Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast

Inferring gene-pathway associations from consolidated transcriptome datasets: an interactive gene network explorer for Tetrahymena thermophila

Although an established model organism, Tetrahymena thermophila remains comparatively inaccessible to high throughput screens, and alternative bioinformatic approaches still rely on unconnected datasets and outdated algorithms. Here, we report a new approach to consolidating RNA-seq and microarray data based on a systematic exploration of parameters and computational controls, enabling us to infer functional gene associations from their co-expression patterns. To illustrate the power of this approach, we took advantage of new data regarding a previously studied pathway, the biogenesis of a secretory organelle called the mucocyst. Our untargeted clustering approach recovered over 80% of the genes that were previously verified to play a role in mucocyst biogenesis. Furthermore, we tested four new genes that we predicted to be mucocyst-associated based on their co-expression and found that knocking out each of them results in mucocyst secretion defects. We also found that our approach succeeds in clustering genes associated with several other cellular pathways that we evaluated based on prior literature. We present the Tetrahymena Gene Network Explorer (TGNE) as an interactive tool for genetic hypothesis generation and functional annotation in this organism and as a framework for building similar tools for other systems.

Regulation of the expression of ferrochelatase in a murine model of diabetes mellitus type I

Background

Diabetes produces changes on cellular hemeprotein metabolism. The last enzyme of heme biosynthetic pathway is ferrochelatase (FECH), an enzyme that catalyzes the insertion of ferrous ion into protoporphyrin IX to produce heme. The aim of this work was to investigate whether FECH expression can be other key point in the regulation of heme biosynthesis in diabetic animals.

Methods

Mice were rendered diabetic with streptozotocin (STZ, 170 mg/kg body weight i.p. for 15 days). Liver FECH protein and mRNA levels were evaluated by Western blot and Northern blot respectively. Vanadate was used as a hypoglycemic agent. The levels of the transcription factor Sp1 bound to the FECH promoter were assessed by chromatin immunoprecipitation (ChIP).

Results

Hyperglycemia caused an increase in FECH mRNA levels but no changes in FECH protein expression. ChIP analysis revealed that the increase in FECH mRNA levels was due to enhanced Sp1 binding to the FECH promoter in diabetic animals, which was reduced by vanadate administration.

Conclusions

In diabetic animals, enhanced binding of Sp1 to the FECH promoter may be responsible for the increase in FECH mRNA levels. However, this increase was not reflected in the amount of FECH protein, which would confirm that FECH could be another control point in heme synthesis.

Turnover atlas of proteome and phosphoproteome across mouse tissues and brain regions

Understanding how proteins in different mammalian tissues are regulated is central to biology. Protein abundance, turnover, and post-translational modifications such as phosphorylation are key factors that determine tissue-specific proteome properties. However, these properties are challenging to study across tissues and remain poorly understood. Here, we present Turnover-PPT, a comprehensive resource mapping the abundance and lifetime of 11,000 proteins and 40,000 phosphosites in eight mouse tissues and various brain regions using advanced proteomics and stable isotope labeling. We reveal tissue-specific short- and long-lived proteins, strong correlations between interacting protein lifetimes, and distinct impacts of phosphorylation on protein turnover. Notably, we discover a remarkable pattern of turnover changes for peroxisome proteins in specific tissues and that phosphorylation regulates the stability of neurodegeneration-related proteins, such as Tau and α-synuclein. Thus, Turnover-PPT provides fundamental insights into protein stability, tissue dynamic proteotypes, and functional protein phosphorylation and is accessible via an interactive web-based portal at https://yslproteomics.shinyapps.io/tissuePPT.

Macroevolutionary divergence of gene expression driven by selection on protein abundance

The regulation of messenger RNA (mRNA) and protein abundances is well-studied, but less is known about the evolutionary processes shaping their relationship. To address this, we derived a new phylogenetic model and applied it to multispecies mammalian data. Our analyses reveal (i) strong stabilizing selection on protein abundances over macroevolutionary time, (ii) mutations affecting mRNA abundances minimally impact protein abundances, (iii) mRNA abundances evolve under selection to align with protein abundances, and (iv) mRNA abundances adapt faster than protein abundances owing to greater mutational opportunity. These conclusions are supported by comparisons of model parameters with independent functional genomic data. By decomposing mutational and selective influences on mRNA-protein dynamics, our approach provides a framework for discovering the evolutionary rules that drive divergence in gene expression.

Inferring gene-pathway associations from consolidated transcriptome datasets: an interactive gene network explorer for Tetrahymena thermophila

Although an established model organism, Tetrahymena thermophila remains comparatively inaccessible to high throughput screens, and alternative bioinformatic approaches still rely on unconnected datasets and outdated algorithms. Here, we report a new approach to consolidating RNA-seq and microarray data based on a systematic exploration of parameters and computational controls, enabling us to infer functional gene associations from their co-expression patterns. To illustrate the power of this approach, we took advantage of new data regarding a previously studied pathway, the biogenesis of a secretory organelle called the mucocyst. Our untargeted clustering approach recovered over 80% of the genes that were previously verified to play a role in mucocyst biogenesis. Furthermore, we tested four new genes that we predicted to be mucocyst-associated based on their co-expression and found that knocking out each of them results in mucocyst secretion defects. We also found that our approach succeeds in clustering genes associated with several other cellular pathways that we evaluated based on prior literature. We present the Tetrahymena Gene Network Explorer (TGNE) as an interactive tool for genetic hypothesis generation and functional annotation in this organism and as a framework for building similar tools for other systems.

Hypnea musciformis Seaweed Extract Protected Human Mesenchymal Stem Cells From Oxidative Stress Through NRF2 Activation

Previous studies have shown that Hypnea musciformis seaweed extracts (HMEs) possess antioxidant properties, but the molecular mechanisms accounting for this activity are not known. Thus, the present study investigated the molecular mechanisms through which HME exerted its antioxidant activity in human mesenchymal stem cells (WJ-MSCs). After the isolation of HME, its chemical composition was analyzed with gas chromatography mass spectrometry, indicating that it contained amino acids, organic acids, organic amides, sugar alcohols, saturated fatty acids, hydrogenated diterpene alcohols, and other organic compounds. Afterward, HME was shown in vitro to scavenge DPPH·, ABTS·+, ·OH, and O2 ·- radicals, possess reducing activity, and protect from ROO·-induced DNA strand breakage. Finally, the results showed that HME treatment of WJ-MSCs prevented H2O2-induced oxidative stress by decreasing lipid peroxidation, protein oxidation, reactive oxygen species levels, and DNA damage and by increasing glutathione levels. Moreover, our findings showed for the first time that HME's antioxidant activity in WJ-MSCs was mediated through the activation of NRF2, which upregulated the expression of the antioxidant proteins GCLC, GSR, HMOX1, SOD1, TXN, and GPX1. These results provide new insights into H. musciformis' antioxidant properties, which could help substantially its use as a food supplement or for developing biofunctional foods.

