Graph Node Classification to Predict Autism Risk in Genes

This study explores the genetic risk associations with autism spectrum disorder (ASD) using graph neural networks (GNNs), leveraging the Sfari dataset and protein interaction network (PIN) data. We built a gene network with genes as nodes, chromosome band location as node features, and gene interactions as edges. Graph models were employed to classify the autism risk associated with newly introduced genes (test set). Three classification tasks were undertaken to test the ability of our models: binary risk association, multi-class risk association, and syndromic gene association. We tested graph convolutional networks, Graph Sage, graph transformer, and Multi-Layer Perceptron (Baseline) architectures on this problem. The Graph Sage model consistently outperformed the other models, showcasing its utility in classifying ASD-related genes. Our ablation studies show that the chromosome band location and protein interactions contain useful information for this problem. The models achieved 85.80% accuracy on the binary risk classification, 81.68% accuracy on the multi-class risk classification, and 90.22% on the syndromic classification.

Analysis of the Gene Networks and Pathways Correlated with Tissue Differentiation in Prostate Cancer

Prostate cancer (PCa) is the most prevalent non-cutaneous cancer in men. Early PCa detection has been made possible by the adoption of screening methods based on the serum prostate-specific antigen and Gleason score (GS). The aim of this study was to correlate gene expression with the differentiation level of prostate adenocarcinomas, as indicated by GS. We used data from The Cancer Genome Atlas (TCGA) and included 497 prostate cancer patients, 52 of which also had normal tissue sample sequencing data. Gene ontology analysis revealed that higher GSs were associated with greater responses to DNA damage, telomere lengthening, and cell division. Positive correlation was found with transcription factor activator of the adenovirus gene E2 (E2F) and avian myelocytomatosis viral homolog (MYC) targets, G2M checkpoints, DNA repair, and mitotic spindles. Immune cell deconvolution revealed high M0 macrophage counts and an increase in M2 macrophages dependent on the GS. The molecular pathways most correlated with GSs were cell cycle, RNA transport, and calcium signaling (depleted). A combinatorial approach identified a set of eight genes able to differentiate by k-Nearest Neighbors (kNN) between normal tissues, low-Gleason tissues, and high-Gleason tissues with high accuracy. In conclusion, our study could be a step forward to better understanding the link between gene expression and PCa progression and aggressiveness.

Gene networks and the evolution of olfactory organs, eyes, hair cells and motoneurons: a view encompassing lancelets, tunicates and vertebrates

Key developmental pathways and gene networks underlie the formation of sensory cell types and structures involved in chemosensation, vision and mechanosensation, and of the efferents these sensory inputs can activate. We describe similarities and differences in these pathways and gene networks in selected species of the three main chordate groups, lancelets, tunicates, and vertebrates, leading to divergent development of olfactory receptors, eyes, hair cells and motoneurons. The lack of appropriately posited expression of certain transcription factors in lancelets and tunicates prevents them from developing vertebrate-like olfactory receptors and eyes, although they generate alternative structures for chemosensation and vision. Lancelets and tunicates lack mechanosensory cells associated with the sensation of acoustic stimuli, but have gravisensitive organs and ciliated epidermal sensory cells that may (and in some cases clearly do) provide mechanosensation and thus the capacity to respond to movement relative to surrounding water. Although functionally analogous to the vertebrate vestibular apparatus and lateral line, homology is questionable due to differences in the expression of the key transcription factors Neurog and Atoh1/7, on which development of vertebrate hair cells depends. The vertebrate hair cell-bearing inner ear and lateral line thus likely represent major evolutionary advances specific to vertebrates. Motoneurons develop in vertebrates under the control of the ventral signaling molecule hedgehog/sonic hedgehog (Hh,Shh), against an opposing inhibitory effect mediated by dorsal signaling molecules. Many elements of Shh-signaling and downstream genes involved in specifying and differentiating motoneurons are also exhibited by lancelets and tunicates, but the repertoire of MNs in vertebrates is broader, indicating greater diversity in motoneuron differentiation programs.

Hybridization and gene expression: Beyond differentially expressed genes

Gene expression has a key role in reproductive isolation, and studies of hybrid gene expression have identified mechanisms causing hybrid sterility. Here, we review the evidence for altered gene expression following hybridization and outline the mechanisms shown to contribute to altered gene expression in hybrids. Transgressive gene expression, transcending that of both parental species, is pervasive in early generation sterile hybrids, but also frequently observed in viable, fertile hybrids. We highlight studies showing that hybridization can result in transgressive gene expression, also in established hybrid lineages or species. Such extreme patterns of gene expression in stabilized hybrid taxa suggest that altered hybrid gene expression may result in hybridization-derived evolutionary novelty. We also conclude that while patterns of misexpression in hybrids are well documented, the understanding of the mechanisms causing misexpression is lagging. We argue that jointly assessing differences in cell composition and cell-specific changes in gene expression in hybrids, in addition to assessing changes in chromatin and methylation, will significantly advance our understanding of the basis of altered gene expression. Moreover, uncovering to what extent evolution of gene expression results in altered expression for individual genes, or entire networks of genes, will advance our understanding of how selection moulds gene expression. Finally, we argue that jointly studying the dual roles of altered hybrid gene expression, serving both as a mechanism for reproductive isolation and as a substrate for hybrid ecological adaptation, will lead to significant advances in our understanding of the evolution of gene expression.

C9orf72 gene networks in the human brain correlate with cortical thickness in C9-FTD and implicate vulnerable cell types

Introduction

A hexanucleotide repeat expansion (HRE) intronic to chromosome 9 open reading frame 72 (C9orf72) is recognized as the most common genetic cause of amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and ALS-FTD. Identifying genes that show similar regional co-expression patterns to C9orf72 may help identify novel gene targets and biological mechanisms that mediate selective vulnerability to ALS and FTD pathogenesis.

Methods

We leveraged mRNA expression data in healthy brain from the Allen Human Brain Atlas to evaluate C9orf72 co-expression patterns. To do this, we correlated average C9orf72 expression values in 51 regions across different anatomical divisions (cortex, subcortex, and cerebellum) with average gene expression values for 15,633 protein-coding genes, including 54 genes known to be associated with ALS, FTD, or ALS-FTD. We then performed imaging transcriptomic analyses to evaluate whether the identified C9orf72 co-expressed genes correlated with patterns of cortical thickness in symptomatic C9orf72 pathogenic HRE carriers (n = 19) compared to controls (n = 23). Lastly, we explored whether genes with significant C9orf72 imaging transcriptomic correlations (i.e., "C9orf72 imaging transcriptomic network") were enriched in specific cell populations in the brain and enriched for specific biological and molecular pathways.

Results

A total of 2,120 genes showed an anatomical distribution of gene expression in the brain similar to C9orf72 and significantly correlated with patterns of cortical thickness in C9orf72 HRE carriers. This C9orf72 imaging transcriptomic network was differentially expressed in cell populations previously implicated in ALS and FTD, including layer 5b cells, cholinergic neurons in the spinal cord and brainstem and medium spiny neurons of the striatum, and was enriched for biological and molecular pathways associated with protein ubiquitination, autophagy, cellular response to DNA damage, endoplasmic reticulum to Golgi vesicle-mediated transport, among others.

Conclusion

Considered together, we identified a network of C9orf72 associated genes that may influence selective regional and cell-type-specific vulnerabilities in ALS/FTD.

