Key genes and regulatory networks for diabetic retinopathy based on hypoxia-related genes:a bioinformatics analysis

AIM:To prevent neovascularization in diabetic retinopathy(DR)patients and partially control disease progression.METHODS:Hypoxia-related differentially expressed genes(DEGs)were identified from the GSE60436 and GSE102485 datasets,followed by gene ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis.Potential candidate drugs were screened using the CMap database.Subsequently,a protein-protein interaction(PPI)network was constructed to identify hypoxia-related hub genes.A nomogram was generated using the rms R package,and the correlation of hub genes was analyzed using the Hmisc R package.The clinical significance of hub genes was validated by comparing their expression levels between disease and normal groups and constructing receiver operating characteristic curve(ROC)curves.Finally,a hypoxia-related miRNA-transcription factor(TF)-Hub gene network was constructed using the NetworkAnalyst online tool.RESULTS:Totally 48 hypoxia-related DEGs and screened 10 potential candidate drugs with interaction relationships to upregulated hypoxia-related genes were identified,such as ruxolitinib,meprylcaine,and deferiprone.In addition,8 hub genes were also identified:glycogen phosphorylase muscle associated(PYGM),glyceraldehyde-3-phosphate dehydrogenase spermatogenic(GAPDHS),enolase 3(ENO3),aldolase fructose-bisphosphate C(ALDOC),phosphoglucomutase 2(PGM2),enolase 2(ENO2),phosphoglycerate mutase 2(PGAM2),and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3(PFKFB3).Based on hub gene predictions,the miRNA-TF-Hub gene network revealed complex interactions between 163 miRNAs,77 TFs,and hub genes.The results of ROC showed that the except for GAPDHS,the area under curve(AUC)values of the other 7 hub genes were greater than 0.758,indicating their favorable diagnostic performance.CONCLUSION:PYGM,GAPDHS,ENO3,ALDOC,PGM2,ENO2,PGAM2,and PFKFB3 are hub genes in DR,and hypoxia-related hub genes exhibited favorable diagnostic performance.

Regulatory potential of soil available carbon,nitrogen,and functional genes on N_(2)O emissions in two upland plantation systems

Dynamic nitrification and denitrification processes are affected by changes in soil redox conditions,and they play a vital role in regulating soil N_(2)O emissions in rice-based cultivation.It is imperative to understand the influences of different upland crop planting systems on soil N_(2)O emissions.In this study,we focused on two representative rotation systems in Central China:rapeseed–rice(RR)and wheat–rice(WR).We examined the biotic and abiotic processes underlying the impacts of these upland plantings on soil N_(2)O emissions.The results revealed that during the rapeseed-cultivated seasons in the RR rotation system,the average N_(2)O emissions were 1.24±0.20 and 0.81±0.11 kg N ha^(–1)for the first and second seasons,respectively.These values were comparable to the N_(2)O emissions observed during the first and second wheat-cultivated seasons in the WR rotation system(0.98±0.25 and 0.70±0.04 kg N ha^(–1),respectively).This suggests that upland cultivation has minimal impacts on soil N_(2)O emissions in the two rotation systems.Strong positive correlations were found between N_(2)O fluxes and soil ammonium(NH_(4)^(+)),nitrate(NO_(3)^(–)),microbial biomass nitrogen(MBN),and the ratio of soil dissolved organic carbon(DOC)to NO_(3)^(–)in both RR and WR rotation systems.Moreover,the presence of the AOA-amoA and nirK genes were positively associated with soil N_(2)O fluxes in the RR and WR systems,respectively.This implies that these genes may have different potential roles in facilitating microbial N_(2)O production in various upland plantation models.By using a structural equation model,we found that soil moisture,mineral N,MBN,and the AOA-amoA gene accounted for over 50%of the effects on N_(2)O emissions in the RR rotation system.In the WR rotation system,soil moisture,mineral N,MBN,and the AOA-amoA and nirK genes had a combined impact of over 70%on N_(2)O emissions.These findings demonstrate the interactive effects of functional genes and soil factors,including soil physical characteristics,available carbon and nitrogen,and their ratio,on soil N_(2)O emissions during upland cultivation seasons under rice-upland rotations.