Multi-omics analysis of aggregative multicellularity

All organisms have to carefully regulate their gene expression, not least during development. mRNA levels are often used as proxy for protein output; however, this approach ignores post-transcriptional effects. In particular, mRNA-protein correlation remains elusive for organisms that exhibit aggregative rather than clonal multicellularity. We addressed this issue by generating a paired transcriptomics and proteomics time series during the transition from uni-to multicellular stage in the social ameba Dictyostelium discoideum. Our data reveals that mRNA and protein levels correlate highly during unicellular growth, but decrease when multicellular development is initiated. This accentuates that transcripts alone cannot accurately predict protein levels. The dataset provides a useful resource to study gene expression during aggregative multicellular development. Additionally, our study provides an example of how to analyze and visualize mRNA and protein levels, which should be broadly applicable to other organisms and conditions.

Patterns of protein synthesis in the budding yeast cell cycle: variable or constant?

Proteins are the principal macromolecular constituent of proliferating cells, and protein synthesis is viewed as a primary metric of cell growth. While there are celebrated examples of proteins whose levels are periodic in the cell cycle (e.g., cyclins), the concentration of most proteins was not thought to change in the cell cycle, but some recent results challenge this notion. The 'bulk' protein is the focus of this article, specifically the rate of its synthesis, in the budding yeast Saccharomyces cerevisiae.

Single-molecule fluorescence multiplexing by multi-parameter spectroscopic detection of nanostructured FRET labels

Multiplexed, real-time fluorescence detection at the single-molecule level can reveal the stoichiometry, dynamics and interactions of multiple molecular species in mixtures and other complex samples. However, fluorescence-based sensing is typically limited to the detection of just 3-4 colours at a time due to low signal-to-noise ratio, high spectral overlap and the need to maintain the chemical compatibility of dyes. Here we engineered a palette of several dozen composite fluorescent labels, called FRETfluors, for multiplexed spectroscopic measurements at the single-molecule level. FRETfluors are compact nanostructures constructed from three chemical components (DNA, Cy3 and Cy5) with tunable spectroscopic properties due to variations in geometry, fluorophore attachment chemistry and DNA sequence. We demonstrate FRETfluor labelling and detection for low-concentration (<100 fM) mixtures of mRNA, dsDNA and proteins using an anti-Brownian electrokinetic trap. In addition to identifying the unique spectroscopic signature of each FRETfluor, this trap differentiates FRETfluors attached to a target from unbound FRETfluors, enabling wash-free sensing. Although usually considered an undesirable complication of fluorescence, here the inherent sensitivity of fluorophores to the local physicochemical environment provides a new design axis complementary to changing the FRET efficiency. As a result, the number of distinguishable FRETfluor labels can be combinatorically increased while chemical compatibility is maintained, expanding prospects for spectroscopic multiplexing at the single-molecule level using a minimal set of chemical building blocks.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Co-translational Assembly Pathways of Nuclear Multiprotein Complexes Involved in the Regulation of Gene Transcription

Most factors that regulate gene transcription in eukaryotic cells are multimeric, often large, protein complexes. The understanding of the biogenesis pathways of such large and heterogeneous protein assemblies, as well as the dimerization partner choice among transcription factors, is crucial to interpret and control gene expression programs and consequent cell fate decisions. Co-translational assembly (Co-TA) is thought to play key roles in the biogenesis of protein complexes by directing complex formation during protein synthesis. In this review we discuss the principles of Co-TA with a special focus for the assembly of transcription regulatory complexes. We outline the expected molecular advantages of establishing co-translational interactions, pointing at the available, or missing, evidence for each of them. We hypothesize different molecular mechanisms based on Co-TA to explain the allocation "dilemma" of paralog proteins and subunits shared by different transcription complexes. By taking as a paradigm the different assembly pathways employed by three related transcription regulatory complexes (TFIID, SAGA and ATAC), we discuss alternative Co-TA strategies for nuclear multiprotein complexes and the widespread - yet specific - use of Co-TA for the formation of nuclear complexes involved in gene transcription. Ultimately, we outlined a series of open questions which demand well-defined lines of research to investigate the principles of gene regulation that rely on the coordinated assembly of protein complexes.

Decoding the Heterogeneity and Specialized Function of Translation Machinery Through Ribosome Profiling in Yeast Mutants of Initiation Factors

The nuanced heterogeneity and specialized functions of translation machinery are increasingly recognized as crucial for precise translational regulation. Here, high-throughput ribosomal profiling (ribo-seq) is used to analyze the specialized roles of eukaryotic initiation factors (eIFs) in the budding yeast. By examining changes in ribosomal distribution across the genome resulting from knockouts of eIF4A, eIF4B, eIF4G1, CAF20, or EAP1, or knockdowns of eIF1, eIF1A, eIF4E, or PAB1, two distinct initiation-factor groups, the "looping" and "scanning" groups are discerned, based on similarities in the ribosomal landscapes their perturbation induced. The study delves into the cis-regulatory sequence features of genes influenced predominantly by each group, revealing that genes more dependent on the looping-group factors generally have shorter transcripts and poly(A) tails. In contrast, genes more dependent on the scanning-group factors often possess upstream open reading frames and exhibit a higher GC content in their 5' untranslated regions. From the ribosomal RNA fragments identified in the ribo-seq data, ribosomal heterogeneity associated with perturbation of specific initiation factors is further identified, suggesting their potential roles in regulating ribosomal components. Collectively, the study illuminates the complexity of translational regulation driven by heterogeneity and specialized functions of translation machinery, presenting potential approaches for targeted gene translation manipulation.

GSTM2 alleviates heart failure by inhibiting DNA damage in cardiomyocytes

BACKGROUND

Heart failure (HF) seriously threatens human health worldwide. However, the pathological mechanisms underlying HF are still not fully clear.

