Genome-wide survey of interindividual differences of RNA stability in human lymphoblastoid cell lines

MicroRNA-regulated suppression of some overexpressed genes in schizophrenia and their evolutionary significance

Impaired formation of the brain or nervous system is the root cause of neurodevelopmental disorders which appear in pregnancy or soon after birth. One such neurodevelopmental disorder is Schizophrenia. Among the most serious forms of psychosis, Schizophrenia (SCZ) affects 1 % of the general population. MiRNA targeting sites and codon usage of nine overexpressed genes in Schizophrenia were investigated in this study. The neutrality plot demonstrated the importance of natural selection over mutational pressure in the evolution of these genes. The analysis of COSM revealed that the miRNA target regions of the genes were encoded by non-optimal codons, resulting in low translational efficiency, whereas the GC content revealed that the miRNA-mRNA binding was strong. From this study it was concluded that each overexpressed gene was targeted by several human miRNAs for putative suppression. These identified miRNAs could have therapeutic potential in Schizophrenia therapy.

Uneven distribution of prokaryote-derived horizontal gene transfer in fungi: a lifestyle-dependent phenomenon

Horizontal gene transfer (HGT) in fungi is less understood despite its significance in prokaryotes. In this study, we systematically searched for HGT events in 829 representative fungal genomes. Using a combination of sequence similarity and phylogeny-based approaches, we detected 20,093 prokaryotic-derived transferred genes across 750 fungal genomes, via 8,815 distinct HGT events. Notably, our analysis revealed that eight lifestyle-related traits significantly influence HGT diversity in fungi. For instance, parasites exhibited the highest estimated number of HGT-acquired genes, followed by saprotrophs, with symbionts showing the lowest. HGT-acquired genes were predominantly associated with metabolism and cellular functions and underwent purifying selection. Moreover, horizontally transferred genes with introns have significantly higher expression levels compared to intron-lacking genes, suggesting a probable role of intron gains in the adaptation of HGT-acquired genes. Overall, our findings highlight the influence of lifestyle on HGT diversity in fungi and underscore the substantial contribution of HGT to fungal adaptation.

IMPORTANCE

This study sheds new light on the role of horizontal gene transfer (HGT) in fungi, an area that has remained relatively unexplored compared to its well-established prevalence in bacteria. By analyzing 829 fungal genomes, we identified over 20,000 genes that fungi acquired from prokaryotes, revealing the significant impact of HGT on fungal evolution. Our findings highlight that fungal lifestyle traits, such as being parasitic or saprotrophic, play a key role in determining the extent of HGT, with parasites showing the highest gene acquisition rates. We also uncovered unique patterns of HGT occurrence based on fungal morphology and reproduction. Importantly, genes with introns, which are more highly expressed, appear to play a crucial role in fungal adaptation. This research deepens our understanding of how HGT contributes to the metabolic diversity and ecological success of fungi, and it underscores the broader significance of gene transfer in shaping fungal evolution.

Epstein-Barr virus induces host shutoff extensively via BGLF5-independent mechanisms

Epstein-Barr virus (EBV) is a ubiquitous oncogenic virus associated with multiple cancers and autoimmune diseases. Unlike most herpesviruses, EBV reactivation from latency occurs asymptomatically, allowing it to spread efficiently to other hosts. However, available models are limited by the inefficient and asynchronous reactivation from latency into lytic replication. To address this problem, we develop a dual-fluorescent lytic reporter (DFLR) EBV that specifically labels cells in the early and late stages of replication. Using lymphoblastoid cell lines transformed by DFLR EBV as a model for EBV reactivation in B cells, we observe extensive reprogramming of the host cell transcriptome during lytic cycle progression. This includes widespread shutoff of host gene expression and disruption of mRNA processing. Unexpectedly, host shutoff remains extensive even in cells infected with DFLR EBV deleted for the BGLF5 nuclease. These findings implicate BGLF5-independent mechanisms as the primary drivers of host transcriptome remodeling during EBV lytic replication.

Cellular energy regulates mRNA degradation in a codon-specific manner

Codon optimality is a major determinant of mRNA translation and degradation rates. However, whether and through which mechanisms its effects are regulated remains poorly understood. Here we show that codon optimality associates with up to 2-fold change in mRNA stability variations between human tissues, and that its effect is attenuated in tissues with high energy metabolism and amplifies with age. Mathematical modeling and perturbation data through oxygen deprivation and ATP synthesis inhibition reveal that cellular energy variations non-uniformly alter the effect of codon usage. This new mode of codon effect regulation, independent of tRNA regulation, provides a fundamental mechanistic link between cellular energy metabolism and eukaryotic gene expression.

UPF1 regulates mRNA stability by sensing poorly translated coding sequences

Post-transcriptional mRNA regulation shapes gene expression, yet how cis-elements and mRNA translation interface to regulate mRNA stability is poorly understood. We find that the strength of translation initiation, upstream open reading frame (uORF) content, codon optimality, AU-rich elements, microRNA binding sites, and open reading frame (ORF) length function combinatorially to regulate mRNA stability. Machine-learning analysis identifies ORF length as the most important conserved feature regulating mRNA decay. We find that Upf1 binds poorly translated and untranslated ORFs, which are associated with a higher decay rate, including mRNAs with uORFs and those with exposed ORFs after stop codons. Our study emphasizes Upf1's converging role in surveilling mRNAs with exposed ORFs that are poorly translated, such as mRNAs with long ORFs, ORF-like 3' UTRs, and mRNAs containing uORFs. We propose that Upf1 regulation of poorly/untranslated ORFs provides a unifying mechanism of surveillance in regulating mRNA stability and homeostasis in an exon-junction complex (EJC)-independent nonsense-mediated decay (NMD) pathway that we term ORF-mediated decay (OMD).

Development and Comparison of 4-Thiouridine to Cytidine Base Conversion Reaction

To study transcriptome dynamics without harming cells, it is essential to convert chemical bases. 4-Thiouridine (4sU) is a biocompatible uridine analogue that can be converted into a cytidine analogue. Although several reactions can convert 4sU into a cytidine analogue, few studies have compared the features of these reactions. In this study, we performed three reported base conversion reactions, including osmium tetroxide, iodoacetamide, and sodium periodate treatment, as well as a new reaction using 2,4-dinitrofluorobenzene. We compared the reaction time, conversion efficacy, and effects on reverse transcription. These reactions successfully converted 4sU into a cytidine analogue quantitatively using trinucleotides. However, the conversion efficacy and effect on reverse transcription vary depending on the reaction with the RNA transcript. OsO4 treatment followed by NH4Cl treatment showed the best base-conversion efficiency. Nevertheless, each reaction has its own advantages and disadvantages as a tool for studying the transcriptome. Therefore, it is crucial to select the appropriate reaction for the target of interest.

