Persistence drives gene clustering in bacterial genomes

Directory of Open Access Journals (Sweden)

Rocha Eduardo PC

2008-01-01

Full Text Available Abstract Background Gene clustering plays an important role in the organization of the bacterial chromosome and several mechanisms have been proposed to explain its extent. However, the controversies raised about the validity of each of these mechanisms remind us that the cause of this gene organization remains an open question. Models proposed to explain clustering did not take into account the function of the gene products nor the likely presence or absence of a given gene in a genome. However, genomes harbor two very different categories of genes: those genes present in a majority of organisms – persistent genes – and those present in very few organisms – rare genes. Results We show that two classes of genes are significantly clustered in bacterial genomes: the highly persistent and the rare genes. The clustering of rare genes is readily explained by the selfish operon theory. Yet, genes persistently present in bacterial genomes are also clustered and we try to understand why. We propose a model accounting specifically for such clustering, and show that indispensability in a genome with frequent gene deletion and insertion leads to the transient clustering of these genes. The model describes how clusters are created via the gene flux that continuously introduces new genes while deleting others. We then test if known selective processes, such as co-transcription, physical interaction or functional neighborhood, account for the stabilization of these clusters. Conclusion We show that the strong selective pressure acting on the function of persistent genes, in a permanent state of flux of genes in bacterial genomes, maintaining their size fairly constant, that drives persistent genes clustering. A further selective stabilization process might contribute to maintaining the clustering.

Inactivation of human α-globin gene expression by a de novo deletion located upstream of the α-globin gene cluster

International Nuclear Information System (INIS)

Liebhaber, S.A.; Weiss, I.; Cash, F.E.; Griese, E.U.; Horst, J.; Ayyub, H.; Higgs, D.R.

1990-01-01

Synthesis of normal human hemoglobin A, α 2 β 2 , is based upon balanced expression of genes in the α-globin gene cluster on chromosome 15 and the β-globin gene cluster on chromosome 11. Full levels of erythroid-specific activation of the β-globin cluster depend on sequences located at a considerable distance 5' to the β-globin gene, referred to as the locus-activating or dominant control region. The existence of an analogous element(s) upstream of the α-globin cluster has been suggested from observations on naturally occurring deletions and experimental studies. The authors have identified an individual with α-thalassemia in whom structurally normal α-globin genes have been inactivated in cis by a discrete de novo 35-kilobase deletion located ∼30 kilobases 5' from the α-globin gene cluster. They conclude that this deletion inactivates expression of the α-globin genes by removing one or more of the previously identified upstream regulatory sequences that are critical to expression of the α-globin genes

Identification of nitrogen-fixing genes and gene clusters from metagenomic library of acid mine drainage.

Directory of Open Access Journals (Sweden)

Zhimin Dai

Full Text Available Biological nitrogen fixation is an essential function of acid mine drainage (AMD microbial communities. However, most acidophiles in AMD environments are uncultured microorganisms and little is known about the diversity of nitrogen-fixing genes and structure of nif gene cluster in AMD microbial communities. In this study, we used metagenomic sequencing to isolate nif genes in the AMD microbial community from Dexing Copper Mine, China. Meanwhile, a metagenome microarray containing 7,776 large-insertion fosmids was constructed to screen novel nif gene clusters. Metagenomic analyses revealed that 742 sequences were identified as nif genes including structural subunit genes nifH, nifD, nifK and various additional genes. The AMD community is massively dominated by the genus Acidithiobacillus. However, the phylogenetic diversity of nitrogen-fixing microorganisms is much higher than previously thought in the AMD community. Furthermore, a 32.5-kb genomic sequence harboring nif, fix and associated genes was screened by metagenome microarray. Comparative genome analysis indicated that most nif genes in this cluster are most similar to those of Herbaspirillum seropedicae, but the organization of the nif gene cluster had significant differences from H. seropedicae. Sequence analysis and reverse transcription PCR also suggested that distinct transcription units of nif genes exist in this gene cluster. nifQ gene falls into the same transcription unit with fixABCX genes, which have not been reported in other diazotrophs before. All of these results indicated that more novel diazotrophs survive in the AMD community.

Identification of nitrogen-fixing genes and gene clusters from metagenomic library of acid mine drainage.

Science.gov (United States)

Dai, Zhimin; Guo, Xue; Yin, Huaqun; Liang, Yili; Cong, Jing; Liu, Xueduan

2014-01-01

Biological nitrogen fixation is an essential function of acid mine drainage (AMD) microbial communities. However, most acidophiles in AMD environments are uncultured microorganisms and little is known about the diversity of nitrogen-fixing genes and structure of nif gene cluster in AMD microbial communities. In this study, we used metagenomic sequencing to isolate nif genes in the AMD microbial community from Dexing Copper Mine, China. Meanwhile, a metagenome microarray containing 7,776 large-insertion fosmids was constructed to screen novel nif gene clusters. Metagenomic analyses revealed that 742 sequences were identified as nif genes including structural subunit genes nifH, nifD, nifK and various additional genes. The AMD community is massively dominated by the genus Acidithiobacillus. However, the phylogenetic diversity of nitrogen-fixing microorganisms is much higher than previously thought in the AMD community. Furthermore, a 32.5-kb genomic sequence harboring nif, fix and associated genes was screened by metagenome microarray. Comparative genome analysis indicated that most nif genes in this cluster are most similar to those of Herbaspirillum seropedicae, but the organization of the nif gene cluster had significant differences from H. seropedicae. Sequence analysis and reverse transcription PCR also suggested that distinct transcription units of nif genes exist in this gene cluster. nifQ gene falls into the same transcription unit with fixABCX genes, which have not been reported in other diazotrophs before. All of these results indicated that more novel diazotrophs survive in the AMD community.

Identification of Nitrogen-Fixing Genes and Gene Clusters from Metagenomic Library of Acid Mine Drainage

Science.gov (United States)

Yin, Huaqun; Liang, Yili; Cong, Jing; Liu, Xueduan

2014-01-01

Biological nitrogen fixation is an essential function of acid mine drainage (AMD) microbial communities. However, most acidophiles in AMD environments are uncultured microorganisms and little is known about the diversity of nitrogen-fixing genes and structure of nif gene cluster in AMD microbial communities. In this study, we used metagenomic sequencing to isolate nif genes in the AMD microbial community from Dexing Copper Mine, China. Meanwhile, a metagenome microarray containing 7,776 large-insertion fosmids was constructed to screen novel nif gene clusters. Metagenomic analyses revealed that 742 sequences were identified as nif genes including structural subunit genes nifH, nifD, nifK and various additional genes. The AMD community is massively dominated by the genus Acidithiobacillus. However, the phylogenetic diversity of nitrogen-fixing microorganisms is much higher than previously thought in the AMD community. Furthermore, a 32.5-kb genomic sequence harboring nif, fix and associated genes was screened by metagenome microarray. Comparative genome analysis indicated that most nif genes in this cluster are most similar to those of Herbaspirillum seropedicae, but the organization of the nif gene cluster had significant differences from H. seropedicae. Sequence analysis and reverse transcription PCR also suggested that distinct transcription units of nif genes exist in this gene cluster. nifQ gene falls into the same transcription unit with fixABCX genes, which have not been reported in other diazotrophs before. All of these results indicated that more novel diazotrophs survive in the AMD community. PMID:24498417