RESULTS

In this study, we performed proteomics and transcriptomics analyses on samples from human HF patients and healthy donors to obtain an overview of the detailed changes in protein and mRNA expression that occur during HF. We found substantial differences in protein expression changes between the atria and ventricles of myocardial tissues from patients with HF. Interestingly, the metabolic state of ventricular tissues was altered in HF samples, and inflammatory pathways were activated in atrial tissues. Through analysis of differentially expressed genes in HF samples, we found that several glutathione S-transferase (GST) family members, especially glutathione S-transferase M2-2 (GSTM2), were decreased in all the ventricular samples. Furthermore, GSTM2 overexpression effectively relieved the progression of cardiac hypertrophy in a transverse aortic constriction (TAC) surgery-induced HF mouse model. Moreover, we found that GSTM2 attenuated DNA damage and extrachromosomal circular DNA (eccDNA) production in cardiomyocytes, thereby ameliorating interferon-I-stimulated macrophage inflammation in heart tissues.

CONCLUSIONS

Our study establishes a proteomic and transcriptomic map of human HF tissues, highlights the functional importance of GSTM2 in HF progression, and provides a novel therapeutic target for HF.

Discordant skeletal muscle gene and protein responses to exercise

The ability of skeletal muscle to adapt to repeated contractile stimuli is one of the most intriguing aspects of physiology. The molecular bases underpinning these adaptations involve increased protein activity and/or expression, mediated by an array of pre- and post-transcriptional processes, as well as translational and post-translational control. A longstanding dogma assumes a direct relationship between exercise-induced increases in mRNA levels and subsequent changes in the abundance of the proteins they encode. Drawing on the results of recent studies, we dissect and question the common assumption of a direct relationship between changes in the skeletal muscle transcriptome and proteome induced by repeated muscle contractions (e.g., exercise).

On the Decoupling of Evolutionary Changes in mRNA and Protein Levels

Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here, we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level; this observation held true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and the translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic data.

Single-cell quantification of ribosome occupancy in early mouse development

Translation regulation is critical for early mammalian embryonic development¹. However, previous studies had been restricted to bulk measurements², precluding precise determination of translation regulation including allele-specific analyses. Here, to address this challenge, we developed a novel microfluidic isotachophoresis (ITP) approach, named RIBOsome profiling via ITP (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. We identified differential translation efficiency as a key mechanism regulating genes involved in centrosome organization and N⁶-methyladenosine modification of RNAs. Our high-coverage measurements enabled, to our knowledge, the first analysis of allele-specific ribosome engagement in early development. These led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes and reduced translation efficiency of transcripts exhibiting allele-biased expression. By integrating our measurements with proteomics data, we discovered that ribosome occupancy in germinal vesicle-stage oocytes is the predominant determinant of protein abundance in the zygote. The Ribo-ITP approach will enable numerous applications by providing high-coverage and high-resolution ribosome occupancy measurements from ultra-low input samples including single cells.

Integration of a multi-omics stem cell differentiation dataset using a dynamical model

Stem cell differentiation is a highly dynamic process involving pervasive changes in gene expression. The large majority of existing studies has characterized differentiation at the level of individual molecular profiles, such as the transcriptome or the proteome. To obtain a more comprehensive view, we measured protein, mRNA and microRNA abundance during retinoic acid-driven differentiation of mouse embryonic stem cells. We found that mRNA and protein abundance are typically only weakly correlated across time. To understand this finding, we developed a hierarchical dynamical model that allowed us to integrate all data sets. This model was able to explain mRNA-protein discordance for most genes and identified instances of potential microRNA-mediated regulation. Overexpression or depletion of microRNAs identified by the model, followed by RNA sequencing and protein quantification, were used to follow up on the predictions of the model. Overall, our study shows how multi-omics integration by a dynamical model could be used to nominate candidate regulators.

Consequences of poly(ethylene oxide) and poloxamer P188 on transcription in healthy and stressed myoblasts

Poly(ethylene oxide) (PEO) and poloxamers, a class of poly(ethylene oxide)-b-poly(propylene oxide)-b-poly(ethylene oxide) (PEO-PPO-PEO) triblock copolymers, have many personal and medical care applications, including the stabilization of stressed cellular membranes. Despite the widespread use, the cellular transcriptional response to these molecules is relatively unknown. C2C12 myoblasts, a model muscle cell, were subjected to short-term Poloxamer 188 (P188) and PEO181 (8,000 g/mol) treatment in culture. RNA was extracted and sequenced to quantify transcriptomic impact. The addition of moderate concentrations (14 µM) of either polymer to unstressed cells caused substantial differential gene expression, including at least twofold modulation of 357 and 588 genes, respectively. In addition, evaluation of the transcriptome response to osmotic stress without polymer treatment revealed dramatic change in RNA expression. Interestingly, the addition of polymer to stressed cells-at concentrations that provide physiological protection-did not yield a significant difference in expression of any gene relative to stress alone. Genome-scale expression analysis was corroborated by single-gene quantitative real-time PCR. Changes in protein expression were measured via western blot, which revealed partial alignment with the RNA results. Collectively, the significant changes to expression of multiple genes and resultant protein translation demonstrates an unexpectedly broad biochemical response to these polymers in healthy myoblasts in vitro. Meanwhile, the lack of substantial transcriptional response to polymer treatment in stressed cells highlights the physical nature of that protective mechanism.

Decoupling of evolutionary changes in mRNA and protein levels

Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level, which is true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and its translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic studies.

Ribosome profiling reveals the translational landscape and allele-specific translational efficiency in rice

Translational regulation is a critical step in the process of gene expression and governs the synthesis of proteins from mRNAs. Many studies have revealed translational regulation in plants in response to various environmental stimuli. However, there have been no studies documenting the comprehensive landscape of translational regulation and allele-specific translational efficiency in multiple plant tissues, especially those of rice, a main staple crop that feeds nearly half of the world's population. Here we used RNA sequencing and ribosome profiling data to analyze the transcriptome and translatome of an elite hybrid rice, Shanyou 63 (SY63), and its parental varieties Zhenshan 97 and Minghui 63. The results revealed that gene expression patterns varied more among tissues than among varieties at the transcriptional and translational levels. We identified 3392 upstream open reading frames (uORFs), and the uORF-containing genes were enriched in transcription factors. Only 668 of 13 492 long non-coding RNAs could be translated into peptides. Finally, we discovered numerous genes with allele-specific translational efficiency in SY63 and demonstrated that some cis-regulatory elements may contribute to allelic divergence in translational efficiency. Overall, these findings may improve our understanding of translational regulation in rice and provide information for molecular breeding research.

