Genome-wide dissection of AT-hook motif nuclear-localized gene family and their expression profiling for drought and salt stress in rice (Oryza sativa)

AT-hook motif nuclear localized (AHL) genes are functionally very less explored, but their nature is very diverse. In the present study, we identified 20 AHL genes in rice. Phylogenetic analyses and evolutionary classification of AHL genes showed that they are conserved in plants, but the number of genes is still expanding in different crops and regulating new biological functions. Gene structure analysis showed that OsAHLs are with and without intron types of genes, suggesting that AHL genes added intron during evolution for neofunctionalization. The cis analysis of OsAHL genes suggested its motif diversity. In order to understand the function, 19 transcriptomes were identified from various tissues and different developmental stages of rice, and they were divided into eight groups by different temporal and spatial expression. Through co-expression analysis, 11 OsAHLs and 13 novel genes with intricate networks that control many biological pathways in rice were identified. The interactions of OsAHL proteins showed that they co-regulate important processes including flowering, reproductive organ development, and photosynthesis activity. The functionality of all 20 genes of OsAHL for drought and salt stress in leaf tissues of two contrasting genotypes (IR64 and NL44) of rice was studied using qRT-PCR. The result clearly showed significant upregulation of OsAHL genes under drought and salt conditions over the control. The differential expression between IR64 and NL44 showed a significant upregulation of OsAHL genes in NL44 as compared to the IR64 genotype under drought and salt stress. Overall, the result indicates that AHL genes might be involved in mediating drought and salt-signaling transduction pathways. The drought- and salt-tolerant nature of NL44 was also confirmed by expression profiling.

microRNA-mRNA Analysis Reveals Tissue-Specific Regulation of microRNA in Mangrove Clam (Geloina erosa)

Geloina erosa is an important benthic animal in the mangrove, serving as an indicator organism for coastal environmental pollution. This study aimed to investigate the tissue-specific expression of miRNAs and their regulatory roles in predicted targets in G. erosa. Through miRNA sequencing and co-expression network analysis, we extensively studied the miRNA expression in three tissues: gills, hepatopancreas, and muscle. The results revealed a total of 1412 miRNAs, comprising 1047 known miRNAs, and 365 newly predicted miRNAs. These miRNAs exhibited distinct tissue-specific expression patterns. In the miRNA target gene prediction, a total of 7404 potential predicted targets were identified, representing approximately 33% of all unique transcripts associated with miRNAs. Further co-expression network analysis revealed nine modules, each showing a positive correlation with specific tissues (gills, hepatopancreas, or muscle). The blue module showed a significant correlation with gills (r = 0.83, p-value = 0.006), the black module was significantly related to the hepatopancreas (r = 0.78, p-value = 0.01), and the purple module was significantly correlated with muscle (r = 0.83, p-value = 0.006). Within these modules, related miRNAs tended to cluster together, while their correlations with other modules were relatively weak. Functional enrichment analysis was performed on miRNAs and their predicted targets in each tissue. In the gills, miRNAs primarily regulate immune-related genes, substance transport, and cytoskeletal organization. In the hepatopancreas, miRNAs suppressed genes involved in shell formation and played a role in cellular motor activity and metabolism. In muscle, miRNAs participate in metabolism and photoreceptive processes, as well as immune regulation. In summary, this study provides valuable insights into the tissue-specific regulation of miRNAs in G. erosa, highlighting their potential roles in immune response, metabolism, and environmental adaptation. These findings offer important clues for understanding the molecular mechanisms and biological processes in G. erosa, laying the foundation for further validation and elucidation of these regulatory relationships.

Bioinformatic Identification of Potential RNA Alterations on the Atrial Fibrillation Remodeling from Human Pulmonary Veins

Atrial fibrillation (AF) is the most frequent persistent arrhythmia. Many genes have been reported as a genetic background for AF. However, most transcriptome analyses of AF are limited to the atrial samples and have not been evaluated by multiple cardiac regions. In this study, we analyzed the expression levels of protein-coding and long noncoding RNAs (lncRNAs) in six cardiac regions by RNA-seq. Samples were donated from six subjects with or without persistent AF for left atria, left atrial appendages, right atria, sinoatrial nodes, left ventricles, right ventricles, and pulmonary veins (PVs), and additional four right atrial appendages samples were collected from patients undergoing mitral valve replacement. In total, 23 AF samples were compared to 23 non-AF samples. Surprisingly, the most influenced heart region in gene expression by AF was the PV, not the atria. The ion channel-related gene set was significantly enriched upon analysis of these significant genes. In addition, some significant genes are cancer-related lncRNAs in PV in AF. A co-expression network analysis could detect the functional gene clusters. In particular, the cancer-related lncRNA, such as SAMMSON and FOXCUT, belong to the gene network with the cancer-related transcription factor FOXC1. Thus, they may also play an aggravating role in the pathogenesis of AF, similar to carcinogenesis. In the least, this study suggests that (1) RNA alteration is most intense in PVs and (2) post-transcriptional gene regulation by lncRNA may contribute to the progression of AF. Through the screening analysis across the six cardiac regions, the possibility that the PV region can play a role other than paroxysmal triggering in the pathogenesis of AF was demonstrated for the first time. Future research with an increase in the number of PV samples will lead to a novel understanding of the pathophysiology of AF.

