Small networks of expressed genes in the whole blood and relationships to profiles in circulating metabolites provide insights in inter-individual variability of feed efficiency in growing pigs.

BACKGROUND: Feed efficiency is a research priority to support a sustainable meat production. It is recognized as a complex trait that integrates multiple biological pathways orchestrated in and by various tissues. This study aims to determine networks between biological entities to explain inter-individual variation of feed efficiency in growing pigs. RESULTS: The feed conversion ratio (FCR), a measure of feed efficiency, and its two component traits, average daily gain and average daily feed intake, were obtained from 47 growing pigs from a divergent selection for residual feed intake and fed high-starch or high-fat high-fiber diets during 58 days. Datasets of transcriptomics (60 k porcine microarray) in the whole blood and metabolomics (1H-NMR analysis and target gas chromatography) in plasma were available for all pigs at the end of the trial. A weighted gene co-expression network was built from the transcriptomics dataset, resulting in 33 modules of co-expressed molecular probes. The eigengenes of eight of these modules were significantly ([Formula: see text]) or tended to be ([Formula: see text]) correlated to FCR. Great homogeneity in the enriched biological pathways was observed in these modules, suggesting co-expressed and co-regulated constitutive genes. They were mainly enriched in genes participating to immune and defense-related processes, and to a lesser extent, to translation, cell development or learning. They were also generally associated with growth rate and percentage of lean mass. In the whole network, only one module composed of genes participating to the response to substances, was significantly associated with daily feed intake and body adiposity. The plasma profiles in circulating metabolites and in fatty acids were summarized by weighted linear combinations using a dimensionality reduction method. Close association was thus found between a module composed of co-expressed genes participating to T cell receptor signaling and cell development process in the whole blood and related to FCR, and the circulating concentrations of polyunsaturated fatty acids in plasma. CONCLUSION: These systemic approaches have highlighted networks of entities driving key biological processes involved in the phenotypic difference in feed efficiency between animals. Connecting transcriptomics and metabolic levels together had some additional benefits.

Fixing molecular complexes in BioPAX standards to enrich interactions and detect redundancies using semantic web technologies.

MOTIVATION: Molecular complexes play a major role in the regulation of biological pathways. The Biological Pathway Exchange format (BioPAX) facilitates the integration of data sources describing interactions some of which involving complexes. The BioPAX specification explicitly prevents complexes to have any component that is another complex (unless this component is a black-box complex whose composition is unknown). However, we observed that the well-curated Reactome pathway database contains such recursive complexes of complexes. We propose reproductible and semantically rich SPARQL queries for identifying and fixing invalid complexes in BioPAX databases, and evaluate the consequences of fixing these nonconformities in the Reactome database. RESULTS: For the Homo sapiens version of Reactome, we identify 5833 recursively defined complexes out of the 14 987 complexes (39%). This situation is not specific to the Human dataset, as all tested species of Reactome exhibit between 30% (Plasmodium falciparum) and 40% (Sus scrofa, Bos taurus, Canis familiaris, and Gallus gallus) of recursive complexes. As an additional consequence, the procedure also allows the detection of complex redundancies. Overall, this method improves the conformity and the automated analysis of the graph by repairing the topology of the complexes in the graph. This will allow to apply further reasoning methods on better consistent data. AVAILABILITY AND IMPLEMENTATION: We provide a Jupyter notebook detailing the analysis https://github.com/cjuigne/non_conformities_detection_biopax.

MicroRNA signatures in genetic frontotemporal dementia and amyotrophic lateral sclerosis.

