Top-ranked expressed gene transcripts of human protein-coding genes investigated with GTEx dataset

Copy number losses of oncogenes and gains of tumor suppressor genes generate common driver mutations

Cancer driver genes can undergo positive selection for various types of genetic alterations, including gain-of-function or loss-of-function mutations and copy number alterations (CNA). We investigated the landscape of different types of alterations affecting driver genes in 17,644 cancer exomes and genomes. We find that oncogenes may simultaneously exhibit signatures of positive selection and also negative selection in different gene segments, suggesting a method to identify additional tumor types where an oncogene is a driver or a vulnerability. Next, we characterize the landscape of CNA-dependent selection effects, revealing a general trend of increased positive selection on oncogene mutations not only upon CNA gains but also upon CNA deletions. Similarly, we observe a positive interaction between mutations and CNA gains in tumor suppressor genes. Thus, two-hit events involving point mutations and CNA are universally observed regardless of the type of CNA and may signal new therapeutic opportunities. An analysis with focus on the somatic CNA two-hit events can help identify additional driver genes relevant to a tumor type. By a global inference of point mutation and CNA selection signatures and interactions thereof across genes and tissues, we identify 9 evolutionary archetypes of driver genes, representing different mechanisms of (in)activation by genetic alterations.

Housekeeping protein-coding genes interrogated with tissue and individual variations

Housekeeping protein-coding genes are stably expressed genes in cells and tissues that are thought to be engaged in fundamental cellular biological functions. They are often utilized as normalization references in molecular biology research and are especially important in integrated bioinformatic investigations. Prior studies have examined human housekeeping protein-coding genes by analyzing various gene expression datasets. The inclusion of different tissue types significantly impacted the discovery of housekeeping genes. In this report, we investigated particularly individual human subject expression differences in protein-coding genes across different tissue types. We used GTEx V8 gene expression datasets obtained from more than 16,000 human normal tissue samples. Furthermore, the Gini index is utilized to investigate the expression variations of protein-coding genes between tissue and individual donor subjects. Housekeeping protein-coding genes found using Gini index profiles may vary depending on the tissue subtypes investigated, particularly given the diverse sample size collections across the GTEx tissue subtypes. We subsequently selected major tissues and identified subsets of housekeeping genes with stable expression levels among human donors within those tissues. In this work, we provide alternative sets of housekeeping protein-coding genes that show more consistent expression patterns in human subjects across major solid organs. Weblink: https://hpsv.ibms.sinica.edu.tw .

Diviner uncovers hundreds of novel human (and other) exons though comparative analysis of proteins

Background

Eukaryotic genes are often composed of multiple exons that are stitched together by splicing out the intervening introns. These exons may be conditionally joined in different combinations to produce a collection of related, but distinct, mRNA transcripts. For protein-coding genes, these products of alternative splicing lead to production of related protein variants (isoforms) of a gene. Complete labeling of the protein-coding content of a eukaryotic genome requires discovery of mRNA encoding all isoforms, but it is impractical to enumerate all possible combinations of tissue, developmental stage, and environmental context; as a result, many true exons go unlabeled in genome annotations.

Results

One way to address the combinatoric challenge of finding all isoforms in a single organism A is to leverage sequencing efforts for other organisms - each time a new organism is sequenced, it may be under a new combination of conditions, so that a previously unobserved isoform may be sequenced. We present Diviner, a software tool that identifies previously undocumented exons in organisms by comparing isoforms across species. We demonstrate Diviner's utility by locating hundreds of novel exons in the genomes of human, mouse, and rat, as well as in the ferret genome. Further, we provide analyses supporting the notion that most of the new exons reported by Diviner are likely to be part of a true (but unobserved) isoform of the containing species.

