Comparative transcriptome analysis of T lymphocyte subpopulations and identification of critical regulators defining porcine thymocyte identity

Introduction

The development and migration of T cells in the thymus and peripheral tissues are crucial for maintaining adaptive immunity in mammals. However, the regulatory mechanisms underlying T cell development and thymocyte identity formation in pigs remain largely underexplored.

Method

Here, by integrating bulk and single-cell RNA-sequencing data, we investigated regulatory signatures of porcine thymus and lymph node T cells.

Results

The comparison of T cell subpopulations derived from porcine thymus and lymph nodes revealed that their transcriptomic differences were influenced more by tissue origin than by T cell phenotypes, and that lymph node cells exhibited greater transcriptional diversity than thymocytes. Through weighted gene co-expression network analysis (WGCNA), we identified the key modules and candidate hub genes regulating the heterogeneity of T cell subpopulations. Further, we integrated the porcine thymocyte dataset with peripheral blood mononuclear cell (PBMC) dataset to systematically compare transcriptomic differences between T cell types from different tissues. Based on single-cell datasets, we further identified the key transcription factors (TFs) responsible for maintaining porcine thymocyte identity and unveiled that these TFs coordinately regulated the entire T cell development process. Finally, we performed GWAS of cell type-specific differentially expressed genes (DEGs) and 30 complex traits, and found that the DEGs in thymus-related and peripheral blood-related cell types, especially CD4_SP cluster and CD8-related cluster, were significantly associated with pig productive and reproductive traits.

Discussion

Our findings provide an insight into T cell development and lay a foundation for further exploring the porcine immune system and genetic mechanisms underlying complex traits in pigs.

Tissue-specific transcriptome analyses in Drosophila provide novel insights into the mode of action of the insecticide spinosad and the function of its target, nAChRα6

BACKGROUND

The insecticides spinosad and imidacloprid are neurotoxins with distinct modes of action. Both target nicotinic acetylcholine receptors (nAChRs), albeit different subunits. Spinosad is an allosteric modulator, that upon binding initiates endocytosis of its target, nAChRα6. Imidacloprid binding triggers excessive neuronal ion influx. Despite these differences, low-dose effects converge downstream in the precipitation of oxidative stress and neurodegeneration.

RESULTS

Using RNA-sequencing, we compared the transcriptional signatures of spinosad and imidacloprid, at low-dose exposures. Both insecticides cause up-regulation of glutathione S-transferase and cytochrome P450 genes in the brain and down-regulation in the fat body, whereas reduced expression of immune-related genes is observed in both tissues. Spinosad shows unique impacts on genes involved in lysosomal function, protein folding, and reproduction. Co-expression analyses revealed little to no correlation between genes affected by spinosad and nAChRα6 expressing neurons, but a positive correlation with glial cell markers. We also detected and experimentally confirmed nAChRα6 expression in fat body cells and male germline cells. This led us to uncover lysosomal dysfunction in the fat body following spinosad exposure, and a fitness cost in spinosad-resistant (nAChRα6 null) males - oxidative stress in testes, and reduced fertility.

CONCLUSION

Spinosad and imidacloprid share transcriptional perturbations in immunity-, energy homeostasis-, and oxidative stress-related genes. Low doses of other neurotoxic insecticides should be investigated for similar impacts. While target-site spinosad resistance mutation has evolved in the field, this may have a fitness cost. Our findings demonstrate the power of tissue-specific transcriptomics approach and the use of single-cell transcriptome data. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Comprehensive Analysis and Characterization of the GATA Gene Family, with Emphasis on the GATA6 Transcription Factor in Poplar

GATA transcription factors are ubiquitously present in eukaryotic organisms and play a crucial role in multiple biological processes, such as plant growth, stress response, and hormone signaling. However, the study of GATA factors in poplar is currently limited to a small number of proteins, despite their evident functional importance. In this investigation, we utilized the most recent genome annotation and stringent criteria to identify 38 GATA transcription factor genes in poplar. Subsequently, we conducted a comprehensive analysis of this gene family, encompassing phylogenetic classification, protein characterization, analysis of promoter cis-acting elements, and determination of chromosomal location. Our examination of gene duplication events indicated that both tandem and segmental duplications have contributed to the expansion of the GATA gene family in poplar, with segmental duplication potentially being a major driving force. By performing collinearity analysis of genes across six different species, we identified 74 pairs of co-linear genes, which provide valuable insights for predicting gene functions from a comparative genomics perspective. Furthermore, through the analysis of gene expression patterns, we identified five GATA genes that exhibited differential expression in leaf-stem-root tissues and eight genes that were responsive to salt stress. Of particular interest was GATA6, which displayed strong induction by salt stress and overlapped between the two gene sets. We discovered that GATA6 encodes a nuclear-localized protein with transcription activation activity, which is continuously induced by salt stress in leaf and root tissues. Moreover, we constructed a co-expression network centered around GATA6, suggesting the potential involvement of these genes in the growth, development, and response to abiotic stress processes in poplar through cell transport systems and protein modification mechanisms, such as vesicle-mediated transport, intracellular transport, ubiquitination, and deubiquitination. This research provides a foundation for further exploration of the functions and mechanisms of GATA transcription factors in poplar.

Transcriptomic and metabolomic characterization of antibacterial activity of Melastoma dodecandrum

Antibacterial resistance poses a significant global threat, necessitating the discovery of new therapeutic agents. Plants are a valuable source of secondary metabolites with demonstrated anticancer and antibacterial properties. In this study, we reveal that Melastoma dodecandrum exhibits both bacteriostatic and bactericidal effects against Pseudomonas aeruginosa and Staphylococcus aureus. Treatment with plant extracts results in membrane damage and a reduction in P.aeruginosa swimming and swarming motility. A comparative analysis of bacterial transcriptomes exposed to M.dodecandrum extracts and four distinct antibiotics indicates that the extracts may trigger similar transcriptomic responses as triclosan, a fatty acid synthesis inhibitor. Activity-guided fractionation suggests that the antibacterial activity is not attributable to hydrolyzable tannins, but to unidentified minor compounds. Additionally, we identified 104 specialized metabolic pathways and demonstrated a high level of transcriptional coordination between these biosynthetic pathways and phytohormones, highlighting potential regulatory mechanisms of antibacterial metabolites in M.dodecandrum.

The enhanced Valsa canker resistance conferred by MdLecRK-S.4.3 in Pyrus betulifolia can be largely suppressed by PbePUB36

L-type lectin receptor-like kinases (L-LecRKs) act as a sensor of extracellular signals and an initiator for plant immune responses. However, the function of LecRK-S.4 on plant immunity has not been extensively investigated. At present, in the apple (Malus domestica) genome, we identified that MdLecRK-S.4.3, a homologous gene of LecRK-S.4, was differentially expressed during the occursion of Valsa canker. Over-expression of MdLecRK-S.4.3 facilitated the induction of immune response and enhanced the Valsa canker resistance of apple and pear fruit, and 'Duli-G03' (Pyrus betulifolia) suspension cells. On the contrary, the expression of PbePUB36, RLCK XI subfamily member, was significantly repressed in the MdLecRK-S.4.3 overexpressed cell lines. Over-expression of PbePUB36 interfered with the Valsa canker resistance and immune response caused by up-regulation of MdLecRK-S.4.3. Furthermore, MdLecRK-S.4.3 interacted with BAK1 or PbePUB36 in vivo. In conclusion, MdLecRK-S.4.3 activated various immune responses and positively regulate Valsa canker resistance, which could be largely compromised by PbePUB36. MdLecRK-S.4.3 interacted with PbePUB36 and/or MdBAK1 to mediate the immune responses. This finding provides a reference for studying the molecular mechanism of resistance to Valsa canker and resistance breeding.

Evolutionary and functional analysis reveals the crucial roles of receptor-like proteins in resistance to Valsa canker in Rosaceae

Rosaceae is an economically important plant family that can be affected by a multitude of pathogenic microbes, some of which can cause dramatic losses in production. As a type of pattern-recognition receptor, receptor-like proteins (RLPs) are considered vital regulators of plant immunity. Based on genome-wide identification, bioinformatic analysis, and functional determination, we investigated the evolutionary characteristics of RLPs, and specifically those that regulate Valsa canker, a devastating fungal disease affecting apple and pear production. A total of 3028 RLPs from the genomes of 19 species, including nine Rosaceae, were divided into 24 subfamilies. Five subfamilies and seven co-expression modules were found to be involved in the responses to Valsa canker signals of the resistant pear rootstock Pyrus betulifolia 'Duli-G03'. Fourteen RLPs were subsequently screened as candidate genes for regulation of resistance. Among these, PbeRP23 (Chr13.g24394) and PbeRP27 (Chr16.g31400) were identified as key resistance genes that rapidly enhance the resistance of 'Duli-G03' and strongly initiate immune responses, and hence they have potential for further functional exploration and breeding applications for resistance to Valsa canker. In addition, as a consequence of this work we have established optimal methods for the classification and screening of disease-resistant RLPs.

