Detection of new candidate genes controlling seed weight by integrating gene coexpression analysis and QTL mapping in Brassica napus L.

Seed weight is a component of seed yield in rapeseed(Brassica napus L.).Although quantitative trait loci(QTL)for seed weight have been reported in rapeseed,only a few causal quantitative trait genes(QTGs)have been identified,resulting in a limitation in understanding of seed weight regulation.We constructed a gene coexpression network at the early seed developmental stage using transcripts of 20,408 genes in QTL intervals and 1017 rapeseed homologs of known genes from other species.Among the 10 modules in this gene coexpression network,modules 1 and 2 were core modules and contained genes involved in source–flow–sink processes such as synthesis and transportation of fatty acid and protein,and photosynthesis.A hub gene SERINE CARBOXYPEPTIDASE-LIKE 19(SCPL19)was identified by candidate gene association analysis in rapeseed and functionally investigated using Arabidopsis T-DNA mutant and overexpression lines.Our study demonstrates the power of gene coexpression analysis to prioritize candidate genes from large candidate QTG sets and enhances the understanding of molecular mechanism for seed weight at the early developmental stage in rapeseed.

Salivary metabolites are promising noninvasive biomarkers of druginduced liver injury

BACKGROUND Drug-induced liver injury(DILI)is one of the most common adverse events of medication use,and its incidence is increasing.However,early detection of DILI is a crucial challenge due to a lack of biomarkers and noninvasive tests.AIM To identify salivary metabolic biomarkers of DILI for the future development of noninvasive diagnostic tools.METHODS Saliva samples from 31 DILI patients and 35 healthy controls(HCs)were subjected to untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with tandem mass spectrometry.Subsequent analyses,including partial least squares-discriminant analysis modeling,t tests and weighted metabolite coexpression network analysis(WMCNA),were conducted to identify key differentially expressed metabolites(DEMs)and metabolite sets.Furthermore we utilized least absolute shrinkage and selection operato and random fores analyses for biomarker prediction.The use of each metabolite and metabolite set to detect DILI was evaluated with area under the receiver operating characteristic curves.RESULTS We found 247 differentially expressed salivary metabolites between the DILI group and the HC group.Using WMCNA,we identified a set of 8 DEMs closely related to liver injury for further prediction testing.Interestingly,the distinct separation of DILI patients and HCs was achieved with five metabolites,namely,12-hydroxydodecanoic acid,3-hydroxydecanoic acid,tetradecanedioic acid,hypoxanthine,and inosine(area under the curve:0.733-1).CONCLUSION Salivary metabolomics revealed previously unreported metabolic alterations and diagnostic biomarkers in the saliva of DILI patients.Our study may provide a potentially feasible and noninvasive diagnostic method for DILI,but further validation is needed.

Identification of immune cell-related prognostic genes characterized by a distinct microenvironment in hepatocellular carcinoma

BACKGROUND The development and progression of hepatocellular carcinoma(HCC)have been reported to be associated with immune-related genes and the tumor microenvir-onment.Nevertheless,there are not enough prognostic biomarkers and models available for clinical use.Based on seven prognostic genes,this study calculated overall survival in patients with HCC using a prognostic survival model and revealed the immune status of the tumor microenvironment(TME).AIM To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC.METHODS We obtained clinical information and gene expression data of HCC from The Cancer Genome Atlas(TCGA)and International Cancer Genome Consortium(ICGC)datasets.TCGA and ICGC datasets were used for screening prognostic genes along with developing and validating a seven-gene prognostic survival model by weighted gene coexpression network analysis and least absolute shrinkage and selection operator regression with Cox regression.The relative analysis of tumor mutation burden(TMB),TME cell infiltration,immune check-points,immune therapy,and functional pathways was also performed based on prognostic genes.RESULTS Seven prognostic genes were identified for signature construction.Survival receiver operating characteristic curve analysis showed the good performance of survival prediction.TMB could be regarded as an independent factor in HCC survival prediction.There was a significant difference in stromal score,immune score,and estimate score between the high-risk and low-risk groups stratified based on the risk score derived from the seven-gene prognostic model.Several immune checkpoints,including VTCN1 and TNFSF9,were found to be associated with the seven prognostic genes and risk score.Different combinations of checkpoint blockade targeting inhibitory CTLA4 and PD1 receptors and potential chemotherapy drugs hold great promise for specific HCC therapies.Potential pathways,such as cell cycle regulation and metabolism of some amino acids,were also identified and analyzed.CONCLUSION The novel seven-gene(CYTH3,ENG,HTRA3,PDZD4,SAMD14,PGF,and PLN)prognostic model showed high predictive efficiency.The TMB analysis based on the seven genes could depict the basic profile of the immune response in HCC,which might be worthy of clinical application.

