Co-regulated gene module detection for time series gene expression data

It is important to detect interaction effect of multiple genes during certain biological process. In this paper, we proposed, from systems biology perspective, the concept of co-regulated gene module, which consists of genes that are regulated by the same regulator（s）. Given a time series gene expression data, a hidden Markov model-based Bayesian model was developed to calculate the likelihood of the observed data, assuming the co-regulated gene modules are known. We further developed a Gibbs sampling strategy that is integrated with reversible jump Markov chain Monte Carlo to obtain the posterior probabilities of the co-regulated gene modules. Simulation study validated the proposed method. When compared with two existing methods, the proposed approach significantly outperformed the conventional methods.

Study on the Effects of Losartan on Cardiomyocyte Apoptosis and Gene Expression After Ischemia and Reperfusion in vivo in Rats

Summary: In order to study the effects of losartan on cardiomyocyte apoptosis following ischemia (0. 5 h) and reperfusion (48 h) in vivo and bcl-2 and bax gene expression, TUNEL staining method, immunohistochemistry and in situ hybridization histochemistry (ISHH) were used to monitor the apoptotic cells, mRNA and protein of gene expression, respectively. Image processing system was used to quantitively dispose the positive metric substance of both immunohistochemistry and ISHH through the average optical density (OD) value. The number of the apop- totic cells were 38±9 (control group), 0-1 (sham operation group) and 9±4 (losartan-treated group) in each visual field respectively with the difference among the groups being significant (P< 0. 001 ). OD values of bcl-2 (ISHH) were 0. 07425± 0. 02029 (control group ), 0. 05961± 0. 009932 (sham operation group) and 0. 07619±0. 01445 (losartan-treated group ) respectively, while OD values of bcl-2 (immunohistochemistry) were 0. 1374±0. 01367 (control group ), 0. 08510±0. 01862 (sham operation group) and 0. 1252±0. 02064 (losartan-treated group). hcl-2 gene expression was increased significantly in the control group and losartan-treated group as com- pared with sham operation group (P < 0. 05 ). OD value of bax (immunohistochemistry) was 09727±0. 02230 (control group), 0. 06182±0. 01430 (sham operation group) and 0. 06213± 0. 01420 (losartan-treated group). bax gene expression was decreased very significantly in losartan-treated group and sham operation group as compared with control group (P<0. 001 ). Bcl-2/ bax ratio was 1. 413 (control group), 1. 376 (sham operation group) and 2. 016 (losartan-treated group) respectively. The results indicated that losartan might inhibit cardiomyocyte apoptosis following ischemia and reperfusion. The mechanism might be that bax gene expression was inhibited to increase bcl-2/bax ratio.

Decoding transcriptional regulation via a human gene expression predictor

Transcription factors(TFs)regulate cellular activities by controlling gene expression,but a predictive model describing how TFs quantitatively modulate human transcriptomes is lacking.We construct a universal human gene expression predictor named EXPLICIT-Human and utilize it to decode transcriptional regulation.Using the expression of 1613 TFs,the predictor reconstitutes highly accurate transcriptomes for samples derived from a wide range of tissues and conditions.The broad applicability of the predictor indicates that it recapitulates the quantitative relationships between TFs and target genes ubiquitous across tissues.Significant interacting TF-target gene pairs are extracted from the predictor and enable downstream inference of TF regulators for diverse pathways involved in development,immunity,metabolism,and stress response.A detailed analysis of the hematopoiesis process reveals an atlas of key TFs regulating the development of different hematopoietic cell lineages,and a portion of these TFs are conserved between humans and mice.The results demonstrate that our method is capable of delineating the TFs responsible for fate determination.Compared to other existing tools,EXPLICIT-Human shows a better performance in recovering the correct TF regulators.

Comprehensive multi-omics analysis identified core molecular processes in esophageal cancer and revealed GNGT2 as a potential prognostic marker

BACKGROUND Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world.Although a series of studies on esophageal cancer have been reported,the molecular pathogenesis of the disease remains elusive.AIM To investigate comprehensively the molecular process of esophageal cancer.METHODS Differential expression analysis was performed to identify differentially expressed genes(DEGs)in different stages of esophageal cancer from The Cancer Genome Atlas data.Exacting gene interaction modules were generated,and hub genes in the module interaction network were found.Further,through survival analysis,methylation analysis,pivot analysis,and enrichment analysis,some important molecules and related functions/pathways were identified to elucidate potential mechanisms in esophageal cancer.RESULTS A total of 7457 DEGs and 14 gene interaction modules were identified.These module genes were significantly involved in the positive regulation of protein transport,gastric acid secretion,insulin-like growth factor receptor binding,and other biological processes as well as p53 signaling pathway,epidermal growth factor signaling pathway,and epidermal growth factor receptor signaling pathway.Transcription factors(including hypoxia inducible factor 1A)and noncoding RNAs(including colorectal differentially expressed and hsa-miR-330-3p)that significantly regulate dysfunction modules were identified.Survival analysis showed that G protein subunit gamma transducin 2(GNGT2)was closely related to survival of esophageal cancer.DEGs with strong methylation regulation ability were identified,including SST and SH3GL2.Furthermore,the expression of GNGT2 was evaluated by quantitative real time polymerase chain reaction,and the results showed that GNGT2 expression was significantly upregulated in esophageal cancer patient samples and cell lines.Moreover,cell counting kit-8 assay revealed that GNGT2 could promote the proliferation of esophageal cancer cell lines.CONCLUSION This study not only revealed the potential regulatory factors involved in the development of esophageal cancer but also deepens our understanding of its underlying mechanism.