Genomic imprints of unparalleled growth

Chlorella ohadii was isolated from desert biological soil crusts, one of the harshest habitats on Earth, and is emerging as an exciting new green model for studying growth, photosynthesis and metabolism under a wide range of conditions. Here, we compared the genome of C. ohadii, the fastest growing alga on record, to that of other green algae, to reveal the genomic imprints empowering its unparalleled growth rate and resistance to various stressors, including extreme illumination. This included the genome of its close relative, but slower growing and photodamage sensitive, C. sorokiniana UTEX 1663. A larger number of ribosome-encoding genes, high intron abundance, increased codon bias and unique genes potentially involved in metabolic flexibility and resistance to photodamage are all consistent with the faster growth of C. ohadii. Some of these characteristics highlight general trends in Chlorophyta and Chlorella spp. evolution, and others open new broad avenues for mechanistic exploration of their relationship with growth. This work entails a unique case study for the genomic adaptations and costs of exceptionally fast growth and sheds light on the genomic signatures of fast growth in photosynthetic cells. It also provides an important resource for future studies leveraging the unique properties of C. ohadii for photosynthesis and stress response research alongside their utilization for synthetic biology and biotechnology aims.

Functional characterization of the disease-associated CCL2 rs1024611G-rs13900T haplotype: The role of the RNA-binding protein HuR

CC-chemokine ligand 2 (CCL2) is involved in the pathogenesis of several diseases associated with monocyte/macrophage recruitment, such as HIV-associated neurocognitive disorder (HAND), tuberculosis, and atherosclerosis. The rs1024611 (alleles:A>G; G is the risk allele) polymorphism in the CCL2 cis-regulatory region is associated with increased CCL2 expression in vitro and ex vivo, leukocyte mobilization in vivo, and deleterious disease outcomes. However, the molecular basis for the rs1024611-associated differential CCL2 expression remains poorly characterized. It is conceivable that genetic variant(s) in linkage disequilibrium (LD) with rs1024611 could mediate such effects. Previously, we used rs13900 (alleles:_C>T) in the CCL2 3' untranslated region (3' UTR) that is in perfect LD with rs1024611 to demonstrate allelic expression imbalance (AEI) of CCL2 in heterozygous individuals. Here we tested the hypothesis that the rs13900 could modulate CCL2 expression by altering mRNA turnover and/or translatability. The rs13900 T allele conferred greater stability to the CCL2 transcript when compared to the rs13900 C allele. The rs13900 T allele also had increased binding to Human Antigen R (HuR), an RNA-binding protein, in vitro and ex vivo. The rs13900 alleles imparted differential activity to reporter vectors and influenced the translatability of the reporter transcript. We further demonstrated a role for HuR in mediating allele-specific effects on CCL2 expression in overexpression and silencing studies. The presence of the rs1024611G-rs13900T conferred a distinct transcriptomic signature related to inflammation and immunity. Our studies suggest that the differential interactions of HuR with rs13900 could modulate CCL2 expression and explain the interindividual differences in CCL2-mediated disease susceptibility.

Low RNA stability signifies increased post-transcriptional regulation of cell identity genes

Cell identity genes are distinct from other genes with respect to the epigenetic mechanisms to activate their transcription, e.g. by super-enhancers and broad H3K4me3 domains. However, it remains unclear whether their post-transcriptional regulation is also unique. We performed a systematic analysis of transcriptome-wide RNA stability in nine cell types and found that unstable transcripts were enriched in cell identity-related pathways while stable transcripts were enriched in housekeeping pathways. Joint analyses of RNA stability and chromatin state revealed significant enrichment of super-enhancers and broad H3K4me3 domains at the gene loci of unstable transcripts. Intriguingly, the RNA m6A methyltransferase, METTL3, preferentially binds to chromatin at super-enhancers, broad H3K4me3 domains and their associated genes. METTL3 binding intensity is positively correlated with RNA m6A methylation and negatively correlated with RNA stability of cell identity genes, probably due to co-transcriptional m6A modifications promoting RNA decay. Nanopore direct RNA-sequencing showed that METTL3 knockdown has a stronger effect on RNA m6A and mRNA stability for cell identity genes. Our data suggest a run-and-brake model, where cell identity genes undergo both frequent transcription and fast RNA decay to achieve precise regulation of RNA expression.

satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect

The impact of millions of individual genetic variants on molecular phenotypes in coding sequences remains unknown. Multiplexed assays of variant effect (MAVEs) are scalable methods to annotate relevant variants, but existing software lacks standardization, requires cumbersome configuration, and does not scale to large targets. We present satmut_utils as a flexible solution for simulation and variant quantification. We then benchmark MAVE software using simulated and real MAVE data. We finally determine mRNA abundance for thousands of cystathionine beta-synthase variants using two experimental methods. The satmut_utils package enables high-performance analysis of MAVEs and reveals the capability of variants to alter mRNA abundance.

Parallel recovery of chromatin accessibility and gene expression dynamics from frozen human regulatory T cells

Epigenetic features such as DNA accessibility dictate transcriptional regulation in a cell type- and cell state- specific manner, and mapping this in health vs. disease in clinically relevant material is opening the door to new mechanistic insights and new targets for therapy. Assay for Transposase Accessible Chromatin Sequencing (ATAC-seq) allows chromatin accessibility profiling from low cell input, making it tractable on rare cell populations, such as regulatory T (Treg) cells. However, little is known about the compatibility of the assay with cryopreserved rare cell populations. Here we demonstrate the robustness of an ATAC-seq protocol comparing primary Treg cells recovered from fresh or cryopreserved PBMC samples, in the steady state and in response to stimulation. We extend this method to explore the feasibility of conducting simultaneous quantitation of chromatin accessibility and transcriptome from a single aliquot of 50,000 cryopreserved Treg cells. Profiling of chromatin accessibility and gene expression in parallel within the same pool of cells controls for cellular heterogeneity and is particularly beneficial when constrained by limited input material. Overall, we observed a high correlation of accessibility patterns and transcription factor dynamics between fresh and cryopreserved samples. Furthermore, highly similar transcriptomic profiles were obtained from whole cells and from the supernatants recovered from ATAC-seq reactions. We highlight the feasibility of applying these techniques to profile the epigenomic landscape of cells recovered from cryopreservation biorepositories.

The genetic and biochemical determinants of mRNA degradation rates in mammals

BACKGROUND

Degradation rate is a fundamental aspect of mRNA metabolism, and the factors governing it remain poorly characterized. Understanding the genetic and biochemical determinants of mRNA half-life would enable more precise identification of variants that perturb gene expression through post-transcriptional gene regulatory mechanisms.

RESULTS

We establish a compendium of 39 human and 27 mouse transcriptome-wide mRNA decay rate datasets. A meta-analysis of these data identified a prevalence of technical noise and measurement bias, induced partially by the underlying experimental strategy. Correcting for these biases allowed us to derive more precise, consensus measurements of half-life which exhibit enhanced consistency between species. We trained substantially improved statistical models based upon genetic and biochemical features to better predict half-life and characterize the factors molding it. Our state-of-the-art model, Saluki, is a hybrid convolutional and recurrent deep neural network which relies only upon an mRNA sequence annotated with coding frame and splice sites to predict half-life (r=0.77). The key novel principle learned by Saluki is that the spatial positioning of splice sites, codons, and RNA-binding motifs within an mRNA is strongly associated with mRNA half-life. Saluki predicts the impact of RNA sequences and genetic mutations therein on mRNA stability, in agreement with functional measurements derived from massively parallel reporter assays.

