GeneBase 1.1: a tool to summarize data from NCBI gene datasets and its application to an update of human gene statistics

Massively parallel reporter assays identify functional enhancer variants at QT interval GWAS loci

Genome-wide association studies (GWAS) have identified >30 loci with multiple common noncoding variants explaining interindividual electrocardiographic QT interval (QTi) variation. Of the many types of noncoding functional elements, here we sought to identify transcriptional enhancers with sequence variation and their cognate transcription factors (TFs) that alter the expression of proximal cardiac genes to affect QTi variation. We used massively parallel reporter assays (MPRA) in mouse cardiomyocyte HL-1 cells to screen for functional enhancer variants among 1,018 QTi-associated GWAS variants that overlap candidate cardiac enhancers across 31 loci. We identified 445 GWAS variant-containing enhancers of which 79 showed significant allelic difference in enhancer activity across 21 GWAS loci, with multiple enhancer variants per locus. Of these, we predicted differential binding by cardiac TFs, including AP-1, ATF-1, GATA2, MEF2, NKX2.5, SRF and TBX5 which are known to play key roles in development and homeostasis, at 49 enhancer variants. Finally, we used expression quantitative trait locus mapping and predicted promoter-enhancer contacts to identify 14 candidate target genes through analyses of 36 enhancer variants at 16 loci. This study provides strong evidence for 14 cardiac genes, 10 of them novel, impacting on QTi variation, beyond explaining observed genetic associations.

Nucleic acid therapeutics: Past, present, and future

Nucleic acid therapeutics have become increasingly recognized in recent years for their capability to target both coding and non-coding sequences. Several types of nucleic acid modalities, including siRNA, mRNA, aptamer, along with antisense oligo, have been approved by regulatory bodies for therapeutic use. The field of nucleic acid therapeutics has been brought to the forefront by the rapid development of vaccines against COVID-19, followed by a number of approvals for clinical use including much anticipated CRISPR-Cas9. However, obstacles such as the difficulty of achieving efficient and targeted delivery to diseased sites remain. This review provides an overview of nucleic acid therapeutics and highlights substantial advancements, including critical engineering, conjugation, and delivery strategies, that are paving the way for their growing role in modern medicine.

From computational models of the splicing code to regulatory mechanisms and therapeutic implications

Since the discovery of RNA splicing and its role in gene expression, researchers have sought a set of rules, an algorithm or a computational model that could predict the splice isoforms, and their frequencies, produced from any transcribed gene in a specific cellular context. Over the past 30 years, these models have evolved from simple position weight matrices to deep-learning models capable of integrating sequence data across vast genomic distances. Most recently, new model architectures are moving the field closer to context-specific alternative splicing predictions, and advances in sequencing technologies are expanding the type of data that can be used to inform and interpret such models. Together, these developments are driving improved understanding of splicing regulatory mechanisms and emerging applications of the splicing code to the rational design of RNA- and splicing-based therapeutics.

inDrops-2: a flexible, versatile and cost-efficient droplet microfluidic approach for high-throughput scRNA-seq of fresh and preserved clinical samples

The expansion of single-cell analytical techniques has empowered the exploration of diverse biological questions at the individual cells. Droplet-based single-cell RNA sequencing (scRNA-seq) methods have been particularly widely used due to their high-throughput capabilities and small reaction volumes. While commercial systems have contributed to the widespread adoption of droplet-based scRNA-seq, their relatively high cost limits the ability to profile large numbers of cells and samples. Moreover, as the scale of single-cell sequencing continues to expand, accommodating diverse workflows and cost-effective multi-biospecimen profiling becomes more critical. Herein, we present inDrops-2, an open-source scRNA-seq technology designed to profile live or preserved cells with a sensitivity matching that of state-of-the-art commercial systems but at a 6-fold lower cost. We demonstrate the flexibility of inDrops-2, by implementing two prominent scRNA-seq protocols, based on exponential and linear amplification of barcoded-complementary DNA, and provide useful insights into the advantages and disadvantages inherent to each approach. We applied inDrops-2 to simultaneously profile multiple human lung carcinoma samples that had been subjected to cell preservation, long-term storage and multiplexing to obtain a multiregional cellular profile of the tumor microenvironment. The scalability, sensitivity and cost efficiency make inDrops-2 stand out among other droplet-based scRNA-seq methods, ideal for large-scale studies on rare cell molecular signatures.

Exploring autism spectrum disorder and co-occurring trait associations to elucidate multivariate genetic mechanisms and insights

BACKGROUND

Autism spectrum disorder (ASD) is a partially heritable neurodevelopmental trait, and people with ASD may also have other co-occurring trait such as ADHD, anxiety disorders, depression, mental health issues, learning difficulty, physical health traits and communication challenges. The concomitant development of ASD and other neurological traits is assumed to result from a complex interplay between genetics and the environment. However, only a limited number of studies have performed multivariate genome-wide association studies (GWAS) for ASD.

METHODS

We conducted to-date the largest multivariate GWAS on ASD and 8 ASD co-occurring traits (ADHD, ADHD childhood, anxiety stress (ASDR), bipolar (BIP), disruptive behaviour (DBD), educational attainment (EA), major depression, and schizophrenia (SCZ)) using summary statistics from leading studies. Multivariate associations and central traits were further identified. Subsequently, colocalization and Mendelian randomization (MR) analysis were performed on the associations identified with the central traits containing ASD. To further validate our findings, pathway and quantified trait loci (QTL) resources as well as independent datasets consisting of 112 (45 probands) whole genome sequence data from the GEMMA project were utilized.

RESULTS

Multivariate GWAS resulted in 637 significant associations (p < 5e-8), among which 322 are reported for the first time for any trait. 37 SNPs were identified to contain ASD and one or more traits in their central trait set, including variants mapped to known SFARI ASD genes MAPT, CADPS and NEGR1 as well as novel ASD genes KANSL1, NSF and NTM, associated with immune response, synaptic transmission, and neurite growth respectively. Mendelian randomization analyses found that genetic liability for ADHD childhood, ASRD and DBT has causal effects on the risk of ASD while genetic liability for ASD has causal effects on the risk of ADHD, ADHD childhood, BIP, WA, MDD and SCZ. Frequency differences of SNPs found in NTM and CADPS genes, respectively associated with neurite growth and neural/endocrine calcium regulation, were found between GEMMA ASD probands and controls. Pathway, QTL and cell type enrichment implicated microbiome, enteric inflammation, and central nervous system enrichments.

CONCLUSIONS

Our study, combining multivariate GWAS with systematic decomposition, identified novel genetic associations related to ASD and ASD co-occurring driver traits. Statistical tests were applied to discern evidence for shared and interpretable liability between ASD and co-occurring traits. These findings expand upon the current understanding of the complex genetics regulating ASD and reveal insights of neuronal brain disruptions potentially driving development and manifestation.