Differential Gene Expression in Human Fibroblasts Simultaneously Exposed to Ionizing Radiation and Simulated Microgravity

During future space missions, astronauts will be exposed to cosmic radiation and microgravity (μG), which are known to be health risk factors. To examine the differentially expressed genes (DEG) and their prevalent biological processes and pathways as a response to these two risk factors simultaneously, 1BR-hTERT human fibroblast cells were cultured under 1 gravity (1G) or simulated μG for 48 h in total and collected at 0 (sham irradiated), 3 or 24 h after 1 Gy of X-ray or Carbon-ion (C-ion) irradiation. A three-dimensional clinostat was used for the simulation of μG and the simultaneous radiation exposure of the samples. The RNA-seq method was used to produce lists of differentially expressed genes between different environmental conditions. Over-representation analyses were performed and the enriched biological pathways and targeting transcription factors were identified. Comparing sham-irradiated cells under simulated μG and 1G conditions, terms related to response to oxygen levels and muscle contraction were identified. After irradiation with X-rays or C-ions under 1G, identified DEGs were found to be involved in DNA damage repair, signal transduction by p53 class mediator, cell cycle arrest and apoptosis pathways. The same enriched pathways emerged when cells were irradiated under simulated μG condition. Nevertheless, the combined effect attenuated the transcriptional response to irradiation which may pose a subtle risk in space flights.

Modeling the Flowering Activation Motif during Vernalization in Legumes: A Case Study of M. trancatula

In many plant species, flowering is promoted by the cold treatment or vernalization. The mechanism of vernalization-induced flowering has been extensively studied in Arabidopsis but remains largely unknown in legumes. The orthologs of the FLC gene, a major regulator of vernalization response in Arabidopsis, are absent or non-functional in the vernalization-sensitive legume species. Nevertheless, the legume integrator genes FT and SOC1 are involved in the transition of the vernalization signal to meristem identity genes, including PIM (AP1 ortholog). However, the regulatory contribution of these genes to PIM activation in legumes remains elusive. Here, we presented the theoretical and data-driven analyses of a feed-forward regulatory motif that includes a vernalization-responsive FT gene and several SOC1 genes, which independently activate PIM and thereby mediate floral transition. Our theoretical model showed that the multiple regulatory branches in this regulatory motif facilitated the elimination of no-sense signals and amplified useful signals from the upstream regulator. We further developed and analyzed four data-driven models of PIM activation in Medicago trancatula in vernalized and non-vernalized conditions in wild-type and fta1-1 mutants. The model with FTa1 providing both direct activation and indirect activation via three intermediate activators, SOC1a, SOC1b, and SOC1c, resulted in the most relevant PIM dynamics. In this model, the difference between regulatory inputs of SOC1 genes was nonessential. As a result, in the M. trancatula model, the cumulative action of SOC1a, SOC1b, and SOC1c was favored. Overall, in this study, we first presented the in silico analysis of vernalization-induced flowering in legumes. The considered vernalization network motif can be supplemented with additional regulatory branches as new experimental data become available.

Fishing Innate Immune System Properties through the Transcriptomic Single-Cell Data of Teleostei

The innate immune system is the first line of defense in multicellular organisms. Danio rerio is widely considered a promising model for IIS-related research, with the most amount of scRNAseq data available among Teleostei. We summarized the scRNAseq and spatial transcriptomics experiments related to the IIS for zebrafish and other Teleostei from the GEO NCBI and the Single-Cell Expression Atlas. We found a considerable number of scRNAseq experiments at different stages of zebrafish development in organs such as the kidney, liver, stomach, heart, and brain. These datasets could be further used to conduct large-scale meta-analyses and to compare the IIS of zebrafish with the mammalian one. However, only a small number of scRNAseq datasets are available for other fish (turbot, salmon, cavefish, and dark sleeper). Since fish biology is very diverse, it would be a major mistake to use zebrafish alone in fish immunology studies. In particular, there is a special need for new scRNAseq experiments involving nonmodel Teleostei, e.g., long-lived species, cancer-resistant fish, and various fish ecotypes.

Gene networks for use in metabolomic data analysis of blood plasma from patients with postoperative delirium

Postoperative delirium (POD) is considered one of the most severe complications, resulting in impaired cognitive function, extended hospitalization, and higher treatment costs. The challenge of early POD diagnosis becomes particularly significant in cardiac surgery cases, as the incidence of this complication exceeds 50 % in certain patient categories. While it is known that neuroinflammation, neurotransmitter imbalances, disruptions in neuroendocrine regulation, and interneuronal connections contribute significantly to the development of POD, the molecular, genetic mechanisms of POD in cardiac surgery patients, along with potential metabolomic diagnostic markers, remain inadequately understood. In this study, blood plasma was collected from a group of patients over 65 years old after cardiac surgery involving artificial circulation. The collected samples were analyzed for sphingomyelin content and quantity using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS/MS) methods. The analysis revealed four significantly different sphingomyelin contents in patients with POD compared to those who did not develop POD (control group). Employing gene network reconstruction, we perceived a set of 82 regulatory enzymes affiliated with the genetic coordination of the sphingolipid metabolism pathway. Within this set, 47 are assumed to be regulators of gene expression, governing the transcription of enzymes pivotal to the metabolic cascade. Complementing this, an additional assembly of 35 regulators are considered to be regulators of activity, degradation, and translocation dynamics of enzymes integral to the aforementioned pathway. Analysis of the overrepresentation of diseases with which these regulatory proteins are associated showed that the regulators can be categorized into two groups, associated with cardiovascular pathologies (CVP) and neuropsychiatric diseases (NPD), respectively. The regulators associated with CVP are expectedly related to the effects on myocardial tissue during surgery. It is hypothesized that dysfunction of NPD-associated regulators may specifically account for the development of POD after cardiac surgery. Thus, the identified regulatory genes may provide a basis for planning further experiments, in order to study disorders at the level of expression of these genes, as well as impaired function of proteins encoded by them in patients with POD. The identified significant sphingolipids can be considered as potential markers of POD.

Gene Regulatory Networks: Improving Inferences with Transfer Learning

Deep transfer learning improves the inference of gene regulatory networks in human cells, reveals disease-associated genes, and identifies network-based druggable targets in human heart disease.

Prioritization of potential pharmacological targets for the development of anti-hepatocarcinoma drugs modulating the extrinsic apoptosis pathway: the reconstruction and analysis of associative gene networks help

Hepatocellular carcinoma (HCC) is a common severe type of liver cancer characterized by an extremely aggressive course and low survival rates. It is known that disruptions in the regulation of apoptosis activation are some of the key features inherent in most cancer cells, which determines the pharmacological induction of apoptosis as an important strategy for cancer therapy. The computer design of chemical compounds capable of specifically regulating the external signaling pathway of apoptosis induction represents a promising approach for creating new effective ways of therapy for liver cancer and other oncological diseases. However, at present, most of the studies are devoted to pharmacological effects on the internal (mitochondrial) apoptosis pathway. In contrast, the external pathway induced via cell death receptors remains out of focus. Aberrant gene methylation, along with hepatitis C virus (HCV) infection, are important risk factors for the development of hepatocellular carcinoma. The reconstruction of gene networks describing the molecular mechanisms of interaction of aberrantly methylated genes with key participants of the extrinsic apoptosis pathway and their regulation by HCV proteins can provide important information when searching for pharmacological targets. In the present study, 13 criteria were proposed for prioritizing potential pharmacological targets for developing anti-hepatocarcinoma drugs modulating the extrinsic apoptosis pathway. The criteria are based on indicators of the structural and functional organization of reconstructed gene networks of hepatocarcinoma, the extrinsic apoptosis pathway, and regulatory pathways of virus-extrinsic apoptosis pathway interaction and aberrant gene methylation-extrinsic apoptosis pathway interaction using ANDSystem. The list of the top 100 gene targets ranked according to the prioritization rating was statistically significantly (p-value = 0.0002) enriched for known pharmacological targets approved by the FDA, indicating the correctness of the prioritization method. Among the promising potential pharmacological targets, six highly ranked genes (JUN, IL10, STAT3, MYC, TLR4, and KHDRBS1) are likely to deserve close attention.