CONCLUSIONS

Our work produces a more robust ground truth for transcriptome-wide mRNA half-lives in mammalian cells. Using these revised measurements, we trained Saluki, a model that is over 50% more accurate in predicting half-life from sequence than existing models. Saluki succinctly captures many of the known determinants of mRNA half-life and can be rapidly deployed to predict the functional consequences of arbitrary mutations in the transcriptome.

A catalog of the genetic causes of hereditary angioedema in the Canary Islands (Spain)

Hereditary angioedema (HAE) is a rare disease where known causes involve C1 inhibitor dysfunction or dysregulation of the kinin cascade. The updated HAE management guidelines recommend performing genetic tests to reach a precise diagnosis. Unfortunately, genetic tests are still uncommon in the diagnosis routine. Here, we characterized for the first time the genetic causes of HAE in affected families from the Canary Islands (Spain). Whole-exome sequencing data was obtained from 41 affected patients and unaffected relatives from 29 unrelated families identified in the archipelago. The Hereditary Angioedema Database Annotation (HADA) tool was used for pathogenicity classification and causal variant prioritization among the genes known to cause HAE. Manual reclassification of prioritized variants was used in those families lacking known causal variants. We detected a total of eight different variants causing HAE in this patient series, affecting essentially SERPING1 and F12 genes, one of them being a novel SERPING1 variant (c.686-12A>G) with a predicted splicing effect which was reclassified as likely pathogenic in one family. Altogether, the diagnostic yield by assessing previously reported causal genes and considering variant reclassifications according to the American College of Medical Genetics guidelines reached 66.7% (95% Confidence Interval [CI]: 30.1-91.0) in families with more than one affected member and 10.0% (95% CI: 1.8-33.1) among cases without family information for the disease. Despite the genetic causes of many patients remain to be identified, our results reinforce the need of genetic tests as first-tier diagnostic tool in this disease, as recommended by the international WAO/EAACI guidelines for the management of HAE.

Modulation of RNA stability regulates gene expression in two opposite ways: through buffering of RNA levels upon global perturbations and by supporting adapted differential expression

The steady state levels of RNAs, often referred to as expression levels, result from a well-balanced combination of RNA transcription and decay. Alterations in RNA levels will therefore result from tight regulation of transcription rates, decay rates or both. Here, we explore the role of RNA stability in achieving balanced gene expression and present genome-wide RNA stabilities in Drosophila melanogaster male and female cells as well as male cells depleted of proteins essential for dosage compensation. We identify two distinct RNA-stability mediated responses involved in regulation of gene expression. The first of these responds to acute and global changes in transcription and thus counteracts potentially harmful gene mis-expression by shifting the RNA stability in the direction opposite to the transcriptional change. The second response enhances inter-individual differential gene expression by adjusting the RNA stability in the same direction as a transcriptional change. Both mechanisms are global, act on housekeeping as well as non-housekeeping genes and were observed in both flies and mammals. Additionally, we show that, in contrast to mammals, modulation of RNA stability does not detectably contribute to dosage compensation of the sex-chromosomes in D. melanogaster.

Sorting and packaging of RNA into extracellular vesicles shape intracellular transcript levels

BACKGROUND

Extracellular vesicles (EVs) are released by nearly every cell type and have attracted much attention for their ability to transfer protein and diverse RNA species from donor to recipient cells. Much attention has been given so far to the features of EV short RNAs such as miRNAs. However, while the presence of mRNA and long noncoding RNA (lncRNA) transcripts in EVs has also been reported by multiple different groups, the properties and function of these longer transcripts have been less thoroughly explored than EV miRNA. Additionally, the impact of EV export on the transcriptome of exporting cells has remained almost completely unexamined. Here, we globally investigate mRNA and lncRNA transcripts in endothelial EVs in multiple different conditions.

RESULTS

In basal conditions, long RNA transcripts enriched in EVs have longer than average half-lives and distinctive stability-related sequence and structure characteristics including shorter transcript length, higher exon density, and fewer 3' UTR A/U-rich elements. EV-enriched long RNA transcripts are also enriched in HNRNPA2B1 binding motifs and are impacted by HNRNPA2B1 depletion, implicating this RNA-binding protein in the sorting of long RNA to EVs. After signaling-dependent modification of the cellular transcriptome, we observed that, unexpectedly, the rate of EV enrichment relative to cells was altered for many mRNA and lncRNA transcripts. This change in EV enrichment was negatively correlated with intracellular abundance, with transcripts whose export to EVs increased showing decreased abundance in cells and vice versa. Correspondingly, after treatment with inhibitors of EV secretion, levels of mRNA and lncRNA transcripts that are normally highly exported to EVs increased in cells, indicating a measurable impact of EV export on the long RNA transcriptome of the exporting cells. Compounds with different mechanisms of inhibition of EV secretion affected the cellular transcriptome differently, suggesting the existence of multiple EV subtypes with different long RNA profiles.

CONCLUSIONS

We present evidence for an impact of EV physiology on the characteristics of EV-producing cell transcriptomes. Our work suggests a new paradigm in which the sorting and packaging of transcripts into EVs participate, together with transcription and RNA decay, in controlling RNA homeostasis and shape the cellular long RNA abundance profile.

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Targeting 3' and 5' untranslated regions with antisense oligonucleotides to stabilize frataxin mRNA and increase protein expression

Friedreich's ataxia (FRDA) is a severe multisystem disease caused by transcriptional repression induced by expanded GAA repeats located in intron 1 of the Frataxin (FXN) gene encoding frataxin. FRDA results from decreased levels of frataxin; thus, stabilization of the FXN mRNA already present in patient cells represents an attractive and unexplored therapeutic avenue. In this work, we pursued a novel approach based on oligonucleotide-mediated targeting of FXN mRNA ends to extend its half-life and availability as a template for translation. We demonstrated that oligonucleotides designed to bind to FXN 5' or 3' noncoding regions can increase FXN mRNA and protein levels. Simultaneous delivery of oligonucleotides targeting both ends increases efficacy of the treatment. The approach was confirmed in several FRDA fibroblast and induced pluripotent stem cell-derived neuronal progenitor lines. RNA sequencing and single-cell expression analyses confirmed oligonucleotide-mediated FXN mRNA upregulation. Mechanistically, a significant elongation of the FXN mRNA half-life without any changes in chromatin status at the FXN gene was observed upon treatment with end-targeting oligonucleotides, indicating that transcript stabilization is responsible for frataxin upregulation. These results identify a novel approach toward upregulation of steady-state mRNA levels via oligonucleotide-mediated end targeting that may be of significance to any condition resulting from transcription downregulation.