Ferroptosis-related genes are involved in asthma and regulate the immune microenvironment

Background: Asthma was a chronic inflammatory illness driven by complicated genetic regulation and environmental exposure. The complex pathophysiology of asthma has not been fully understood. Ferroptosis was involved in inflammation and infection. However, the effect of ferroptosis on asthma was still unclear. The study was designed to identify ferroptosis-related genes in asthma, providing potential therapeutic targets. Methods: We conducted a comprehensive analysis combined with WGCNA, PPI, GO, KEGG, and CIBERSORT methods to identify ferroptosis-related genes that were associated with asthma and regulated the immune microenvironment in GSE147878 from the GEO. The results of this study were validated in GSE143303 and GSE27066, and the hub genes related to ferroptosis were further verified by immunofluorescence and RT-qPCR in the OVA asthma model. Results: 60 asthmatics and 13 healthy controls were extracted for WGCNA. We found that genes in the black module (r = -0.47, p < 0.05) and magenta module (r = 0.51, p < 0.05) were associated with asthma. CAMKK2 and CISD1 were discovered to be ferroptosis-related hub genes in the black and magenta module, separately. We found that CAMKK2 and CISD1 were mainly involved in the CAMKK-AMPK signaling cascade, the adipocytokine signaling pathway, the metal cluster binding, iron-sulfur cluster binding, and 2 iron, 2 sulfur cluster binding in the enrichment analysis, which was strongly correlated with the development of ferroptosis. We found more infiltration of M2 macrophages and less Tregs infiltration in the asthma group compared to healthy controls. In addition, the expression levels of CISD1 and Tregs were negatively correlated. Through validation, we found that CAMKK2 and CISD1 expression were upregulated in the asthma group compared to the control group and would inhibit the occurrence of ferroptosis. Conclusion: CAMKK2 and CISD1 might inhibit ferroptosis and specifically regulate asthma. Moreover, CISD1 might be tied to the immunological microenvironment. Our results could be useful to provide potential immunotherapy targets and prognostic markers for asthma.

Genome-Wide Identification and Characterization of CPR5 Genes in Gossypium Reveals Their Potential Role in Trichome Development

Trichomes protect plants against insects, microbes, herbivores, and abiotic damages and assist seed dispersal. The function of CPR5 genes have been found to be involved in the trichome development but the research on the underlying genetic and molecular mechanisms are extremely limited. Herein, genome wide identification and characterization of CPR5 genes was performed. In total, 26 CPR5 family members were identified in Gossypium species. Phylogenetic analysis, structural characteristics, and synteny analysis of CPR5s showed the conserved evolution relationships of CPR5. The promoter analysis of CPR5 genes revealed hormone, stress, and development-related cis-elements. Gene ontology (GO) enrichment analysis showed that the CPR5 genes were largely related to biological regulation, developmental process, multicellular organismal process. Protein-protein interaction analysis predicted several trichome development related proteins (SIM, LGO, and GRL) directly interacting with CPR5 genes. Further, nine putative Gossypium-miRNAs were also identified, targeting Gossypium CPR5 genes. RNA-Seq data of G. arboreum (with trichomes) and G. herbaceum (with no trichomes) was used to perform the co-expression network analysis. GheCPR5.1 was identified as a hub gene in a co-expression network analysis. RT-qPCR of GheCPR5.1 gene in different tissues suggests that this gene has higher expressions in the petiole and might be a key candidate involved in the trichome development. Virus induced gene silencing of GheCPR5.1 (Ghe02G17590) confirms its role in trichome development and elongation. Current results provide proofs of the possible role of CPR5 genes and provide preliminary information for further studies of GheCPR5.1 functions in trichome development.