Molecular-genetic pathways of hepatitis C virus regulation of the expression of cellular factors PREB and PLA2G4C, which play an important role in virus replication

The participants of Hepatitis C virus (HCV) replication are both viral and host proteins. Therapeutic approaches based on activity inhibition of viral non-structural proteins NS3, NS5A, and NS5B are undergoing clinical trials. However, rapid mutation processes in the viral genome and acquisition of drug resistance to the existing drugs remain the main obstacles to fighting HCV. Identifying the host factors, exploring their role in HCV RNA replication, and studying viral effects on their expression is essential for understanding the mechanisms of viral replication and developing novel, effective curative approaches. It is known that the host factors PREB (prolactin regulatory element binding) and PLA2G4C (cytosolic phospholipase A2 gamma) are important for the functioning of the viral replicase complex and the formation of the platforms of HCV genome replication. The expression of PREB and PLA2G4C was significantly elevated in the presence of the HCV genome. However, the mechanisms of its regulation by HCV remain unknown. In this paper, using a text-mining technology provided by ANDSystem, we reconstructed and analyzed gene networks describing regulatory effects on the expression of PREB and PLA2G4C by HCV proteins. On the basis of the gene network analysis performed, we put forward hypotheses about the modulation of the host factors functions resulting from protein-protein interaction with HCV proteins. Among the viral proteins, NS3 showed the greatest number of regulatory linkages. We assumed that NS3 could inhibit the function of host transcription factor (TF) NOTCH1 by protein-protein interaction, leading to upregulation of PREB and PLA2G4C. Analysis of the gene networks and data on differential gene expression in HCV-infected cells allowed us to hypothesize further how HCV could regulate the expression of TFs, the binding sites of which are localized within PREB and PLA2G4C gene regions. The results obtained can be used for planning studies of the molecular-genetic mechanisms of viral-host interaction and searching for potential targets for anti-HCV therapy.

Genetic Interactions in Various Environmental Conditions in Caenorhabditis elegans

Although it is well known that epistasis plays an important role in many evolutionary processes (e.g., speciation, evolution of sex), our knowledge on the frequency and prevalent sign of epistatic interactions is mainly limited to unicellular organisms or cell cultures of multicellular organisms. This is even more pronounced in regard to how the environment can influence genetic interactions. To broaden our knowledge in that respect we studied gene-gene interactions in a whole multicellular organism, Caenorhabditis elegans. We screened over one thousand gene interactions, each one in standard laboratory conditions, and under three different stressors: heat shock, oxidative stress, and genotoxic stress. Depending on the condition, between 7% and 22% of gene pairs showed significant genetic interactions and an overall sign of epistasis changed depending on the condition. Sign epistasis was quite common, but reciprocal sign epistasis was extremally rare. One interaction was common to all conditions, whereas 78% of interactions were specific to only one environment. Although epistatic interactions are quite common, their impact on evolutionary processes will strongly depend on environmental factors.

The potential clinical impact of cell type-specific genetic regulation: Crohn's disease

Complex diseases are heterogenous due to variation in their genetic and environmental underpinnings, leading to varied treatment responses. Genome-wide association studies (GWAS) integrated with single-cell expression quantitative trait loci analyses (eQTL) can pinpoint cell-type specific candidate disease-relevant genes and pathways. This knowledge can be applied to patient stratification and novel therapeutic target identification. Here, we describe the translational potential of cell-type specific genetic regulation, using Crohn's disease as an example.

Beyond conflict: Kinship theory of intragenomic conflict predicts individual variation in altruistic behaviour

Behavioural variation is essential for animals to adapt to different social and environmental conditions. The Kinship Theory of Intragenomic Conflict (KTIC) predicts that parent-specific alleles can support different behavioural strategies to maximize allele fitness. Previous studies, including in honey bees (Apis mellifera), supported predictions of the KTIC for parent-specific alleles to promote selfish behaviour. Here, we test the KTIC prediction that for altruism-promoting genes (i.e. those that promote behaviours that support the reproductive fitness of kin), the allele with the higher altruism optimum should be selected to be expressed while the other is silenced. In honey bee colonies, workers act altruistically when tending to the queen by performing a 'retinue' behaviour, distributing the queen's mandibular pheromone (QMP) throughout the hive. Workers exposed to QMP do not activate their ovaries, ensuring they care for the queen's brood instead of competing to lay unfertilized eggs. Due to the haplodiploid genetics of honey bees, the KTIC predicts that response to QMP is favoured by the maternal genome. We report evidence for parent-of-origin effects on the retinue response behaviour, ovarian development and gene expression in brains of worker honey bees exposed to QMP, consistent with the KTIC. Additionally, we show enrichment for genes with parent-of-origin expression bias within gene regulatory networks associated with variation in bees' response to QMP. Our study demonstrates that intragenomic conflict can shape diverse social behaviours and influence expression patterns of single genes as well as gene networks.

A multi-level approach reveals key physiological and molecular traits in the response of two rice genotypes subjected to water deficit at the reproductive stage

Rice is more vulnerable to drought than maize, wheat, and sorghum because its water requirements remain high throughout the rice life cycle. The effects of drought vary depending on the timing, intensity, and duration of the events, as well as on the rice genotype and developmental stage. It can affect all levels of organization, from genes to the cells, tissues, and/or organs. In this study, a moderate water deficit was applied to two contrasting rice genotypes, IAC 25 and CIRAD 409, during their reproductive stage. Multi-level transcriptomic, metabolomic, physiological, and morphological analyses were performed to investigate the complex traits involved in their response to drought. Weighted gene network correlation analysis was used to identify the specific molecular mechanisms regulated by each genotype, and the correlations between gene networks and phenotypic traits. A holistic analysis of all the data provided a deeper understanding of the specific mechanisms regulated by each genotype, and enabled the identification of gene markers. Under non-limiting water conditions, CIRAD 409 had a denser shoot, but shoot growth was slower despite better photosynthetic performance. Under water deficit, CIRAD 409 was weakly affected regardless of the plant level analyzed. In contrast, IAC 25 had reduced growth and reproductive development. It regulated transcriptomic and metabolic activities at a high level, and activated a complex gene regulatory network involved in growth-limiting processes. By comparing two contrasting genotypes, the present study identified the regulation of some fundamental processes and gene markers, that drive rice development, and influence its response to water deficit, in particular, the importance of the biosynthetic and regulatory pathways for cell wall metabolism. These key processes determine the biological and mechanical properties of the cell wall and thus influence plant development, organ expansion, and turgor maintenance under water deficit. Our results also question the genericity of the antagonism between morphogenesis and organogenesis observed in the two genotypes.

Small RNAs, Large Networks: Posttranscriptional Regulons in Gram-Negative Bacteria

Small regulatory RNA (sRNAs) are key mediators of posttranscriptional gene control in bacteria. Assisted by RNA-binding proteins, a single sRNA often modulates the expression of dozens of genes, and thus sRNAs frequently adopt central roles in regulatory networks. Posttranscriptional regulation by sRNAs comes with several unique features that cannot be achieved by transcriptional regulators. However, for optimal network performance, transcriptional and posttranscriptional control mechanisms typically go hand-in-hand. This view is reflected by the ever-growing class of mixed network motifs involving sRNAs and transcription factors, which are ubiquitous in biology and whose regulatory properties we are beginning to understand. In addition, sRNA activity can be antagonized by base-pairing with sponge RNAs, adding yet another layer of complexity to these networks. In this article, we summarize the regulatory concepts underlying sRNA-mediated gene control in bacteria and discuss how sRNAs shape the output of a network, focusing on several key examples.

