CDKN1A regulation on chondrogenic differentiation of human chondrocytes in osteoarthritis through single-cell and bulk sequencing analysis

Objective

Chondrocyte death is the hallmark of cartilage degeneration during osteoarthritis (OA). However, the specific pathogenesis of cell death in OA chondrocytes has not been elucidated. This study aims to validate the role of CDKN1A, a key programmed cell death (PCD)-related gene, in chondrogenic differentiation using a combination of single-cell and bulk sequencing approaches.

Design

OA-related RNA-seq data (GSE114007, GSE55235, GSE152805) were downloaded from Gene Expression Omnibus database. PCD-related genes were obtained from GeneCards database. RNA-seq was performed to annotate the cell types in OA and control samples. Differentially expressed genes (DEGs) among those cell types (scRNA-DEGs) were screened. A nomogram of OA was constructed based on the featured genes, and potential drugs targeting the featured genes were predicted. The presence of key genes was confirmed using Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR), Western blot (WB), and immunohistochemistry (IHC). Micromass culture and Alcian blue staining were used to determine the effect of CDKN1A on chondrogenesis.

Results

Six cell types, namely HomC, HTC, RepC, preFC, FC, and RegC, were annotated in scRNA-seq data. Five featured genes (JUN, CDKN1A, HMGB2, DDIT3, and DDIT4) were screened by multiple biological information analysis methods. TAXOTERE had the highest ability to dock with DDIT3. Functional analysis indicated that CDKN1A was enriched in processes related to collagen catabolism and acts as a positive regulator of autophagy. Additionally, CDKN1A was found to be associated with several KEGG pathways, including those involved in acute myeloid leukemia and autoimmune thyroid disease. CDKN1A was confirmed down-regulated in the joint tissues of OA mouse model and OA model cell. Inhibiting the expression of CDKN1A can significantly suppress the differentiation of OA chondrocytes.

Conclusion

Our findings highlight the critical role of CDKN1A in promoting cartilage formation in both in vivo and in vitro and suggest its potential as a therapeutic target for OA treatment.

Constructing a screening model to obtain the functional herbs for the treatment of active ulcerative colitis based on herb-compound-target network and immuno-infiltration analysis

The therapeutic effect of most traditional Chinese medicines (TCM) on ulcerative colitis is unclear, The objective of this study was to develop a core herbal screening model aimed at facilitating the transition from active ulcerative colitis (UC) to inactive. We obtained the gene expression dataset GSE75214 for UC from the GEO database and analysed the differentially expressed genes (DEGs) between active and inactive groups. Gene modules associated with the active group were screened using WGCNA, and immune-related genes (IRGs) were obtained from the ImmPort database. The TCMSP database was utilized to acquire the herb-molecule-target network and identify the herb-related targets (HRT). We performed intersection operations on HRTs, DEGs, IRGs, and module genes to identify candidate genes and conducted enrichment analyses. Subsequently, three machine learning algorithms (SVM-REF analysis, Random Forest analysis, and LASSO regression analysis) were employed to refine the hubgene from the candidate genes. Based on the hub genes identified in this study, we conducted compound and herb matching and further screened herbs related to abdominal pain and blood in stool using the Symmap database.Besides, the stability between molecules and targets were assessed using molecular docking and molecular dynamic simulation methods. An intersection operation was performed on HRT, DEGs, IRGs, and module genes, leading to the identification of 23 candidate genes. Utilizing three algorithms (RandomForest, SVM-REF, and LASSO) for analyzing the candidate genes and identifying the intersection, we identified five core targets (CXCL2, DUOX2, LYZ, MMP9, and AGT) and 243 associated herbs. Hedysarum Multijugum Maxim. (Huangqi), Sophorae Flavescentis Radix (Kushen), Cotyledon Fimbriata Turcz. (Wasong), and Granati Pericarpium (Shiliupi) were found to be capable of relieving abdominal pain and hematochezia during active UC. Molecular docking demonstrated that the compounds of the four aforementioned herbs showed positive docking activity with their core targets. The results of molecular dynamic simulations indicated that well-docked active molecules had a more stable structure when bound to their target complexes. The study has shed light on the potential of TCMs in treating active UC from an immunomodulatory perspective, consequently, 5 core targets and 4 key herbs has been identified. These findings can provide a theoretical basis for subsequent management and treatment of active UC with TCM, as well as offer original ideas for further research and development of innovative drugs for alleviating UC.

Transcriptome sequencing analysis reveals a potential role of lncRNA NONMMUT058932.2 and NONMMUT029203.2 in abnormal myelin development of male offspring following prenatal PM2.5 exposure