Harnessing natural variation to identify cis regulators of sex-biased gene expression in a multi-strain mouse liver model

Sex differences in gene expression are widespread in the liver, where many autosomal factors act in tandem with growth hormone signaling to regulate individual variability of sex differences in liver metabolism and disease. Here, we compare hepatic transcriptomic and epigenetic profiles of mouse strains C57BL/6J and CAST/EiJ, representing two subspecies separated by 0.5-1 million years of evolution, to elucidate the actions of genetic factors regulating liver sex differences. We identify 144 protein coding genes and 78 lncRNAs showing strain-conserved sex bias; many have gene ontologies relevant to liver function, are more highly liver-specific and show greater sex bias, and are more proximally regulated than genes whose sex bias is strain-dependent. The strain-conserved genes include key growth hormone-dependent transcriptional regulators of liver sex bias; however, three other transcription factors, Trim24, Tox, and Zfp809, lose their sex-biased expression in CAST/EiJ mouse liver. To elucidate the observed strain specificities in expression, we characterized the strain-dependence of sex-biased chromatin opening and enhancer marks at cis regulatory elements (CREs) within expression quantitative trait loci (eQTL) regulating liver sex-biased genes. Strikingly, 208 of 286 eQTLs with strain-specific, sex-differential effects on expression were associated with a complete gain, loss, or reversal of the sex differences in expression between strains. Moreover, 166 of the 286 eQTLs were linked to the strain-dependent gain or loss of localized sex-biased CREs. Remarkably, a subset of these CREs apparently lacked strain-specific genetic variants yet showed coordinated, strain-dependent sex-biased epigenetic regulation. Thus, we directly link hundreds of strain-specific genetic variants to the high variability in CRE activity and expression of sex-biased genes and uncover underlying genetically-determined epigenetic states controlling liver sex bias in genetically diverse mouse populations.

Mutations in tomato 1-aminocyclopropane carboxylic acid synthase2 uncover its role in development beside fruit ripening

The role of ethylene in plant development is mostly inferred from its exogenous application. The usage of mutants affecting ethylene biosynthesis proffers a better alternative to decipher its role. In tomato (Solanum lycopersicum), 1-aminocyclopropane carboxylic acid synthase2 (ACS2) is a key enzyme regulating ripening-specific ethylene biosynthesis. We characterised two contrasting acs2 mutants; acs2-1 overproduces ethylene, has higher ACS activity, and has increased protein levels, while acs2-2 is an ethylene underproducer, displays lower ACS activity, and has lower protein levels than wild type. Consistent with high/low ethylene emission, the mutants show opposite phenotypes, physiological responses, and metabolomic profiles compared with the wild type. The acs2-1 mutant shows early seed germination, faster leaf senescence, and accelerated fruit ripening. Conversely, acs2-2 has delayed seed germination, slower leaf senescence, and prolonged fruit ripening. The phytohormone profiles of mutants were mostly opposite in the leaves and fruits. The faster/slower senescence of acs2-1/acs2-2 leaves correlated with the endogenous ethylene/zeatin ratio. The genetic analysis showed that the metabolite profiles of respective mutants co-segregated with the homozygous mutant progeny. Our results uncover that besides ripening, ACS2 participates in the vegetative and reproductive development of tomato. The distinct influence of ethylene on phytohormone profiles indicates the intertwining of ethylene action with other phytohormones in regulating plant development.

Codon Usage and Splicing Jointly Influence mRNA Localization

In the human genome, most genes undergo splicing, and patterns of codon usage are splicing dependent: guanine and cytosine (GC) content is the highest within single-exon genes and within first exons of multi-exon genes. However, the effects of codon usage on gene expression are typically characterized in unspliced model genes. Here, we measured the effects of splicing on expression in a panel of synonymous reporter genes that varied in nucleotide composition. We found that high GC content increased protein yield, mRNA yield, cytoplasmic mRNA localization, and translation of unspliced reporters. Splicing did not affect the expression of GC-rich variants. However, splicing promoted the expression of AT-rich variants by increasing their steady-state protein and mRNA levels, in part through promoting cytoplasmic localization of mRNA. We propose that splicing promotes the nuclear export of AU-rich mRNAs and that codon- and splicing-dependent effects on expression are under evolutionary pressure in the human genome.

A Protocol for Transcriptome-Wide Inference of RNA Metabolic Rates in Mouse Embryonic Stem Cells

The relative ease of mouse Embryonic Stem Cells (mESCs) culture and the potential of these cells to differentiate into any of the three primary germ layers: ectoderm, endoderm and mesoderm (pluripotency), makes them an ideal and frequently used ex vivo system to dissect how gene expression changes impact cell state and differentiation. These efforts are further supported by the large number of constitutive and inducible mESC mutants established with the aim of assessing the contributions of different pathways and genes to cell homeostasis and gene regulation. Gene product abundance is controlled by the modulation of the rates of RNA synthesis, processing, and degradation. The ability to determine the relative contribution of these different RNA metabolic rates to gene expression control using standard RNA-sequencing approaches, which only capture steady state abundance of transcripts, is limited. In contrast, metabolic labeling of RNA with 4-thiouridine (4sU) coupled with RNA-sequencing, allows simultaneous and reproducible inference of transcriptome wide synthesis, processing, and degradation rates. Here we describe, a detailed protocol for 4sU metabolic labeling in mESCs that requires short 4sU labeling times at low concentration and minimally impacts cellular homeostasis. This approach presents a versatile method for in-depth characterization of the gene regulatory strategies governing gene steady state abundance in mESC.

Coding regions affect mRNA stability in human cells

A new paradigm has emerged that coding regions can regulate mRNA stability in model organisms. Here, due to differences in cognate tRNA abundance, synonymous codons are translated at different speeds, and slow codons then stimulate mRNA decay. To ask if this phenomenon also occurs in humans, we isolated RNA stability effects due to coding regions using the human ORFeome collection. We find that many open reading frame (ORF) characteristics, such as length and secondary structure, fail to provide explanations for how coding regions alter mRNA stability, and, instead, that the ORF relies on translation to impact mRNA stability. Consistent with what has been seen in other organisms, codon use is related to the effects of ORFs on transcript stability. Importantly, we found instability-associated codons have longer A-site dwell times, suggesting for the first time in humans a connection between elongation speed and mRNA decay. Thus, we propose that codon usage alters decoding speeds and so affects human mRNA stability.

Predicting Functional Effects of Synonymous Variants: A Systematic Review and Perspectives

Recent advances in high-throughput experimentation have put the exploration of genome sequences at the forefront of precision medicine. In an effort to interpret the sequencing data, numerous computational methods have been developed for evaluating the effects of genome variants. Interestingly, despite the fact that every person has as many synonymous (sSNV) as non-synonymous single nucleotide variants, our ability to predict their effects is limited. The paucity of experimentally tested sSNV effects appears to be the limiting factor in development of such methods. Here, we summarize the details and evaluate the performance of nine existing computational methods capable of predicting sSNV effects. We used a set of observed and artificially generated variants to approximate large scale performance expectations of these tools. We note that the distribution of these variants across amino acid and codon types suggests purifying evolutionary selection retaining generated variants out of the observed set; i.e., we expect the generated set to be enriched for deleterious variants. Closer inspection of the relationship between the observed variant frequencies and the associated prediction scores identifies predictor-specific scoring thresholds of reliable effect predictions. Notably, across all predictors, the variants scoring above these thresholds were significantly more often generated than observed. which confirms our assumption that the generated set is enriched for deleterious variants. Finally, we find that while the methods differ in their ability to identify severe sSNV effects, no predictor appears capable of definitively recognizing subtle effects of such variants on a large scale.