An unbiased seed-based RNAi selection screen identifies small RNAs that inhibit androgen signaling and prostate cancer cell growth

Blocking androgen receptor signaling is the mainstay of therapy for advanced prostate cancer (PCa). However, acquired resistance to single agents targeting this pathway results in the development of lethal castration-resistant PCa. Combination therapy approaches represent a promising strategy for the treatment of advanced disease. Here, we explore a therapeutic strategy for PCa based on the ability of shRNAs/siRNAs to function essentially as miRNAs and, via seed sequence complementarity, induce RNA interference of numerous targets simultaneously. We developed a library that contained shRNAs with all possible seed sequence combinations to identify those ones that most potently reduce cell growth and viability when expressed in PCa cells. Validation of some of these RNAi sequences indicated that the toxic effect is associated with seed sequence complementarity to the 3' UTR of AR coregulatory and essential genes. In fact, expression of siRNAs containing the identified toxic seed sequences led to global inhibition of AR-mediated gene expression and reduced expression of cell-cycle genes. When tested in mice, the toxic shRNAs also inhibited castration-resistant PCa and exhibited therapeutic efficacy in pre-established tumors. Our findings highlight RNAi of androgen signaling networks as a promising therapeutic strategy for PCa.

Plasma cortisol-linked gene networks in hepatic and adipose tissues implicate corticosteroid-binding globulin in modulating tissue glucocorticoid action and cardiovascular risk

Genome-wide association meta-analysis (GWAMA) by the Cortisol Network (CORNET) consortium identified genetic variants spanning the SERPINA6/SERPINA1 locus on chromosome 14 associated with morning plasma cortisol, cardiovascular disease (CVD), and SERPINA6 mRNA expression encoding corticosteroid-binding globulin (CBG) in the liver. These and other findings indicate that higher plasma cortisol levels are causally associated with CVD; however, the mechanisms by which variations in CBG lead to CVD are undetermined. Using genomic and transcriptomic data from The Stockholm Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET) study, we identified plasma cortisol-linked single-nucleotide polymorphisms (SNPs) that are trans-associated with genes from seven different vascular and metabolic tissues, finding the highest representation of trans-genes in the liver, subcutaneous fat, and visceral abdominal fat, [false discovery rate (FDR) = 15%]. We identified a subset of cortisol-associated trans-genes that are putatively regulated by the glucocorticoid receptor (GR), the primary transcription factor activated by cortisol. Using causal inference, we identified GR-regulated trans-genes that are responsible for the regulation of tissue-specific gene networks. Cis-expression Quantitative Trait Loci (eQTLs) were used as genetic instruments for identification of pairwise causal relationships from which gene networks could be reconstructed. Gene networks were identified in the liver, subcutaneous fat, and visceral abdominal fat, including a high confidence gene network specific to subcutaneous adipose (FDR = 10%) under the regulation of the interferon regulatory transcription factor, IRF2. These data identify a plausible pathway through which variation in the liver CBG production perturbs cortisol-regulated gene networks in peripheral tissues and thereby promote CVD.

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection

Hepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSystem. Gene expression regulation was statistically significant. Gene network analysis identified four out of 70 HCC marker genes whose expression regulation by viral proteins may be associated with HCC: DNA-binding protein inhibitor ID - 1 (ID1), flap endonuclease 1 (FEN1), cyclin-dependent kinase inhibitor 2A (CDKN2A), and telomerase reverse transcriptase (TERT). It suggested the following viral protein effects in HCV/human protein heterocomplexes: HCV NS3(p70) protein activates human STAT3 and NOTC1; NS2-3(p23), NS5B(p68), NS1(E2), and core(p21) activate SETD2; NS5A inhibits SMYD3; and NS3 inhibits CCN2. Interestingly, NS3 and E1(gp32) activate c-Jun when it positively regulates CDKN2A and inhibit it when it represses TERT. The discovered regulatory mechanisms might be key areas of focus for creating medications and preventative therapies to decrease the likelihood of HCC development during HCV infection.

Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks

A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.

C9orf72 gene networks in the human brain correlate with cortical thickness in C9-FTD and implicate vulnerable cell types

Introduction

A hexanucleotide repeat expansion (HRE) intronic to chromosome 9 open reading frame 72 (C9orf72) is recognized as the most common genetic cause of amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and ALS-FTD. Identifying genes that show similar regional co-expression patterns to C9orf72 may help identify novel gene targets and biological mechanisms that mediate selective vulnerability to ALS and FTD pathogenesis.

Methods

We leveraged mRNA expression data in healthy brain from the Allen Human Brain Atlas to evaluate C9orf72 co-expression patterns. To do this, we correlated average C9orf72 expression values in 51 regions across different anatomical divisions (cortex, subcortex, cerebellum) with average gene expression values for 15,633 protein-coding genes, including 50 genes known to be associated with ALS, FTD, or ALS-FTD. We then evaluated whether the identified C9orf72 co-expressed genes correlated with patterns of cortical thickness in symptomatic C9orf72 pathogenic HRE carriers (n=19). Lastly, we explored whether genes with significant C9orf72 radiogenomic correlations (i.e., 'C9orf72 gene network') were enriched in specific cell populations in the brain and enriched for specific biological and molecular pathways.

Results

A total of 1,748 genes showed an anatomical distribution of gene expression in the brain similar to C9orf72 and significantly correlated with patterns of cortical thickness in C9orf72 HRE carriers. This C9orf72 gene network was differentially expressed in cell populations previously implicated in ALS and FTD, including layer 5b cells, cholinergic motor neurons in the spinal cord, and medium spiny neurons of the striatum, and was enriched for biological and molecular pathways associated with multiple neurotransmitter systems, protein ubiquitination, autophagy, and MAPK signaling, among others.

Conclusions

Considered together, we identified a network of C9orf72-associated genes that may influence selective regional and cell-type-specific vulnerabilities in ALS/FTD.

The use of in silico extreme pathway (ExPa) analysis to identify conserved reproductive transcriptional-regulatory networks in humans, mice, and zebrafish

Vertebrate sex determination and differentiation are coordinated by the activations and maintenance of reproductive transcriptional-regulatory networks (TRNs). There is considerable interest in studying the conserved design principles and functions of reproductive TRNs given that their intricate regulation is susceptible to disruption by gene mutations or exposures to exogenous endocrine disrupting chemicals (or EDCs). In this manuscript, the Boolean rules describing reproductive TRNs in humans, mice, and zebrafish, were represented as a pseudo-stoichiometric matrix model. This model mathematically described the interactions of 35 transcription factors with 21 sex determination and differentiation genes across the three species. The in silico approach of Extreme Pathway (ExPa) analysis was used to predict the extent of TRN gene activations subject to the species-specific transcriptomics data, from across various developmental life-stages. A goal of this work was to identify conserved and functional reproductive TRNs across the three species. ExPa analyses predicted the sex differentiation genes, DHH, DMRT1, and AR, to be highly active in male humans, mice, and zebrafish. Whereas FOXL2 was the most active gene in female humans and mice; and CYP19A1A in female zebrafish. These results agree with the expectation that regardless of a lack of sex determination genes in zebrafish, the TRNs responsible for canalizing male vs. female sexual differentiation are conserved with mammalian taxa. ExPa analysis therefore provides a framework with which to study the TRNs that influence the development of sexual phenotypes. And the in silico predicted conservation of sex differentiation TRNs between mammals and zebrafish identifies the piscine species as an effective in vivo model to study mammalian reproductive systems under normal or perturbed pathologies.