Cuproptosis-related gene LIPT1 as a prognostic indicator in non-small cell lung cancer: Functional involvement and regulation of ATOX1 expression

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths, necessitating a deeper understanding of novel cell death pathways like cuproptosis. This study explored the relevance of cuproptosis-related genes in NSCLC and their potential prognostic significance. We analyzed the expression of 16 cuproptosis-related genes in 1017 NSCLC tumors and 578 Genotype-Tissue Expression (GTEx) normal samples from The Cancer Genome Atlas (TCGA) to identify significant genes. A risk model and prognostic nomogram were employed to identify the pivotal prognostic gene. Further in vitro experiments were conducted to investigate the functions of the identified genes in NSCLC cell lines. LIPT1, a gene for lipoate-protein ligase 1 enzyme, emerged as the central prognostic gene with decreased expression in NSCLC. Importantly, elevated LIPT1 levels were associated with a favorable prognosis for NSCLC patients. Overexpression of LIPT1 inhibited cell growth and enhanced apoptosis in NSCLC. We confirmed that LIPT1 downregulates the copper chaperone gene antioxidant 1 (ATOX1), thereby impeding NSCLC progression. Our study identified LIPT1 as a valuable prognostic biomarker in NSCLC as it elucidates its tumor-inhibitory role through the modulation of ATOX1. These findings offered insights into the potential therapeutic targeting of LIPT1 in NSCLC, contributing to a deeper understanding of this deadly disease.

Natural antisense transcripts as versatile regulators of gene expression

Long non-coding RNAs (lncRNAs) are emerging as a major class of gene products that have central roles in cell and developmental biology. Natural antisense transcripts (NATs) are an important subset of lncRNAs that are expressed from the opposite strand of protein-coding and non-coding genes and are a genome-wide phenomenon in both eukaryotes and prokaryotes. In eukaryotes, a myriad of NATs participate in regulatory pathways that affect expression of their cognate sense genes. Recent developments in the study of NATs and lncRNAs and large-scale sequencing and bioinformatics projects suggest that whether NATs regulate expression, splicing, stability or translation of the sense transcript is influenced by the pattern and degrees of overlap between the sense-antisense pair. Moreover, epigenetic gene regulatory mechanisms prevail in somatic cells whereas mechanisms dependent on the formation of double-stranded RNA intermediates are prevalent in germ cells. The modulating effects of NATs on sense transcript expression make NATs rational targets for therapeutic interventions.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

Isoform alterations in the ubiquitination machinery impacting gastrointestinal malignancies

The advancement of RNAseq and isoform-specific expression platforms has led to the understanding that isoform changes can alter molecular signaling to promote tumorigenesis. An active area in cancer research is uncovering the roles of ubiquitination on spliceosome assembly contributing to transcript diversity and expression of alternative isoforms. However, the effects of isoform changes on functionality of ubiquitination machineries (E1, E2, E3, E4, and deubiquitinating (DUB) enzymes) influencing onco- and tumor suppressor protein stabilities is currently understudied. Characterizing these changes could be instrumental in improving cancer outcomes via the identification of novel biomarkers and targetable signaling pathways. In this review, we focus on highlighting reported examples of direct, protein-coded isoform variation of ubiquitination enzymes influencing cancer development and progression in gastrointestinal (GI) malignancies. We have used a semi-automated system for identifying relevant literature and applied established systems for isoform categorization and functional classification to help structure literature findings. The results are a comprehensive snapshot of known isoform changes that are significant to GI cancers, and a framework for readers to use to address isoform variation in their own research. One of the key findings is the potential influence that isoforms of the ubiquitination machinery have on oncoprotein stability.

The impact of tRNA modifications on translation in cancer: identifying novel therapeutic avenues

Recent advancements have illuminated the critical role of RNA modifications in post-transcriptional regulation, shaping the landscape of gene expression. This review explores how tRNA modifications emerge as critical players, fine-tuning functionalities that not only maintain the fidelity of protein synthesis but also dictate gene expression and translation profiles. Highlighting their dysregulation as a common denominator in various cancers, we systematically investigate the intersection of both cytosolic and mitochondrial tRNA modifications with cancer biology. These modifications impact key processes such as cell proliferation, tumorigenesis, migration, metastasis, bioenergetics and the modulation of the tumor immune microenvironment. The recurrence of altered tRNA modification patterns across different cancer types underscores their significance in cancer development, proposing them as potential biomarkers and as actionable targets to disrupt tumorigenic processes, offering new avenues for precision medicine in the battle against cancer.