Coexpression of vascular endothelial growth factor and its receptor KDR on gastric adenocarcinoma MGC803 cell line and stimulation of exogenous VEGF_(165) to MGC803 cells

Vascular endothelial growth factor (VEGF), also known as vascular permeability factor (VPF), is an angiogenic factor playing an important role in tumor growth. VEGF/VPF interacts with endothelial cells by way of two high-affinity receptor tyrosine kinases: flt-1 and KDR. The vast majority of published studies have described expression of the VPF/VEGF receptors specifically in endothelial cells. To elucidate the further function of VEGF in solid tumor development, the coex-pression of VEGF and KDR in gastric adenocarcinoma MGC803 cell lines was shown by reverse transcription polymerase chain reaction (RT-PCR). The MGC803 tumor cells could also be strongly immunostained for KDR by immunocytochemistry. It was further demonstrated that exogenous VEGF-165 can stimulate the MGC803 cell growth in both dose-dependent and time-dependent manners by 3H-thymidine incorporation. Furthermore, anti-VEGF165 monoclonal antibody and anti-KDR monoclonal antibody could dose-dependently block the VEGF166-induced cell

Transcriptional modules related to hepatocellular carcinoma survival： coexpression network analysis

We performed weighted gene coexpression network analysis （WGCNA） to gain insights into the molecular aspects of hepatocellular carcinoma （HCC）. Raw microarray datasets （including 488 samples） were downloaded from the Gene Expression Omnibus （GEO） website. Data were normalized using the RMA algorithm. We utilized the WGCNA to identify the coexpressed genes （modules） after non-specific filtering. Correlation and survival analyses were conducted using the modules, and gene ontology （GO） enrichment was applied to explore the possible mechanisms. Eight distinct modules were identified by the WGCNA. Pink and red modules were associated with liver function, whereas turquoise and black modules were inversely correlated with tumor staging. Poor outcomes were found in the low expression group in the turquoise module and in the high expression group in the red module. In addition, GO enrichment analysis suggested that inflammation, immune, virus-related, and interferon-mediated pathways were enriched in the turquoise module. Several potential biomarkers, such as cyclin-dependent kinase 1 （CDK1）, topoisomerase 2α （TOP2A）, and serpin peptidase inhibitor clade C （antithrombin） member 1 （SERPINC1）, were also identified. In conclusion, gene signatures identified from the genome-based assays could contribute to HCC stratification. WGCNA was able to identify significant groups of genes associated with cancer prognosis.

Coexpression of TLR9 and VEGF-C is associated with lymphatic metastasis in prostate cancer

Prostate cancer(PCa)is one of the most frequent cancers in men,and its biomolecular targets have been extensively studied.This study aimed to analyze the expression of toll-like receptor 9(TLR9)and vascular endothelial growth factor C(VEGF-C)and the clinical value of the coexpression of TLR9 and VEGF-C in PCa.We retrospectively evaluated 55 patients with clinically localized,intermediate-risk,or high-risk PCa who underwent laparoscopic radical prostatectomy(LRP)and extended pelvic lymph node dissection(ePLND)without neoadjuvant hormonal therapy at a single institution from June 2013 to December 2016.In all 55 patients,the median number of lymph nodes(LNs)resected was 23(range:18-31),and a total of 1269 LNs were removed,of which 78 LNs were positive.Seventeen patients had positive LNs,with a positive rate of 30.9%.In addition,the immunohistochemical results in the above patients revealed that high TLR9 expression was correlated with higher Gleason score(GS)(P=0.049),increased LN metastasis(P=0.004),and more perineural invasion(PNI)(P=0.033).Moreover,VEGF-C expression was associated with GS(P=0.040),pathological stage(pT stage)(P=0.022),LN metastasis(P=0.003),and PNI(P=0.001).Furthermore,a significant positive correlation between TLR9 and VEGF-C was found(P<0.001),and the TLR9/VEGF-C phenotype was associated with LN metastasis(P=0.047).Collectively,we propose that TLR9 stimulation may promote LN metastasis in PCa cells through the upregulation of VEGF-C expression,thereby affecting the prognosis of PCa patients.Therefore,these markers may serve as valuable targets for the treatment of PCa.