From Schizophrenia Genetics to Disease Biology: Harnessing New Concepts and Technologies

Schizophrenia (SZ) is a severe mental disorder afflicting around 1% of the population. It is highly heritable but with complex genetics. Recent research has unraveled a plethora of risk loci for SZ. Accordingly, our conceptual understanding of SZ genetics has been rapidly evolving, from oligogenic models towards polygenic or even omnigenic models. A pressing challenge to the field, however, is the translation of the many genetic findings of SZ into disease biology insights leading to more effective treatments. Bridging this gap requires the integration of genetic findings and functional genomics using appropriate cellular models. Harnessing new technologies, such as the development of human induced pluripotent stem cells (hiPSC) and the CRISPR/Cas-based genome/epigenome editing approach are expected to change our understanding of SZ disease biology to a fundamentally higher level. Here, we discuss some new developments.

Innovative strategies for annotating the "relationSNP" between variants and molecular phenotypes

Characterizing how variation at the level of individual nucleotides contributes to traits and diseases has been an area of growing interest since the completion of sequencing the first human genome. Our understanding of how a single nucleotide polymorphism (SNP) leads to a pathogenic phenotype on a genome-wide scale is a fruitful endeavor for anyone interested in developing diagnostic tests, therapeutics, or simply wanting to understand the etiology of a disease or trait. To this end, many datasets and algorithms have been developed as resources/tools to annotate SNPs. One of the most common practices is to annotate coding SNPs that affect the protein sequence. Synonymous variants are often grouped as one type of variant, however there are in fact many tools available to dissect their effects on gene expression. More recently, large consortiums like ENCODE and GTEx have made it possible to annotate non-coding regions. Although annotating variants is a common technique among human geneticists, the constant advances in tools and biology surrounding SNPs requires an updated summary of what is known and the trajectory of the field. This review will discuss the history behind SNP annotation, commonly used tools, and newer strategies for SNP annotation. Additionally, we will comment on the caveats that distinguish approaches from one another, along with gaps in the current state of knowledge, and potential future directions. We do not intend for this to be a comprehensive review for any specific area of SNP annotation, but rather it will be an excellent resource for those unfamiliar with computational tools used to functionally characterize SNPs. In summary, this review will help illustrate how each SNP annotation method impacts the way in which the genetic and molecular etiology of a disease is explored in-silico.

Gaining insight into transcriptome-wide RNA population dynamics through the chemistry of 4-thiouridine

Cellular RNA levels are the result of a juggling act between RNA transcription, processing, and degradation. By tuning one or more of these parameters, cells can rapidly alter the available pool of transcripts in response to stimuli. While RNA sequencing (RNA-seq) is a vital method to quantify RNA levels genome-wide, it is unable to capture the dynamics of different RNA populations at steady-state or distinguish between different mechanisms that induce changes to the steady-state (i.e., altered rate of transcription vs. degradation). The dynamics of different RNA populations can be studied by targeted incorporation of noncanonical nucleosides. 4-Thiouridine (s⁴ U) is a commonly used and versatile RNA metabolic label that allows the study of many properties of RNA metabolism from synthesis to degradation. Numerous experimental strategies have been developed that leverage the power of s⁴ U to label newly transcribed RNA in whole cells, followed by enrichment with activated disulfides or chemistry to induce C mutations at sites of s⁴ U during sequencing. This review presents existing methods to study RNA population dynamics genome-wide using s⁴ U metabolic labeling, as well as a discussion of considerations and challenges when designing s⁴ U metabolic labeling experiments. This article is categorized under: RNA Methods > RNA Analyses in Cells RNA Turnover and Surveillance > Regulation of RNA Stability.

The common VWF single nucleotide variants c.2365A>G and c.2385T>C modify VWF biosynthesis and clearance

Plasma levels of von Willebrand factor (VWF) vary considerably in the general population and this variation has been linked to several genetic and environmental factors. Genetic factors include 2 common single nucleotide variants (SNVs) located in VWF, rs1063856 (c.2365A>G) and rs1063857 (c.2385T>C), although to date the mechanistic basis for their association with VWF level is unknown. Using genotypic/phenotypic information from a European healthy control population, in vitro analyses of recombinant VWF expressing both SNVs, and in vivo murine models, this study determined the precise nature of their association with VWF level and investigated the mechanism(s) involved. Possession of either SNV corresponded with a significant increase in plasma VWF in healthy controls (P < .0001). In vitro expression confirmed this observation and highlighted an independent effect for each SNV (P < .0001 and P < .01, respectively), despite close proximity and strong linkage disequilibrium between them both. The influence of c.2365A>G on VWF levels was also confirmed in vivo. This increase in VWF protein corresponded to an increase in VWF messenger RNA (mRNA) resulting, in part, from prolonged mRNA half-life. In addition, coinheritance of both SNVs was associated with a lower VWF propeptide-to-VWF antigen ratio in healthy controls (P < .05) and a longer VWF half-life in VWF knockout mice (P < .0001). Both SNVs therefore directly increase VWF plasma levels through a combined influence on VWF biosynthesis and clearance, and may have an impact on disease phenotype in both hemostatic and thrombotic disorders.

DRUID: a pipeline for transcriptome-wide measurements of mRNA stability

Control of messenger RNA (mRNA) stability is an important aspect of gene regulation. The gold standard for measuring mRNA stability transcriptome-wide uses metabolic labeling, biochemical isolation of labeled RNA populations, and high-throughput sequencing. However, difficult normalization procedures have inhibited widespread adoption of this approach. Here, we present DRUID (for determination of rates using intron dynamics), a new computational pipeline that is robust, easy to use, and freely available. Our pipeline uses endogenous introns to normalize time course data and yields reproducible half-lives, even with data sets that were otherwise unusable. DRUID can handle data sets from a variety of organisms, spanning yeast to humans, and we even applied it retroactively on published data sets. We anticipate that DRUID will allow broad application of metabolic labeling for studies of transcript stability.