Long non-coding RNA generated from CDKN1A gene by alternative polyadenylation regulates p21 expression during DNA damage response

Alternative Polyadenylation (APA) is an emerging mechanism for dynamic changes in gene expression. Previously, we described widespread APA occurrence in introns during the DNA damage response (DDR). Here, we show that a DDR-activated APA event occurs in the first intron of CDKN1A, inducing an alternate last exon-containing lncRNA. We named this lncRNA SPUD (Selective Polyadenylation Upon DNA Damage). SPUD localizes to polysomes in the cytoplasm and is detectable as multiple isoforms in available high-throughput studies. SPUD has low abundance compared to the CDKN1A full-length isoform under non-stress conditions, and SPUD is induced in cancer and normal cells under a variety of DNA damaging conditions in part through p53. The RNA binding protein HuR binds to and promotes the stability of SPUD precursor RNA. SPUD induction increases p21 protein, but not mRNA levels, affecting p21 functions in cell-cycle, CDK2 expression and cell growth. Like CDKN1A full-length isoform, SPUD can bind two competitive p21 translational regulators, the inhibitor calreticulin and the activator CUGBP1; SPUD alters their association with CDKN1A full-length in a DDR-dependent manner, promoting CDKN1A translation. Together, these results show a new regulatory mechanism by which a lncRNA controls p21 expression post-transcriptionally, highlighting lncRNA relevance in DDR progression and cell-cycle.

Isoform switching leads to downregulation of cytokine producing genes in estrogen receptor positive breast cancer

Objective: Estrogen receptor breast cancer (BC) is characterized by the expression of estrogen receptors. It is the most common cancer among women, with an incidence rate of 2.26 million cases worldwide. The aim of this study was to identify differentially expressed genes and isoform switching between estrogen receptor positive and triple negative BC samples. Methods: The data were collected from ArrayExpress, followed by preprocessing and subsequent mapping from HISAT2. Read quantification was performed by StringTie, and then R package ballgown was used to perform differential expression analysis. Functional enrichment analysis was conducted using Enrichr, and then immune genes were shortlisted based on the ScType marker database. Isoform switch analysis was also performed using the IsoformSwitchAnalyzeR package. Results: A total of 9,771 differentially expressed genes were identified, of which 86 were upregulated and 117 were downregulated. Six genes were identified as mainly associated with estrogen receptor positive BC, while a novel set of ten genes were found which have not previously been reported in estrogen receptor positive BC. Furthermore, alternative splicing and subsequent isoform usage in the immune system related genes were determined. Conclusion: This study identified the differential usage of isoforms in the immune system related genes in cancer cells that suggest immunosuppression due to the dysregulation of CXCR chemokine receptor binding, iron ion binding, and cytokine activity.

Autonomous action and cooperativity between the ONECUT2 transcription factor and its 3' untranslated region

The transcription factor ONECUT2 (OC2) is a master transcriptional regulator operating in metastatic castration-resistant prostate cancer that suppresses androgen receptor activity and promotes neural differentiation and tumor cell survival. OC2 mRNA possesses an unusually long (14,575 nt), evolutionarily conserved 3' untranslated region (3' UTR) with many microRNA binding sites, including up to 26 miR-9 sites. This is notable because miR-9 targets many of the same genes regulated by the OC2 protein. Paradoxically, OC2 expression is high in tissues with high miR-9 expression. The length and complex secondary structure of OC2 mRNA suggests that it is a potent master competing endogenous RNA (ceRNA) capable of sequestering miRNAs. Here, we describe a novel role for OC2 3' UTR in lethal prostate cancer consistent with a function as a ceRNA. A plausible ceRNA network in OC2-driven tumors was constructed computationally and then confirmed in prostate cancer cell lines. Genes regulated by OC2 3' UTR exhibited high overlap (up to 45%) with genes driven by the overexpression of the OC2 protein in the absence of 3' UTR, indicating a cooperative functional relationship between the OC2 protein and its 3' UTR. These overlapping networks suggest an evolutionarily conserved mechanism to reinforce OC2 transcription by protection of OC2-regulated mRNAs from miRNA suppression. Both the protein and 3' UTR showed increased polycomb-repressive complex activity. The expression of OC2 3' UTR mRNA alone (without protein) dramatically increased the metastatic potential by in vitro assays. Additionally, OC2 3' UTR increased the expression of Aldo-Keto reductase and UDP-glucuronyl transferase family genes responsible for altering the androgen synthesis pathway. ONECUT2 represents the first-described dual-modality transcript that operates as both a key transcription factor driving castration-resistant prostate cancer and a master ceRNA that promotes and protects the same transcriptional network.