Construction of Severe Eosinophilic Asthma Related Competing Endogenous RNA Network by Weighted Gene Co-Expression Network Analysis

Background: Currently, disease control in patients with severe eosinophilic asthma is not optimistic. Competing endogenous RNA (ceRNA) networks have been found to play a key role in asthma in recent years. However, it is unclear whether ceRNA networks play an important part in severe eosinophilic asthma. Methods: Firstly, gene expression profiles related to severe eosinophilic asthma were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, the key modules were identified by the weighted gene co-expression network analysis (WGCNA). Thirdly, genes in modules highly associated with severe eosinophilic asthma were selected for further construction of the ceRNA network. Fourthly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on hub genes. Finally, the results of this study were validated on the GSE143303, GSE137268, and GSE147878 datasets. Results: 22 severe eosinophilic asthmatics and 13 healthy controls were extracted for WGCNA. We found that the genes in the black module (r = -0.75, p < 0.05) and yellow module (r = 0.65, p < 0.05) were highly associated with severe eosinophilic asthma. EP300 was discovered to serve the key connecting function in the ceRNA network. Surprisingly, lncRNAs seem to eliminate the role of EP300 in the black module and we discovered that CCT8 and miRNA-mRNA formed a circRNA-miRNA-mRNA network in the yellow module. We found that EP300 and FOXO3 in the black module were regulated by steroid hormones in the enrichment analysis, which were related to the medication used by the patient. Through validation of other datasets, we found that the hub genes in the yellow module were the key genes in the treatment of severe eosinophilic asthma. In particular, RPL17 and HNRNPK might specifically regulate severe eosinophilic asthma. Conclusion: RPL17 and HNRNPK might particularly regulate severe eosinophilic asthma. Our results could be useful to provide potential immunotherapy targets and prognostic markers for severe eosinophilic asthma.

Transcriptomics of Differential Ripening in 'd'Anjou' Pear (Pyrus communis L.)

Estimating maturity in pome fruits is a critical task that directs virtually all postharvest supply chain decisions. This is especially important for European pear (Pyrus communis) cultivars because losses due to spoilage and senescence must be minimized while ensuring proper ripening capacity is achieved (in part by satisfying a fruit chilling requirement). Reliable methods are lacking for accurate estimation of pear fruit maturity, and because ripening is maturity dependent it makes predicting ripening capacity a challenge. In this study of the European pear cultivar 'd'Anjou', we sorted fruit at harvest based upon on-tree fruit position to build contrasts of maturity. Our sorting scheme showed clear contrasts of maturity between canopy positions, yet there was substantial overlap in the distribution of values for the index of absorbance difference (I _AD ), a non-destructive spectroscopic measurement that has been used as a proxy for pome fruit maturity. This presented an opportunity to explore a contrast of maturity that was more subtle than I _AD could differentiate, and thus guided our subsequent transcriptome analysis of tissue samples taken at harvest and during storage. Using a novel approach that tests for condition-specific differences of co-expressed genes, we discovered genes with a phased character that mirrored our sorting scheme. The expression patterns of these genes are associated with fruit quality and ripening differences across the experiment. Functional profiles of these co-expressed genes are concordant with previous findings, and also offer new clues, and thus hypotheses, about genes involved in pear fruit quality, maturity, and ripening. This work may lead to new tools for enhanced postharvest management based on activity of gene co-expression modules, rather than individual genes. Further, our results indicate that modules may have utility within specific windows of time during postharvest management of 'd'Anjou' pear.

High BLM Expression Predicts Poor Clinical Outcome and Contributes to Malignant Progression in Human Cholangiocarcinoma

Molecular mechanisms underlying the tumorigenesis of a highly malignant cancer, cholangiocarcinoma (CCA), are still obscure. In our study, the CCA expression profile data were acquired from The Cancer Genome Atlas (TCGA) database, and differentially expressed genes (DEGs) in the TCGA-Cholangiocarcinoma (TCGA-CHOL) data set were utilized to construct a co-expression network via weighted gene co-expression network analysis (WGCNA). The blue gene module associated with the histopathologic grade of CCA was screened. Then, five candidate hub genes were screened by combining the co-expression network with protein–protein interaction (PPI) network. After progression and survival analyses, bloom syndrome helicase (BLM) was ultimately identified as a real hub gene. Moreover, the receiver operating characteristic (ROC) curve analysis suggested that BLM had a favorable diagnostic and predictive recurrence value for CCA. The gene set enrichment analysis (GSEA) results for a single hub gene revealed the importance of cell cycle-related pathways in the CCA progression and prognosis. Furthermore, we detected the BLM expression in vitro, and the results demonstrated that the expression level of BLM was much higher in the CCA tissues and cells relative to adjacent non-tumor samples and normal bile duct epithelial cells. Additionally, after further silencing the BLM expression by small interfering RNA (siRNA), the proliferation and migration ability of CCA cells were all inhibited, and the cell cycle was arrested. Altogether, a real hub gene (BLM) and cell cycle-related pathways were identified in the present study, and the gene BLM may be involved in the CCA progression and could act as a reliable biomarker for potential diagnosis and prognostic evaluation.