Cis-regulatory elements explain most of the mRNA stability variation across genes in yeast

The stability of mRNA is one of the major determinants of gene expression. Although a wealth of sequence elements regulating mRNA stability has been described, their quantitative contributions to half-life are unknown. Here, we built a quantitative model for Saccharomyces cerevisiae based on functional mRNA sequence features that explains 59% of the half-life variation between genes and predicts half-life at a median relative error of 30%. The model revealed a new destabilizing 3' UTR motif, ATATTC, which we functionally validated. Codon usage proves to be the major determinant of mRNA stability. Nonetheless, single-nucleotide variations have the largest effect when occurring on 3' UTR motifs or upstream AUGs. Analyzing mRNA half-life data of 34 knockout strains showed that the effect of codon usage not only requires functional decapping and deadenylation, but also the 5'-to-3' exonuclease Xrn1, the nonsense-mediated decay genes, but not no-go decay. Altogether, this study quantitatively delineates the contributions of mRNA sequence features on stability in yeast, reveals their functional dependencies on degradation pathways, and allows accurate prediction of half-life from mRNA sequence.

Pervasive coexpression of spatially proximal genes is buffered at the protein level

Genes are not randomly distributed in the genome. In humans, 10% of protein-coding genes are transcribed from bidirectional promoters and many more are organised in larger clusters. Intriguingly, neighbouring genes are frequently coexpressed but rarely functionally related. Here we show that coexpression of bidirectional gene pairs, and closeby genes in general, is buffered at the protein level. Taking into account the 3D architecture of the genome, we find that co-regulation of spatially close, functionally unrelated genes is pervasive at the transcriptome level, but does not extend to the proteome. We present evidence that non-functional mRNA coexpression in human cells arises from stochastic chromatin fluctuations and direct regulatory interference between spatially close genes. Protein-level buffering likely reflects a lack of coordination of post-transcriptional regulation of functionally unrelated genes. Grouping human genes together along the genome sequence, or through long-range chromosome folding, is associated with reduced expression noise. Our results support the hypothesis that the selection for noise reduction is a major driver of the evolution of genome organisation.

How introns enhance gene expression

In many eukaryotes, including mammals, plants, yeast, and insects, introns can increase gene expression without functioning as a binding site for transcription factors. This phenomenon was termed 'intron-mediated enhancement'. Introns can increase transcript levels by affecting the rate of transcription, nuclear export, and transcript stability. Moreover, introns can also increase the efficiency of mRNA translation. This review discusses the current knowledge about these processes. The role of splicing in IME and the significance of intron position relative to the sites of transcription and translation initiation are elaborated. Particular emphasis is placed on the question why different introns, present at the same location of the same genes and spliced at a similar high efficiency, can have very different impacts on expression - from almost no effect to considerable stimulation. This situation can be at least partly accounted for by the identification of splicing-unrelated intronic elements with a special ability to enhance mRNA accumulation or translational efficiency. The many factors that could lead to the large variation observed between the impact of introns in different genes and experimental systems are highlighted. It is suggested that there is no sole, definite answer to the question "how do introns enhance gene expression". Rather, each intron-gene combination might undergo its own unique mixture of processes that lead to the perceptible outcome.

Independent regulation of gene expression level and noise by histone modifications

The inherent stochasticity generates substantial gene expression variation among isogenic cells under identical conditions, which is frequently referred to as gene expression noise or cell-to-cell expression variability. Similar to (average) expression level, expression noise is also subject to natural selection. Yet it has been observed that noise is negatively correlated with expression level, which manifests as a potential constraint for simultaneous optimization of both. Here, we studied expression noise in human embryonic cells with computational analysis on single-cell RNA-seq data and in yeast with flow cytometry experiments. We showed that this coupling is overcome, to a certain degree, by a histone modification strategy in multiple embryonic developmental stages in human, as well as in yeast. Importantly, this epigenetic strategy could fit into a burst-like gene expression model: promoter-localized histone modifications (such as H3K4 methylation) are associated with both burst size and burst frequency, which together influence expression level, while gene-body-localized ones (such as H3K79 methylation) are more associated with burst frequency, which influences both expression level and noise. We further knocked out the only “writer” of H3K79 methylation in yeast, and observed that expression noise is indeed increased. Consistently, dosage sensitive genes, such as genes in the Wnt signaling pathway, tend to be marked with gene-body-localized histone modifications, while stress responding genes, such as genes regulating autophagy, tend to be marked with promoter-localized ones. Our findings elucidate that the “division of labor” among histone modifications facilitates the independent regulation of expression level and noise, extend the “histone code” hypothesis to include expression noise, and shed light on the optimization of transcriptome in evolution.

Gene expression noise, or cell-to-cell expression variability, has been a topic of intense interest for more than a decade. The prevailing model of “burst-like transcription” mediated by the promoter transitions between on and off states explains the formation of noise in eukaryotes. Albeit widely accepted, the cis- elements that determine the burst frequency and burst size remain largely unknown. Here we systematically examined the relationship between transcriptional burst frequency/size and all major histone modifications in various cell types, including human embryonic cells, mouse embryonic stem cells, and yeast, and found that histone markers can be divided into two groups based on their associations with burst frequency/ size. Coincidently, promoter-localized histone markers are associated with both burst size and burst frequency whereas gene-body-localized ones are more associated with burst frequency. We further knocked out a gene that is responsible for “writing” a gene-body histone mark in yeast, and found that burst frequency is indeed reduced. Our findings reveal a new mechanism of transcriptional burst regulation and shed light on the simultaneous optimization of gene expression level and noise in evolution.

Pervasive yet nonuniform contributions of Dcp2 and Cnot7 to maternal mRNA clearance in zebrafish

mRNA degradation is a fundamental biological process that erases transcribed genetic information from cells. During maternal-to-zygotic transition of animal development, thousands of maternal mRNAs are degraded by multiple mechanisms including microRNAs and codon-mediated decay. Enzymatic requirements for maternal mRNA clearance, however, are not fully understood. Here, we analyzed a contribution of the decapping enzyme Dcp2 to maternal mRNA clearance in zebrafish by over-expressing catalytically inactive Dcp2 and performing RNA-seq analysis. As expected, Dcp2 had a widespread role in maternal mRNA clearance. Interestingly, each mRNA showed differential dependency on Dcp2-mediated decapping and Cnot7-mediated deadenylation for degradation. Correlation analysis identified several mRNA features that were associated with the observed differential dependency. Our results show pervasive yet nonuniform contributions of the decapping enzyme Dcp2 and the deadenylase Cnot7 to maternal mRNA clearance.

Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples

RNA degradation is a ubiquitous process that occurs in living and dead cells, as well as during handling and storage of extracted RNA. Reduced RNA quality caused by degradation is an established source of uncertainty for all RNA-based gene expression quantification techniques. RNA sequencing is an increasingly preferred method for transcriptome analyses, and dependence of its results on input RNA integrity is of significant practical importance. This study aimed to characterize the effects of varying input RNA integrity [estimated as RNA integrity number (RIN)] on transcript level estimates and delineate the characteristic differences between transcripts that differ in degradation rate. The study used ribodepleted total RNA sequencing data from a real-life clinically collected set (n = 32) of human solid tissue (placenta) samples. RIN-dependent alterations in gene expression profiles were quantified by using DESeq2 software. Our results indicate that small differences in RNA integrity affect gene expression quantification by introducing a moderate and pervasive bias in expression level estimates that significantly affected 8.1% of studied genes. The rapidly degrading transcript pool was enriched in pseudogenes, short noncoding RNAs, and transcripts with extended 3' untranslated regions. Typical slowly degrading transcripts (median length, 2389 nt) represented protein coding genes with 4-10 exons and high guanine-cytosine content.-Reiman, M., Laan, M., Rull, K., Sõber, S. Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples.