OBJECTIVE: MicroRNAs are promising biomarkers of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), but discrepant results between studies have so far hampered their use in clinical trials. We aim to assess all previously identified circulating microRNA signatures as potential biomarkers of genetic FTD and/or ALS, using homogeneous, independent validation cohorts of C9orf72 and GRN mutation carriers. METHODS: 104 individuals carrying a C9orf72 or a GRN mutation, along with 31 controls, were recruited through the French research network on FTD/ALS. All subjects underwent blood sampling, from which circulating microRNAs were extracted. We measured differences in the expression levels of 65 microRNAs, selected from 15 published studies about FTD or ALS, between 31 controls, 17 C9orf72 presymptomatic subjects, and 29 C9orf72 patients. We also assessed differences in the expression levels of 30 microRNAs, selected from five studies about FTD, between 31 controls, 30 GRN presymptomatic subjects, and 28 GRN patients. RESULTS: More than half (35/65) of the selected microRNAs were differentially expressed in the C9orf72 cohort, while only a small proportion (5/30) of microRNAs were differentially expressed in the GRN cohort. In multivariate analyses, only individuals in the C9orf72 cohort could be adequately classified (ROC AUC up to 0.98 for controls versus presymptomatic subjects, 0.94 for controls versus patients, and 0.77 for presymptomatic subjects versus patients) with some of the signatures. INTERPRETATION: Our results suggest that previously identified microRNAs using sporadic or mixed cohorts of FTD and ALS patients could potentially serve as biomarkers of C9orf72-associated disease, but not GRN-associated disease.

Disease Progression Score Estimation From Multimodal Imaging and MicroRNA Data Using Supervised Variational Autoencoders.

Frontotemporal dementia and amyotrophic lateral sclerosis are rare neurodegenerative diseases with no effective treatment. The development of biomarkers allowing an accurate assessment of disease progression is crucial for evaluating new therapies. Concretely, neuroimaging and transcriptomic (microRNA) data have been shown useful in tracking their progression. However, no single biomarker can accurately measure progression in these complex diseases. Additionally, large samples are not available for such rare disorders. It is thus essential to develop methods that can model disease progression by combining multiple biomarkers from small samples. In this paper, we propose a new framework for computing a disease progression score (DPS) from cross-sectional multimodal data. Specifically, we introduce a supervised multimodal variational autoencoder that can infer a meaningful latent space, where latent representations are placed along a disease trajectory. A score is computed by orthogonal projections onto this path. We evaluate our framework with multiple synthetic datasets and with a real dataset containing 14 patients, 40 presymptomatic genetic mutation carriers and 37 controls from the PREV-DEMALS study. There is no ground truth for the DPS in real-world scenarios, therefore we use the area under the ROC curve (AUC) as a proxy metric. Results with the synthetic datasets support this choice, since the higher the AUC, the more accurate the predicted simulated DPS. Experiments with the real dataset demonstrate better performance in comparison with state-of-the-art approaches. The proposed framework thus leverages cross-sectional multimodal datasets with small sample sizes to objectively measure disease progression, with potential application in clinical trials.

Towards a reproducible interactome: semantic-based detection of redundancies to unify protein-protein interaction databases.

MOTIVATION: Information on protein-protein interactions is collected in numerous primary databases with their own curation process. Several meta-databases aggregate primary databases to provide more exhaustive datasets. In addition to exhaustivity, aggregation contributes to reliability by providing an overview of the various studies and detection methods supporting an interaction. However, interactions listed in different primary databases are partly redundant because some publications reporting protein-protein interactions have been curated by multiple primary databases. Mere aggregation can thus introduce a bias if these redundancies are not identified and eliminated. To overcome this bias, meta-databases rely on the Molecular Interaction ontology that describes interaction detection methods, but they do not fully take advantage of the ontology's rich semantics, which leads to systematically overestimating interaction reproducibility. RESULTS: We propose a precise definition of explicit and implicit redundancy and show that both can be easily detected using Semantic Web technologies. We apply this process to a dataset from the Agile Protein Interactomes DataServer (APID) meta-database and show that while explicit redundancies were detected by the APID aggregation process, about 15% of APID entries are implicitly redundant and should not be taken into account when presenting confidence-related metrics. More than 90% of implicit redundancies result from the aggregation of distinct primary databases, whereas the remaining occurs between entries of a single database. Finally, we build a 'reproducible interactome' with interactions that have been reproduced by multiple methods or publications. The size of the reproducible interactome is drastically impacted by removing redundancies for both yeast (-59%) and human (-56%), and we show that this is largely due to implicit redundancies. AVAILABILITY AND IMPLEMENTATION: Software, data and results are available at https://gitlab.com/nnet56/reproducible-interactome, https://reproducible-interactome.genouest.org/, Zenodo (https://doi.org/10.5281/zenodo.5595037) and NDEx (https://doi.org/10.18119/N94302 and https://doi.org/10.18119/N97S4D). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

EXOSC10/Rrp6 is essential for the eight-cell embryo/morula transition.