Neuronal P2X4 receptor may contribute to peripheral inflammatory pain in rat spinal dorsal horn

Objective

Intense inflammation may result in pain, which manifests as spinal central sensitization. There is growing evidence that purinergic signaling plays a pivotal role in the orchestration of pain processing. Over the last decade the ionotropic P2X purino receptor 4 (P2X4) got into spotlight in neuropathic disorders, however its precise spinal expression was scantily characterized during inflammatory pain. Thus, we intended to analyze the receptor distribution within spinal dorsal horn and lumbar dorsal root ganglia (DRG) of rats suffering in inflammatory pain induced by complete Freund adjuvant (CFA).

Methods

CFA-induced peripheral inflammation was validated by mechanical and thermal behavioral tests. In order to ensure about the putative alteration of spinal P2X4 receptor gene expression qPCR reactions were designed, followed by immunoperoxidase and Western blot experiments to assess changes at a protein level. Colocalization of P2X4 with neuronal and glial markers was investigated by double immunofluorescent labelings, which were subsequently analyzed with IMARIS software. Transmission electronmicroscopy was applied to study the ultrastructural localization of the receptor. Concurrently, in lumbar DRG cells similar methodology has been carried out to complete our observations.

Results

The figures of mechanical and thermal behavioral tests proved the establishment of CFA-induced inflammatory pain. We observed significant enhancement of P2X4 transcript level within the spinal dorsal horn 3 days upon CFA administration. Elevation of P2X4 immunoreactivity within Rexed lamina I-II of the spinal gray matter was synchronous with mRNA expression, and confirmed by protein blotting. According to IMARIS analysis the robust protein increase was mainly detected on primary afferent axonterminals and GFAP-labelled astrocyte membrane compartments, but not on postsynaptic dendrites was also validated ultrastructurally within the spinal dorsal horn. Furthermore, lumbar DRG analysis demonstrated that peptidergic and non-peptidergic nociceptive subsets of ganglia cells were also abundantly positive for P2X4 receptor in CFA model.

Conclusion

Here we provide novel evidence about involvement of neuronal and glial P2X4 receptor in the establishment of inflammatory pain.

DNAJB8 facilitates autophagic-lysosomal degradation of viral Vif protein and restricts HIV-1 virion infectivity by rescuing APOBEC3G expression in host cells

HSP40/DNAJ family of proteins is the most diverse chaperone family, comprising about 49 isoforms in humans. Several reports have demonstrated the functional role of a few of these isoforms in the pathogenesis of various viruses, including HIV-1. Our earlier study has shown that several isoforms of HSP40 get significantly modulated at the mRNA level during HIV-1 infection in T cells. To explore the biological role of these significantly modulated isoforms, we analyzed their effect on HIV-1 gene expression and virus production using knockdown and overexpression studies. Among these isoforms, DNAJA3, DNAJB1, DNAJB7, DNAJC4, DNAJC5B, DNAJC5G, DNAJC6, DNAJC22, and DNAJC30 seem to positively regulate virus replication, whereas DNAJB3, DNAJB6, DNAJB8, and DNAJC5 negatively regulate virus replication. Further investigation on the infectivity of the progeny virion demonstrated that only DNAJB8 negatively regulates the progeny virion infectivity. It was further identified that DNAJB8 protein is involved in the downregulation of Vif protein, required for the infectivity of HIV-1 virions. DNAJB8 seems to direct Vif protein for autophagic-lysosomal degradation, leading to rescue of the cellular restriction factor APOBEC3G from Vif-mediated proteasomal degradation, resulting in enhanced packaging of APOBEC3G in budding virions and release of less infective progeny virion particles. Finally, our results also indicate that during the early stage of HIV-1 infection, enhanced expression of DNAJB8 promotes the production of less infective progeny virions, but at the later stage or at the peak of infection, reduced expression of DNJAB8 protein allows the HIV-1 to replicate and produce more infective progeny virion particles.

A dynamical stochastic model of yeast translation across the cell cycle

Translation is a central step in gene expression, however its quantitative and time-resolved regulation is poorly understood. We developed a discrete, stochastic model for protein translation in S. cerevisiae in a whole-transcriptome, single-cell context. A "base case" scenario representing an average cell highlights translation initiation rates as the main co-translational regulatory parameters. Codon usage bias emerges as a secondary regulatory mechanism through ribosome stalling. Demand for anticodons with low abundancy is shown to cause above-average ribosome dwelling times. Codon usage bias correlates strongly both with protein synthesis rates and elongation rates. Applying the model to a time-resolved transcriptome estimated by combining data from FISH and RNA-Seq experiments, it could be shown that increased total transcript abundance during the cell cycle decreases translation efficiency at single transcript level. Translation efficiency grouped by gene function shows highest values for ribosomal and glycolytic genes. Ribosomal proteins peak in S phase while glycolytic proteins rank highest in later cell cycle phases.

Multi-Omics Methods Applied to Flower Development

Developmental processes in multicellular organisms depend on the proficiency of cells to orchestrate different gene expression programs. Over the past years, several studies of reproductive organ development have considered genomic analyses of transcription factors and global gene expression changes, modeling complex gene regulatory networks. Nevertheless, the dynamic view of developmental processes requires, as well, the study of the proteome in its expression, complexity, and relationship with the transcriptome. In this chapter, we describe a dual extraction method-for protein and RNA-for the characterization of genome expression at proteome level and its correlation to transcript expression data. We also present a shotgun proteomic procedure (LC-MS/MS) followed by a pipeline for the imputation of missing values in mass spectrometry results.

YMLA: A comparative platform to carry out functional enrichment analysis for multiple gene lists in yeast

Comparative analysis among multiple gene lists on their functional features is now a routine task due to the advancement of high-throughput experiments. Several enrichment analysis tools were developed in the past. However, these tools mainly focus on one gene list and contain only gene ontology or interaction features. What makes it worse, comparative investigation and customized feature set reanalysis are still unavailable. Therefore, we constructed the YMLA (Yeast Multiple List Analyzer) platform in this research. YMLA includes 39 yeast features and facilitates comparative analysis among multiple gene lists via tabular views, heatmaps, and network plots. Moreover, the customized feature set reanalysis function was implemented in YMLA to help form mechanism hypotheses based on a selected enriched feature subset. We demonstrated the biological applicability of YMLA via example lists consisting of genes with top/bottom translation efficiency values. The analysis results provided by YMLA reveal novel facts consistent with previous experiments. YMLA is available at https://cosbi7.ee.ncku.edu.tw/YMLA/.