Exploration of compatibility rules and discovery of active ingredients in TCM formulas by network pharmacology

Network pharmacology is an interdisciplinary field that utilizes computer science, technology, and biological networks to investigate the intricate interplay among compounds/ingredients, targets, and diseases. Within the realm of traditional Chinese medicine (TCM), network pharmacology serves as a scientific approach to elucidate the compatibility relationships and underlying mechanisms of action in TCM formulas. It facilitates the identification of potential active ingredients within these formulas, providing a comprehensive understanding of their holistic and systematic nature, which aligns with the holistic principles inherent in TCM theory. TCM formulas exhibit complexity due to their multi-component characteristic, involving diverse targets and pathways. Consequently, investigating their material basis and mechanisms becomes challenging. Network pharmacology has emerged as a valuable approach in TCM formula research, leveraging its holistic and systematic advantages. The manuscript aims to provide an overview of the application of network pharmacology in studying TCM formula compatibility rules and explore future research directions. Specifically, we focus on how network pharmacology aids in interpreting TCM pharmacological theories and understanding formula compositions. Additionally, we elucidate the process of utilizing network pharmacology to identify active ingredients within TCM formulas. These findings not only offer novel research models and perspectives for integrating network pharmacology with TCM theory but also present new methodologies for investigating TCM formula compatibility. All in all, network pharmacology has become an indispensable and crucial tool in advancing TCM formula research.

Natural selection acting on complex traits hampers the predictive accuracy of polygenic scores in ancient samples

The prediction of phenotypes from ancient humans has gained interest due to its potential to investigate the evolution of complex traits. These predictions are commonly performed using polygenic scores computed with DNA information from ancient humans along with genome-wide association studies (GWAS) data from present-day humans. However, numerous evolutionary processes could impact the prediction of phenotypes from ancient humans based on polygenic scores. In this work we investigate how natural selection impacts phenotypic predictions on ancient individuals using polygenic scores. We use simulations of an additive trait to analyze how natural selection impacts phenotypic predictions with polygenic scores. We simulate a trait evolving under neutrality, stabilizing selection and directional selection. We find that stabilizing and directional selection have contrasting effects on ancient phenotypic predictions. Stabilizing selection accelerates the loss of large-effect alleles contributing to trait variation. Conversely, directional selection accelerates the loss of small and large-effect alleles that drive individuals farther away from the optimal phenotypic value. These effects result in specific shared genetic variation patterns between ancient and modern populations which hamper the accuracy of polygenic scores to predict phenotypes. Furthermore, we conducted simulations that include realistic strengths of stabilizing selection and heritability estimates to show how natural selection could impact the predictive accuracy of ancient polygenic scores for two widely studied traits: height and body mass index. We emphasize the importance of considering how natural selection can decrease the reliability of ancient polygenic scores to perform phenotypic predictions on an ancient population.

New insights into the dynamics of m6A epitranscriptome: hybrid-seq identifies novel mRNAs of the m6A writers METTL3/14

Background: N6-methyladenosine (m6A), a prevalent mRNA modification, is dynamically regulated by methyltransferases, including METTL3 and METTL14.Materials & methods: In the current study, we employed a custom hybrid-seq method to identify novel METTL3/14 transcripts, explore their protein-coding capacities and predict the putative role of the METTL isoforms.Results: Demultiplexing of the hybrid-seq barcoded datasets unraveled the expression patterns of the newly identified mRNAs in major malignancies as well as in non-malignant cells, providing a deeper understanding of the methylation pathways. Open reading frame query revealed novel METTL3/14 isoforms, broadening our perspective for the structural diversity within METTL family.Conclusion: Our findings offer significant insights into the intricate transcriptional landscape of METTL3/14, shedding light on the regulatory mechanisms underlying methylation in mRNAs.

Three-dimensional genome architecture persists in a 52,000-year-old woolly mammoth skin sample

Analyses of ancient DNA typically involve sequencing the surviving short oligonucleotides and aligning to genome assemblies from related, modern species. Here, we report that skin from a female woolly mammoth (†Mammuthus primigenius) that died 52,000 years ago retained its ancient genome architecture. We use PaleoHi-C to map chromatin contacts and assemble its genome, yielding 28 chromosome-length scaffolds. Chromosome territories, compartments, loops, Barr bodies, and inactive X chromosome (Xi) superdomains persist. The active and inactive genome compartments in mammoth skin more closely resemble Asian elephant skin than other elephant tissues. Our analyses uncover new biology. Differences in compartmentalization reveal genes whose transcription was potentially altered in mammoths vs. elephants. Mammoth Xi has a tetradic architecture, not bipartite like human and mouse. We hypothesize that, shortly after this mammoth's death, the sample spontaneously freeze-dried in the Siberian cold, leading to a glass transition that preserved subfossils of ancient chromosomes at nanometer scale.

Determinants of gastric cancer immune escape identified from non-coding immune-landscape quantitative trait loci

The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3' untranslated region (3'-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3'-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3'-UTR eQTLs in immune-related genes. Our approach identifies numerous 3'-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer.

Genomic language model predicts protein co-regulation and function

Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. Machine learning has shown promise in learning latent relationships underlying the sequence-structure-function paradigm from massive protein sequence datasets. However, to date, limited attempts have been made in extending this continuum to include higher order genomic context information. Evolutionary processes dictate the specificity of genomic contexts in which a gene is found across phylogenetic distances, and these emergent genomic patterns can be leveraged to uncover functional relationships between gene products. Here, we train a genomic language model (gLM) on millions of metagenomic scaffolds to learn the latent functional and regulatory relationships between genes. gLM learns contextualized protein embeddings that capture the genomic context as well as the protein sequence itself, and encode biologically meaningful and functionally relevant information (e.g. enzymatic function, taxonomy). Our analysis of the attention patterns demonstrates that gLM is learning co-regulated functional modules (i.e. operons). Our findings illustrate that gLM's unsupervised deep learning of the metagenomic corpus is an effective and promising approach to encode functional semantics and regulatory syntax of genes in their genomic contexts and uncover complex relationships between genes in a genomic region.

Cost and time-efficient construction of a 3'-end mRNA library from unpurified bulk RNA in a single tube

The major drawbacks of RNA sequencing (RNA-seq), a remarkably accurate transcriptome profiling method, is its high cost and poor scalability. Here, we report a highly scalable and cost-effective method for transcriptomics profiling called Bulk transcriptOme profiling of cell Lysate in a single poT (BOLT-seq), which is performed using unpurified bulk 3'-end mRNA in crude cell lysates. During BOLT-seq, RNA/DNA hybrids are directly subjected to tagmentation, and second-strand cDNA synthesis and RNA purification are omitted, allowing libraries to be constructed in 2 h of hands-on time. BOLT-seq was successfully used to cluster small molecule drugs based on their mechanisms of action and intended targets. BOLT-seq competes effectively with alternative library construction and transcriptome profiling methods.

An optimized workflow of full-length transcriptome sequencing for accurate fusion transcript identification

Next-generation sequencing has revolutionized cancer genomics by enabling high-throughput mutation screening yet detecting fusion genes reliably remains challenging. Long-read sequencing offers potential for accurate fusion transcript identification, though challenges persist. In this study, we present an optimized workflow using nanopore sequencing technology to precisely identify fusion transcripts. Our approach encompasses a tailored library preparation protocol, data processing, and fusion gene analysis pipeline. We evaluated the performance using Universal Human Reference RNA and human adenocarcinoma cell lines. Our optimized nanopore sequencing workflow generated high-quality full-length transcriptome data characterized by an extended length distribution and comprehensive transcript coverage. Validation experiments confirmed novel fusion events with potential clinical relevance. Our protocol aims to mitigate biases and enhance accuracy, facilitating increased adoption in clinical diagnostics. Continued advancements in long-read sequencing promise deeper insights into fusion gene biology and improved cancer diagnostics.

