Next generation software for functional trend analysis

Cytosolic Ribosomal Protein Haploinsufficiency affects Mitochondrial Morphology and Respiration

The interplay between ribosomal protein composition and mitochondrial function is essential for sustaining energy homeostasis. Precise stoichiometric production of ribosomal proteins is crucial to maximize protein synthesis efficiency while reducing the energy costs to the cell. However, the impact of this balance on mitochondrial ATP generation, morphology and function remains unclear. Particularly, the loss of a single copy ribosomal protein gene is observed in Mendelian disorders like Diamond Blackfan Anemia and is common in somatic tumors, yet the implications of this imbalance on mitochondrial function and energy dynamics are still unclear. In this study, we investigated the impact of haploinsufficiency for four ribosomal protein genes implicated in ribosomopathy disorders (rps-10, rpl-5, rpl-33, rps-23) in Caenorhabditis elegans and corresponding reductions in human lymphoblast cells. Our findings uncover significant, albeit variably penetrant, mitochondrial morphological differences across these mutants, alongside an upregulation of glutathione transferases, and SKN-1 dependent increase in oxidative stress resistance, indicative of increased ROS production. Specifically, loss of a single copy of rps-10 in C. elegans led to decreased mitochondrial activity, characterized by lower energy levels and reduced oxygen consumption. A similar reduction in mitochondrial activity and energy levels was observed in human leukemia cells with a 50% reduction in RPS10 transcript levels. Importantly, we also observed alterations in the translation efficiency of nuclear and mitochondrial electron transport chain components in response to reductions in ribosomal protein genes' expression in both C. elegans and human cells. This suggests a conserved mechanism whereby the synthesis of components vital for mitochondrial function are adjusted in the face of compromised ribosomal machinery. Finally, mitochondrial membrane and cytosolic ribosomal components exhibited significant covariation at the RNA and translation efficiency level in lymphoblastoid cells across a diverse group of individuals, emphasizing the interplay between the protein synthesis machinery and mitochondrial energy production. By uncovering the impact of ribosomal protein haploinsufficiency on the translation efficiency of electron transport chain components, mitochondrial physiology, and the adaptive stress responses, we provide evidence for an evolutionarily conserved strategy to safeguard cellular functionality under genetic stress.

ADARs regulate cuticle collagen expression and promote survival to pathogen infection

BACKGROUND

In all organisms, the innate immune system defends against pathogens through basal expression of molecules that provide critical barriers to invasion and inducible expression of effectors that combat infection. The adenosine deaminase that act on RNA (ADAR) family of RNA-binding proteins has been reported to influence innate immunity in metazoans. However, studies on the susceptibility of ADAR mutant animals to infection are largely lacking.

RESULTS

Here, by analyzing adr-1 and adr-2 null mutants in well-established slow-killing assays, we find that both Caenorhabditis elegans ADARs are important for organismal survival to gram-negative and gram-positive bacteria, all of which are pathogenic to humans. Furthermore, our high-throughput sequencing and genetic analysis reveal that ADR-1 and ADR-2 function in the same pathway to regulate collagen expression. Consistent with this finding, our scanning electron microscopy studies indicate adr-1;adr-2 mutant animals also have altered cuticle morphology prior to pathogen exposure.

CONCLUSIONS

Our data uncover a critical role of the C. elegans ADAR family of RNA-binding proteins in promoting cuticular collagen expression, which represents a new post-transcriptional regulatory node that influences the extracellular matrix. In addition, we provide the first evidence that ADAR mutant animals have altered susceptibility to infection with several opportunistic human pathogens, suggesting a broader role of ADARs in altering physical barriers to infection to influence innate immunity.

Mining toxicogenomic data for dose-responsive pathways: implications in advancing next-generation risk assessment

Introduction: While targeted investigation of key toxicity pathways has been instrumental for biomarker discovery, unbiased and holistic analysis of transcriptomic data provides a complementary systems-level perspective. However, in a systematic context, this approach has yet to receive comprehensive and methodical implementation. Methods: Here, we took an integrated bioinformatic approach by re-analyzing publicly available MCF7 cell TempO-seq data for 44 ToxCast chemicals using an alternative pipeline to demonstrate the power of this approach. The original study has focused on analyzing the gene signature approach and comparing them to in vitro biological pathway altering concentrations determined from ToxCast HTS assays. Our workflow, in comparison, involves sequential differential expression, gene set enrichment, benchmark dose modeling, and identification of commonly perturbed pathways by network visualization. Results: Using this approach, we identified dose-responsive molecular changes, biological pathways, and points of departure in an untargeted manner. Critically, benchmark dose modeling based on pathways recapitulated points of departure for apical endpoints, while also revealing additional perturbed mechanisms missed by single endpoint analyses. Discussion: This systems-toxicology approach provides multifaceted insights into the complex effects of chemical exposures. Our work highlights the importance of unbiased data-driven techniques, alongside targeted methods, for comprehensively evaluating molecular initiating events, dose-response relationships, and toxicity pathways. Overall, integrating omics assays with robust bioinformatics holds promise for improving chemical risk assessment and advancing new approach methodologies (NAMs).

Increasing confidence in new approach methodologies for inhalation risk assessment with multiple end point assays using 5-day repeated exposure to 1,3-dichloropropene

New Approach Methodologies (NAMs) are being widely used to reduce, refine, and replace, animal use in studying toxicology. For respiratory toxicology, this includes both in silico and in vitro alternatives to replace traditional in vivo inhalation studies. 1,3-Dichloropropene (1,3-DCP) is a volatile organic compound that is widely used in agriculture as a pre-planting fumigant. Short-term exposure of humans to 1,3-DCP can result in mucous membrane irritation, chest pain, headache, and dizziness. In our previous work, we exposed differentiated cells representing different parts of the respiratory epithelium to 1,3-DCP vapor, measured cytotoxicity, and did In Vitro to In Vivo Extrapolation (IVIVE). We have extended our previous study with 1,3-DCP vapors by conducting transcriptomics on acutely exposed nasal cultures and have implemented a separate 5-day repeated exposure with multiple endpoints to gain further molecular insight into our model. MucilAir™ Nasal cell culture models, representing the nasal epithelium, were exposed to six sub-cytotoxic concentrations of 1,3-DCP vapor at the air-liquid interface, and the nasal cultures were analyzed by different methodologies, including histology, transcriptomics, and glutathione (GSH) -depletion assays. We observed the dose-dependent effect of 1,3-DCP in terms of differential gene expression, change in cellular morphology from pseudostratified columnar epithelium to squamous epithelium, and depletion of GSH in MucilAir™ nasal cultures. The MucilAir™ nasal cultures were also exposed to 3 concentrations of 1,3-DCP using repeated exposure 4 h per day for 5 days and the histological analyses indicated changes in cellular morphology and a decrease in ciliated bodies and an increase in apoptotic bodies, with increasing concentrations of 1,3-DCP. Altogether, our results suggest that sub-cytotoxic exposures to 1,3-DCP lead to several molecular and cellular perturbations, providing significant insight into the mode-of-action (MoA) of 1,3-DCP using an innovative NAM model.

Ribosome biogenesis disruption mediated chromatin structure changes revealed by SRAtac, a customizable end to end analysis pipeline for ATAC-seq

The nucleolus is a large nuclear body that serves as the primary site for ribosome biogenesis. Recent studies have suggested that it also plays an important role in organizing chromatin architecture. However, to establish a causal relationship between nucleolar ribosome assembly and chromatin architecture, genetic tools are required to disrupt nucleolar ribosome biogenesis. In this study, we used ATAC-seq to investigate changes in chromatin accessibility upon specific depletion of two ribosome biogenesis components, RPOA-2 and GRWD-1, in the model organism Caenorhabditis elegans. To facilitate the analysis of ATAC-seq data, we introduced two tools: SRAlign, an extensible NGS data processing workflow, and SRAtac, a customizable end-to-end ATAC-seq analysis pipeline. Our results revealed highly comparable changes in chromatin accessibility following both RPOA-2 and GRWD-1 perturbations. However, we observed a weak correlation between changes in chromatin accessibility and gene expression. While our findings corroborate the idea of a feedback mechanism between ribosomal RNA synthesis, nucleolar ribosome large subunit biogenesis, and chromatin structure during the L1 stage of C. elegans development, they also prompt questions regarding the functional impact of these alterations on gene expression.