The conserved 3'-5' exoribonuclease EXOSC10/Rrp6 is required for gametogenesis, brain development, erythropoiesis and blood cell enhancer function. The human ortholog is essential for mitosis in cultured cancer cells. Little is known, however, about the role of Exosc10 during embryo development and organogenesis. We generated an Exosc10 knockout model and find that Exosc10-/- mice show an embryonic lethal phenotype. We demonstrate that Exosc10 maternal wild type mRNA is present in mutant oocytes and that the gene is expressed during all stages of early embryogenesis. Furthermore, we observe that EXOSC10 early on localizes to the periphery of nucleolus precursor bodies in blastomeres, which is in keeping with the protein's role in rRNA processing and may indicate a function in the establishment of chromatin domains during initial stages of embryogenesis. Finally, we infer from genotyping data for embryonic days e7.5, e6.5 and e4.5 and embryos cultured in vitro that Exosc10-/- mutants arrest at the eight-cell embryo/morula transition. Our results demonstrate a novel essential role for Exosc10 during early embryogenesis, and they are consistent with earlier work showing that impaired ribosome biogenesis causes a developmental arrest at the morula stage.

PAX2GRAPHML: a python library for large-scale regulation network analysis using BioPAX.

SUMMARY: PAX2GRAPHML is an open-source Python library that allows to easily manipulate BioPAX source files as regulated reaction graphs described in.graphml format. The concept of regulated reactions, which allows connecting regulatory, signaling and metabolic levels, has been used. Biochemical reactions and regulatory interactions are homogeneously described by regulated reactions involving substrates, products, activators and inhibitors as elements. PAX2GRAPHML is highly flexible and allows generating graphs of regulated reactions from a single BioPAX source or by combining and filtering BioPAX sources. Supported by the graph exchange format .graphml, the large-scale graphs produced from one or more data sources can be further analyzed with PAX2GRAPHML or standard Python and R graph libraries. AVAILABILITY AND IMPLEMENTATION: https://pax2graphml.genouest.org.

Exposure of human fetal kidneys to mild analgesics interferes with early nephrogenesis.

Acetaminophen, aspirin, and ibuprofen are mild analgesics commonly used by pregnant women, the sole current recommendation being to avoid ibuprofen from the fifth month of gestation. The nephrotoxicity of these three analgesics is well documented in adults, as is their interference with prostaglandins biosynthesis. Here we investigated the effect of these analgesics on human first trimester kidneys ex vivo. We first evaluated prostaglandins biosynthesis functionality by performing a wide screening of prostaglandin expression patterns in first trimester human kidneys. We demonstrated that prostaglandins biosynthesis machinery is functional during early nephrogenesis. Human fetal kidney explants aged 7-12 developmental weeks were exposed ex vivo to ibuprofen, aspirin or acetaminophen for 7 days, and analyzed by histology, immunohistochemistry, and flow cytometry. This study has revealed that these analgesics induced a spectrum of abnormalities within early developing structures, ranging from cell death to a decline in differentiating glomeruli density. These results warrant caution for the use of these medicines during the first trimester of pregnancy.

Plasma microRNA signature in presymptomatic and symptomatic subjects with C9orf72-associated frontotemporal dementia and amyotrophic lateral sclerosis.

OBJECTIVE: To identify potential biomarkers of preclinical and clinical progression in chromosome 9 open reading frame 72 gene (C9orf72)-associated disease by assessing the expression levels of plasma microRNAs (miRNAs) in C9orf72 patients and presymptomatic carriers. METHODS: The PREV-DEMALS study is a prospective study including 22 C9orf72 patients, 45 presymptomatic C9orf72 mutation carriers and 43 controls. We assessed the expression levels of 2576 miRNAs, among which 589 were above noise level, in plasma samples of all participants using RNA sequencing. The expression levels of the differentially expressed miRNAs between patients, presymptomatic carriers and controls were further used to build logistic regression classifiers. RESULTS: Four miRNAs were differentially expressed between patients and controls: miR-34a-5p and miR-345-5p were overexpressed, while miR-200c-3p and miR-10a-3p were underexpressed in patients. MiR-34a-5p was also overexpressed in presymptomatic carriers compared with healthy controls, suggesting that miR-34a-5p expression is deregulated in cases with C9orf72 mutation. Moreover, miR-345-5p was also overexpressed in patients compared with presymptomatic carriers, which supports the correlation of miR-345-5p expression with the progression of C9orf72-associated disease. Together, miR-200c-3p and miR-10a-3p underexpression might be associated with full-blown disease. Four presymptomatic subjects in transitional/prodromal stage, close to the disease conversion, exhibited a stronger similarity with the expression levels of patients. CONCLUSIONS: We identified a signature of four miRNAs differentially expressed in plasma between clinical conditions that have potential to represent progression biomarkers for C9orf72-associated frontotemporal dementia and amyotrophic lateral sclerosis. This study suggests that dysregulation of miRNAs is dynamically altered throughout neurodegenerative diseases progression, and can be detectable even long before clinical onset. TRIAL REGISTRATION NUMBER: NCT02590276.

