Structural Controllability of Complex Networks Based on Preferential Matching

Minimum driver node sets (MDSs) play an important role in studying the structural controllability of complex networks. Recent research has shown that MDSs tend to avoid high-degree nodes. However, this observation is based on the analysis of a small number of MDSs, because enumerating all of the MDSs of a network is a #P problem. Therefore, past research has not been sufficient to arrive at a convincing conclusion. In this paper, first, we propose a preferential matching algorithm to find MDSs that have a specific degree property. Then, we show that the MDSs obtained by preferential matching can be composed of high- and medium-degree nodes. Moreover, the experimental results also show that the average degree of the MDSs of some networks tends to be greater than that of the overall network, even when the MDSs are obtained using previous research method. Further analysis shows that whether the driver nodes tend to be high-degree nodes or not is closely related to the edge direction of the network.     

The evolutionary scrambling and developmental unscrambling of germline genes in hypotrichous ciliates.

Genes in the germline (micronuclear) genome of hypotrichous ciliates are interrupted by multiple, short, non-coding, AT-rich sequences called internal eliminated segments, or IESs. During conversion of a micronucleus to a somatic nucleus (macronucleus) after cell mating, all IESs are excised from the germline genes and the gene segments, called macronuclear-destined segments, or MDSs, are spliced. Excision of the approximately 150 000 IESs from a haploid germline genome in Oxytricha nova requires approximately 150 000 recombinant events. In three of 10 genes the MDSs are scrambled. During macronuclear development the MDSs are unscrambled, possibly by folding of the DNA to allow MDSs to ligate in the correct order. The nine MDSs in the actin I gene of O.nova are scrambled in the random order, 3-4-6-5-7-9-2-1-8, and MDS 2 is inverted. The 14 MDSs in the alphaTP gene of O.nova and Stylonychia mytilus are scrambled in the non-random order, 1-3-5-7-9-11-2-4-6-8-10-12-13-14. The 45 MDSs in the DNA pol alpha gene are non-randomly scrambled into an odd/even series, with an inversion of one-third of the gene. Additional IESs have been inserted into these three genes during evolution of Oxytricha trifallax, slightly modifying scrambling patterns. The non-random scrambled patterns in the alphaTP and DNA pol alpha genes are explained by multiple, simultaneous IES insertions. The randomly scrambled pattern in the actin I gene may arise from an initially non-randomly scrambled pattern by recombination among multiple IESs. Alternatively, IESs inserted sporadically (individually) in a non-scrambled configuration might subsequently recombine, converting a non-scrambled gene into a randomly scrambled one. IESs shift along a DNA molecule, most likely as a result of mutations at MDS/IES junctions. Shifting of IESs has the effect of 'transferring' nucleotides from one MDS to another, but does not change the overall sequence of nucleotides in the combined MDSs. In addition to shifting in position, IESs accumulate mutations at a high rate and increase and decrease in length within a species and during speciation. The phenomena of IESs and of MDS scrambling represent remarkable flexibility of the hypotrich genome, possibly reflecting a process of MDS shuffling that facilitates the evolution of genes.     

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network(interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy(IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.     

尖毛虫属Actin Ⅰ、α-TBP和DNA pol α乱序基因的模式研究

研究旨在对尖毛虫属内现有物种的3种乱序小核基因结构进行比较,探讨其乱序模式。于湛江湖光红树林水域中采集到一个尖毛虫属物种Oxytricha sp.（ZJ）,成功扩增了其肌动蛋白Ⅰ（ActinⅠ）、端粒结合蛋白（α-TBP）、DNA聚合酶α（DNA pol α）3个乱序基因的完整大核基因序列和完整/部分小核基因序列,并结合已有资料对比研究了尖毛虫属这3个乱序基因的进化。结果表明:（1）Oxytricha sp.（ZJ）与O.nova的小核Actin Ⅰ基因具有相同的乱序模式,区别于其余的尖毛虫属物种;在增加尖毛虫属物种的基础上,对前人推测提出了质疑,我们认为MDS-IES接合处移动现象在乱序MDSs之间并非比非乱序MDSs之间更保守。（2）Oxytricha sp.（ZJ）与O.nova的小核α-TBP基因具有相同乱序模式和相似长度的IESs。（3）Oxytricha sp.（ZJ）的小核DNA pol α基因乱序模式,区别于任一已报道物种,与属内O. trifallax最为相近。基于序列分析,在DNA pol α基因中发现了一例IES转换为MDS的痕迹,以及由此导致原先MDS的丢失。研究发现在编码区内IES向MDS的转变,使得本应删除的序列成为基因组永久保留的一部分。     

The germline gene encoding DNA polymerase alpha in the hypotrichous ciliate Oxytricha nova is extremely scrambled.