Inhibition of ribosome biogenesis in the epidermis is sufficient to trigger organism-wide growth quiescence independently of nutritional status in C. elegans

Interorgan communication is crucial for multicellular organismal growth, development, and homeostasis. Cell nonautonomous inhibitory cues, which limit tissue-specific growth alterations, are not well characterized due to cell ablation approach limitations. In this study, we employed the auxin-inducible degradation system in C. elegans to temporally and spatially modulate ribosome biogenesis, through depletion of essential factors (RPOA-2, GRWD-1, or TSR-2). Our findings reveal that embryo-wide inhibition of ribosome biogenesis induces a reversible early larval growth quiescence, distinguished by a unique gene expression signature that is different from starvation or dauer stages. When ribosome biogenesis is inhibited in volumetrically similar tissues, including body wall muscle, epidermis, pharynx, intestine, or germ line, it results in proportionally stunted growth across the organism to different degrees. We show that specifically inhibiting ribosome biogenesis in the epidermis is sufficient to trigger an organism-wide growth quiescence. Epidermis-specific ribosome depletion leads to larval growth quiescence at the L3 stage, reduces organism-wide protein synthesis, and induced cell nonautonomous gene expression alterations. Further molecular analysis reveals overexpression of secreted proteins, suggesting an organism-wide regulatory mechanism. We find that UNC-31, a dense-core vesicle (DCV) pathway component, plays a significant role in epidermal ribosome biogenesis-mediated growth quiescence. Our tissue-specific knockdown experiments reveal that the organism-wide growth quiescence induced by epidermal-specific ribosome biogenesis inhibition is suppressed by reducing unc-31 expression in the epidermis, but not in neurons or body wall muscles. Similarly, IDA-1, a membrane-associated protein of the DCV, is overexpressed, and its knockdown in epidermis suppresses the organism-wide growth quiescence in response to epidermal ribosome biogenesis inhibition. Finally, we observe an overall increase in DCV puncta labeled by IDA-1 when epidermal ribosome biogenesis is inhibited, and these puncta are present in or near epidermal cells. In conclusion, these findings suggest a novel mechanism of nutrition-independent multicellular growth coordination initiated from the epidermis tissue upon ribosome biogenesis inhibition.

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.

Transcriptomic Study on Human Skin Samples: Identification of Two Subclasses of Actinic Keratoses

Actinic keratoses (AKs) are sun-damaged skin areas that affect 20% of the European adult population and more than 50% of people aged 70 years and over. There are currently no clinical or histological features allowing us to identify to which clinical class (i.e., regression or progression) an AK belongs. A transcriptomic approach seems to be a robust tool for AK characterization, but there is a need for additional studies, including more patients and elucidating the molecular signature of an AK. In this context, the present study, including the largest number of patients to date, is the first aiming at identifying biological features to objectively distinguish different AK signatures. We highlight two distinct molecular profiles: AKs featuring a molecular profile similar to squamous cell carcinomas (SCCs), which are called "lesional AKs" (AK_Ls), and AKs featuring a molecular profile similar to normal skin tissue, which are called "non-lesional AKs" (AK_NLs). The molecular profiles of both AK subclasses were studied, and 316 differentially expressed genes (DEGs) were identified between the two classes. The 103 upregulated genes in AK_L were related to the inflammatory response. Interestingly, downregulated genes were associated with keratinization. Finally, based on a connectivity map approach, our data highlight that the VEGF pathway could be a promising therapeutic target for high-risk lesions.

Dietary stress remodels the genetic architecture of lifespan variation in outbred Drosophila

Evolutionary theory suggests that lifespan-reducing alleles should be purged from the gene pool, and yet decades of genome-wide association and model organism studies have shown that they persist. One potential explanation is that alleles that regulate lifespan do so only in certain environmental contexts. We exposed outbred Drosophila to control and high-sugar diets and genotyped more than 10,000 adult flies to track allele frequency changes over the course of a single adult lifespan. We identified thousands of lifespan-associated alleles associated with early versus late-life trade-offs, late-onset effects and genotype-by-environment interactions. Remarkably, a third of lifespan-associated genetic variation had environmentally dependent effects on lifespan. We find that lifespan-reducing alleles are often recently derived, have stronger effects on a high-sugar diet and show signatures of selection in wild Drosophila populations, consistent with the evolutionary mismatch hypothesis. Our results provide insight into the highly polygenic and context-dependent genetic architecture of lifespan variation and the evolutionary processes that shape this key trait.

ZmCCT10-relayed photoperiod sensitivity regulates natural variation in the arithmetical formation of male germinal cells in maize

Extensive mutational screening studies have documented genes regulating anther and pollen development. Knowledge concerning how formation of male germinal cell is arithmetically controlled in natural populations, under different environmental conditions, is lacking. We counted pollen number within a single anther and a maize-teosinte BC₂ S₃ recombinant inbred line population to identify ZmCCT10 as a major determinant of pollen number variation. ZmCCT10 was originally identified as a photoperiod-sensitive negative regulator of flowering. ZmCCT10 inactivation, after transposon insertion within its promoter, is proposed to have accelerated maize spread toward higher latitudes, thus allowing temperate maize to flower under long-day conditions. We showed that the active ZmCCT10 allele decreased pollen formation. As different active and inactive ZmCCT10 alleles have been found in natural maize populations, this represents the first report of a gene controlling pollen number in a crop natural population. These findings suggest that higher pollen number, which provides a competitive advantage in open-pollinated populations, may have been one of the major driving forces for the selection of an inactive ZmCCT10 allele during tropical maize domestication. We provide evidence that ZmCCT10 has opposite effects on cell proliferation of archesporial and tapetum cells and it modulates expression of key regulators during early anther development.

Survival-based CRISPR genetic screens across a panel of permissive cell lines identify common and cell-specific SARS-CoV-2 host factors

SARS-CoV-2 depends on host cell components for infection and replication. Identification of virus-host dependencies offers an effective way to elucidate mechanisms involved in viral infection and replication. If druggable, host factor dependencies may present an attractive strategy for anti-viral therapy. In this study, we performed genome wide CRISPR knockout screens in Vero E6 cells and four human cell lines including Calu-3, UM-UC-4, HEK-293 and HuH-7 to identify genetic regulators of SARS-CoV-2 infection. Our findings identified only ACE2, the cognate SARS-CoV-2 entry receptor, as a common host dependency factor across all cell lines, while other host genes identified were largely cell line specific, including known factors TMPRSS2 and CTSL. Several of the discovered host-dependency factors converged on pathways involved in cell signalling, immune-related pathways, and chromatin modification. Notably, the chromatin modifier gene KMT2C in Calu-3 cells had the strongest impact in preventing SARS-CoV-2 infection when perturbed.

Molecular Characterization of the Dual Effect of the GPER Agonist G-1 in Glioblastoma

Glioblastoma (GBM) is the most common primary brain tumor in adults. Despite conventional treatment, consisting of a chirurgical resection followed by concomitant radio-chemotherapy, the 5-year survival rate is less than 5%. Few risk factors are clearly identified, but women are 1.4-fold less affected than men, suggesting that hormone and particularly estrogen signaling could have protective properties. Indeed, a high GPER1 (G-protein-coupled estrogen receptor) expression is associated with better survival, especially in women who produce a greater amount of estrogen. Therefore, we addressed the anti-tumor effect of the GPER agonist G-1 in vivo and characterized its molecular mechanism of action in vitro. First, the antiproliferative effect of G-1 was confirmed in a model of xenografted nude mice. A transcriptome analysis of GBM cells exposed to G-1 was performed, followed by functional analysis of the differentially expressed genes. Lipid and steroid synthesis pathways as well as cell division processes were both affected by G-1, depending on the dose and duration of the treatment. ANGPTL4, the first marker of G-1 exposure in GBM, was identified and validated in primary GBM cells and patient samples. These data strongly support the potential of G-1 as a promising chemotherapeutic compound for the treatment of GBM.