The anti-cancer drug 5-fluorouracil affects cell cycle regulators and potential regulatory long non-coding RNAs in yeast.

5-fluorouracil (5-FU) was isolated as an inhibitor of thymidylate synthase, which is important for DNA synthesis. The drug was later found to also affect the conserved 3'-5' exoribonuclease EXOSC10/Rrp6, a catalytic subunit of the RNA exosome that degrades and processes protein-coding and non-coding transcripts. Work on 5-FU's cytotoxicity has been focused on mRNAs and non-coding transcripts such as rRNAs, tRNAs and snoRNAs. However, the effect of 5-FU on long non-coding RNAs (lncRNAs), which include regulatory transcripts important for cell growth and differentiation, is poorly understood. RNA profiling of synchronized 5-FU treated yeast cells and protein assays reveal that the drug specifically inhibits a set of cell cycle regulated genes involved in mitotic division, by decreasing levels of the paralogous Swi5 and Ace2 transcriptional activators. We also observe widespread accumulation of different lncRNA types in treated cells, which are typically present at high levels in a strain lacking EXOSC10/Rrp6. 5-FU responsive lncRNAs include potential regulatory antisense transcripts that form double-stranded RNAs (dsRNAs) with overlapping sense mRNAs. Some of these transcripts encode proteins important for cell growth and division, such as the transcription factor Ace2, and the RNA exosome subunit EXOSC6/Mtr3. In addition to revealing a transcriptional effect of 5-FU action via DNA binding regulators involved in cell cycle progression, our results have implications for the function of putative regulatory lncRNAs in 5-FU mediated cytotoxicity. The data raise the intriguing possibility that the drug deregulates lncRNAs/dsRNAs involved in controlling eukaryotic cell division, thereby highlighting a new class of promising therapeutical targets.

Seminal Simian Immunodeficiency Virus in Chronically Infected Cynomolgus Macaques Is Dominated by Virus Originating from Multiple Genital Organs.

The sexual transmission of viruses is responsible for the spread of multiple infectious diseases. Although the human immunodeficiency virus (HIV)/AIDS pandemic remains fueled by sexual contacts with infected semen, the origin of virus in semen is still unknown. In a substantial number of HIV-infected men, viral strains present in semen differ from the ones in blood, suggesting that HIV is locally produced within the genital tract. Such local production may be responsible for the persistence of HIV in semen despite effective antiretroviral therapy. In this study, we used single-genome amplification, amplicon sequencing (env gene), and phylogenetic analyses to compare the genetic structures of simian immunodeficiency virus (SIV) populations across all the male genital organs and blood in intravenously inoculated cynomolgus macaques in the chronic stage of infection. Examination of the virus populations present in the male genital tissues of the macaques revealed compartmentalized SIV populations in testis, epididymis, vas deferens, seminal vesicles, and urethra. We found genetic similarities between the viral strains present in semen and those in epididymis, vas deferens, and seminal vesicles. The contribution of male genital organs to virus shedding in semen varied among individuals and could not be predicted based on their infection or proinflammatory cytokine mRNA levels. These data indicate that rather than a single source, multiple genital organs are involved in the release of free virus and infected cells into semen. These findings have important implications for our understanding of systemic virus shedding and persistence in semen and for the design of eradication strategies to access viral reservoirs.IMPORTANCE Semen is instrumental for the dissemination of viruses through sexual contacts. Worryingly, a number of systemic viruses, such as HIV, can persist in this body fluid in the absence of viremia. The local source(s) of virus in semen, however, remains unknown. To elucidate the anatomic origin(s) of the virus released in semen, we compared viral populations present in semen with those in the male genital organs and blood of the Asian macaque model, using single-genome amplification, amplicon sequencing (env gene), and phylogenetic analysis. Our results show that multiple genital tissues harbor compartmentalized strains, some of them (i.e., from epididymis, vas deferens, and seminal vesicles) displaying genetic similarities with the viral populations present in semen. This study is the first to uncover local genital sources of viral populations in semen, providing a new basis for innovative targeted strategies to prevent and eradicate HIV in the male genital tract.