Evolutionary conservation of regulatory elements in vertebrate HOX gene clusters

Energy Technology Data Exchange (ETDEWEB)

Santini, Simona; Boore, Jeffrey L.; Meyer, Axel

2003-12-31

Due to their high degree of conservation, comparisons of DNA sequences among evolutionarily distantly-related genomes permit to identify functional regions in noncoding DNA. Hox genes are optimal candidate sequences for comparative genome analyses, because they are extremely conserved in vertebrates and occur in clusters. We aligned (Pipmaker) the nucleotide sequences of HoxA clusters of tilapia, pufferfish, striped bass, zebrafish, horn shark, human and mouse (over 500 million years of evolutionary distance). We identified several highly conserved intergenic sequences, likely to be important in gene regulation. Only a few of these putative regulatory elements have been previously described as being involved in the regulation of Hox genes, while several others are new elements that might have regulatory functions. The majority of these newly identified putative regulatory elements contain short fragments that are almost completely conserved and are identical to known binding sites for regulatory proteins (Transfac). The conserved intergenic regions located between the most rostrally expressed genes in the developing embryo are longer and better retained through evolution. We document that presumed regulatory sequences are retained differentially in either A or A clusters resulting from a genome duplication in the fish lineage. This observation supports both the hypothesis that the conserved elements are involved in gene regulation and the Duplication-Deletion-Complementation model.

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

Science.gov (United States)

Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

2015-09-01

We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering

Directory of Open Access Journals (Sweden)

Markatou Marianthi

2011-01-01

Full Text Available Abstract Background The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation, but the signaling mechanisms between irradiated and non-irradiated bystander cells are not fully understood. In this study, we measured a time-series of gene expression after α-particle irradiation and applied the Feature Based Partitioning around medoids Algorithm (FBPA, a new clustering method suitable for sparse time series, to identify signaling modules that act in concert in the response to direct irradiation and bystander signaling. We compared our results with those of an alternate clustering method, Short Time series Expression Miner (STEM. Results While computational evaluations of both clustering results were similar, FBPA provided more biological insight. After irradiation, gene clusters were enriched for signal transduction, cell cycle/cell death and inflammation/immunity processes; but only FBPA separated clusters by function. In bystanders, gene clusters were enriched for cell communication/motility, signal transduction and inflammation processes; but biological functions did not separate as clearly with either clustering method as they did in irradiated samples. Network analysis confirmed p53 and NF-κB transcription factor-regulated gene clusters in irradiated and bystander cells and suggested novel regulators, such as KDM5B/JARID1B (lysine (K-specific demethylase 5B and HDACs (histone deacetylases, which could epigenetically coordinate gene expression after irradiation. Conclusions In this study, we have shown that a new time series clustering method, FBPA, can provide new leads to the mechanisms regulating the dynamic cellular response to radiation. The findings implicate epigenetic control of gene expression in addition to transcription factor networks.

A scale invariant clustering of genes on human chromosome 7

Directory of Open Access Journals (Sweden)

Kendal Wayne S

2004-01-01

Full Text Available Abstract Background Vertebrate genes often appear to cluster within the background of nontranscribed genomic DNA. Here an analysis of the physical distribution of gene structures on human chromosome 7 was performed to confirm the presence of clustering, and to elucidate possible underlying statistical and biological mechanisms. Results Clustering of genes was confirmed by virtue of a variance of the number of genes per unit physical length that exceeded the respective mean. Further evidence for clustering came from a power function relationship between the variance and mean that possessed an exponent of 1.51. This power function implied that the spatial distribution of genes on chromosome 7 was scale invariant, and that the underlying statistical distribution had a Poisson-gamma (PG form. A PG distribution for the spatial scattering of genes was validated by stringent comparisons of both the predicted variance to mean power function and its cumulative distribution function to data derived from chromosome 7. Conclusion The PG distribution was consistent with at least two different biological models: In the microrearrangement model, the number of genes per unit length of chromosome represented the contribution of a random number of smaller chromosomal segments that had originated by random breakage and reconstruction of more primitive chromosomes. Each of these smaller segments would have necessarily contained (on average a gamma distributed number of genes. In the gene cluster model, genes would be scattered randomly to begin with. Over evolutionary timescales, tandem duplication, mutation, insertion, deletion and rearrangement could act at these gene sites through a stochastic birth death and immigration process to yield a PG distribution. On the basis of the gene position data alone it was not possible to identify the biological model which best explained the observed clustering. However, the underlying PG statistical model implicated neutral

A 6-gene signature identifies four molecular subgroups of neuroblastoma

LENUS (Irish Health Repository)

Abel, Frida

2011-04-14

Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and\\/or dead of disease, p < 0.05, Fisher\\'s exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group\\'s specific characteristics.

Global Analysis of miRNA Gene Clusters and Gene Families Reveals Dynamic and Coordinated Expression

Directory of Open Access Journals (Sweden)

Li Guo

2014-01-01

Full Text Available To further understand the potential expression relationships of miRNAs in miRNA gene clusters and gene families, a global analysis was performed in 4 paired tumor (breast cancer and adjacent normal tissue samples using deep sequencing datasets. The compositions of miRNA gene clusters and families are not random, and clustered and homologous miRNAs may have close relationships with overlapped miRNA species. Members in the miRNA group always had various expression levels, and even some showed larger expression divergence. Despite the dynamic expression as well as individual difference, these miRNAs always indicated consistent or similar deregulation patterns. The consistent deregulation expression may contribute to dynamic and coordinated interaction between different miRNAs in regulatory network. Further, we found that those clustered or homologous miRNAs that were also identified as sense and antisense miRNAs showed larger expression divergence. miRNA gene clusters and families indicated important biological roles, and the specific distribution and expression further enrich and ensure the flexible and robust regulatory network.

Transcriptional regulation of gene expression clusters in motor neurons following spinal cord injury

Directory of Open Access Journals (Sweden)

Westerdahl Ann-Charlotte

2010-06-01

Full Text Available Abstract Background Spinal cord injury leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems. Increased excitability of motor neurons has been implicated in injury-induced spasticity, where the reappearance of self-sustained plateau potentials in the absence of modulatory inputs from the brain correlates with the development of spasticity. Results Here we examine the dynamic transcriptional response of motor neurons to spinal cord injury as it evolves over time to unravel common gene expression patterns and their underlying regulatory mechanisms. For this we use a rat-tail-model with complete spinal cord transection causing injury-induced spasticity, where gene expression profiles are obtained from labeled motor neurons extracted with laser microdissection 0, 2, 7, 21 and 60 days post injury. Consensus clustering identifies 12 gene clusters with distinct time expression profiles. Analysis of these gene clusters identifies early immunological/inflammatory and late developmental responses as well as a regulation of genes relating to neuron excitability that support the development of motor neuron hyper-excitability and the reappearance of plateau potentials in the late phase of the injury response. Transcription factor motif analysis identifies differentially expressed transcription factors involved in the regulation of each gene cluster, shaping the expression of the identified biological processes and their associated genes underlying the changes in motor neuron excitability. Conclusions This analysis provides important clues to the underlying mechanisms of transcriptional regulation responsible for the increased excitability observed in motor neurons in the late chronic phase of spinal cord injury suggesting alternative targets for treatment of spinal cord injury. Several transcription factors were identified as potential regulators of gene clusters containing elements related to motor neuron hyper

Transcriptional regulation of gene expression clusters in motor neurons following spinal cord injury.