Target Entrapment Based on Adaptive Transformation of Gene Regulatory Networks

The complexity of unknown scenarios and the dynamics involved in target entrapment make designing control strategies for swarm robots a formidable task,which in turn impacts their efficiency in complex and dynamic settings.To address these challenges,this paper introduces an adaptive swarm robot entrapment control model grounded in the transformation of gene regulatory networks(AT-GRN).This innovative model enables swarm robots to dynamically adjust entrap-ment strategies by assessing current environmental conditions via real-time sensory data.Further-more,an improved motion control model for swarm robots is designed to dynamically shape the for-mation generated by the AT-GRN.Through two sets of rigorous experimental environments,the proposed model significantly enhances the trapping performance of swarm robots in complex envi-ronments,demonstrating remarkable adaptability and stability.

Large-scale loss-of-function perturbations reveal a comprehensive epigenetic regulatory network in breast cancer

Objective:Epigenetic abnormalities have a critical role in breast cancer by regulating gene expression;however,the intricate interrelationships and key roles of approximately 400 epigenetic regulators in breast cancer remain elusive.It is important to decipher the comprehensive epigenetic regulatory network in breast cancer cells to identify master epigenetic regulators and potential therapeutic targets.Methods:We employed high-throughput sequencing-based high-throughput screening(HTS^(2))to effectively detect changes in the expression of 2,986 genes following the knockdown of 400 epigenetic regulators.Then,bioinformatics analysis tools were used for the resulting gene expression signatures to investigate the epigenetic regulations in breast cancer.Results:Utilizing these gene expression signatures,we classified the epigenetic regulators into five distinct clusters,each characterized by specific functions.We discovered functional similarities between BAZ2B and SETMAR,as well as CLOCK and CBX3.Moreover,we observed that CLOCK functions in a manner opposite to that of HDAC8 in downstream gene regulation.Notably,we constructed an epigenetic regulatory network based on the gene expression signatures,which revealed 8 distinct modules and identified 10 master epigenetic regulators in breast cancer.Conclusions:Our work deciphered the extensive regulation among hundreds of epigenetic regulators.The identification of 10 master epigenetic regulators offers promising therapeutic targets for breast cancer treatment.

Regulatory T cells in skin regeneration and wound healing

As the body’s integumentary system,the skin is vulnerable to injuries.The subsequent wound healing processes aim to restore dermal and epidermal integrity and functionality.To this end,multiple tissue-resident cells and recruited immune cells cooperate to efficiently repair the injured tissue.Such temporally-and spatially-coordinated interplay necessitates tight regulation to prevent collateral damage such as overshooting immune responses and excessive inflammation.In this context,regulatory T cells(Tregs)hold a key role in balancing immune homeostasis and mediating cutaneous wound healing.A comprehensive understanding of Tregs’multifaceted field of activity may help decipher wound pathologies and,ultimately,establish new treatment modalities.Herein,we review the role of Tregs in orchestrating the regeneration of skin adnexa and catalyzing healthy wound repair.Further,we discuss how Tregs operate during fibrosis,keloidosis,and scarring.

Determining Nodulation Regulatory (Rj) Genes of Myanmar Soybean Cultivars and Their Symbiotic Effectiveness with <i>Bradyrhizobium japonicum</i>USDA110

Soybean (Glycine max L.) plays an essential role in human nutrition as a protein source, and in plant nutrition as a N source. The rate of N fixation varies depending on the cultivars and compatibility between the inoculated Rhizobium strain and the host cultivar. Characterizing the nodulation regulatory (Rj) genes is necessary to determine the compatibility of cultivars and Rhizobium strains. Rj genes were previously identified based on inoculation tests and PCR analyses. The six cultivars Yezin-3, Yezin-7, Yezin-11, Shan Seine (Local), Madaya (Local), and Hinthada (Local) were identified as harboring the Rj4 gene. Two cultivars, Yezin-6 and Yezin-8, were classified as non-Rj-gene harboring. Two other cultivars, Yezin-9 and Yezin-10, were identified as Rj3- and Rj2Rj3-gene harboring, respectively. Ours is the first report on Rj3- and Rj2Rj3-gene harboring cultivars in Myanmar. We evaluated Myanmar soybean cultivars for symbiotic effectiveness, relying on the standard strain Bradyrhizobium japonicum USDA110. In our first experiment, the soybean cultivar Yezin-11 (Rj4) showed the highest N fixing potential. Based on their potential for fixing N and nodulation, the top six soybean cultivars were Yezin-11 (Rj4), Yezin-9 (Rj3), Yezin-6 (non-Rj), Yezin-8 (non-Rj), Yezin-3 (Rj4) and Yezin-10 (Rj2Rj3). These cultivars were selected for a second experiment, which revealed that the N fixation, nodulation, and plant growth of Yezin-11 (Rj4) *Corresponding author. A. Z. Htwe et al. 2800 were superior to the other cultivars. We conclude that Yezin-11 (Rj4) is the most efficient cultivar for nodulation and N fixation when inoculated with B. japonicum USDA110.

