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Summary Today’s immense growth in complex biological data demands effective and flexible tools for integration, analysis and extraction of valuable insights. Here, we present CoNI, a practical R package for the unsupervised integration of numerical omics datasets. Our tool is based on partial correlations to identify putative confounding variables for a set of paired dependent variables. CoNI combines two omics datasets in an integrated, complex hypergraph-like network, represented as a weighted undirected graph, a bipartite graph, or a hypergraph structure. These network representations form a basis for multiple further analyses, such as identifying priority candidates of biological importance or comparing network structures dependent on different conditions. Availability and implementation The R package CoNI is available on the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/CoNI/) and GitLab (https://gitlab.com/computational-discovery-research/coni). It is distributed under the GNU General Public License (version 3). Supplementary information Supplementary data are available at Bioinformatics Advances online.

By accentuating drug efficacy and impeding resistance mechanisms, combinatorial, multi‐agent therapies have emerged as key approaches in the treatment of complex diseases, most notably cancer. Using high‐throughput drug screens, we uncovered distinct metabolic vulnerabilities and thereby identified drug combinations synergistically causing a starvation‐like lethal catabolic response in tumor cells from different cancer entities. Domperidone, a dopamine receptor antagonist, as well as several tricyclic antidepressants (TCAs), including imipramine, induced cancer cell death in combination with the mitochondrial uncoupler niclosamide ethanolamine (NEN) through activation of the integrated stress response pathway and the catabolic CLEAR network. Using transcriptome and metabolome analyses, we characterized a combinatorial response, mainly driven by the transcription factors CHOP and TFE3, which resulted in cell death through enhanced pyrimidine catabolism as well as reduced pyrimidine synthesis. Remarkably, the drug combinations sensitized human organoid cultures to the standard‐of‐care chemotherapy paclitaxel. Thus, our combinatorial approach could be clinically implemented into established treatment regimen, which would be further facilitated by the advantages of drug repurposing., This study identifies novel combinatorial drug treatments to induce death of different tumor cells, and defines the mechanisms of synergism between a mitochondrial uncoupler and antidepressants or dopamine receptor antagonists.

The exceptional longevity of social insect queens despite their lifelong high fecundity remains poorly understood in ageing biology. To gain insights into the mechanisms that might underlie ageing in social insects, we compared gene expression patterns between young and old castes (both queens and workers) across different lineages of social insects (two termite, two bee and two ant species). After global analyses, we paid particular attention to genes of the insulin/insulin-like growth factor 1 signalling (IIS)/target of rapamycin (TOR)/juvenile hormone (JH) network, which is well known to regulate lifespan and the trade-off between reproduction and somatic maintenance in solitary insects. Our results reveal a major role of the downstream components and target genes of this network (e.g. JH signalling, vitellogenins, major royal jelly proteins and immune genes) in affecting ageing and the caste-specific physiology of social insects, but an apparently lesser role of the upstream IIS/TOR signalling components. Together with a growing appreciation of the importance of such downstream targets, this leads us to propose the TI–J–LiFe ( T OR/ I IS– J H– Li fespan and Fe cundity) network as a conceptual framework for understanding the mechanisms of ageing and fecundity in social insects and beyond. This article is part of the theme issue ‘Ageing and sociality: why, when and how does sociality change ageing patterns?’

Description, The inner workings of the clock system rely on communicating signals between distal tissues to maintain daily metabolism., The mammalian circadian clock, expressed throughout the brain and body, controls daily metabolic homeostasis. Clock function in peripheral tissues is required, but not sufficient, for this task. Because of the lack of specialized animal models, it is unclear how tissue clocks interact with extrinsic signals to drive molecular oscillations. Here, we isolated the interaction between feeding and the liver clock by reconstituting Bmal1 exclusively in hepatocytes (Liver-RE), in otherwise clock-less mice, and controlling timing of food intake. We found that the cooperative action of BMAL1 and the transcription factor CEBPB regulates daily liver metabolic transcriptional programs. Functionally, the liver clock and feeding rhythm are sufficient to drive temporal carbohydrate homeostasis. By contrast, liver rhythms tied to redox and lipid metabolism required communication with the skeletal muscle clock, demonstrating peripheral clock cross-talk. Our results highlight how the inner workings of the clock system rely on communicating signals to maintain daily metabolism.