RNA splicing dysregulation and the hallmarks of cancer

Dysregulated RNA splicing is a molecular feature that characterizes almost all tumour types. Cancer-associated splicing alterations arise from both recurrent mutations and altered expression of trans-acting factors governing splicing catalysis and regulation. Cancer-associated splicing dysregulation can promote tumorigenesis via diverse mechanisms, contributing to increased cell proliferation, decreased apoptosis, enhanced migration and metastatic potential, resistance to chemotherapy and evasion of immune surveillance. Recent studies have identified specific cancer-associated isoforms that play critical roles in cancer cell transformation and growth and demonstrated the therapeutic benefits of correcting or otherwise antagonizing such cancer-associated mRNA isoforms. Clinical-grade small molecules that modulate or inhibit RNA splicing have similarly been developed as promising anticancer therapeutics. Here, we review splicing alterations characteristic of cancer cell transcriptomes, dysregulated splicing's contributions to tumour initiation and progression, and existing and emerging approaches for targeting splicing for cancer therapy. Finally, we discuss the outstanding questions and challenges that must be addressed to translate these findings into the clinic.

Delineation of functionally essential protein regions for 242 neurodevelopmental genes

Neurodevelopmental disorders (NDDs), including severe paediatric epilepsy, autism and intellectual disabilities are heterogeneous conditions in which clinical genetic testing can often identify a pathogenic variant. For many of them, genetic therapies will be tested in this or the coming years in clinical trials. In contrast to first-generation symptomatic treatments, the new disease-modifying precision medicines require a genetic test-informed diagnosis before a patient can be enrolled in a clinical trial. However, even in 2022, most identified genetic variants in NDD genes are 'variants of uncertain significance'. To safely enrol patients in precision medicine clinical trials, it is important to increase our knowledge about which regions in NDD-associated proteins can 'tolerate' missense variants and which ones are 'essential' and will cause a NDD when mutated. In addition, knowledge about functionally indispensable regions in the 3D structure context of proteins can also provide insights into the molecular mechanisms of disease variants. We developed a novel consensus approach that overlays evolutionary, and population based genomic scores to identify 3D essential sites (Essential3D) on protein structures. After extensive benchmarking of AlphaFold predicted and experimentally solved protein structures, we generated the currently largest expert curated protein structure set for 242 NDDs and identified 14 377 Essential3D sites across 189 gene disorders associated proteins. We demonstrate that the consensus annotation of Essential3D sites improves prioritization of disease mutations over single annotations. The identified Essential3D sites were enriched for functional features such as intermembrane regions or active sites and discovered key inter-molecule interactions in protein complexes that were otherwise not annotated. Using the currently largest autism, developmental disorders, and epilepsies exome sequencing studies including >360 000 NDD patients and population controls, we found that missense variants at Essential3D sites are 8-fold enriched in patients. In summary, we developed a comprehensive protein structure set for 242 NDDs and identified 14 377 Essential3D sites in these. All data are available at https://es-ndd.broadinstitute.org for interactive visual inspection to enhance variant interpretation and development of mechanistic hypotheses for 242 NDDs genes. The provided resources will enhance clinical variant interpretation and in silico drug target development for NDD-associated genes and encoded proteins.