A comprehensive assessment of exome capture methods for RNA sequencing of formalin-fixed and paraffin-embedded samples

RNA-Seq analysis of Formalin-Fixed and Paraffin-Embedded (FFPE) samples has emerged as a highly effective approach and is increasingly being used in clinical research and drug development. However, the processing and storage of FFPE samples are known to cause extensive degradation of RNAs, which limits the discovery of gene expression or gene fusion-based biomarkers using RNA sequencing, particularly methods reliant on Poly(A) enrichment. Recently, researchers have developed an exome targeted RNA-Seq methodology that utilizes biotinylated oligonucleotide probes to enrich RNA transcripts of interest, which could overcome these limitations. Nevertheless, the standardization of this experimental framework, including probe designs, sample multiplexing, sequencing read length, and bioinformatic pipelines, remains an essential requirement. In this study, we conducted a comprehensive comparison of three main commercially available exome capture kits and evaluated key experimental parameters, to provide the overview of the advantages and limitations associated with the selection of library preparation protocols and sequencing platforms. The results provide valuable insights into the best practices for obtaining high-quality data from FFPE samples.

Different elongation factors distinctly modulate RNA polymerase II transcription in Arabidopsis

Various transcript elongation factors (TEFs) including modulators of RNA polymerase II (RNAPII) activity and histone chaperones tune the efficiency of transcription in the chromatin context. TEFs are involved in establishing gene expression patterns during growth and development in Arabidopsis, while little is known about the genomic distribution of the TEFs and the way they facilitate transcription. We have mapped the genome-wide occupancy of the elongation factors SPT4-SPT5, PAF1C and FACT, relative to that of elongating RNAPII phosphorylated at residues S2/S5 within the carboxyterminal domain. The distribution of SPT4-SPT5 along transcribed regions closely resembles that of RNAPII-S2P, while the occupancy of FACT and PAF1C is rather related to that of RNAPII-S5P. Under transcriptionally challenging heat stress conditions, mutant plants lacking the corresponding TEFs are differentially impaired in transcript synthesis. Strikingly, in plants deficient in PAF1C, defects in transcription across intron/exon borders are observed that are cumulative along transcribed regions. Upstream of transcriptional start sites, the presence of FACT correlates with nucleosomal occupancy. Under stress conditions FACT is particularly required for transcriptional upregulation and to promote RNAPII transcription through +1 nucleosomes. Thus, Arabidopsis TEFs are differently distributed along transcribed regions, and are distinctly required during transcript elongation especially upon transcriptional reprogramming.

Interplays between cis- and trans-Acting Factors for Alternative Splicing in Response to Environmental Changes during Biological Invasions of Ascidians

Alternative splicing (AS), a pivotal biological process contributing to phenotypic plasticity, creates a bridge linking genotypes with phenotypes. Despite its importance, the AS mechanisms underlying environmental response and adaptation have not been well studied, and more importantly, the cis- and trans-acting factors influencing AS variation remain unclear. Using the model invasive congeneric ascidians, Ciona robusta, and Ciona savignyi, we compared their AS responses to environmental changes and explored the potential determinants. Our findings unveiled swift and dynamic AS changes in response to environmental challenges, and differentially alternative spliced genes (DASGs) were functionally enriched in transmembrane transport processes. Interestingly, both the prevalence and level of AS in C. robusta were lower than those observed in C. savignyi. Furthermore, these two indices were higher under temperature stresses compared to salinity stresses in C. savignyi. All the observed patterns underscore the species-specific and environmental context-dependent AS responses to environmental challenges. The dissimilarities in genomic structure and exon/intron size distributions between these two species likely contributed to the observed AS variation. Moreover, we identified a total of 11 and 9 serine/arginine-rich splicing factors (SRSFs) with conserved domains and gene structures in the genomes of C. robusta and C. savignyi, respectively. Intriguingly, our analysis revealed that all detected SRSFs did not exhibit prevalent AS regulations. Instead, we observed AS control over a set of genes related to splicing factors and spliceosome components. Altogether, our results elucidate species-specific and environmental challenge-dependent AS response patterns in closely related invasive ascidians. The identified splicing factors and spliceosome components under AS control offer promising candidates for further investigations into AS-mediated rapid responses to environmental challenges complementary to SRSFs.

Uncovering the effect of RNA polymerase steric interactions on gene expression noise: Analytical distributions of nascent and mature RNA numbers

The telegraph model is the standard model of stochastic gene expression, which can be solved exactly to obtain the distribution of mature RNA numbers per cell. A modification of this model also leads to an analytical distribution of nascent RNA numbers. These solutions are routinely used for the analysis of single-cell data, including the inference of transcriptional parameters. However, these models neglect important mechanistic features of transcription elongation, such as the stochastic movement of RNA polymerases and their steric (excluded-volume) interactions. Here we construct a model of gene expression describing promoter switching between inactive and active states, binding of RNA polymerases in the active state, their stochastic movement including steric interactions along the gene, and their unbinding leading to a mature transcript that subsequently decays. We derive the steady-state distributions of the nascent and mature RNA numbers in two important limiting cases: constitutive expression and slow promoter switching. We show that RNA fluctuations are suppressed by steric interactions between RNA polymerases, and that this suppression can in some instances even lead to sub-Poissonian fluctuations; these effects are most pronounced for nascent RNA and less prominent for mature RNA, since the latter is not a direct sensor of transcription. We find a relationship between the parameters of our microscopic mechanistic model and those of the standard models that ensures excellent consistency in their prediction of the first and second RNA number moments over vast regions of parameter space, encompassing slow, intermediate, and rapid promoter switching, provided the RNA number distributions are Poissonian or super-Poissonian. Furthermore, we identify the limitations of inference from mature RNA data, specifically showing that it cannot differentiate between highly distinct RNA polymerase traffic patterns on a gene.

Familial and genetic association with neurodevelopmental disorders caused by a heterozygous variant in the SRRM2 gene

Background

Neurodevelopmental disorders (NDDs) are a class of disorders affecting brain development and function, characterized by an inability to reach cognitive, emotional, and motor developmental milestones. The pathology of NDDs is complex. A recent study found that variants in the SRRM2 gene cause NDDs. However, genetic conditions play the most important role in the etiology of NDD. The genetic causes of NDD are extremely heterogeneous, leading to certain challenges in clinical diagnosis.

Methods

A pregnant woman with congenital intelligence disorder came to our hospital for genetic diagnosis to predict the status of her fetus. Her mother and a brother also suffer from congenital intelligence disorder. She has a daughter with speech delay. Whole exome sequencing was used to identify a mutation (c.1415C>G) in the SRRM2 gene of this family that resulted in a change in the 472nd amino acid residue of the SRRM2 protein from serine to terminated.

Conclusion

We report a family with an autosomal dominant genetic disorder caused by variants in the SRRM2 gene causing NDDs. Prenatal diagnosis can help patients with this genetic disorder to have healthy offspring.