Metabolic labeling and recovery of nascent RNA to accurately quantify mRNA stability

Changes in the rate of mRNA decay are closely coordinated with transcriptional changes and together these events have profound effects on gene expression during development and disease. Traditional approaches to assess mRNA decay have relied on inhibition of transcription, which can alter mRNA decay rates and confound interpretation. More recently, metabolic labeling combined with chemical modification and fractionation of labeled RNAs has allowed the isolation of nascent transcripts and the subsequent calculation of mRNA decay rates. This approach has been widely adopted for measuring mRNA half-lives on a global scale, but has proven challenging to use for analysis of single genes. We present a series of normalization and quality assurance steps to be used in combination with 4-thiouridine pulse labeling of cultured eukaryotic cells. Importantly, we demonstrate how the relative amount of 4sU-labeled nascent RNA influences accurate quantification. The approach described facilitates reproducible measurement of individual mRNA half-lives using 4-thiouridine and could be adapted for use with other nucleoside analogs.

Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins

Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample size limitations by integrating tumor genomics data with a wide spectrum of gene-specific properties to search for rare drivers, functionally classify them, and detect features characteristic of driver genes. We show that our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of potentially novel drivers that eluded over a dozen pan-cancer/multi-tumor type studies. In particular, feature analysis reveals a highly concentrated pool of known and putative tumor suppressors among the <1% of genes that encode very large, chromatin-regulating proteins. Thus, our study highlights the need for deeper characterization of very large, epigenetic regulators in the context of cancer causality.

Post-transcriptional regulation of cytokine and growth factor signaling in cancer

Cytokines and growth factors regulate cell proliferation, differentiation, migration and apoptosis, and play important roles in coordinating growth signal responses during development. The expression of cytokine genes and the signals transmitted through cytokine receptors are tightly regulated at several levels, including transcriptional and post-transcriptional levels. A majority of cytokine mRNAs, including growth factor transcripts, contain AU-rich elements (AREs) in their 3' untranslated regions that control gene expression by regulating mRNA degradation and changing translational rates. In addition, numerous proteins involved in transmitting signals downstream of cytokine receptors are regulated at the level of mRNA degradation by GU-rich elements (GREs) found in their 3' untranslated regions. Abnormal stabilization and overexpression of ARE or GRE-containing transcripts had been observed in many malignancies, which is a consequence of the malfunction of RNA-binding proteins. In this review, we briefly summarize the role of AREs and GREs in regulating mRNA turnover to coordinate cytokine and growth factor expression, and we describe how dysregulation of mRNA degradation mechanisms contributes to the development and progression of cancer.

Multiple Transcript Properties Related to Translation Affect mRNA Degradation Rates in Saccharomyces cerevisiae

Degradation of mRNA contributes to variation in transcript abundance. Studies of individual mRNAs have shown that both cis and trans factors affect mRNA degradation rates. However, the factors underlying transcriptome-wide variation in mRNA degradation rates are poorly understood. We investigated the contribution of different transcript properties to transcriptome-wide degradation rate variation in the budding yeast, Saccharomyces cerevisiae, using multiple regression analysis. We find that multiple transcript properties are significantly associated with variation in mRNA degradation rates, and that a model incorporating these properties explains ∼50% of the genome-wide variance. Predictors of mRNA degradation rates include transcript length, ribosome density, biased codon usage, and GC content of the third position in codons. To experimentally validate these factors, we studied individual transcripts expressed from identical promoters. We find that decreasing ribosome density by mutating the first translational start site of a transcript increases its degradation rate. Using coding sequence variants of green fluorescent protein (GFP) that differ only at synonymous sites, we show that increased GC content of the third position of codons results in decreased rates of mRNA degradation. Thus, in steady-state conditions, a large fraction of genome-wide variation in mRNA degradation rates is determined by inherent properties of transcripts, many of which are related to translation, rather than specific regulatory mechanisms.

MicroRNA Stability in FFPE Tissue Samples: Dependence on GC Content

MicroRNAs (miRNAs) are small non-coding RNAs responsible for fine-tuning of gene expression at post-transcriptional level. The alterations in miRNA expression levels profoundly affect human health and often lead to the development of severe diseases. Currently, high throughput analyses, such as microarray and deep sequencing, are performed in order to identify miRNA biomarkers, using archival patient tissue samples. MiRNAs are more robust than longer RNAs, and resistant to extreme temperatures, pH, and formalin-fixed paraffin-embedding (FFPE) process. Here, we have compared the stability of miRNAs in FFPE cardiac tissues using next-generation sequencing. The mode read length in FFPE samples was 11 nucleotides (nt), while that in the matched frozen samples was 22 nt. Although the read counts were increased 1.7-fold in FFPE samples, compared with those in the frozen samples, the average miRNA mapping rate decreased from 32.0% to 9.4%. These results indicate that, in addition to the fragmentation of longer RNAs, miRNAs are to some extent degraded in FFPE tissues as well. The expression profiles of total miRNAs in two groups were highly correlated (0.88 <r < 0.92). However, the relative read count of each miRNA was different depending on the GC content (p<0.0001). The unequal degradation of each miRNA affected the abundance ranking in the library, and miR-133a was shown to be the most abundant in FFPE cardiac tissues instead of miR-1, which was predominant before fixation. Subsequent quantitative PCR (qPCR) analyses revealed that miRNAs with GC content of less than 40% are more degraded than GC-rich miRNAs (p<0.0001). We showed that deep sequencing data obtained using FFPE samples cannot be directly compared with that of fresh frozen samples. The combination of miRNA deep sequencing and other quantitative analyses, such as qPCR, may improve the utility of archival FFPE tissue samples.

Evaluating biomarkers to model cancer risk post cosmic ray exposure

Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing biomarkers and to evaluate the potential for biomarkers to inform models of post exposure cancer risk. Because cellular stress response pathways to space radiation and environmental carcinogens share common nodes, biomarker-driven risk models may be broadly applicable for estimating risks for other carcinogens.

Measure transcript integrity using RNA-seq data

Background

Stored biological samples with pathology information and medical records are invaluable resources for translational medical research. However, RNAs extracted from the archived clinical tissues are often substantially degraded. RNA degradation distorts the RNA-seq read coverage in a gene-specific manner, and has profound influences on whole-genome gene expression profiling.

Result

We developed the transcript integrity number (TIN) to measure RNA degradation. When applied to 3 independent RNA-seq datasets, we demonstrated TIN is a reliable and sensitive measure of the RNA degradation at both transcript and sample level. Through comparing 10 prostate cancer clinical samples with lower RNA integrity to 10 samples with higher RNA quality, we demonstrated that calibrating gene expression counts with TIN scores could effectively neutralize RNA degradation effects by reducing false positives and recovering biologically meaningful pathways. When further evaluating the performance of TIN correction using spike-in transcripts in RNA-seq data generated from the Sequencing Quality Control consortium, we found TIN adjustment had better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91, accuracy = 0.90), as compared to gene expression analysis results without TIN correction (sensitivity = 0.98, specificity = 0.50, accuracy = 0.86).