We report the structure of the micronuclear (germline) gene encoding the large catalytic subunit of DNA polymerase alpha (DNA pol alpha) in the ciliate Oxytricha nova. It contains 44 internal eliminated segments (IESs) that divide the gene into 45 macronuclear-destined segments (MDSs) that are in a non-randomly scrambled order with an inversion near the gene center. Odd numbered MDSs 29-43, containing 230 bp out of a total of 4938 bp of macronuclear sequence, are missing from the 14 kb cloned gene. The missing MDSs have not been located but are at least several kilobases from the main body of the gene. The remarkably scrambled DNA pol alpha gene must be extensively cut, re-ordered and spliced and an inversion must occur to produce an unscrambled, functional version of the gene during development of a new macronucleus. Unscrambling is hypothesized to occur by a homologous recombination mechanism guided by repeat sequences at MDS ends.     

Saccharomyces cerevisiae-based system for studying clustered DNA damages

DNA-damaging agents can induce clustered lesions or multiply damaged sites (MDSs) on the same or opposing DNA strands. In the latter, attempts to repair MDS can generate closely opposed single-strand break intermediates that may convert non-lethal or mutagenic base damage into double-strand breaks (DSBs). We constructed a diploid S. cerevisiae yeast strain with a chromosomal context targeted by integrative DNA fragments carrying different damages to determine whether closely opposed base damages are converted to DSBs following the outcomes of the homologous recombination repair pathway. As a model of MDS, we studied clustered uracil DNA damages with a known location and a defined distance separating the lesions. The system we describe might well be extended to assessing the repair of MDSs with different compositions, and to most of the complex DNA lesions induced by physical and chemical agents.     

DNA repair of clustered uracils in HeLa cells

Two or more base damages, abasic sites or single-strand breaks (SSBs) within two helical turns of the DNA form a multiply damaged site (MDS) or clustered lesion. Studies in vitro and in bacteria indicate that attempts to repair two closely opposed base lesions can potentially form a lethal double-strand break (DSB). Ionizing radiation and chemotherapeutic agents introduce complex lesions, and the inability of a cell to repair MDSs is believed to contribute to the lethality of these treatments. The goal of this work was to extend the in vitro studies by examining MDS repair in mammalian cells under physiological conditions. Here, two opposing uracil residues separated by 3, 5, 7, 13 or 29 base-pairs were chosen as model DNA lesions. Double-stranded oligonucleotides containing no damage, a single uracil residue or the MDS were introduced into a non-replicating mammalian construct within the firefly luciferase open reading frame, or at the 5' or 3' end of the luciferase expression cassette. Following transient transfection into HeLa cells, luciferase activity was measured or plasmid DNA was re-isolated from the cells. Formation of a DSB was expected to decrease luciferase expression. However, certain single uracil residues as well as the MDSs decreased luciferase activity, which suggested that the reduction in activity was not due to DSB formation. In fact, Southern analysis of the re-isolated plasmid did not show the presence of linear DNA and demonstrated that none of the constructs was destroyed during repair. Further analysis of the re-isolated DNA demonstrated that only a small percentage of molecules originally carrying a single lesion or an MDS contained deletions. This work indicates that the majority of the clustered lesions were not converted to DSBs and that repair systems in mammalian cells may have established mechanisms to avoid the accumulation of SSB-repair intermediates.     

Evolution of internal eliminated segments and scrambling in the micronuclear gene encoding DNA polymerase alpha in two Oxytricha species.

To learn about the evolution of internal eliminated segments (IESs) and gene scrambling in hypotrichous ciliates we determined the structure of the micronuclear (germline) gene encoding DNA polymerasealpha(DNA polalpha) in Oxytricha trifallax and compared it to the previously published structure of the germline DNA polalphagene in Oxytricha nova . The DNA polalphagene of O.trifallax contains 51 macronuclear-destined segments (MDSs) separated by 50 IESs, compared to 45 MDSs and 44 IESs in the O.nova gene. This means that IESs and MDSs have been gained and/or lost during evolutionary divergence of the two species. Most of the MDSs are highly scrambled in a similar non-random pattern in the two species. We present a model to explain how IESs, non-scrambled MDSs and scrambled MDSs may be added and/or eliminated during evolution. Corresponding IESs in the two species differ totally in sequence, and junctions between MDSs and IESs are shifted by 1-18 bp in O.trifallax compared to the O.nova gene. In both species a short region of the gene is distantly separated from the main part of the gene. Comparison of the gene in the two species shows that IESs and scrambling are highly malleable over evolutionary time.     