Science.gov (United States)

Ryge, Jesper; Winther, Ole; Wienecke, Jacob; Sandelin, Albin; Westerdahl, Ann-Charlotte; Hultborn, Hans; Kiehn, Ole

2010-06-09

Spinal cord injury leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems. Increased excitability of motor neurons has been implicated in injury-induced spasticity, where the reappearance of self-sustained plateau potentials in the absence of modulatory inputs from the brain correlates with the development of spasticity. Here we examine the dynamic transcriptional response of motor neurons to spinal cord injury as it evolves over time to unravel common gene expression patterns and their underlying regulatory mechanisms. For this we use a rat-tail-model with complete spinal cord transection causing injury-induced spasticity, where gene expression profiles are obtained from labeled motor neurons extracted with laser microdissection 0, 2, 7, 21 and 60 days post injury. Consensus clustering identifies 12 gene clusters with distinct time expression profiles. Analysis of these gene clusters identifies early immunological/inflammatory and late developmental responses as well as a regulation of genes relating to neuron excitability that support the development of motor neuron hyper-excitability and the reappearance of plateau potentials in the late phase of the injury response. Transcription factor motif analysis identifies differentially expressed transcription factors involved in the regulation of each gene cluster, shaping the expression of the identified biological processes and their associated genes underlying the changes in motor neuron excitability. This analysis provides important clues to the underlying mechanisms of transcriptional regulation responsible for the increased excitability observed in motor neurons in the late chronic phase of spinal cord injury suggesting alternative targets for treatment of spinal cord injury. Several transcription factors were identified as potential regulators of gene clusters containing elements related to motor neuron hyper-excitability, the manipulation of which potentially could be

Gene duplication, modularity and adaptation in the evolution of the aflatoxin gene cluster

Directory of Open Access Journals (Sweden)

Jakobek Judy L

2007-07-01

Full Text Available Abstract Background The biosynthesis of aflatoxin (AF involves over 20 enzymatic reactions in a complex polyketide pathway that converts acetate and malonate to the intermediates sterigmatocystin (ST and O-methylsterigmatocystin (OMST, the respective penultimate and ultimate precursors of AF. Although these precursors are chemically and structurally very similar, their accumulation differs at the species level for Aspergilli. Notable examples are A. nidulans that synthesizes only ST, A. flavus that makes predominantly AF, and A. parasiticus that generally produces either AF or OMST. Whether these differences are important in the evolutionary/ecological processes of species adaptation and diversification is unknown. Equally unknown are the specific genomic mechanisms responsible for ordering and clustering of genes in the AF pathway of Aspergillus. Results To elucidate the mechanisms that have driven formation of these clusters, we performed systematic searches of aflatoxin cluster homologs across five Aspergillus genomes. We found a high level of gene duplication and identified seven modules consisting of highly correlated gene pairs (aflA/aflB, aflR/aflS, aflX/aflY, aflF/aflE, aflT/aflQ, aflC/aflW, and aflG/aflL. With the exception of A. nomius, contrasts of mean Ka/Ks values across all cluster genes showed significant differences in selective pressure between section Flavi and non-section Flavi species. A. nomius mean Ka/Ks values were more similar to partial clusters in A. fumigatus and A. terreus. Overall, mean Ka/Ks values were significantly higher for section Flavi than for non-section Flavi species. Conclusion Our results implicate several genomic mechanisms in the evolution of ST, OMST and AF cluster genes. Gene modules may arise from duplications of a single gene, whereby the function of the pre-duplication gene is retained in the copy (aflF/aflE or the copies may partition the ancestral function (aflA/aflB. In some gene modules, the

A genomics based discovery of secondary metabolite biosynthetic gene clusters in Aspergillus ustus.

Directory of Open Access Journals (Sweden)

Borui Pi

Full Text Available Secondary metabolites (SMs produced by Aspergillus have been extensively studied for their crucial roles in human health, medicine and industrial production. However, the resulting information is almost exclusively derived from a few model organisms, including A. nidulans and A. fumigatus, but little is known about rare pathogens. In this study, we performed a genomics based discovery of SM biosynthetic gene clusters in Aspergillus ustus, a rare human pathogen. A total of 52 gene clusters were identified in the draft genome of A. ustus 3.3904, such as the sterigmatocystin biosynthesis pathway that was commonly found in Aspergillus species. In addition, several SM biosynthetic gene clusters were firstly identified in Aspergillus that were possibly acquired by horizontal gene transfer, including the vrt cluster that is responsible for viridicatumtoxin production. Comparative genomics revealed that A. ustus shared the largest number of SM biosynthetic gene clusters with A. nidulans, but much fewer with other Aspergilli like A. niger and A. oryzae. These findings would help to understand the diversity and evolution of SM biosynthesis pathways in genus Aspergillus, and we hope they will also promote the development of fungal identification methodology in clinic.

A Genomics Based Discovery of Secondary Metabolite Biosynthetic Gene Clusters in Aspergillus ustus

Science.gov (United States)

Pi, Borui; Yu, Dongliang; Dai, Fangwei; Song, Xiaoming; Zhu, Congyi; Li, Hongye; Yu, Yunsong

2015-01-01

Secondary metabolites (SMs) produced by Aspergillus have been extensively studied for their crucial roles in human health, medicine and industrial production. However, the resulting information is almost exclusively derived from a few model organisms, including A. nidulans and A. fumigatus, but little is known about rare pathogens. In this study, we performed a genomics based discovery of SM biosynthetic gene clusters in Aspergillus ustus, a rare human pathogen. A total of 52 gene clusters were identified in the draft genome of A. ustus 3.3904, such as the sterigmatocystin biosynthesis pathway that was commonly found in Aspergillus species. In addition, several SM biosynthetic gene clusters were firstly identified in Aspergillus that were possibly acquired by horizontal gene transfer, including the vrt cluster that is responsible for viridicatumtoxin production. Comparative genomics revealed that A. ustus shared the largest number of SM biosynthetic gene clusters with A. nidulans, but much fewer with other Aspergilli like A. niger and A. oryzae. These findings would help to understand the diversity and evolution of SM biosynthesis pathways in genus Aspergillus, and we hope they will also promote the development of fungal identification methodology in clinic. PMID:25706180

Identification, characterization and metagenome analysis of oocyte-specific genes organized in clusters in the mouse genome

Directory of Open Access Journals (Sweden)