Comparative Transcriptome and Co-Expression Network Analyses Reveal the Molecular Mechanism of Calcium-Deficiency-Triggered Tipburn in Chinese Cabbage (Brassica rapa L. ssp. Pekinensis)

Chinese cabbage tipburn is characterized by the formation of necrotic lesions on the margin of leaves, including on the insides of the leafy head. This physiological disorder is associated with a localized calcium deficiency during leaf development. However, little information is available regarding the molecular mechanisms governing Ca-deficiency-triggered tipburn. This study comprehensively analysed the transcriptomic comparison between control and calcium treatments (CK and 0 mM Ca) in Chinese cabbage to determine its molecular mechanism in tipburn. Our analysis identified that the most enriched gene ontology (GO) categories are photosynthesis, thylakoid and cofactor binding. Moreover, the KEGG pathway was most enriched in photosynthesis, carbon metabolism and carbon fixation. We also analyzed the co-expression network by functional categories and identified ten critical hub differentially expressed genes (DEGs) in each gene regulatory network (GRN). These DEGs might involve abiotic stresses, developmental processes, cell wall metabolism, calcium distribution, transcription factors, plant hormone biosynthesis and signal transduction pathways. Under calcium deficiency, CNX1, calmodulin-binding proteins and CMLs family proteins were downregulated compared to CK. In addition, plant hormones such as GA, JA, BR, Auxin and ABA biosynthesis pathways genes were downregulated under calcium treatment. Likewise, HATs, ARLs and TCP transcription factors were reported as inactive under calcium deficiency, and potentially involved in the developmental process. This work explores the specific DEGs' significantly different expression levels in 0 mM Ca and the control involved in plant hormones, cell wall developments, a light response such as chlorophylls and photosynthesis, transport metabolism and defence mechanism and redox. Our results provide critical evidence of the potential roles of the calcium signal transduction pathway and candidate genes governing Ca-deficiency-triggered tipburn in Chinese cabbage.

Transcriptomics and metabolomics changes triggered by exogenous 6-benzylaminopurine in relieving epicotyl dormancy of Polygonatum cyrtonema Hua seeds

Polygonatum cyrtonema Hua is one of the most useful herbs in traditional Chinese medicine and widely used in medicinal and edible perennial plant. However, the seeds have the characteristics of epicotyl dormancy. In this study, the molecular basis for relieving epicotyl dormancy of P. cyrtonema seeds under exogenous 6-benzylaminopurine (6-BA) treatment was revealed for the first time through transcriptome and metabolomics analysis. We determined the elongation of epicotyl buds as a critical period for dormancy release and found that the content of trans-zeatin, proline, auxin and gibberellin was higher, while flavonoids and arginine were lower in the treatment group. Transcriptome analysis showed that there were significant differences in gene expression in related pathways, and the expression patterns were highly consistent with the change of metabolites in corresponding pathways. Co-expression analysis showed that cytokinin dehydrogenase of P. cyrtonema (PcCKXs) and pelargonidin in flavonoid biosynthesis, as well as L-proline, L-ornithine, and L-citrulline in arginine and proline metabolism form network modules, indicating that they have related regulatory roles. Above all, our findings provide new insight into the exogenous 6-BA relieving epicotyl dormancy of P. cyrtonema seeds.

Regulatory Modules of Metabolites and Protein Phosphorylation in Arabidopsis Genotypes With Altered Sucrose Allocation

Multi-omics data sets are increasingly being used for the interpretation of cellular processes in response to environmental cues. Especially, the posttranslational modification of proteins by phosphorylation is an important regulatory process affecting protein activity and/or localization, which, in turn, can have effects on metabolic processes and metabolite levels. Despite this importance, relationships between protein phosphorylation status and metabolite abundance remain largely underexplored. Here, we used a phosphoproteomics-metabolomics data set collected at the end of day and night in shoots and roots of Arabidopsis to propose regulatory relationships between protein phosphorylation and accumulation or allocation of metabolites. For this purpose, we introduced a novel, robust co-expression measure suited to the structure of our data sets, and we used this measure to construct metabolite-phosphopeptide networks. These networks were compared between wild type and plants with perturbations in key processes of sugar metabolism, namely, sucrose export (sweet11/12 mutant) and starch synthesis (pgm mutant). The phosphopeptide-metabolite network turned out to be highly sensitive to perturbations in sugar metabolism. Specifically, KING1, the regulatory subunit of SnRK1, was identified as a primary candidate connecting protein phosphorylation status with metabolism. We additionally identified strong changes in the fatty acid network of the sweet11/12 mutant, potentially resulting from a combination of fatty acid signaling and metabolic overflow reactions in response to high internal sucrose concentrations. Our results further suggest novel protein-metabolite relationships as candidates for future targeted research.

Identification of Key Aroma Compounds Responsible for the Floral Ascents of Green and Black Teas from Different Tea Cultivars

Chemicals underlying the floral aroma of dry teas needs multi-dimensional investigations. Green, black, and freeze-dried tea samples were produced from five tea cultivars, and only ‘Chunyu2’ and ‘Jinguanyin’ dry teas had floral scents. ‘Chunyu2’ green tea contained the highest content of total volatiles (134.75 μg/g) among green tea samples, while ‘Jinguanyin’ black tea contained the highest content of total volatiles (1908.05 μg/g) among black tea samples. The principal component analysis study showed that ‘Chunyu2’ and ‘Jinguanyin’ green teas and ‘Chunyu2’ black tea were characterized by the abundant presence of certain alcohols with floral aroma, while ‘Jinguanyin’ black tea was discriminated due to the high levels of certain alcohols, esters, and aldehydes. A total of 27 shared volatiles were present in different tea samples, and the contents of 7 floral odorants in dry teas had correlations with those in fresh tea leaves (p < 0.05). Thus, the tea cultivar is crucial to the floral scent of dry tea, and these seven volatiles could be promising breeding indices.

Co-Expression Analysis of microRNAs and Proteins in Brain of Alzheimer's Disease Patients

Alzheimer's disease (AD) is the most common form of dementia globally; however, the aetiology of AD remains elusive hindering the development of effective therapeutics. MicroRNAs (miRNAs) are regulators of gene expression and have been of growing interest in recent studies in many pathologies including AD not only for their use as biomarkers but also for their implications in the therapeutic field. In this study, miRNA and protein profiles were obtained from brain tissues of different stage (Braak III-IV and Braak V-VI) of AD patients and compared to matched controls. The aim of the study was to identify in the late stage of AD, the key dysregulated pathways that may contribute to pathogenesis and then to evaluate whether any of these pathways could be detected in the early phase of AD, opening new opportunity for early treatment that could stop or delay the pathology. Six common pathways were found regulated by miRNAs and proteins in the late stage of AD, with one of them (Rap1 signalling) activated since the early phase. MiRNAs and proteins were also compared to explore an inverse trend of expression which could lead to the identification of new therapeutic targets. These results suggest that specific miRNA changes could represent molecular fingerprint of neurodegenerative processes and potential therapeutic targets for early intervention.

Putative Factors Interfering Cell Cycle Re-Entry in Alzheimer's Disease: An Omics Study with Differential Expression Meta-Analytics and Co-Expression Profiling

BACKGROUND

Neuronal cell cycle re-entry (CCR) is a mechanism, along with amyloid-β (Aβ) oligomers and hyperphosphorylated tau proteins, contributing to toxicity in Alzheimer's disease (AD).

OBJECTIVE

This study aimed to examine the putative factors in CCR based on evidence corroboration by combining meta-analysis and co-expression analysis of omic data.

METHODS

The differentially expressed genes (DEGs) and CCR-related modules were obtained through the differential analysis and co-expression of transcriptomic data, respectively. Differentially expressed microRNAs (DEmiRNAs) were extracted from the differential miRNA expression studies. The dysregulations of DEGs and DEmiRNAs as binary outcomes were independently analyzed by meta-analysis based on a random-effects model. The CCR-related modules were mapped to human protein-protein interaction databases to construct a network. The importance score of each node within the network was determined by the PageRank algorithm, and nodes that fit the pre-defined criteria were treated as putative CCR-related factors.

RESULTS

The meta-analysis identified 18,261 DEGs and 36 DEmiRNAs, including genes in the ubiquitination proteasome system, mitochondrial homeostasis, and CCR, and miRNAs associated with AD pathologies. The co-expression analysis identified 156 CCR-related modules to construct a protein-protein interaction network. Five genes, UBC, ESR1, EGFR, CUL3, and KRAS, were selected as putative CCR-related factors. Their functions suggested that the combined effects of cellular dyshomeostasis and receptors mediating Aβ toxicity from impaired ubiquitination proteasome system are involved in CCR.

CONCLUSION

This study identified five genes as putative factors and revealed the significance of cellular dyshomeostasis in the CCR of AD.