Transcriptome-based analysis of key genes and pathways affecting the linoleic acid content in chickens

Linoleic acid is an essential polyunsaturated fatty acid that cannot be synthesized by humans or animals themselves and can only be obtained externally.The amount of linoleic acid present has an impact on the quality and flavour of meat and indirectly affects consumer preference.However,the molecular mechanisms influencing the deposition of linoleic acid in organisms are not clear.As the molecular mechanisms of linoleic acid deposition are not well understood,to investigate the main effector genes affecting the linoleic acid content,this study aimed to screen for hub genes in slow-type yellow-feathered chickens by transcriptome sequencing(RNA-Seq)and weighted gene coexpression network analysis(WGCNA).We screened for candidate genes associated with the linoleic acid content in slow-type yellow-feathered broilers.A total of 399 Tiannong partridge chickens were slaughtered at 126 days of age,fatty acid levels were measured in pectoral muscle,and pectoral muscle tissue was collected for transcriptome sequencing.Transcriptome sequencing results were combined with phenotypes for WGCNA to screen for candidate genes.KEGG enrichment analysis was also performed on the genes that were significantly enriched in the modules with the highest correlation.A total of 13310 genes were identified after quality control of transcriptomic data from 399 pectoral muscle tissues.WGCNA was performed,and a total of 26 modules were obtained,eight of which were highly correlated with the linoleic acid content.Four key genes,namely,MDH2,ATP5B,RPL7A and PDGFRA,were screened according to the criteria|GS|>0.2 and|MM|>0.8.The functional enrichment results showed that the genes within the target modules were mainly enriched in metabolic pathways.In this study,a large-sample-size transcriptome analysis revealed that metabolic pathways play an important role in the regulation of the linoleic acid content in Tiannong partridge chickens,and MDH2,ATP5B,RPL7A and PDGFRA were screened as important candidate genes affecting the linoleic acid content.The results of this study provide a theoretical basis for selecting molecular markers and comprehensively understanding the molecular mechanism affecting the linoleic acid content in muscle,providing an important reference for the breeding of slow-type yellowfeathered broiler chickens.

Establishment of a prognostic model related to tregs and natural killer cells infiltration in bladder cancer

BACKGROUND Regulatory T cells(Tregs)and natural killer(NK)cells play an essential role in the development of bladder urothelial carcinoma(BUC).AIM To construct a prognosis-related model to judge the prognosis of patients with bladder cancer,meanwhile,predict the sensitivity of patients to chemotherapy and immunotherapy.METHODS Bladder cancer information data was obtained from The Cancer Genome Atlas and GSE32894.The CIBERSORT was used to calculate the immune score of each sample.Weighted gene co-expression network analysis was used to find genes that will have the same or similar expression patterns.Subsequently,multivariate cox regression and lasso regression was used to further screen prognosis-related genes.The prrophetic package was used to predict phenotype from gene expression data,drug sensitivity of external cell line and predict clinical data.RESULTS The stage and risk scores are independent prognostic factors in patients with BUC.Mutations in FGFR3 lead to an increase in Tregs percolation and affect the prognosis of the tumor,and additionally,EMP1,TCHH and CNTNAP3B in the model are mainly positively correlated with the expression of immune checkpoints,while CMTM8,SORT1 and IQSEC1 are negatively correlated with immune checkpoints and the high-risk group had higher sensitivity to chemotherapy drugs.CONCLUSION Prognosis-related models of bladder tumor patients,based on Treg and NK cell percolation in tumor tissue.In addition to judging the prognosis of patients with bladder cancer,it can also predict the sensitivity of patients to chemotherapy and immunotherapy.At the same time,patients were divided into high and low risk groups based on this model,and differences in genetic mutations were found between the high and low risk groups.