Identification of Gender- and Subtype-Specific Gene Expression Associated with Patient Survival in Low-Grade and Anaplastic Glioma in Connection with Steroid Signaling

Simple Summary

Gliomas are primary brain tumors that are initially slow growing but progress to be more aggressive and, ultimately, fatal within a few years. They are more common in men than in women, suggesting a protective role for female hormones. By analyzing patient data collected in the public TGCA-LGG database, we have demonstrated a link between the expression level of key steroid biosynthesis enzymes or hormone receptors with patient survival, in ways that are dependent on gender and molecular subtype. We also determined the genes which expression associated with these actors of steroid signaling and the functions they perform, to decipher the mechanisms underlying gender-dependent differences. Together, these results establish, for the first time, the involvement of hormones in low-grade and anaplastic gliomas and provide clues for refining their classification and, thus, facilitating more personalized management of patients.

Abstract

Low-grade gliomas are rare primary brain tumors, which fatally evolve to anaplastic gliomas. The current treatment combines surgery, chemotherapy, and radiotherapy. If gender differences in the natural history of the disease were widely described, their underlying mechanisms remain to be determined for the identification of reliable markers of disease progression. We mined the transcriptomic and clinical data from the TCGA-LGG and CGGA databases to identify male-over-female differentially expressed genes and selected those associated with patient survival using univariate analysis, depending on molecular characteristics (IDH wild-type/mutated; 1p/19q codeleted/not) and grade. Then, the link between the expression levels (low or high) of the steroid biosynthesis enzyme or receptors of interest and survival was studied using the log-rank test. Finally, a functional analysis of gender-specific correlated genes was performed. HOX-related genes appeared to be differentially expressed between males and females in both grades, suggesting that a glioma could originate in perturbation of developmental signals. Moreover, aromatase, androgen, and estrogen receptor expressions were associated with patient survival and were mainly related to angiogenesis or immune response. Therefore, consideration of the tight control of steroid hormone production and signaling seems crucial for the understanding of glioma pathogenesis and emergence of future targeted therapies.

Systematic exploration of dynamic splicing networks reveals conserved multistage regulators of neurogenesis

Alternative splicing (AS) is a critical regulatory layer; yet, factors controlling functionally coordinated splicing programs during developmental transitions are poorly understood. Here, we employ a screening strategy to identify factors controlling dynamic splicing events important for mammalian neurogenesis. Among previously unknown regulators, Rbm38 acts widely to negatively control neural AS, in part through interactions mediated by the established repressor of splicing, Ptbp1. Puf60, a ubiquitous factor, is surprisingly found to promote neural splicing patterns. This activity requires a conserved, neural-differential exon that remodels Puf60 co-factor interactions. Ablation of this exon rewires distinct AS networks in embryonic stem cells and at different stages of mouse neurogenesis. Single-cell transcriptome analyses further reveal distinct roles for Rbm38 and Puf60 isoforms in establishing neuronal identity. Our results describe important roles for previously unknown regulators of neurogenesis and establish how an alternative exon in a widely expressed splicing factor orchestrates temporal control over cell differentiation.

Transcriptional and Epigenetic Consequences of DMSO Treatment on HepaRG Cells

Dimethyl sulfoxide (DMSO) is used to sustain or favor hepatocyte differentiation in vitro. Thus, DMSO is used in the differentiation protocol of the HepaRG cells that present the closest drug-metabolizing enzyme activities to primary human hepatocytes in culture. The aim of our study is to clarify its influence on liver-specific gene expression. For that purpose, we performed a large-scale analysis (gene expression and histone modification) to determine the global role of DMSO exposure during the differentiation process of the HepaRG cells. The addition of DMSO drives the upregulation of genes mainly regulated by PXR and PPARα whereas genes not affected by this addition are regulated by HNF1α, HNF4α, and PPARα. DMSO-differentiated-HepaRG cells show a differential expression for genes regulated by histone acetylation, while differentiated-HepaRG cells without DMSO show gene signatures associated with histone deacetylases. In addition, we observed an interplay between cytoskeleton organization and EMC remodeling with hepatocyte maturation.

GLIDER: Function Prediction from GLIDE-based Neigborhoods

MOTIVATION

Protein function prediction, based on the patterns of connection in a Protein-Protein Interaction (or Association) network, is perhaps the most studied of the classical, fundamental inference problems for biological networks. A highly successful set of recent approaches use random walk-based low dimensional embeddings, that tend to place functionally similar proteins into coherent spatial regions. However, these approaches lose valuable local graph structure from the network when considering only the embedding. We introduce GLIDER, a method that replaces a protein-protein interaction or association network with a new graph-based similarity network. GLIDER is based on a variant of our previous GLIDE method, which was designed to predict missing links in Protein-Protein Association networks, capturing implicit local and global (i.e. embedding-based) graph properties.

RESULTS

GLIDER outperforms competing methods on the task of predicting GO functional labels in cross-validation on a heterogeneous collection of four Human Protein-Protein Association networks derived from the 2016 DREAM Disease Module Identification Challenge, and also on three different protein-protein association networks built from the STRING database. We show that this is due to the strong functional enrichment that is present in the local GLIDER neighborhood in multiple different types of protein-protein association networks. Furthermore, we introduce the GLIDER graph neighborhood as a way for biologists to visualize the local neighborhood of a disease gene. As an application, we look at the local GLIDER neighborhoods of a set of known Parkinson's Disease GWAS genes, rediscover many genes which have known involvement in Parkinson's disease pathways, plus suggest some new genes to study.

AVAILABILITY

All code is publicly available and can be accessed here: https://github.com/kap-devkota/GLIDER.

SUPPLEMENTARY INFORMATION

is available at Bioinformatics online.

Systematic mapping of nuclear domain-associated transcripts reveals speckles and lamina as hubs of functionally distinct retained introns

The nucleus is highly compartmentalized through the formation of distinct classes of membraneless domains. However, the composition and function of many of these structures are not well understood. Using APEX2-mediated proximity labeling and RNA sequencing, we surveyed human transcripts associated with nuclear speckles, several additional domains, and the lamina. Remarkably, speckles and lamina are associated with distinct classes of retained introns enriched in genes that function in RNA processing, translation, and the cell cycle, among other processes. In contrast to the lamina-proximal introns, retained introns associated with speckles are relatively short, GC-rich, and enriched for functional sites of RNA-binding proteins that are concentrated in these domains. They are also highly differentially regulated across diverse cellular contexts, including the cell cycle. Thus, our study provides a resource of nuclear domain-associated transcripts and further reveals speckles and lamina as hubs of distinct populations of retained introns linked to gene regulation and cell cycle progression.

A Minimal Subset of Seven Genes Associated with Tumor Hepatocyte Differentiation Predicts a Poor Prognosis in Human Hepatocellular Carcinoma

Simple Summary

Liver cancer is one of the most commonly diagnosed cancers worldwide and the fourth leading cause of cancer-related deaths. Hepatocellular carcinoma (HCC) accounts for at least 80% of all malignant liver primary tumors. A better characterization of molecular mechanisms underlying HCC onset and progression may lead to discover new therapeutic targets and biomarkers. In this study, we performed an integrative transcriptomics analysis to evaluate the clinical relevance of genes associated with hepatocyte differentiation in human HCC. The HepaRG cell line model was used to define a gene expression signature reflecting the status of tumor hepatocyte differentiation. This signature was able to stratify HCC patients into clinically relevant molecular subtypes. Then, a minimal subset of seven differentiation-associated genes was identified to predict a poor prognosis in several cancer datasets.

Abstract

Hepatocellular carcinoma (HCC) is a deadly cancer worldwide as a result of a frequent late diagnosis which limits the therapeutic options. Tumor progression in HCC is closely correlated with the dedifferentiation of hepatocytes, the main parenchymal cells in the liver. Here, we hypothesized that the expression level of genes reflecting the differentiation status of tumor hepatocytes could be clinically relevant in defining subsets of patients with different clinical outcomes. To test this hypothesis, an integrative transcriptomics approach was used to stratify a cohort of 139 HCC patients based on a gene expression signature established in vitro in the HepaRG cell line using well-controlled culture conditions recapitulating tumor hepatocyte differentiation. The HepaRG model was first validated by identifying a robust gene expression signature associated with hepatocyte differentiation and liver metabolism. In addition, the signature was able to distinguish specific developmental stages in mice. More importantly, the signature identified a subset of human HCC associated with a poor prognosis and cancer stem cell features. By using an independent HCC dataset (TCGA consortium), a minimal subset of seven differentiation-related genes was shown to predict a reduced overall survival, not only in patients with HCC but also in other types of cancers (e.g., kidney, pancreas, skin). In conclusion, the study identified a minimal subset of seven genes reflecting the differentiation status of tumor hepatocytes and clinically relevant for predicting the prognosis of HCC patients.