TOXsIgN: a cross-species repository for toxicogenomic signatures.

Motivation: At the same time that toxicologists express increasing concern about reproducibility in this field, the development of dedicated databases has already smoothed the path toward improving the storage and exchange of raw toxicogenomic data. Nevertheless, none provides access to analyzed and interpreted data as originally reported in scientific publications. Given the increasing demand for access to this information, we developed TOXsIgN, a repository for TOXicogenomic sIgNatures. Results: The TOXsIgN repository provides a flexible environment that facilitates online submission, storage and retrieval of toxicogenomic signatures by the scientific community. It currently hosts 754 projects that describe more than 450 distinct chemicals and their 8491 associated signatures. It also provides users with a working environment containing a powerful search engine as well as bioinformatics/biostatistics modules that enable signature comparisons or enrichment analyses. Availability and implementation: The TOXsIgN repository is freely accessible at http://toxsign.genouest.org. Website implemented in Python, JavaScript and MongoDB, with all major browsers supported. Supplementary information: Supplementary data are available at Bioinformatics online.

Clinicopathological characteristics of ROS1- and RET-rearranged NSCLC in caucasian patients: Data from a cohort of 713 non-squamous NSCLC lacking KRAS/EGFR/HER2/BRAF/PIK3CA/ALK alterations.

Targeted therapies have substantially changed the management of non-small cell lung cancer (NSCLC) patients with driver oncogenes. Given the high frequency, EGFR and ALK aberrations were the first to be detected and paved the way for tyrosine kinase inhibitor (TKI) treatments. Other kinases such as ROS1 and more recently RET have emerged as promising targets, and ROS1 and RET TKIs are already available for precision medicine. We screened a large cohort of 713 Caucasian non-squamous NSCLC patients lacking EGFR/KRAS/BRAF/HER2/PI3KCA/ALK aberrations for ROS1 and RET rearrangements using fluorescence in situ hybridization to determine the frequency and clinicopathological characteristics of ROS1- and RET-positive patients. Frequencies of ROS1 and RET rearrangements were 2.1% and 2.52%, respectively. Contrary to common belief, both ROS1 and RET rearrangements were detected in patients with a history of smoking, and the RET-positive patients were not younger than the negative patients. Moreover, RET but not ROS1 rearrangement was associated with the female gender. Nearly half of the ROS1-rearranged patients were successfully treated with ROS1 TKIs. In contrast, only 5/18 RET-positive patients received off-label RET TKIs. Two patients had stable disease, and three experienced disease progression. In addition to the 18 RET-positive cases, 10 showed isolated 5' signals. The clinical relevance is unknown but if the frequency is confirmed by other groups, the question whether these patients are eligible to TKIs will arise. More potent RET TKIs are under development and may improve the response rate in RET-positive patients. Therefore, we recommend the routine implementation of RET testing in non-squamous NSCLC patients, including those with a history of smoking.

The protein expression landscape of mitosis and meiosis in diploid budding yeast.