Long noncoding RNA NALT1-induced gastric cancer invasion and metastasis via NOTCH signaling pathway

BACKGROUNDLong noncoding RNAs (lncRNAs) are aberrant and play critical roles in gastriccancer (GC) progression and metastasis. Searching for coexpressed lncRNAclusters or representative biomarkers related to malignant phenotypes of GC mayhelp to elucidate the mechanism of tumor development and predict the prognosisof GC.AIMTo investigate the prognostic value of NOTCH1 associated with lncRNA in T cellacute lymphoblastic leukemia 1 (NALT1) in GC and the mechanism of itsinvolvement in GC invasion and metastasis.METHODSRNA sequencing and corresponding clinical data were downloaded from TheCancer Genome Atlas database. The significance module was studied byweighted gene coexpression network analysis. A total of 336 clinical sampleswere included in the study. Gene silencing, reverse transcription polymerasechain reaction, western blotting, scrape motility assay, and Transwell migrationassay were used to assess the function of hub-lncRNAs.RESULTSAt the transcriptome level, 3339 differentially expressed lncRNAs were obtained.weighted gene coexpression network analysis was used to obtain 15 lncRNAclusters and observe their coexpression. Pearson’s correlation showed that blue module was correlated with tumor grade and survival. NALT1 was the hublncRNAof blue module and was an independent risk factor for GC prognosis.NALT1 was overexpressed in GC and its expression was closely related toinvasion and metastasis. The mechanism may involve NALT1 regulation ofNOTCH1, which is associated with lncRNA in T cell acute lymphoblasticleukemia, through cis regulation, thereby affecting the expression of the NOTCHsignaling pathway.CONCLUSIONNALT1 is overexpressed and promotes invasion and metastasis of GC. Themechanism may be related to regulation of NOTCH1 by NALT1 and its effect onNOTCH signaling pathway expression.

Identification of key genes controlling cancer stem cell characteristics in gastric cancer

BACKGROUND Self-renewal of gastric cancer stem cells(GCSCs)is considered to be the underlying cause of the metastasis,drug resistance,and recurrence of gastric cancer(GC).AIM To characterize the expression of stem cell-related genes in GC.METHODS RNA sequencing results and clinical data for gastric adenoma and adenocarcinoma samples were obtained from The Cancer Genome Atlas database,and the results of the GC mRNA expression-based stemness index(mRNAsi)were analyzed.Weighted gene coexpression network analysis was then used to find modules of interest and their key genes.Survival analysis of key genes was performed using the online tool Kaplan-Meier Plotter,and the online database Oncomine was used to assess the expression of key genes in GC.RESULTS mRNAsi was significantly upregulated in GC tissues compared to normal gastric tissues(P<0.0001).A total of 16 modules were obtained from the gene coexpression network;the brown module was most positively correlated with mRNAsi.Sixteen key genes(BUB1,BUB1 B,NCAPH,KIF14,RACGAP1,RAD54 L,TPX2,KIF15,KIF18 B,CENPF,TTK,KIF4 A,SGOL2,PLK4,XRCC2,a n d C1 orf112)were identified in the brown module.The functional and pathway enrichment analyses showed that the key genes were significantly enriched in the spindle cellular component,the sister chromatid segregation biological process,the motor activity molecular function,and the cell cycle and homologous recombination pathways.Survival analysis and Oncomine analysis revealed that the prognosis of patients with GC and the expression of three genes(RAD54 L,TPX2,and XRCC2)were consistently related.CONCLUSION Sixteen key genes are primarily associated with stem cell self-renewal and cell proliferation characteristics.RAD54 L,TPX2,and XRCC2 are the most likely therapeutic targets for inhibiting the stemness characteristics of GC cells.