Transcriptome Reveals Allele Contribution to Heterosis in Maize

Heterosis, which has greatly increased maize yields, is associated with gene expression patterns during key developmental stages that enhance hybrid phenotypes relative to parental phenotypes. Before heterosis can be more effectively used for crop improvement, hybrid maize developmental gene expression patterns must be better understood. Here, six maize hybrids, including the popular hybrid Zhengdan958 (ZC) from China, were studied. Maize hybrids created in-house were generated using an incomplete diallel cross (NCII)-based strategy from four elite inbred parental lines. Differential gene expression (DEG) profiles corresponding to three developmental stages revealed that hybrid partial expression patterns exhibited complementarity of expression of certain parental genes, with parental allelic expression patterns varying both qualitatively and quantitatively in hybrids. Single-parent expression (SPE) and parent-specific expression (PSE) types of qualitative variation were most prevalent, 43.73 and 41.07% of variation, respectively. Meanwhile, negative super-dominance (NSD) and positive super-dominance (PSD) types of quantitative variation were most prevalent, 31.06 and 24.30% of variation, respectively. During the early reproductive growth stage, the gene expression pattern differed markedly from other developmental stage patterns, with allelic expression patterns during seed development skewed toward low-value parental alleles in hybrid seeds exhibiting significant quantitative variation-associated superiority. Comparisons of qualitative gene expression variation rates between ZC and other hybrids revealed proportions of SPE-DEGs (41.36%) in ZC seed DEGs that significantly exceeded the average proportion of SPE-DEGs found in seeds of other hybrids (28.36%). Importantly, quantitative gene expression variation rate comparisons between ZC and hybrids, except for transgressive expression, revealed that the ZC rate exceeded the average rate for other hybrids, highlighting the importance of partial gene expression in heterosis. Moreover, enriched ZC DEGs exhibiting distinct tissue-specific expression patterns belonged to four biological pathways, including photosynthesis, plant hormone signal transduction, biology metabolism and biosynthesis. These results provide valuable technical insights for creating hybrids exhibiting strong heterosis.

The molecular architecture of Drosophila melanogaster defense against Beauveria bassiana explored through evolve and resequence and quantitative trait locus mapping

Little is known about the genetic architecture of antifungal immunity in natural populations. Using two population genetic approaches, quantitative trait locus (QTL) mapping and evolve and resequence (E&R), we explored D. melanogaster immune defense against infection with the fungus Beauveria bassiana. The immune defense was highly variable both in the recombinant inbred lines from the Drosophila Synthetic Population Resource used for our QTL mapping and in the synthetic outbred populations used in our E&R study. Survivorship of infection improved dramatically over just 10 generations in the E&R study, and continued to increase for an additional nine generations, revealing a trade-off with uninfected longevity. Populations selected for increased defense against B. bassiana evolved cross resistance to a second, distinct B. bassiana strain but not to bacterial pathogens. The QTL mapping study revealed that sexual dimorphism in defense depends on host genotype, and the E&R study indicated that sexual dimorphism also depends on the specific pathogen to which the host is exposed. Both the QTL mapping and E&R experiments generated lists of potentially causal candidate genes, although these lists were nonoverlapping.

Genes with 5' terminal oligopyrimidine tracts preferentially escape global suppression of translation by the SARS-CoV-2 Nsp1 protein

Viruses rely on the host translation machinery to synthesize their own proteins. Consequently, they have evolved varied mechanisms to co-opt host translation for their survival. SARS-CoV-2 relies on a nonstructural protein, Nsp1, for shutting down host translation. However, it is currently unknown how viral proteins and host factors critical for viral replication can escape a global shutdown of host translation. Here, using a novel FACS-based assay called MeTAFlow, we report a dose-dependent reduction in both nascent protein synthesis and mRNA abundance in cells expressing Nsp1. We perform RNA-seq and matched ribosome profiling experiments to identify gene-specific changes both at the mRNA expression and translation levels. We discover that a functionally coherent subset of human genes is preferentially translated in the context of Nsp1 expression. These genes include the translation machinery components, RNA binding proteins, and others important for viral pathogenicity. Importantly, we uncovered a remarkable enrichment of 5' terminal oligo-pyrimidine (TOP) tracts among preferentially translated genes. Using reporter assays, we validated that 5' UTRs from TOP transcripts can drive preferential expression in the presence of Nsp1. Finally, we found that LARP1, a key effector protein in the mTOR pathway, may contribute to preferential translation of TOP transcripts in response to Nsp1 expression. Collectively, our study suggests fine-tuning of host gene expression and translation by Nsp1 despite its global repressive effect on host protein synthesis.

Loss of coordinated expression between ribosomal and mitochondrial genes revealed by comprehensive characterization of a large family with a rare Mendelian disorder

Non-canonical intronic variants are a poorly characterized yet highly prevalent class of alterations associated with Mendelian disorders. Here, we report the first RNA expression and splicing analysis from a family whose members carry a non-canonical splice variant in an intron of RPL11 (c.396 +3A>G). This mutation is causative for Diamond Blackfan Anemia (DBA) in this family despite incomplete penetrance and variable expressivity. Our analyses revealed a complex pattern of disruptions with many novel junctions of RPL11. These include an RPL11 transcript that is translated with a late stop codon in the 3' untranslated region (3'UTR) of the main isoform. We observed that RPL11 transcript abundance is comparable among carriers regardless of symptom severity. Interestingly, both the small and large ribosomal subunit transcripts were significantly overexpressed in individuals with a history of anemia in addition to congenital abnormalities. Finally, we discovered that coordinated expression between mitochondrial components and RPL11 was lost in all carriers, which may lead to variable expressivity. Overall, this study highlights the importance of RNA splicing and expression analyses in families for molecular characterization of Mendelian diseases.

Cold adaptation drives population genomic divergence in the ecological specialist, Drosophila montana

Detecting signatures of ecological adaptation in comparative genomics is challenging, but analysing population samples with characterised geographic distributions, such as clinal variation, can help identify genes showing covariation with important ecological variation. Here, we analysed patterns of geographic variation in the cold-adapted species Drosophila montana across phenotypes, genotypes and environmental conditions and tested for signatures of cold adaptation in population genomic divergence. We first derived the climatic variables associated with the geographic distribution of 24 populations across two continents to trace the scale of environmental variation experienced by the species, and measured variation in the cold tolerance of the flies of six populations from different geographic contexts. We then performed pooled whole genome sequencing of these six populations, and used Bayesian methods to identify SNPs where genetic differentiation is associated with both climatic variables and the population phenotypic measurements, while controlling for effects of demography and population structure. The top candidate SNPs were enriched on the X and fourth chromosomes, and they also lay near genes implicated in other studies of cold tolerance and population divergence in this species and its close relatives. We conclude that ecological adaptation has contributed to the divergence of D. montana populations throughout the genome and in particular on the X and fourth chromosomes, which also showed highest interpopulation F_ST . This study demonstrates that ecological selection can drive genomic divergence at different scales, from candidate genes to chromosome-wide effects.

