Ali, N. The paradigm of intracellular parasite survival and drug resistance in leishmanial parasite through genome plasticity and epigenetics: Perception and future perspective. Front. Cell. Infect. Microbiol. 2023, 13, 1001973. [Google Scholar] [CrossRef]
  118. Pisetsky, DS. Pathogenesis of autoimmune disease. Nature Reviews Nephrology. 2023;19(8):509-24.
  119. Goodnow, C.C. Pathways for self-tolerance and the treatment of autoimmune diseases. Lancet 2001, 357, 2115–2121. [Google Scholar] [CrossRef]
  120. Xu, B.; Liu, Y.; Chen, G.; Jiang, P.; Qu, Y.; Wang, M.; Kao, X. Genome-wide analysis of abnormal splicing regulators and alternative splicing involved in immune regulation in systemic lupus erythematosus. Autoimmunity 2025, 58, 2448463. [Google Scholar] [CrossRef]
  121. Lazzari, E.; Jefferies, C.A. IRF5-mediated signaling and implications for SLE. Clin. Immunol. 2014, 153, 343–352. [Google Scholar] [CrossRef]
  122. Stone, R.C.; Du, P.; Feng, D.; Dhawan, K.; Rönnblom, L.; Eloranta, M.-L.; Donnelly, R.; Barnes, B.J. RNA-Seq for Enrichment and Analysis of IRF5 Transcript Expression in SLE. PLOS ONE 2013, 8, e54487. [Google Scholar] [CrossRef]
  123. Chikuma, S. CTLA-4, an essential immune-checkpoint for T-cell activation. Emerging Concepts Targeting Immune Checkpoints in Cancer and Autoimmunity. 2017:99-126.
  124. Ahmad, R.; Ahsan, H. Dual autoimmune diseases: Rheumatoid arthritis with systemic lupus erythematosus and Type 1 diabetes mellitus with multiple sclerosis. Rheumatol. Autoimmun. 2022, 2, 120–128. [Google Scholar] [CrossRef]
  125. Grisar, J.; Munk, M.; Steiner, C.W.; Amoyo-Minar, L.; Tohidast-Akrad, M.; Zenz, P.; Steiner, G.; Smolen, J.S. Expression patterns of CD44 and CD44 splice variants in patients with rheumatoid arthritis. . 2012, 30, 64–72. [Google Scholar]
  126. Naor, D.; Nedvetzki, S. CD44 in rheumatoid arthritis. Arthritis Res. Ther. 2003, 5, 105–115. [Google Scholar] [CrossRef]
  127. Ibáñez-Costa, A.; Perez-Sanchez, C.; Patiño-Trives, A.M.; Luque-Tevar, M.; Font, P.; de la Rosa, I.A.; Roman-Rodriguez, C.; Abalos-Aguilera, M.C.; Conde, C.; Gonzalez, A.; et al. Splicing machinery is impaired in rheumatoid arthritis, associated with disease activity and modulated by anti-TNF therapy. Ann. Rheum. Dis. 2022, 81, 56–67. [Google Scholar] [CrossRef] [PubMed]
  128. Banerjee, S.; Galarza-Muñoz, G.; Garcia-Blanco, M.A. Role of RNA Alternative Splicing in T Cell Function and Disease. Genes 2023, 14, 1896. [Google Scholar] [CrossRef] [PubMed]
  129. Tzaban, S.; Stern, O.; Zisman, E.; Eisenberg, G.; Klein, S.; Frankenburg, S.; Lotem, M. Alternative splicing of modulatory immune receptors in T lymphocytes: a newly identified and targetable mechanism for anticancer immunotherapy. Front. Immunol. 2025, 15, 1490035. [Google Scholar] [CrossRef]