Genetic architecture of maize yield traits dissected by QTL mapping and GWAS in maize

The study of yield traits can reveal the genetic architecture of grain yield for improving maize production.In this study, an association panel comprising 362 inbred lines and a recombinant inbred line population derived from X178 × 9782 were used to identify candidate genes for nine yield traits. High-priority overlap(HPO) genes, which are genes prioritized in a genome-wide association study(GWAS), were investigated using coexpression networks. The GWAS identified 51 environmentally stable SNPs in two environments and 36 pleiotropic SNPs, including three SNPs with both attributes. Seven hotspots containing 41 trait-associated SNPs were identified on six chromosomes by permutation. Pyramiding of superior alleles showed a highly positive effect on all traits, and the phenotypic values of ear diameter and ear weight consistently corresponded with the number of superior alleles in tropical and temperate germplasm. A total of 61 HPO genes were detected after trait-associated SNPs were combined with the coexpression networks. Linkage mapping identified 16 environmentally stable and 16 pleiotropic QTL.Seven SNPs that were located in QTL intervals were assigned as consensus SNPs for the yield traits.Among the candidate genes predicted by our study, some genes were confirmed to function in seed development. The gene Zm00001 d016656 encoding a serine/threonine protein kinase was associated with five different traits across multiple environments. Some genes were uniquely expressed in specific tissues and at certain stages of seed development. These findings will provide genetic information and resources for molecular breeding of maize grain yield.

Identification of the Potential Function of circRNA in Hypertrophic Cardiomyopathy Based on Mutual RNA-RNA and RNA-RBP Relationships Shown by Microarray Data

The pathogenesis of hypertrophic cardiomyopathy(HCM)is very complicated,particularly regarding the role of circular RNA(circRNA).This research pays special attention to the relationships of the circRNA-mediated network,including RNA-RNA relationships and RNA-RNA binding protein(RNA-RBP)relationships.We use the parameter framework technology proposed in this paper to screen differentially expressed circRNA,messenger RNA(mRNA),and microRNA(miRNA)from the expression profile of samples related to HCM.And 31 pairs of circRNA and mRNA relationship pairs were extracted,combined with the miRNA targeting database;145 miRNA-mRNA relationship pairs were extracted;268 circRNA-mRNA-miRNA triads were established through the common mRNA in the 2 types of relationship pairs.Thus,268 circRNA-miRNA regulatory relationships were deduced and 30 circRNARBP relationship pairs were analyzed at the protein level.On this basis,a circRNA-mediated regulatory network corresponding to the two levels of RNA-RNA and RNA-RBP was established.And then the roles of circRNA in HCM were analyzed through circRNA-mRNA,circRNA-miRNA,and circRNA-RBP,and the possible role in disease development mas inferred.

Determining the transcriptional regulation pattern of PgTIP1 in transgenic Arabidopsis thaliana by constructing gene

The seed size, seed mass, and growth rate of transgenic Arabidopsis plants containing PgTIP1, a ginseng tonoplast aquaporin gene, are significantly higher than those of wild-type Arabidopsis plants. Whole genome expression and bioinformatics analysis, including analysis of co-expression networks and transcription factors (Tfscan), were used to determine the key genes that are activated after the expression of PgTIP1 and the transcription factors that play important roles in the regulation of the genes controlling growth of Arabidopsis thaliana seeds by using transgenic Arabidopsis plants containing PgTIP1. Differential gene analysis showed that transformation of exogenous PgTIP1 to Arabidopsis induced endogenous gene expression changes. Analysis of gene co-expression networks revealed 2 genes, PIP1 (plasma membrane aquaporin 1 gene) and RD26 (responsive to desiccation 26 gene;a NAC transcription factor), that were localized in the core of the networks. Analysis of the transcriptional regulation network of transgenic Arabidopsis plants containing PgTIP1 showed that PIP1 and RD26 were regulated via DNA binding with a finger domain on transcription factor 2 (Dof2). In this study, we demonstrated that Dof2 induces up-regulation of PIP1 and RD26 after transformation with PgTIP1. The results of this study provide a new means for conducting research into and controlling growth of Arabidopsis thaliana seeds.