Numerous epidemiological studies have shown that PM2.5 exposure in early life can influence brain development and increase the risk of neurodevelopmental disorders in boys, but the underlying molecular mechanisms remain unclear. In the current study, pregnant C57BL/6 J mice were oropharyngeally administered with PM2.5 suspension (3mg/kg/2 days) until the birth of offspring. Based on mRNA expression profiles, two-way analysis of variance (two-way ANOVA) and weighted gene co-expression network analysis (WGCNA) were conducted to explore the most impacted neurodevelopmental processes in male offspring and the most significantly associated gene modules. Gene Ontology (GO) enrichment and Encyclopedia of Genes and Genomes (KEGG) pathway analyses suggested that prenatal PM2.5 exposure significantly altered several biological processes (such as substrate adhesion-dependent cell spreading, myelination, and ensheathment of neurons) and KEGG pathways (such as tight junction and axon guidance). We further found that PM2.5 exposure significantly changed the expression of myelination-related genes in male offspring during postnatal development and impaired myelin ultrastructure on PNDs 14 and 21, as demonstrated by the decreased thickness of myelin sheaths in the optic nerves, and mild loss of myelin in the corpus callosum. Importantly, lncRNA NONMMUT058932.2 and NONMMUT029203.2 played key roles in abnormal myelination by regulating the expression of several myelination-related genes (Fa2h, Mal, Sh3tc2, Trf and Tppp) through the binding to transcription factor Ctcf. Our work provides genomic evidence for prenatal PM2.5 exposure-induced neurodevelopmental disorders in male offspring.

Transcriptomic and genetic approaches reveal that the pipecolate biosynthesis pathway simultaneously regulates tomato fruit ripening and quality

Pipecolic acid (Pip) and N-hydroxypipecolic acid (NHP) have been found to accumulate during the ripening of multiple types of fruits; however, the function and mechanism of pipecolate pathway in fruits remain unclear. Here study was conducted on fruits produced by the model plant tomato, wherein the NHP biosynthesis-related genes, Slald1 and Slfmo1, were mutated. The results showed that the fruits of both the Slald1 and the Slfmo1 mutants exhibited a delayed onset of ripening, decreased fruit size, nutrition and flavor. Exogenous treatment with Pip and NHP promoted fruit ripening and improved fruit quality. Transcriptomic analysis combined with weighted gene co-expression network analysis revealed that the genes involved in the biosynthesis of amino acids, carbon metabolism, photosynthesis, starch and sucrose metabolism, flavonoid biosynthesis, and plant hormone signal transduction were affected by SlFMO1 gene mutation. Transcription factor prediction analysis revealed that the NAC and AP2/ERF-ERF family members are notably involved in the regulation pathway. Overall, our results suggest that the pipecolate biosynthesis pathway is involved in the simultaneous regulation of fruit ripening and quality and indicate that a regulatory mechanism at the transcriptional level exists. However, possible roles of endogenously synthesized Pip and NHP in these processes remain to be determined. The biosynthesis pathway genes SlALD1 and SlFMO1 may be potential breeding targets for promoting fruit ripening and improving fruit quality with concomitant yield increases.

Gene co-expression network analysis identifies hub genes associated with different tolerance under calcium deficiency in two peanut cultivars

BACKGROUND

Peanut is an economically-important oilseed crop and needs a large amount of calcium for its normal growth and development. Calcium deficiency usually leads to embryo abortion and subsequent abnormal pod development. Different tolerance to calcium deficiency has been observed between different cultivars, especially between large and small-seed cultivars.

RESULTS

In order to figure out different molecular mechanisms in defensive responses between two cultivars, we treated a sensitive (large-seed) and a tolerant (small-seed) cultivar with different calcium levels. The transcriptome analysis identified a total of 58 and 61 differentially expressed genes (DEGs) within small-seed and large-seed peanut groups under different calcium treatments, and these DEGs were entirely covered by gene modules obtained via weighted gene co-expression network analysis (WGCNA). KEGG enrichment analysis showed that the blue-module genes in the large-seed cultivar were mainly enriched in plant-pathogen attack, phenolic metabolism and MAPK signaling pathway, while the green-module genes in the small-seed cultivar were mainly enriched in lipid metabolism including glycerolipid and glycerophospholipid metabolisms. By integrating DEGs with WGCNA, a total of eight hub-DEGs were finally identified, suggesting that the large-seed cultivar concentrated more on plant defensive responses and antioxidant activities under calcium deficiency, while the small-seed cultivar mainly focused on maintaining membrane features to enable normal photosynthesis and signal transduction.

CONCLUSION

The identified hub genes might give a clue for future gene validation and molecular breeding to improve peanut survivability under calcium deficiency.

Effects of prenatal pesticide exposure on the fetal brain and placenta transcriptomes in a rodent model

Organophosphate and pyrethroid pesticides are among the most extensively used insecticides worldwide. Prenatal exposures to both classes of pesticides have been linked to a wide range of neurobehavioral deficits in the offspring. The placenta is a neuroendocrine organ and the crucial regulator of the intrauterine environment; early-life toxicant exposures could impact neurobehavior by disrupting placental processes. Female C57BL/6 J mice were exposed via oral gavage to an organophosphate, chlorpyrifos (CPF) at 5 mg/kg, a pyrethroid, deltamethrin (DM), at 3 mg/kg, or vehicle only control (CTL). Exposure began two weeks before breeding and continued every three days until euthanasia at gestational day 17. The transcriptomes of fetal brain (CTL n = 18, CPF n = 6, DM n = 8) and placenta (CTL n = 19, CPF n = 16, DM n = 12) were obtained through RNA sequencing, and resulting data was evaluated using weighted gene co-expression networks, differential expression, and pathway analyses. Fourteen brain gene co-expression modules were identified; CPF exposure disrupted the module related to ribosome and oxidative phosphorylation, whereas DM disrupted the modules related to extracellular matrix and calcium signaling. In the placenta, network analyses revealed 12 gene co-expression modules. While CPF exposure disrupted modules related to endocytosis, Notch and Mapk signaling, DM exposure dysregulated modules linked to spliceosome, lysosome and Mapk signaling pathways. Overall, in both tissues, CPF exposure impacted oxidative phosphorylation, while DM was linked to genes involved in spliceosome and cell cycle. The transcription factor Max involved in cell proliferation was overexpressed by both pesticides in both tissues. In summary, gestational exposure to two different classes of pesticide can induce similar pathway-level transcriptome changes in the placenta and the brain; further studies should investigate if these changes are linked to neurobehavioral impairments.