Vaiman Daniel

2005-05-01

Full Text Available Abstract Background Genes specifically expressed in the oocyte play key roles in oogenesis, ovarian folliculogenesis, fertilization and/or early embryonic development. In an attempt to identify novel oocyte-specific genes in the mouse, we have used an in silico subtraction methodology, and we have focused our attention on genes that are organized in genomic clusters. Results In the present work, five clusters have been studied: a cluster of thirteen genes characterized by an F-box domain localized on chromosome 9, a cluster of six genes related to T-cell leukaemia/lymphoma protein 1 (Tcl1 on chromosome 12, a cluster composed of a SPErm-associated glutamate (E-Rich (Speer protein expressed in the oocyte in the vicinity of four unknown genes specifically expressed in the testis on chromosome 14, a cluster composed of the oocyte secreted protein-1 (Oosp-1 gene and two Oosp-related genes on chromosome 19, all three being characterized by a partial N-terminal zona pellucida-like domain, and another small cluster of two genes on chromosome 19 as well, composed of a TWIK-Related spinal cord K+ channel encoding-gene, and an unknown gene predicted in silico to be testis-specific. The specificity of expression was confirmed by RT-PCR and in situ hybridization for eight and five of them, respectively. Finally, we showed by comparing all of the isolated and clustered oocyte-specific genes identified so far in the mouse genome, that the oocyte-specific clusters are significantly closer to telomeres than isolated oocyte-specific genes are. Conclusion We have studied five clusters of genes specifically expressed in female, some of them being also expressed in male germ-cells. Moreover, contrarily to non-clustered oocyte-specific genes, those that are organized in clusters tend to map near chromosome ends, suggesting that this specific near-telomere position of oocyte-clusters in rodents could constitute an evolutionary advantage. Understanding the biological

A 6-gene signature identifies four molecular subgroups of neuroblastoma

Science.gov (United States)

2011-01-01

Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p INSS stage 4 and/or dead of disease, p < 0.05, Fisher's exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics. PMID:21492432

An Effective Tri-Clustering Algorithm Combining Expression Data with Gene Regulation Information

Directory of Open Access Journals (Sweden)

Ao Li

2009-04-01

Full Text Available Motivation: Bi-clustering algorithms aim to identify sets of genes sharing similar expression patterns across a subset of conditions. However direct interpretation or prediction of gene regulatory mechanisms may be difficult as only gene expression data is used. Information about gene regulators may also be available, most commonly about which transcription factors may bind to the promoter region and thus control the expression level of a gene. Thus a method to integrate gene expression and gene regulation information is desirable for clustering and analyzing. Methods: By incorporating gene regulatory information with gene expression data, we define regulated expression values (REV as indicators of how a gene is regulated by a specific factor. Existing bi-clustering methods are extended to a three dimensional data space by developing a heuristic TRI-Clustering algorithm. An additional approach named Automatic Boundary Searching algorithm (ABS is introduced to automatically determine the boundary threshold. Results: Results based on incorporating ChIP-chip data representing transcription factor-gene interactions show that the algorithms are efficient and robust for detecting tri-clusters. Detailed analysis of the tri-cluster extracted from yeast sporulation REV data shows genes in this cluster exhibited significant differences during the middle and late stages. The implicated regulatory network was then reconstructed for further study of defined regulatory mechanisms. Topological and statistical analysis of this network demonstrated evidence of significant changes of TF activities during the different stages of yeast sporulation, and suggests this approach might be a general way to study regulatory networks undergoing transformations.

antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

DEFF Research Database (Denmark)

Weber, Tilmann; Blin, Kai; Duddela, Srikanth

2015-01-01

Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we...... introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration...... of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products...

Clustering gene expression regulators: new approach to disease subtyping.

Directory of Open Access Journals (Sweden)

Mikhail Pyatnitskiy

Full Text Available One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms, that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Characterization of the largest effector gene cluster of Ustilago maydis.

Directory of Open Access Journals (Sweden)

Thomas Brefort

2014-07-01

Full Text Available In the genome of the biotrophic plant pathogen Ustilago maydis, many of the genes coding for secreted protein effectors modulating virulence are arranged in gene clusters. The vast majority of these genes encode novel proteins whose expression is coupled to plant colonization. The largest of these gene clusters, cluster 19A, encodes 24 secreted effectors. Deletion of the entire cluster results in severe attenuation of virulence. Here we present the functional analysis of this genomic region. We show that a 19A deletion mutant behaves like an endophyte, i.e. is still able to colonize plants and complete the infection cycle. However, tumors, the most conspicuous symptoms of maize smut disease, are only rarely formed and fungal biomass in infected tissue is significantly reduced. The generation and analysis of strains carrying sub-deletions identified several genes significantly contributing to tumor formation after seedling infection. Another of the effectors could be linked specifically to anthocyanin induction in the infected tissue. As the individual contributions of these genes to tumor formation were small, we studied the response of maize plants to the whole cluster mutant as well as to several individual mutants by array analysis. This revealed distinct plant responses, demonstrating that the respective effectors have discrete plant targets. We propose that the analysis of plant responses to effector mutant strains that lack a strong virulence phenotype may be a general way to visualize differences in effector function.

Genome-wide identification of physically clustered genes suggests chromatin-level co-regulation in male reproductive development in Arabidopsis thaliana.

Science.gov (United States)

Reimegård, Johan; Kundu, Snehangshu; Pendle, Ali; Irish, Vivian F; Shaw, Peter; Nakayama, Naomi; Sundström, Jens F; Emanuelsson, Olof

2017-04-07

Co-expression of physically linked genes occurs surprisingly frequently in eukaryotes. Such chromosomal clustering may confer a selective advantage as it enables coordinated gene regulation at the chromatin level. We studied the chromosomal organization of genes involved in male reproductive development in Arabidopsis thaliana. We developed an in-silico tool to identify physical clusters of co-regulated genes from gene expression data. We identified 17 clusters (96 genes) involved in stamen development and acting downstream of the transcriptional activator MS1 (MALE STERILITY 1), which contains a PHD domain associated with chromatin re-organization. The clusters exhibited little gene homology or promoter element similarity, and largely overlapped with reported repressive histone marks. Experiments on a subset of the clusters suggested a link between expression activation and chromatin conformation: qRT-PCR and mRNA in situ hybridization showed that the clustered genes were up-regulated within 48 h after MS1 induction; out of 14 chromatin-remodeling mutants studied, expression of clustered genes was consistently down-regulated only in hta9/hta11, previously associated with metabolic cluster activation; DNA fluorescence in situ hybridization confirmed that transcriptional activation of the clustered genes was correlated with open chromatin conformation. Stamen development thus appears to involve transcriptional activation of physically clustered genes through chromatin de-condensation. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

QTL global meta-analysis: are trait determining genes clustered?