Prediction of the Effects of Variants and Differential Expression of Key Host Genes ACE2, TMPRSS2, and FURIN in SARS-CoV-2 Pathogenesis: An In Silico Approach

A new strain of the beta coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is solely responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic. Although several studies suggest that the spike protein of this virus interacts with the cell surface receptor, angiotensin-converting enzyme 2 (ACE2), and is subsequently cleaved by TMPRSS2 and FURIN to enter into the host cell, conclusive insight about the interaction pattern of the variants of these proteins is still lacking. Thus, in this study, we analyzed the functional conjugation among the spike protein, ACE2, TMPRSS2, and FURIN in viral pathogenesis as well as the effects of the mutations of the proteins through the implementation of several bioinformatics approaches. Analysis of the intermolecular interactions revealed that T27A (ACE2), G476S (receptor-binding domain [RBD] of the spike protein), C297T (TMPRSS2), and P812S (cleavage site for TMPRSS2) coding variants may render resistance in viral infection, whereas Q493L (RBD), S477I (RBD), P681R (cleavage site for FURIN), and P683W (cleavage site for FURIN) may lead to increase viral infection. Genotype-specific expression analysis predicted several genetic variants of ACE2 (rs2158082, rs2106806, rs4830971, and rs4830972), TMPRSS2 (rs458213, rs468444, rs4290734, and rs6517666), and FURIN (rs78164913 and rs79742014) that significantly alter their normal expression which might affect the viral spread. Furthermore, we also found that ACE2, TMPRSS2, and FURIN proteins are functionally co-related with each other, and several genes are highly co-expressed with them, which might be involved in viral pathogenesis. This study will thus help in future genomics and proteomics studies of SARS-CoV-2 and will provide an opportunity to understand the underlying molecular mechanism during SARS-CoV-2 pathogenesis.

Identification of a Four-Gene Signature With Prognostic Significance in Endometrial Cancer Using Weighted-Gene Correlation Network Analysis

Endometrial hyperplasia (EH) is a precursor for endometrial cancer (EC). However, biomarkers for the progression from EH to EC and standard prognostic biomarkers for EC have not been identified. In this study, we aimed to identify key genes with prognostic significance for the progression from EH to EC. Weighted-gene correlation network analysis (WGCNA) was used to identify hub genes utilizing microarray data (GSE106191) downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified from the Uterine Corpus Endometrial Carcinoma (UCEC) dataset of The Cancer Genome Atlas database. The Limma-Voom R package was applied to detect differentially expressed genes (DEGs; mRNAs) between cancer and normal samples. Genes with |log2 (fold change [FC])| > 1.0 and p < 0.05 were considered as DEGs. Univariate and multivariate Cox regression and survival analyses were performed to identify potential prognostic genes using hub genes overlapping in the two datasets. All analyses were conducted using R Bioconductor and related packages. Through WGCNA and overlapping genes in hub modules with DEGs in the UCEC dataset, we identified 42 hub genes. The results of the univariate and multivariate Cox regression analyses revealed that four hub genes, BUB1B, NDC80, TPX2, and TTK, were independently associated with the prognosis of EC (Hazard ratio [95% confidence interval]: 0.591 [0.382–0.912], p = 0.017; 0.605 [0.371–0.986], p = 0.044; 1.678 [1.132–2.488], p = 0.01; 2.428 [1.372–4.29], p = 0.02, respectively). A nomogram was established with a risk score calculated using the four genes’ coefficients in the multivariate analysis, and tumor grade and stage had a favorable predictive value for the prognosis of EC. The survival analysis showed that the high-risk group had an unfavorable prognosis compared with the low-risk group (p < 0.0001). The receiver operating characteristic curves also indicated that the risk model had a potential predictive value of prognosis with area under the curve 0.807 at 2 years, 0.783 at 3 years, and 0.786 at 5 years. We established a four-gene signature with prognostic significance in EC using WGCNA and established a nomogram to predict the prognosis of EC.

Genome-Wide Identification and Analyses of Drought/Salt-Responsive Cytochrome P450 Genes in Medicago truncatula

Cytochrome P450 monooxygenases (P450s) catalyze a great number of biochemical reactions and play vital roles in plant growth, development and secondary metabolism. As yet, the genome-scale investigation on P450s is still lacking in the model legume Medicago truncatula. In particular, whether and how many MtP450s are involved in drought and salt stresses for Medicago growth, development and yield remain unclear. In this study, a total of 346 MtP450 genes were identified and classified into 10 clans containing 48 families. Among them, sixty-one MtP450 genes pairs are tandem duplication events and 10 MtP450 genes are segmental duplication events. MtP450 genes within one family exhibit high conservation and specificity in intron–exon structure. Meanwhile, many Mt450 genes displayed tissue-specific expression pattern in various tissues. Specifically, the expression pattern of 204 Mt450 genes under drought/NaCl treatments were analyzed by using the weighted correlation network analysis (WGCNA). Among them, eight genes (CYP72A59v1, CYP74B4, CYP71AU56, CYP81E9, CYP71A31, CYP704G6, CYP76Y14, and CYP78A126), and six genes (CYP83D3, CYP76F70, CYP72A66, CYP76E1, CYP74C12, and CYP94A52) were found to be hub genes under drought/NaCl treatments, respectively. The expression levels of these selected hub genes could be induced, respectively, by drought/NaCl treatments, as validated by qPCR analyses, and most of these genes are involved in the secondary metabolism and fatty acid pathways. The genome-wide identification and co-expression analyses of M. truncatulaP450 superfamily genes established a gene atlas for a deep and systematic investigation of P450 genes in M. truncatula, and the selected drought-/salt-responsive genes could be utilized for further functional characterization and molecular breeding for resistance in legume crops.

The gene expression patterns of neuronal cells reveal the pathogenesis of autism

OBJECTIVE

To explore the effects of early comprehensive and specific behavioral interventions on improving social communication and attenuating anxiety in autism patients.

METHODS

This study was based on the modular comprehensive analysis method and explored the neurotransmitter conduction mechanism in the pathogenesis of autism. We downloaded autism-related data from the Gene Expression Omnibus (GEO) database and performed a differential analysis, a co-expression Network Analysis (WGCNA) analysis, a GO function, and a KEGG pathway enrichment analysis. Finally, we predicted the non-coding RNAs (ncRNAs) and transcription factors (TFs) that regulate the module on the basis of hypergeometric testing.

RESULTS

We obtained five co-expression modules, in which the active regulatory effects of the MTA3, PHB2, TNXB, DCTN2, and RBM23 genes in the dysfunction modules were obtained. The module genes were predominantly involved in biological processes and significantly regulated the mRNA monitoring and calcium signaling pathways. In addition, we identified a prominent regulation effect of the ncRNA and TF pivots on the dysfunction modules.

CONCLUSIONS

This study deciphered a comprehensive network of key genes involved in autism, and it reveals the main dysfunction modules, the latent regulatory factors, and the driver genes for autism, contributing to our further understanding of the mechanisms of autism neuronal conduction disorders.

Potential prognostic markers and significant lncRNA-mRNA co-expression pairs in laryngeal squamous cell carcinoma

lncRNA-mRNA co-expression pairs and prognostic markers related to the development of laryngeal squamous cell carcinoma (LSCC) were investigated. The lncRNA and mRNA expression data of LSCC in GSE84957 and RNA-seq data of 112 LSCC samples from TCGA database were used. Differentially expressed genes (DEGs) and lncRNAs (DE-lncRNAs) between LSCC and para-cancer tissues were identified. Co-expression analysis of DEGs and DE-lncRNA was conducted. Protein-protein interaction network for co-expressed DEGs of top 25 DE-lncRNA was constructed, followed by survival analysis for key nodes in co-expression network. Finally, expressions of several DE-lncRNAs and DEGs were verified using qRT-PCR. The lncRNA-mRNA network showed that ANKRD20A5P, C21orf15, CYP4F35P, LOC_I2_011146, XLOC_006053, XLOC_I2_003881, and LOC100506027 were highlighted in network. Some DEGs, including FUT7, PADI1, PPL, ARHGAP40, MUC21, and CEACAM1, were co-expressed with above lncRNAs. Survival analysis showed that PLOD1, GLT25D1, and KIF22 were significantly associated with prognosis. qRT-PCR results showed that the expressions of MUC21, CEACAM1, FUT7, PADI1, PPL, ARHGAP40, ANKRD20A5P, C21orf15, CYP4F35P, XLOC_I2_003881, LOC_I2_011146, and XLOC_006053 were downregulated, whereas the expression of LOC100506027 was upregulated in LSCC tissues. PLOD1, GLT25D1, and KIF22 may be potential prognostic markers in the development of LSCC. C21orf15-MUC21/CEACAM1/FUT7/PADI1/PPL/ARHGAP40 are potential lncRNA-mRNA pairs that play significant roles in the development of LSCC.

Comprehensive analysis of the long non-coding RNA expression profile and functional roles in a contrast-induced acute kidney injury rat model

Long non-coding RNAs (lncRNAs) have been identified as a class of regulatory RNAs that participate in both physiological and pathological conditions, including acute kidney injury. However, the roles of lncRNA dysregulation in the pathogenesis of contrast-induced acute kidney injury (CI-AKI) are largely unknown. In the present study, the expression profiles of lncRNAs in kidney tissue were compared between rats with CI-AKI and controls using high-throughput RNA sequencing. In total, 910 differentially expressed (DE) lncRNAs (DElncRNAs), including 415 downregulated and 495 upregulated lncRNAs, were identified at 12 h after intra-arterial iodinated contrast medium injection (fold change ≥2; P<0.05). Eight DElncRNAs were further selected and validated using reverse transcription-quantitative polymerase chain reaction. A previous study defined microRNA (miRNA) and mRNA expression changes in the same CI-AKI model. In the present study, a lncRNA-mRNA co-expression network comprising 349 DElncRNAs and 202 DEmRNAs was constructed. The function of these DElncRNAs was mainly associated with oxidative stress and inflammation. Additionally, lncRNA-associated competing endogenous RNA (ceRNA) analysis revealed a network comprising 40 DElncRNA nodes, 5 DEmiRNA nodes and 59 DEmRNA nodes. Among which, the carnosine dipeptidase 1-specific and the transmembrane protein 184B-specific networks were likely to be associated with CI-AKI. The results of the present study revealed the expression profile and potential roles of lncRNAs in CI-AKI, and provide a framework for further mechanistic studies.

Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression

Subsyndromal symptomatic depression (SSD) and major depressive disorder (MDD) have been classified as distinct diseases, due to their dissimilar gene expression profiles and responses to venlafaxine. To identify specific biomarkers of these two diseases, we conducted a secondary analysis of the gene expression signatures of SSD patients, MDD patients and healthy controls (n=8/group) from the study of Yi et al. Global, individual, specific, enrichment and co-expression analyses were used to compare the transcriptomic profiles of peripheral blood lymphocytes from the three groups. The global and individual analyses revealed that different genes were up- and downregulated in the SSD and MDD groups. Through our specific analysis, we identified 1719 and 3278 differentially expressed genes specifically associated with MDD and SSD, respectively. Enrichment and co-expression analyses demonstrated that the genes specific to MDD were enriched in pathways associated with hormone levels and immune responses, while those specific to SSD were associated with immune function. The specific hub gene for the MDD co-expression network was transmembrane protein 132B (TMEM132B), while the hub genes for SSD were actin-related protein 2/3 complex (ARPC2) and solute carrier family 5 member 5 (SLC5A5). This bioinformatic analysis has provided potential biomarkers that can distinguish SSD from MDD.

Identification of VWF as a Novel Biomarker in Lung Adenocarcinoma by Comprehensive Analysis

Lung adenocarcinoma (LUAD) is one of the most malignant tumors with high morbidity and mortality worldwide due to the lack of reliable methods for early diagnosis and effective treatment. It’s imperative to study the mechanism of its development and explore new biomarkers for early detection of LUAD. In this study, the Gene Expression Omnibus (GEO) dataset GSE43458 and The Cancer Genome Atlas (TCGA) were used to explore the differential co-expressed genes between LUAD and normal samples. Three hundred sixity-six co-expressed genes were identified by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) method. Those genes were mainly enriched in ameboidal-type cell migration (biological process), collagen-containing extracellular matrix (cell component), and extracellular matrix structure constituent (molecular function). The protein-protein network (PPI) was constructed and 10 hub genes were identified, including IL6, VWF, CDH5, PECAM1, EDN1, BDNF, CAV1, SPP1, TEK, and SELE. The expression level of hub genes was validated in the GEPIA database, compared with normal tissues, VWF is lowly expressed and SPP1 is upregulated in LUAD tissues. The survival analysis showed increased expression of SPP1 indicated unfavorable prognosis whereas high expression of VWF suggested favorable prognosis in LUAD (p < 0.05). Based on the immune infiltration analysis, the relationship between SPP1 and VWF expression and macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD. Quantitative real-time PCR (qRT-PCR) and western blotting were used to validate the expression of VWF and SPP1 in normal human bronchial epithelial (HBE) cell and three LUAD cell lines, H1299, H1975, and A549. Immunohistochemistry (IHC) was further performed to detect the expression of VWF in 10 cases LUAD samples and matched normal tissues. In summary, the data suggest that VWF is a potential novel biomarker for prognosis of LUAD.

Loss of COMT activity reduces lateral root formation and alters the response to water limitation in sorghum brown midrib (bmr) 12 mutant

Lignin is a key target for modifying lignocellulosic biomass for efficient biofuel production. Brown midrib 12 (bmr12) encodes the sorghum caffeic acid O-methyltransferase (COMT) and is one of the key enzymes in monolignol biosynthesis. Loss of function mutations in COMT reduces syringyl (S) lignin subunits and improves biofuel conversion rate. Although lignin plays an important role in maintaining cell wall integrity of xylem vessels, physiological and molecular consequences due to loss of COMT on root growth and adaptation to water deficit remain unexplored. We addressed this gap by evaluating the root morphology, anatomy and transcriptome of bmr12 mutant. The mutant had reduced lateral root density (LRD) and altered root anatomy and response to water limitation. The wild-type exhibits similar phenotypes under water stress, suggesting that bmr12 may be in a water deficit responsive state even in well-watered conditions. bmr12 had increased transcript abundance of genes involved in (a)biotic stress response, gibberellic acid (GA) biosynthesis and signaling. We show that bmr12 is more sensitive to exogenous GA application and present evidence for the role of GA in regulating reduced LRD in bmr12. These findings elucidate the phenotypic and molecular consequences of COMT deficiency under optimal and water stress environments in grasses.

Knocking out NEGATIVE REGULATOR OF PHOTOSYNTHESIS 1 increases rice leaf photosynthesis and biomass production in the field

Improving photosynthesis is a major approach to increasing crop yield potential. Here we identify a transcription factor as a negative regulator of photosynthesis, which can be manipulated to increase rice photosynthesis and plant biomass in the field. This transcription factor, named negative regulator of photosynthesis 1 (NRP1; Os07g0471900), was identified through a co-expression analysis using rice leaf RNA sequencing data. NRP1 expression showed significantly negative correlation with the expression of many genes involved in photosynthesis. Knocking out NRP1 led to greater photosynthesis and increased biomass in the field, while overexpression of NRP1 decreased photosynthesis and biomass. Transcriptomic data analysis shows that NRP1 can negatively regulate the expression of photosynthetic genes. Protein transactivation experiments show that NRP1 is a transcription activator, implying that NRP1 may indirectly regulate photosynthetic gene expression through an unknown regulator. This study shows that combination of bioinformatics analysis with transgenic testing can be used to identify new regulators to improve photosynthetic efficiency in crops.

[Differential mRNA expression in C57BL/6 mice with bleomycin-induced pulmonary fibrosis and its association with LncRNA co-expression network]

OBJECTIVE

To study the changes in mRNA and long non-coding RNA (lncRNA) expression profiles in a mouse model of bleomycin-induced lung fibrosis and identify lung fibrosis-related mRNA for coding-noncoding coexpression (CNC) bioinformatics analysis of the differential lncRNAs.

METHODS

Lung fibrosis was induced by intratracheal injection of bleomycin in 10 C57BL/6 mice and another 10 mice with intratracheal injection of saline served as the control group. Lung tissues were harvested from the mice at 14 days after the injections and lung fibrosis was assessed using Masson and HE staining. LncRNA chip technology was used to screen the differentially expressed mRNAs and lncRNAs in mice with lung fibrosis, and GO and KEGG pathway analyses of the differential mRNAs were performed using NCBI database and UCSC database to identify possible fibrosis-related mRNAs, which were validated by qRT-PCR to construct a coding and non-coding co- expression network with the differential lncRNAs.

RESULTS

Compared with the control mice, the mice with intratracheal injection of bleomycin showed obvious lung fibrosis. The results of gene chip analysis showed that 127 mRNAs were upregulated and 184 mRNAs were down-regulated in the model group as compared with the control group. GO and pathway analysis suggested that the differentially expressed genes participated mainly in immune response, cell differentiation, and cytoskeletons; the involved signal pathways were associated mainly with cytokine and cytokine receptor interaction and chemokine signal transduction. Bioinformatics analysis identified a significant coexpression network between the fibrosisrelated mRNA and the differentially expressed lncRNA.

CONCLUSIONS

In mice with lung fibrosis, the differential expressions of fibrosis-related mRNAs in the lung tissues are closely correlated with the co- expressions of a large number of differential lncRNAs, which points to a new direction for investigation of the pathogenesis of pulmonary fibrosis.

Identification of Novel Potential Genes Involved in Cancer by Integrated Comparative Analyses

The main hallmarks of cancer diseases are the evasion of programmed cell death, uncontrolled cell division, and the ability to invade adjacent tissues. The explosion of omics technologies offers challenging opportunities to identify molecular agents and processes that may play relevant roles in cancer. They can support comparative investigations, in one or multiple experiments, exploiting evidence from one or multiple species. Here, we analyzed gene expression data from induction of programmed cell death and stress response in Homo sapiens and compared the results with Saccharomyces cerevisiae gene expression during the response to cell death. The aim was to identify conserved candidate genes associated with Homo sapiens cell death, favored by crosslinks based on orthology relationships between the two species. We identified differentially-expressed genes, pathways that are significantly dysregulated across treatments, and characterized genes among those involved in induced cell death. We investigated on co-expression patterns and identified novel genes that were not expected to be associated with death pathways, that have a conserved pattern of expression between the two species. Finally, we analyzed the resulting list by HumanNet and identified new genes predicted to be involved in cancer. The data integration and the comparative approach between distantly-related reference species that were here exploited pave the way to novel discoveries in cancer therapy and also contribute to detect conserved genes potentially involved in programmed cell death.

