GoPipe:批量序列的Gene Ontology注释和统计分析(英文)

随着后基因组时代的到来,批量的测序,特别是EST的测序,逐渐成为普通实验室的日常工作. 这些新的序列往往需要进行批量的Gene Ontology (GO)的注释及随后的统计分析. 但是目前除了Goblet以外,并没有软件适合对未知序列进行批量的GO注释,而GoBlet因为具有上载量的限制,以及仅仅利用BLAST作为预测工具,所以仍有许多不足之处. 开发了一个软件包GoPipe,通过整合BLAST和InterProScan的结果来进行序列注释,并提供了进一步作统计比较的工具. 主程序接收任意个BLAST和InterProScan的结果文件,并依次进行文本分析、数据整合、去除冗余、统计分析和显示等工作. 还提供了统计的工具来比较不同输入对GO的分布来挖掘生物学意义. 另外,在交集工作模式下,程序取InterProScan和BLAST结果的交集,在测试数据集中,其精确度达到99.1%,这大大超过了InterProScan本身对GO预测的精确度,而敏感度只是稍微下降. 较高的精确度、较快的速度和较大的灵活性使它成为对未知序列进行批量Gene Ontology注释的理想的工具. 上述软件包可以在网站(http://gopipe.fishgenome.org/ ) 免费获得或者与作者联系获取.

ARGs-OAP v3.0:Antibiotic-Resistance Gene Database Curation and Analysis Pipeline Optimization

Antibiotic resistance,which is encoded by antibiotic-resistance genes(ARGs),has proliferated to become a growing threat to public health around the world.With technical advances,especially in the popularization of metagenomic sequencing,scientists have gained the ability to decipher the profiles of ARGs in diverse samples with high accuracy at an accelerated speed.To analyze thousands of ARGs in a highthroughput way,standardized and integrated pipelines are needed.The new version(v3.0)of the widely used ARGs online analysis pipeline(ARGs-OAP)has made significant improvements to both the reference database-the structured ARG(SARG)database-and the integrated analysis pipeline.SARG has been enhanced with sequence curation to improve annotation reliability,incorporate emerging resistance genotypes,and determine rigorous mechanism classification.The database has been further organized and visualized online in the format of a tree-like structure with a dictionary.It has also been divided into sub-databases for different application scenarios.In addition,the ARGs-OAP has been improved with adjusted quantification methods,simplified tool implementation,and multiple functions with userdefined reference databases.Moreover,the online platform now provides a diverse biostatistical analysis workflow with visualization packages for the efficient interpretation of ARG profiles.The ARGs-OAP v3.0 with an improved database and analysis pipeline will benefit academia,governmental management,and consultation regarding risk assessment of the environmental prevalence of ARGs.

RNA sequencing of exosomes secreted by fibroblast and Schwann cells elucidates mechanisms underlying peripheral nerve regeneration

Exosomes exhibit complex biological functions and mediate a variety of biological processes,such as promoting axonal regeneration and functional recove ry after injury.Long non-coding RNAs(IncRNAs)have been reported to play a crucial role in axonal regeneration.Howeve r,the role of the IncRNA-microRNAmessenger RNA(mRNA)-competitive endogenous RNA(ceRNA)network in exosome-mediated axonal regeneration remains unclear.In this study,we performed RNA transcriptome sequencing analysis to assess mRNA expression patterns in exosomes produced by cultured fibroblasts(FC-EXOs)and Schwann cells(SCEXOs).Diffe rential gene expression analysis,Gene Ontology analysis,Kyoto Encyclopedia of Genes and Genomes analysis,and protein-protein intera ction network analysis were used to explo re the functions and related pathways of RNAs isolated from FC-EXOs and SC-EXOs.We found that the ribosome-related central gene Rps5 was enriched in FC-EXOs and SC-EXOs,which suggests that it may promote axonal regeneration.In addition,using the miRWalk and Starbase prediction databases,we constructed a regulatory network of ceRNAs targeting Rps5,including 27 microRNAs and five IncRNAs.The ceRNA regulatory network,which included Ftx and Miat,revealed that exsosome-derived Rps5 inhibits scar formation and promotes axonal regeneration and functional recovery after nerve injury.Our findings suggest that exosomes derived from fibro blast and Schwann cells could be used to treat injuries of peripheral nervous system.