The Material Properties of the Cell Nucleus: A Matter of Scale

Chromatin regulatory processes physically take place in the environment of the cell nucleus, which is filled with the chromosomes and a plethora of smaller biomolecules. The nucleus contains macromolecular assemblies of different sizes, from nanometer-sized protein complexes to micrometer-sized biomolecular condensates, chromosome territories, and nuclear bodies. This multiscale organization impacts the transport processes within the nuclear interior, the global mechanical properties of the nucleus, and the way the nucleus senses and reacts to mechanical stimuli. Here, we discuss recent work on these aspects, including microrheology and micromanipulation experiments assessing the material properties of the nucleus and its subcomponents. We summarize how the properties of multiscale media depend on the time and length scales probed in the experiment, and we reconcile seemingly contradictory observations made on different scales. We also revisit the concept of liquid-like and solid-like material properties for complex media such as the nucleus. We propose that the nucleus can be considered a multiscale viscoelastic medium composed of three major components with distinct properties: the lamina, the chromatin network, and the nucleoplasmic fluid. This multicomponent organization enables the nucleus to serve its different functions as a reaction medium on the nanoscale and as a mechanosensor and structural scaffold on the microscale.

Gene therapy for Duchenne muscular dystrophy: an update on the latest clinical developments

INTRODUCTION

Duchenne muscular dystrophy (DMD) is one of the most severe and devastating neuromuscular hereditary diseases with a male newborn incidence of 20 000 cases each year. The disease caused by mutations (exon deletions, nonsense mutations, intra-exonic insertions or deletions, exon duplications, splice site defects, and deep intronic mutations) in the DMD gene, progressively leads to muscle wasting and loss of ambulation. This situation is painful for both patients and their families, calling for an emergent need for effective treatments.

AREAS COVERED

In this review, the authors describe the state of the gene therapy approach in clinical trials for DMD. This therapeutics included gene replacement, gene substitution, RNA-based therapeutics, readthrough mutation, and the CRISPR approach.

EXPERT OPINION

Only a few drug candidates have yet been granted conditional approval for the treatment of DMD. Most of these therapies have only a modest capability to restore the dystrophin or improve muscle function, suggesting an important unmet need in the development of DMD therapeutics. Complementary genes and cellular therapeutics need to be explored to both restore dystrophin, improve muscle function, and efficiently reconstitute the muscle fibers in the advanced stage of the disease.

Alternative Splicing, RNA Editing, and the Current Limits of Next Generation Sequencing

The advent of next generation sequencing (NGS) has fostered a shift in basic analytic strategies of a gene expression analysis in diverse pathologies for the purposes of research, pharmacology, and personalized medicine. What was once highly focused research on individual signaling pathways or pathway members has, from the time of gene expression arrays, become a global analysis of gene expression that has aided in identifying novel pathway interactions, the discovery of new therapeutic targets, and the establishment of disease-associated profiles for assessing progression, stratification, or a therapeutic response. But there are significant caveats to this analysis that do not allow for the construction of the full picture. The lack of timely updates to publicly available databases and the "hit and miss" deposition of scientific data to these databases relegate a large amount of potentially important data to "garbage", begging the question, "how much are we really missing?" This brief perspective aims to highlight some of the limitations that RNA binding/modifying proteins and RNA processing impose on our current usage of NGS technologies as relating to cancer and how not fully appreciating the limitations of current NGS technology may negatively affect therapeutic strategies in the long run.

Theory of chromatin organization maintained by active loop extrusion

The active loop extrusion hypothesis proposes that chromatin threads through the cohesin protein complex into progressively larger loops until reaching specific boundary elements. We build upon this hypothesis and develop an analytical theory for active loop extrusion which predicts that loop formation probability is a nonmonotonic function of loop length and describes chromatin contact probabilities. We validate our model with Monte Carlo and hybrid Molecular Dynamics-Monte Carlo simulations and demonstrate that our theory recapitulates experimental chromatin conformation capture data. Our results support active loop extrusion as a mechanism for chromatin organization and provide an analytical description of chromatin organization that may be used to specifically modify chromatin contact probabilities.

Prime editing strategies to mediate exon skipping in DMD gene

Duchenne muscular dystrophy is a rare and lethal hereditary disease responsible for progressive muscle wasting due to mutations in the DMD gene. We used the CRISPR-Cas9 Prime editing technology to develop different strategies to correct frameshift mutations in DMD gene carrying the deletion of exon 52 or exons 45 to 52. With optimized epegRNAs, we were able to induce the specific substitution of the GT nucleotides of the splice donor site of exon 53 in up to 32% of HEK293T cells and 28% of patient myoblasts. We also achieved up to 44% and 29% deletion of the G nucleotide of the GT splice site of exon 53, as well as inserted 17% and 5.5% GGG between the GT splice donor site of exon 51 in HEK293T cells and human myoblasts, respectively. The modification of the splice donor site for exon 51 and exon 53 provoke their skipping and allowed exon 50 to connect to exon 53 and allowed exon 44 to connect to exon 54, respectively. These corrections restored the expression of dystrophin as demonstrated by western blot. Thus, Prime editing was used to induce specific substitutions, insertions and deletions in the splice donor sites for exons 51 and 53 to correct the frameshift mutations in DMD gene carrying deletions of exon 52 and exons 45 to 52, respectively.

mRNA recognition and packaging by the human transcription-export complex

Newly made mRNAs are processed and packaged into mature ribonucleoprotein complexes (mRNPs) and are recognized by the essential transcription-export complex (TREX) for nuclear export1,2. However, the mechanisms of mRNP recognition and three-dimensional mRNP organization are poorly understood3. Here we report cryo-electron microscopy and tomography structures of reconstituted and endogenous human mRNPs bound to the 2-MDa TREX complex. We show that mRNPs are recognized through multivalent interactions between the TREX subunit ALYREF and mRNP-bound exon junction complexes. Exon junction complexes can multimerize through ALYREF, which suggests a mechanism for mRNP organization. Endogenous mRNPs form compact globules that are coated by multiple TREX complexes. These results reveal how TREX may simultaneously recognize, compact and protect mRNAs to promote their packaging for nuclear export. The organization of mRNP globules provides a framework to understand how mRNP architecture facilitates mRNA biogenesis and export.

The sound of silence: mechanisms and implications of HUSH complex function

The vertebrate genome is under constant threat of invasion by genetic parasites. Whether the host can immediately recognize and respond to invading elements has been unclear. The discovery of the human silencing hub (HUSH) complex, and the finding that it provides immediate protection from genome invasion by silencing products of reverse transcription, have important implications for mammalian genome evolution. In this review, we summarize recent insights into HUSH function and describe how cellular introns provide a novel means of self-nonself discrimination, allowing HUSH to recognize and transcriptionally repress a broad range of intronless genetic elements. We discuss how HUSH contributes to genome evolution, and highlight studies reporting the critical role of HUSH in development and implicating HUSH in the control of immune signaling and cancer progression.