Gene co-expression in response to Staphylococcus aureus infection reveals networks of genes with specific functions during bovine subclinical mastitis

Staphylococcus aureus is one of the most prevalent contagious bacterial pathogen of bovine mastitis. The subclinical mastitis it causes has long-term economic implications and it is difficult to control. To further understanding of the genetic basis of mammary gland defense against S. aureus infection, the transcriptomes of milk somatic cells from 15 cows with persistent natural S. aureus infection (S. aureus-positive, SAP) and 10 healthy control cows (HC) were studied by deep RNA-sequencing technology. Comparing the transcriptomes of SAP to HC group revealed 4,077 differentially expressed genes (DEG; 1,616 up- and 2,461 downregulated). Functional annotation indicated enrichment of DEG in 94 Gene Ontology (GO) and 47 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Terms related to the immune response and disease processes were mostly enriched for by upregulated DEG, whereas biological process terms related to cell adhesion, cell movement and localization, and tissue development were mostly enriched for by downregulated DEG. Weighted gene co-expression network analysis grouped DEG into 7 modules, the most important module (colored turquoise by software and here referred to as Turquoise module) was positively significantly correlated with S. aureus subclinical mastitis. The 1,546 genes in the Turquoise module were significantly enriched in 48 GO terms and 72 KEGG pathways, with 80% of them being disease- and immune-related terms [e.g., immune system process (GO:0002376), cytokine-cytokine receptor interaction (bta04060) and S. aureus infection (bta05150)]. Some DEG such as IFNG, IL18, IL1B, NFKB1, CXCL8, and IL12B were enriched in immune and disease pathways suggesting their possible involvement in the regulation of the host response to S. aureus infection. Four modules (Yellow, Brown, Blue, and Red) were negatively correlated (significantly) with S. aureus subclinical mastitis, and were enriched in functional annotations involved in the regulation of cell migration, cell communication, metabolic process, and blood circulatory system development, respectively. Application of sparse partial least squares discriminant analysis to genes of the Turquoise module identified 5 genes (NR2F6, PDLIM5, RAB11FIP5, ACOT4, and TMEM53) capable of explaining the majority of the differences in the expression patterns between SAP and HC cows. In conclusion, this study has furthered understanding of the genetic changes in the mammary gland and the molecular mechanisms underlying S. aureus mastitis, as well as revealed a list of candidate discriminant genes with potential regulatory roles in response to S. aureus infection.

Different chromatin-scanning modes lead to targeting of compacted chromatin by pioneer factors FOXA1 and SOX2

Pioneer transcription factors interact with nucleosomes to scan silent, compact chromatin, enabling cooperative events that modulate gene activity. While at a subset of sites pioneer factors access chromatin by assisted loading with other transcription factors, the nucleosome-binding properties of pioneer factors enable them to initiate zygotic genome activation, embryonic development, and cellular reprogramming. To better understand nucleosome targeting in vivo, we assess whether pioneer factors FoxA1 and Sox2 target stable or unstable nucleosomes and find that they target DNase-resistant, stable nucleosomes, whereas HNF4A, a non-nucleosome binding factor, targets open, DNase-sensitive chromatin. Despite FOXA1 and SOX2 targeting similar proportions of DNase-resistant chromatin, using single-molecule tracking, we find that FOXA1 uses lower nucleoplasmic diffusion and longer residence times while SOX2 uses higher nucleoplasmic diffusion and shorter residence times to scan compact chromatin, while HNF4 scans compact chromatin much less efficiently. Thus, pioneer factors target compact chromatin through distinct processes.

Emergent molecular traits of lettuce and tomato grown under wavelength-selective solar cells

The integration of semi-transparent organic solar cells (ST-OSCs) in greenhouses offers new agrivoltaic opportunities to meet the growing demands for sustainable food production. The tailored absorption/transmission spectra of ST-OSCs impacts the power generated as well as crop growth, development and responses to the biotic and abiotic environments. To characterize crop responses to ST-OSCs, we grew lettuce and tomato, traditional greenhouse crops, under three ST-OSC filters that create different light spectra. Lettuce yield and early tomato development are not negatively affected by the modified light environment. Our genomic analysis reveals that lettuce production exhibits beneficial traits involving nutrient content and nitrogen utilization while select ST-OSCs impact regulation of flowering initiation in tomato. These results suggest that ST-OSCs integrated into greenhouses are not only a promising technology for energy-neutral, sustainable and climate-change protected crop production, but can deliver benefits beyond energy considerations.

Using Machine Learning to Explore Shared Genetic Pathways and Possible Endophenotypes in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a heterogeneous condition, characterized by complex genetic architectures and intertwined genetic/environmental interactions. Novel analysis approaches to disentangle its pathophysiology by computing large amounts of data are needed. We present an advanced machine learning technique, based on a clustering analysis on genotypical/phenotypical embedding spaces, to identify biological processes that might act as pathophysiological substrates for ASD. This technique was applied to the VariCarta database, which contained 187,794 variant events retrieved from 15,189 individuals with ASD. Nine clusters of ASD-related genes were identified. The 3 largest clusters included 68.6% of all individuals, consisting of 1455 (38.0%), 841 (21.9%), and 336 (8.7%) persons, respectively. Enrichment analysis was applied to isolate clinically relevant ASD-associated biological processes. Two of the identified clusters were characterized by individuals with an increased presence of variants linked to biological processes and cellular components, such as axon growth and guidance, synaptic membrane components, or transmission. The study also suggested other clusters with possible genotype-phenotype associations. Innovative methodologies, including machine learning, can improve our understanding of the underlying biological processes and gene variant networks that undergo the etiology and pathogenic mechanisms of ASD. Future work to ascertain the reproducibility of the presented methodology is warranted.

Contrast subgraphs allow comparing homogeneous and heterogeneous networks derived from omics data

BACKGROUND

Biological networks are often used to describe the relationships between relevant entities, particularly genes and proteins, and are a powerful tool for functional genomics. Many important biological problems can be investigated by comparing biological networks between different conditions or networks obtained with different techniques.

FINDINGS

We show that contrast subgraphs, a recently introduced technique to identify the most important structural differences between 2 networks, provide a versatile tool for comparing gene and protein networks of diverse origin. We demonstrate the use of contrast subgraphs in the comparison of coexpression networks derived from different subtypes of breast cancer, coexpression networks derived from transcriptomic and proteomic data, and protein-protein interaction networks assayed in different cell lines.

CONCLUSIONS

These examples demonstrate how contrast subgraphs can provide new insight in functional genomics by extracting the gene/protein modules whose connectivity is most altered between 2 conditions or experimental techniques.

Effects of PUFA-Rich Dietary Strategies on Ruminants' Mammary Gland Gene Network: A Nutrigenomics Review

Although the inclusion of polyunsaturated fatty acids (PUFAs) in ruminants' diets appears to be a well-documented strategy to enrich milk with PUFAs, several gene networks that regulate milk synthesis and mammary gland homeostasis could be impaired. The objective of this literature review is to assess the effects of nutritional strategies focused on enriching milk with PUFAs on gene networks regulating mammary gland function and lipogenesis, as well as the impact of feed additives and bioactive compounds with prominent antioxidant potential on immune-oxidative transcriptional profiling, as a part of mammary gland homeostasis and health. The findings support the conclusion that PUFAs' inclusion in ruminants' diets more strongly downregulate the stearoyl-CoA desaturase (SCD) gene compared to other key genes involved in de novo fatty acid synthesis in the mammary gland. Additionally, it was revealed that seed oils rich in linoleic and linolenic acids have no such strong impact on networks that regulate lipogenic homeostasis compared to marine oils rich in eicosapentaenoic and docosahexaenoic acids. Furthermore, ample evidence supports that cows and sheep are more prone to the suppression of lipogenesis pathways compared to goats under the impact of dietary marine PUFAs. On the other hand, the inclusion of feed additives and bioactive compounds with prominent antioxidant potential in ruminants' diets can strengthen mammary gland immune-oxidative status. Considering that PUFA's high propensity to oxidation can induce a cascade of pro-oxidant incidences, the simultaneous supplementation of antioxidant compounds and especially polyphenols may alleviate any side effects caused by PUFA overload in the mammary gland. In conclusion, future studies should deeply investigate the effects of PUFAs on mammary gland gene networks in an effort to holistically understand their impact on both milk fat depression syndrome and homeostatic disturbance.