The application of hidden markov model in building genetic regulatory network

The research hotspot in post-genomic era is from sequence to function. Building genetic regulatory network (GRN) can help to understand the regulatory mechanism between genes and the function of organisms. Probabilistic GRN has been paid more attention recently. This paper discusses the Hidden Markov Model (HMM) approach served as a tool to build GRN. Different genes with similar expression levels are considered as different states during training HMM. The probable regulatory genes of target genes can be found out through the resulting states transition matrix and the determinate regulatory functions can be predicted using nonlinear regression algorithm. The experiments on artificial and real-life datasets show the effectiveness of HMM in building GRN.

Fluctuation Resonance of Feed Forward Loops in Gene Regulatory Networks

The feed forward loop （FFL）, wherein a gene X can regulate target gene Z alone or cooperatively with gene Y, is one of the most important motifs in gene regulatory networks. Gene expression often involves a small number of reactant molecules and thus internal molecular fluctuation is considerable. Here we studied how an FFL responds to small external signal inputs at gene X, with particular attention paid to the fluctuation resonance （FR） phenomenon of gene Z. We found that for all coherent FFLs, where the sign of the direct regulation path from X to Z is the same as the overall sign of the indirect path via Y, the FR shows a regular single peak, while for incoherent FFLs, the FR exhibits distinct bimodal shapes. The results indicate that one could use small external signals to help identify the regulatory structure of an unknown FFL in complex gene networks.

Reconstruction of Gene Regulatory Networks Based on Two-Stage Bayesian Network Structure Learning Algorithm

In the post-genomic biology era,the reconstruction of gene regulatory networks from microarray gene expression data is very important to understand the underlying biological system,and it has been a challenging task in bioinformatics.The Bayesian network model has been used in reconstructing the gene regulatory network for its advantages,but how to determine the network structure and parameters is still important to be explored.This paper proposes a two-stage structure learning algorithm which integrates immune evolution algorithm to build a Bayesian network.The new algorithm is evaluated with the use of both simulated and yeast cell cycle data.The experimental results indicate that the proposed algorithm can find many of the known real regulatory relationships from literature and predict the others unknown with high validity and accuracy.

Stochastic resonance induced by a multiplicative periodic signal in the gene transcriptional regulatory system with correlated noises

This paper investigates the stochastic resonance （SR） induced by a multiplicative periodic signal in the gene transcriptional regulatory system with correlated noises. The expression of the signal-to-noise ratio （SNR） is derived. The results indicate that the existence of a maximum in SNR vs. the additive noise intensity α the multiplicative noise intensity D and the cross-correlated noise intensity λ is the identifying characteristic of the SR phenomenon and there is a critical phenomenon in the SNR as a function of λ, i.e., for the case of smaller values of noise intensity （α or D）, the SNR decreases as λ increases; however, for the case of larger values of noise intensity （α or D）, the SNR increases as λ increases.

Reconstructing gene regulatory networks in single-cell transcriptomic data analysis

Gene regulatory networks play pivotal roles in our understanding of biological processes/mechanisms at the molecular level.Many studies have developed sample-specific or cell-type-specific gene regulatory networks from single-cell transcriptomic data based on a large amount of cell samples.Here,we review the state-of-the-art computational algorithms and describe various applications of gene regulatory networks in biological studies.

Combination of Neuro-Fuzzy Network Models with Biological Knowledge for Reconstructing Gene Regulatory Networks

Inferring gene regulatory networks from large-scale expression data is an important topic in both cellular systems and computational biology. The inference of regulators might be the core factor for understanding actual regulatory conditions in gene regulatory networks, especially when strong regulators do work significantly. In this paper, we propose a novel approach based on combining neuro-fu^zy network models with biological knowledge to infer strong regulators and interrelated fuzzy rules. The hybrid neuro-fuzzy architecture can not only infer the fuzzy rules, which are suitable for describing the regulatory conditions in regulatory nctworks＋ but also explain the meaning of nodes and weight value in the neural network. It can get useful rules automatically without lhctitious judgments. At the same time, it does not add recursive layers to the model, and the model can also strengthen the relationships among genes and reduce calculation. We use the proposed approach to reconstruct a partial gene regulatory network of yeast, The results show that this approach can work effectively.