Genes with 5' terminal oligopyrimidine tracts preferentially escape global suppression of translation by the SARS-CoV-2 Nsp1 protein

Viruses rely on the host translation machinery to synthesize their own proteins. Consequently, they have evolved varied mechanisms to co-opt host translation for their survival. SARS-CoV-2 relies on a non-structural protein, Nsp1, for shutting down host translation. However, it is currently unknown how viral proteins and host factors critical for viral replication can escape a global shutdown of host translation. Here, using a novel FACS-based assay called MeTAFlow, we report a dose-dependent reduction in both nascent protein synthesis and mRNA abundance in cells expressing Nsp1. We perform RNA-Seq and matched ribosome profiling experiments to identify gene-specific changes both at the mRNA expression and translation level. We discover a functionally-coherent subset of human genes are preferentially translated in the context of Nsp1 expression. These genes include the translation machinery components, RNA binding proteins, and others important for viral pathogenicity. Importantly, we uncovered a remarkable enrichment of 5' terminal oligo-pyrimidine (TOP) tracts among preferentially translated genes. Using reporter assays, we validated that 5' UTRs from TOP transcripts can drive preferential expression in the presence of NSP1. Finally, we found that LARP1, a key effector protein in the mTOR pathway may contribute to preferential translation of TOP transcripts in response to Nsp1 expression. Collectively, our study suggests fine tuning of host gene expression and translation by Nsp1 despite its global repressive effect on host protein synthesis.

Transcriptome-wide analysis of epitranscriptome and translational efficiency associated with heterosis in maize

Heterosis has been extensively utilized to increase productivity in crops, yet the underlying molecular mechanisms remain largely elusive. Here, we generated transcriptome-wide profiles of mRNA abundance, m6A methylation, and translational efficiency from the maize F1 hybrid B73×Mo17 and its two parental lines to ascertain the contribution of each regulatory layer to heterosis at the seedling stage. We documented that although the global abundance and distribution of m6A remained unchanged, a greater number of genes had gained an m6A modification in the hybrid. Superior variations were observed at the m6A modification and translational efficiency levels when compared with mRNA abundance between the hybrid and parents. In the hybrid, the vast majority of genes with m6A modification exhibited a non-additive expression pattern, the percentage of which was much higher than that at levels of mRNA abundance and translational efficiency. Non-additive genes involved in different biological processes were hierarchically coordinated by discrete combinations of three regulatory layers. These findings suggest that transcriptional and post-transcriptional regulation of gene expression make distinct contributions to heterosis in hybrid maize. Overall, this integrated multi-omics analysis provides a valuable portfolio for interpreting transcriptional and post-transcriptional regulation of gene expression in hybrid maize, and paves the way for exploring molecular mechanisms underlying hybrid vigor.

Stability of the cytosine methylome during post-testicular sperm maturation in mouse

Beyond the haploid genome, mammalian sperm carry a payload of epigenetic information with the potential to modulate offspring phenotypes. Recent studies show that the small RNA repertoire of sperm is remodeled during post-testicular maturation in the epididymis. Epididymal maturation has also been linked to changes in the sperm methylome, suggesting that the epididymis might play a broader role in shaping the sperm epigenome. Here, we characterize the genome-wide methylation landscape in seven germ cell populations from throughout the male reproductive tract. We find very few changes in the cytosine methylation landscape between testicular germ cell populations and cauda epididymal sperm, demonstrating that the sperm methylome is stable throughout post-testicular maturation. Although our sequencing data suggested that caput epididymal sperm exhibit a highly unusual methylome, follow-up studies revealed that this resulted from contamination of caput sperm by extracellular DNA. Extracellular DNA formed web-like structures that ensnared sperm, and was present only in sperm samples obtained from the caput epididymis and vas deferens of virgin males. Curiously, contaminating extracellular DNA was associated with citrullinated histone H3, potentially resulting from a PAD-driven genome decondensation process. Taken together, our data emphasize the stability of cytosine methylation in mammalian sperm, and identify a surprising, albeit transient, period during which sperm are associated with extracellular DNA.

An ensemble learning approach for modeling the systems biology of drug-induced injury

BACKGROUND

Drug-induced liver injury (DILI) is an adverse reaction caused by the intake of drugs of common use that produces liver damage. The impact of DILI is estimated to affect around 20 in 100,000 inhabitants worldwide each year. Despite being one of the main causes of liver failure, the pathophysiology and mechanisms of DILI are poorly understood. In the present study, we developed an ensemble learning approach based on different features (CMap gene expression, chemical structures, drug targets) to predict drugs that might cause DILI and gain a better understanding of the mechanisms linked to the adverse reaction.

RESULTS

We searched for gene signatures in CMap gene expression data by using two approaches: phenotype-gene associations data from DisGeNET, and a non-parametric test comparing gene expression of DILI-Concern and No-DILI-Concern drugs (as per DILIrank definitions). The average accuracy of the classifiers in both approaches was 69%. We used chemical structures as features, obtaining an accuracy of 65%. The combination of both types of features produced an accuracy around 63%, but improved the independent hold-out test up to 67%. The use of drug-target associations as feature obtained the best accuracy (70%) in the independent hold-out test.

CONCLUSIONS

When using CMap gene expression data, searching for a specific gene signature among the landmark genes improves the quality of the classifiers, but it is still limited by the intrinsic noise of the dataset. When using chemical structures as a feature, the structural diversity of the known DILI-causing drugs hampers the prediction, which is a similar problem as for the use of gene expression information. The combination of both features did not improve the quality of the classifiers but increased the robustness as shown on independent hold-out tests. The use of drug-target associations as feature improved the prediction, specially the specificity, and the results were comparable to previous research studies.

Taste perception and lifestyle: insights from phenotype and genome data among Africans and Asians

Taste is essential for the interaction of animals with their food and has co-evolved with diet. Humans have peopled a large range of environments and present a wide range of diets, but little is known about the diversity and evolution of human taste perception. We measured taste recognition thresholds across populations differing in lifestyles (hunter gatherers and farmers from Central Africa, nomad herders, and farmers from Central Asia). We also generated genome-wide genotype data and performed association studies and selection scans in order to link the phenotypic variation in taste sensitivity with genetic variation. We found that hunter gatherers have lower overall sensitivity as well as lower sensitivity to quinine and fructose than their farming neighbors. In parallel, there is strong population divergence in genes associated with tongue morphogenesis and genes involved in the transduction pathway of taste signals in the African populations. We find signals of recent selection in bitter taste-receptor genes for all four populations. Enrichment analysis on association scans for the various tastes confirmed already documented associations and revealed novel GO terms that are good candidates for being involved in taste perception. Our framework permitted us to gain insight into the genetic basis of taste sensitivity variation across populations and lifestyles.

Incomplete multi-view gene clustering with data regeneration using Shape Boltzmann Machine

Deciphering patterns in the structural and functional anatomy of genes can prove to be very helpful in understanding genetic biology and genomics. Also, the availability of the multiple omics data, along with the advent of machine learning techniques, aids medical professionals in gaining insights about various biological regulations. Gene clustering is one of the many such computation techniques that can help in understanding gene behavior. However, more comprehensive and reliable insights can be gained if different modalities/views of biomedical data are considered. However, in most multi-view cases, each view contains some missing data, leading to incomplete multi-view clustering. In this study, we have presented a deep Boltzmann machine-based incomplete multi-view clustering framework for gene clustering. Here, we seek to regenerate the data of the three NCBI datasets in the incomplete modalities using Shape Boltzmann Machines. The overall performance of the proposed multi-view clustering technique has been evaluated using the Silhouette index and Davies-Bouldin index, and the comparative analysis shows an improvement over state-of-the-art methods. Finally, to prove that the improvement attained by the proposed incomplete multi-view clustering is statistically significant, we perform Welch's t-test. AVAILABILITY OF DATA AND MATERIALS: https://github.com/piyushmishra12/IMC.

The molecular aetiology of tRNA synthetase depletion: induction of a GCN4 amino acid starvation response despite homeostatic maintenance of charged tRNA levels

During protein synthesis, charged tRNAs deliver amino acids to translating ribosomes, and are then re-charged by tRNA synthetases (aaRS). In humans, mutant aaRS cause a diversity of neurological disorders, but their molecular aetiologies are incompletely characterised. To understand system responses to aaRS depletion, the yeast glutamine aaRS gene (GLN4) was transcriptionally regulated using doxycycline by tet-off control. Depletion of Gln4p inhibited growth, and induced a GCN4 amino acid starvation response, indicative of uncharged tRNA accumulation and Gcn2 kinase activation. Using a global model of translation that included aaRS recharging, Gln4p depletion was simulated, confirming slowed translation. Modelling also revealed that Gln4p depletion causes negative feedback that matches translational demand for Gln-tRNA^Gln to aaRS recharging capacity. This maintains normal charged tRNA^Gln levels despite Gln4p depletion, confirmed experimentally using tRNA Northern blotting. Model analysis resolves the paradox that Gln4p depletion triggers a GCN4 response, despite maintenance of tRNA^Gln charging levels, revealing that normally, the aaRS population can sequester free, uncharged tRNAs during aminoacylation. Gln4p depletion reduces this sequestration capacity, allowing uncharged tRNA^Gln to interact with Gcn2 kinase. The study sheds new light on mutant aaRS disease aetiologies, and explains how aaRS sequestration of uncharged tRNAs can prevent GCN4 activation under non-starvation conditions.