Long Non-Coding RNA Generated from CDKN1A Gene by Alternative Polyadenylation Regulates p21 Expression during DNA Damage Response

Alternative Polyadenylation (APA) is an emerging mechanism for dynamic changes in gene expression. Previously, we described widespread APA occurrence in introns during the DNA damage response (DDR). Here, we show that a DNA damage activated APA event occurs in the first intron of CDKN1A , inducing an alternate last exon (ALE)-containing lncRNA. We named this lncRNA SPUD (Selective Polyadenylation Upon Damage). SPUD localizes to polysomes in the cytoplasm and is detectable as multiple isoforms in available high throughput studies. SPUD has low abundance compared to the CDKN1A full-length isoform and is induced in cancer and normal cells under a variety of DNA damaging conditions in part through p53 transcriptional activation. RNA binding protein (RBP) HuR and the transcriptional repressor CTCF regulate SPUD levels. SPUD induction increases p21 protein, but not CDKN1A full-length levels, affecting p21 functions in cell-cycle, CDK2 expression, and cell viability. Like CDKN1A full-length isoform, SPUD can bind two competitive p21 translational regulators, the inhibitor calreticulin and the activator CUGBP1; SPUD can change their association with CDKN1A full-length in a DDR-dependent manner. Together, these results show a new regulatory mechanism by which a lncRNA controls p21 expression post-transcriptionally, highlighting lncRNA relevance in DDR progression and cellcycle.

Mirage2's high-quality spliced protein-to-genome mappings produce accurate multiple-sequence alignments of isoforms

The organization of homologous protein sequences into multiple sequence alignments (MSAs) is a cornerstone of modern analysis of proteins. Recent focus on the importance of alternatively-spliced isoforms in disease and cell biology has highlighted the need for MSA software that can appropriately account for isoforms and the exon-length insertions or deletions that isoforms may have relative to each other. We previously developed Mirage, a software package for generating MSAs for isoforms spanning multiple species. Here, we present Mirage2, which retains the fundamental algorithms of the original Mirage implementation while providing substantially improved translated mapping and improving several aspects of usability. We demonstrate that Mirage2 is highly effective at mapping proteins to their encoding exons, and that these protein-genome mappings lead to extremely accurate intron-aware alignments. Additionally, Mirage2 implements a number of engineering improvements that simplify installation and use.

Structure-guided isoform identification for the human transcriptome

Recently developed methods to predict three-dimensional protein structure with high accuracy have opened new avenues for genome and proteome research. We explore a new hypothesis in genome annotation, namely whether computationally predicted structures can help to identify which of multiple possible gene isoforms represents a functional protein product. Guided by protein structure predictions, we evaluated over 230,000 isoforms of human protein-coding genes assembled from over 10,000 RNA sequencing experiments across many human tissues. From this set of assembled transcripts, we identified hundreds of isoforms with more confidently predicted structure and potentially superior function in comparison to canonical isoforms in the latest human gene database. We illustrate our new method with examples where structure provides a guide to function in combination with expression and evolutionary evidence. Additionally, we provide the complete set of structures as a resource to better understand the function of human genes and their isoforms. These results demonstrate the promise of protein structure prediction as a genome annotation tool, allowing us to refine even the most highly curated catalog of human proteins. More generally we demonstrate a practical, structure-guided approach that can be used to enhance the annotation of any genome.

TEx-MST: tissue expression profiles of MANE select transcripts

Recently, a new reference transcript dataset [Matched Annotation from the NCBI and EMBL-EBI (MANE) select] was released by NCBI and EMBL-EBI to make available a new unified representative transcript for human protein-coding genes. While the main purpose of MANE project is to provide a harmonized gene and transcript information standard, there is no explicit tissue expression information about these MANE select transcripts. In this report, we tried to provide useful expression profiles of MANE select transcripts in various normal human tissues to allow further interrogation of their molecular modulations and functional significance. We obtained the new V9 transcript expression dataset from the Genotype-Tissue Expression (GTEx) web portal. This new GTEx dataset, based on a long-read sequencing platform, affords better assessment of the expression of alternative spliced transcripts. This tissue expression profiles of MANE select transcripts (TEx-MST) database not only provides the basic information of MANE select transcripts but also tissue expression profiles on alternative transcripts in protein-coding genes. Users can initiate the interrogation by gene symbol searches or by browsing the MANE genes with various criteria (such as genome locations or expression rankings). We further utilized the GENCODE biotype feature to identify the top-ranked protein-coding transcripts by choosing the most expressed protein-coding transcripts from GTEx datasets (both V8 and V9 datasets). In summary, there are 18 083 genes matched between MANE and GTEx. Among them, 13 245 MANE select transcripts matched with the top-ranked protein-coding transcripts in GTEx V9 dataset, which underlined the dominate expression of MANE select transcripts. This TEx-MST web bioinformatic database provides a visualized user interface for the normal tissue expression patterns of MANE select transcripts using the newly released GTEx dataset.