A Systematic Review on Attenuation of PCSK9 in Relation to Atherogenesis Biomarkers Associated with Natural Products or Plant Bioactive Compounds in In Vitro Studies: A Critique on the Quality and Imprecision of Studies

A systematic review was performed to identify all the related publications describing PCSK9 and atherogenesis biomarkers attenuation associated with a natural product and plant bioactive compounds in in vitro studies. This review emphasized the imprecision and quality of the included research rather than the detailed reporting of the results. Literature searches were conducted in Scopus, PubMed, and Science Direct from 2003 until 2021, following the Cochrane handbook. The screening of titles, abstracts, and full papers was performed by two independent reviewers, followed by data extraction and validity. Study quality and validity were assessed using the Imprecision Tool, Model, and Marker Validity Assessment that has been developed for basic science studies. A total of 403 articles were identified and 31 of those that met the inclusion criteria were selected. 13 different atherogenesis biomarkers in relation to PCSK9 were found, and the most studied biomarkers are LDLR, SREBP, and HNF1α. In terms of quality, our review suggests that the basic science study in investigating atherogenesis biomarkers is deficient in terms of imprecision and validity.

Relative specificity as an important consideration in the big data era

Technological breakthroughs such as high-throughput methods, genomics, single-cell studies, and machine learning have fundamentally transformed research and ushered in the big data era of biology. Nevertheless, current data collections, analyses, and modeling frequently overlook relative specificity, a crucial property of molecular interactions in biochemical systems. Relative specificity describes how, for example, an enzyme reacts with its many substrates at different rates, and how this discriminatory action alone is sufficient to modulate the substrates and downstream events. As a corollary, it is not only important to comprehensively identify an enzyme’s substrates, but also critical to quantitatively determine how the enzyme interacts with the substrates and to evaluate how it shapes subsequent biological outcomes. Genomics and high-throughput techniques have greatly facilitated the studies of relative specificity in the 21st century, and its functional significance has been demonstrated in complex biochemical systems including transcription, translation, protein kinases, RNA-binding proteins, and animal microRNAs (miRNAs), although it remains ignored in most work. Here we analyze recent findings in big data and relative specificity studies and explain how the incorporation of relative specificity concept might enhance our mechanistic understanding of gene functions, biological phenomena, and human diseases.

Experimental reproducibility limits the correlation between mRNA and protein abundances in tumor proteomic profiles

Large-scale studies of human proteomes have revealed only a moderate correlation between mRNA and protein abundances. It is unclear to what extent this moderate correlation reflects post-transcriptional regulation and to what extent it reflects measurement error. Here, by analyzing replicate profiles of tumors and cell lines, we show that there is considerable variation in the reproducibility of measurements of transcripts and proteins from individual genes. Proteins with more reproducible measurements tend to have a higher mRNA-protein correlation, suggesting that measurement reproducibility accounts for a substantial fraction of the unexplained variation between mRNA and protein abundances. The reproducibility of individual proteins is somewhat consistent across studies, and we exploit this to develop an aggregate reproducibility score that explains a substantial amount of the variation in mRNA-protein correlations across multiple studies. Finally, we show that pathways previously reported to have a higher-than-average mRNA-protein correlation may simply contain members that can be more reproducibly quantified.

The dynamic proteome in Arabidopsis thaliana early embryogenesis

The morphology of the flowering plant is established during early embryogenesis. In recent years, many studies have focused on transcriptional profiling in plant embryogenesis, but the dynamic landscape of the Arabidopsis thaliana proteome remains elusive. In this study, Arabidopsis embryos at 2/4-cell, 8-cell, 16-cell, 32-cell, globular and heart stages were collected for nanoproteomic analysis. In total, 5386 proteins were identified. Of these, 1051 proteins were universally identified in all developmental stages and a range of 27 to 2154 proteins was found to be stage specific. These proteins could be grouped into eight clusters according to their expression levels. Gene Ontology enrichment analysis showed that genes involved in ribosome biogenesis and auxin-activated signalling were enriched during early embryogenesis, indicating that active translation and auxin signalling are important events in Arabidopsis embryo development. Combining RNA-sequencing data with the proteomics analysis, the correlation between mRNA and protein was evaluated. An overall positive correlation was found between mRNA and protein. This work provides a comprehensive landscape of the Arabidopsis proteome in early embryogenesis. Some important proteins/transcription factors identified through network analysis may serve as potential targets for future investigation.

Mass spectrometry-based draft of the mouse proteome

The laboratory mouse ranks among the most important experimental systems for biomedical research and molecular reference maps of such models are essential informational tools. Here, we present a quantitative draft of the mouse proteome and phosphoproteome constructed from 41 healthy tissues and several lines of analyses exemplify which insights can be gleaned from the data. For instance, tissue- and cell-type resolved profiles provide protein evidence for the expression of 17,000 genes, thousands of isoforms and 50,000 phosphorylation sites in vivo. Proteogenomic comparison of mouse, human and Arabidopsis reveal common and distinct mechanisms of gene expression regulation and, despite many similarities, numerous differentially abundant orthologs that likely serve species-specific functions. We leverage the mouse proteome by integrating phenotypic drug (n > 400) and radiation response data with the proteomes of 66 pancreatic ductal adenocarcinoma (PDAC) cell lines to reveal molecular markers for sensitivity and resistance. This unique atlas complements other molecular resources for the mouse and can be explored online via ProteomicsDB and PACiFIC.

Proteome allocations change linearly with the specific growth rate of Saccharomyces cerevisiae under glucose limitation

Saccharomyces cerevisiae is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of S. cerevisiae by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis.

Diverse impact of N-acetylcysteine or alpha-lipoic acid supplementation during high-fat diet regime on fatty acid transporters in visceral and subcutaneous adipose tissue

PURPOSE

Adipose tissue's (AT) structural changes accompanying obesity may alter lipid transport protein expression and, thus, the fatty acids (FAs) transport and lipid balance of the body. Metabolic abnormalities within AT contribute to the elevated production of reactive oxygen species and increased oxidative/nitrosative stress. Although compounds such as N-acetylcysteine (NAC) and α-lipoic acid (ALA), which restore redox homeostasis, may improve lipid metabolism in AT, the mechanism of action of these antioxidants on lipid metabolism in AT is still unknown. This study aimed to examine the impact of NAC and ALA on the level and FA composition of the lipid fractions, and the expression of FA transporters in the visceral and subcutaneous AT of high-fat diet-fed rats.