  130. Lim J, Sari-Ak D, Bagga T. Siglecs as therapeutic targets in cancer. Biology. 2021;10(11):1178.
  131. Li, H.; Reksten, T.R.; Ice, J.A.; Kelly, J.A.; Adrianto, I.; Rasmussen, A.; Wang, S.; He, B.; Grundahl, K.M.; Glenn, S.B.; et al. Identification of a Sjögren's syndrome susceptibility locus at OAS1 that influences isoform switching, protein expression, and responsiveness to type I interferons. PLOS Genet. 2017, 13, e1006820–e1006820. [Google Scholar] [CrossRef]
  132. Del Papa, N.; Minniti, A.; Lorini, M.; Carbonelli, V.; Maglione, W.; Pignataro, F.; Montano, N.; Caporali, R.; Vitali, C. The Role of Interferons in the Pathogenesis of Sjögren’s Syndrome and Future Therapeutic Perspectives. Biomolecules 2021, 11, 251. [Google Scholar] [CrossRef] [PubMed]
  133. Voulgarelis, M.; Tzioufas, A.G. Pathogenetic mechanisms in the initiation and perpetuation of Sjögren's syndrome. Nat. Rev. Rheumatol. 2010, 6, 529–537. [Google Scholar] [CrossRef]
  134. Zhou, H.; Yang, J.; Tian, J.; Wang, S. CD8+ T Lymphocytes: Crucial Players in Sjögren’s Syndrome. Front. Immunol. 2021, 11. [Google Scholar] [CrossRef]
  135. Xu, Y.; Wang, W.; Tian, Y.; Liu, J.; Yang, R. Polymorphisms in STAT4 and IRF5 increase the risk of systemic sclerosis: a meta-analysis. Int. J. Dermatol. 2015, 55, 408–416. [Google Scholar] [CrossRef]
  136. Mennella, A.; Ocone, G.; Stefanantoni, K.; Frasca, L. The Role of IRF8 Polymorphisms in Systemic Sclerosis Development and Pathogenesis. J. Mol. Pathol. 2024, 5, 120–132. [Google Scholar] [CrossRef]
  137. Frangogiannis, N.G. Transforming growth factor–β in tissue fibrosis. J. Exp. Med. 2020, 217, e20190103. [Google Scholar] [CrossRef] [PubMed]
  138. Evsyukova, I.; Somarelli, J.A.; Gregory, S.G.; Garcia-Blanco, M.A. Alternative splicing in multiple sclerosis and other autoimmune diseases. RNA Biol. 2010, 7, 462–473. [Google Scholar] [CrossRef] [PubMed]
  139. Greer, J.M.; Trifilieff, E.; Pender, M.P. Correlation Between Anti-Myelin Proteolipid Protein (PLP) Antibodies and Disease Severity in Multiple Sclerosis Patients With PLP Response-Permissive HLA Types. Front. Immunol. 2020, 11, 1891. [Google Scholar] [CrossRef] [PubMed]
  140. Schanda, K.; Peschl, P.; Lerch, M.; Seebacher, B.; Mindorf, S.; Ritter, N.; Probst, M.; Hegen, H.; Di Pauli, F.; Wendel, E.-M.; et al. Differential Binding of Autoantibodies to MOG Isoforms in Inflammatory Demyelinating Diseases. Neurol. - Neuroimmunol. Neuroinflammation 2021, 8. [Google Scholar] [CrossRef]
  141. Ohno, K.; Ohkawara, B.; Shen, X.-M.; Selcen, D.; Engel, A.G. Clinical and Pathologic Features of Congenital Myasthenic Syndromes Caused by 35 Genes—A Comprehensive Review. Int. J. Mol. Sci. 2023, 24, 3730. [Google Scholar] [CrossRef]
  142. Marín-Sánchez, A.; Álvarez-Sierra, D.; González, O.; Lucas-Martin, A.; Sellés-Sánchez, A.; Rudilla, F.; Enrich, E.; Colobran, R.; Pujol-Borrell, R. Regulation of TSHR Expression in the Thyroid and Thymus May Contribute to TSHR Tolerance Failure in Graves' Disease Patients via Two Distinct Mechanisms. Front. Immunol. 2019, 10, 1695. [Google Scholar] [CrossRef]
  143. Brand, O.J.; Barrett, J.C.; Simmonds, M.J.; Newby, P.R.; McCabe, C.J.; Bruce, C.K.; Kysela, B.; Carr-Smith, J.D.; Brix, T.; Hunt, P.J.; et al. Association of the thyroid stimulating hormone receptor gene (TSHR) with Graves' disease. Hum. Mol. Genet. 2009, 18, 1704–1713. [Google Scholar] [CrossRef]