Development and validation of an RBP gene signature for prognosis prediction in colorectal cancer based on WGCNA

BACKGROUND

RNA binding proteins (RBPs) have been implicated in oncogenesis and progression in various cancers. However, the potential value of RBPs as prognostic indicators and therapeutic targets in colorectal cancer (CRC) requires further investigation.

METHODS

Four thousand eighty two RBPs were collected from literature. The weighted gene co-expression network analysis (WGCNA) was performed to identify prognosis-related RBP gene modules based on the data attained from the TCGA cohorts. LASSO algorithm was conducted to establish a prognostic risk model, and the validity of the proposed model was confirmed by an independent GEO dataset. Functional enrichment analysis was performed to reveal the potential biological functions and pathways of the signature and to estimate tumor immune infiltration. Potential therapeutic compounds were inferred utilizing CMap database. Expressions of hub genes were further verified through the Human Protein Atlas (HPA) database and RT-qPCR.

RESULTS

One thousand seven hundred thirty four RBPs were differently expressed in CRC samples and 4 gene modules remarkably linked to the prognosis were identified, based on which a 12-gene signature was established for prognosis prediction. Multivariate Cox analysis suggested this signature was an independent predicting factor of overall survival (P < 0.001; HR:3.682; CI:2.377-5.705) and ROC curves indicated it has an effective predictive performance (1-year AUC: 0.653; 3-year AUC:0.673; 5-year AUC: 0.777). GSEA indicated that high risk score was correlated with several cancer-related pathways, including cytokine-cytokine receptor cross talk, ECM receptor cross talk, HEDGEHOG signaling cascade and JAK/STAT signaling cascade. ssGSEA analysis exhibited a significant correlation between immune status and the risk signature. Noscapine and clofazimine were screened as potential drugs for CRC patients with high-risk scores. TDRD5 and GPC1 were identified as hub genes and their expression were validated in 15 pairs of surgically resected CRC tissues.

CONCLUSION

Our research provides a depth insight of RBPs' role in CRC and the proposed signature are helpful to the personalized treatment and prognostic judgement.

Identification of key pathways and genes in the progression of silicosis based on WGCNA

Silicosis, induced by inhaling silica particles in workplaces, is one of the most common occupational diseases. The prognosis of silicosis and its consequent fibrosis is extremely poor due to limited treatment modalities and lack of understanding of the disease mechanisms. In this study, a Wistar rat model for silicosis fibrosis was established by intratracheal instillation of silica (0, 50, 100 and 200 mg/mL, 1 mL) with the evidence of Hematoxylin and Eosin (HE) and Masson staining and the expressions of inflammatory and fibrotic proteins of rats' lung tissues. RNA of lung tissues of rats exposed to 200 mg/mL silica particles and normal saline for 14 d and 28 d was extracted and sequenced to detect differentially expressed genes (DEGs) and to identify silicosis fibrosis-associated modules and hub genes by Weighted gene co-expression network analysis (WGCNA). Predictions of gene functions and signaling pathways were conducted using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. In this study, it has been demonstrated the promising role of the Hippo signaling pathway in silicosis fibrosis, which will be conducive to elucidating the specific mechanism of pulmonary fibrosis induced by silica and to determining molecular initiating event (MIE) and adverse outcome pathway (AOP) of silicosis fibrosis.

Exploration of anti-chromium mechanism of marine Penicillium janthinellum P1 through combinatorial transcriptomic analysis and WGCNA

Fungi have a promising application prospect in the remediation of heavy-metal wastewater pollution which is a sticky global problem. New marine-derived strain Penicillium janthinellum P1 is of high chromium resistance. However, a comprehensive study of the transcriptomics in Penicillium janthinellum P1 strains is lacking. Firstly, the changing trends of a series of physiological and biochemical indices of P1 strain at 0 M and 1 M Cr concentration were investigated to track the ROS variation. Secondly, transcriptome sequencing of P1 was performed by RNA-Seq sequencing technology. The transcriptome data indicated that 12,352 coding protein regions were predicted, and 6655 differentially expressed genes were identified by DESeq2, of which 4234 genes were up-regulated, and 2421 genes down-regulated. Through further co-expression network of WGCNA analysis, the filtered unigenes were clustered into 19 modules. Combined with the physiological and biochemical findings, the three modules with the highest correlation with the six traits were selected to construct the network, and 52 hub genes were obtained. Furthermore, 10 speculative hub genes related to chromium resistance were selected and verified by real-time PCR. The results were in line with the expected experimental assumption. These results improve our understanding of the transcriptomic dimensions of the high chromium resistance of Penicillium janthinellum P1 strains.