Analysis of differentially expressed genes related to cerebral ischaemia in young rats based on the Gene Expression Omnibus database

BACKGROUND The incidence rate of cerebral infarction in young people is increasing day by day,the age of onset tends to be younger,and its internal pathogenesis and mechanism are very complicated,which leads to greater difficulties in treatment.Therefore,it is essential to analyze the key pathway that affects the onset of cerebral infarction in young people from the perspective of genetics.AIM To compare the differentially expressed genes in the brain tissue of young and aged rats with middle cerebral artery occlusion and to analyse their effect on the key signalling pathway involved in the development of cerebral ischaemia in young rats.METHODS The Gene Expression Omnibus 2R online analysis tool was used to analyse the differentially expressed genes in the GSE166162 dataset regarding the development of cerebral ischaemia in young and aged groups of rats.DAVID 6.8 software was further used to filter the differentially expressed genes.These genes were subjected to Gene Ontology(GO)function analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis to determine the key gene pathway that affects the occurrence of cerebral ischaemia in young rats.RESULTS Thirty-five differentially expressed genes(such as Igf2,Col1a2,and Sfrp1)were obtained;73 GO enrichment analysis pathways are mainly involved in biological processes such as drug response,amino acid stimulation response,blood vessel development,various signalling pathways,and enzyme regulation.They are involved in molecular functions such as drug binding,protein binding,dopamine binding,metal ion binding,and dopamine neurotransmitter receptor activity.KEGG pathway enrichment analysis showed a significantly enriched pathway:The cyclic adenosine monophosphate(c-AMP)signalling pathway.CONCLUSION The c-AMP signalling pathway might be the key pathway in the intervention of cerebral infarction in young people.

To analyze the differentially expressed genes in chronic rejection after renal transplantation by bioinformatics

Objective: To use bioinformatics technology to analyse differentially expressed genes in chronic rejection after renal transplantation, we can screen out potential pathogenic targets associated with the development of this disease, providing a theoretical basis for finding new therapeutic targets. Methods: Gene microarray data were downloaded from the Gene Expression Profiling Integrated Database (GEO) and cross-calculated to identify differentially expressed genes (DEGs). Analysis of differentially expressed genes (DEGs) with gene ontology (GO) is a method used to study the differences in gene expression under different conditions as well as their functions and interrelationships, while Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis is a tool used to explore the functions and pathways of genes in specific biological processes. By calculating the distribution of immune cell infiltration, the result of immune infiltration in the rejection group can be analysed as a trait in Weighted Gene Co-Expression Network Analysis (WGCNA) for genes associated with rejection. Then, protein-protein interaction networks (PPI) were constructed using the STRING database and Cytoscape software to identify hub gene markers. Results: A total of 60 integrated DEGs were obtained from 3 datasets (GSE7392, GSE181757, GSE222889). By GO and KEGG analysis, the GEDs were mainly concentrated in the regulation of immune response, defence response, regulation of immune system processes, and stimulation response. The pathways were mainly enriched in antigen processing and presentation, EBV infection, graft-versus-host, allograft rejection, and natural killer cell-mediated cytotoxicity. After further screening using WGCNA and PPI networks, HLA-A, HLA-B, HLA-F, and TYROBP were identified as hub genes (Hub genes). The data GSE21374 with clinical information was selected to construct the diagnostic efficacy and risk prediction model plots of the four hub genes, and the results concluded that all four Hub genes had good diagnostic value (area under the curve in the range of 0.794-0.819). From the inference, it can be concluded that the four genes, HLA-A, HLA-B, HLA-F and TYROBP, may have an important role in the development and progression of chronic rejection after renal transplantation. Conclusion: DEGs play an important role in the study of the pathogenesis of chronic rejection after renal transplantation, and can provide theoretical support for further research on the pathogenesis of chronic rejection after renal transplantation and the discovery of new therapeutic targets through enrichment analysis and pivotal gene screening, as well as inferential analyses of related diagnostic efficacy and disease risk prediction.

基于语义路径覆盖的Gene Ontology术语间语义相似性度量方法

进行GO(gene ontology)语义相似性度量是解决生物学数据集成中语义异构问题的重要方法。传统方法主要是基于距离的度量和基于信息量的度量。文中提出了一种基于语义路径覆盖的度量方法,并实现了其中Combine算法。该算法首先计算出每个节点的信息量,然后分别计算两个节点的语义路径的交的节点信息量之和以及这两个节点语义路径的并的节点信息量之和,将这两者之间的比率作为相似性度量值。实验结果表明该算法具有较高的相关系数。