Network Analysis and Transcriptome Profiling Identify Autophagic and Mitochondrial Dysfunctions in SARS-CoV-2 Infection

Analyzing host cells' transcriptional response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection will help delineate biological processes underlying viral pathogenesis. First, analysis of expression profiles of lung cell lines A549 and Calu3 revealed upregulation of antiviral interferon signaling genes in response to all three SARS-CoV-2, MERS-CoV, or influenza A virus (IAV) infections. However, perturbations in expression of genes involved in inflammatory, mitochondrial, and autophagy processes were specifically observed in SARS-CoV-2-infected cells. Next, a validation study in infected human nasopharyngeal samples also revealed perturbations in autophagy and mitochondrial processes. Specifically, mTOR expression, mitochondrial ribosomal, mitochondrial complex I, lysosome acidification, and mitochondrial fission promoting genes were concurrently downregulated in both infected cell lines and human samples. SARS-CoV-2 infection impeded autophagic flux either by upregulating GSK3B in lung cell lines or by downregulating autophagy genes, SNAP29, and lysosome acidification genes in human samples, contributing to increased viral replication. Therefore, drugs targeting lysosome acidification or autophagic flux could be tested as intervention strategies. Finally, age-stratified SARS-CoV-2-positive human data revealed impaired upregulation of chemokines, interferon-stimulated genes, and tripartite motif genes that are critical for antiviral signaling. Together, this analysis has revealed specific aspects of autophagic and mitochondrial function that are uniquely perturbed in SARS-CoV-2-infected host cells.

Enhanced Activity of Genes Associated With Photosynthesis, Phytohormone Metabolism and Cell Wall Synthesis Is Involved in Gibberellin-Mediated Sugarcane Internode Growth

Internode elongation is an important trait in sugarcane as it affects the sugarcane yield. Gibberellin (GA) is a key modulator of internode elongation in sugarcane. Understanding the gene expression features of GA-mediated internode elongation has both scientific and practical significance. This study aimed to examine the transcriptomic changes in the internode elongation of sugarcane following GA treatment. Eighteen cDNA libraries from the internode tissues on days of 0, 3, and 6 in control and GA treatment groups were sequenced and their gene expression were studied. RNA-seq analysis revealed 1,338,723,248 reads and 70,821 unigenes from elongating internodes of sugarcane. Comparative studies discovered a large number of transcripts that were differentially expressed in GA-treated samples compared to the control. Further analysis revealed that the differentially expressed genes were enriched in the metabolic process, one-carbon compound transport, and single-organism process. Kyoto Encyclopedia of Genes and Genomes pathway annotation showed significant enrichment in photosynthesis and plant hormone signal transduction, indicating its involvement in internode elongation. The function analysis suggested that metabolic pathways and biosynthesis of secondary metabolites, plant hormones, and cell wall components were enriched in the internodes of the GA-treated plants. The hub genes were identified, with the function of cellulose synthesis. The results of this study provide a global view of mRNA changes during sugarcane internode elongation and extend our knowledge of the GA-mediated cellular processes involved in sugarcane stem growth.

Transcriptional Signature Derived from Murine Tumor-Associated Macrophages Correlates with Poor Outcome in Breast Cancer Patients

Tumor-associated macrophages (TAMs) are frequently the most abundant immune cells in cancers and are associated with poor survival. Here, we generated TAM molecular signatures from K14cre;Cdh1^flox/flox;Trp53^flox/flox (KEP) and MMTV-NeuT (NeuT) transgenic mice that resemble human invasive lobular carcinoma (ILC) and HER2⁺ tumors, respectively. Determination of TAM-specific signatures requires comparison with healthy mammary tissue macrophages to avoid overestimation of gene expression differences. TAMs from the two models feature a distinct transcriptomic profile, suggesting that the cancer subtype dictates their phenotype. The KEP-derived signature reliably correlates with poor overall survival in ILC but not in triple-negative breast cancer patients, indicating that translation of murine TAM signatures to patients is cancer subtype dependent. Collectively, we show that a transgenic mouse tumor model can yield a TAM signature relevant for human breast cancer outcome prognosis and provide a generalizable strategy for determining and applying immune cell signatures provided the murine model reflects the human disease.