Polymorphism of glutathione S-transferase P1 of dogs with mammary tumours

Mammary tumours constitute more than half of neoplasms in female dogs from different countries. Genome sequences are associated with cancer susceptibility but there is little information available about genetic polymorphisms of glutathione S-transferase P1 (GSTP1) in canine cancers. The aim of this study was to find single nucleotide polymorphisms (SNPs) in GSTP1 of dogs (Canis lupus familiaris) with mammary tumours compared to healthy dogs and to determine the association between GSTP1 polymorphisms and the occurrence of these tumours. The study population included 36 client-owned female dogs with mammary tumours and 12 healthy female dogs, with no previous diagnosis of cancer. DNA was extracted from blood and amplified by PCR assay. PCR-products were sequenced by Sanger method and analysed manually. The 33 polymorphisms were found in GSTP1: 1 coding SNP (exon 4), 24 non-coding SNPs (9 in exon 1), 7 deletions and 1 insertion. The 17 polymorphisms have been found in introns 1, 4, 5 and 6. The dogs with mammary tumours have significant difference from healthy in SNPs I4 c.1018 + 123 T > C (OR 13.412, 95%CI 1.574-114.267, P = .001), I5 c.1487 + 27 T > C (OR 10.737, 95%CI 1.260-91.477, P = .004), I5 c.1487 + 842 G > C (OR 4.714, 95% CI 1.086-20.472, P = .046) and I6 c.2481 + 50 A > G (OR 12.000, 95% CI 1.409-102.207, P = .002). SNP E5 c.1487 T > C and I5 c.1487 + 829 delG also differed significantly (P = .03) but not to the confidence interval. The study, for the first time, showed a positive association of SNPs in GSTP1 with mammary tumours of dogs, that can possibly be used to predict the occurrence of this pathology.

Profiling lariat intermediates reveals genetic determinants of early and late co-transcriptional splicing

Long introns with short exons in vertebrate genes are thought to require spliceosome assembly across exons (exon definition), rather than introns, thereby requiring transcription of an exon to splice an upstream intron. Here, we developed CoLa-seq (co-transcriptional lariat sequencing) to investigate the timing and determinants of co-transcriptional splicing genome wide. Unexpectedly, 90% of all introns, including long introns, can splice before transcription of a downstream exon, indicating that exon definition is not obligatory for most human introns. Still, splicing timing varies dramatically across introns, and various genetic elements determine this variation. Strong U2AF2 binding to the polypyrimidine tract predicts early splicing, explaining exon definition-independent splicing. Together, our findings question the essentiality of exon definition and reveal features beyond intron and exon length that are determinative for splicing timing.

Integrative omics indicate FMRP sequesters mRNA from translation and deadenylation in human neuronal cells

How fragile X syndrome protein (FMRP) binds mRNAs and regulates mRNA metabolism remains unclear. Our previous work using human neuronal cells focused on mRNAs targeted for nonsense-mediated mRNA decay (NMD), which we showed are generally bound by FMRP and destabilized upon FMRP loss. Here, we identify >400 high-confidence FMRP-bound mRNAs, only ∼35% of which are NMD targets. Integrative transcriptomics together with SILAC-LC-MS/MS reveal that FMRP loss generally results in mRNA destabilization and more protein produced per FMRP target. We use our established RIP-seq technology to show that FMRP footprints are independent of protein-coding potential, target GC-rich and structured sequences, and are densest in 5' UTRs. Regardless of where within an mRNA FMRP binds, we find that FMRP protects mRNAs from deadenylation and directly binds the cytoplasmic poly(A)-binding protein. Our results reveal how FMRP sequesters polyadenylated mRNAs into stabilized and translationally repressed complexes, whose regulation is critical for neurogenesis and synaptic plasticity.

Prime editing optimized RTT permits the correction of the c.8713C>T mutation in DMD gene

Duchenne muscular dystrophy is a severe debilitating genetic disease caused by different mutations in the DMD gene leading to the absence of dystrophin protein under the sarcolemma. We used CRISPR-Cas9 prime editing technology for correction of the c.8713C>T mutation in the DMD gene and tested different variations of reverse transcription template (RTT) sequences. We increased by 3.8-fold the editing percentage of the target nucleotide located at +13. A modification of the protospacer adjacent motif sequence (located at +6) and a silent mutation (located at +9) were also simultaneously added to the target sequence modification. We observed significant differences in editing efficiency in interconversion of different nucleotides and the distance between the target, the nicking site, and the additional mutations. We achieved 22% modifications in myoblasts of a DMD patient, which led to dystrophin expression detected by western blot in the myotubes that they formed. RTT optimization permitted us to improve the prime editing of a point mutation located at +13 nucleotides from the nick site to restore dystrophin protein.

Identification of qPCR reference genes suitable for normalising gene expression in the developing mouse embryo

Background: Progression through mammalian embryogenesis involves many interacting cell types and multiple differentiating cell lineages. Quantitative polymerase chain reaction (qPCR) analysis of gene expression in the developing embryo is a valuable tool for deciphering these processes, but normalisation to stably-expressed reference genes is essential for such analyses. Gene expression patterns change globally and dramatically as embryonic development proceeds, rendering identification of consistently appropriate reference genes challenging. Methods: We have investigated expression stability in mouse embryos from mid to late gestation (E11.5-E18.5), both at the whole-embryo level, and within the head and forelimb specifically, using 15 candidate reference genes ( ACTB, 18S, SDHA, GAPDH, HTATSF1, CDC40, RPL13A, CSNK2A2, AP3D1, HPRT1, CYC1, EIF4A, UBC, B2M and PAK1IP1), and four complementary algorithms (geNorm, Normfinder, Bestkeeper and deltaCt). Results: Unexpectedly, all methods suggest that many genes within our candidate panel are acceptable references, though AP3D1, RPL13A and PAK1IP1 are the strongest performing genes overall (scoring highly in whole embryos, heads or forelimbs alone, and in all samples collectively). HPRT1 and B2M are conversely poor choices, and show strong developmental regulation. We further show that normalisation using our three highest-scoring references can reveal subtle patterns of developmental expression even in genes ostensibly ranked as acceptably stable ( CDC40, HTATSF1). Conclusion: AP3D1, RPL13A and PAK1IP1 represent universally suitable reference genes for expression studies in the E11.5-E18.5 mouse embryo.

Identification of qPCR reference genes suitable for normalising gene expression in the developing mouse embryo

Background: Progression through mammalian embryogenesis involves many interacting cell types and multiple differentiating cell lineages. Quantitative polymerase chain reaction (qPCR) analysis of gene expression in the developing embryo is a valuable tool for deciphering these processes, but normalisation to stably-expressed reference genes is essential for such analyses. Gene expression patterns change globally and dramatically as embryonic development proceeds, rendering identification of consistently appropriate reference genes challenging.

Methods: We have investigated expression stability in mouse embryos from mid to late gestation (E11.5–E18.5), both at the whole-embryo level, and within the head and forelimb specifically, using 15 candidate reference genes ( ACTB, 18S, SDHA, GAPDH, HTATSF1, CDC40, RPL13A, CSNK2A2, AP3D1, HPRT1, CYC1, EIF4A, UBC, B2M and PAK1IP1), and four complementary algorithms (geNorm, Normfinder, Bestkeeper and deltaCt).