Objective Technological advances have brought a steady increase in the availability of various types of omics data, from genomics to metabolomics. Integrating these multi-omics data is a chance and challenge for systems biology; yet, tools to fully tap their potential remain scarce. Methods We present here a fully unsupervised and versatile correlation-based method – termed Correlation guided Network Integration (CoNI) – to integrate multi-omics data into a hypergraph structure that allows for the identification of effective modulators of metabolism. Our approach yields single transcripts of potential relevance that map to specific, densely connected, metabolic subgraphs or pathways. Results By applying our method on transcriptomics and metabolomics data from murine livers under standard Chow or high-fat diet, we identified eleven genes with potential regulatory effects on hepatic metabolism. Five candidates, including the hepatokine INHBE, were validated in human liver biopsies to correlate with diabetes-related traits such as overweight, hepatic fat content, and insulin resistance (HOMA-IR). Conclusion Our method's successful application to an independent omics dataset confirmed that the novel CoNI framework is a transferable, entirely data-driven, flexible, and versatile tool for multiple omics data integration and interpretation., Graphical abstract Image 1

BackgroundWild tomato species, likeSolanum chilense, are important germplasm resources for enhanced biotic and abiotic stress resistance in tomato breeding. In addition,S. chilenseserves as a model system to study adaptation of plants to drought and to investigate the evolution of seed banks. However to date, the absence of a well annotated reference genome in this compulsory outcrossing, very diverse species limits in-depth studies on the genes involved.FindingsWe generated ∼134 Gb of DNA and 157 Gb of RNA sequence data ofS chilense, which yielded a draft genome with an estimated length of 914 Mb in total encoding 25,885 high-confidence (hc) predicted gene models, which show homology to known protein-coding genes of other tomato species. Approximately 71% (18,290) of the hc gene models are additionally supported by RNA-seq data derived from leaf tissue samples. A benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis of predicted gene models retrieved 93.3% BUSCO genes, which is in the current range of high-quality genomes for non-inbred plants. To further verify the genome annotation completeness and accuracy, we manually inspected the NLR resistance gene family and assessed its assembly quality. We revealed the existence of unique gene families of NLRs toS. chilense. Comparative genomics analyses ofS. chilense, cultivated tomatoS. lycopersicumand its wild relativeS. pennelliirevealed similar levels of highly syntenic gene clusters between the three species.ConclusionsWe generated the first genome and transcriptome sequence assembly for the wild tomato speciesSolanum chilenseand demonstrated its value in comparative genomics analyses. We make these genomes available for the scientific community as an important resource for studies on adaptation to biotic and abiotic stress inSolanaceae, on evolution of self-incompatibility, and for tomato breeding.

Wild tomato species, like Solanum chilense, are important germplasm resources for enhanced biotic and abiotic stress resistance in tomato breeding. S. chilense also serves as a model to study adaptation of plants to drought and the evolution of seed banks. The absence of a well-annotated reference genome in this compulsory outcrossing, very diverse species limits in-depth studies on the genes involved. We generated ∼134 Gb of DNA and 157 Gb of RNA sequence data for S chilense, which yielded a draft genome with an estimated length of 914 Mb, encoding 25,885 high-confidence predicted gene models, which show homology to known protein-coding genes of other tomato species. Approximately 71% of these gene models are supported by RNA-seq data derived from leaf tissue samples. Benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis of predicted gene models retrieved 93.3% of BUSCO genes. To further verify the genome annotation completeness and accuracy, we manually inspected the NLR resistance gene family and assessed its assembly quality. We find subfamilies of NLRs unique to S. chilense. Synteny analysis suggests significant degree of the gene order conservation between the S. chilense, S. lycopersicum and S. pennellii genomes. We generated the first genome and transcriptome sequence assemblies for the wild tomato species Solanum chilense and demonstrated their value in comparative genomics analyses. These data are an important resource for studies on adaptation to biotic and abiotic stress in Solanaceae, on evolution of self-incompatibility and for tomato breeding.

Social insects provide promising new avenues for aging research. Within a colony, individuals that share the same genetic background can differ in lifespan by up to two orders of magnitude. Reproducing queens (and in termites also kings) can live for more than 20 years, extraordinary lifespans for insects. We studied aging in a termite species, Cryptotermes secundus, which lives in less socially complex societies with a few hundred colony members. Reproductives develop from workers which are totipotent immatures. Comparing transcriptomes of young and old individuals, we found evidence for aging in reproductives that was especially associated with DNA and protein damage and the activity of transposable elements. By contrast, workers seemed to be better protected against aging. Thus our results differed from those obtained for social insects that live in more complex societies. Yet, they are in agreement with lifespan estimates for the study species. Our data are also in line with expectations from evolutionary theory. For individuals that are able to reproduce, it predicts that aging should only start after reaching maturity. As C. secundus workers are immatures with full reproductive options we expect them to invest into anti-aging processes. Our study illustrates that the degree of aging can differ between social insects and that it may be associated with caste-specific opportunities for reproduction.