Saccharomyces cerevisiae is an established model organism for the molecular analysis of fundamental biological processes. The genomes of numerous strains have been sequenced, and the transcriptome and proteome ofmajor phases during the haploid and diploid yeast life cycle have been determined. However, much less is known about dynamic changes of the proteome when cells switch from mitotic growth to meiotic development. We report a quantitative protein profiling analysis of yeast cell division and differentiation based on mass spectrometry. Information about protein levels was integrated with strand-specific tiling array expression data. We identified a total of 2366 proteins in at least one condition, including 175 proteins showing a statistically significant>5-fold change across the sample set, and 136 proteins detectable in sporulating but not respiring cells. We correlate protein expression patterns with biological processes and molecular function by Gene Ontology term enrichment, chemoprofiling, transcription interference and the formation of double stranded RNAs by overlapping sense/antisense transcripts. Our work provides initial quantitative insight into protein expression in diploid respiring and differentiating yeast cells. Critically, it associates developmentally regulated induction of antisense long noncoding RNAs and double stranded RNAs with fluctuating protein concentrations during growth and development. BIOLOGICAL SIGNIFICANCE: This integrated genomics analysis helps better understand how the transcriptome and the proteome correlate in diploid yeast cells undergoing mitotic growth in the presence of acetate (respiration) versus meiotic differentiation (Meiosis I and II). The study (i) provides quantitative expression data for 2366 proteins and their cognate mRNAs in at least one sample, (ii) shows strongly fluctuating protein levels during growth and differentiation for 175 cases, and (iii) identifies 136 proteins absent in mitotic but present in meiotic yeast cells. We have integrated protein profiling data using mass spectrometry with tiling array RNA profiling data and information on double-stranded RNAs (dsRNAs) by overlapping sense/antisense transcripts from an RNA-Sequencing experiment. This work therefore provides quantitative insight into protein expression during cell division and development and associates changing protein levels with developmental stage specific induction of antisense transcripts and the formation of dsRNAs.

Exposure to the widely used herbicide atrazine results in deregulation of global tissue-specific RNA transcription in the third generation and is associated with a global decrease of histone trimethylation in mice.

The epigenetic events imposed during germline reprogramming and affected by harmful exposure can be inherited and transferred to subsequent generations via gametes inheritance. In this study, we examine the transgenerational effects promoted by widely used herbicide atrazine (ATZ). We exposed pregnant outbred CD1 female mice and the male progeny was crossed for three generations with untreated females. We demonstrate here that exposure to ATZ affects meiosis, spermiogenesis and reduces the spermatozoa number in the third generation (F3) male mice. We suggest that changes in testis cell types originate from modified transcriptional network in undifferentiated spermatogonia. Importantly, exposure to ATZ dramatically increases the number of transcripts with novel transcription initiation sites, spliced variants and alternative polyadenylation sites. We found the global decrease in H3K4me3 occupancy in the third generation males. The regions with altered H3K4me3 occupancy in F3 ATZ-derived males correspond to altered H3K4me3 occupancy of F1 generation and 74% of changed peaks in F3 generation are associated with enhancers. The regions with altered H3K4me3 occupancy are enriched in SP family and WT1 transcription factor binding sites. Our data suggest that the embryonic exposure to ATZ affects the development and the changes induced by ATZ are transferred up to three generations.

Ndt80 activates the meiotic ORC1 transcript isoform and SMA2 via a bi-directional middle sporulation element in Saccharomyces cerevisiae.

The origin of replication complex subunit ORC1 is important for DNA replication. The gene is known to encode a meiotic transcript isoform (mORC1) with an extended 5'-untranslated region (5'-UTR), which was predicted to inhibit protein translation. However, the regulatory mechanism that controls the mORC1 transcript isoform is unknown and no molecular biological evidence for a role of mORC1 in negatively regulating Orc1 protein during gametogenesis is available. By interpreting RNA profiling data obtained with growing and sporulating diploid cells, mitotic haploid cells, and a starving diploid control strain, we determined that mORC1 is a middle meiotic transcript isoform. Regulatory motif predictions and genetic experiments reveal that the activator Ndt80 and its middle sporulation element (MSE) target motif are required for the full induction of mORC1 and the divergently transcribed meiotic SMA2 locus. Furthermore, we find that the MSE-binding negative regulator Sum1 represses both mORC1 and SMA2 during mitotic growth. Finally, we demonstrate that an MSE deletion strain, which cannot induce mORC1, contains abnormally high Orc1 levels during post-meiotic stages of gametogenesis. Our results reveal the regulatory mechanism that controls mORC1, highlighting a novel developmental stage-specific role for the MSE element in bi-directional mORC1/SMA2 gene activation, and correlating mORC1 induction with declining Orc1 protein levels. Because eukaryotic genes frequently encode multiple transcripts possessing 5'-UTRs of variable length, our results are likely relevant for gene expression during development and disease in higher eukaryotes.

The epigenetic processes of meiosis in male mice are broadly affected by the widely used herbicide atrazine.