Gene Ontology在生物数据整合中的应用

异构数据的高效整合,在生物数据呈爆炸性增长、生物数据库复杂度不断增加的今天,具有重要的理论价值和实际意义。该文基于BioDW——一个整合的生物信息学数据仓库平台,利用统一的GeneOntology语义模型,建立异构数据库之间的语义链接,在概念和联系层次上有效地解决了生物异构数据的整合问题,实现了对生物数据智能化的多重、复合和交叉检索,为生物信息的进一步研究奠定了坚实的基础。

Discovering hidden information of gene ontology based on complex networks analysis

To resolve the ontology understanding problem, the structural features and the potential important terms of a large-scale ontology are investigated from the perspective of complex networks analysis. Through the empirical studies of the gene ontology with various perspectives, this paper shows that the whole gene ontology displays the same topological features as complex networks including ＂small world＂ and ＂scale-free＂,while some sub-ontologies have the ＂scale-free＂ property but no ＂small world＂ effect.The potential important terms in an ontology are discovered by some famous complex network centralization methods.An evaluation method based on information retrieval in MEDLINE is designed to measure the effectiveness of the discovered important terms.According to the relevant literature of the gene ontology terms,the suitability of these centralization methods for ontology important concepts discovering is quantitatively evaluated.The experimental results indicate that the betweenness centrality is the most appropriate method among all the evaluated centralization measures.

一种基于Gene Ontology注释信息的基因选择算法

基因选择算法是辅助生物学分析最重要的方法之一,但这类统计学算法受样本量相对基因数目过少的困扰。提出一种结合Gene Ontology(GO)注释信息的基因选择算法,用GO注释接近基因的方差的加权平均进行修正,增强小样本量下对总体的估计,进而寻找差异表达基因。将该算法与其他5种常见算法对比,以选择出的基因为特征构建分类器,以分类器的可靠性作为衡量算法的标准。3组芯片实验的结果表明,该算法在小样本情况下具有一定优势。亦有Pubmed文献证明,该算法可以鉴别出其他算法未曾发现的致病基因。该方法所建立起来的框架,是把生物学注释信息引入算法改进的一种有效尝试。

采用基于Gene Ontology的聚类方法研究白血病的遗传异质性

采用基因表达谱可以研究基因功能模块与疾病异质性之间的关系。根据两套白血病基因表达谱数据,将富集高变异基因的Gene Ontology基因功能模块作为特征功能模块,将疾病样本聚为两类。通过对比原始多类标签,采用聚类评估指标来分析两类化聚类结果的效果,并探讨特征功能模块与疾病异质性之间的关系。实验结果显示:在两套不同的白血病基因表达谱数据中得到的特征功能模块类似,它们对白血病亚型有较强的分型能力。

Rules-based object-relational databases ontology construction

To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions ave formalized according to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.

pLoc-mGpos: Incorporate Key Gene Ontology Information into General PseAAC for Predicting Subcellular Localization of Gram-Positive Bacterial Proteins

The basic unit in life is cell.?It contains many protein molecules located at its different organelles. The growth and reproduction of a cell as well as most of its other biological functions are performed via these proteins. But proteins in different organelles or subcellular locations have different functions. Facing?the avalanche of protein sequences generated in the postgenomic age, we are challenged to develop high throughput tools for identifying the subcellular localization of proteins based on their sequence information alone. Although considerable efforts have been made in this regard, the problem is far apart from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions that are particularly important for drug targets. Using the ML-GKR (Multi-Label Gaussian Kernel Regression) method,?we developed a new predictor called “pLoc-mGpos” by in-depth extracting the key information from GO (Gene Ontology) into the Chou’s general PseAAC (Pseudo Amino Acid Composition)?for predicting the subcellular localization of Gram-positive bacterial proteins with both single and multiple location sites. Rigorous cross-validation on a same stringent benchmark dataset indicated that the proposed pLoc-mGpos predictor is remarkably superior to “iLoc-Gpos”, the state-of-the-art predictor for the same purpose.?To maximize the convenience of most experimental scientists, a user-friendly web-server for the new powerful predictor has been established at http://www.jci-bioinfo.cn/pLoc-mGpos/, by which users can easily get their desired results without the need to go through the complicated mathematics involved.

De novo transcriptome sequencing reveals candidate genes involved in orange shell coloration of bay scallop Argopecten irradians

Molluscan shell color has received persistent attention for its distinctive diversity and complexity. In the present study, six transcriptome libraries obtained from two developmental stages, pre-pigmentation and post-pigmentation, were used for paired-end sequencing in the bay scallop Argopecten irradians. In total, 289 839 646 paired-end reads were assembled into 70 929 transcripts. Using BLASTX and BLASTN, 30 896 unigenes were successfully annotated against the SWISS-PROT, NR, and KOG database. Gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes classification identified numbers of unigenes involved in biomineralization and pigmentation. Digital gene expression analysis revealed that melanin, trace metal elements and porphyrins are potentially involved in shell coloration of A. irradians.