A Network Partition Algorithm for Mining Gene Functional Modules of Colon Cancer from DNA Microarray Data

Computational analysis is essential for transforming the masses of microarray datainto a mechanistic understanding of cancer. Here we present a method for findinggene functional modules of cancer from microarray data and have applied it tocolon cancer. First, a colon cancer gene network and a normal colon tissue genenetwork were constructed using correlations between the genes. Then the modulesthat tended to have a homogeneous functional composition were identified by split-ting up the network. Analysis of both networks revealed that they are scale-free.Comparison of the gene functional modules for colon cancer and normal tissuesshowed that the modules’ functions changed with their structures.

Repair mechanism of astrocytes and non-astrocytes in spinal cord injury

BACKGROUND Spinal cord injury(SCI)is a destructive disease that incurs huge personal and social costs,and there is no effective treatment.Although the pathogenesis and treatment mechanism of SCI has always been a strong scientific focus,the pathogenesis of SCI is still under investigation.AIM To determine the key genes based on the modularization of in-depth analysis,in order to identify the repair mechanism of astrocytes and non-astrocytes in SCI.METHODS Firstly,the differences between injured and non-injured spinal cord of astrocyte(HA),injured and non-injured spinal cord of non-astrocyte(FLOW),injured spinal cord of non-injured astrocyte(HA)and non-injured spinal cord of nonastrocyte(FLOW),and non-injured spinal cord of astrocyte(HA)and nonastrocyte(FLOW)were analyzed.The total number of differentially expressed genes was obtained by merging the four groups of differential results.Secondly,the genes were co-expressed and clustered.Then,the enrichment of GO function and KEGG pathway of module genes was analyzed.Finally,non-coding RNA,transcription factors and drugs that regulate module genes were predicted using hypergeometric tests.RESULTS In summary,we obtained 19 expression modules involving 5216 differentially expressed genes.Among them,miR-494,XIST and other genes were differentially expressed in SCI patients,and played an active regulatory role in dysfunction module,and these genes were recognized as the driving genes of SCI.Enrichment results showed that module genes were significantly involved in the biological processes of inflammation,oxidation and apoptosis.Signal pathways such as NF-kappa B/A20,AMPK and MAPK were significantly regulated.In addition,non-coding RNA pivot(including miR-136-5p and let-7d-5p,etc.)and transcription factor pivot(including NFKB1,MYC,etc.)were identified as significant regulatory dysfunction modules.CONCLUSION Overall,this study uncovered a co-expression network of key genes involved in astrocyte and non-astrocyte regulation in SCI.These findings helped to reveal the core dysfunction modules,potential regulatory factors and driving genes of the disease,and to improve our understanding of its pathogenesis.

Genome-and transcriptome-wide association studies provide insights into the genetic basis of natural variation of seed oil content in Brassica napus

Seed oil content(SOC)is a highly important and complex trait in oil crops.Here,we decipher the genetic basis of natural variation in SOC of Brassica napus by genome-and transcriptome-wide association studies using 505 inbred lines.We mapped reliable quantitative trait loci(QTLs)that control SOC in eight environments,evaluated the effect of each QTL on SOC,and analyzed selection in QTL regions during breeding.Six-hundred and ninety-two genes and four gene modules significantly associated with SOC were identified by analyzing population transcriptomes from seeds.A gene prioritization framework,POCKET(prioritizing the candidate genes by incorporating information on knowledge-based gene sets,effects of variants,genome-wide association studies,and transcriptome-wide association studies),was implemented to determine the causal genes in the QTL regions based on multi-omic datasets.A pair of homologous genes,BnPMT6s,in two QTLs were identified and experimentally demonstrated to negatively regulate SOC.This study provides rich genetic resources for improving SOC and valuable insights toward understanding the complex machinery that directs oil accumulation in the seeds of B.napus and other oil crops.

Posttranscriptional induction of p21Wafl mediated by ectopic p16^(INK4) in human diploid fibroblast

Background Both p16^INK4 and p21waf1 are tumor suppressors with similar biological functions in the regulation of cellular senescence. Previous reports showed that p16^INK4 could be activated by p21waf1 through transcriptional factor Spl in HeLa cells. This study was undertaken to determine the effects of p16^INK4 on the expression and functions of p21^waf1. Methods Human diploid fibroblast 2BS cells were stably transfected with sense （2BS/p16^INK4）, antisense p16^INK4 （2BS/asp16^INK4） or empty vector （2BS/neo） .Then they were assayed by reverse-transcription polymerase chain reaction （RT-PCR）, fluorescence activated cell sorting （FACS） and Western blot. Results 2BS/p16^INK4 cells exhibited cell cycle arrest in both G1 and G2/M phases. Endogenous p21^waf1 protein levels increased twofold in the 2BS/p16^INK4 cells, but not decreased in the 2BS/asp16^INK4 cells. P21^waf1 mRNA levels were not affected in neither 2BS/p16^INK4 nor 2BS/asp16^INK4 cells. Conclusion p16^INK4 may play an important role in the regulation of cellular senescence by modulating the p21^waf1 protein level via the posttranscriptional mechanism.

Programmable pyrrole-imidazole polyamides:A potent tool for DNA targeting

Hairpin pyrrole-imidazole(Py-Im) polyamides are a class of programmable minor-groove binders that recognize pre-determined DNA double helixes with high affinity and specificity. They are capable of regulating gene expression by modulating the activity of transcription factors. To date, Py-Im polyamides have been successfully applied as a potent tool to disturb DNA functions and considered as a group of promising candidates for the clinical applications. Herein, this review will focus on summarizing the recent advances of Py-Im polyamides from their synthesis to applications via various modifications at the molecular level.