Key genes and functional coexpression modules involved in the pathogenesis of systemic lupus erythematosus

We performed a systematic review of genome‐wide gene expression datasets to identify key genes and functional modules involved in the pathogenesis of systemic lupus erythematosus (SLE) at a systems level. Genome‐wide gene expression datasets involving SLE patients were searched in Gene Expression Omnibus and ArrayExpress databases. Robust rank aggregation (RRA) analysis was used to integrate those public datasets and identify key genes associated with SLE. The weighted gene coexpression network analysis (WGCNA) was adapted to identify functional modules involved in SLE pathogenesis, and the gene ontology enrichment analysis was utilized to explore their functions. The aberrant expressions of several randomly selected key genes were further validated in SLE patients through quantitative real‐time polymerase chain reaction. Fifteen genome‐wide gene expression datasets were finally included, which involved a total of 1,778 SLE patients and 408 healthy controls. A large number of significantly upregulated or downregulated genes were identified through RRA analysis, and some of those genes were novel SLE gene signatures and their molecular roles in etiology of SLE remained vague. WGCNA further successfully identified six main functional modules involved in the pathogenesis of SLE. The most important functional module involved in SLE included 182 genes and mainly enriched in biological processes, including defense response to virus, interferon signaling pathway, and cytokine‐mediated signaling pathway. This study identifies a number of key genes and functional coexpression modules involved in SLE, which provides deepening insights into the molecular mechanism of SLE at a systems level and also provides some promising therapeutic targets.     

Resources and transgenesis techniques for functional genomics in Xenopus

Recent developments in genomic resources and high‐throughput transgenesis techniques have allowed Xenopus to ‘metamorphose’ from a classic model for embryology to a leading‐edge experimental system for functional genomics. This process has incorporated the fast‐breeding diploid frog, Xenopus tropicalis, as a new model‐system for vertebrate genomics and genetics. Sequencing of the X. tropicalis genome is nearly complete, and its comparison with mammalian sequences offers a reliable guide for the genome‐wide prediction of cis‐regulatory elements. Unique cDNA sets have been generated for both X. tropicalis and X. laevis, which have facilitated non‐redundant, systematic gene expression screening and comprehensive gene expression analysis. A variety of transgenesis techniques are available for both X. laevis and X. tropicalis, and the appropriate procedure may be chosen depending on the purpose for which it is required. Effective use of these resources and techniques will help to reveal the overall picture of the complex wiring of gene regulatory networks that control vertebrate development.     

Genome-wide functional screen of 3′UTR variants uncovers causal variants for human disease and evolution

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Molecular and biochemical characterization of galectin from amphioxus: primitive galectin of chordates participated in the infection processes

A novel F4-carbohydrate recognition domain (CRD)-linker-F3-CRD-type bi-CRD Branchiostoma belcheri tsingtauense galectin (BbtGal)-L together with its alternatively spliced mono-CRD isoform BbtGal-S from amphioxus intestine was encoded by a 9488-bp unique gene with eight exons and seven introns. The recombinant proteins of BbtGal were found to have beta-galactoside-binding activity, indicating that BbtGal was a member of the galectin family. Phylogenetic analysis of this gene along with its splicing form and genome structure suggested that the BbtGal gene was the primitive form of the chordate galectin family. Real-time polymerase chain reaction analyses (PCR) indicated that BbtGal mRNA was expressed during all stages of embryonic development. In terms of tissue distribution, BbtGal-L mRNA was mainly expressed in the immunity-related organs, such as hepatic diverticulum, intestine, and gill, but BbtGal-S was ubiquitously expressed in all tissues. The expression of BbtGal-L mRNA was elevated after acute challenge with various microorganisms, but BbtGal-L only bound to specific bacteria. The immune function of BbtGal was consistent with its localization both outside and inside the cell. Our study on amphioxus galectin may help further understanding of the evolution of chordate galectin in terms of host-pathogen interaction in the immune system.     