Neural crest-derived tumor neuroblastoma and melanoma share 1p13.2 as susceptibility locus that shows a long-range interaction with the SLC16A1 gene

Neuroblastoma (NB) and malignant cutaneous melanoma (CMM) are neural crest cells (NCC)-derived tumors and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association studies (GWAS). We took a three-staged approach to conduct cross-disease meta-analysis of GWAS for NB and CMM (2101 NB cases and 4202 controls; 12 874 CMM cases and 23 203 controls) to identify shared loci. Findings were replicated in 1403 NB cases and 1403 controls of European ancestry and in 636 NB, 508 CMM cases and 2066 controls of Italian origin. We found a cross-association at locus 1p13.2 (rs2153977, odds ratio = 0.91, P = 5.36 × 10-8). We also detected a suggestive (P < 10-7) NB-CMM cross-association at 2q37.1 with opposite effect on cancer risk. Pathway analysis of 110 NB-CMM risk loci with P < 10-4 demonstrated enrichment of biological processes such as cell migration, cell cycle, metabolism and immune response, which are essential of human NCC development, underlying both tumors. In vitro and in silico analyses indicated that the rs2153977-T protective allele, located in an NB and CMM enhancer, decreased expression of SLC16A1 via long-range loop formation and altered a T-box protein binding site. Upon depletion of SLC16A1, we observed a decrease of cellular proliferation and invasion in both NB and CMM cell lines, suggesting its role as oncogene. This is the largest study to date examining pleiotropy across two NC cell-derived tumors identifying 1p13.2 as common susceptibility locus for NB and CMM risk. We demonstrate that combining genome-wide association studies results across cancers with same origins can identify new loci common to neuroblastoma and melanoma arising from tissues which originate from neural crest cells. Our results also show 1p13.2 confer risk to neuroblastoma and melanoma by regulating SLC16A1.

Characterization of a Novel Murine Colon Carcinoma Subline with High-Metastatic Activity Established by In Vivo Selection Method

The establishment of cancer cell lines, which have different metastatic abilities compared with the parental cell, is considered as an effective approach to investigate mechanisms of metastasis. A highly metastatic potential mouse colon cancer cell subline, Colon-26MGS, was derived from the parental cell line Colon-26 by in vivo selection using continuous subcutaneous implanting to immunocompetent mice. To clarify the mechanisms involved in the enhancement of metastasis, morphological characteristics, cell proliferation, and gene expression profiles were compared between Colon-26MGS and the parental cell. Colon-26MGS showed over 10 times higher metastatic ability compared with the parental cell, but there were no differences in morphological characteristics and in vitro proliferation rates. In addition, the Colon-26MGS-bearing mice exhibited no marked change of splenocyte population and lung pre-metastatic niche with tumor-free mice, but there were significant differences compared to Colon-26-bearing mice. RNA-seq analyses indicated that immune costimulatory molecules were significantly up-regulated in Colon-26MGS. These results suggest that Colon-26MGS showed not only higher metastatic activity, but also less induction property of host immune response compared to parental Colon-26. Colon-26MGS has proven to be a novel useful tool for studying multiple mechanisms involving metastasis enhancement.

In-silico simulated prototype-patients using TPMS technology to study a potential adverse effect of sacubitril and valsartan

Unveiling the mechanism of action of a drug is key to understand the benefits and adverse reactions of a medication in an organism. However, in complex diseases such as heart diseases there is not a unique mechanism of action but a wide range of different responses depending on the patient. Exploring this collection of mechanisms is one of the clues for a future personalized medicine. The Therapeutic Performance Mapping System (TPMS) is a Systems Biology approach that generates multiple models of the mechanism of action of a drug. Each molecular mechanism generated could be associated to particular individuals, here defined as prototype-patients, hence the generation of models using TPMS technology may be used for detecting adverse effects to specific patients. TPMS operates by (1) modelling the responses in humans with an accurate description of a protein network and (2) applying a Multilayer Perceptron-like and sampling strategy to find all plausible solutions. In the present study, TPMS is applied to explore the diversity of mechanisms of action of the drug combination sacubitril/valsartan. We use TPMS to generate a wide range of models explaining the relationship between sacubitril/valsartan and heart failure (the indication), as well as evaluating their association with macular degeneration (a potential adverse effect). Among the models generated, we identify a set of mechanisms of action associated to a better response in terms of heart failure treatment, which could also be associated to macular degeneration development. Finally, a set of 30 potential biomarkers are proposed to identify mechanisms (or prototype-patients) more prone of suffering macular degeneration when presenting good heart failure response. All prototype-patients models generated are completely theoretical and therefore they do not necessarily involve clinical effects in real patients. Data and accession to software are available at http://sbi.upf.edu/data/tpms/

Genome-wide analysis of expression quantitative trait loci (eQTLs) reveals the regulatory architecture of gene expression variation in the storage roots of sweet potato

Dissecting the genetic regulation of gene expression is critical for understanding phenotypic variation and species evolution. However, our understanding of the transcriptional variability in sweet potato remains limited. Here, we analyzed two publicly available datasets to explore the landscape of transcriptomic variations and its genetic basis in the storage roots of sweet potato. The comprehensive analysis identified a total of 724,438 high-confidence single nucleotide polymorphisms (SNPs) and 26,026 expressed genes. Expression quantitative trait locus (eQTL) analysis revealed 4408 eQTLs regulating the expression of 3646 genes, including 2261 local eQTLs and 2147 distant eQTLs. Two distant eQTL hotspots were found with target genes significantly enriched in specific functional classifications. By combining the information from regulatory network analyses, eQTLs and association mapping, we found that IbMYB1-2 acts as a master regulator and is the major gene responsible for the activation of anthocyanin biosynthesis in the storage roots of sweet potato. Our study provides the first insight into the genetic architecture of genome-wide expression variation in sweet potato and can be used to investigate the potential effects of genetic variants on key agronomic traits in sweet potato.

Natural Variation in RNA m6A Methylation and Its Relationship with Translational Status

N ⁶ -methyladenosine (m⁶A) is the most abundant modification of eukaryotic mRNA. Although m⁶A has been demonstrated to affect almost all aspects of RNA metabolism, its global contribution to the post-transcriptional balancing of translational efficiency remains elusive in plants. In this study, we performed a parallel analysis of the transcriptome-wide mRNA m⁶A distribution and polysome profiling in two maize (Zea mays) inbred lines to assess the global correlation of m⁶A modification with translational status. m⁶A sites are widely distributed in thousands of protein-coding genes, confined to a consensus motif and primarily enriched in the 3' untranslated regions, and highly coordinated with alternative polyadenylation usage, suggesting a role of m⁶A modification in regulating alternative polyadenylation site choice. More importantly, we identified that the m⁶A modification shows multifaceted correlations with the translational status depending on its strength and genic location. Moreover, we observed a substantial intraspecies variation in m⁶A modification, and this natural variation was shown to be partly driven by gene-specific expression and alternative splicing. Together, these findings provide an invaluable resource for ascertaining transcripts that are subject to m⁶A modification in maize and pave the way to a better understanding of natural m⁶A variation in mediating gene expression regulation.