Bioinformatic analysis for potential biological processes and key targets of heart failure-related stroke

This study aimed to uncover underlying mechanisms and promising intervention targets of heart failure (HF)-related stroke. HF-related dataset GSE42955 and stroke-related dataset GSE58294 were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was conducted to identify key modules and hub genes. Gene Ontology (GO) and pathway enrichment analyses were performed on genes in the key modules. Genes in HF- and stroke-related key modules were intersected to obtain common genes for HF-related stroke, which were further intersected with hub genes of stroke-related key modules to obtain key genes in HF-related stroke. Key genes were functionally annotated through GO in the Reactome and Cytoscape databases. Finally, key genes were validated in these two datasets and other datasets. HF- and stroke-related datasets each identified two key modules. Functional enrichment analysis indicated that protein ubiquitination, Wnt signaling, and exosomes were involved in both HF- and stroke-related key modules. Additionally, ten hub genes were identified in stroke-related key modules and 155 genes were identified as common genes in HF-related stroke. OTU deubiquitinase with linear linkage specificity(OTULIN) and nuclear factor interleukin 3-regulated(NFIL3) were determined to be the key genes in HF-related stroke. Through functional annotation, OTULIN was involved in protein ubiquitination and Wnt signaling, and NFIL3 was involved in DNA binding and transcription. Importantly, OTULIN and NFIL3 were also validated to be differentially expressed in all HF and stroke groups. Protein ubiquitination, Wnt signaling, and exosomes were involved in HF-related stroke. OTULIN and NFIL3 may play a key role in HF-related stroke through regulating these processes, and thus serve as promising intervention targets.

Transcriptome, degradome and physiological analysis provide new insights into the mechanism of inhibition of litchi fruit senescence by melatonin

Litchi fruit has high commercial value on the international market, but senesces rapidly after harvest. We used weighted gene co-expression network analysis (WGCNA) and degradome technology to investigate the molecular mechanisms of melatonin-mediated delay of litchi fruit senescence through application of exogenous melatonin and p-chlorophenylalanine (p-CPA, an inhibitor of melatonin biosynthesis) treatments. Results demonstrated that exogenous melatonin treatment delayed litchi fruit senescence while p-CPA accelerated senescence. Coupled analyses of transcriptome and physiological parameters of litchi fruit provided the correlation of network modules with dynamic changes in browning index during storage. Additionally, we found that microRNAs (miR858 and miR160a) and their targets were actively involved in melatonin-mediated delay of litchi fruit senescence. Melatonin treatment decreased abscisic acid (ABA) content but increased PP2C and F-box expression levels, suggesting the involvement of ABA signaling in melatonin-mediated antisenescence. The transcriptions of ZAT, NAC and DREB1 were activated by melatonin treatment. Moreover, the major functional genes involved in histone methylation, γ-aminobutyric acid (GABA) metabolism, energy production, reactive oxygen species (ROS) accumulation and cell death were identified in the melatonin-inhibited litchi pericarp browning. Taken together, we first constructed the global map of the important regulators and pathways to delay litchi senescence and pericarp browning mediated by melatonin.

A proteomic network approach resolves stage-specific molecular phenotypes in chronic traumatic encephalopathy

Background

There is an association between repetitive head injury (RHI) and a pathologic diagnosis of chronic traumatic encephalopathy (CTE) characterized by the aggregation of proteins including tau. The underlying molecular events that cause these abnormal protein accumulations remain unclear. Here, we hypothesized that identifying the human brain proteome from serial CTE stages (CTE I-IV) would provide critical new insights into CTE pathogenesis. Brain samples from frontotemporal lobar degeneration due to microtubule associated protein tau (FTLD-MAPT) mutations were also included as a distinct tauopathy phenotype for comparison.

Methods

Isobaric tandem mass tagged labeling and mass spectrometry (TMT-MS) followed by integrated differential and co-expression analysis (i.e., weighted gene co-expression network analysis (WGCNA)) was used to define modules of highly correlated proteins associated with clinical and pathological phenotypes in control (n = 23), CTE (n = 43), and FTLD-MAPT (n = 12) post-mortem cortical tissues. We also compared these findings to network analysis of AD brain.

Results

We identified over 6000 unique proteins across all four CTE stages which sorted into 28 WGCNA modules. Consistent with Alzheimer’s disease, specific modules demonstrated reduced neuronal protein levels, suggesting a neurodegeneration phenotype, while other modules were increased, including proteins associated with inflammation and glial cell proliferation. Notably, unique CTE-specific modules demonstrated prominent enrichment of immunoglobulins, including IGHM and IGLL5, and extracellular matrix (ECM) proteins as well as progressive protein changes with increasing CTE pathologic stage. Finally, aggregate cell subtype (i.e., neurons, microglia, astrocytes) protein abundance levels in CTE cases were similar in expression to AD, but at intermediate levels between controls and the more exaggerated phenotype of FTLD-MAPT, especially in astrocytes.

Conclusions

Overall, we identified thousands of protein changes in CTE postmortem brain and demonstrated that CTE has a pattern of neurodegeneration in neuronal-synaptic and inflammation modules similar to AD. We also identified unique CTE progressive changes, including the enrichment of immunoglobulins and ECM proteins even in early CTE stages. Early and sustained changes in astrocyte modules were also observed. Overall, the prominent overlap with FTLD-MAPT cases confirmed that CTE is on the tauopathy continuum and identified CTE stage specific molecular phenotypes that provide novel insights into disease pathogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13024-021-00462-3.