Directory of Open Access Journals (Sweden)

Adelson David L

2009-04-01

Full Text Available Abstract Background A key open question in biology is if genes are physically clustered with respect to their known functions or phenotypic effects. This is of particular interest for Quantitative Trait Loci (QTL where a QTL region could contain a number of genes that contribute to the trait being measured. Results We observed a significant increase in gene density within QTL regions compared to non-QTL regions and/or the entire bovine genome. By grouping QTL from the Bovine QTL Viewer database into 8 categories of non-redundant regions, we have been able to analyze gene density and gene function distribution, based on Gene Ontology (GO with relation to their location within QTL regions, outside of QTL regions and across the entire bovine genome. We identified a number of GO terms that were significantly over represented within particular QTL categories. Furthermore, select GO terms expected to be associated with the QTL category based on common biological knowledge have also proved to be significantly over represented in QTL regions. Conclusion Our analysis provides evidence of over represented GO terms in QTL regions. This increased GO term density indicates possible clustering of gene functions within QTL regions of the bovine genome. Genes with similar functions may be grouped in specific locales and could be contributing to QTL traits. Moreover, we have identified over-represented GO terminology that from a biological standpoint, makes sense with respect to QTL category type.

A 6-gene signature identifies four molecular subgroups of neuroblastoma

Directory of Open Access Journals (Sweden)

Kogner Per

2011-04-01

Full Text Available Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB; Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples. Four distinct clusters were identified by Principal Components Analysis (PCA in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics.

Antibiotic discovery throughout the Small World Initiative: A molecular strategy to identify biosynthetic gene clusters involved in antagonistic activity.

Science.gov (United States)

Davis, Elizabeth; Sloan, Tyler; Aurelius, Krista; Barbour, Angela; Bodey, Elijah; Clark, Brigette; Dennis, Celeste; Drown, Rachel; Fleming, Megan; Humbert, Allison; Glasgo, Elizabeth; Kerns, Trent; Lingro, Kelly; McMillin, MacKenzie; Meyer, Aaron; Pope, Breanna; Stalevicz, April; Steffen, Brittney; Steindl, Austin; Williams, Carolyn; Wimberley, Carmen; Zenas, Robert; Butela, Kristen; Wildschutte, Hans

2017-06-01

The emergence of bacterial pathogens resistant to all known antibiotics is a global health crisis. Adding to this problem is that major pharmaceutical companies have shifted away from antibiotic discovery due to low profitability. As a result, the pipeline of new antibiotics is essentially dry and many bacteria now resist the effects of most commonly used drugs. To address this global health concern, citizen science through the Small World Initiative (SWI) was formed in 2012. As part of SWI, students isolate bacteria from their local environments, characterize the strains, and assay for antibiotic production. During the 2015 fall semester at Bowling Green State University, students isolated 77 soil-derived bacteria and genetically characterized strains using the 16S rRNA gene, identified strains exhibiting antagonistic activity, and performed an expanded SWI workflow using transposon mutagenesis to identify a biosynthetic gene cluster involved in toxigenic compound production. We identified one mutant with loss of antagonistic activity and through subsequent whole-genome sequencing and linker-mediated PCR identified a 24.9 kb biosynthetic gene locus likely involved in inhibitory activity in that mutant. Further assessment against human pathogens demonstrated the inhibition of Bacillus cereus, Listeria monocytogenes, and methicillin-resistant Staphylococcus aureus in the presence of this compound, thus supporting our molecular strategy as an effective research pipeline for SWI antibiotic discovery and genetic characterization. © 2017 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

Science.gov (United States)

Xu, Pingzhen

2018-01-01

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

GraphTeams: a method for discovering spatial gene clusters in Hi-C sequencing data.

Science.gov (United States)

Schulz, Tizian; Stoye, Jens; Doerr, Daniel

2018-05-08

Hi-C sequencing offers novel, cost-effective means to study the spatial conformation of chromosomes. We use data obtained from Hi-C experiments to provide new evidence for the existence of spatial gene clusters. These are sets of genes with associated functionality that exhibit close proximity to each other in the spatial conformation of chromosomes across several related species. We present the first gene cluster model capable of handling spatial data. Our model generalizes a popular computational model for gene cluster prediction, called δ-teams, from sequences to graphs. Following previous lines of research, we subsequently extend our model to allow for several vertices being associated with the same label. The model, called δ-teams with families, is particular suitable for our application as it enables handling of gene duplicates. We develop algorithmic solutions for both models. We implemented the algorithm for discovering δ-teams with families and integrated it into a fully automated workflow for discovering gene clusters in Hi-C data, called GraphTeams. We applied it to human and mouse data to find intra- and interchromosomal gene cluster candidates. The results include intrachromosomal clusters that seem to exhibit a closer proximity in space than on their chromosomal DNA sequence. We further discovered interchromosomal gene clusters that contain genes from different chromosomes within the human genome, but are located on a single chromosome in mouse. By identifying δ-teams with families, we provide a flexible model to discover gene cluster candidates in Hi-C data. Our analysis of Hi-C data from human and mouse reveals several known gene clusters (thus validating our approach), but also few sparsely studied or possibly unknown gene cluster candidates that could be the source of further experimental investigations.

Statistical indicators of collective behavior and functional clusters in gene networks of yeast

Science.gov (United States)

Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

Utility and Limitations of Using Gene Expression Data to Identify Functional Associations.

Directory of Open Access Journals (Sweden)

Sahra Uygun

2016-12-01

Full Text Available Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets.

Co-evolution of secondary metabolite gene clusters and their host

DEFF Research Database (Denmark)

Kjærbølling, Inge; Vesth, Tammi Camilla; Frisvad, Jens Christian

Secondary metabolite gene cluster evolution is mainly driven by two events: gene duplication and annexation and horizontal gene transfer. Here we use comparative genomics of Aspergillus species to investigate the evolution of secondary metabolite (SM) gene clusters across a wide spectrum of speci....... We investigate the dynamic evolutionary relationship between the cluster and the host by examining the genes within the cluster and the number of homologous genes found within the host and in closely related species.......Secondary metabolite gene cluster evolution is mainly driven by two events: gene duplication and annexation and horizontal gene transfer. Here we use comparative genomics of Aspergillus species to investigate the evolution of secondary metabolite (SM) gene clusters across a wide spectrum of species...

Evolution and Diversity of Biosynthetic Gene Clusters in Fusarium

Directory of Open Access Journals (Sweden)

Koen Hoogendoorn

2018-06-01

Full Text Available Plant pathogenic fungi in the Fusarium genus cause severe damage to crops, resulting in great financial losses and health hazards. Specialized metabolites synthesized by these fungi are known to play key roles in the infection process, and to provide survival advantages inside and outside the host. However, systematic studies of the evolution of specialized metabolite-coding potential across Fusarium have been scarce. Here, we apply a combination of bioinformatic approaches to identify biosynthetic gene clusters (BGCs across publicly available genomes from Fusarium, to group them into annotated families and to study gain/loss events of BGC families throughout the history of the genus. Comparison with MIBiG reference BGCs allowed assignment of 29 gene cluster families (GCFs to pathways responsible for the production of known compounds, while for 57 GCFs, the molecular products remain unknown. Comparative analysis of BGC repertoires using ancestral state reconstruction raised several new hypotheses on how BGCs contribute to Fusarium pathogenicity or host specificity, sometimes surprisingly so: for example, a gene cluster for the biosynthesis of hexadehydro-astechrome was identified in the genome of the biocontrol strain Fusarium oxysporum Fo47, while being absent in that of the tomato pathogen F. oxysporum f.sp. lycopersici. Several BGCs were also identified on supernumerary chromosomes; heterologous expression of genes for three terpene synthases encoded on the Fusarium poae supernumerary chromosome and subsequent GC/MS analysis showed that these genes are functional and encode enzymes that each are able to synthesize koraiol; this observed functional redundancy supports the hypothesis that localization of copies of BGCs on supernumerary chromosomes provides freedom for evolutionary innovations to occur, while the original function remains conserved. Altogether, this systematic overview of biosynthetic diversity in Fusarium paves the way for