  144. Latif, R.; Mezei, M.; A Morshed, S.; Ma, R.; Ehrlich, R.; Davies, T.F. A Modifying Autoantigen in Graves’ Disease. Endocrinology 2019, 160, 1008–1020. [Google Scholar] [CrossRef]
  145. Yarani, R.; Shojaeian, A.; Palasca, O.; Doncheva, N.T.; Jensen, L.J.; Gorodkin, J.; Pociot, F. Differentially Expressed miRNAs in Ulcerative Colitis and Crohn’s Disease. Front. Immunol. 2022, 13, 865777. [Google Scholar] [CrossRef]
  146. Robinson, P.; Magness, E.; Montoya, K.; Engineer, N.; Eckols, T.K.; Rodriguez, E.; Tweardy, D.J. Genetic and Small-Molecule Modulation of Stat3 in a Mouse Model of Crohn’s Disease. J. Clin. Med. 2022, 11, 7020. [Google Scholar] [CrossRef]
  147. Zhou, J.; Zhang, Q.; Zhao, Y.; Song, Y.; Leng, Y.; Chen, M.; Zhou, S.; Wang, Z. The regulatory role of alternative splicing in inflammatory bowel disease. Front. Immunol. 2023, 14, 1095267. [Google Scholar] [CrossRef] [PubMed]
  148. Pai, Y.-C.; Weng, L.-T.; Wei, S.-C.; Wu, L.-L.; Shih, D.Q.; Targan, S.R.; Turner, J.R.; Yu, L.C.-H. Gut Microbial Transcytosis Induced by Tumour Necrosis Factor-like 1A-dependent Activation of a Myosin Light Chain Kinase Splice Variant Contributes to Inflammatory Bowel Disease. J. Crohn’s Colitis 2020, 15, 258–272. [Google Scholar] [CrossRef] [PubMed]
  149. Derer, S.; Brethack, A.-K.; Pietsch, C.; Jendrek, S.T.; Nitzsche, T.; Bokemeyer, A.; Hov, J.R.; Schäffler, H.; Bettenworth, D.; A Grassl, G.; et al. Inflammatory Bowel Disease–associated GP2 Autoantibodies Inhibit Mucosal Immune Response to Adherent-invasive Bacteria. Inflamm. Bowel Dis. 2020, 26, 1856–1868. [Google Scholar] [CrossRef]
  150. Kan, S.-H.; Mancini, G.; Gallagher, G. Identification and characterization of multiple splice forms of the human interleukin-23 receptor α chain in mitogen-activated leukocytes. Genes Immun. 2008, 9, 631–639. [Google Scholar] [CrossRef]
  151. Lahiri, A.; Hedl, M.; Yan, J.; Abraham, C. Human LACC1 increases innate receptor-induced responses and a LACC1 disease-risk variant modulates these outcomes. Nat. Commun. 2017, 8, 15614. [Google Scholar] [CrossRef]
  152. Huang, C.; Hedl, M.; Ranjan, K.; Abraham, C. LACC1 Required for NOD2-Induced, ER Stress-Mediated Innate Immune Outcomes in Human Macrophages and LACC1 Risk Variants Modulate These Outcomes. Cell Rep. 2019, 29, 4525–4539.e4. [Google Scholar] [CrossRef]
  153. Li, C. Unfolded Protein Response and Crohn’s Diseases: A Molecular Mechanism of Wound Healing in the Gut. Gastrointest. Disord. 2021, 3, 31–43. [Google Scholar] [CrossRef]
  154. Muise A, Rotin D. Apical junction complex proteins and ulcerative colitis: a focus on the PTPRS gene. Expert review of molecular diagnostics. 2008;8(4):465-77.
  155. Klak, M.; Gomółka, M.; Kowalska, P.; Cichoń, J.; Ambrożkiewicz, F.; Serwańska-Świętek, M.; Berman, A.; Wszoła, M. Type 1 diabetes: genes associated with disease development. Central Eur. J. Immunol. 2020, 45, 439–453. [Google Scholar] [CrossRef]
  156. Eizirik DL, Szymczak F, Mallone R. Why does the immune system destroy pancreatic β-cells but not α-cells in type 1 diabetes? Nature Reviews Endocrinology. 2023;19(7):425-34.