Identification of collagen genes related to immune infiltration and epithelial-mesenchymal transition in glioma

Background

Gliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression.

Methods

We downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assays were used to measure the cell migration and invasion capacity. Western blotting was used to test the expression of epithelial-mesenchymal transition (EMT) related markers.

Results

We identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the EMT process of glioma. Finally, taking COL3A1 as a further research object, the results showed that knockdown of COL3A1 significantly inhibited the migration, invasion, and EMT process of SHG44 and A172 cells.

Conclusions

In summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01982-0.

Genome-wide identification and characterization of long non-coding RNAs involved in flag leaf senescence of rice

KEY MESSAGE

This study showed the systematic identification of long non-coding RNAs (lncRNAs) involving in flag leaf senescence of rice, providing the possible lncRNA-mRNA regulatory relationships and lncRNA-miRNA-mRNA ceRNA networks during leaf senescence. LncRNAs have been reported to play crucial roles in diverse biological processes. However, no systematic identification of lncRNAs associated with leaf senescence in plants has been studied. In this study, a genome-wide high throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. A total of 3953 lncRNAs and 38757 mRNAs were identified, of which 343 lncRNAs and 9412 mRNAs were differentially expressed. Through weighted gene co-expression network analysis (WGCNA), 22 continuously down-expressed lncRNAs targeting 812 co-expressed mRNAs and 48 continuously up-expressed lncRNAs targeting 1209 co-expressed mRNAs were considered to be significantly associated with flag leaf senescence. Gene Ontology results suggested that the senescence-associated lncRNAs targeted mRNAs involving in many biological processes, including transcription, hormone response, oxidation-reduction process and substance metabolism. Additionally, 43 senescence-associated lncRNAs were predicted to target 111 co-expressed transcription factors. Interestingly, 8 down-expressed lncRNAs and 29 up-expressed lncRNAs were found to separately target 12 and 20 well-studied senescence-associated genes (SAGs). Furthermore, analysis on the competing endogenous RNA (CeRNA) network revealed that 6 down-expressed lncRNAs possibly regulated 51 co-expressed mRNAs through 15 miRNAs, and 14 up-expressed lncRNAs possibly regulated 117 co-expressed mRNAs through 21 miRNAs. Importantly, by expression validation, a conserved miR164-NAC regulatory pathway was found to be possibly involved in leaf senescence, where lncRNA MSTRG.62092.1 may serve as a ceRNA binding with miR164a and miR164e to regulate three transcription factors. And two key lncRNAs MSTRG.31014.21 and MSTRG.31014.36 also could regulate the abscisic-acid biosynthetic gene BGIOSGA025169 (OsNCED4) and BGIOSGA016313 (NAC family) through osa-miR5809. The possible regulation networks of lncRNAs involving in leaf senescence were discussed, and several candidate lncRNAs were recommended for prior transgenic analysis. These findings will extend the understanding on the regulatory roles of lncRNAs in leaf senescence, and lay a foundation for functional research on candidate lncRNAs.

Identification and verification of genes related to pollen development and male sterility induced by high temperature in the thermo-sensitive genic male sterile wheat line

Bioinformatic analysis identified the function of genes regulating wheat fertility. Barley stripe mosaic virus-induced gene silencing verified that the genes TaMut11 and TaSF3 are involved in pollen development and related to fertility conversion. Environment-sensitive genic male sterility is of vital importance to hybrid vigor in crop production and breeding. Therefore, it is meaningful to study the function of the genes related to pollen development and male sterility, which is still not fully understand currently. In this study, YanZhan 4110S, a new thermo-sensitive genic male sterility wheat line, and its near-isogenic line YanZhan 4110 were analyzed. Through comparative transcriptome basic bioinformatics and weighted gene co-expression network to further identify some hub genes, the genes TaMut11 and TaSF3 associated with pollen development and male sterility induced by high-temperature were identified in YanZhan 4110S. Further verification through barley stripe mosaic virus-induced gene silencing elucidated that the silencing of TaMut11 and TaSF3 caused pollen abortion, finally resulting in the declination of fertility. These findings provided data on the abortive mechanism in environment-sensitive genic male sterility wheat.

Identification and analysis of spinal cord injury subtypes using weighted gene co-expression network analysis

Background

Spinal cord injury (SCI) has an immediate and devastating impact on the control over various movements and sensations. However, no effective therapies for SCI currently exist.

Methods

To identify and analyze SCI subtypes, we obtained the expression profile data of the 1,057 genes (889 intersection genes) in GSE45550 using weighted gene co-expression network analysis (WGCNA), and 14 co-expression gene modules were identified. Next, we filtered out the network degree top 10 (degree >80) genes, considered the final key SCI genes. A multifactor regulatory network (105 interaction pairs), consisting of messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs), and transcription factors (TFs) was constructed. This network was involved in the co-expression of key genes. We selected the top 10 regulatory factors (degree >4) as core regulators in the multifactor regulatory network.

Results

The results of functional enrichment analysis of the target gene expressing the core regulatory factor [1,059] showed that these target genes were enriched in pathways for human cytomegalovirus infection, chronic myeloid leukemia, and pancreatic cancer. Further, we used the key genes in the co-expression network to categorize the SCI samples in GSE45550. The expression levels of the top 6 genes (CCNB2, CCNB1, CKS2, COL5A1, KIF20A, and RACGAP1) may act as potential marker genes for different SCI subtypes. On the basis of these different subtypes, 8 SCI core gene CDK1-associated drugs were also found to provide potential therapeutic options for SCI.