Stochastic resonance in the gene transcriptional regulatory system subjected to noises

We have investigated in the adiabatic limit the phenomenon of stochastic resonance in the gene transcriptional regulatory system subjected to an additive noise, a multiplicative noise, and a weakly periodic signal. Using the general two-state approach for the asymmetry system, the analytic expression of signal-to-noise ratio is obtained. The effects of the additive noise intensity a, the multiplicative noise intensity D and the amplitude of input periodic signal A on the signal-to-noise ratio are analysed by numerical calculation. It is found that the existence of a maximum in the RSNR a and RSNR D plots is the identifying characteristic of the stochastic resonance phenomenon in the weakened noise intensity region. The stochastic resonance phenomena are restrained with increasing a and D, and enhanced with increasing A.

Mutagenesis reveals that the rice OsMPT3 gene is an important osmotic regulatory factor

Plant mitochondrial phosphate transporters regulate phosphate transport and ATP synthesis. Determining whether they function in abiotic stress response process would shed light on their response to salt stress. We used the CRISPR/Cas9 gene-editing system to mutagenize two mitochondrial phosphate transporters, OsMPT3;1 and OsMPT3;2, to investigate their regulatory roles under salt stress. Two cas9(CRISPR-associated protein9)-free homozygous mutants, mpt33 and mpt30, were confirmed to be stable. Both OsMPT3;1 and OsMPT3;2 were markedly induced by salt stress, and their mutagenesis strongly inhibited growth and development, especially under salt stress. Mutagenesis sharply reduced the accumulation of ATP, phosphate, calcium, soluble sugar, and proline and increased osmotic potential, malondialdehyde, and Na^+ /K^+ ratio under salt stress. Both mutants demonstrate normal growth and development in the presence of ATP, revealing high sensitivity to exogenous ATP under salt stress. The mutants showed lowered rates of Na^+ efflux but also of K^+ and Ca^(2+) influx under salt stress. Mutagenesis of OsMPT3;2 altered the enrichment profiles of differentially expressed genes involved mainly in synthesis of secondary metabolites, metabolism of glycolysis, pyruvate, tricarboxylic acid cycle, in response to salt stress. The mutant displayed significant accumulation differences in 14 metabolites involved in 17 metabolic pathways, and strongly up-regulated the accumulation of glutamine, a precursor in proline synthesis, under salt stress. These findings suggest that the OsMPT3 gene modulates phosphate transport and energy supply for ATP synthesis and triggers changes in accumulation of ions and metabolites participating in osmotic regulation in rice under salt stress, thus increasing rice salt tolerance. This study demonstrates the effective application of CRISPR/Cas9 gene-editing to the investigation of plant functional genes.

Regulatory Analysis of IPP Isomerase Gene in Haematococcus pluvialis

The unicellular green alga Haematococcus pluvia/is uniquely accumulates carotenoids in the cytoplasm and in late developmental stages turns deep-red in color because of accumulation of astaxanthin in the cytosol. The enzyme, isopentenyl pyrophosphate （IPP） isomerase, plays a key role in astaxanthin biosynthesis of H. pluvialis. In this paper, two separate 5＇-flanking regions （1.8 kb and 2.5 kb） of IPP isomerase gene was cloned through walking upstream firstly. Results of sequence analysis =showed that two separate 5＇-flanking regions of IPP isomerase gene might have similar putative cis-acting elements such as ABA （abscisic acid）-responsive element （ABRE）, drought-responsive element （DRE/C-repeat）, light-responsive element （G-box, GAG-motif, I-box and ATC-motif）, heat-shock element （HSE）, wound-responsive element （WUN-motif）, SA （salicylic acid）-responsive element （TCA-element）, auxin-responsive element （TGA-element）, MeJA （methyl jasmonate）-responsive element （TGACG-element）, enhancer-like element involved in anoxic specific inducibility （GC-motif） and MYB binding sites （MBS and MRE）, except for typical TATA box or CCAAT box, which exhibit diversiform transcriptional patterns of IPP isomerase gene in astaxanthin biosynthesis of Haematococcus pluvialis.