Definition of the Minimal Contents for the Molecular Simulation of the Yeast Cytoplasm

The cytoplasm is a densely packed environment filled with macromolecules with hindered diffusion. Molecular simulation of the diffusion of biomolecules under such macromolecular crowding conditions requires the definition of a simulation cell with a cytoplasmic-like composition. This has been previously done for prokaryote cells (E. coli) but not for eukaryote cells such as yeast as a model organism. Yeast proteomics datasets vary widely in terms of cell growth conditions, the technique used to determine protein composition, the reported relative abundance of proteins, and the units in which abundances are reported. We determined that the gene ontology profiles of the most abundant proteins across these datasets are similar, but their abundances vary greatly. To overcome this problem, we chose five mass spectrometry proteomics datasets that fulfilled the following criteria: high internal consistency, consistency with published experimental data, and freedom from GFP-tagging artifacts. Using these datasets, the contents of a simulation cell containing a single 80S ribosome were defined, such that the macromolecular density and the mass ratio of ribosomal-to-cytoplasmic proteins were consistent with experiment and chosen datasets. Finally, multiple tRNAs were added, consistent with their experimentally-determined number in the yeast cell. The resulting composition can be readily used in molecular simulations representative of yeast cytoplasmic macromolecular crowding conditions to characterize a variety of phenomena, such as protein diffusion, protein-protein interactions and biological processes such as protein translation.

Genomics of Early Cardiac Dysfunction and Mortality in Obese Drosophila melanogaster

In experimental evolution, we impose functional demands on laboratory populations of model organisms using selection. After enough generations of such selection, the resulting populations constitute excellent material for physiological research. An intense selection regime for increased starvation resistance was imposed on 10 large outbred Drosophila populations. We observed the selection responses of starvation and desiccation resistance, metabolic reserves, and heart robustness via electrical pacing. Furthermore, we sequenced the pooled genomes of these populations. As expected, significant increases in starvation resistance and lipid content were found in our 10 intensely selected SCO populations. The selection regime also improved desiccation resistance, water content, and glycogen content among these populations. Additionally, the average rate of cardiac arrests in our 10 obese SCO populations was double the rate of the 10 ancestral CO populations. Age-specific mortality rates were increased at early adult ages by selection. Genomic analysis revealed a large number of single nucleotide polymorphisms across the genome that changed in frequency as a result of selection. These genomic results were similar to those obtained in our laboratory from less direct selection procedures. The combination of extensive genomic and phenotypic differentiation between these 10 populations and their ancestors makes them a powerful system for the analysis of the physiological underpinnings of starvation resistance.

Mouse screen reveals multiple new genes underlying mouse and human hearing loss

Adult-onset hearing loss is very common, but we know little about the underlying molecular pathogenesis impeding the development of therapies. We took a genetic approach to identify new molecules involved in hearing loss by screening a large cohort of newly generated mouse mutants using a sensitive electrophysiological test, the auditory brainstem response (ABR). We review here the findings from this screen. Thirty-eight unexpected genes associated with raised thresholds were detected from our unbiased sample of 1,211 genes tested, suggesting extreme genetic heterogeneity. A wide range of auditory pathophysiologies was found, and some mutant lines showed normal development followed by deterioration of responses, revealing new molecular pathways involved in progressive hearing loss. Several of the genes were associated with the range of hearing thresholds in the human population and one, SPNS2, was involved in childhood deafness. The new pathways required for maintenance of hearing discovered by this screen present new therapeutic opportunities.

This study uses an electrophysiological screen of over a thousand new mutant mouse lines to identify 38 new genes underlying deafness, some associated with human hearing function, revealing a wide range of molecular and pathological mechanisms.

Progressive hearing loss with age is extremely common in the population, leading to difficulties in understanding speech, increased social isolation, and associated depression. We know it has a significant heritability, but so far we know very little about the molecular pathways leading to hearing loss, hampering the development of treatments. Here, we describe a large-scale screen of 1,211 new targeted mouse mutant lines, resulting in the identification of 38 genes underlying hearing loss that were not previously suspected of involvement in hearing. Some of these genes reveal molecular pathways that may be useful targets for drug development. Our further analysis of the genes identified and the varied pathological mechanisms within the ear resulting from the mutations suggests that hearing loss is an extremely heterogeneous disorder and may have as many as 1,000 genes involved.

Genome-Wide Analysis of Starvation-Selected Drosophila melanogaster-A Genetic Model of Obesity

Experimental evolution affords the opportunity to investigate adaptation to stressful environments. Studies combining experimental evolution with whole-genome resequencing have provided insight into the dynamics of adaptation and a new tool to uncover genes associated with polygenic traits. Here, we selected for starvation resistance in populations of Drosophila melanogaster for over 80 generations. In response, the starvation-selected lines developed an obese condition, storing nearly twice the level of total lipids than their unselected controls. Although these fats provide a ∼3-fold increase in starvation resistance, the imbalance in lipid homeostasis incurs evolutionary cost. Some of these tradeoffs resemble obesity-associated pathologies in mammals including metabolic depression, low activity levels, dilated cardiomyopathy, and disrupted sleeping patterns. To determine the genetic basis of these traits, we resequenced genomic DNA from the selected lines and their controls. We found 1,046,373 polymorphic sites, many of which diverged between selection treatments. In addition, we found a wide range of genetic heterogeneity between the replicates of the selected lines, suggesting multiple mechanisms of adaptation. Genome-wide heterozygosity was low in the selected populations, with many large blocks of SNPs nearing fixation. We found candidate loci under selection by using an algorithm to control for the effects of genetic drift. These loci were mapped to a set of 382 genes, which associated with many processes including nutrient response, catabolic metabolism, and lipid droplet function. The results of our study speak to the evolutionary origins of obesity and provide new targets to understand the polygenic nature of obesity in a unique model system.

Maternal Ribosomes Are Sufficient for Tissue Diversification during Embryonic Development in C. elegans

Caenorhabditis elegans provides an amenable system to explore whether newly composed ribosomes are required to progress through development. Despite the complex pattern of tissues that are formed during embryonic development, we found that null homozygotes lacking any of the five different ribosomal proteins (RPs) can produce fully functional first-stage larvae, with similar developmental competence seen upon complete deletion of the multi-copy ribosomal RNA locus. These animals, relying on maternal but not zygotic contribution of ribosomal components, are capable of completing embryogenesis. In the absence of new ribosomal components, the resulting animals are arrested before progression from the first larval stage and fail in two assays for postembryonic plasticity of neuronal structure. Mosaic analyses of larvae that are a mixture of ribosome-competent and non-competent cells suggest a global regulatory mechanism in which ribosomal insufficiency in a subset of cells triggers organism-wide growth arrest.

Characterization of Proteome Variation During Modern Maize Breeding

The success of modern maize breeding has been demonstrated by remarkable increases in productivity with tremendous modification of agricultural phenotypes over the last century. Although the underlying genetic changes of the maize adaptation from tropical to temperate regions have been extensively studied, our knowledge is limited regarding the accordance of protein and mRNA expression levels accompanying such adaptation. Here we conducted an integrative analysis of proteomic and transcriptomic changes in a maize association panel. The minimum extent of correlation between protein and RNA levels suggests that variation in mRNA expression is often not indicative of protein expression at a population scale. This is corroborated by the observation that mRNA- and protein-based coexpression networks are relatively independent of each other, and many pQTLs arise without the presence of corresponding eQTLs. Importantly, compared with transcriptome, the subtypes categorized by the proteome show a markedly high accuracy to resemble the genomic subpopulation. These findings suggest that proteome evolved under a greater evolutionary constraint than transcriptome during maize adaptation from tropical to temperate regions. Overall, the integrated multi-omics analysis provides a functional context to interpret gene expression variation during modern maize breeding.

A common neighbor based technique to detect protein complexes in PPI networks

Detection of protein complexes by analyzing and understanding PPI networks is an important task and critical to all aspects of cell biology. We present a technique called PROtein COmplex DEtection based on common neighborhood (PROCODE) that considers the inherent organization of protein complexes as well as the regions with heavy interactions in PPI networks to detect protein complexes. Initially, the core of the protein complexes is detected based on the neighborhood of PPI network. Then a merging strategy based on density is used to attach proteins and protein complexes to the core-protein complexes to form biologically meaningful structures. The predicted protein complexes of PROCODE was evaluated and analyzed using four PPI network datasets out of which three were from budding yeast and one from human. Our proposed technique is compared with some of the existing techniques using standard benchmark complexes and PROCODE was found to match very well with actual protein complexes in the benchmark data. The detected complexes were at par with existing biological evidence and knowledge.