Protein modeling,molecular network and molecular dynamics study of newly sequenced interleukin-18 (IL-18) gene in Mus musculus

Interleukin-18 (IL-18) belongs to the superfamily of IL-1 protein and exerts a pleiotropic pro-inflammatory effect on the body. Generally, this protein is significantly involved in immune defense during infection in cells, but sometimes its anomalous activities produce some inflammatory diseases like rheumatoid arthritis and Crohn’s disease. In the present study, the IL-18 gene was isolated from mice and was subsequently cloned and sequenced. Further, the network analysis was carried out to explore the functional role of IL-18 protein in animals. The 3D protein structure of the IL-18 protein was generated and docked with appropriate 3-([3-cholamidopropyl]dimethylammonio)-1-propanesulfonate (CPS) ligand. Later the complex structure of the protein was subjected to molecular dynamics simulation (MDS) for 50 ns to determine the effect of ligand on protein. The network analysis explored the correlation of IL-18 protein with others proteins and their involvement in the different significant pathway to defend the cell from various diseases. As confirmed by MDS, the CPS:IL-18 complex was found to be highly stable. Our results further indicated that CPS ligand has the potential to act as a drug molecule, in future, for counteracting IL-18 activity. To date, no structural details were available for animal IL-18. Hence, the finding of this study will be useful in broadening the horizon towards a better understanding of the functional and structural aspects of IL-18 in animals.     

Bmi-1基因表达在骨髓增生异常综合征中的临床意义

目的:探讨Bmi-1基因表达在骨髓增生异常综合征(MDS)中的临床意义。方法:选择2011年1月~2012年12月我院收治的MDS患者41例为研究组,另选取非恶性血液病患者20例为对照组,检测Bmi-1的表达水平,并检测其骨髓白血病干细胞免疫表型(CD34+CD38-CD123+),然后分析患者Bmi-1的表达水平与骨髓原始细胞比例及骨髓染色体核型的关系。结果:Bmi-1表达水平研究组患者明显高于对照组,且研究组中RA患者明显低于RAEB患者,但RA患者及RAEB患者均高于对照组(P0.01);Bmi-1基因高表达组白血病干细胞免疫表型CD34+CD38-CD123+/CD34+明显高于Bmi-1基因低表达组患者(P0.01);Bmi-1基因高表达组中,骨髓原始细胞5%的病例数及染色体不良核型发生率均高于低表达组。结论:Bmi-1基因的表达可以作为MDS患者在分子水平上的恶性程度标志之一。     

Modelling the evolution of genetic regulatory networks

An evolutionary model of genetic regulatory networks is developed, based on a model of network encoding and dynamics called the Artificial Genome (AG). This model derives a number of specific genes and their interactions from a string of (initially random) bases in an idealized manner analogous to that employed by natural DNA. The gene expression dynamics are determined by updating the gene network as if it were a simple Boolean network. The generic behaviour of the AG model is investigated in detail. In particular, we explore the characteristic network topologies generated by the model, their dynamical behaviours, and the typical variance of network connectivities and network structures. These properties are demonstrated to agree with a probabilistic analysis of the model, and the typical network structures generated by the model are shown to lie between those of random networks and scale-free networks in terms of their degree distribution. Evolutionary processes are simulated using a genetic algorithm, with selection acting on a range of properties from gene number and degree of connectivity through periodic behaviour to specific patterns of gene expression. The evolvability of increasingly complex patterns of gene expression is examined in detail. When a degree of redundancy is introduced, the average number of generations required to evolve given targets is reduced, but limits on evolution of complex gene expression patterns remain. In addition, cyclic gene expression patterns with periods that are multiples of shorter expression patterns are shown to be inherently easier to evolve than others. Constraints imposed by the template-matching nature of the AG model generate similar biases towards such expression patterns in networks in initial populations, in addition to the somewhat scale-free nature of these networks. The significance of these results on current understanding of biological evolution is discussed.     

Network Properties of Complex Human Disease Genes Identified through Genome-Wide Association Studies

Background

Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs), thereby eliminating discovery bias.

Principal findings

We derived a network of complex diseases (n = 54) and complex disease genes (n = 349) to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process.

Conclusions

This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.     

Aberrant Dendritic Excitability: A Common Pathophysiology in CNS Disorders Affecting Memory?

Discovering the etiology of pathophysiologies and aberrant behavior in many central nervous system (CNS) disorders has proven elusive because susceptibility to these diseases can be a product of multiple factors such as genetics, epigenetics, and environment. Advances in molecular biology and wide-scale genomics have shown that a large heterogeneity of genetic mutations are potentially responsible for the neuronal pathologies and dysfunctional behaviors seen in CNS disorders. Despite this seemingly complex array of genetic and physiological factors, many disorders of the CNS converge on common dysfunctions in memory. In this review, we propose that mechanisms underlying the development of many CNS disorders may share an underlying cause involving abnormal dendritic integration of synaptic signals. Through understanding the relationship between molecular genetics and dendritic computation, future research may uncover important links between neuronal physiology at the cellular level and higher-order circuit and network abnormalities observed in CNS disorders, and their subsequent affect on memory.     