InvasionDB: A genome and gene database of invasive alien species

Invasive alien species(IAS) are species whose introduction to areas outside of their native range cause harm to economics, biodiversity, and the environment. Understanding the genetic basis of invasiveness is critical for preventing invasion by an alien species and managing IAS with eco-friendly control methods. In addition, uncovering the genomic features of IAS is essential for accurately predicting invasiveness. However, even though increasing efforts have been devoted to sequencing the genomes of IAS, there is still not an integrated genome database for the invasive biology community. Here, we first determined a list of invasive plants and animals by mining references and databases. Then, we retrieved the genomic and gene data of these IAS, and constructed a database, Invasion DB. Invasion DB encompasses 131 IAS genomes, 76 annotated IAS assemblies, and links these data to conventional functions such as searching for gene coding sequences and Pfam, KEGG, NR annotations, BLAST server, JBrowse, and downloads services. Next, we analyzed 19 invasivenessrelated gene families which confer invasiveness in insects. To study the roles of noncoding RNA in invasiveness, we also annotated 135 494 mi RNAs, 89 294 r RNAs, and 2 671 941 t RNAs from these IAS. In summary, Invasion DB is useful for studying the invasiveness at the genomic level, and thus helps to develop novel management strategies to control IAS.

Gene-Ontology Analysis on the Differentially Expressed Genes in Maize （Zea mays L.） Ear Rot

To better know FM （Fusarium moniliforme） induced genes in maize ear rot, GO （gene ontology） method was performed to analyze detail physiological functions in the defensive response after pathogen infection. This gene annotation system was widely used to investigate large numbers of genes involving in real active role or regulator in cell response. First of all, differentially expressed genes were isolated by using genechip platform at 96 h post-inoculation with FM in maize inbred Bt-1. In total, 482 differentially expressed unique genes were screened out in inbred Bt-1 when compared to mock-inoculated bract tissues. Then, each gene was annotated to define functional class by GO method. Finally, these large FM-responsive genes with significant differentially change were sorted into cellular component, molecular function and biological process with complicated network by molecular annotation system. The demonstrated information in the GO analysis could provide another view for understanding the molecular mechanism and indicate a deeply complicated network with gene function underlying disease development in the host tissue. The findings in this study provide important bases to probe the molecular processes, the alteration of metabolism and the immune mechanism upon the FM infection in maize.

基于Gene Ontology的MicroRNA功能聚类

MicroRNA(miRNA)的许多生物过程是通过影响靶基因的转录后表达.miRNA与靶标之间的互补程度和性质决定其基因调控作用.结构相似性可以作为一个强有力的方法推断分子功能的相似性.然而,结构比对的方法来度量miRNA之间的相似性通常不太准确,而且时间开销大.对这些表达差异的miRNA的靶标基因进行聚类,可以很好地理解miRNA的功能.提出一个新的GO(gene Ontology)语义相似性的方法来区分miRNA功能组.该方法采用项信息和边的权重来度量GO项的权重.此外,2个GO图的共同项和非共同项还被用来度量这2个图之间的相似度.对于2个miRNA,它们之间的相似性可以用它们靶标基因标注的GO项的相似性来计算.实验结果表明此方法不仅可以将相似功能的miRNA聚在一起,而且可以预测未知miRNA的功能.

Integrating Gene Ontology and Blast to predict gene functions

A GoBlast system was built to predict gene function by integrating Blast search and Gene Ontology (GO) annotations together. The operation system was based on Debian Linux 3.1, with Apache as the web server and Mysql database as the data storage system. FASTA files with GO annotations were taken as the sequence source for blast alignment, which were formatted by wu-formatdb program. The GoBlast system includes three Bioperl modules in Perl:a data input module, a data process module and a data output module. A GoBlast query starts with an amino acid or nucleotide sequence. It ends with an output in an html page, presenting high scoring gene products which are of a high homology to the queried sequence and listing associated GO terms beside respective gene poducts. A simple click on a GO term leads to the detailed explanation of the specific gene function. This avails gene function prediction by Blast. GoBlast can be a very useful tool for functional genome research and is available for free at http://bioq.org/goblast.