Killing effect of coexpressing cytosine deaminase and thymidine kinase on rat vascular smooth muscle cells

Background Vascular smooth muscle cell (VSMC) proliferation following arterial injury plays a critical role in a variety of vascular proliferative disorders, such as atherosclerosis and restenosis after balloon angioplasty. Herpes simplex virus-thymidine kinase (HSV-TK)/ganciclovir (GCV) and E.coli cytosine deaminase (CD)/5-fluorocytosine (5-Fc) suicide gene systems have been successfully employed in cardiovascular gene therapy, respectively. We reasoned that coexpression of both HSV-TK with CD suicide genes would lead to increased cell killing. To test this imagine, the adenoviral vectors expressing TK and/or CD genes were developed and tested on vascular smooth muscle cells. Methods Adenoviral vectors, including Ad-EF1α-CD-cytomegolovirus (CMV)-TK coexpressing both CD and TK double suicide genes, Ad-EF1α-CD and Ad-CMV-TK expressing CD and TK respectively, and control vector Ad-CMV-LacZ, were constructed and prepared with homologous recombination in RecA+E.coli cells. Integration and expression of CD and/or TK gene were identified by PCR and Western blot. Primary cultured VSMCs were infected at a multiplicity of infection (MOI) of 20 with exposure to their matching prodrugs 5-Fc and GCV. Cell mortality was measured by methyl thiazolyl tetrazolium (MTT) assays. Flow cytometry analysis was used to detect cell death. Apoptotic cells were analyzed using Hoechst 33342 fluorescence dye as a DNA probe. Genomic DNA cleavage of apoptotic VSMCs was tested by agarose gel electrophoresis. Results Recombinant adenovirus expressing CD and/or TK suicide genes were successfully constructed. Both single and double suicide genes could be integrated into adenoviral genome and expressed. Cytotoxic effects of Ad-EF1α-CD-CMV-TK double suicide genes combined with 5-Fc and GCV were higher than those of Ad-CMV-TK and Ad-EF1α-CD single gene groups. The rate of cell survival was only (9±3)% in the Ad-EF1α-CD-CMV-TK group, but (37±3)% in the Ad-CMV-TK and (46±4)% in the Ad-EF1α-CD groups (P<0.05). Flow cytometry analysis indicated that the killing mechanisms of the groups were different. Necrosis and apoptosis were involved in the mechanism of the double gene group. Based on the DNA stainability with Hoechst 33342, the apoptotic rates of VSMCs in the Ad-EF1α-CD-CMV-TK [(11.0±2.1)%] and Ad-CMV-TK [(12.0±2.2)%] groups were higher than those in Ad-CMV-LacZ [(1.2±0.11)%] and Ad-EF1α-CD [(5.0±1.8)%] groups (P<0.05, respctively). DNA smear could be observed in both Ad-CMV-TK and Ad-EF1α-CD-CMV-TK groups after administration of prodrugs. Conclusions The killing effect on rat VSMCs mediated by adenoviral CD/TK double suicide genes is superior to that of single suicide gene. The killing mechanism of recombinant adenovirus coexpressing CD/TK double suicide genes is mainly through cytotoxic effect and apoptosis.

A simplified method for reconstituting active E.coli DNA polymerase Ⅲ

Genome duplication in E.coli is carried out by DNA polymeraseⅢ,an enzyme complex consisting of ten subunits.Investigations of the biochemical and structural properties of DNA polymeraseⅢrequire the expression and purification of subunits includingα,ε,θ,γ,δ′,δ,andβseparately followed by in vitro reconstitution of the polⅢcore and clamp loader.Here we propose a new method for expressing and purifying DNA polymeraseⅢcomponents by utilizing a protein coexpression strategy.Our results show that the subunits of the polⅢcore and those of the clamp loader can be coexpressed and purified based on inherent interactions between the subunits.The resulting polⅢcore,clamp loader and sliding clamp can be reconstituted effectively to perform DNA polymerization.Our strategy considerably simplifies the expression and purification of DNA polymeraseⅢand provides a feasible and convenient method for exploring other multi-subunit systems.