Co-expression Networks From Gene Expression Variability Between Genetically Identical Seedlings Can Reveal Novel Regulatory Relationships

Co-expression networks are a powerful tool to understand gene regulation. They have been used to identify new regulation and function of genes involved in plant development and their response to the environment. Up to now, co-expression networks have been inferred using transcriptomes generated on plants experiencing genetic or environmental perturbation, or from expression time series. We propose a new approach by showing that co-expression networks can be constructed in the absence of genetic and environmental perturbation, for plants at the same developmental stage. For this, we used transcriptomes that were generated from genetically identical individual plants that were grown under the same conditions and for the same amount of time. Twelve time points were used to cover the 24-h light/dark cycle. We used variability in gene expression between individual plants of the same time point to infer a co-expression network. We show that this network is biologically relevant and use it to suggest new gene functions and to identify new targets for the transcriptional regulators GI, PIF4, and PRR5. Moreover, we find different co-regulation in this network based on changes in expression between individual plants, compared to the usual approach requiring environmental perturbation. Our work shows that gene co-expression networks can be identified using variability in gene expression between individual plants, without the need for genetic or environmental perturbations. It will allow further exploration of gene regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild.

Integrated Analysis of Competing Endogenous RNAs Network Reveals Potential Signatures in Osteosarcoma Development

The purpose of this work was to extract key players such as mRNAs and long non-coding RNA (lncRNAs) in the etiopathogenesis of osteosarcoma (OS). The sequencing analyses (mRNAs and lncRNAs) of OS were conducted followed by differentially expressed mRNAs and lncRNAs (DEmRNAs and DElncRNAs) identification between U-2OS cells with has-miR-590-5p overexpression and negative control cells. Following this, the co-expression and functional enrichment analyses of DEmRNAs and DElncRNAs were carried out. Also, the miRNAs-DElncRNAs-DEmRNAs regulatory network was constructed with DElncRNAs-miRNAs and DElncRNAs-DEmRNAs pairs after the target gene analysis of miRNA. In addition, the ceRNA-has-miR-590-5p was further extracted based on the has-miR-590-5p-DElncRNAs and DElncRNAs-DEmRNAs interactions. Finally, the results of the bioinformatics analysis was verified by reverse-transcription polymerase chain reaction (RT-PCR). Totally, 980 DEmRNAs (539 up-regulated DEmRNAs and 441 down-regulated DEmRNAs) and 682 DElncRNAs (352 up-regulated DElncRNAs and 330 down-regulated DElncRNAs) were extracted between cells with hsa-miR-590-5p overexpression and normal cells. The functional analyses suggested that up-regulated genes were significantly enriched in several GO terms such as signal transduction and cytokine-cytokine receptor interaction pathway while down-regulated genes (SCUBE3, HIST1H4E and EDIL3) were associated with calcium ion binding, cell surface function and nucleosome assembly. Additionally, the miRNAs-DEmRNAs-DEmRNAs network represented 220 pairs among 41 miRNAs, 38 DElncRNAs and 61 DEmRNAs. Furthermore, the ceRNA-hsa-miR-590-5p network consisted of 70 interaction pairs including hsa-miR-590-5p-SCUBE3-CTB-113D17.1, hsa-miR-590-5p-EDIL3-CTB-113D17.1 and hsa-miR-590-5p-HIST1H4E-CTB-113D17.1) among hsa-miR-590-5p, 30 DEmRNAs and 4 down-regulated DElncRNAs. Meanwhile, the RT-PCR results incidated that compared with the blank (KB) and negative control (NC) group, the mRNA expression of SCUBE3, HIST1H4E, and EDIL3 were significantly descreased in mimics group (P value <0.05). The lncRNA CTB-113D17.1 might implicate with OS development probably via serving as a hsa-miR-590-5p sponge to regulate gene targets (SCUBE3, EDIL3 and HIST1H4E), which will facilitate the deep understandings of OS progression.

Systematic Multi-Omics Integration (MOI) Approach in Plant Systems Biology

Across all facets of biology, the rapid progress in high-throughput data generation has enabled us to perform multi-omics systems biology research. Transcriptomics, proteomics, and metabolomics data can answer targeted biological questions regarding the expression of transcripts, proteins, and metabolites, independently, but a systematic multi-omics integration (MOI) can comprehensively assimilate, annotate, and model these large data sets. Previous MOI studies and reviews have detailed its usage and practicality on various organisms including human, animals, microbes, and plants. Plants are especially challenging due to large poorly annotated genomes, multi-organelles, and diverse secondary metabolites. Hence, constructive and methodological guidelines on how to perform MOI for plants are needed, particularly for researchers newly embarking on this topic. In this review, we thoroughly classify multi-omics studies on plants and verify workflows to ensure successful omics integration with accurate data representation. We also propose three levels of MOI, namely element-based (level 1), pathway-based (level 2), and mathematical-based integration (level 3). These MOI levels are described in relation to recent publications and tools, to highlight their practicality and function. The drawbacks and limitations of these MOI are also discussed for future improvement toward more amenable strategies in plant systems biology.

Systematic prediction of the biological functions of TAS2R10 using positive co-expression analysis

Type 2 taste receptor 10 (TAS2R10), belonging to the TAS2R family of bitter receptors, is widely expressed in extra-oral tissues. However, its biological roles beyond bitterness sensing in the tongue have remained largely elusive. The present study aimed to perform a positive co-expression analysis using 60,000 Affymetrix expression arrays and 5,000 The Cancer Genome Atlas datasets to uncover such roles. Based on the functional enrichment analysis, it was indicated that in the Gene Ontology (GO) category biological process, TAS2R10 was mostly involved in 'cellular protein metabolic process', 'protein modification process', 'cellular protein modification process' and 'cellular component assembly'. In the GO category cellular component, the co-expressed genes were accumulated in 'Spt-Ada-Gcn5 acetyltransferase (SAGA)-type complex' and 'SAGA complex', and in the category molecular function, they were concentrated in 'hexosaminidase activity', 'cytoskeletal adaptor activity', 'cyclin binding' and 'β-N-acetylhexosaminidase activity'. Of note, it was indicated that TAS2R10 may be involved in 'ubiquitin-mediated proteolysis', which may provide a starting point to fully investigate the detailed functions of TAS2R10 in the future. TAS2R10 was also indicated to be associated with human diseases, i.e. 'Salmonella infection'. Overall, the present study was the first to perform a comprehensive bioinformatics analysis of the functions of TAS2R10 and provide insight regarding the notion that this gene may have crucial roles beyond bitterness sensing.

Functional Gene Network of Prenyltransferases in Arabidopsis thaliana

Prenyltransferases (PTs) are enzymes that catalyze prenyl chain elongation. Some are highly similar to each other at the amino acid level. Therefore, it is difficult to assign their function based solely on their sequence homology to functional orthologs. Other experiments, such as in vitro enzymatic assay, mutant analysis, and mutant complementation are necessary to assign their precise function. Moreover, subcellular localization can also influence the functionality of the enzymes within the pathway network, because different isoprenoid end products are synthesized in the cytosol, mitochondria, or plastids from prenyl diphosphate (prenyl-PP) substrates. In addition to in vivo functional experiments, in silico approaches, such as co-expression analysis, can provide information about the topology of PTs within the isoprenoid pathway network. There has been huge progress in the last few years in the characterization of individual Arabidopsis PTs, resulting in better understanding of their function and their topology within the isoprenoid pathway. Here, we summarize these findings and present the updated topological model of PTs in the Arabidopsis thaliana isoprenoid pathway.

7-lncRNA Assessment Model for Monitoring and Prognosis of Breast Cancer Patients: Based on Cox Regression and Co-expression Analysis

Background: Breast cancer is one of the deadliest malignant tumors worldwide. Due to its complex molecular and cellular heterogeneity, the efficacy of existing breast cancer risk prediction models is unsatisfactory. In this study, we developed a new lncRNA model to predict the prognosis of patients with BRCA.

Methods: BRCA-related differentially-expressed long non-coding RNA were screened from the Cancer Genome Atlas database. A novel lncRNA model was developed by univariate and multivariate analyses to predict the prognosis of patients with BRCA. The efficacy of the model was verified by TCGA-based breast cancer samples. Identified lncRNA-related mRNA based on the co-expression method.

Results: We constructed a 7-lncRNA breast cancer prediction model including LINC00377, LINC00536, LINC01224, LINC00668, LINC01234, LINC02037, and LINC01456. The breast cancer samples were divided into high-risk and low-risk groups based on the model, which verified the specificity and sensitivity of the model. The Area Under Curve (AUC) of the 3- and 5-year Receiver Operating Characteristic curve were 0.711 and 0.734, respectively, indicating that the model has good performance.

Conclusion: We constructed a 7-lncRNA model to predict the prognosis of patients with BRCA, and suggest that these lncRNAs may play a specific role in the carcinogenesis of BRCA.