Motif-Independent De Novo Detection of Secondary Metabolite Gene Clusters – Towards Identification of Novel Secondary Metabolisms from Filamentous Fungi -

Directory of Open Access Journals (Sweden)

Myco eUmemura

2015-05-01

Full Text Available Secondary metabolites are produced mostly by clustered genes that are essential to their biosynthesis. The transcriptional expression of these genes is often cooperatively regulated by a transcription factor located inside or close to a cluster. Most of the secondary metabolism biosynthesis (SMB gene clusters identified to date contain so-called core genes with distinctive sequence features, such as polyketide synthase (PKS and non-ribosomal peptide synthetase (NRPS. Recent efforts in sequencing fungal genomes have revealed far more SMB gene clusters than expected based on the number of core genes in the genomes. Several bioinformatics tools have been developed to survey SMB gene clusters using the sequence motif information of the core genes, including SMURF and antiSMASH.More recently, accompanied by the development of sequencing techniques allowing to obtain large-scale genomic and transcriptomic data, motif-independent prediction methods of SMB gene clusters, including MIDDAS-M, have been developed. Most these methods detect the clusters in which the genes are cooperatively regulated at transcriptional levels, thus allowing the identification of novel SMB gene clusters regardless of the presence of the core genes. Another type of the method, MIPS-CG, uses the characteristics of SMB genes, which are highly enriched in non-syntenic blocks (NSBs, enabling the prediction even without transcriptome data although the results have not been evaluated in detail. Considering that large portion of SMB gene clusters might be sufficiently expressed only in limited uncommon conditions, it seems that prediction of SMB gene clusters by bioinformatics and successive experimental validation is an only way to efficiently uncover hidden SMB gene clusters. Here, we describe and discuss possible novel approaches for the determination of SMB gene clusters that have not been identified using conventional methods.

Variation in the fumonisin biosynthetic gene cluster in fumonisin-producing and nonproducing black aspergilli.

Science.gov (United States)

Susca, Antonia; Proctor, Robert H; Butchko, Robert A E; Haidukowski, Miriam; Stea, Gaetano; Logrieco, Antonio; Moretti, Antonio

2014-12-01

The ability to produce fumonisin mycotoxins varies among members of the black aspergilli. Previously, analyses of selected genes in the fumonisin biosynthetic gene (fum) cluster in black aspergilli from California grapes indicated that fumonisin-nonproducing isolates of Aspergillus welwitschiae lack six fum genes, but nonproducing isolates of Aspergillus niger do not. In the current study, analyses of black aspergilli from grapes from the Mediterranean Basin indicate that the genomic context of the fum cluster is the same in isolates of A. niger and A. welwitschiae regardless of fumonisin-production ability and that full-length clusters occur in producing isolates of both species and nonproducing isolates of A. niger. In contrast, the cluster has undergone an eight-gene deletion in fumonisin-nonproducing isolates of A. welwitschiae. Phylogenetic analyses suggest each species consists of a mixed population of fumonisin-producing and nonproducing individuals, and that existence of both production phenotypes may provide a selective advantage to these species. Differences in gene content of fum cluster homologues and phylogenetic relationships of fum genes suggest that the mutation(s) responsible for the nonproduction phenotype differs, and therefore arose independently, in the two species. Partial fum cluster homologues were also identified in genome sequences of four other black Aspergillus species. Gene content of these partial clusters and phylogenetic relationships of fum sequences indicate that non-random partial deletion of the cluster has occurred multiple times among the species. This in turn suggests that an intact cluster and fumonisin production were once more widespread among black aspergilli. Copyright © 2014 Elsevier Inc. All rights reserved.

antiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters.

Science.gov (United States)

Weber, Tilmann; Blin, Kai; Duddela, Srikanth; Krug, Daniel; Kim, Hyun Uk; Bruccoleri, Robert; Lee, Sang Yup; Fischbach, Michael A; Müller, Rolf; Wohlleben, Wolfgang; Breitling, Rainer; Takano, Eriko; Medema, Marnix H

2015-07-01

Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Clusters of Antibiotic Resistance Genes Enriched Together Stay Together in Swine Agriculture.

Science.gov (United States)

Johnson, Timothy A; Stedtfeld, Robert D; Wang, Qiong; Cole, James R; Hashsham, Syed A; Looft, Torey; Zhu, Yong-Guan; Tiedje, James M

2016-04-12

Antibiotic resistance is a worldwide health risk, but the influence of animal agriculture on the genetic context and enrichment of individual antibiotic resistance alleles remains unclear. Using quantitative PCR followed by amplicon sequencing, we quantified and sequenced 44 genes related to antibiotic resistance, mobile genetic elements, and bacterial phylogeny in microbiomes from U.S. laboratory swine and from swine farms from three Chinese regions. We identified highly abundant resistance clusters: groups of resistance and mobile genetic element alleles that cooccur. For example, the abundance of genes conferring resistance to six classes of antibiotics together with class 1 integrase and the abundance of IS6100-type transposons in three Chinese regions are directly correlated. These resistance cluster genes likely colocalize in microbial genomes in the farms. Resistance cluster alleles were dramatically enriched (up to 1 to 10% as abundant as 16S rRNA) and indicate that multidrug-resistant bacteria are likely the norm rather than an exception in these communities. This enrichment largely occurred independently of phylogenetic composition; thus, resistance clusters are likely present in many bacterial taxa. Furthermore, resistance clusters contain resistance genes that confer resistance to antibiotics independently of their particular use on the farms. Selection for these clusters is likely due to the use of only a subset of the broad range of chemicals to which the clusters confer resistance. The scale of animal agriculture and its wastes, the enrichment and horizontal gene transfer potential of the clusters, and the vicinity of large human populations suggest that managing this resistance reservoir is important for minimizing human risk. Agricultural antibiotic use results in clusters of cooccurring resistance genes that together confer resistance to multiple antibiotics. The use of a single antibiotic could select for an entire suite of resistance genes if

A genome-wide analysis of nonribosomal peptide synthetase gene clusters and their peptides in a Planktothrix rubescens strain

Directory of Open Access Journals (Sweden)