Negatively Competitive Incoherent Feedforward Loops Mitigate Winner-Take-All Resource Competition

The effects of host resource limitations on the function of synthetic gene circuits have gained significant attention over the past years. Hosts, having evolved resource capacities optimal for their own genome, have been repeatedly demonstrated to suffer from the added burden of synthetic genetic programs, which may in return pose deleterious effects on the circuit's function. Three resource controller archetypes have been proposed previously to mitigate resource distribution problems in dynamic circuits: the local controller, the global controller, and a "negatively competitive" regulatory (NCR) controller that utilizes synthetic competition to combat resource competition. The dynamics of negative feedback forms of these controllers have been previously investigated, and here we extend the analysis of these resource allocation strategies to the incoherent feedforward loop (iFFL) topology. We demonstrate that the three iFFL controllers can attenuate Winner-Take-All resource competition between two bistable switches. We uncover that the parameters associated with the synthetic competition in the NCR iFFL controller are paramount to its increased efficacy over the local controller type, while the global controllers demonstrate to be relatively ineffectual. Interestingly, unlike the negative feedback counterpart topologies, iFFL controllers exhibit a unique coupling of switch activation thresholds which we term the "coactivation threshold shift" effect. Finally, we demonstrate that a nearly fully orthogonal set of bistable switches could be achieved by pairing an NCR controller with an appropriate level of controller resource consumption.

Insight into Glyproline Peptides' Activity through the Modulation of the Inflammatory and Neurosignaling Genetic Response Following Cerebral Ischemia-Reperfusion

Glyprolines are Gly-Pro (GP)- or Pro-Gly (PG)-containing biogenic peptides. These peptides can act as neutrophil chemoattractants, or atheroprotective, anticoagulant, and neuroprotective agents. The Pro-Gly-Pro (PGP) tripeptide is an active factor of resistance to the biodegradation of peptide drugs. The synthetic Semax peptide, which includes Met-Glu-His-Phe (MEHF) fragments of adrenocorticotropic hormone and the C-terminal tripeptide PGP, serves as a neuroprotective drug for the treatment of ischemic stroke. Previously, we revealed that Semax mostly prevented the disruption of the gene expression pattern 24 h after a transient middle cerebral artery occlusion (tMCAO) in a rat brain model. The genes of this pattern were grouped into an inflammatory cluster (IC) and a neurotransmitter cluster (NC). Here, using real-time RT-PCR, the effect of other PGP-containing peptides, PGP and Pro-Gly-Pro-Leu (PGPL), on the expression of a number of genes in the IC and NC was studied 24 h after tMCAO. Both the PGP and PGPL peptides showed Semax-unlike effects, predominantly without changing gene expression 24 h after tMCAO. Moreover, there were IC genes (iL1b, iL6, and Socs3) for PGP, as well as IC (iL6, Ccl3, Socs3, and Fos) and NC genes (Cplx2, Neurod6, and Ptk2b) for PGPL, that significantly changed in expression levels after peptide administration compared to Semax treatment under tMCAO conditions. Furthermore, gene enrichment analysis was carried out, and a regulatory gene network was constructed. Thus, the spectra of the common and unique effects of the PGP, PGPL, and Semax peptides under ischemia-reperfusion were distinguished.

Heat and drought induced transcriptomic changes in barley varieties with contrasting stress response phenotypes

Drought and heat stress substantially impact plant growth and productivity. When subjected to drought or heat stress, plants exhibit reduction in growth resulting in yield losses. The occurrence of these two stresses together intensifies their negative effects. Unraveling the molecular changes in response to combined abiotic stress is essential to breed climate-resilient crops. In this study, transcriptome profiles were compared between stress-tolerant (Otis), and stress-sensitive (Golden Promise) barley genotypes subjected to drought, heat, and combined heat and drought stress for five days during heading stage. The major differences that emerged from the transcriptome analysis were the overall number of differentially expressed genes was relatively higher in Golden Promise (GP) compared to Otis. The differential expression of more than 900 transcription factors in GP and Otis may aid this transcriptional reprogramming in response to abiotic stress. Secondly, combined heat and water deficit stress results in a unique and massive transcriptomic response that cannot be predicted from individual stress responses. Enrichment analyses of gene ontology terms revealed unique and stress type-specific adjustments of gene expression. Weighted Gene Co-expression Network Analysis identified genes associated with RNA metabolism and Hsp70 chaperone components as hub genes that can be useful for engineering tolerance to multiple abiotic stresses. Comparison of the transcriptomes of unstressed Otis and GP plants identified several genes associated with biosynthesis of antioxidants and osmolytes were higher in the former that maybe providing innate tolerance capabilities to effectively combat hostile conditions. Lines with different repertoire of innate tolerance mechanisms can be effectively leveraged in breeding programs for developing climate-resilient barley varieties with superior end-use traits.

Computer analysis of regulation of hepatocarcinoma marker genes hypermethylated by HCV proteins

Hepatitis C virus (HCV) is a risk factor that leads to hepatocellular carcinoma (HCC) development. Epigenetic changes are known to play an important role in the molecular genetic mechanisms of virus-induced oncogenesis. Aberrant DNA methylation is a mediator of epigenetic changes that are closely associated with the HCC pathogenesis and considered a biomarker for its early diagnosis. The ANDSystem software package was used to reconstruct and evaluate the statistical significance of the pathways HCV could potentially use to regulate 32 hypermethylated genes in HCC, including both oncosuppressor and protumorigenic ones identified by genome-wide analysis of DNA methylation. The reconstructed pathways included those affecting protein-protein interactions (PPI), gene expression, protein activity, stability, and transport regulations, the expression regulation pathways being statistically significant. It has been shown that 8 out of 10 HCV proteins were involved in these pathways, the HCV NS3 protein being implicated in the largest number of regulatory pathways. NS3 was associated with the regulation of 5 tumor-suppressor genes, which may be the evidence of its central role in HCC pathogenesis. Analysis of the reconstructed pathways has demonstrated that following the transcription factor inhibition caused by binding to viral proteins, the expression of a number of oncosuppressors (WT1, MGMT, SOCS1, P53) was suppressed, while the expression of others (RASF1, RUNX3, WIF1, DAPK1) was activated. Thus, the performed gene-network reconstruction has shown that HCV proteins can influence not only the methylation status of oncosuppressor genes, but also their transcriptional regulation. The results obtained can be used in the search for pharmacological targets to develop new drugs against HCV-induced HCC.

Single-Cell Sequencing Identifies Master Regulators Affected by Panobinostat in Neuroblastoma Cells

The molecular mechanisms and gene regulatory networks sustaining cell proliferation in neuroblastoma (NBL) cells are still not fully understood. In this tumor context, it has been proposed that anti-proliferative drugs, such as the pan-HDAC inhibitor panobinostat, could be tested to mitigate tumor progression. Here, we set out to investigate the effects of panobinostat treatment at the unprecedented resolution offered by single-cell sequencing. We identified a global senescence signature paired with reduction in proliferation in treated Kelly cells and more isolated transcriptional responses compatible with early neuronal differentiation. Using master regulator analysis, we identified BAZ1A, HCFC1, MAZ, and ZNF146 as the transcriptional regulators most significantly repressed by panobinostat. Experimental silencing of these transcription factors (TFs) confirmed their role in sustaining NBL cell proliferation in vitro.

Key gene networks that control magnetosome biomineralization in magnetotactic bacteria

Magnetotactic bacteria (MTB) are a group of phylogenetically and morphologically diverse prokaryotes that have the capability of sensing Earth's magnetic field via nanocrystals of magnetic iron minerals. These crystals are enclosed within intracellular membranes or organelles known as magnetosomes and enable a sensing function known as magnetotaxis. Although MTB were discovered over half a century ago, the study of the magnetosome biogenesis and organization remains limited to a few cultured MTB strains. Here, we present an integrative genomic and phenomic analysis to investigate the genetic basis of magnetosome biomineralization in both cultured and uncultured strains from phylogenetically diverse MTB groups. The magnetosome gene contents/networks of strains are correlated with magnetic particle morphology and chain configuration. We propose a general model for gene networks that control/regulate magnetosome biogenesis and chain assembly in MTB systems.