Comprehensive Analysis of Therapy-Related Messenger RNAs and Long Noncoding RNAs as Novel Biomarkers for Advanced Colorectal Cancer

Colorectal cancer (CRC) is one of the most common types of human cancers. However, the mechanisms underlying CRC progression remained elusive. This study identified differently expressed messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and small nucleolar RNAs (snoRNAs) between pre-therapeutic biopsies and post-therapeutic resections of locally advanced CRC by analyzing a public dataset, GSE94104. We identified 427 dysregulated mRNAs, 4 dysregulated lncRNAs, and 19 dysregulated snoRNAs between pre- and post-therapeutic locally advanced CRC samples. By constructing a protein–protein interaction network and co-expressing networks, we identified 10 key mRNAs, 4 key lncRNAs, and 7 key snoRNAs. Bioinformatics analysis showed therapy-related mRNAs were associated with nucleosome assembly, chromatin silencing at recombinant DNA, negative regulation of gene expression, and DNA replication. Therapy-related lncRNAs were associated with cell adhesion, extracellular matrix organization, angiogenesis, and sister chromatid cohesion. In addition, therapy-related snoRNAs were associated with DNA replication, nucleosome assembly, and telomere organization. We thought this study provided useful information for identifying novel biomarkers for CRC.

Lipid remodeling regulator 1 (LRL1) is differently involved in the phosphorus-depletion response from PSR1 in Chlamydomonas reinhardtii

The elucidation of lipid metabolism in microalgae has attracted broad interest, as their storage lipid, triacylglycerol (TAG), can be readily converted into biofuel via transesterification. TAG accumulates in the form of oil droplets, especially when cells undergo nutrient deprivation, such as for nitrogen (N), phosphorus (P), or sulfur (S). TAG biosynthesis under N-deprivation has been comprehensively studied in the model microalga Chlamydomonas reinhardtii, during which TAG accumulates dramatically. However, the resulting rapid breakdown of chlorophyll restricts overall oil yield productivity and causes cessation of cell growth. In contrast, P-deprivation results in oil accumulation without disrupting chloroplast integrity. We used a reverse genetics approach based on co-expression analysis to identify a transcription factor (TF) that is upregulated under P-depleted conditions. Transcriptomic analysis revealed that the mutants showed repression of genes typically associated with lipid remodeling under P-depleted conditions, such as sulfoquinovosyl diacylglycerol 2 (SQD2), diacylglycerol acyltransferase (DGTT1), and major lipid droplet protein (MLDP). As accumulation of sulfoquinovosyl diacylglycerol and TAG were suppressed in P-depleted mutants, we designated the protein as lipid remodeling regulator 1 (LRL1). LRL1 mutants showed slower growth under P-depletion. Moreover, cell size in the mutant was significantly reduced, and TAG and starch accumulation per cell were decreased. Transcriptomic analysis also suggested the repression of several genes typically upregulated in adaptation to P-depletion that are associated with the cell cycle and P and lipid metabolism. Thus, our analysis of LRL1 provides insights into P-allocation and lipid remodeling under P-depleted conditions in C. reinhardtii. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The sequencing data were made publicly available under the BioProject Accession number PRJDB6733 and an accession number LC488724 at the DNA Data Bank of Japan (DDBJ). The data is available at https://trace.ddbj.nig.ac.jp/BPSearch/bioproject?acc=PRJDB6733; http://getentry.ddbj.nig.ac.jp/getentry/na/LC488724. The metabolome data were made publicly available and can be accessed at http://metabolonote.kazusa.or.jp/SE195:/; http://webs2.kazusa.or.jp/data/nur/.

TNF-like ligand 1A is associated with progression and prognosis of human gastric cancer

Purpose

This study aimed to investigate the function of TNF-like ligand 1A (TL1A) in the tumorigenesis and progression of gastric cancer (GC).

Methods

RNA-seq gene expression and clinical information for GC patients were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) between GC tissue samples and normal controls were screened with the edgeR package. Identification of gene co-expression and functional enrichment analyses were performed with Pearson’s correlation analysis and gene set enrichment analysis (GSEA), respectively. Lastly, survival analysis was performed using the Kaplan-Meier method with the log rank test.

Results

TL1A expression in GC tissue samples were significantly higher than that in normal controls (LogFC=1.07 and P=8.90E-07). Moreover, 215 genes, co-expressed with TL1A, and 21 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were obtained. Next, the miRNA-lncRNA/mRNA network, comprising 7 miRNAs, 27 lncRNAs, and 21 mRNAs, was constructed based on key genes from intersections between co-expression analysis and GSEA. In addition, survival analysis results demonstrated that TL1A (P=2.6e−07) was significantly associated with the overall survival (OS) of GC patients.

Conclusion

TL1A was involved in the tumorigenesis and progression of GC, and was significantly associated with the OS of GC patients.

Genome-Wide Analysis of Glycoside Hydrolase Family 1 β-glucosidase Genes in Brassica rapa and Their Potential Role in Pollen Development

Glycoside hydrolase family 1 (GH1) β-glucosidases (BGLUs) are encoded by a large number of genes, and are involved in many developmental processes and stress responses in plants. Due to their importance in plant growth and development, genome-wide analyses have been conducted in model plants (Arabidopsis and rice) and maize, but not in Brassica species, which are important vegetable crops. In this study, we systematically analyzed B. rapaBGLUs (BrBGLUs), and demonstrated the involvement of several genes in pollen development. Sixty-four BrBGLUs were identified in Brassica databases, which were anchored onto 10 chromosomes, with 10 tandem duplications. Phylogenetic analysis revealed that 64 genes were classified into 10 subgroups, and each subgroup had relatively conserved intron/exon structures. Clustering with Arabidopsis BGLUs (AtBGLUs) facilitated the identification of several important subgroups for flavonoid metabolism, the production of glucosinolates, the regulation of abscisic acid (ABA) levels, and other defense-related compounds. At least six BrBGLUs might be involved in pollen development. The expression of BrBGLU10/AtBGLU20, the analysis of co-expressed genes, and the examination of knocked down Arabidopsis plants strongly suggests that BrBGLU10/AtBGLU20 has an indispensable function in pollen development. The results that are obtained from this study may provide valuable information for the further understanding of β-glucosidase function and Brassica breeding, for nutraceuticals-rich Brassica crops.

Detection of Co-expressed Pathway Modules Associated With Mineral Concentration and Meat Quality in Nelore Cattle

Meat quality is a complex trait that is influenced by genetic and environmental factors, which includes mineral concentration. However, the association between mineral concentration and meat quality, and the specific molecular pathways underlying this association, are not well explored. We therefore analyzed gene expression as measured with RNA-seq in Longissimus thoracis muscle of 194 Nelore steers for association with three meat quality traits (intramuscular fat, meat pH, and tenderness) and the concentration of 13 minerals (Ca, Cr, Co, Cu, Fe, K, Mg, Mn, Na, P, S, Se, and Zn). We identified seven sets of co-expressed genes (modules) associated with at least two traits, which indicates that common pathways influence these traits. From pathway analysis of module hub genes, we further found an over-representation for energy and protein metabolism (AMPK and mTOR signaling pathways) in addition to muscle growth, and protein turnover pathways. Among the identified hub genes FASN, ELOV5, and PDE3B are involved with lipid metabolism and were affected by previously identified eQTLs associated to fat deposition. The reported hub genes and over-represented pathways provide evidence of interplay among gene expression, mineral concentration, and meat quality traits. Future studies investigating the effect of different levels of mineral supplementation in the gene expression and meat quality traits could help us to elucidate the regulatory mechanism by which the genes/pathways are affected.

SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer

Improved cancer prognosis is a central goal for precision health medicine. Though many models can predict differential survival from data, there is a strong need for sophisticated algorithms that can aggregate and filter relevant predictors from increasingly complex data inputs. In turn, these models should provide deeper insight into which types of data are most relevant to improve prognosis. Deep Learning-based neural networks offer a potential solution for both problems because they are highly flexible and account for data complexity in a non-linear fashion. In this study, we implement Deep Learning-based networks to determine how gene expression data predicts Cox regression survival in breast cancer. We accomplish this through an algorithm called SALMON (Survival Analysis Learning with Multi-Omics Neural Networks), which aggregates and simplifies gene expression data and cancer biomarkers to enable prognosis prediction. The results revealed improved performance when more omics data were used in model construction. Rather than use raw gene expression values as model inputs, we innovatively use eigengene modules from the result of gene co-expression network analysis. The corresponding high impact co-expression modules and other omics data are identified by feature selection technique, then examined by conducting enrichment analysis and exploiting biological functions, escalated the interpretation of input feature from gene level to co-expression modules level. Our study shows the feasibility of discovering breast cancer related co-expression modules, sketch a blueprint of future endeavors on Deep Learning-based survival analysis. SALMON source code is available at https://github.com/huangzhii/SALMON/.

webCEMiTool: Co-expression Modular Analysis Made Easy

Co-expression analysis has been widely used to elucidate the functional architecture of genes under different biological processes. Such analysis, however, requires substantial knowledge about programming languages and/or bioinformatics skills. We present webCEMiTool,¹ a unique online tool that performs comprehensive modular analyses in a fully automated manner. The webCEMiTool not only identifies co-expression gene modules but also performs several functional analyses on them. In addition, webCEMiTool integrates transcriptomic data with interactome information (i.e., protein-protein interactions) and identifies potential hubs on each network. The tool generates user-friendly html reports that allow users to search for specific genes in each module, as well as check if a module contains genes overrepresented in specific pathways or altered in a specific sample phenotype. We used webCEMiTool to perform a modular analysis of single-cell RNA-seq data of human cells infected with either Zika virus or dengue virus.