Conclusion

TIN is a reliable measurement of RNA integrity and a valuable approach used to neutralize in vitro RNA degradation effect and improve differential gene expression analysis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0922-z) contains supplementary material, which is available to authorized users.

Strategies for modulating innate immune activation and protein production of in vitro transcribed mRNAs

Synthetic mRNA has recently shown great potential as a tool for genetic introduction of proteins. Its utility as a gene carrier has been demonstrated in several studies for both the introduction of therapeutic proteins and subunit vaccines. At one point, synthetic mRNA was believed to be too immunogenic and labile for pharmaceutical purposes. However, the development of several strategies have enabled mRNA technology to overcome these challenges, including incorporation of modified nucleotides, codon optimization of the coding region, incorporation of untranslated regions into the mRNA, and the use of delivery vehicles. While these approaches have been shown to enhance performance of some mRNA constructs, gene-to-gene variation and low efficiency of mRNA protein production are still significant hurdles. Further mechanistic understanding of how these strategies affect protein production and innate immune activation is needed for the widespread adoption for both therapeutic and vaccine applications. This review highlights key studies involved in the development of strategies employed to increase protein expression and control the immunogenicity of synthetic mRNA. Areas in the literature where improved understanding is needed will also be discussed.

Transcriptome outlier analysis implicates schizophrenia susceptibility genes and enriches putatively functional rare genetic variants

We searched a gene expression dataset comprised of 634 schizophrenia (SZ) cases and 713 controls for expression outliers (i.e., extreme tails of the distribution of transcript expression values) with SZ cases overrepresented compared with controls. These outlier genes were enriched for brain expression and for genes known to be associated with neurodevelopmental disorders. SZ cases showed higher outlier burden (i.e., total outlier events per subject) than controls for genes within copy number variants (CNVs) associated with SZ or neurodevelopmental disorders. Outlier genes were enriched for CNVs and for rare putative regulatory variants, but this only explained a small proportion of the outlier subjects, highlighting the underlying presence of additional genetic and potentially, epigenetic mechanisms.

Post-transcriptional regulation of cytokine signaling by AU-rich and GU-rich elements

Cytokines are necessary for cell communication to enable responses to external stimuli that are imperative for the survival and maintenance of homeostasis. Dysfunction of the cytokine network has detrimental effects on intra- and extracellular environments. Thus, it is critical that the expression of cytokines and the signals transmitted by cytokines to target cells are tightly regulated at numerous levels, including transcriptional and post-transcriptional levels. Here, we briefly summarize the role of AU-rich elements (AREs) in the regulation of cytokine gene expression at the post-transcriptional level and describe a role for GU-rich elements (GREs) in coordinating the regulation of cytokine signaling. GREs function as post-transcriptional regulators of proteins that control cellular activation, growth, and apoptosis. GREs and AREs work in concert to coordinate cytokine signal transduction pathways. The precise regulation of cytokine signaling is particularly important, because its dysregulation can lead to human diseases.

Decoding mechanisms by which silent codon changes influence protein biogenesis and function

SCOPE

Synonymous codon usage has been a focus of investigation since the discovery of the genetic code and its redundancy. The occurrences of synonymous codons vary between species and within genes of the same genome, known as codon usage bias. Today, bioinformatics and experimental data allow us to compose a global view of the mechanisms by which the redundancy of the genetic code contributes to the complexity of biological systems from affecting survival in prokaryotes, to fine tuning the structure and function of proteins in higher eukaryotes. Studies analyzing the consequences of synonymous codon changes in different organisms have revealed that they impact nucleic acid stability, protein levels, structure and function without altering amino acid sequence. As such, synonymous mutations inevitably contribute to the pathogenesis of complex human diseases. Yet, fundamental questions remain unresolved regarding the impact of silent mutations in human disorders. In the present review we describe developments in this area concentrating on mechanisms by which synonymous mutations may affect protein function and human health.

PURPOSE

This synopsis illustrates the significance of synonymous mutations in disease pathogenesis. We review the different steps of gene expression affected by silent mutations, and assess the benefits and possible harmful effects of codon optimization applied in the development of therapeutic biologics.

PHYSIOLOGICAL AND MEDICAL RELEVANCE

Understanding mechanisms by which synonymous mutations contribute to complex diseases such as cancer, neurodegeneration and genetic disorders, including the limitations of codon-optimized biologics, provides insight concerning interpretation of silent variants and future molecular therapies.

Increased expression of X-linked genes in mammals is associated with a higher stability of transcripts and an increased ribosome density

Mammalian sex chromosomes evolved from the degeneration of one homolog of a pair of ancestral autosomes, the proto-Y. This resulted in a gene dose imbalance that is believed to be restored (partially or fully) through upregulation of gene expression from the single active X-chromosome in both sexes by a dosage compensatory mechanism. We analyzed multiple genome-wide RNA stability data sets and found significantly longer average half-lives for X-chromosome transcripts than for autosomal transcripts in various human cell lines, both male and female, and in mice. Analysis of ribosome profiling data shows that ribosome density is higher on X-chromosome transcripts than on autosomal transcripts in both humans and mice, suggesting that the higher stability is causally linked to a higher translation rate. Our results and observations are in accordance with a dosage compensatory upregulation of expressed X-linked genes. We therefore propose that differential mRNA stability and translation rates of the autosomes and sex chromosomes contribute to an evolutionarily conserved dosage compensation mechanism in mammals.

Transcription-coupled RNA surveillance in human genetic diseases caused by splice site mutations

Current estimates indicate that approximately one-third of all disease-causing mutations are expected to disrupt splicing. Abnormal splicing often leads to disruption of the reading frame with introduction of a premature termination codon (PTC) that targets the mRNA for degradation in the cytoplasm by nonsense mediated decay (NMD). In addition to NMD there are RNA surveillance mechanisms that act in the nucleus while transcripts are still associated with the chromatin template. However, the significance of nuclear RNA quality control in the context of human genetic diseases is unknown. Here we used patient-derived lymphoblastoid cell lines as disease models to address how biogenesis of mRNAs is affected by splice site mutations. We observed that most of the mutations analyzed introduce PTCs and trigger mRNA degradation in the cytoplasm. However, for some mutant transcripts, RNA levels associated with chromatin were found down-regulated. Quantification of nascent transcripts further revealed that a subset of genes containing splicing mutations (SM) have reduced transcriptional activity. Following treatment with the translation inhibitor cycloheximide the cytoplasmic levels of mutant RNAs increased, while the levels of chromatin-associated transcripts remained unaltered. These results suggest that transcription-coupled surveillance mechanisms operate independently from NMD to reduce cellular levels of abnormal RNAs caused by SM.