Transcriptome analysis of near-isogenic lines provides molecular insights into starch biosynthesis in maize kernel

Starch is the major component in maize kernels,providing a stable carbohydrate source for humans and livestock as well as raw material for the biofuel industry.Increasing maize kernel starch content will help meet industry demands and has the potential to increase overall yields.We developed a pair of maize near-isogenic lines（NILs） with different alleles for a starch quantitative trait locus on chromosome 3（q HS3）, resulting in different kernel starch content. To investigate the candidate genes for q HS3 and elucidate their effects on starch metabolism, RNA-Seq was performed for the developing kernels of the NILs at 14 and 21 d after pollination（DAP）. Analysis of genomic and transcriptomic data identified 76 genes with nonsynonymous single nucleotide polymorphisms and 384 differentially expressed genes（DEGs） in the in trogressed fragment, including a hexokinase gene, Zm HXK3 a, which catalyzes the conversion of glucose to glucose-6-phosphate and may play a key role instarch metabolism. The expression pattern of all DEGs in starch metabolism shows that altered expression of the candidate genes for q HS3 promoted starch synthesis,with positive consequences for kernel starch content. These results expand the current understanding of starch biosynthesis and accumulation in maize kernels and provide potential candidate genes to increase starch content.

Application of Computational Biology to Decode Brain Transcriptomes

The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases,providing great opportunities for systematically investigating gene expression characteristics across various brain regions throughout a series of developmental stages.Recent studies have revealed that the transcriptional architecture is the key to interpreting the molecular mechanisms of brain complexity.However,our knowledge of brain transcriptional characteristics remains very limited.With the immense efforts to generate high-quality brain transcriptome atlases,new computational approaches to analyze these highdimensional multivariate data are greatly needed.In this review,we summarize some public resources for brain transcriptome atlases and discuss the general computational pipelines that are commonly used in this field,which would aid in making new discoveries in brain development and disorders.

Integrated transcriptomics and metabolomics analyses reveal the molecular mechanisms of red-light on carotenoids biosynthesis in tomato fruit

Carotenoids are the main pigments responsible for the coloration and account for the major antioxidant activity of tomato(Solanum lycopersicum L.)fruit.Significant increments in total carotenoids and lycopene levels were observed in tomato fruit illuminated by red light relative to white light in previous studies,but the mechanism of carotenoid biosynthesis regulated by red light is stll unclear.In the present study,the influence of red light on carotenoid biosynthesis in postharvest tomato fruit was conducted using targeted metabolomics and transcriptomic methods.A total of 25 differentially accumulated carotenoids and 1939 differentially expressed genes were isolated and identified.The results illustrated that the contents of phytoene and lycopene were considerably higher in fruit treated with red light than those with white light at 12 h.These differentially expressed genes are mainly enriched in plant hormone signal transduction,photosynthesis,secondary metabolite biosynthesis,and plant circadian rhythm.Moreover,from the results of coexpression network analysis,15 transcription factors from red light-treated fruit were screened;among these,transcription factors of SIERF4,SlbHLH93 and SllAA29,which are involved in signal transduction of light and hormones,respectively,may also play important roles in carotenoid biosynthesis regulated by red light in tomato fruit.It is concluded that red light enhanced carotenoid biosynthesis in postharvest tomato fruit and the mechanisms of enhanced carotenoid biosynthesis were not only associated with the direct regulation by red light signalling,but also with the indirect regulation by hormonal signalling.

B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Col- lectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG path- ways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches （e.g., gene coexpression network alignment algorithms） in elucidating biochemical pathways involved in complex signaling events in ceils.

A Deep Look into the Program of Rapid Tumor Growth of Hepatocellular Carcinoma

Background and Aims:Great efforts have been made towards increasing our understanding of the pathogenesis involved in hepatocellular carcinoma(HCC),but the rapid growth inherent to such tumor development remains to be explored.Methods:We identified distinct gene coexpression modes upon liver tumor growth using weighted gene coexpression network analysis.Modeling of tumor growth as signaling activity was employed to understand the main cascades responsible for the growth.Hub genes in the modules were determined,examined in vitro,and further assembled into the growth signature.Results:We revealed modules related to the different growth states in HCC,especially the fastest growth module,which is preserved among different HCC cohorts.Moreover,signaling flux in the cell cycle pathway was found to act as a driving force for rapid growth.Twenty hub genes in the module were identified and assembled into the growth signature,and two genes(NCAPH,and RAD54L)were tested for their growth potential in vitro.Genetic alteration of the growth signature affected the global gene expression.The activity of the signature was associated with tumor metabolism and immunity in HCC.Finally,the prognosis effect of the growth signature was reproduced in nine cancers.Conclusions:These results collectively demonstrate the molecule organization of rapid tumor growth in HCC,which is a highly synergistic process,with implications for the future management of patients.