  157. Roep, B.O.; Peakman, M. Antigen Targets of Type 1 Diabetes Autoimmunity. Cold Spring Harb. Perspect. Med. 2012, 2, a007781–a007781. [Google Scholar] [CrossRef]
  158. Gerold, K.D.; Zheng, P.; Rainbow, D.B.; Zernecke, A.; Wicker, L.S.; Kissler, S. The Soluble CTLA-4 Splice Variant Protects From Type 1 Diabetes and Potentiates Regulatory T-Cell Function. Diabetes 2011, 60, 1955–1963. [Google Scholar] [CrossRef]
  159. Bloor, C.A.; Knight, R.A.; Kedia, R.K.; Spiteri, M.A.; Allen, J.T. Differential mRNA Expression of Insulin-like Growth Factor-1 Splice Variants in Patients With Idiopathic Pulmonary Fibrosis and Pulmonary Sarcoidosis. Am. J. Respir. Crit. Care Med. 2001, 164, 265–272. [Google Scholar] [CrossRef] [PubMed]
  160. Funaguma, S.; Iida, A.; Saito, Y.; Tanboon, J.; Reyes, F.V.D.L.; Sonehara, K.; Goto, Y.-I.; Okada, Y.; Hayashi, S.; Nishino, I. Retrotrans-genomics identifies aberrant THE1B endogenous retrovirus fusion transcripts in the pathogenesis of sarcoidosis. Nat. Commun. 2025, 16, 1–14. [Google Scholar] [CrossRef] [PubMed]
  161. Liu, Q.; Fang, L.; Wu, C. Alternative Splicing and Isoforms: From Mechanisms to Diseases. Genes 2022, 13, 401. [Google Scholar] [CrossRef]
  162. Liu, C.S.; Park, C.; Ngo, T.; Saikumar, J.; Palmer, C.R.; Shahnaee, A.; Romanow, W.J.; Chun, J. RNA Isoform Diversity in Human Neurodegenerative Diseases. eneuro 2024, 11. [Google Scholar] [CrossRef]
  163. Sandbrink, R.; Masters, C.L.; Beyreuther, K. APP Gene Family Alternative Splicing Generates Functionally Related Isoformsa. Ann. New York Acad. Sci. 1996, 777, 281–287. [Google Scholar] [CrossRef]
  164. De Paoli-Iseppi R, Joshi S, Gleeson J, Prawer YDJ, Yu Y, Agarwal R, et al. Long-read sequencing reveals the RNA isoform repertoire of neuropsychiatric risk genes in human brain. medRxiv. 2024:2024.02. 22.24303189.
  165. Lücking C, Brice* A. Alpha-synuclein and Parkinson's disease. Cellular and Molecular Life Sciences CMLS. 2000;57:1894-908.
  166. Li, Y.; Sun, S. RNA dysregulation in neurodegenerative diseases. EMBO J. 2025, 44, 613–638. [Google Scholar] [CrossRef]
  167. Highley JR, Kirby J, Jansweijer JA, Webb PS, Hewamadduma CA, Heath PR, et al. Loss of nuclear TDP-43 in amyotrophic lateral sclerosis (ALS) causes altered expression of splicing machinery and widespread dysregulation of RNA splicing in motor neurones. Neuropathology and applied neurobiology. 2014;40(6):670-85.
  168. Maziuk, B.; Ballance, H.I.; Wolozin, B. Dysregulation of RNA Binding Protein Aggregation in Neurodegenerative Disorders. Front. Mol. Neurosci. 2017, 10, 89. [Google Scholar] [CrossRef]
  169. Nik, S.; Bowman, T.V. Splicing and neurodegeneration: Insights and mechanisms. Wiley Interdiscip. Rev. RNA 2019, 10, e1532. [Google Scholar] [CrossRef]
  170. Seixas AI, Holmes SE, Takeshima H, Pavlovich A, Sachs N, Pruitt JL, et al. Loss of junctophilin-3 contributes to Huntington disease-like 2 pathogenesis. Annals of neurology. 2012;71(2):245-57.
  171. Bourinaris, T.; Athanasiou, A.; Efthymiou, S.; Wiethoff, S.; Salpietro, V.; Houlden, H. Allelic and phenotypic heterogeneity in Junctophillin-3 related neurodevelopmental and movement disorders. Eur. J. Hum. Genet. 2021, 29, 1027–1031. [Google Scholar] [CrossRef]
  172. Varela, M.D.; Georgiou, M.; Alswaiti, Y.; Kabbani, J.; Fujinami, K.; Fujinami-Yokokawa, Y.; Khoda, S.; Mahroo, O.A.; Robson, A.G.; Webster, A.R.; et al. CRB1-Associated Retinal Dystrophies: Genetics, Clinical Characteristics, and Natural History. Arch. Ophthalmol. 2022, 246, 107–121. [Google Scholar] [CrossRef]
  173. Douglas, V.P.; Douglas, K.A.; Iannaccone, A. Microbiome and Inherited Retinal Degenerations. Am. J. Pathol. 2023, 193, 1669–1674. [Google Scholar] [CrossRef] [PubMed]
  174. Marti´nez-Gimeno, M.; Gamundi, M.J.; Hernan, I.; Maseras, M.; Milla´, E.; Ayuso, C.; Garci´a-Sandoval, B.; Beneyto, M.; Vilela, C.; Baiget, M.; et al. Mutations in the Pre-mRNA Splicing-Factor GenesPRPF3,PRPF8, andPRPF31in Spanish Families with Autosomal Dominant Retinitis Pigmentosa. Investig. Opthalmology Vis. Sci. 2003, 44, 2171–2177. [Google Scholar] [CrossRef] [PubMed]
  175. Krausová, M.; Kreplová, M.; Banik, P.; Cvačková, Z.; Kubovčiak, J.; Modrák, M.; Zudová, D.; Lindovský, J.; Kubik-Zahorodna, A.; Pálková, M.; et al. Retinitis pigmentosa–associated mutations in mouse Prpf8 cause misexpression of circRNAs and degeneration of cerebellar granule cells. Life Sci. Alliance 2023, 6, e202201855. [Google Scholar] [CrossRef]
  176. De Stefano, M.E.; Ferretti, V.; Mozzetta, C. Synaptic alterations as a neurodevelopmental trait of Duchenne muscular dystrophy. Neurobiol. Dis. 2022, 168, 105718. [Google Scholar] [CrossRef]
  177. Wallace DJ, Wallace JB. All about fibromyalgia: a guide for patients and their families: Oxford University Press; 2002.