Conclusions

These results may provide a novel therapeutic strategy for the treatment of SCI.

Systematic identification and characterization of circular RNAs involved in flag leaf senescence of rice

Circular RNAs (circRNAs) identification, expression profiles, and construction of circRNA-parental gene relationships and circRNA-miRNA-mRNA ceRNA networks indicate that circRNAs are involved in flag leaf senescence of rice. Circular RNAs (circRNAs) are a class of 3'-5' head-to-tail covalently closed non-coding RNAs which have been proved to play important roles in various biological processes. However, no systematic identification of circRNAs associated with leaf senescence in rice has been studied. In this study, a genome-wide high-throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. Here, a total of 6612 circRNAs were identified, among which, 113 circRNAs were differentially expressed (DE) during the leaf senescence process. Moreover, 4601 (69.59%) circRNAs were derived from the exons or introns of their parental genes, while 2110 (71%) of the parental genes produced only one circRNA. The sequence alignment analysis showed that hundreds of rice circRNAs were conserved among different plant species. Gene Ontology (GO) enrichment analysis revealed that parental genes of DE circRNAs were enriched in many biological processes closely related to leaf senescence. Through weighted gene co-expression network analysis (WGCNA), six continuously down-expressed circRNAs, 18 continuously up-expressed circRNAs and 15 turn-point high-expressed circRNAs were considered to be highly associated with leaf senescence. Additionally, a total of 17 senescence-associated circRNAs were predicted to have parental genes, in which, regulations of three circRNAs to their parental genes were validated by qRT-PCR. The competing endogenous RNA (ceRNA) networks were also constructed. And a total of 11 senescence-associated circRNAs were predicted to act as miRNA sponges to regulate mRNAs, in which, regulation of two circRNAs to eight mRNAs was validated by qRT-PCR. It is discussed that senescence-associated circRNAs were involved in flag leaf senescence probably through mediating their parental genes and ceRNA networks, to participate in several well-studied senescence-associated processes, mainly including the processes of transcription, translation, and posttranslational modification (especially protein glycosylation), oxidation-reduction process, involvement of senescence-associated genes, hormone signaling pathway, proteolysis, and DNA damage repair. This study not only showed the systematic identification of circRNAs involved in leaf senescence of rice, but also laid a foundation for functional research on candidate circRNAs.

Upregulation of STAT1-CCL5 axis is a biomarker of colon cancer and promotes the proliferation of colon cancer cells

Background

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in men and women globally. Investigating genetic ground differences between normal and CRC tissues would be significant for identifying some key oncogenic pathways and developing anti-cancer agents.

Methods

Weighted gene co-expression network analysis (WGCNA) method was used to screen out core pathways related to the clinical traits of CRC patients. Then, multiple databases were utilized to further verify the hub genes obtained from data mining. Finally, to explore the role of hub genes in CRC, cell counting and EdU assays were performed.

Results

The results of the WGCNA analysis showed that a module (turquoise module) was highly related with CRC differentiation grade (R =0.53, P<0.0001). Enrichment analysis indicated that genes of the turquoise module were remarkably enriched in multiple inflammatory processes and pathways. Among all hub genes of the turquoise module, the mRNA levels of STAT1 and CCL5 were significantly higher in CRC than in normal colon tissues. STAT1 expression was highly positively correlated with the level of CCL5. The results of the cell counting, EdU, CCK-8, and CFSE staining assays showed that interfering with STAT1 and CCL5 could inhibit the proliferation of CRC cells.

Conclusions

Our study indicated that the STAT1-CCL5 axis is an important modulator in the development of CRC through promoting cell proliferation. Moreover, the levels of STAT1 and CCL5 might be valuable biomarkers for CRC screening.

Glycerophosphodiester phosphodiesterase 1 (GDE1) acts as a potential tumor suppressor and is a novel therapeutic target for non-mucin-producing colon adenocarcinoma

Colon adenocarcinoma (COAD) represents a major public health issue due to its high incidence and mortality. As different histological subtypes of COAD are related to various survival outcomes and different therapies, finding specific targets and treatments for different subtypes is one of the major demands of individual disease therapy. Interestingly, as these different subtypes show distinct metabolic profiles, it may be possible to find specific targets related to histological typing by targeting COAD metabolism. In this study, the differential expression patterns of metabolism-related genes between COAD (n = 289) and adjacent normal tissue (n = 41) were analyzed by one-way ANOVA. We then used weighted gene co-expression network analysis (WGCNA) to further identify metabolism-related gene connections. To determine the critical genes related to COAD metabolism, we obtained 2,114 significantly differentially expressed genes (DEGs) and 12 modules. Among them, we found the hub module to be significantly associated with histological typing, including non-mucin-producing colon adenocarcinoma and mucin-producing colon adenocarcinoma. Combining survival analysis, we identified glycerophosphodiester phosphodiesterase 1 (GDE1) as the most significant gene associated with histological typing and prognosis. This gene displayed significantly lower expression in COAD compared with normal tissues and was significantly correlated with the prognosis of non-mucin-producing colon adenocarcinoma (p = 0.0017). Taken together, our study showed that GDE1 exhibits considerable potential as a novel therapeutic target for non-mucin-producing colon adenocarcinoma.