Evolution of wing pigmentation in Drosophila: Diversity,physiological regulation,and cis-regulatory evolution

Fruit flies (Drosophila and its close relatives, or “drosophilids”) are a group that includes an important model organism, Drosophila melanogaster, and also very diverse species distributed worldwide. Many of these species have black or brown pigmentation patterns on their wings, and have been used as material for evo-devo research. Pigmentation patterns are thought to have evolved rapidly compared with body plans or body shapes; hence they are advantageous model systems for studying evolutionary gains of traits and parallel evolution. Various groups of drosophilids, including genus Idiomyia (Hawaiian Drosophila), have a variety of pigmentations, ranging from simple black pigmentations around crossveins to a single antero-distal spot and a more complex mottled pattern. Pigmentation patterns are sometimes obviously used for sexual displays; however, in some cases they may have other functions. The process of wing formation in Drosophila, the general mechanism of pigmentation formation, and the transport of substances necessary for pigmentation, including melanin precursors, through wing veins are summarized here. Lastly, the evolution of the expression of genes regulating pigmentation patterns, the role of cis-regulatory regions, and the conditions required for the evolutionary emergence of pigmentation patterns are discussed. Future prospects for research on the evolution of wing pigmentation pattern formation in drosophilids are presented, particularly from the point of view of how they compare with other studies of the evolution of new traits.     

In search of morphological modules: a systematic review

Morphological modularity arises in complex living beings due to a semi‐independent inheritance, development, and function of body parts. Modularity helps us to understand the evolvability and plasticity of organismal form, and how morphological variation is structured during evolution and development. For this reason, delimiting morphological modules and establishing the factors involved in their origins is a lively field of inquiry in biology today. Although it is thought that modularity is pervasive in all living beings, actually we do not know how often modularity is present in different morphological systems. We also do not know whether some methodological approaches tend to reveal modular patterns more easily than others, or whether some factors are more related to the formation of modules or the integration of the whole phenotype. This systematic review seeks to answer these type of questions through an examination of research investigating morphological modularity from 1958 to present. More than 200 original research articles were gathered in order to reach a quantitative appraisal on what is studied, how it is studied, and how the results are explained. The results reveal an heterogeneous picture, where some taxa, systems, and approaches are over‐studied, while others receive minor attention. Thus, this review points out various trends and gaps in the study of morphological modularity, offering a broad picture of current knowledge and where we can direct future research efforts.     

基因打靶技术在植物基因功能研究中的应用

水稻、拟南芥等模式植物基因组测序计划的完成,验证预测基因的功能成为植物功能基因组学的重要内容,基因打靶(gene targeting)技术在哺乳动物中的成功应用为该技术在植物上展现了广阔的应用前景。现对植物基因打靶技术的影响因素、基因打靶在植物中的应用现状作一介绍。     

Identification of key gene modules and pathways of human glioma through coexpression network

Glioma causes great harm to people worldwide. Systemic coexpression analysis of this disease could be beneficial for the identification and development of new prognostic and predictive markers in the clinical management of glioma. In this study, we extracted data sets from the Gene Expression Omnibus data set by using “glioma” as the keyword. Then, a coexpression module was constructed with the help of Weighted Gene Coexpression Network Analysis software. Besides, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the genes in these modules. As a result, the critical modules and target genes were identified. Eight coexpression modules were constructed using the 4,000 genes with a high expression value of the total 141 glioma samples. The result of the analysis of the interaction among these modules showed that there was a high scale independence degree among them. The GO and KEGG enrichment analyses showed that there was a significant difference in the enriched terms and degree among these eight modules, and module 5 was identified as the most important module. Besides, the pathways it was enriched in, hsa04510: Focal adhesion and hsa04610: Complement and coagulation cascades, were determined as the most important pathways. In summary, module 5 and the pathways it was enriched in, hsa04510: Focal adhesion and has 04610: Complement and coagulation cascades, have the potential to serve as biomarkers for patients with glioma.     