Results: Unexpectedly, all methods suggest that many genes within our candidate panel are acceptable references, though AP3D1, RPL13A and PAK1IP1 are the strongest performing genes overall (scoring highly in whole embryos, heads or forelimbs alone, and in all samples collectively). HPRT1 and B2M are conversely poor choices, and show strong developmental regulation. We further show that normalisation using our three highest-scoring references can reveal subtle patterns of developmental expression even in genes ostensibly ranked as acceptably stable ( CDC40, HTATSF1).

Conclusion: AP3D1, RPL13A and PAK1IP1 represent universally suitable reference genes for expression studies in the E11.5-E18.5 mouse embryo.

Delivering the Promise of Gene Therapy with Nanomedicines in Treating Central Nervous System Diseases

Central Nervous System (CNS) diseases, such as Alzheimer's diseases (AD), Parkinson's Diseases (PD), brain tumors, Huntington's disease (HD), and stroke, still remain difficult to treat by the conventional molecular drugs. In recent years, various gene therapies have come into the spotlight as versatile therapeutics providing the potential to prevent and treat these diseases. Despite the significant progress that has undoubtedly been achieved in terms of the design and modification of genetic modulators with desired potency and minimized unwanted immune responses, the efficient and safe in vivo delivery of gene therapies still poses major translational challenges. Various non-viral nanomedicines have been recently explored to circumvent this limitation. In this review, an overview of gene therapies for CNS diseases is provided and describes recent advances in the development of nanomedicines, including their unique characteristics, chemical modifications, bioconjugations, and the specific applications that those nanomedicines are harnessed to deliver gene therapies.

Using total RNA quality metrics for time since deposition estimates in degrading bloodstains

The physicochemical changes occurring in biomolecules in degrading bloodstains can be used to approximate the time since deposition (TSD) of bloodstains. This would provide forensic scientists with critical information regarding the timeline of the events involving bloodshed. Our study aims to quantify the timewise degradation trends and temperature dependence found in total RNA from bloodstains without the use of amplification, expanding the scope of the RNA TSD research which has traditionally targeted mRNA and miRNA. Bovine blood with ACD-A anticoagulant was deposited and stored in plastic microcentrifuge tubes at 21 or 4°C and tested over different timepoints spanning 1 week. Total RNA was extracted from each sample and analyzed using automated high sensitivity gel electrophoresis. Nine RNA metrics were visually assessed and quantified using linear and mixed models. The RNA Integrity Number equivalent (RINe) and DV200 were not influenced by the addition of anticoagulant and demonstrated strong negative trends over time. The RINe model fit was high (R²  = 0.60), and while including the biological replicate as a random effect increased the fit for all RNA metrics, no significant differences were found between biological replicates stored at the same temperature for the RINe and DV200. This suggests that these standardized metrics can be directly compared between scenarios and individuals, with DV200 having an inflection point at approximately 28 h. This study provides a novel approach for blood TSD research, revealing metrics that are not affected by inter-individual variation, and improving our understanding of the rapid RNA degradation occurring in bloodstains.

An Optimized Direct Lysis Gene Expression Microplate Assay and Applications for Disease, Differentiation, and Pharmacological Cell-Based Studies

Routine cell culture reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) gene expression analysis is limited in scalability due to minimum sample requirement and multistep isolation procedures. In this study, we aimed to optimize and apply a cost-effective and rapid protocol for directly sampling gene expression data from microplate cell cultures. The optimized protocol involves direct lysis of microplate well population followed by a reduced thermocycler reaction time one-step RT-qPCR assay. In applications for inflammation and stress-induced cell-based models, the direct lysis RT-qPCR microplate assay was utilized to detect IFN1 and PPP1R15A expression by poly(I:C) treated primary fibroblast cultures, IL6 expression by poly(I:C) iPSC-derived astrocytes, and differential PPP1R15A expression by ER-stressed vanishing white-matter disease patient induced pluripotent stem cell (iPSC)-derived astrocytes. In application for neural differentiation medium recipe optimizations, conditions were screened for SYN1 and VGLUT1 in neuronal cultures, and S100B, GFAP and EAAT1 in astrocyte cultures. The protocol provides microplate gene expression results from cell lysate to readout within ~35 min, with comparable cost to routine RT-qPCR, and it may be utilized to support laboratory cell-based assays in basic and applied scientific and medical fields of research including stem-cell differentiation, cell physiology, and drug mechanism studies.

Detection of Chimeric Cellular: HIV mRNAs Generated Through Aberrant Splicing in HIV-1 Latently Infected Resting CD4+ T Cells

Latent HIV-1 provirus in infected individuals on suppressive therapy does not always remain transcriptionally silent. Both HIV-1 LTR and human gene promoter derived transcriptional events can contribute HIV-1 sequences to the mRNA produced in the cell. In addition, chimeric cellular:HIV mRNA can arise through readthrough transcription and aberrant splicing. Using target enrichment coupled to the Illumina Mi-Seq and PacBio RS II platforms, we show that 3’ LTR activation is frequent in latently infected cells from both the CCL19-induced primary cell model of HIV-1 latency as well as ex vivo samples. In both systems of latent HIV-1 infection, we detected several chimeric species that were generated via activation of a cryptic splice donor site in the 5’ LTR of HIV-1. Aberrant splicing involving the major HIV-1 splice donor sites, SD1 and SD4 disrupts post-transcriptional processing of the gene in which HIV-1 is integrated. In the primary cell model of HIV-1 latency, Tat-encoding sequences are incorporated into the chimeric mRNA transcripts through the use of SD4. Our study unravels clues to the characteristics of HIV-1 integrants that promote formation of chimeric cellular:HIV mRNA and improves the understanding of the HIV-1 RNA footprint in latently infected cells.

Therapeutic Strategies for Dystrophin Replacement in Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is an X-linked hereditary disease characterized by progressive muscle wasting due to modifications in the DMD gene (exon deletions, nonsense mutations, intra-exonic insertions or deletions, exon duplications, splice site defects, and deep intronic mutations) that result in a lack of functional dystrophin expression. Many therapeutic approaches have so far been attempted to induce dystrophin expression and improve the patient phenotype. In this manuscript, we describe the relevant updates for some therapeutic strategies for DMD aiming to restore dystrophin expression. We also present and analyze in vitro and in vivo ongoing experimental approaches to treat the disease.

MicroRNAs and their delivery in diabetic fibrosis

The global prevalence of diabetes mellitus was estimated to be 463 million people in 2019 and is predicted to rise to 700 million by 2045. The associated financial and societal costs of this burgeoning epidemic demand an understanding of the pathology of this disease, and its complications, that will inform treatment to enable improved patient outcomes. Nearly two decades after the sequencing of the human genome, the significance of noncoding RNA expression is still being assessed. The family of functional noncoding RNAs known as microRNAs regulates the expression of most genes encoded by the human genome. Altered microRNA expression profiles have been observed both in diabetes and in diabetic complications. These transcripts therefore have significant potential and novelty as targets for therapy, therapeutic agents and biomarkers.