Identification and validation of key modules and hub genes associated with the pathological stage of oral squamous cell carcinoma by weighted gene co-expression network analysis

Background

Oral squamous cell carcinoma (OSCC) is a major lethal malignant cancer of the head and neck region, yet its molecular mechanisms of tumourigenesis are still unclear.

Patients and methods

We performed weighted gene co-expression network analysis (WGCNA) on RNA-sequencing data with clinical information obtained from The Cancer Genome Atlas (TCGA) database. The relationship between co-expression modules and clinical traits was investigated by Pearson correlation analysis. Furthermore, the prognostic value and expression level of the hub genes of these modules were validated based on data from the TCGA database and other independent datasets from the Gene Expression Omnibus (GEO) database and the Human Protein Atlas database. The significant modules and hub genes were also assessed by functional analysis and gene set enrichment analysis (GSEA).

Results

We found that the turquoise module was strongly correlated with pathologic T stage and significantly enriched in critical functions and pathways related to tumourigenesis. PPP1R12B, CFD, CRYAB, FAM189A2 and ANGPTL1 were identified and statistically validated as hub genes in the turquoise module and were closely implicated in the prognosis of OSCC. GSEA indicated that five hub genes were significantly involved in many well-known cancer-related biological functions and signaling pathways.

Conclusion

In brief, we systematically discovered a co-expressed turquoise module and five hub genes associated with the pathologic T stage for the first time, which provided further insight that WGCNA may reveal the molecular regulatory mechanism involved in the carcinogenesis and progression of OSCC. In addition, the five hub genes may be considered candidate prognostic biomarkers and potential therapeutic targets for the precise early diagnosis, clinical treatment and prognosis of OSCC in the future.

Transcriptomics analysis revealing candidate genes and networks for sex differentiation of yesso scallop (Patinopecten yessoensis)

Background

The Yesso scallop, Patinopecten (Mizuhopecten) yessoensis, is a commercially important bivalve in the coastal countries of Northeast Asia. It has complex modes of sex differentiation, but knowledge of the mechanisms underlying this sex determination and differentiation is limited.

Results

In this study, the gonad tissues from females and males at three developmental stages were used to investigate candidate genes and networks for sex differentiation via RNA-Req. A total of 901,980,606 high quality clean reads were obtained from 18 libraries, of which 417 expressed male-specific genes and 754 expressed female-specific genes. Totally, 10,074 genes differentially expressed in females and males were identified. Weighted gene co-expression network analysis (WGCNA) revealed that turquoise and green gene modules were significantly positively correlated with male gonads, while coral1 and black modules were significantly associated with female gonads. The most important gene for sex determination and differentiation was Pydmrt 1, which was the only gene discovered that determined the male sex phenotype during early gonadal differentiation. Enrichment analyses of GO terms and KEGG pathways revealed that genes involved in metabolism, genetic and environmental information processes or pathways are sex-biased. Forty-nine genes in the five modules involved in sex differentiation or determination were identified and selected to construct a gene co-expression network and a hypothesized sex differentiation pathway.

Conclusions

The current study focused on screening genes of sex differentiation in Yesso scallop, highlighting the potential regulatory mechanisms of gonadal development in P. yessoensis. Our data suggested that WCGNA can facilitate identification of key genes for sex differentiation and determination. Using this method, a hypothesized P. yessoensis sex determination and differentiation pathway was constructed. In this pathway, Pydmrt 1 may have a leading function.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-6021-6) contains supplementary material, which is available to authorized users.

A novel 4-gene signature for overall survival prediction in lung adenocarcinoma patients with lymph node metastasis

Background

Lung adenocarcinoma (LUAD) patients experiencing lymph node metastasis (LNM) always exhibit poor clinical outcomes. A biomarker or gene signature that could predict survival in these patients would have a substantial clinical impact, allowing for earlier detection of mortality risk and for individualized therapy.

Methods

With the aim to identify a novel mRNA signature associated with overall survival, we analysed LUAD patients with LNM extracted from The Cancer Genome Atlas (TCGA). LASSO Cox regression was applied to build the prediction model. An external cohort was applied to validate the prediction model.

Results

We identified a 4-gene signature that could effectively stratify a high-risk subset of these patients, and time-dependent receiver operating characteristic (tROC) analysis indicated that the signature had a powerful predictive ability. Gene Set Enrichment Analysis (GSEA) showed that the high-risk subset was mainly associated with important cancer-related hallmarks. Moreover, a predictive nomogram was established based on the signature integrated with clinicopathological features. Lastly, the signature was validated by an external cohort from Gene Expression Omnibus (GEO).

Conclusion

In summary, we developed a robust mRNA signature as an independent factor to effectively classify LUAD patients with LNM into low- and high-risk groups, which might provide a basis for personalized treatments for these patients.