基于双聚类挖掘癌症共享的基因功能模块

基因多效性是癌症遗传机制中的普遍现象, 但罕见系统性的分析。文章提出采用双聚类挖掘基因功能模块的新思路探索癌症的共享分子机制和不同癌症间的关系。获取20种癌症的基因表达数据, 应用改良t检验和倍数法筛选出至少在两种癌症中差异表达的基因, 得到10417×20的数据矩阵; 采用双聚类方法获得22个癌症共享的基因簇; 进一步富集分析得到17个基因功能模块(Bonferroni校正后P<0.05), 主要参与有丝分裂染色单体分离的调控、细胞分化、免疫和炎症反应、胶原纤维组织等生物过程; 主要执行ATP结合和微管活动、MHCⅡ类受体活性、肽链内切酶抑制活性等分子功能; 活动区域主要在细胞骨架、染色体、MHCⅡ蛋白质复合体、中间丝蛋白、胶原纤维等。基于模块构建癌症相关网络, 显示胃癌、卵巢腺癌、宫颈鳞癌和间皮瘤等之间相关程度较高, 而两种血液系统癌症(急性髓细胞性白血病与多发性骨髓瘤)分子机制与其他癌症存在较大差异。可见癌症共享的基因功能模块与多种生物机制有关, 癌症之间相似性可能与组织起源、共同的致癌机制等有关。文章提出的基因多效性分析方法有助于解释人类复杂性疾病的共享分子机制。     

Selection for distinct gene expression properties favours the evolution of mutational robustness in gene regulatory networks

Mutational robustness is a genotype's tendency to keep a phenotypic trait with little and few changes in the face of mutations. Mutational robustness is both ubiquitous and evolutionarily important as it affects in different ways the probability that new phenotypic variation arises. Understanding the origins of robustness is specially relevant for systems of development that are phylogenetically widespread and that construct phenotypic traits with a strong impact on fitness. Gene regulatory networks are examples of this class of systems. They comprise sets of genes that, through cross‐regulation, build the gene activity patterns that define cellular responses, different tissues or distinct cell types. Several empirical observations, such as a greater robustness of wild‐type phenotypes, suggest that stabilizing selection underlies the evolution of mutational robustness. However, the role of selection in the evolution of robustness is still under debate. Computer simulations of the dynamics and evolution of gene regulatory networks have shown that selection for any gene activity pattern that is steady and self‐sustaining is sufficient to promote the evolution of mutational robustness. Here, I generalize this scenario using a computational model to show that selection for different aspects of a gene activity phenotype increases mutational robustness. Mutational robustness evolves even when selection favours properties that conflict with the stationarity of a gene activity pattern. The results that I present support an important role for stabilizing selection in the evolution of robustness in gene regulatory networks.     

Variation and evolution of biomolecular systems: searching for functional relevance

The availability of genome sequences and functional genomics data from multiple species enables us to compare the composition of biomolecular systems like biochemical pathways and protein complexes between species. Here, we review small- and large-scale, "genomics-based" approaches to biomolecular systems variation. In general, caution is required when comparing the results of bioinformatics analyses of genomes or of functional genomics data between species. Limitations to the sensitivity of sequence analysis tools and the noisy nature of genomics data tend to lead to systematic overestimates of the amount of variation. Nevertheless, the results from detailed manual analyses, and of large-scale analyses that filter out systematic biases, point to a large amount of variation in the composition of biomolecular systems. Such observations challenge our understanding of the function of the systems and their individual components and can potentially facilitate the identification and functional characterization of sub-systems within a system. Mapping the inter-species variation of complex biomolecular systems on a phylogenetic species tree allows one to reconstruct their evolution.     

Synthetic circuits reveal how mechanisms of gene regulatory networks constrain evolution

Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such biases are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most pertinent evidence is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in Escherichia coli that produce a gene expression stripe—a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.     

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 data into a mechanistic understanding of cancer. Here we present a method for finding gene functional modules of cancer from microarray data and have applied it to colon cancer. First, a colon cancer gene network and a normal colon tissue gene network were constructed using correlations between the genes. Then the modules that tended to have a homogeneous functional composition were identified by splitting up the network. Analysis of both networks revealed that they are scale-free. Comparison of the gene functional modules for colon cancer and normal tissues showed that the modules＇ functions changed with their structures.