Database URL: TEx-MST is available at https://texmst.ibms.sinica.edu.tw/

Molecular Modelling Hurdle in the Next-Generation Sequencing Era

There are challenges in the genetic diagnosis of rare diseases, and pursuing an optimal strategy to identify the cause of the disease is one of the main objectives of any clinical genomics unit. A range of techniques are currently used to characterize the genomic variability within the human genome to detect causative variants of specific disorders. With the introduction of next-generation sequencing (NGS) in the clinical setting, geneticists can study single-nucleotide variants (SNVs) throughout the entire exome/genome. In turn, the number of variants to be evaluated per patient has increased significantly, and more information has to be processed and analyzed to determine a proper diagnosis. Roughly 50% of patients with a Mendelian genetic disorder are diagnosed using NGS, but a fair number of patients still suffer a diagnostic odyssey. Due to the inherent diversity of the human population, as more exomes or genomes are sequenced, variants of uncertain significance (VUSs) will increase exponentially. Thus, assigning relevance to a VUS (non-synonymous as well as synonymous) in an undiagnosed patient becomes crucial to assess the proper diagnosis. Multiple algorithms have been used to predict how a specific mutation might affect the protein’s function, but they are far from accurate enough to be conclusive. In this work, we highlight the difficulties of genomic variability determined by NGS that have arisen in diagnosing rare genetic diseases, and how molecular modelling has to be a key component to elucidate the relevance of a specific mutation in the protein’s loss of function or malfunction. We suggest that the creation of a multi-omics data model should improve the classification of pathogenicity for a significant amount of the detected genomic variability. Moreover, we argue how it should be incorporated systematically in the process of variant evaluation to be useful in the clinical setting and the diagnostic pipeline.

Characterization of RNA content in individual phase-separated coacervate microdroplets

Condensates formed by complex coacervation are hypothesized to have played a crucial part during the origin-of-life. In living cells, condensation organizes biomolecules into a wide range of membraneless compartments. Although RNA is a key component of biological condensates and the central component of the RNA world hypothesis, little is known about what determines RNA accumulation in condensates and to which extend single condensates differ in their RNA composition. To address this, we developed an approach to read the RNA content from single synthetic and protein-based condensates using high-throughput sequencing. We find that certain RNAs efficiently accumulate in condensates. These RNAs are strongly enriched in sequence motifs which show high sequence similarity to short interspersed elements (SINEs). We observe similar results for protein-derived condensates, demonstrating applicability across different in vitro reconstituted membraneless organelles. Thus, our results provide a new inroad to explore the RNA content of phase-separated droplets at single condensate resolution.

Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset

The discovery and quantification of mRNA transcripts using short-read next-generation sequencing (NGS) data is a complicated task. There are far more alternative mRNA transcripts expressed by human genes than can be identified from NGS transcriptome data and various bioinformatic pipelines, while the numbers of annotated human protein-coding genes has gradually declined in recent years. It is essential to learn more about the thorough tissue expression profiles of alternative transcripts in order to obtain their molecular modulations and actual functional significance. In this report, we present a bioinformatic database for interrogating the representative tissue of human protein-coding transcripts. The database allows researchers to visually explore the top-ranked transcript expression profiles in particular tissue types. Most transcripts of protein-coding genes were found to have certain tissue expression patterns. This observation demonstrated that many alternative transcripts were particularly modulated in different cell types. This user-friendly tool visually represents transcript expression profiles in a tissue-specific manner. Identification of tissue specific protein-coding genes and transcripts is a substantial advance towards interpreting their biological functions and further functional genomics studies.