MATERIALS AND METHODS

Male Wistar rats were randomly divided into four groups. The mRNA levels and protein expression of FA transporters were assessed using real-time PCR and Western Blot analyses. The collected samples were subjected to histological evaluation. The level of lipids (FFA, DAG, and TAG) was measured using gas-liquid chromatography.

RESULTS

We found that antioxidants affect FA transporter expressions at both the transcript and protein levels, and, therefore, they promote changes in AT's lipid pools. One of the most remarkable findings of our research is that different antioxidant molecules may have a varying impact on AT phenotype.

CONCLUSION

NAC and ALA exert different influences on AT, which is reflected in histopathological images, FA transport proteins expression patterns, or even the lipid storage capacity of adipocytes.

Growth-rate-dependent and nutrient-specific gene expression resource allocation in fission yeast

Cellular resources are limited and their relative allocation to gene expression programmes determines physiological states and global properties such as the growth rate. Here, we determined the importance of the growth rate in explaining relative changes in protein and mRNA levels in the simple eukaryote Schizosaccharomyces pombe grown on non-limiting nitrogen sources. Although expression of half of fission yeast genes was significantly correlated with the growth rate, this came alongside wide-spread nutrient-specific regulation. Proteome and transcriptome often showed coordinated regulation but with notable exceptions, such as metabolic enzymes. Genes positively correlated with growth rate participated in every level of protein production apart from RNA polymerase II-dependent transcription. Negatively correlated genes belonged mainly to the environmental stress response programme. Critically, metabolic enzymes, which represent ∼55-70% of the proteome by mass, showed mostly condition-specific regulation. In summary, we provide a rich account of resource allocation to gene expression in a simple eukaryote, advancing our basic understanding of the interplay between growth-rate-dependent and nutrient-specific gene expression.

Heat stress regulates the expression of TPK1 gene at transcriptional and post-transcriptional levels in Saccharomyces cerevisiae

In Saccharomyces cerevisiae cAMP regulates different cellular processes through PKA. The specificity of the response of the cAMP-PKA pathway is highly regulated. Here we address the mechanism through which the cAMP-PKA pathway mediates its response to heat shock and thermal adaptation in yeast. PKA holoenzyme is composed of a regulatory subunit dimer (Bcy1) and two catalytic subunits (Tpk1, Tpk2, or Tpk3). PKA subunits are differentially expressed under certain growth conditions. Here we demonstrate the increased abundance and half-life of TPK1 mRNA and the assembly of this mRNA in cytoplasmic foci during heat shock at 37 °C. The resistance of the foci to cycloheximide-induced disassembly along with the polysome profiling analysis suggest that TPK1 mRNA is impaired for entry into translation. TPK1 expression was also evaluated during a recurrent heat shock and thermal adaptation. Tpk1 protein level is significantly increased during the recovery periods. The crosstalk of cAMP-PKA pathway and CWI signalling was also studied. Wsc3 sensor and some components of the CWI pathway are necessary for the TPK1 expression upon heat shock. The assembly in foci upon thermal stress depends on Wsc3. Tpk1 expression is lower in a wsc3∆ mutant than in WT strain during thermal adaptation and thus the PKA levels are also lower. An increase in Tpk1 abundance in the PKA holoenzyme in response to heat shock is presented, suggesting that a recurrent stress enhanced the fitness for the coming favourable conditions. Therefore, the regulation of TPK1 expression by thermal stress contributes to the specificity of cAMP-PKA signalling.

Increased expression of the fluorescent reporter protein ymNeonGreen in Saccharomyces cerevisiae by reducing RNA secondary structure near the start codon

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Stable secondary RNA structure 3′ of the start codon inhibits ymNeonGreen expression.

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Removing secondary RNA structure increased expression in S. cerevisiae and E. coli.

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Expression was increased 2-fold in S. cerevisiae.

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Expression was increased 3.8-fold in E. coli.

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Increased expression in S. cerevisiae was promoter independent.

Expression of a new fluorescent reporter protein called mNeonGreen, that is not based on the jellyfish green fluorescent protein (GFP) sequence, shows increased brightness and folding speed compared to enhanced GFP. However, in vivo brightness of mNeonGreen and its yeast-optimized variant ymNeonGreen in S. cerevisiae is lower than expected, limiting the use of this high quantum yield, fast-folding reporter in budding yeast. This study shows that secondary RNA structure near the start codon in the ymNeonGreen ORF inhibits expression in S. cerevisiae. Removing secondary structure, without altering the ymNeonGreen protein sequence, led to a 2 and 4-fold increase in fluorescence when expressed in S. cerevisiae and E. coli, respectively. In S. cerevisiae, increased fluorescence was seen with strong and weak promoters and led to higher transcript levels suggesting greater transcript stability and improved expression in the absence of stable secondary RNA structure near the start codon.

Conservation of Differential Animal MicroRNA Processing by Drosha and Dicer

In complex biochemical systems, an enzyme, protein, or RNA, symbolized as E, has hundreds or thousands of substrates or interacting partners. The relative specificity hypothesis proposes that such an E would differentially interact with and influence its many distinct, downstream substrates, thereby regulating the underlying biological process (es). The importance of relative specificity has been underappreciated, and evidence of its physiological consequences particularly lacking. Previously we showed that human Drosha and Dicer ribonucleases (RNases) both discriminate their respective microRNA (miRNA) substrates, and that differential cleavage by Drosha contributes to global differential miRNA expression. If relative specificity is an important biological mechanism, it should be evolutionarily conserved. To test this hypothesis, we hereby examined the cleavage of hundreds of zebrafish and fruitfly miRNA intermediates by Drosha and Dicer and the impact on miRNA biogenesis in these organisms. We showed that Drosha action regulates differential miRNA expression in zebrafish and fruitflies and identified the conserved secondary structure features and sequences in miRNA transcripts that control Drosha activity and miRNA expression. Our results established the conservation of miRNA processing mechanisms and regulatory functions by Drosha and Dicer, greatly strengthened the evidence for the physiological consequences of relative specificity as well as demonstrated its evolutionary significance.