Oscillatory and anti-oscillatory motifs in genetic regulatory networks

Recently, self-sustained oscillatory genetic regulatory networks （GRNs） have attracted significant attention in the biological field. Given a GRN, it is important to anticipate whether the network could generate oscillation with proper parameters, and what the key ingredients for the oscillation are. In this paper the ranges of some function-related parameters which are favorable to sustained oscillations are considered. In particular, some oscillatory motifs appearing with high-frequency in most of the oscillatory GRNs are observed. Moreover, there are some anti-oscillatory motifs which have a strong oscillation repressing effect. Some conclusions analyzing these motif effects and constructing oscillatory GRNs are provided.

Okadaic acid: a tool to study regulatory mechanisms for neurodegeneration and regeneration in Alzheimer's disease

Okadaic acid： Okadaic acid （OKA）, a polyether （C38 fatty acid） toxin, is a potent and selective inhibitor of protein phosphatase, PP1 and protein phosphatase 2A （PP2A）. It is mainly extracted from a black sponge Hallichondria okadaii and has been suggested to play a potent probe for studying the various molecular, cellular, biochemical and mechanism of neurotoxicity. It is known as a selective and potent in- hibitor of serine/threonine phosphatases 1 and 2A induces hyperphosphorylation of tau in vitro and in vivo. It has been reported that Alzheimer＇s disease （AD） is a complex multi- factorial neurodegenerative disorder and hyperphosphor- ylated tau protein is a major pathological hallmark of AD. The reduced activity of phosphatases like, PP2A has been implicated in the brain of AD patients. OKA also induced inhibition of protein phosphatases cause neurofibrillary tangles （NFTs） like pathological changes and tau hyperphos- phorylation seen in AD pathology. Our and others reports inferred that OKA induces neurodegeneration along with tau hyperphosphorylation, GSK3β activation, oxidative stress, neuroinflammation and neurotoxicity which are char- acteristic of AD pathology （Figure 1）.

A cluster of mutagenesis revealed an osmotic regulatory role of the OsPIP1 genes in enhancing rice salt tolerance

Aquaporins play important regulatory roles in improving plant abiotic stress tolerance.To better understand whether the Os PIP1 genes collectively dominate the osmotic regulation in rice under salt stress,a cluster editing of the Os PIP1;1,Os PIP1;2 and Os PIP1;3 genes in rice was performed by CRISPR/Cas9 system.Sequencing showed that two mutants with Cas9-free,line 14 and line 18 were successfully edited.Briefly,line 14 deleted a single C base in both the Os PIP1;1 and Os PIP1;3 genes,and inserted a single T base in the Os PIP1;2 gene,respectively.While line 18 demonstrated an insertion of a single A base in the Os PIP1;1gene and a single T base in both the Os PIP1;2 and Os PIP1;3 genes,respectively.Multiplex editing of the Os PIP1 genes significantly inhibited photosynthetic rate and accumulation of compatible metabolites,but increased MDA contents and osmotic potentials in the mutants,thus delaying rice growth under salt stress.Functional loss of the Os PIP1 genes obviously suppressed the expressions of the Os PIP1,Os SOS1,Os CIPK24 and Os CBL4 genes,and increased the influxes of Na+and effluxes of K^(+)/H^(+)in the roots,thus accumulating more Na+in rice mutants under salt stress.This study suggests that the Os PIP1 genes are essential modulators collectively contributing to the enhancement of rice salt stress tolerance,and multiplex editing of the Os PIP1 genes provides insight into the osmotic regulation of the PIP genes.

Regulatory genes controlling neural stem cells differentiation into neurons

The recent progress in neural stem cells （NSCs） research has shed lights on possibility of repair and restoration of neuronal function in neurodegenerative diseases using stem cells. Induction of stem cells differentiate into mature neurons is critical to achieve the clinical applications of NSCs. At present, molecular mechanisms modulating NSC differentiation are not fully understood. Differentiation of stem cells into neuronal and glial cells involves an array of changes in expression of transcription factors. Transcription factors then trigger the expression of a variety of central nervous system （CNS） genes that lead NSCs to differentiate towards different cell types. In this paper, we summarized the recent findings on the gene regulation of NSCs differentiation into neuronal cells.

Research of Gene Regulatory Network with Multi-Time Delay Based on Bayesian Network

The gene regulatory network was reconstructed according to time-series microarray data getting from hybridization at different time between gene chips to analyze coordination and restriction between genes. An algorithm for controlling the gene expression regulatory network of the whole cell was designed using Bayesian network which provides an effective aided analysis for gene regulatory network.