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Murine TAM signatures prognosticate outcomes in corresponding cancer patients

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TAM signatures are robust when they are compared with healthy tissue macrophages

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TAM transcriptome is dictated by tissue and tumor subtype-related signals

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Murine TAM signatures can be translated only when a suitable model is chosen

Network Analysis and Transcriptome Profiling Identify Autophagic and Mitochondrial Dysfunctions in SARS-CoV-2 Infection

Analyzing host transcriptional changes in response to SARS-CoV-2 infection will help delineate biological processes underlying viral pathogenesis. Comparison of expression profiles of lung cell lines A549 (infected with either SARS-CoV-2 (with ACE2 expression)) or Influenza A virus (IAV)) and Calu3 (infected with SARS-CoV-2 or MERS-CoV) revealed upregulation of the antiviral interferon signaling in all three viral infections. However, perturbations in inflammatory, mitochondrial, and autophagy processes were specifically observed in SARS-CoV-2 infected cells. Validation of findings from cell line data revealed perturbations in autophagy and mitochondrial processes in the infected human nasopharyngeal samples. Specifically, downregulation of mTOR expression, mitochondrial ribosomal, mitochondrial complex I, and lysosome acidification genes were concurrently observed in both infected cell lines and human datasets. Furthermore, SARS-CoV-2 infection impedes autophagic flux by upregulating GSK3B in lung cell lines, or by downregulating autophagy genes, SNAP29 and lysosome acidification genes in human samples, contributing to increased viral replication. Therefore, drugs targeting lysosome acidification or autophagic flux could be tested as intervention strategies. Additionally, downregulation of MTFP1 (in cell lines) or SOCS6 (in human samples) results in hyperfused mitochondria and impede proper interferon response. Coexpression networks analysis identifies correlated clusters of genes annotated to inflammation and mitochondrial processes that are misregulated in SARS-CoV-2 infected cells. Finally, comparison of age stratified human gene expression data revealed impaired upregulation of chemokines, interferon stimulated and tripartite motif genes that are critical for antiviral signaling. Together, this analysis has revealed specific aspects of autophagic and mitochondrial function that are uniquely perturbed in SARS-CoV-2 infection.

Identification and Annotation of Potential Function of Regulatory Antisense Long Non-Coding RNAs Related to Feed Efficiency in Bos taurus Bulls

Long non-coding RNAs (lncRNAs) can influence transcriptional and translational processes in mammalian cells and are associated with various developmental, physiological and phenotypic conditions. However, they remain poorly understood and annotated in livestock species. We combined phenotypic, metabolomics and liver transcriptomic data of bulls divergent for residual feed intake (RFI) and fat accretion. Based on a project-specific transcriptome annotation for the bovine reference genome ARS-UCD.1.2 and multiple-tissue total RNA sequencing data, we predicted 3590 loci to be lncRNAs. To identify lncRNAs with potential regulatory influence on phenotype and gene expression, we applied the regulatory impact factor algorithm on a functionally prioritized set of loci (n = 4666). Applying the algorithm of partial correlation and information theory, significant and independent pairwise correlations were calculated and co-expression networks were established, including plasma metabolites correlated with lncRNAs. The network hub lncRNAs were assessed for potential cis-actions and subjected to biological pathway enrichment analyses. Our results reveal a prevalence of antisense lncRNAs positively correlated with adjacent protein-coding genes and suggest their participation in mitochondrial function, acute phase response signalling, TCA-cycle, fatty acid β-oxidation and presumably gluconeogenesis. These antisense lncRNAs indicate a stabilizing function for their cis-correlated genes and a putative regulatory role in gene expression.

Identification Hub Genes in Colorectal Cancer by Integrating Weighted Gene Co-Expression Network Analysis and Clinical Validation in vivo and vitro

Colorectal cancer (CRC) is the third leading cause of death in the world. However, the key roles of most molecules in CRC remain unclear. This study aimed to identify key modules and hub genes associated with the progression of CRC. The data of the patients with CRC were obtained from the Gene Expression Omnibus (GEO) database and assessed by weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses performed in R. by WGCNA, several hub genes that regulate the mechanism of tumorigenesis in CRC were identified, which were associated with clinical traits. Next, we screened hub genes related to the progression of CRC authenticated by The Cancer Genome Atlas (TCGA) and Oncomine databases. Three hub genes (HCLS1, EVI2B, and CD48) were identified, and survival analysis was further performed. Moreover, the results of qPCR and immunohistochemistry staining revealed that HCLS1, EVI2B, and CD48 are tumor suppressor genes. Further, the functional study verified that over-expression of HCLS1, EVI2B, and CD48 can reduce the proliferation, migration, and invasion ability of CRC cells and significantly suppress CRC tumor growth in vivo. In summary, we identified three hub genes that were associated with the progression of CRC that can be applied in treatment.