BACKGROUND: Environmental factors such as pesticides can cause phenotypic changes in various organisms, including mammals. We studied the effects of the widely used herbicide atrazine (ATZ) on meiosis, a key step of gametogenesis, in male mice. METHODS: Gene expression pattern was analysed by Gene-Chip array. Genome-wide mapping of H3K4me3 marks distribution was done by ChIP-sequencing of testis tissue using Illumina technologies. RT-qPCR was used to validate differentially expressed genes or differential peaks. RESULTS: We demonstrate that exposure to ATZ reduces testosterone levels and the number of spermatozoa in the epididymis and delays meiosis. Using Gene-Chip and ChIP-Seq analysis of H3K4me3 marks, we found that a broad range of cellular functions, including GTPase activity, mitochondrial function and steroid-hormone metabolism, are affected by ATZ. Furthermore, treated mice display enriched histone H3K4me3 marks in regions of strong recombination (double-strand break sites), within very large genes and reduced marks in the pseudoautosomal region of X chromosome. CONCLUSIONS: Our data demonstrate that atrazine exposure interferes with normal meiosis, which affects spermatozoa production.

Extreme multifunctional proteins identified from a human protein interaction network.

Moonlighting proteins are a subclass of multifunctional proteins whose functions are unrelated. Although they may play important roles in cells, there has been no large-scale method to identify them, nor any effort to characterize them as a group. Here, we propose the first method for the identification of 'extreme multifunctional' proteins from an interactome as a first step to characterize moonlighting proteins. By combining network topological information with protein annotations, we identify 430 extreme multifunctional proteins (3% of the human interactome). We show that the candidates form a distinct sub-group of proteins, characterized by specific features, which form a signature of extreme multifunctionality. Overall, extreme multifunctional proteins are enriched in linear motifs and less intrinsically disordered than network hubs. We also provide MoonDB, a database containing information on all the candidates identified in the analysis and a set of manually curated human moonlighting proteins.

Global alterations of the transcriptional landscape during yeast growth and development in the absence of Ume6-dependent chromatin modification.

Chromatin modification enzymes are important regulators of gene expression and some are evolutionarily conserved from yeast to human. Saccharomyces cerevisiae is a major model organism for genome-wide studies that aim at the identification of target genes under the control of conserved epigenetic regulators. Ume6 interacts with the upstream repressor site 1 (URS1) and represses transcription by recruiting both the conserved histone deacetylase Rpd3 (through the co-repressor Sin3) and the chromatin-remodeling factor Isw2. Cells lacking Ume6 are defective in growth, stress response, and meiotic development. RNA profiling studies and in vivo protein-DNA binding assays identified mRNAs or transcript isoforms that are directly repressed by Ume6 in mitosis. However, a comprehensive understanding of the transcriptional alterations, which underlie the complex ume6Δ mutant phenotype during fermentation, respiration, or sporulation, is lacking. We report the protein-coding transcriptome of a diploid MAT a/α wild-type and ume6/ume6 mutant strains cultured in rich media with glucose or acetate as a carbon source, or sporulation-inducing medium. We distinguished direct from indirect effects on mRNA levels by combining GeneChip data with URS1 motif predictions and published high-throughput in vivo Ume6-DNA binding data. To gain insight into the molecular interactions between successive waves of Ume6-dependent meiotic genes, we integrated expression data with information on protein networks. Our work identifies novel Ume6 repressed genes during growth and development and reveals a strong effect of the carbon source on the derepression pattern of transcripts in growing and developmentally arrested ume6/ume6 mutant cells. Since yeast is a useful model organism for chromatin-mediated effects on gene expression, our results provide a rich source for further genetic and molecular biological work on the regulation of cell growth and cell differentiation in eukaryotes.

The ReproGenomics Viewer: an integrative cross-species toolbox for the reproductive science community.

We report the development of the ReproGenomics Viewer (RGV), a multi- and cross-species working environment for the visualization, mining and comparison of published omics data sets for the reproductive science community. The system currently embeds 15 published data sets related to gametogenesis from nine model organisms. Data sets have been curated and conveniently organized into broad categories including biological topics, technologies, species and publications. RGV's modular design for both organisms and genomic tools enables users to upload and compare their data with that from the data sets embedded in the system in a cross-species manner. The RGV is freely available at http://rgv.genouest.org.