  178. Park, D.-J.; Kang, J.-H.; Yim, Y.-R.; Kim, J.-E.; Lee, J.-W.; Lee, K.-E.; Wen, L.; Kim, T.-J.; Park, Y.-W.; Lee, S.-S. Exploring Genetic Susceptibility to Fibromyalgia. Chonnam Med J. 2015, 51, 58–65. [Google Scholar] [CrossRef]
  179. Kong, S.W.; Hu, Y.W.; Ho, J.W.; Ikeda, S.; Polster, S.; John, R.; Hall, J.L.; Bisping, E.; Pieske, B.; dos Remedios, C.G.; et al. Heart Failure–Associated Changes in RNA Splicing of Sarcomere Genes. Circ. Cardiovasc. Genet. 2010, 3, 138–146. [Google Scholar] [CrossRef]
  180. Cao, J.; Wei, Z.; Nie, Y.; Chen, H.-Z. Therapeutic potential of alternative splicing in cardiovascular diseases. EBioMedicine 2024, 101, 104995. [Google Scholar] [CrossRef] [PubMed]
  181. Xue, J.; Zhou, D.; Poulsen, O.; Hartley, I.; Imamura, T.; Xie, E.X.; Haddad, G.G. Exploring miRNA-mRNA regulatory network in cardiac pathology in Na+/H+exchanger isoform 1 transgenic mice. Physiol. Genom. 2018, 50, 846–861. [Google Scholar] [CrossRef]
  182. Park, J.Y.; Li, W.; Zheng, D.; Zhai, P.; Zhao, Y.; Matsuda, T.; Vatner, S.F.; Sadoshima, J.; Tian, B. Comparative Analysis of mRNA Isoform Expression in Cardiac Hypertrophy and Development Reveals Multiple Post-Transcriptional Regulatory Modules. PLOS ONE 2011, 6, e22391. [Google Scholar] [CrossRef]
  183. Han, X.; Li, W.; Chen, C.; Liu, J.; Sun, J.; Wang, F.; Wang, C.; Mu, J.; Gu, X.; Liu, F.; et al. Genetic variants and mRNA expression levels of KLF4 and KLF5 with hypertension: A combination of case-control study and cohort study. J. Biomed. Res. 2025, 39, 103–10. [Google Scholar] [CrossRef]
  184. Zhang, X.; Wang, L.; Han, Z.; Dong, J.; Pang, D.; Fu, Y.; Li, L. KLF4 alleviates cerebral vascular injury by ameliorating vascular endothelial inflammation and regulating tight junction protein expression following ischemic stroke. J. Neuroinflammation 2020, 17, 1–16. [Google Scholar] [CrossRef] [PubMed]
  185. Ni, H.; Haemmig, S.; Deng, Y.; Chen, J.; Simion, V.; Yang, D.; Sukhova, G.; Shvartz, E.; Wara, A.K.; Cheng, H.S.; et al. A Smooth Muscle Cell–Enriched Long Noncoding RNA Regulates Cell Plasticity and Atherosclerosis by Interacting With Serum Response Factor. Arter. Thromb. Vasc. Biol. 2021, 41, 2399–2416. [Google Scholar] [CrossRef] [PubMed]
  186. Jiang, Y.; Qian, H.-Y. Transcription factors: key regulatory targets of vascular smooth muscle cell in atherosclerosis. Mol. Med. 2023, 29, 1–15. [Google Scholar] [CrossRef] [PubMed]
  187. Fang, L.; Sun, Q.; Roth, M. Immunologic and Non-Immunologic Mechanisms Leading to Airway Remodeling in Asthma. Int. J. Mol. Sci. 2020, 21, 757. [Google Scholar] [CrossRef]
  188. Grzela, K.; Litwiniuk, M.; Zagorska, W.; Grzela, T. Airway Remodeling in Chronic Obstructive Pulmonary Disease and Asthma: the Role of Matrix Metalloproteinase-9. Arch. Immunol. et Ther. Exp. 2015, 64, 47–55. [Google Scholar] [CrossRef]