Gene regulatory networks for lignin biosynthesis in switchgrass (Panicum virgatum)

Cell wall recalcitrance is the major challenge to improving saccharification efficiency in converting lignocellulose into biofuels. However, information regarding the transcriptional regulation of secondary cell wall biogenesis remains poor in switchgrass (Panicum virgatum), which has been selected as a biofuel crop in the United States. In this study, we present a combination of computational and experimental approaches to develop gene regulatory networks for lignin formation in switchgrass. To screen transcription factors (TFs) involved in lignin biosynthesis, we developed a modified method to perform co-expression network analysis using 14 lignin biosynthesis genes as bait (target) genes. The switchgrass lignin co-expression network was further extended by adding 14 TFs identified in this study, and seven TFs identified in previous studies, as bait genes. Six TFs (PvMYB58/63, PvMYB42/85, PvMYB4, PvWRKY12, PvSND2 and PvSWN2) were targeted to generate overexpressing and/or down-regulated transgenic switchgrass lines. The alteration of lignin content, cell wall composition and/or plant growth in the transgenic plants supported the role of the TFs in controlling secondary wall formation. RNA-seq analysis of four of the transgenic switchgrass lines revealed downstream target genes of the secondary wall-related TFs and crosstalk with other biological pathways. In vitro transactivation assays further confirmed the regulation of specific lignin pathway genes by four of the TFs. Our meta-analysis provides a hierarchical network of TFs and their potential target genes for future manipulation of secondary cell wall formation for lignin modification in switchgrass.

Identification of key proteins and lncRNAs in hypertrophic cardiomyopathy by integrated network analysis

INTRODUCTION

Hypertrophic cardiomyopathy (HCM), a genetically heterogeneous disorder of cardiac myocytes, is one of the main causes of sudden cardiac death of young people. However, the molecular mechanism involved in HCM has remained largely unclear. Of note, non-coding RNAs were reported to play an important role in human diseases. In this study, we focused on identifying differentially expressed long non-coding RNA (lncRNAs) and mRNAs in HCM by analyzing a public dataset (GSE36961).

MATERIAL AND METHODS

We performed bioinformatics analysis to explore key pathways underlying HCM progression. Gene Ontology (GO) analysis was first performed to evaluate the potential roles of differentially expressed genes and lncRNAs in HCM. Moreover, protein-protein interaction (PPI) networks were constructed to reveal interactions among differentially expressed proteins. Specifically, co-expression networks were also constructed to identify hub lncRNAs in HCM.

RESULTS

A total of 6147 mRNAs (p < 0.001) and 126 lncRNAs (p < 0.001) were found to be dysregulated in HCM. Gene Ontology (GO) analysis showed that these differentially expressed genes and lncRNAs were associated with metabolism, energy pathways, signal transduction, and cell communication. Moreover, TSPYL3, LOC401431, LOC158376, LOC606724, PDIA3P and LOH3CR2A (p < 0.001) were identified as key lncRNAs in HCM progression.

CONCLUSIONS

Taken together, our analysis revealed a series of lncRNAs and mRNAs that were differentially expressed in HCM and which were involved in HCM progression by regulating pathways, such as metabolism, energy pathways, signal transduction, and cell communication. This study will provide useful information to explore the mechanisms underlying HCM progression and to provide potential candidate biomarkers for diagnosis in HCM.

Identification of Key lncRNAs Associated With Atherosclerosis Progression Based on Public Datasets

Atherosclerosis is one of the most common type of cardiovascular disease and the prime cause of mortality in the aging population worldwide. However, the detail mechanisms and special biomarkers of atherosclerosis remain to be further investigated. Lately, long non-coding RNAs (lncRNAs) has attracted much more attention than other types of ncRNAs. In our work, we found and confirmed differently expressed lncRNAs and mRNAs in atherosclerosis by analyzing GSE28829. We performed the weighted gene co-expression network analysis (WGCNA) by analyzing GSE40231 to confirm highly correlated genes. Gene Ontology (GO) analysis were utilized to assess the potential functions of differential expressed lncRNAs in atherosclerosis. Co-expression networks were also constructed to confirm hub lncRNAs in atherosclerosis. A total of 5784 mRNAs and 654 lncRNAs were found to be dysregulated in the progression of atherosclerosis. A total of 15 lncRNA-mRNA co-expression modules were identified in this study based on WGCNA analysis. Moreover, a few lncRNAs, such as ZFAS1, LOC100506730, LOC100506691, DOCK9-AS2, RP11-6I2.3, LOC100130219, were confirmed as important lncRNAs in atherosclerosis. Taken together, bioinformatics analysis revealed these lncRNAs were involved in regulating the leukotriene biosynthetic process, gene expression, actin filament organization, t-circle formation, antigen processing, and presentation, interferon-gamma-mediated signaling pathway, and activation of GTPase activity. We believed that this study would provide potential novel therapeutic and prognostic targets for atherosclerosis.

Systematic Analysis of Gene Expression Alteration and Co-Expression Network of Eukaryotic Initiation Factor 4A-3 in Cancer

Purpose: Eukaryotic initiation factor 4A-3 (EIF4A3) is an RNA-binding protein (RBP) that is a core component of the exon junction complex (EJC). It has been identified as an important player in post-transcriptional regulation processes. Recently, investigations have focused on EIF4A3 dysfunction in carcinogenesis. The present study aims to determine whether EIF4A3 can serve as a prognostic marker and potential regulatory mechanism in human cancers. Materials and methods: EIF4A3 expression in various cancers was assessed using Oncomine. The Correlation between EIF4A3 expression and patient survival was evaluated using PrognoScan. EIF4A3 mutations in various cancers were investigated using cBioPortal. EIF4A3 co-expression networks in various cancers were established using Coexpedia. Finally, we analyzed potential functional roles of EIF4A3 using Gene Ontology and pathway enrichment analyses by FunRich V3. Results: EIF4A3 was overexpressed in common malignancies at the transcription levels. High incidences of the breast, lung, and urinary cancers were closely related to the prognostic index for survival. The most prevalent mutation in EIF4A3 was E59K/Q. The tumor necrosis factor-α (TNF-α)/nuclear factor-κB (NF-κB) signaling pathway was affected by these mutations. Co-expression networks showed that EIF4A3 regulates apoptosis and cell cycle via several cancer-related signal pathways, and promotes tumor cell migration, invasion and drug resistance. Conclusion: Our results suggest the potential role for EIF4A3 to serve as a diagnostic marker or therapeutic target for certain types of cancers.

Revealing the Critical Regulators of Cell Identity in the Mouse Cell Atlas

Recent progress in single-cell technologies has enabled the identification of all major cell types in mouse. However, for most cell types, the regulatory mechanism underlying their identity remains poorly understood. By computational analysis of the recently published mouse cell atlas data, we have identified 202 regulons whose activities are highly variable across different cell types, and more importantly, predicted a small set of essential regulators for each major cell type in mouse. Systematic validation by automated literature and data mining provides strong additional support for our predictions. Thus, these predictions serve as a valuable resource that would be useful for the broad biological community. Finally, we have built a user-friendly, interactive web portal to enable users to navigate this mouse cell network atlas.

Gene Function Prediction Based on Developmental Transcriptomes of the Two Sexes in C. elegans

We compare whole-animal RNA-seq transcriptomes for C. elegans males and hermaphrodites from the late L3 larval stage to young adulthood. During this interval, male sexual structures develop, including extensive neurogenesis and synaptogenesis that nearly doubles the size of the nervous system. Previous genome-wide expression studies in C. elegans have usually focused on only one sex—the hermaphrodite—and there are a relatively large number of genes that remain without meaningful annotation. In the present study, differential expression analysis of the RNA-seq data revealed 1,751 genes expressed at a higher level in the male. By differential expression and co-expression analyses, we identified transcription factors required for differentiation of male genital structures, semen proteins, and candidates for components of synapse function. Comparison with other prediction tools suggests that our dataset can expand gene predictions. The results validate the dataset as a rich resource for future gene discovery in C. elegans.

Overexpression of COL3A1 confers a poor prognosis in human bladder cancer identified by co-expression analysis

Human bladder cancer (BCa) is one of the worldwide cancers in men and women populations, with the etiology and mechanism unknown. In our study, we constructed a weighted gene co-expression network to identify gene modules associated with the progression of BCa (n = 93). In the significant module (R² = 0.48), a total of 103 network hub genes were identified, and 4 of them were hub nodes in the protein-protein interaction network as well. In validation, COL3A1 showed a higher correlation with the disease progression than any other hub genes in hub module in the test set (p < 0.001). Functional and pathway enrichment analysis demonstrated that COL3A1 is overrepresented in pathway of focal adhesion, which associated with tumor progression and might cause metastasis. Gene set enrichment analysis (GSEA) also demonstrated that the gene set of “MAPK signaling pathway” and focal adhesion related pathways were enriched in BCa samples with COL3A1 highly expressed (FDR < 0.05). Considering the clinicopathological parameters, highly-expressed COL3A1 was closely correlated with local recurrence and BCa stage. Survival analysis revealed that BCa patients with higher expression of COL3A1 had a significantly shorter overall survival time and disease free survival time.In conclusion, based on the co-expression analysis, COL3A1 was identified in the association with progression and prognosis of BCa, which might refer a poor prognosisprobably by regulating MAPK signaling pathway.