Identifying gene modules of thyroid cancer associated with pathological stage by weighted gene co-expression network analysis

Thyroid cancer is the most common type of endocrine tumor. The TNM classification remains a standard for treatment determination and predicting prognosis in thyroid cancer. The genes modules associated with the progression of papillary thyroid carcinoma (PTC) were not clear. We applied a weighted gene co-expression network analysis (WGCNA) and differential expression analysis to systematically identified co-expressed gene modules and hub genes associated with PTC progression based on The Cancer Genome Atlas (TCGA) PTC transcriptome sequencing data. An independent validation cohort, GSE27155, was used to evaluate the preservation of gene modules. We identified two co-expressed genes modules associated with progression of PTC. Enrichment analysis indicated that the two modules were enriched in angiogenesis and extracellular matrix organization. DCN, COL1A1, COL1A2, COL5A2 and COL3A1 were hub genes in the co-expressed network. We systematically identified co-expressed gene modules and hub genes associated with PTC progression for the first time, which provided insights into the mechanisms underlying PTC progression and some potential targets for the treatment of PTC.

Bladder cancer stage-associated hub genes revealed by WGCNA co-expression network analysis

Background

Bladder cancer was a malignant disease in patients, our research aimed at discovering the possible biomarkers for the diseases.

Results

The gene chip GSE31684, including 93samples, was downloaded from the GEO datasets and co-expression network was constructed by the data. Molecular complex detection(MCODE) was used to identify hub genes. The most significant cluster including 16 genes: CDH11, COL3A1, COL6A3, COL5A1, AEBP1, COL1A2, NTM, COL11A1, THBS2, COL8A1, COL1A1, BGN, MMP2, PXDN, THY1, and TGFB1I1 was identified. After annotated by BiNGO, they were suggested associated with collagen fibril organization and blood vessel development. In addition, the Kaplan Meier curves were obtained by UALCAN. The high expression of THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1, and TGFB1I1 indicated poor prognosis of the patients(P < 0.05). Finally, we examined genes’ expression between low and high tumor stage by the Wilcoxon test(P < 0.05), TGFB1I1 was excluded.

Conclusion

THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1 associated with the tumor stage as well as tumor patients’ prognosis. COL5A1, COL8A1(P < 0.01) may serve as therapeutic targets for the disease.

Identification of biomarkers of chromophobe renal cell carcinoma by weighted gene co-expression network analysis

Background

Chromophobe renal cell carcinoma (ChRCC) is the second common subtype of non-clear cell renal cell carcinoma (nccRCC), which accounting for 4–5% of renal cell carcinoma (RCC). However, there is no effective bio-marker to predict clinical outcomes of this malignant disease. Bioinformatic methods may provide a feasible potential to solve this problem.

Methods

In this study, differentially expressed genes (DEGs) of ChRCC samples on The Cancer Genome Atlas database were filtered out to construct co-expression modules by weighted gene co-expression network analysis and the key module were identified by calculating module-trait correlations. Functional analysis was performed on the key module and candidate hub genes were screened out by co-expression and MCODE analysis. Afterwards, real hub genes were filter out in an independent dataset GSE15641 and validated by survival analysis.

Results

Overall 2215 DEGs were screened out to construct eight co-expression modules. Brown module was identified as the key module for the highest correlations with pathologic stage, neoplasm status and survival status. 29 candidate hub genes were identified. GO and KEGG analysis demonstrated most candidate genes were enriched in mitotic cell cycle. Three real hub genes (SKA1, ERCC6L, GTSE-1) were selected out after mapping candidate genes to GSE15641 and two of them (SKA1, ERCC6L) were significantly related to overall survivals of ChRCC patients.

Conclusions

In summary, our findings identified molecular markers correlated with progression and prognosis of ChRCC, which might provide new implications for improving risk evaluation, therapeutic intervention, and prognosis prediction in ChRCC patients.

Electronic supplementary material

The online version of this article (10.1186/s12935-018-0703-z) contains supplementary material, which is available to authorized users.

Integration of summary data from GWAS and eQTL studies identified novel causal BMD genes with functional predictions

PURPOSE

Osteoporosis is a common global health problem characterized by low bone mineral density (BMD) and increased risk of fracture. Genome-wide association studies (GWAS) have identified >100 genetic loci associated with BMD. However, the functional genes responsible for most associations remain largely unknown. We conducted an innovative summary statistic data-based Mendelian randomization (SMR) analysis to identify novel causal genes associated with BMD and explored their potential functional significance.

METHODS

After quality control of the largest GWAS meta-analysis data of BMD and the largest expression quantitative trait loci (eQTL) meta-analysis data from peripheral blood samples, 5967 genes were tested using the SMR method. Another eQTL data was used to verify the results. Next we performed a fine-mapping association analysis to investigate the functional SNP in the identified loci. Weighted gene co-expression network analysis (WGCNA) was used to explore functional relationships for the identified novel genes with known putative osteoporosis genes. Further, we assessed functions of the identified genes through in vitro cellular study or previous functional studies.

RESULTS

We identified two potentially causal genes (ASB16-AS1 and SYN2) associated with BMD. SYN2 was a novel osteoporosis candidate gene and ASB16-AS1 locus was known to be associated with BMD but was not the nearest gene to the top GWAS SNP. Fine-mapping association analysis showed that rs184478 and rs795000 was predicted to be possible causal SNPs in ASB16-AS1 and SYN2, respectively. ASB16-AS1 co-expressed with several known putative osteoporosis risk genes. In vitro cellular study showed that over-expressed ASB16-AS1 increased the expression of osteoblastogenesis related genes (BMP2 and ALPL), indicating its functional significance.

CONCLUSION

Our findings support that ASB16-AS1 and SYN2 may represent two novel functional genes underlying BMD variation. The findings provide a basis for further functional mechanistic studies.