  189. Panek, M.G.; Karbownik, M.S.; Górski, K.M.; Koćwin, M.; Kardas, G.; Marynowski, M.; Kuna, P. New insights into the regulation of TGF-β/Smad and MPK signaling pathway gene expressions by nasal allergen and methacholine challenge test in asthma. Clin. Transl. Allergy 2022, 12, e12172. [Google Scholar] [CrossRef]
  190. Khalenkow, D.; Brandsma, C.-A.; Timens, W.; Choy, D.F.; Grimbaldeston, M.A.; Rosenberger, C.M.; Slebos, D.-J.; Kerstjens, H.A.M.; Faiz, A.; Koppelman, G.H.; et al. Alternative Splicing Is a Major Factor Shaping Transcriptome Diversity in Mild and Severe Chronic Obstructive Pulmonary Disease. Am. J. Respir. Cell Mol. Biol. 2024, 70, 414–423. [Google Scholar] [CrossRef]
  191. Lackey, L.; Coria, A.; Ghosh, A.J.; Grayeski, P.; Hatfield, A.; Shankar, V.; Platig, J.; Xu, Z.; Ramos, S.B.V.; Silverman, E.K.; et al. Alternative poly-adenylation modulates α1-antitrypsin expression in chronic obstructive pulmonary disease. PLOS Genet. 2021, 17, e1009912. [Google Scholar] [CrossRef]
  192. Corley, M.; Solem, A.; Phillips, G.; Lackey, L.; Ziehr, B.; Vincent, H.A.; Mustoe, A.M.; Ramos, S.B.V.; Weeks, K.M.; Moorman, N.J.; et al. An RNA structure-mediated, posttranscriptional model of human α-1-antitrypsin expression. Proc. Natl. Acad. Sci. 2017, 114, E10244–E10253. [Google Scholar] [CrossRef]
  193. Chen, D.; Zhu, S. Whole-exome sequencing identification of a recurrent CRYBB2 variant in a four-generation Chinese family with congenital nuclear cataracts. Exp. Ther. Med. 2021, 22, 1–13. [Google Scholar] [CrossRef]
  194. E Barnum, C.; Al Saai, S.; Patel, S.D.; Cheng, C.; Anand, D.; Xu, X.; Dash, S.; Siddam, A.D.; Glazewski, L.; Paglione, E.; et al. The Tudor-domain protein TDRD7, mutated in congenital cataract, controls the heat shock protein HSPB1 (HSP27) and lens fiber cell morphology. Hum. Mol. Genet. 2020, 29, 2076–2097. [Google Scholar] [CrossRef] [PubMed]
  195. Lachke, S.A.; Alkuraya, F.S.; Kneeland, S.C.; Ohn, T.; Aboukhalil, A.; Howell, G.R.; Saadi, I.; Cavallesco, R.; Yue, Y.; Tsai, A.C.-H.; et al. Mutations in the RNA Granule Component TDRD7 Cause Cataract and Glaucoma. Science 2011, 331, 1571–1576. [Google Scholar] [CrossRef] [PubMed]
  196. Korvala, J.; Jüppner, H.; Mäkitie, O.; Sochett, E.; Schnabel, D.; Mora, S.; Bartels, C.F.; Warman, M.L.; Deraska, D.; Cole, W.G.; et al. Mutations in LRP5 cause primary osteoporosis without features of OI by reducing Wnt signaling activity. BMC Med Genet. 2012, 13, 26–26. [Google Scholar] [CrossRef]
  197. Liu, W.; Zhu, J.; Wu, Z.; Yin, Y.; Wu, Q.; Wu, Y.; Zheng, J.; Wang, C.; Chen, H.; Qazi, T.J.; et al. Insight of novel biomarkers for papillary thyroid carcinoma through multiomics. Front. Oncol. 2023, 13, 1269751. [Google Scholar] [CrossRef]
  198. Piazzi, M.; Bavelloni, A.; Salucci, S.; Faenza, I.; Blalock, W.L. Alternative Splicing, RNA Editing, and the Current Limits of Next Generation Sequencing. Genes 2023, 14, 1386. [Google Scholar] [CrossRef]
  199. Stamm S, Ben-Ari S, Rafalska I, Tang Y, Zhang Z, Toiber D, et al. Function of alternative splicing. Gene. 2005;344:1-20.