Genome-Wide Association Study and Genomic Prediction Elucidate the Distinct Genetic Architecture of Aluminum and Proton Tolerance in Arabidopsis thaliana

Under acid soil conditions, Al stress and proton stress can occur, reducing root growth and function. However, these stressors are distinct, and tolerance to each is governed by multiple physiological processes. To better understand the genes that underlie these coincidental but experimentally separable stresses, a genome-wide association study (GWAS) and genomic prediction (GP) models were created for approximately 200 diverse Arabidopsis thaliana accessions. GWAS and genomic prediction identified 140/160 SNPs associated with Al and proton tolerance, respectively, which explained approximately 70% of the variance observed. Reverse genetics of the genes in loci identified novel Al and proton tolerance genes, including TON1-RECRUITING MOTIF 28 (AtTRM28) and THIOREDOXIN H-TYPE 1 (AtTRX1), as well as genes known to be associated with tolerance, such as the Al-activated malate transporter, AtALMT1. Additionally, variation in Al tolerance was partially explained by expression level polymorphisms of AtALMT1 and AtTRX1 caused by cis-regulatory allelic variation. These results suggest that we successfully identified the loci that regulate Al and proton tolerance. Furthermore, very small numbers of loci were shared by Al and proton tolerance as determined by the GWAS. There were substantial differences between the phenotype predicted by genomic prediction and the observed phenotype for Al tolerance. This suggested that the GWAS-undetectable genetic factors (e.g., rare-allele mutations) contributing to the variation of tolerance were more important for Al tolerance than for proton tolerance. This study provides important new insights into the genetic architecture that produces variation in the tolerance of acid soil.

Molecular mechanisms of acclimation to long-term elevated temperature exposure in marine symbioses

Seawater temperature rise in French Polynesia has repeatedly resulted in the bleaching of corals and giant clams. Because giant clams possess distinctive ectosymbiotic features, they represent a unique and powerful model for comparing molecular pathways involved in (a) maintenance of symbiosis and (b) acquisition of thermotolerance among coral reef organisms. Herein, we explored the physiological and transcriptomic responses of the clam hosts and their photosynthetically active symbionts over a 65 day experiment in which clams were exposed to either normal or environmentally relevant elevated seawater temperatures. Additionally, we used metabarcoding data coupled with in situ sampling/survey data to explore the relative importance of holobiont adaptation (i.e., a symbiont community shift) versus acclimation (i.e., physiological changes at the molecular level) in the clams' responses to environmental change. We finally compared transcriptomic data to publicly available genomic datasets for Symbiodiniaceae dinoflagellates (both cultured and in hospite with the coral Pocillopora damicornis) to better tease apart the responses of both hosts and specific symbiont genotypes in this mutualistic association. Gene module preservation analysis revealed that the function of the symbionts' photosystem II was impaired at high temperature, and this response was also found across all holobionts and Symbiodiniaceae lineages examined. Similarly, epigenetic modulation appeared to be a key response mechanism for symbionts in hospite with giant clams exposed to high temperatures, and such modulation was able to distinguish thermotolerant from thermosensitive Cladocopium goreaui ecotypes; epigenetic processes may, then, represent a promising research avenue for those interested in coral reef conservation in this era of changing global climate.

Misregulation of ELK1, AP1, and E12 Transcription Factor Networks Is Associated with Melanoma Progression

Melanoma is among the most malignant cutaneous cancers and when metastasized results in dramatically high mortality. Despite advances in high-throughput gene expression profiling in cancer transcriptomic studies, our understanding of mechanisms driving melanoma progression is still limited. We present here an in-depth bioinformatic analysis of the melanoma RNAseq, chromatin immunoprecipitation (ChIP)seq, and single-cell (sc)RNA seq data to understand cancer progression. Specifically, we have performed a consensus network analysis of RNA-seq data from clinically re-grouped melanoma samples to identify gene co-expression networks that are conserved in early (stage 1) and late (stage 4/invasive) stage melanoma. Overlaying the fold-change information on co-expression networks revealed several coordinately up or down-regulated subnetworks that may play a critical role in melanoma progression. Furthermore, by incorporating histone lysine-27 acetylation information and highly expressed genes identified from the single-cell RNA data from melanoma patient samples, we present a comprehensive list of pathways, putative protein-protein interactions (PPIs) and transcription factor (TF) networks that are driving cancer progression. From this analysis, we have identified Elk1, AP1 and E12 TF networks that coordinately change expression in late melanoma when compared to early melanoma, implicating these TFs in melanoma progression. Additionally, the sumoylation-associated interactome is upregulated in invasive melanoma. Together, this bioinformatic analysis potentially implicates a combination of TF networks and PPIs in melanoma progression, which if confirmed in the experimental systems, could be used as targets for drug intervention in melanoma.