Evolution of the Neocortex Through RNA-Binding Proteins and Post-transcriptional Regulation

The human neocortex is undoubtedly considered a supreme accomplishment in mammalian evolution. It features a prenatally established six-layered structure which remains plastic to the myriad of changes throughout an organism’s lifetime. A fundamental feature of neocortical evolution and development is the abundance and diversity of the progenitor cell population and their neuronal and glial progeny. These evolutionary upgrades are partially enabled due to the progenitors’ higher proliferative capacity, compartmentalization of proliferative regions, and specification of neuronal temporal identities. The driving force of these processes may be explained by temporal molecular patterning, by which progenitors have intrinsic capacity to change their competence as neocortical neurogenesis proceeds. Thus, neurogenesis can be conceptualized along two timescales of progenitors’ capacity to (1) self-renew or differentiate into basal progenitors (BPs) or neurons or (2) specify their fate into distinct neuronal and glial subtypes which participate in the formation of six-layers. Neocortical development then proceeds through sequential phases of proliferation, differentiation, neuronal migration, and maturation. Temporal molecular patterning, therefore, relies on the precise regulation of spatiotemporal gene expression. An extensive transcriptional regulatory network is accompanied by post-transcriptional regulation that is frequently mediated by the regulatory interplay between RNA-binding proteins (RBPs). RBPs exhibit important roles in every step of mRNA life cycle in any system, from splicing, polyadenylation, editing, transport, stability, localization, to translation (protein synthesis). Here, we underscore the importance of RBP functions at multiple time-restricted steps of early neurogenesis, starting from the cell fate transition of transcriptionally primed cortical progenitors. A particular emphasis will be placed on RBPs with mostly conserved but also divergent evolutionary functions in neural progenitors across different species. RBPs, when considered in the context of the fascinating process of neocortical development, deserve to be main protagonists in the story of the evolution and development of the neocortex.

Scaling Up Single-Cell Proteomics

Single-cell tandem MS has enabled analyzing hundreds of single cells per day and quantifying thousands of proteins across the cells. The broad dissemination of these capabilities can empower the dissection of pathophysiological mechanisms in heterogeneous tissues. Key requirements for achieving this goal include robust protocols performed on widely accessible hardware, robust quality controls, community standards, and automated data analysis pipelines that can pinpoint analytical problems and facilitate their timely resolution. Toward meeting these requirements, this perspective outlines both existing resources and outstanding opportunities, such as parallelization, for catalyzing the wide dissemination of quantitative single-cell proteomics analysis that can be scaled up to tens of thousands of single cells. Indeed, simultaneous parallelization of the analysis of peptides and single cells is a promising approach for multiplicative increase in the speed of performing deep and quantitative single-cell proteomics. The community is ready to begin a virtuous cycle of increased adoption fueling the development of more technology and resources for single-cell proteomics that in turn drive broader adoption, scientific discoveries, and clinical applications.

Combinations of slow-translating codon clusters can increase mRNA half-life in Saccharomyces cerevisiae

The presence of a single cluster of nonoptimal codons was found to decrease a transcript's half-life through the interaction of the ribosome-associated quality control machinery with stalled ribosomes in Saccharomyces cerevisiae The impact of multiple nonoptimal codon clusters on a transcript's half-life, however, is unknown. Using a kinetic model, we predict that inserting a second nonoptimal cluster near the 5' end can lead to synergistic effects that increase a messenger RNA's (mRNA's) half-life in S. cerevisiae Specifically, the 5' end cluster suppresses the formation of ribosome queues, reducing the interaction of ribosome-associated quality control factors with stalled ribosomes. We experimentally validate this prediction by introducing two nonoptimal clusters into three different genes and find that their mRNA half-life increases up to fourfold. The model also predicts that in the presence of two clusters, the cluster closest to the 5' end is the primary determinant of mRNA half-life. These results suggest the "translational ramp," in which nonoptimal codons are located near the start codon and increase translational efficiency, may have the additional biological benefit of allowing downstream slow-codon clusters to be present without decreasing mRNA half-life. These results indicate that codon usage bias plays a more nuanced role in controlling cellular protein levels than previously thought.

Proteome-wide Association Study Provides Insights Into the Genetic Component of Protein Abundance in Psychiatric Disorders

BACKGROUND

Genome-wide association studies have identified multiple risk variants for psychiatric disorders. Nevertheless, how the risk variants confer risk of psychiatric disorders remains largely unknown.

METHODS

We performed proteome-wide association studies to identify genes whose cis-regulated protein abundance change in the human brain were associated with psychiatric disorders.

RESULTS

By integrating genome-wide associations of four common psychiatric disorders and two independent brain proteomes (n = 376 and n = 152, respectively) from the dorsolateral prefrontal cortex, we identified 61 genes (including 48 genes for schizophrenia, 12 genes for bipolar disorder, 5 genes for depression, and 2 genes for attention-deficit/hyperactivity disorder) whose genetically regulated protein abundance levels were associated with risk of psychiatric disorders. Comparison with transcriptome-wide association studies identified 18 overlapping genes that showed significant associations with psychiatric disorders at both proteome-wide and transcriptome-wide levels, suggesting that genetic risk variants likely confer risk of psychiatric disorders by regulating messenger RNA expression and protein abundance of these genes.

CONCLUSIONS

Our study not only provides new insights into the genetic component of protein abundance in psychiatric disorders but also highlights several high-confidence risk proteins (including CNNM2 and CTNND1) for schizophrenia and depression. These high-confidence risk proteins represent promising therapeutic targets for future drug development.

Quantitative model suggests both intrinsic and contextual features contribute to the transcript coding ability determination in cells

Gene transcription and protein translation are two key steps of the 'central dogma.' It is still a major challenge to quantitatively deconvolute factors contributing to the coding ability of transcripts in mammals. Here, we propose ribosome calculator (RiboCalc) for quantitatively modeling the coding ability of RNAs in human genome. In addition to effectively predicting the experimentally confirmed coding abundance via sequence and transcription features with high accuracy, RiboCalc provides interpretable parameters with biological information. Large-scale analysis further revealed a number of transcripts with a variety of coding ability for distinct types of cells (i.e. context-dependent coding transcripts), suggesting that, contrary to conventional wisdom, a transcript's coding ability should be modeled as a continuous spectrum with a context-dependent nature.

Differential p16 expression levels in the liver, hepatocytes and hepatocellular cell lines

Background

One of the most frequently deleted genes in cancer is CDKN2A encoding p16. This protein is often overexpressed in senescent cells, while its suppression can bypass the oncogene-induced senescence to enable transformation and tumorigenesis. The roles of the protein p16 are recently being expanded from the cell cycle progression regulator to the cellular regulator interacting in several different pathways. Yet data on its liver and liver cells' expression are inconclusive.

Methods

The expression of the p16 gene in liver and liver cells was determined by RT-qPCR and compared to its protein amounts by western blotting.