Evaluation of Personalized Skincare Through in-silico Gene Interactive Networks and Cellular Responses to UVR and Oxidative Stress

Purpose

Personalized approaches in dermatology are designed to match the specific requirements based on the individual genetic makeup. One major factor accounting for the differences in skin phenotypes is single nucleotide polymorphism (SNP) within several genes with diverse roles that extend beyond skin tone and pigmentation. Therefore, the cellular sensitivities to the environmental stress and damage linked to extrinsic aging could also underlie the individual characteristics of the skin and dictate the unique skin care requirements. This study aimed to identify the likely biomarkers and molecular signatures expressed in skin cells of different ethnic backgrounds, which could aid further the design of personalized skin products based on specific demands.

Methods

Using data mining and in-silico modeling, the association of SNP-affected genes with three major skin types of European, Asian and African origin was analyzed and compared within the structure-function gene interaction networks. Cultured dermal fibroblasts were subsequently subjected to ultraviolet radiation and oxidative stress and analyzed for DNA damage and senescent markers. The protective applications of two cosmetic ingredients, Resveratrol and Quercetin, were validated in both cellular and in-silico models.

Results

Each skin type was characterized by the presence of SNPs in the genes controlling facultative and constitutive pigmentation, which could also underlie the major differences in responses to photodamage, such as oxidative stress, inflammation, and barrier homeostasis. Skin-type-specific dermal fibroblasts cultured in-vitro demonstrated distinctive sensitivities to ultraviolet radiation and oxidative stress, which could be modulated further by the bioactive compounds with the predicted capacities to interact with some of the genes in the in-silico models.

Conclusion

Evaluation of the SNP-affected gene networks and likely sensitivities of skin cells, defined as low threshold levels to extrinsic stress factors, can provide a valuable tool for the design and formulation of personalized skin products that match more accurately diverse ethnic backgrounds.

Evidence for a conserved queen-worker genetic toolkit across slave-making ants and their ant hosts

The ecological success of social Hymenoptera (ants, bees, wasps) depends on the division of labour between the queen and workers. Each caste exhibits highly specialised morphology, behaviour, and life-history traits, such as lifespan and fecundity. Despite strong defences against alien intruders, insect societies are vulnerable to social parasites, such as workerless inquilines or slave-making ants. Here, we investigate whether gene expression varies in parallel ways between lifestyles (slave-making versus host ants) across five independent origins of ant slavery in the "Formicoxenus-group" of the ant tribe Crematogastrini. As caste differences are often less pronounced in slave-making ants than in non-parasitic ants, we also compare caste-specific gene expression patterns between lifestyles. We demonstrate a substantial overlap in expression differences between queens and workers across taxa, irrespective of lifestyle. Caste affects the transcriptomes much more profoundly than lifestyle, as indicated by 37 times more genes being linked to caste than to lifestyle and by multiple caste-associated modules of co-expressed genes with strong connectivity. However, several genes and one gene module are linked to slave-making across the independent origins of this parasitic lifestyle, pointing to some evolutionary convergence. Finally, we do not find evidence for an interaction between caste and lifestyle, indicating that caste differences in gene expression remain consistent even when species switch to a parasitic lifestyle. Our findings strongly support the existence of a core set of genes whose expression is linked to the queen and worker caste in this ant taxon, as proposed by the "genetic toolkit" hypothesis.

Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize

Rapid population growth and increasing demand for food, feed, and bioenergy in these times of unprecedented climate change require breeding for increased biomass production on the world's croplands. To accelerate breeding programs, knowledge of the relationship between biomass features and underlying gene networks is needed to guide future breeding efforts. To this end, large-scale multiomics datasets were created with genetically diverse maize lines, all grown in long-term organic and conventional cropping systems. Analysis of the datasets, integrated using regression modeling and network analysis revealed key metabolites, elements, gene transcripts, and gene networks, whose contents during vegetative growth substantially influence the build-up of plant biomass in the reproductive phase. We found that S and P content in the source leaf and P content in the root during the vegetative stage contributed the most to predicting plant performance at the reproductive stage. In agreement with the Gene Ontology enrichment analysis, the cis-motifs and identified transcription factors associated with upregulated genes under phosphate deficiency showed great diversity in the molecular response to phosphate deficiency in selected lines. Furthermore, our data demonstrate that genotype-dependent uptake, assimilation, and allocation of essential nutrient elements (especially C and N) during vegetative growth under phosphate starvation plays an important role in determining plant biomass by controlling root traits related to nutrient uptake. These integrative multiomics results revealed key factors underlying maize productivity and open new opportunities for efficient, rapid, and cost-effective plant breeding to increase biomass yield of the cereal crop maize under adverse environmental factors.

The Emerging Roles of Long Non-Coding RNAs in Intellectual Disability and Related Neurodevelopmental Disorders

In the human brain, long non-coding RNAs (lncRNAs) are widely expressed in an exquisitely temporally and spatially regulated manner, thus suggesting their contribution to normal brain development and their probable involvement in the molecular pathology of neurodevelopmental disorders (NDD). Bypassing the classic protein-centric conception of disease mechanisms, some studies have been conducted to identify and characterize the putative roles of non-coding sequences in the genetic pathogenesis and diagnosis of complex diseases. However, their involvement in NDD, and more specifically in intellectual disability (ID), is still poorly documented and only a few genomic alterations affecting the lncRNAs function and/or expression have been causally linked to the disease endophenotype. Considering that a significant fraction of patients still lacks a genetic or molecular explanation, we expect that a deeper investigation of the non-coding genome will unravel novel pathogenic mechanisms, opening new translational opportunities. Here, we present evidence of the possible involvement of many lncRNAs in the etiology of different forms of ID and NDD, grouping the candidate disease-genes in the most frequently affected cellular processes in which ID-risk genes were previously collected. We also illustrate new approaches for the identification and prioritization of NDD-risk lncRNAs, together with the current strategies to exploit them in diagnosis.

Feature selection and classification over the network with missing node observations

Jointly analyzing transcriptomic data and the existing biological networks can yield more robust and informative feature selection results, as well as better understanding of the biological mechanisms. Selecting and classifying node features over genome-scale networks has become increasingly important in genomic biology and genomic medicine. Existing methods have some critical drawbacks. The first is they do not allow flexible modeling of different subtypes of selected nodes. The second is they ignore nodes with missing values, very likely to increase bias in estimation. To address these limitations, we propose a general modeling framework for Bayesian node classification (BNC) with missing values. A new prior model is developed for the class indicators incorporating the network structure. For posterior computation, we resort to the Swendsen-Wang algorithm for efficiently updating class indicators. BNC can naturally handle missing values in the Bayesian modeling framework, which improves the node classification accuracy and reduces the bias in estimating gene effects. We demonstrate the advantages of our methods via extensive simulation studies and the analysis of the cutaneous melanoma dataset from The Cancer Genome Atlas.

Temporal Gene Expression Profiles Reflect the Dynamics of Lymphoid Differentiation

Understanding the emergence of lymphoid committed cells from multipotent progenitors (MPP) is a great challenge in hematopoiesis. To gain deeper insight into the dynamic expression changes associated with these transitions, we report the quantitative transcriptome of two MPP subsets and the common lymphoid progenitor (CLP). While the transcriptome is rather stable between MPP2 and MPP3, expression changes increase with differentiation. Among those, we found that pioneer lymphoid genes such as Rag1, Mpeg1, and Dntt are expressed continuously from MPP2. Others, such as CD93, are CLP specific, suggesting their potential use as new markers to improve purification of lymphoid populations. Notably, a six-transcription factor network orchestrates the lymphoid differentiation program. Additionally, we pinpointed 24 long intergenic-non-coding RNA (lincRNA) differentially expressed through commitment and further identified seven novel forms. Collectively, our approach provides a comprehensive landscape of coding and non-coding transcriptomes expressed during lymphoid commitment.