The Case for, and Challenges of, Human Cardiac Tissue in Advancing Phosphoprotein Research

Cardiovascular disease (CVD) and stroke affect over 92 million Americans and account for nearly 1 out of 3 deaths in the US. The use of animal models in cardiovascular research has led to considerable advances in treatment and in our understanding of the pathophysiology of many CVDs. Still, animals may not fully recapitulate human disease states; species differences have long been postulated to be one of the main reasons for a failure of translation between animals and humans in drug discovery and development. Indeed, it has become increasingly clear over the past few decades that to answer certain biomedical questions, like the physiological mechanisms that go awry in many human CVDs, animal tissues may not always be the best option to use. While human cardiac tissue has long been used for laboratory research, published findings often contradict each other, leading to difficulties in interpretation. Current difficulties in utilizing human cardiac tissue include differences in acquisition time, varying tissue procurement protocols, and the struggle to define a human “control” sample. With the tremendous emphasis on translational research that continues to grow, research studies using human tissues are becoming more common. This mini review will discuss advantages, disadvantages, and considerations of using human cardiac tissue in the study of CVDs, paying specific attention to the study of phosphoproteins.

The RNA methyltransferase METTL8 installs m3C32 in mitochondrial tRNAsThr/Ser(UCN) to optimise tRNA structure and mitochondrial translation

Modified nucleotides in tRNAs are important determinants of folding, structure and function. Here we identify METTL8 as a mitochondrial matrix protein and active RNA methyltransferase responsible for installing m3C32 in the human mitochondrial (mt-)tRNAThr and mt-tRNASer(UCN). METTL8 crosslinks to the anticodon stem loop (ASL) of many mt-tRNAs in cells, raising the question of how methylation target specificity is achieved. Dissection of mt-tRNA recognition elements revealed U34G35 and t6A37/(ms2)i6A37, present concomitantly only in the ASLs of the two substrate mt-tRNAs, as key determinants for METTL8-mediated methylation of C32. Several lines of evidence demonstrate the influence of U34, G35, and the m3C32 and t6A37/(ms2)i6A37 modifications in mt-tRNAThr/Ser(UCN) on the structure of these mt-tRNAs. Although mt-tRNAThr/Ser(UCN) lacking METTL8-mediated m3C32 are efficiently aminoacylated and associate with mitochondrial ribosomes, mitochondrial translation is mildly impaired by lack of METTL8. Together these results define the cellular targets of METTL8 and shed new light on the role of m3C32 within mt-tRNAs.

Uncovering the impacts of alternative splicing on the proteome with current omics techniques

The high‐throughput sequencing of cellular RNAs has underscored a broad effect of isoform diversification through alternative splicing on the transcriptome. Moreover, the differential production of transcript isoforms from gene loci has been recognized as a critical mechanism in cell differentiation, organismal development, and disease. Yet, the extent of the impact of alternative splicing on protein production and cellular function remains a matter of debate. Multiple experimental and computational approaches have been developed in recent years to address this question. These studies have unveiled how molecular changes at different steps in the RNA processing pathway can lead to differences in protein production and have functional effects. New and emerging experimental technologies open exciting new opportunities to develop new methods to fully establish the connection between messenger RNA expression and protein production and to further investigate how RNA variation impacts the proteome and cell function.

This article is categorized under:

RNA Processing > Splicing Regulation/Alternative Splicing

Translation > Regulation

RNA Evolution and Genomics > Computational Analyses of RNA

Biology of the mRNA Splicing Machinery and Its Dysregulation in Cancer Providing Therapeutic Opportunities

Dysregulation of messenger RNA (mRNA) processing—in particular mRNA splicing—is a hallmark of cancer. Compared to normal cells, cancer cells frequently present aberrant mRNA splicing, which promotes cancer progression and treatment resistance. This hallmark provides opportunities for developing new targeted cancer treatments. Splicing of precursor mRNA into mature mRNA is executed by a dynamic complex of proteins and small RNAs called the spliceosome. Spliceosomes are part of the supraspliceosome, a macromolecular structure where all co-transcriptional mRNA processing activities in the cell nucleus are coordinated. Here we review the biology of the mRNA splicing machinery in the context of other mRNA processing activities in the supraspliceosome and present current knowledge of its dysregulation in lung cancer. In addition, we review investigations to discover therapeutic targets in the spliceosome and give an overview of inhibitors and modulators of the mRNA splicing process identified so far. Together, this provides insight into the value of targeting the spliceosome as a possible new treatment for lung cancer.