A network analysis of the human T-cell activation gene network identifies JAGGED1 as a therapeutic target for autoimmune diseases

Understanding complex diseases will benefit the recognition of the properties of the gene networks that control biological functions. Here, we set out to model the gene network that controls T-cell activation in humans, which is critical for the development of autoimmune diseases such as Multiple Sclerosis (MS). The network was established on the basis of the quantitative expression from 104 individuals of 20 genes of the immune system, as well as on biological information from the Ingenuity database and Bayesian inference. Of the 31 links (gene interactions) identified in the network, 18 were identified in the Ingenuity database and 13 were new and we validated 7 of 8 interactions experimentally. In the MS patients network, we found an increase in the weight of gene interactions related to Th1 function and a decrease in those related to Treg and Th2 function. Indeed, we found that IFN-ss therapy induces changes in gene interactions related to T cell proliferation and adhesion, although these gene interactions were not restored to levels similar to controls. Finally, we identify JAG1 as a new therapeutic target whose differential behaviour in the MS network was not modified by immunomodulatory therapy. In vitro treatment with a Jagged1 agonist peptide modulated the T-cell activation network in PBMCs from patients with MS. Moreover, treatment of mice with experimental autoimmune encephalomyelitis with the Jagged1 agonist ameliorated the disease course, and modulated Th2, Th1 and Treg function. This study illustrates how network analysis can predict therapeutic targets for immune intervention and identified the immunomodulatory properties of Jagged1 making it a new therapeutic target for MS and other autoimmune diseases.     

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Multi-organ whole-genome measurements and reverse engineering to uncover gene networks underlying complex traits

Together with computational analysis and modeling, the development of whole-genome measurement technologies holds the potential to fundamentally change research on complex disorders such as coronary artery disease. With these tools, the stage has been set to reveal the full repertoire of biological components (genes, proteins, and metabolites) in complex diseases and their interplay in modules and networks. Here we review how network identification based on reverse engineering, as applied to whole-genome datasets from simpler organisms, is now being adapted to more complex settings such as datasets from human cell lines and organs in relation to physiological and pathological states. Our focus is on the use of a systems biological approach to identify gene networks in coronary atherosclerosis. We also address how gene networks will probably play a key role in the development of early diagnostics and treatments for complex disorders in the coming era of individualized medicine.     

Codependency and mutual exclusivity for gene community detection from sparse single-cell transcriptome data

Single-cell RNA-seq (scRNA-seq) can be used to characterize cellular heterogeneity in thousands of cells. The reconstruction of a gene network based on coexpression patterns is a fundamental task in scRNA-seq analyses, and the mutual exclusivity of gene expression can be critical for understanding such heterogeneity. Here, we propose an approach for detecting communities from a genetic network constructed on the basis of coexpression properties. The community-based comparison of multiple coexpression networks enables the identification of functionally related gene clusters that cannot be fully captured through differential gene expression-based analysis. We also developed a novel metric referred to as the exclusively expressed index (EEI) that identifies mutually exclusive gene pairs from sparse scRNA-seq data. EEI quantifies and ranks the exclusive expression levels of all gene pairs from binary expression patterns while maintaining robustness against a low sequencing depth. We applied our methods to glioblastoma scRNA-seq data and found that gene communities were partially conserved after serum stimulation despite a considerable number of differentially expressed genes. We also demonstrate that the identification of mutually exclusive gene sets with EEI can improve the sensitivity of capturing cellular heterogeneity. Our methods complement existing approaches and provide new biological insights, even for a large, sparse dataset, in the single-cell analysis field.     

Characterization of the hemopoietic defect in early stages of the myelodysplastic syndromes

Myelodysplasia (MDS) is a heterogeneous disorder characterised by bone marrow failure and progression to acute myeloid leukaemia where the molecular and cellular haematopoietic defects are poorly understood. To gain insight into this the pathogenesis of this condition, we analyzed gene expression profiles of bone marrow CD34⁺ stem/progenitor cells from patients with MDS at a early stage in the disease and compared them with profiles from CD34⁺ cells from age-matched controls and patients with non-MDS anaemia. Given the heterogeneity of early MDS, a surprisingly consistent finding was decreased expression of B-cell lineage affiliated genes in MDS patients compared to normal controls and samples with non-MDS anaemia. These findings were then confirmed in the original samples and further samples from a new MDS patient group by Taqman Real Time PCR. Flow cytometry on unfractionated marrow from independent samples also demonstrated reduced B-cell progenitors in MDS patients compared to normal controls. These novel findings suggest a common perturbation in early MDS haematopoiesis. They also provide the rationale for a larger study to evaluate the diagnostic utility of reduced B-cell progenitor number as a diagnostic biomarker of early low risk MDS which can pose a diagnostic challenge.