Analysis of differential genes of ischemic stroke-induced heart tissue in mice based on GEO database

Objective:The differential genes of left ventricle in middle cerebral artery occlusion model(MCAO)mice and Sham mice(Sham)mice at 24h and 72h after ischemia were compared respectively,and the differential genes and their regulated functional pathways were analyzed at different time points after ischemic stroke,so as to analyze the mechanism of inducing cardiac dysfunction after ischemic stroke and provide evidence for its treatment.Methods:Gene-chip data from the left ventricle of MCAO mice and Sham mice were downloaded from the GEO database at the National Center for Biotechnology Information(NCBI).The differentially expressed genes were obtained by R language software programming.The GO functional enrichment and KEGG pathway enrichment analysis of the obtained differential genes were performed using DAVID 6.8 online analysis tool,and the Omicshare online analysis tool was used to visualize the enrichment analysis results.Results:At 24h after ischemia,187 differentially expressed genes were obtained,including 56 GO enrichment pathways and 5 KEGG enrichment pathways with significant significance.After 72h after ischemia,51 differentially expressed genes were obtained,14 GO enrichment pathways and 3 KEGG enrichment pathways with significant significance.The two time points involved Aplnr and Itgb6 gene targets and PI3K-Akt signaling pathway.Conclusion:①By analyzing the gene expression profile data,the differentially expressed genes and related pathways of cardiac dysfunction induced by ischemic stroke were obtained.②PI3K-AKT signaling pathway is closely related to the regulation of cardiac function,and regulation of PI3K-AKT signaling pathway may be an important direction for the treatment of cardiac dysfunction after ischemic stroke.

Exploring Splicing Variants and Novel Genes in Sacred Lotus Based on RNA-seq Data

Sacred lotus(Nelumbo nucifera)is a typical aquatic plant,belonging to basal eudicot plant,which is ideal for genome and genetic evolutionary study.Understanding lotus gene diversity is important for the study of molecular genetics and breeding.In this research,public RNA-seq data and the annotated reference genome were used to identify the genes in lotus.A total of 26,819 consensus and 1,081 novel genes were identified.Meanwhile,a comprehensive analysis of gene alternative splicing events was conducted,and a total of 19,983“internal”alternative splicing(AS)events and 14,070“complete”AS events were detected in 5,878 and 5,881 multi-exon expression genes,respectively.Observations made from the AS events show the predominance of intron retention(IR)subtype of AS events representing 33%.IR is followed by alternative acceptor(AltA),alternative donor(AltD)and exon skipping(ES),highlighting the universality of the intron definition model in plants.In addition,functional annotations of the gene with AS indicated its relationship to a number of biological processes such as cellular process and metabolic process,showing the key role for alternative splicing in influencing the growth and development of lotus.The results contribute to a better understanding of the current gene diversity in lotus,and provide an abundant resource for future functional genome analysis in lotus.

Reduced non-CpG methylation is a potential epigenetic target after spinal cord injury

DNA methylation is a critical epigenetic regulator in the occurrence and development of diseases and is closely related to various functional responses in relation to spinal cord injury.To investigate the role of DNA methylation in spinal cord injury,we constructed a library with reduced-representation bisulfite sequencing data obtained at various time points(day 0-42)after spinal cord injury in mice.Global DNA methylation levels,specifically non-CpG(CHG and CHH)methylation levels,decreased modestly following spinal cord injury.Stages post-spinal cord injury were classified as early(day 0-3),intermediate(day7-14),and late(day 28-42)based on similarity and hie rarchical cluste ring of global DNA methylation patterns.The non-CpG methylation level,which included CHG and CHH methylation levels,was markedly reduced despite accounting for a minor proportion of total methylation abundance.At multiple genomic sites,including the 5’untranslated regions,promoter,exon,intron,and 3’untranslated regions,the non-CpG methylation level was markedly decreased following spinal cord injury,whereas the CpG methylation level remained unchanged at these locations.Approximately one-half of the differentially methylated regions were located in intergenic areas;the other differentially methylated regions in both CpG and non-CpG regions were cluste red in intron regions,where the DNA methylation level was highest.The function of genes associated with differentially methylated regions in promoter regions was also investigated.From Gene Ontology analysis results,DNA methylation was implicated in a number of essential functional responses to spinal cord injury,including neuronal synaptic connection creation and axon regeneration.Notably,neither CpG methylation nor non-CpG methylation was implicated in the functional response of glial or inflammatory cells.In summary,our work elucidated the dynamic pattern of DNA methylation in the spinal co rd following injury and identified reduced nonCpG methylation as an epigenetic target after spinal cord injury in mice.