A Chemoproteomic Strategy for Direct and Proteome-Wide Covalent Inhibitor Target-Site Identification

Despite recent clinical successes for irreversible drugs, potential toxicities mediated by unpredictable modification of off-target cysteines represents a major hurdle for expansion of covalent drug programs. Understanding the proteome-wide binding profile of covalent inhibitors can significantly accelerate their development; however, current mass spectrometry strategies typically do not provide a direct, amino acid level readout of covalent activity for complex, selective inhibitors. Here we report the development of CITe-Id, a novel chemoproteomic approach that employs covalent pharmacologic inhibitors as enrichment reagents in combination with an optimized proteomic platform to directly quantify dose-dependent binding at cysteine-thiols across the proteome. CITe-Id analysis of our irreversible CDK inhibitor THZ1 identified dose-dependent covalent modification of several unexpected kinases, including a previously unannotated cysteine (C840) on the understudied kinase PKN3. These data streamlined our development of JZ128 as a new selective covalent inhibitor of PKN3. Using JZ128 as a probe compound, we identified novel potential PKN3 substrates, thus offering an initial molecular view of PKN3 cellular activity. CITe-Id provides a powerful complement to current chemoproteomic platforms to characterize the selectivity of covalent inhibitors, identify new, pharmacologically addressable cysteine-thiols, and inform structure-based drug design programs.

Δ9-tetrahydrocannabinol modulates the proteasome system in the brain

Cannabis is the most consumed illicit drug worldwide. Its principal psychoactive component, Δ⁹-tetrahydrocannabinol (THC), affects multiple brain functions, including cognitive performance, by modulating cannabinoid type-1 (CB1) receptors. These receptors are strongly enriched in presynaptic terminals, where they modulate neurotransmitter release. We analyzed, through a proteomic screening of hippocampal synaptosomal fractions, those proteins and pathways modulated 3 h after a single administration of an amnesic dose of THC (10 mg/kg, i.p.). Using an isobaric labeling approach, we identified 2040 proteins, 1911 of them previously reported in synaptic proteomes, confirming the synaptic content enrichment of the samples. Initial analysis revealed a significant alteration of 122 proteins, where 42 increased and 80 decreased their expression. Gene set enrichment analysis indicated an over-representation of mitochondrial associated functions and cellular metabolic processes. A second analysis focusing on extreme changes revealed 28 proteins with altered expression after THC treatment, 15 of them up-regulated and 13 down-regulated. Using a network topology-based scoring algorithm we identified those proteins in the mouse proteome with the greatest association to the 28 modulated proteins. This analysis pinpointed a significant alteration of the proteasome function, since top scoring proteins were related to the proteasome system (PS), a protein complex involved in ATP-dependent protein degradation. In this regard, we observed that THC decreases 20S proteasome chymotrypsin-like protease activity in the hippocampus. Our data describe for the first time the modulation of the PS in the hippocampus following THC administration under amnesic conditions that may contribute to an aberrant plasticity at synapses.

Ultrafiltration and size exclusion chromatography combined with asymmetrical-flow field-flow fractionation for the isolation and characterisation of extracellular vesicles from urine

Extracellular vesicles (EVs) have a great potential in clinical applications. However, their isolation from different bodily fluids and their characterisation are currently not optimal or standardised. Here, we report the results of examining the performance of ultrafiltration combined with size exclusion chromatography (UF-SEC) to isolate EVs from urine. The results reveal that UF-SEC is an efficient method and provides high purity. Furthermore, we introduce asymmetrical-flow field-flow fractionation coupled with a UV detector and multi-angle light-scattering detector (AF4/UV-MALS) as a characterisation method and compare it with current methods. We demonstrate that AF4/UV-MALS is a straightforward and reproducible method for determining size, amount and purity of isolated urinary EVs.

THD-Tricluster: A robust triclustering technique and its application in condition specific change analysis in HIV-1 progression data

Developing a cost-effective and robust triclustering algorithm that can identify triclusters of high biological significance in the gene-sample-time (GST) domain is a challenging task. Most existing triclustering algorithms can detect shifting and scaling patterns in isolation, they are not able to handle co-occurring shifting-and-scaling patterns. This paper makes an attempt to address this issue. It introduces a robust triclustering algorithm called THD-Tricluster to identify triclusters over the GST domain. In addition to applying over several benchmark datasets for its validation, the proposed THD-Tricluster algorithm was applied on HIV-1 progression data to identify disease-specific genes. THD-Tricluster could identify 38 most responsible genes for the deadly disease which includes GATA3, EGR1, JUN, ELF1, AGFG1, AGFG2, CX3CR1, CXCL12, CCR5, CCR2, and many others. The results are validated using GeneCard and other established results.

Measuring phenotype-phenotype similarity through the interactome

BACKGROUND

Recently, measuring phenotype similarity began to play an important role in disease diagnosis. Researchers have begun to pay attention to develop phenotype similarity measurement. However, existing methods ignore the interactions between phenotype-associated proteins, which may lead to inaccurate phenotype similarity.

RESULTS

We proposed a network-based method PhenoNet to calculate the similarity between phenotypes. We localized phenotypes in the network and calculated the similarity between phenotype-associated modules by modeling both the inter- and intra-similarity.

CONCLUSIONS

PhenoNet was evaluated on two independent evaluation datasets: gene ontology and gene expression data. The result shows that PhenoNet performs better than the state-of-art methods on all evaluation tests.

Network Analysis of UBE3A/E6AP-Associated Proteins Provides Connections to Several Distinct Cellular Processes

Perturbations in activity and dosage of the UBE3A ubiquitin-ligase have been linked to Angelman syndrome and autism spectrum disorders. UBE3A was initially identified as the cellular protein hijacked by the human papillomavirus E6 protein to mediate the ubiquitylation of p53, a function critical to the oncogenic potential of these viruses. Although a number of substrates have been identified, the normal cellular functions and pathways affected by UBE3A are largely unknown. Previously, we showed that UBE3A associates with HERC2, NEURL4, and MAPK6/ERK3 in a high-molecular-weight complex of unknown function that we refer to as the HUN complex (HERC2, UBE3A, and NEURL4). In this study, the combination of two complementary proteomic approaches with a rigorous network analysis revealed cellular functions and pathways in which UBE3A and the HUN complex are involved. In addition to finding new UBE3A-associated proteins, such as MCM6, SUGT1, EIF3C, and ASPP2, network analysis revealed that UBE3A-associated proteins are connected to several fundamental cellular processes including translation, DNA replication, intracellular trafficking, and centrosome regulation. Our analysis suggests that UBE3A could be involved in the control and/or integration of these cellular processes, in some cases as a component of the HUN complex, and also provides evidence for crosstalk between the HUN complex and CAMKII interaction networks. This study contributes to a deeper understanding of the cellular functions of UBE3A and its potential role in pathways that may be affected in Angelman syndrome, UBE3A-associated autism spectrum disorders, and human papillomavirus-associated cancers.

Detangling PPI networks to uncover functionally meaningful clusters

Background

Decomposing a protein-protein interaction network (PPI network) into non-overlapping clusters or communities, sometimes called “network modules,” is an important way to explore functional roles of sets of genes. When the method to accomplish this decomposition is solely based on purely graph-theoretic measures of the interconnection structure of the network, this is often called unsupervised clustering or community detection. In this study, we compare unsupervised computational methods for decomposing a PPI network into non-overlapping modules. A method is preferred if it results in a large proportion of nodes being assigned to functionally meaningful modules, as measured by functional enrichment over terms from the Gene Ontology (GO).

Results

We compare the performance of three popular community detection algorithms with the same algorithms run after the network is pre-processed by removing and reweighting based on the diffusion state distance (DSD) between pairs of nodes in the network. We call this “detangling” the network. In almost all cases, we find that detangling the network based on the DSD distance reweighting provides more meaningful clusters.

Conclusions

Re-embedding using the DSD distance metric, before applying standard community detection algorithms, can assist in uncovering GO functionally enriched clusters in the yeast PPI network.