  200. Dou, Z.; Zhao, D.; Chen, X.; Xu, C.; Jin, X.; Zhang, X.; Wang, Y.; Xie, X.; Li, Q.; Di, C.; et al. Aberrant Bcl-x splicing in cancer: from molecular mechanism to therapeutic modulation. J. Exp. Clin. Cancer Res. 2021, 40, 1–18. [Google Scholar] [CrossRef]
  201. Wojtyś, W.; Oroń, M. How Driver Oncogenes Shape and Are Shaped by Alternative Splicing Mechanisms in Tumors. Cancers 2023, 15, 2918. [Google Scholar] [CrossRef]
  202. Sugiura, R.; Satoh, R.; Takasaki, T. ERK: A Double-Edged Sword in Cancer. ERK-Dependent Apoptosis as a Potential Therapeutic Strategy for Cancer. Cells 2021, 10, 2509. [Google Scholar] [CrossRef]
  203. Montano, N.; Cenci, T.; Martini, M.; D’alessandris, Q.G.; Pelacchi, F.; Ricci-Vitiani, L.; Maira, G.; De Maria, R.; Larocca, L.M.; Pallini, R. Expression of EGFRvIII in Glioblastoma: Prognostic Significance Revisited. Neoplasia 2011, 13, 1113–IN6. [Google Scholar] [CrossRef]
  204. Batool SM, Muralidharan K, Hsia T, Falotico S, Gamblin AS, Rosenfeld YB, et al. Highly sensitive EGFRvIII detection in circulating extracellular vesicle RNA of glioma patients. Clinical Cancer Research. 2022;28(18):4070-82.
  205. Yang, J.; Yan, J.; Liu, B. Targeting EGFRvIII for glioblastoma multiforme. Cancer Lett. 2017, 403, 224–230. [Google Scholar] [CrossRef]
  206. Dome, A.; Dymova, M.; Richter, V.; Stepanov, G. Post-Transcriptional Modifications of RNA as Regulators of Apoptosis in Glioblastoma. Int. J. Mol. Sci. 2022, 23, 9272. [Google Scholar] [CrossRef] [PubMed]
  207. Yang, H.D.; Nam, S.W. Pathogenic diversity of RNA variants and RNA variation-associated factors in cancer development. Exp. Mol. Med. 2020, 52, 582–593. [Google Scholar] [CrossRef]
  208. Srivastava, S.; Sreenath, T.L.; Dobi, A.; Petrovics, G. Oncogenic activation ofERG:A predominant mechanism in prostate cancer. J. Carcinog. 2011, 10, 37. [Google Scholar] [CrossRef] [PubMed]
  209. Adamo, P.; Ladomery, M.R. The oncogene ERG: a key factor in prostate cancer. Oncogene 2015, 35, 403–414. [Google Scholar] [CrossRef] [PubMed]
  210. Prasad NB, Somervell H, Tufano RP, Dackiw AP, Marohn MR, Califano JA, et al. Identification of genes differentially expressed in benign versus malignant thyroid tumors. Clinical Cancer Research. 2008;14(11):3327-37.
  211. Liu, D.; Rudland, P.S.; Sibson, D.R.; Barraclough, R. Identification of mRNAs differentially-expressed between benign and malignant breast tumour cells. Br. J. Cancer 2002, 87, 423–431. [Google Scholar] [CrossRef]
  212. Zhang, Y.; Qian, J.; Gu, C.; Yang, Y. Alternative splicing and cancer: a systematic review. Signal Transduct. Target. Ther. 2021, 6, 78. [Google Scholar] [CrossRef]
  213. Fu, T.; Amoah, K.; Chan, T.W.; Bahn, J.H.; Lee, J.-H.; Terrazas, S.; Chong, R.; Kosuri, S.; Xiao, X. Massively parallel screen uncovers many rare 3′ UTR variants regulating mRNA abundance of cancer driver genes. Nat. Commun. 2024, 15, 1–20. [Google Scholar] [CrossRef]
  214. Tovar-Parra D, Gil-Quiñones SR, Nova J, Gutierrez-Castaneda LD. 3’UTR-CDKN2A and CDK4 germline variants are associated with susceptibility to cutaneous melanoma. in vivo. 2021;35(3):1529-36.