Nederbragt Alexander J

2009-08-01

Full Text Available Abstract Background Cyanobacteria often produce several different oligopeptides, with unknown biological functions, by nonribosomal peptide synthetases (NRPS. Although some cyanobacterial NRPS gene cluster types are well described, the entire NRPS genomic content within a single cyanobacterial strain has never been investigated. Here we have combined a genome-wide analysis using massive parallel pyrosequencing ("454" and mass spectrometry screening of oligopeptides produced in the strain Planktothrix rubescens NIVA CYA 98 in order to identify all putative gene clusters for oligopeptides. Results Thirteen types of oligopeptides were uncovered by mass spectrometry (MS analyses. Microcystin, cyanopeptolin and aeruginosin synthetases, highly similar to already characterized NRPS, were present in the genome. Two novel NRPS gene clusters were associated with production of anabaenopeptins and microginins, respectively. Sequence-depth of the genome and real-time PCR data revealed three copies of the microginin gene cluster. Since NRPS gene cluster candidates for microviridin and oscillatorin synthesis could not be found, putative (gene encoded precursor peptide sequences to microviridin and oscillatorin were found in the genes mdnA and oscA, respectively. The genes flanking the microviridin and oscillatorin precursor genes encode putative modifying enzymes of the precursor oligopeptides. We therefore propose ribosomal pathways involving modifications and cyclisation for microviridin and oscillatorin. The microviridin, anabaenopeptin and cyanopeptolin gene clusters are situated in close proximity to each other, constituting an oligopeptide island. Conclusion Altogether seven nonribosomal peptide synthetase (NRPS gene clusters and two gene clusters putatively encoding ribosomal oligopeptide biosynthetic pathways were revealed. Our results demonstrate that whole genome shotgun sequencing combined with MS-directed determination of oligopeptides successfully

A remarkably stable TipE gene cluster: evolution of insect Para sodium channel auxiliary subunits

Directory of Open Access Journals (Sweden)

Li Jia

2011-11-01

Full Text Available Abstract Background First identified in fruit flies with temperature-sensitive paralysis phenotypes, the Drosophila melanogaster TipE locus encodes four voltage-gated sodium (NaV channel auxiliary subunits. This cluster of TipE-like genes on chromosome 3L, and a fifth family member on chromosome 3R, are important for the optional expression and functionality of the Para NaV channel but appear quite distinct from auxiliary subunits in vertebrates. Here, we exploited available arthropod genomic resources to trace the origin of TipE-like genes by mapping their evolutionary histories and examining their genomic architectures. Results We identified a remarkably conserved synteny block of TipE-like orthologues with well-maintained local gene arrangements from 21 insect species. Homologues in the water flea, Daphnia pulex, suggest an ancestral pancrustacean repertoire of four TipE-like genes; a subsequent gene duplication may have generated functional redundancy allowing gene losses in the silk moth and mosquitoes. Intronic nesting of the insect TipE gene cluster probably occurred following the divergence from crustaceans, but in the flour beetle and silk moth genomes the clusters apparently escaped from nesting. Across Pancrustacea, TipE gene family members have experienced intronic nesting, escape from nesting, retrotransposition, translocation, and gene loss events while generally maintaining their local gene neighbourhoods. D. melanogaster TipE-like genes exhibit coordinated spatial and temporal regulation of expression distinct from their host gene but well-correlated with their regulatory target, the Para NaV channel, suggesting that functional constraints may preserve the TipE gene cluster. We identified homology between TipE-like NaV channel regulators and vertebrate Slo-beta auxiliary subunits of big-conductance calcium-activated potassium (BKCa channels, which suggests that ion channel regulatory partners have evolved distinct lineage

Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data.

Science.gov (United States)

Ren, Zhonglu; Wang, Wenhui; Li, Jinming

2016-02-01

Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

Deletion and Gene Expression Analyses Define the Paxilline Biosynthetic Gene Cluster in Penicillium paxilli

Directory of Open Access Journals (Sweden)

Emily J. Parker

2013-08-01

Full Text Available The indole-diterpene paxilline is an abundant secondary metabolite synthesized by Penicillium paxilli. In total, 21 genes have been identified at the PAX locus of which six have been previously confirmed to have a functional role in paxilline biosynthesis. A combination of bioinformatics, gene expression and targeted gene replacement analyses were used to define the boundaries of the PAX gene cluster. Targeted gene replacement identified seven genes, paxG, paxA, paxM, paxB, paxC, paxP and paxQ that were all required for paxilline production, with one additional gene, paxD, required for regular prenylation of the indole ring post paxilline synthesis. The two putative transcription factors, PP104 and PP105, were not co-regulated with the pax genes and based on targeted gene replacement, including the double knockout, did not have a role in paxilline production. The relationship of indole dimethylallyl transferases involved in prenylation of indole-diterpenes such as paxilline or lolitrem B, can be found as two disparate clades, not supported by prenylation type (e.g., regular or reverse. This paper provides insight into the P. paxilli indole-diterpene locus and reviews the recent advances identified in paxilline biosynthesis.

Clustering gene expression data based on predicted differential effects of GV interaction.

Science.gov (United States)

Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

Conservation of gene linkage in dispersed vertebrate NK homeobox clusters.

Science.gov (United States)

Wotton, Karl R; Weierud, Frida K; Juárez-Morales, José L; Alvares, Lúcia E; Dietrich, Susanne; Lewis, Katharine E

2009-10-01

Nk homeobox genes are important regulators of many different developmental processes including muscle, heart, central nervous system and sensory organ development. They are thought to have arisen as part of the ANTP megacluster, which also gave rise to Hox and ParaHox genes, and at least some NK genes remain tightly linked in all animals examined so far. The protostome-deuterostome ancestor probably contained a cluster of nine Nk genes: (Msx)-(Nk4/tinman)-(Nk3/bagpipe)-(Lbx/ladybird)-(Tlx/c15)-(Nk7)-(Nk6/hgtx)-(Nk1/slouch)-(Nk5/Hmx). Of these genes, only NKX2.6-NKX3.1, LBX1-TLX1 and LBX2-TLX2 remain tightly linked in humans. However, it is currently unclear whether this is unique to the human genome as we do not know which of these Nk genes are clustered in other vertebrates. This makes it difficult to assess whether the remaining linkages are due to selective pressures or because chance rearrangements have "missed" certain genes. In this paper, we identify all of the paralogs of these ancestrally clustered NK genes in several distinct vertebrates. We demonstrate that tight linkages of Lbx1-Tlx1, Lbx2-Tlx2 and Nkx3.1-Nkx2.6 have been widely maintained in both the ray-finned and lobe-finned fish lineages. Moreover, the recently duplicated Hmx2-Hmx3 genes are also tightly linked. Finally, we show that Lbx1-Tlx1 and Hmx2-Hmx3 are flanked by highly conserved noncoding elements, suggesting that shared regulatory regions may have resulted in evolutionary pressure to maintain these linkages. Consistent with this, these pairs of genes have overlapping expression domains. In contrast, Lbx2-Tlx2 and Nkx3.1-Nkx2.6, which do not seem to be coexpressed, are also not associated with conserved noncoding sequences, suggesting that an alternative mechanism may be responsible for the continued clustering of these genes.

Semi-supervised consensus clustering for gene expression data analysis

OpenAIRE

Wang, Yunli; Pan, Youlian

2014-01-01

Background Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustness and quality of clustering results. Incorporating prior knowledge in clustering process (semi-supervised clustering) has been shown to improve the consistency between the data partitioning and do...

Transcriptional analysis of exopolysaccharides biosynthesis gene clusters in Lactobacillus plantarum.