Alternative Splicing and Isoforms: From Mechanisms to Diseases

Alternative splicing of pre-mRNA is a key mechanism for increasing the complexity of proteins in humans, causing a diversity of expression of transcriptomes and proteomes in a tissue-specific manner. Alternative splicing is regulated by a variety of splicing factors. However, the changes and errors of splicing regulation caused by splicing factors are strongly related to many diseases, something which represents one of this study’s main interests. Further understanding of alternative splicing regulation mediated by cellular factors is also a prospective choice to develop specific drugs for targeting the dynamic RNA splicing process. In this review, we firstly concluded the basic principle of alternative splicing. Afterwards, we showed how splicing isoforms affect physiological activities through specific disease examples. Finally, the available treatment methods relative to adjusting splicing activities have been summarized.

Characterization of transcript enrichment and detection bias in single-nucleus RNA-seq for mapping of distinct human adipocyte lineages

Single-cell RNA sequencing (scRNA-seq) enables molecular characterization of complex biological tissues at high resolution. The requirement of single-cell extraction, however, makes it challenging for profiling tissues such as adipose tissue, for which collection of intact single adipocytes is complicated by their fragile nature. For such tissues, single-nucleus extraction is often much more efficient and therefore single-nucleus RNA sequencing (snRNA-seq) presents an alternative to scRNA-seq. However, nuclear transcripts represent only a fraction of the transcriptome in a single cell, with snRNA-seq marked with inherent transcript enrichment and detection biases. Therefore, snRNA-seq may be inadequate for mapping important transcriptional signatures in adipose tissue. In this study, we compare the transcriptomic landscape of single nuclei isolated from preadipocytes and mature adipocytes across human white and brown adipocyte lineages, with whole-cell transcriptome. We show that snRNA-seq is capable of identifying the broad cell types present in scRNA-seq at all states of adipogenesis. However, we also explore how and why the nuclear transcriptome is biased and limited, as well as how it can be advantageous. We robustly characterize the enrichment of nuclear-localized transcripts and adipogenic regulatory lncRNAs in snRNA-seq, while also providing a detailed understanding for the preferential detection of long genes upon using this technique. To remove such technical detection biases, we propose a normalization strategy for a more accurate comparison of nuclear and cellular data. Finally, we show successful integration of scRNA-seq and snRNA-seq data sets with existing bioinformatic tools. Overall, our results illustrate the applicability of snRNA-seq for the characterization of cellular diversity in the adipose tissue.

Mapping of Nonhomologous End Joining-Mediated Integration Facilitates Genome-Scale Trackable Mutagenesis in Yarrowia lipolytica

Genome-scale mutagenesis, phenotypic screening, and tracking the causal mutations is a powerful approach for genetic analysis. However, classic mutagenesis approaches require extensive effort to identify causal mutations. It is desirable to demonstrate a powerful approach for rapid trackable mutagenesis. Here, we mapped the distribution of nonhomologous end joining (NHEJ)-mediated integration for the first time and demonstrated that it can be used for constructing the genome-scale trackable mutagenesis library in Yarrowia lipolytica. The sequencing of 9.15 × 10⁵ insertions showed that NHEJ-mediated integration inserted DNA randomly across the chromosomes, and the transcriptional regulatory regions exhibited integration preference. The insertions were located in both nucleosome-occupancy regions and nucleosome-free regions. Using NHEJ-mediated integration to construct the genome-scale mutagenesis library, the new targets that improved β-carotene biosynthesis and acetic acid tolerance were identified rapidly. This mutagenesis approach is readily applicable to other organisms with strong NHEJ preference and will contribute to cell factory construction.

Transcription-Replication Coordination

Transcription and replication are the two most essential processes that a cell does with its DNA: they allow cells to express the genomic content that is required for their functions and to create a perfect copy of this genomic information to pass on to the daughter cells. Nevertheless, these two processes are in a constant ambivalent relationship. When transcription and replication occupy the same regions, there is the possibility of conflicts between transcription and replication as transcription can impair DNA replication progression leading to increased DNA damage. Nevertheless, DNA replication origins are preferentially located in open chromatin next to actively transcribed regions, meaning that the possibility of conflicts is potentially an accepted incident for cells. Data in the literature point both towards the existence or not of coordination between these two processes to avoid the danger of collisions. Several reviews have been published on transcription-replication conflicts, but we focus here on the most recent findings that relate to how these two processes are coordinated in eukaryotes, considering advantages and disadvantages from coordination, how likely conflicts are at any given time, and which are their potential hotspots in the genome.

Splice site proximity influences alternative exon definition

Alternative splicing enables higher eukaryotes to expand mRNA diversity from a finite number of genes through highly combinatorial splice site selection mechanisms that are influenced by the sequence of competing splice sites, cis-regulatory elements binding trans-acting factors, the length of exons and introns harbouring alternative splice sites and RNA secondary structures at putative splice junctions. To test the hypothesis that the intron definition or exon definition modes of splice site recognition direct the selection of alternative splice patterns, we created a database of alternative splice site usage (ALTssDB). When alternative splice sites are embedded within short introns (intron definition), the 5' and 3' splice sites closest to each other across the intron preferentially pair, consistent with previous observations. However, when alternative splice sites are embedded within large flanking introns (exon definition), the 5' and 3' splice sites closest to each other across the exon are preferentially selected. Thus, alternative splicing decisions are influenced by the intron and exon definition modes of splice site recognition. The results demonstrate that the spliceosome pairs splice sites that are closest in proximity within the unit of initial splice site selection.

Genome surveillance by HUSH-mediated silencing of intronless mobile elements

All life forms defend their genome against DNA invasion. Eukaryotic cells recognize incoming DNA and limit its transcription through repressive chromatin modifications. The human silencing hub (HUSH) complex transcriptionally represses long interspersed element-1 retrotransposons (L1s) and retroviruses through histone H3 lysine 9 trimethylation (H3K9me3)1-3. How HUSH recognizes and initiates silencing of these invading genetic elements is unknown. Here we show that HUSH is able to recognize and transcriptionally repress a broad range of long, intronless transgenes. Intron insertion into HUSH-repressed transgenes counteracts repression, even in the absence of intron splicing. HUSH binds transcripts from the target locus, prior to and independent of H3K9me3 deposition, and target transcription is essential for both initiation and propagation of HUSH-mediated H3K9me3. Genomic data reveal how HUSH binds and represses a subset of endogenous intronless genes generated through retrotransposition of cellular mRNAs. Thus intronless cDNA-the hallmark of reverse transcription-provides a versatile way to distinguish invading retroelements from host genes and enables HUSH to protect the genome from 'non-self' DNA, despite there being no previous exposure to the invading element. Our findings reveal the existence of a transcription-dependent genome-surveillance system and explain how it provides immediate protection against newly acquired elements while avoiding inappropriate repression of host genes.

An RNA-Based Theory of Natural Universal Computation

Life is confronted with computation problems in a variety of domains including animal behavior, single-cell behavior, and embryonic development. Yet we currently do not know of a naturally existing biological system that is capable of universal computation, i.e., Turing-equivalent in scope. Generic finite-dimensional dynamical systems (which encompass most models of neural networks, intracellular signaling cascades, and gene regulatory networks) fall short of universal computation, but are assumed to be capable of explaining cognition and development. I present a class of models that bridge two concepts from distant fields: combinatory logic (or, equivalently, lambda calculus) and RNA molecular biology. A set of basic RNA editing rules can make it possible to compute any computable function with identical algorithmic complexity to that of Turing machines. The models do not assume extraordinarily complex molecular machinery or any processes that radically differ from what we already know to occur in cells. Distinct independent enzymes can mediate each of the rules and RNA molecules solve the problem of parenthesis matching through their secondary structure. In the most plausible of these models all of the editing rules can be implemented with merely cleavage and ligation operations at fixed positions relative to predefined motifs. This demonstrates that universal computation is well within the reach of molecular biology. It is therefore reasonable to assume that life has evolved - or possibly began with - a universal computer that yet remains to be discovered. The variety of seemingly unrelated computational problems across many scales can potentially be solved using the same RNA-based computation system. Experimental validation of this theory may immensely impact our understanding of memory, cognition, development, disease, evolution, and the early stages of life.