Biological Network Approach for the Identification of Regulatory Long Non-Coding RNAs Associated With Metabolic Efficiency in Cattle

Background: Genomic regions associated with divergent livestock feed efficiency have been found predominantly outside protein coding sequences. Long non-coding RNAs (lncRNA) can modulate chromatin accessibility, gene expression and act as important metabolic regulators in mammals. By integrating phenotypic, transcriptomic, and metabolomic data with quantitative trait locus data in prioritizing co-expression network analyses, we aimed to identify and functionally characterize lncRNAs with a potential key regulatory role in metabolic efficiency in cattle. Materials and Methods: Crossbred animals (n = 48) of a Charolais x Holstein F₂-population were allocated to groups of high or low metabolic efficiency based on residual feed intake in bulls, energy corrected milk in cows and intramuscular fat content in both genders. Tissue samples from jejunum, liver, skeletal muscle and rumen were subjected to global transcriptomic analysis via stranded total RNA sequencing (RNAseq) and blood plasma samples were used for profiling of 640 metabolites. To identify lncRNAs within the indicated tissues, a project-specific transcriptome annotation was established. Subsequently, novel transcripts were categorized for potential lncRNA status, yielding a total of 7,646 predicted lncRNA transcripts belonging to 3,287 loci. A regulatory impact factor approach highlighted 92, 55, 35, and 73 lncRNAs in jejunum, liver, muscle, and rumen, respectively. Their ensuing high regulatory impact factor scores indicated a potential regulatory key function in a gene set comprising loci displaying differential expression, tissue specificity and loci overlapping with quantitative trait locus regions for residual feed intake or milk production. These were subjected to a partial correlation and information theory analysis with the prioritized gene set. Results and Conclusions: Independent, significant and group-specific correlations (|r| > 0.8) were used to build a network for the high and the low metabolic efficiency group resulting in 1,522 and 1,732 nodes, respectively. Eight lncRNAs displayed a particularly high connectivity (>100 nodes). Metabolites and genes from the partial correlation and information theory networks, which each correlated significantly with the respective lncRNA, were included in an enrichment analysis indicating distinct affected pathways for the eight lncRNAs. LncRNAs associated with metabolic efficiency were classified to be functionally involved in hepatic amino acid metabolism and protein synthesis and in calcium signaling and neuronal nitric oxide synthase signaling in skeletal muscle cells.

Transcriptomic Sequencing and Co-Expression Network Analysis on Key Genes and Pathways Regulating Nitrogen Use Efficiency in Myriophyllum aquaticum

Massively input and accumulated ammonium is one of the main causes of eutrophication in aquatic ecosystems, which severely deteriorates water quality. Previous studies showed that one of the commonly used macrophytes, Myriophyllum aquaticum, was capable of not only withstanding ammonium of high concentration, but also efficiently assimilating extracellular ammonium to constitutive amino acids and proteins. However, the genetic mechanism regulating such efficient nitrogen metabolism in M. aquaticum is still poorly understood. Therefore, RNA-based analysis was performed in this study to understand the ammonium regulatory mechanism in M. aquaticum in response to various concentrations of ammonium. A total of 7721 genes were differentially expressed, of which those related to nitrogen-transport, assimilation, and remobilization were highly-regulated in response to various concentrations of ammonium. We have also identified transcription factors and protein kinases that were rapidly induced in response to ammonium, which suggests their involvement in ammonium-mediated signalling. Meanwhile, secondary metabolism including phenolics and anthocyanins biosynthesis was also activated in response to various concentrations of ammonium, especially at high ammonium concentrations. These results proposed a complex physiological and genetic regulation network related to nitrogen, carbohydrate, transcription factors, and secondary metabolism for nitrogen use efficiency in M. aquaticum.

Co-expression network analysis identified six hub genes in association with metastasis risk and prognosis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, and its carcinogenesis and progression are influenced by a complex network of gene interactions. A weighted gene co-expression network was constructed to identify gene modules associated with the clinical traits in HCC (n = 214). Among the 13 modules, high correlation was only found between the red module and metastasis risk (classified by the HCC metastasis gene signature) (R² = −0.74). Moreover, in the red module, 34 network hub genes for metastasis risk were identified, six of which (ABAT, AGXT, ALDH6A1, CYP4A11, DAO and EHHADH) were also hub nodes in the protein-protein interaction network of the module genes. Thus, a total of six hub genes were identified. In validation, all hub genes showed a negative correlation with the four-stage HCC progression (P for trend < 0.05) in the test set. Furthermore, in the training set, HCC samples with any hub gene lowly expressed demonstrated a higher recurrence rate and poorer survival rate (hazard ratios with 95% confidence intervals > 1). RNA-sequencing data of 142 HCC samples showed consistent results in the prognosis. Gene set enrichment analysis (GSEA) demonstrated that in the samples with any hub gene highly expressed, a total of 24 functional gene sets were enriched, most of which focused on amino acid metabolism and oxidation. In conclusion, co-expression network analysis identified six hub genes in association with HCC metastasis risk and prognosis, which might improve the prognosis by influencing amino acid metabolism and oxidation.