Resolving stem and progenitor cells in the adult mouse incisor through gene co-expression analysis

Investigations into stem cell-fueled renewal of an organ benefit from an inventory of cell type-specific markers and a deep understanding of the cellular diversity within stem cell niches. Using the adult mouse incisor as a model for a continuously renewing organ, we performed an unbiased analysis of gene co-expression relationships to identify modules of co-expressed genes that represent differentiated cells, transit-amplifying cells, and residents of stem cell niches. Through in vivo lineage tracing, we demonstrated the power of this approach by showing that co-expression module members Lrig1 and Igfbp5 define populations of incisor epithelial and mesenchymal stem cells. We further discovered that two adjacent mesenchymal tissues, the periodontium and dental pulp, are maintained by distinct pools of stem cells. These findings reveal novel mechanisms of incisor renewal and illustrate how gene co-expression analysis of intact biological systems can provide insights into the transcriptional basis of cellular identity.

The grapevine VvibZIPC22 transcription factor is involved in the regulation of flavonoid biosynthesis

In grapevine, flavonoids constitute one of the most abundant subgroups of secondary metabolites, influencing the quality, health value, and typicity of wines. Their synthesis in many plant species is mainly regulated at the transcriptional level by modulation of flavonoid pathway genes either by single regulators or by complexes of different regulators. In particular, bZIP and MYB factors interact synergistically in the recognition of light response units present in the promoter of some genes of the pathway, thus mediating light-dependent flavonoid biosynthesis. We recently identified VvibZIPC22, a member of clade C of the grapevine bZIP family, in a quantitative trait locus (QTL) specifically associated with kaemperol content in mature berries. Here, to validate the involvement of this candidate gene in the fine regulation of flavonol biosynthesis, we characterized its function by in vitro and in vivo experiments. A role for this gene in the control of flavonol biosynthesis was indeed confirmed by its highest expression at flowering and during UV light-mediated induction, paralleled by accumulation of the flavonol synthase 1 transcript and flavonol compounds. The overexpression of VvibZIPC22 in tobacco caused a significant increase in several flavonoids in the flower, via induction of general and specific genes of the pathway. In agreement with this evidence, VvibZIPC22 was able to activate the promoters of specific genes of the flavonoid pathway, alone or together with other factors, as revealed by transient reporter assays. These findings, supported by in silico indications, allowed us to propose VvibZIPC22 as a new regulator of flavonoid biosynthesis in grapevine.

Dynamical properties of gene regulatory networks involved in long-term potentiation

The long-lasting enhancement of synaptic effectiveness known as long-term potentiation (LTP) is considered to be the cellular basis of long-term memory. LTP elicits changes at the cellular and molecular level, including temporally specific alterations in gene networks. LTP can be seen as a biological process in which a transient signal sets a new homeostatic state that is “remembered” by cellular regulatory systems. Previously, we have shown that early growth response (Egr) transcription factors are of fundamental importance to gene networks recruited early after LTP induction. From a systems perspective, we hypothesized that these networks will show less stable architecture, while networks recruited later will exhibit increased stability, being more directly related to LTP consolidation. Using random Boolean network (RBN) simulations we found that the network derived at 24 h was markedly more stable than those derived at 20 min or 5 h post-LTP. This temporal effect on the vulnerability of the networks is mirrored by what is known about the vulnerability of LTP and memory itself. Differential gene co-expression analysis further highlighted the importance of the Egr family and found a rapid enrichment in connectivity at 20 min, followed by a systematic decrease, providing a potential explanation for the down-regulation of gene expression at 24 h documented in our preceding studies. We also found that the architecture exhibited by a control and the 24 h LTP co-expression networks fit well to a scale-free distribution, known to be robust against perturbations. By contrast the 20 min and 5 h networks showed more truncated distributions. These results suggest that a new homeostatic state is achieved 24 h post-LTP. Together, these data present an integrated view of the genomic response following LTP induction by which the stability of the networks regulated at different times parallel the properties observed at the synapse.

Chaperone network composition in Solanum lycopersicum explored by transcriptome profiling and microarray meta-analysis

Heat shock proteins (Hsps) are molecular chaperones primarily involved in maintenance of protein homeostasis. Their function has been best characterized in heat stress (HS) response during which Hsps are transcriptionally controlled by HS transcription factors (Hsfs). The role of Hsfs and Hsps in HS response in tomato was initially examined by transcriptome analysis using the massive analysis of cDNA ends (MACE) method. Approximately 9.6% of all genes expressed in leaves are enhanced in response to HS, including a subset of Hsfs and Hsps. The underlying Hsp-Hsf networks with potential functions in stress responses or developmental processes were further explored by meta-analysis of existing microarray datasets. We identified clusters with differential transcript profiles with respect to abiotic stresses, plant organs and developmental stages. The composition of two clusters points towards two major chaperone networks. One cluster consisted of constitutively expressed plastidial chaperones and other genes involved in chloroplast protein homeostasis. The second cluster represents genes strongly induced by heat, drought and salinity stress, including HsfA2 and many stress-inducible chaperones, but also potential targets of HsfA2 not related to protein homeostasis. This observation attributes a central regulatory role to HsfA2 in controlling different aspects of abiotic stress response and tolerance in tomato.

chinensis)

BACKGROUND

The WRKY transcription factor is an important member of the stress-related transcription factors, which mediate diverse abiotic stresses in many plants. However, up until now, the number of WRKY members, and the regulatory mechanisms involved in abiotic stress responses in Pak-choi (Brassica campestris ssp. chinensis), remained unknown.

RESULTS

We isolated and identified 56 full-length WRKY cDNAs from a Pak-choi stress-induced cDNA library. The 56 putative BcWRKY proteins were divided into three groups based on structural and phylogenetic analyses. A subcellular localization prediction indicated that the putative BcWRKY proteins were enriched in the nuclear region. Experiments involving BcWRKY25 and BcWRKY40 confirmed the prediction. A total of 22 BcWRKYs were differentially expressed in response to at least one stress condition (abscisic acid, cold, salinity, heat, or osmosis) tested on Pak-choi leaves, and a co-expression analysis indicated stress-inducible BcWRKYs co-regulated multiple abiotic stresses. BcWRKY33, BcWRKY40, BcWRKY53, and BcWRKY70 acted as key regulators and played dominant roles within co-regulatory networks of stress-inducible BcWRKYs.

CONCLUSIONS

We first isolated and characterized the 56 stress-inducible WRKY transcription factor family members. A total of 22 stress-inducible BcWRKYs found in leaves can co-regulate multiple environmental stresses by integrating the potential mutual interactions of WRKYs in Pak-choi. This information will be valuable when exploring the molecular mechanisms of WRKYs in response to abiotic stresses in plants.

The distribution of immunomodulatory cells in the lungs of patients with idiopathic pulmonary fibrosis

We have characterized the immune system involvement in the disease processes of idiopathic pulmonary fibrosis in novel ways. To do so, we analyzed lung tissue from 21 cases of idiopathic pulmonary fibrosis and 21 (non-fibrotic, non-cancerous) controls for immune cell and inflammation-related markers. The immunohistochemical analysis of the tissue was grouped by patterns of severity in disease pathology. There were significantly greater numbers of CD68(+) and CD80(+) cells and significantly fewer CD3(+), CD4(+), and CD45RO(+) cells in areas of relatively (histologically) normal lung in biopsy samples from idiopathic pulmonary fibrosis patients compared with controls. In zones of active disease, characterized by epithelial cell regeneration and fibrosis, there were significantly more cells expressing CD4, CD8, CD20, CD68, CD80, chemokine receptor 6 (CCR6), S100, IL-17, tumor necrosis factor-α, and retinoic acid-related orphan receptors compared with histologically normal lung areas from idiopathic pulmonary fibrosis patients. Inflammation was implicated in these active regions by the cells that expressed retinoid orphan receptor-α, -β, and -γ, CCR6, and IL-17. The regenerating epithelial cells predominantly expressed these pro-inflammatory molecules, as evidenced by co-expression analyses with epithelial cytokeratins. Macrophages in pseudo-alveoli and CD3(+) T cells in the fibrotic interstitium also expressed IL-17. Co-expression of IL-17 with retinoid orphan receptors and epithelial cytoskeletal proteins, CD68, and CD3 in epithelial cells, macrophages, and T-cells, respectively, confirmed the production of IL-17 by these cell types. There was little staining for forkhead box p3, CD56, or CD34 in any idiopathic pulmonary fibrosis lung regions. The fibrotic regions had fewer immune cells overall. In summary, our study shows participation of innate and adaptive mononuclear cells in active-disease regions of idiopathic pulmonary fibrosis lung, where the regenerating epithelial cells appear to propagate inflammation. The regenerative mechanisms become skewed to ultimately result in lethal, fibrotic restriction of lung function.