  215. Marco-Puche, G.; Lois, S.; Benítez, J.; Trivino, J.C. RNA-Seq Perspectives to Improve Clinical Diagnosis. Front. Genet. 2019, 10, 1152. [Google Scholar] [CrossRef]
  216. Lappalainen T, Sammeth M, Friedländer MR, ‘t Hoen PA, Monlong J, Rivas MA, et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature. 2013;501(7468):506-11.
  217. Fuzio, P.; Napoli, A.; Ciampolillo, A.; Lattarulo, S.; Pezzolla, A.; Nuzziello, N.; Liuni, S.; Giorgino, F.; Maiorano, E.; Perlino, E. Clusterin transcript variants expression in thyroid tumor: a potential marker of malignancy? BMC Cancer 2015, 15, 1–10. [Google Scholar] [CrossRef]
  218. Andreotti, V.; Bisio, A.; Paillerets, B.B.; Harland, M.; Cabaret, O.; Newton-Bishop, J.; Pastorino, L.; Bruno, W.; Bertorelli, R.; De Sanctis, V.; et al. The CDKN2A/p16INK4a 5′UTR sequence and translational regulation: impact of novel variants predisposing to melanoma. Pigment. Cell Melanoma Res. 2015, 29, 210–221. [Google Scholar] [CrossRef]
  219. Supplitt, S.; Karpinski, P.; Sasiadek, M.; Laczmanska, I. Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine. Int. J. Mol. Sci. 2021, 22, 1422. [Google Scholar] [CrossRef] [PubMed]
  220. Chen, EY. Gaining insights into vertebrate vascular development: Characterization of zebrafish morphants identified from a morpholino-based vascular screen [Ph.D.]. United States -- Minnesota: University of Minnesota; 2004.
  221. Alsafadi, S.; Houy, A.; Battistella, A.; Popova, T.; Wassef, M.; Henry, E.; Tirode, F.; Constantinou, A.; Piperno-Neumann, S.; Roman-Roman, S.; et al. Cancer-associated SF3B1 mutations affect alternative splicing by promoting alternative branchpoint usage. Nat. Commun. 2016, 7, 10615. [Google Scholar] [CrossRef]
  222. Liu Z, Yoshimi A, Wang J, Cho H, Chun-Wei Lee S, Ki M, et al. Mutations in the RNA splicing factor SF3B1 promote tumorigenesis through MYC stabilization. Cancer Discovery. 2020;10(6):806-21.
  223. Wang, L.; Brooks, A.N.; Fan, J.; Wan, Y.; Gambe, R.; Li, S.; Hergert, S.; Yin, S.; Freeman, S.S.; Levin, J.Z.; et al. Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia. Cancer Cell 2016, 30, 750–763. [Google Scholar] [CrossRef] [PubMed]
  224. Ji, S.; Wang, F.; Wu, Y.; Hu, H.; Xing, Z.; Zhu, J.; Xu, S.; Han, T.; Liu, G.; Wu, Z.; et al. Large-scale transcript variants dictate neoepitopes for cancer immunotherapy. Sci. Adv. 2025, 11, eado5600. [Google Scholar] [CrossRef]
  225. Türeci, Ö.; Vormehr, M.; Diken, M.; Kreiter, S.; Huber, C.; Sahin, U. Targeting the Heterogeneity of Cancer with Individualized Neoepitope Vaccines. Clin. Cancer Res. 2016, 22, 1885–1896. [Google Scholar] [CrossRef]
  226. Blass, E.; Ott, P.A. Advances in the development of personalized neoantigen-based therapeutic cancer vaccines. Nat. Rev. Clin. Oncol. 2021, 18, 215–229. [Google Scholar] [CrossRef]
  227. Rukov, J.L.; Shomron, N. MicroRNA pharmacogenomics: Post-transcriptional regulation of drug response. Trends Mol. Med. 2011, 17, 412–423. [Google Scholar] [CrossRef]
  228. Ingelman-Sundberg, M.; Pirmohamed, M. Precision medicine in cardiovascular therapeutics: Evaluating the role of pharmacogenetic analysis prior to drug treatment. J. Intern. Med. 2024, 295, 583–598. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

Disclaimer

Terms of Use

Privacy Policy

Privacy Settings

© 2025 MDPI (Basel, Switzerland) unless otherwise stated