Weighted gene co-expression network analysis of gene modules for the prognosis of esophageal cancer

Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas (TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival (PFS) or overall survival (OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that "glycoprotein binding" was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor (PTAFR) and feline Gardner-Rasheed (FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.

Cell Type Specific Analysis of Human Brain Transcriptome Data to Predict Alterations in Cellular Composition

The central nervous system (CNS) is composed of hundreds of distinct cell types, each expressing different subsets of genes from the genome. High throughput gene expression analysis of the CNS from patients and controls is a common method to screen for potentially pathological molecular mechanisms of psychiatric disease. One mechanism by which gene expression might be seen to vary across samples would be alterations in the cellular composition of the tissue. While the expressions of gene 'markers' for each cell type can provide certain information of cellularity, for many rare cell types markers are not well characterized. Moreover, if only small sets of markers are known, any substantial variation of a marker's expression pattern due to experiment conditions would result in poor sensitivity and specificity. Here, our proposed method combines prior information from mice cell-specific transcriptome profiling experiments with co-expression network analysis, to select large sets of potential cell type-specific gene markers in a systematic and unbiased manner. The method is efficient and robust, and identifies sufficient markers for further cellularity analysis. We then employ the markers to analytically detect changing cellular composition in human brain. Application of our method to temporal human brain microarray data successfully detects changes in cellularity over time that roughly correspond to known epochs of human brain development. Furthermore, application of our method to human brain samples with the neurodevelopmental disorder of autism supports the interpretation that the changes in astrocytes and neurons might contribute to the disorder.

From dusk till dawn: the Arabidopsis thaliana sugar starving responsive network

Plant growth and development are tightly controlled by photosynthetic carbon availability. The understanding of mechanisms governing carbon partitioning in plants will be a valuable tool in order to satisfy the rising global demand for food and biofuel. The goal of this study was to determine if sugar starvation responses were transcriptionally coordinated in Arabidopsis thaliana. A set of sugar-starvation responsive (SSR) genes was selected to perform a co-expression network analysis. Posteriorly, a guided-gene approach was used to identify the SSR-network from public data and to discover candidate regulators of this network. In order to validate the SSR network, a global transcriptome analysis was realized on three A. thaliana starch-deficient mutants. The starch-deficient phenotype in leaves induces sugar starvation syndrome at the end of the night due to the absence of photosynthesis. Promoter sequences of genes belonging to the SSR-network were analyzed in silico reveling over-represented motifs implicated in light, abscisic acid, and sugar responses. A small cluster of protein encoding genes belonging to different metabolic pathways, including three regulatory proteins, a protein kinase, a transcription factor, and a blue light receptor, were identified as the cornerstones of the SSR co-expression network. In summary, a large transcriptionally coordinated SSR network was identified and was validated with transcriptional data from three starch-deficient mutant lines. Candidate master regulators of this network were point out.

Genome-scale identification of cell-wall related genes in Arabidopsis based on co-expression network analysis

BACKGROUND

Identification of the novel genes relevant to plant cell-wall (PCW) synthesis represents a highly important and challenging problem. Although substantial efforts have been invested into studying this problem, the vast majority of the PCW related genes remain unknown.

RESULTS

Here we present a computational study focused on identification of the novel PCW genes in Arabidopsis based on the co-expression analyses of transcriptomic data collected under 351 conditions, using a bi-clustering technique. Our analysis identified 217 highly co-expressed gene clusters (modules) under some experimental conditions, each containing at least one gene annotated as PCW related according to the Purdue Cell Wall Gene Families database. These co-expression modules cover 349 known/annotated PCW genes and 2,438 new candidates. For each candidate gene, we annotated the specific PCW synthesis stages in which it is involved and predicted the detailed function. In addition, for the co-expressed genes in each module, we predicted and analyzed their cis regulatory motifs in the promoters using our motif discovery pipeline, providing strong evidence that the genes in each co-expression module are transcriptionally co-regulated. From the all co-expression modules, we infer that 108 modules are related to four major PCW synthesis components, using three complementary methods.

CONCLUSIONS

We believe our approach and data presented here will be useful for further identification and characterization of PCW genes. All the predicted PCW genes, co-expression modules, motifs and their annotations are available at a web-based database: http://csbl.bmb.uga.edu/publications/materials/shanwang/CWRPdb/index.html.