Structural Characterization of the Highly Restricted Down Syndrome Critical Region on 21q22.13: New KCNJ6 and DSCR4 Transcript Isoforms

Down syndrome (DS) is caused by trisomy of chromosome 21 and it is the most common genetic cause of intellectual disability (ID) in humans. Subjects with DS show a typical phenotype marked by facial dysmorphisms and ID. Partial trisomy 21 (PT21) is a rare genotype characterized by the duplication of a delimited chromosome 21 (Hsa21) portion and it may or may not be associated with DS diagnosis. The highly restricted Down syndrome critical region (HR-DSCR) is a region of Hsa21 present in three copies in all individuals with PT21 and a diagnosis of DS. This region, located on distal 21q22.13, is 34 kbp long and does not include characterized genes. The HR-DSCR is annotated as an intergenic region between KCNJ6-201 transcript encoding for potassium inwardly rectifying channel subfamily J member 6 and DSCR4-201 transcript encoding Down syndrome critical region 4. Two transcripts recently identified by massive RNA-sequencing (RNA-Seq) and automatically annotated on Ensembl database reveal that the HR-DSCR seems to be partially crossed by KCNJ6-202 and DSCR4-202 isoforms. KCNJ6-202 shares the coding sequence with KCNJ6-201 which is involved in many physiological processes, including heart rate in cardiac cells and circuit activity in neuronal cells. DSCR4-202 transcript has the first two exons in common with DSCR4-201, the only experimentally verified gene uniquely present in Hominidae. In this study, we performed in silico and in vitro analyses of the HR-DSCR. Bioinformatic data, obtained using Sequence Read Archive (SRA) and SRA-BLAST software, were confirmed by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and Sanger sequencing on a panel of human tissues. Our data demonstrate that the HR-DSCR cannot be defined as an intergenic region. Further studies are needed to investigate the functional role of the new transcripts, likely involved in DS phenotypes.

The infinite possibilities of RNA therapeutics

Although the study of ribonucleic acid (RNA) therapeutics started decades ago, for many years, this field of research was overshadowed by the growing interest in DNA-based therapies. Nowadays, the role of several types of RNA in cell regulation processes and the development of various diseases have been elucidated, and research in RNA therapeutics is back with force. This short literature review aims to present general aspects of many of the molecules currently used in RNA therapeutics, including in vitro transcribed mRNA (IVT mRNA), antisense oligonucleotides (ASOs), aptamers, small interfering RNAs (siRNAs), and microRNAs (miRNAs). In addition, we describe the state of the art of technologies applied for synthetic RNA manufacture and delivery. Likewise, we detail the RNA-based therapies approved by the FDA so far, as well as the ongoing clinical investigations. As a final point, we highlight the current and potential advantages of working on RNA-based therapeutics and how these could lead to a new era of accessible and personalized healthcare.

Deficiency of the Ribosomal Protein uL5 Leads to Significant Rearrangements of the Transcriptional and Translational Landscapes in Mammalian Cells

Protein uL5 (formerly called L11) is an integral component of the large (60S) subunit of the human ribosome, and its deficiency in cells leads to the impaired biogenesis of 60S subunits. Using RNA interference, we reduced the level of uL5 in HEK293T cells by three times, which caused an almost proportional decrease in the content of the fraction corresponding to 80S ribosomes, without a noticeable diminution in the level of polysomes. By RNA sequencing of uL5-deficient and control cell samples, which were those of total mRNA and mRNA from the polysome fraction, we identified hundreds of differentially expressed genes (DEGs) at the transcriptome and translatome levels and revealed dozens of genes with altered translational efficiency (GATEs). Transcriptionally up-regulated DEGs were mainly associated with rRNA processing, pre-mRNA splicing, translation and DNA repair, while down-regulated DEGs were genes of membrane proteins; the type of regulation depended on the GC content in the 3′ untranslated regions of DEG mRNAs. The belonging of GATEs to up-regulated and down-regulated ones was determined by the coding sequence length of their mRNAs. Our findings suggest that the effects observed in uL5-deficient cells result from an insufficiency of translationally active ribosomes caused by a deficiency of 60S subunits.

A systematic analysis of genetic interactions and their underlying biology in childhood cancer

Childhood cancer is a major cause of child death in developed countries. Genetic interactions between mutated genes play an important role in cancer development. They can be detected by searching for pairs of mutated genes that co-occur more (or less) often than expected. Co-occurrence suggests a cooperative role in cancer development, while mutual exclusivity points to synthetic lethality, a phenomenon of interest in cancer treatment research. Little is known about genetic interactions in childhood cancer. We apply a statistical pipeline to detect genetic interactions in a combined dataset comprising over 2,500 tumors from 23 cancer types. The resulting genetic interaction map of childhood cancers comprises 15 co-occurring and 27 mutually exclusive candidates. The biological explanation of most candidates points to either tumor subtype, pathway epistasis or cooperation while synthetic lethality plays a much smaller role. Thus, other explanations beyond synthetic lethality should be considered when interpreting genetic interaction test results.

High frequency of intron retention and clustered H3K4me3-marked nucleosomes in short first introns of human long non-coding RNAs

BACKGROUND

It is established that protein-coding exons are preferentially localized in nucleosomes. To examine whether the same is true for non-coding exons, we analysed nucleosome occupancy in and adjacent to internal exons in genes encoding long non-coding RNAs (lncRNAs) in human CD4+ T cells and K562 cells.

RESULTS

We confirmed that internal exons in lncRNAs are preferentially associated with nucleosomes, but also observed an elevated signal from H3K4me3-marked nucleosomes in the sequences upstream of these exons. Examination of 200 genomic lncRNA loci chosen at random across all chromosomes showed that high-density regions of H3K4me3-marked nucleosomes, which we term 'slabs', are associated with genomic regions exhibiting intron retention. These retained introns occur in over 50% of lncRNAs examined and are mostly first introns with an average length of just 354 bp, compared to the average length of all human introns of 6355 and 7987 bp in mRNAs and lncRNAs, respectively. Removal of short introns from the dataset abrogated the high upstream H3K4me3 signal, confirming that the association of slabs and short lncRNA introns with intron retention holds genome-wide. The high upstream H3K4me3 signal is also associated with alternatively spliced exons, known to be prominent in lncRNAs. This phenomenon was not observed with mRNAs.

CONCLUSIONS

There is widespread intron retention and clustered H3K4me3-marked nucleosomes in short first introns of human long non-coding RNAs, which raises intriguing questions about the relationship of IR to lncRNA function and chromatin organization.