A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs

In recent years, the increase in awareness of antimicrobial resistance together with the societal demand of healthier meat products have driven attention to health-related traits in livestock production. Previous studies have reported medium to high heritabilities for these traits and described genomic regions associated with them. Despite its genetic component, health- and immunity-related traits are complex and its study by association analysis with genomic markers may be missing some information. To analyse multiple phenotypes and gene-by-gene interactions, systems biology approaches, such as the association weight matrix (AWM), allows combining genome wide association study results with network inference algorithms. The present study aimed to identify gene networks, key regulators and candidate genes associated to immunocompetence in pigs by integrating multiple health-related traits, enriched for innate immune phenotypes, using the AWM approach. The co-association network analysis unveiled a network comprised of 3,636 nodes (genes) and 451,407 edges (interactions), including a total of 246 regulators. From these, five genes (ARNT2, BRMS1L, MED12L, SUPT3H and TRIM25) were selected as key regulators as they were associated with the maximum number of genes with the minimum overlapping (1,827 genes in total). The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. Furthermore, we identified genes co-associated with the key regulators previously reported as candidate genes (e.g., ANGPT1, CD4, CD36, DOCK1, PDE4B, PRKCE, PTPRC and SH2B3) for immunity traits in humans and pigs, but also new candidate ones (e.g., ACSL3, CXADR, HBB, MMP12, PTPN6, WLS) that were not previously described. The co-association analysis revealed new regulators associated with health-related traits in pigs. This approach also identified gene-by-gene interactions and candidate genes involved in pathways related to cell fate and metabolic and immune functions. Our results shed new light in the regulatory mechanisms involved in pig immunity and reinforce the use of the pig as biomedical model.

Gestational Age Dependence of the Maternal Circulating Long Non-Coding RNA Transcriptome During Normal Pregnancy Highlights Antisense and Pseudogene Transcripts

In the post-genomic era, our understanding of the molecular regulators of physiologic and pathologic processes in pregnancy is expanding at the whole-genome level. Longitudinal changes in the known protein-coding transcriptome during normal pregnancy, which we recently reported (Gomez-Lopez et al., 2019), have improved our definition of the major operant networks, yet pregnancy-related functions of the non-coding RNA transcriptome remain poorly understood. A key finding of the ENCODE (Encyclopedia of DNA Elements) Consortium, the successor of the Human Genome Project, was that the human genome contains approximately 60,000 genes, the majority of which do not encode proteins. The total transcriptional output of non-protein-coding RNA genes, collectively referred to as the non-coding transcriptome, is comprised mainly of long non-coding RNA (lncRNA) transcripts (Derrien et al., 2012). Although the ncRNA transcriptome eclipses its protein-coding counterpart in abundance, it has until recently lacked a comprehensive, unbiased, genome-scale characterization over the timecourse of normal human pregnancy. Here, we annotated, characterized, and selectively validated the longitudinal changes in the non-coding transcriptome of maternal whole blood during normal pregnancy to term. We identified nine long non-coding RNAs (lncRNAs), including long intergenic non-coding RNAs (lincRNAs) as well as lncRNAs antisense to or otherwise in the immediate vicinity of protein-coding genes, that were differentially expressed with advancing gestation in normal pregnancy: AL355711, BC039551 (expressed mainly in the placenta), JHDM1D-AS1, A2M-AS1, MANEA-AS1, NR_034004, LINC00649, LINC00861, and LINC01094. By cross-referencing our dataset against major public pseudogene catalogs, we also identified six transcribed pseudogenes that were differentially expressed over time during normal pregnancy in maternal blood: UBBP4, FOXO3B, two Makorin (MKRN) pseudogenes (MKRN9P and LOC441455), PSME2P2, and YBX3P1. We also identified three non-coding RNAs belonging to other classes that were modulated during gestation: the microRNA MIR4439, the small nucleolar RNA (snoRNA) SNORD41, and the small Cajal-body specific ncRNA SCARNA2. The expression profiles of most hits were broadly suggestive of functions in pregnancy. These time-dependent changes of the non-coding transcriptome during normal pregnancy, which may confer specific regulatory impacts on their protein-coding gene targets, will facilitate a deeper molecular understanding of pregnancy and lncRNA-mediated molecular pathways at the maternal-fetal interface and of how these pathways impact maternal and fetal health.

Hypoglycemia, Vascular Disease and Cognitive Dysfunction in Diabetes: Insights from Text Mining-Based Reconstruction and Bioinformatics Analysis of the Gene Networks

Hypoglycemia has been recognized as a risk factor for diabetic vascular complications and cognitive decline, but the molecular mechanisms of the effect of hypoglycemia on target organs are not fully understood. In this work, gene networks of hypoglycemia and cardiovascular disease, diabetic retinopathy, diabetic nephropathy, diabetic neuropathy, cognitive decline, and Alzheimer's disease were reconstructed using ANDSystem, a text-mining-based tool. The gene network of hypoglycemia included 141 genes and 2467 interactions. Enrichment analysis of Gene Ontology (GO) biological processes showed that the regulation of insulin secretion, glucose homeostasis, apoptosis, nitric oxide biosynthesis, and cell signaling are significantly enriched for hypoglycemia. Among the network hubs, INS, IL6, LEP, TNF, IL1B, EGFR, and FOS had the highest betweenness centrality, while GPR142, MBOAT4, SLC5A4, IGFBP6, PPY, G6PC1, SLC2A2, GYS2, GCGR, and AQP7 demonstrated the highest cross-talk specificity. Hypoglycemia-related genes were overrepresented in the gene networks of diabetic complications and comorbidity; moreover, 14 genes were mutual for all studied disorders. Eleven GO biological processes (glucose homeostasis, nitric oxide biosynthesis, smooth muscle cell proliferation, ERK1 and ERK2 cascade, etc.) were overrepresented in all reconstructed networks. The obtained results expand our understanding of the molecular mechanisms underlying the deteriorating effects of hypoglycemia in diabetes-associated vascular disease and cognitive dysfunction.

Glioblastoma gene network reconstruction and ontology analysis by online bioinformatics tools

Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.

A hidden threshold in motor neuron gene networks revealed by modulation of miR-218 dose

Disruption of homeostatic microRNA (miRNA) expression levels is known to cause human neuropathology. However, the gene regulatory and phenotypic effects of altering a miRNA's in vivo abundance (rather than its binary gain or loss) are not well understood. By genetic combination, we generated an allelic series of mice expressing varying levels of miR-218, a motor neuron-selective gene regulator associated with motor neuron disease. Titration of miR-218 cellular dose unexpectedly revealed complex, non-ratiometric target mRNA dose responses and distinct gene network outputs. A non-linearly responsive regulon exhibited a steep miR-218 dose-dependent threshold in repression that, when crossed, resulted in severe motor neuron synaptic failure and death. This work demonstrates that a miRNA can govern distinct gene network outputs at different expression levels and that miRNA-dependent phenotypes emerge at particular dose ranges because of hidden regulatory inflection points of their underlying gene networks.

On the Use of Heterogeneous Stock Mice to Map Transcriptomes Associated With Excessive Ethanol Consumption

We and many others have noted the advantages of using heterogeneous (HS) animals to map genes and gene networks associated with both behavioral and non-behavioral phenotypes. Importantly, genetically complex Mus musculus crosses provide substantially increased resolution to examine old and new relationships between gene expression and behavior. Here we report on data obtained from two HS populations: the HS/NPT derived from eight inbred laboratory mouse strains and the HS-CC derived from the eight collaborative cross inbred mouse strains that includes three wild-derived strains. Our work has focused on the genes and gene networks associated with risk for excessive ethanol consumption, individual variation in ethanol consumption and the consequences, including escalation, of long-term ethanol consumption. Background data on the development of HS mice is provided, including advantages for the detection of expression quantitative trait loci. Examples are also provided of using HS animals to probe the genes associated with ethanol preference and binge ethanol consumption.