Results

p16 is expressed at low levels in the liver and rat hepatocytes. Its expression varies from none to the considerable levels in the examined hepatocellular carcinoma cell lines (FaO and HepG2) and in immortalized mouse hepatocytes. Such significant expression differences of an important cellular regulator warrant the need to closely examine the differences in biochemical pathways correlated with the p16 expression when using hepatocytes and hepatoma liver models.

Translational autoregulation of RF2 protein in E. coli through programmed frameshifting

Various feedback mechanisms regulate the expression of different genes to ensure the required protein levels inside a cell. In this paper, we develop a kinetic model for one such mechanism that autoregulates RF2 protein synthesis in E. coli through programmed frameshifting. The model finds that the programmed frameshifting autoregulates RF2 protein synthesis by two independent mechanisms. First, it increases the rate of RF2 synthesis from each mRNA transcript at low RF2 concentration. Second, programmed frameshifting can dramatically increase the lifetime of RF2 transcripts when RF2 protein levels are lower than a threshold. This sharp increase in mRNA lifetime is caused by a first-order phase transition from a low to a high ribosome density on an RF2 transcript. The high ribosome density prevents the transcript's degradation by shielding it from nucleases, which increases its average lifetime and hence RF2 protein levels. Our study identifies this quality control mechanism that regulates the cellular protein levels by breaking the hierarchy of processes involved in gene expression.

Learning the Regulatory Code of Gene Expression

Data-driven machine learning is the method of choice for predicting molecular phenotypes from nucleotide sequence, modeling gene expression events including protein-DNA binding, chromatin states as well as mRNA and protein levels. Deep neural networks automatically learn informative sequence representations and interpreting them enables us to improve our understanding of the regulatory code governing gene expression. Here, we review the latest developments that apply shallow or deep learning to quantify molecular phenotypes and decode the cis-regulatory grammar from prokaryotic and eukaryotic sequencing data. Our approach is to build from the ground up, first focusing on the initiating protein-DNA interactions, then specific coding and non-coding regions, and finally on advances that combine multiple parts of the gene and mRNA regulatory structures, achieving unprecedented performance. We thus provide a quantitative view of gene expression regulation from nucleotide sequence, concluding with an information-centric overview of the central dogma of molecular biology.

Expression of BCL6 in paediatric B-cell acute lymphoblastic leukaemia and association with prognosis

B-cell lineage acute lymphoblastic leukaemia (B-ALL) is the most common paediatric malignancy. Transcription factor B-cell lymphoma 6 (BCL6) is essential to germinal centre formation and antibody affinity maturation and plays a major role in mature B-cell malignancies. More recently, it was shown to act as a critical downstream regulator in pre-BCR+ B-ALL. We investigated the expression of the BCL6 protein in a population-based cohort of paediatric B-ALL cases and detected moderate to strong positivity through immunohistochemistry in 7% of cases (8/117); however, only two of eight BCL6 cases (25%) co-expressed the ZAP70 protein. In light of these data, the subtype with active pre-BCR signalling constitutes a rare entity in paediatric B-ALL. In three independent larger cohorts with gene expression data, high BCL6 mRNA levels were associated with the TCF3-PBX1, Ph-like, NUTM1, MEF2D and PAX5-alt subgroups and the 'metagene' signature for pre-BCR-associated genes. However, higher-than-median BCL6 mRNA level alone was associated with favourable event free survival in the Nordic paediatric cohort, indicating that using BCL6 as a diagnostic marker requires careful design, and evaluation of protein level is needed alongside the genetic or transcriptomic data.

Reduced Translational Efficiency of Eukaryotic Genes after Duplication Events

Control of gene expression has been found to be predominantly determined at the level of protein translation. However, to date, reduced expression from duplicated genes in eukaryotes for dosage maintenance has only been linked to transcriptional control involving epigenetic mechanisms. Here, we hypothesize that dosage maintenance following gene duplication also involves regulation at the protein level. To test this hypothesis, we compared transcriptome and proteome data of yeast models, Saccharomyces cerevisiae and Schizosaccharomyces pombe, and worm models, Caenorhabditis elegans and Caenorhabditis briggsae, to investigate lineage-specifically duplicated genes. Duplicated genes in both eukaryotic models exhibited a reduced protein-to-mRNA abundance ratio. Moreover, dosage sensitive genes, represented by genes encoding protein complex subunits, reduced their protein-to-mRNA abundance ratios more significantly than the other genes after duplication events. An analysis of ribosome profiling (Ribo-Seq) data further showed that reduced translational efficiency was more prominent for dosage sensitive genes than for the other genes. Meanwhile, no difference in protein degradation rate was associated with duplication events. Translationally repressed duplicated genes were also more likely to be inhibited at the level of transcription. Taken together, these results suggest that translation-mediated dosage control is partially contributed by natural selection and it enhances transcriptional control in maintaining gene dosage after gene duplication events during eukaryotic genome evolution.

Quantifying absolute gene expression profiles reveals distinct regulation of central carbon metabolism genes in yeast

In addition to controlled expression of genes by specific regulatory circuits, the abundance of proteins and transcripts can also be influenced by physiological states of the cell such as growth rate and metabolism. Here we examine the control of gene expression by growth rate and metabolism, by analyzing a multi-omics dataset consisting of absolute-quantitative abundances of the transcriptome, proteome, and amino acids in 22 steady-state yeast cultures. We find that transcription and translation are coordinately controlled by the cell growth rate via RNA polymerase II and ribosome abundance, but they are independently controlled by nitrogen metabolism via amino acid and nucleotide availabilities. Genes in central carbon metabolism, however, are distinctly regulated and do not respond to the cell growth rate or nitrogen metabolism as all other genes. Understanding these effects allows the confounding factors of growth rate and metabolism to be accounted for in gene expression profiling studies.

Divergence in alternative polyadenylation contributes to gene regulatory differences between humans and chimpanzees

While comparative functional genomic studies have shown that inter-species differences in gene expression can be explained by corresponding inter-species differences in genetic and epigenetic regulatory mechanisms, co-transcriptional mechanisms, such as alternative polyadenylation (APA), have received little attention. We characterized APA in lymphoblastoid cell lines from six humans and six chimpanzees by identifying and estimating the usage for 44,432 polyadenylation sites (PAS) in 9518 genes. Although APA is largely conserved, 1705 genes showed significantly different PAS usage (FDR 0.05) between species. Genes with divergent APA also tend to be differentially expressed, are enriched among genes showing differences in protein translation, and can explain a subset of observed inter-species protein expression differences that do not differ at the transcript level. Finally, we found that genes with a dominant PAS, which is used more often than other PAS, are particularly enriched for differentially expressed genes.