Science.gov (United States)

Vastano, Valeria; Perrone, Filomena; Marasco, Rosangela; Sacco, Margherita; Muscariello, Lidia

2016-04-01

Exopolysaccharides (EPS) from lactic acid bacteria contribute to specific rheology and texture of fermented milk products and find applications also in non-dairy foods and in therapeutics. Recently, four clusters of genes (cps) associated with surface polysaccharide production have been identified in Lactobacillus plantarum WCFS1, a probiotic and food-associated lactobacillus. These clusters are involved in cell surface architecture and probably in release and/or exposure of immunomodulating bacterial molecules. Here we show a transcriptional analysis of these clusters. Indeed, RT-PCR experiments revealed that the cps loci are organized in five operons. Moreover, by reverse transcription-qPCR analysis performed on L. plantarum WCFS1 (wild type) and WCFS1-2 (ΔccpA), we demonstrated that expression of three cps clusters is under the control of the global regulator CcpA. These results, together with the identification of putative CcpA target sequences (catabolite responsive element CRE) in the regulatory region of four out of five transcriptional units, strongly suggest for the first time a role of the master regulator CcpA in EPS gene transcription among lactobacilli.

Gene clusters for insecticidal loline alkaloids in the grass-endophytic fungus Neotyphodium uncinatum.

Science.gov (United States)

Spiering, Martin J; Moon, Christina D; Wilkinson, Heather H; Schardl, Christopher L

2005-03-01

Loline alkaloids are produced by mutualistic fungi symbiotic with grasses, and they protect the host plants from insects. Here we identify in the fungal symbiont, Neotyphodium uncinatum, two homologous gene clusters (LOL-1 and LOL-2) associated with loline-alkaloid production. Nine genes were identified in a 25-kb region of LOL-1 and designated (in order) lolF-1, lolC-1, lolD-1, lolO-1, lolA-1, lolU-1, lolP-1, lolT-1, and lolE-1. LOL-2 contained the homologs lolC-2 through lolE-2 in the same order and orientation. Also identified was lolF-2, but its possible linkage with either cluster was undetermined. Most lol genes were regulated in N. uncinatum and N. coenophialum, and all were expressed concomitantly with loline-alkaloid biosynthesis. A lolC-2 RNA-interference (RNAi) construct was introduced into N. uncinatum, and in two independent transformants, RNAi significantly decreased lolC expression (P lol-gene products indicate that the pathway has evolved from various different primary and secondary biosynthesis pathways.

Hox gene clusters in the Indonesian coelacanth, Latimeria menadoensis

Science.gov (United States)

Koh, Esther G. L.; Lam, Kevin; Christoffels, Alan; Erdmann, Mark V.; Brenner, Sydney; Venkatesh, Byrappa

2003-01-01

The Hox genes encode transcription factors that play a key role in specifying body plans of metazoans. They are organized into clusters that contain up to 13 paralogue group members. The complex morphology of vertebrates has been attributed to the duplication of Hox clusters during vertebrate evolution. In contrast to the single Hox cluster in the amphioxus (Branchiostoma floridae), an invertebrate-chordate, mammals have four clusters containing 39 Hox genes. Ray-finned fishes (Actinopterygii) such as zebrafish and fugu possess more than four Hox clusters. The coelacanth occupies a basal phylogenetic position among lobe-finned fishes (Sarcopterygii), which gave rise to the tetrapod lineage. The lobe fins of sarcopterygians are considered to be the evolutionary precursors of tetrapod limbs. Thus, the characterization of Hox genes in the coelacanth should provide insights into the origin of tetrapod limbs. We have cloned the complete second exon of 33 Hox genes from the Indonesian coelacanth, Latimeria menadoensis, by extensive PCR survey and genome walking. Phylogenetic analysis shows that 32 of these genes have orthologs in the four mammalian HOX clusters, including three genes (HoxA6, D1, and D8) that are absent in ray-finned fishes. The remaining coelacanth gene is an ortholog of hoxc1 found in zebrafish but absent in mammals. Our results suggest that coelacanths have four Hox clusters bearing a gene complement more similar to mammals than to ray-finned fishes, but with an additional gene, HoxC1, which has been lost during the evolution of mammals from lobe-finned fishes. PMID:12547909

Conditions for the Evolution of Gene Clusters in Bacterial Genomes

Science.gov (United States)

Ballouz, Sara; Francis, Andrew R.; Lan, Ruiting; Tanaka, Mark M.

2010-01-01

Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model), genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters. PMID:20168992

Genome-scale analysis of positional clustering of mouse testis-specific genes

Directory of Open Access Journals (Sweden)

Lee Bernett TK

2005-01-01

Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.

Conditions for the evolution of gene clusters in bacterial genomes.

Directory of Open Access Journals (Sweden)

Sara Ballouz

2010-02-01

Full Text Available Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model, genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters.

Motif-independent prediction of a secondary metabolism gene cluster using comparative genomics: application to sequenced genomes of Aspergillus and ten other filamentous fungal species.

Science.gov (United States)

Takeda, Itaru; Umemura, Myco; Koike, Hideaki; Asai, Kiyoshi; Machida, Masayuki

2014-08-01

Despite their biological importance, a significant number of genes for secondary metabolite biosynthesis (SMB) remain undetected due largely to the fact that they are highly diverse and are not expressed under a variety of cultivation conditions. Several software tools including SMURF and antiSMASH have been developed to predict fungal SMB gene clusters by finding core genes encoding polyketide synthase, nonribosomal peptide synthetase and dimethylallyltryptophan synthase as well as several others typically present in the cluster. In this work, we have devised a novel comparative genomics method to identify SMB gene clusters that is independent of motif information of the known SMB genes. The method detects SMB gene clusters by searching for a similar order of genes and their presence in nonsyntenic blocks. With this method, we were able to identify many known SMB gene clusters with the core genes in the genomic sequences of 10 filamentous fungi. Furthermore, we have also detected SMB gene clusters without core genes, including the kojic acid biosynthesis gene cluster of Aspergillus oryzae. By varying the detection parameters of the method, a significant difference in the sequence characteristics was detected between the genes residing inside the clusters and those outside the clusters. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

KAUST Repository

Abusamra, Heba

2016-07-20

The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

GenClust: A genetic algorithm for clustering gene expression data

Directory of Open Access Journals (Sweden)

Raimondi Alessandra

2005-12-01

Full Text Available Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a a novel coding of the search space that is simple, compact and easy to update; (b it can be used naturally in conjunction with data driven internal validation methods. We have experimented with the FOM methodology, specifically conceived for validating clusters of gene expression data. The validity of GenClust has been assessed experimentally on real data sets, both with the use of validation measures and in comparison with other algorithms, i.e., Average Link, Cast, Click and K-means. Conclusion Experiments show that none of the algorithms we have used is markedly superior to the others across data sets and validation measures; i.e., in many cases the observed differences between the worst and best performing algorithm may be statistically insignificant and they could be considered equivalent. However, there are cases in which an algorithm may be better than others and therefore worthwhile. In particular, experiments for GenClust show that, although simple in its data representation, it converges very rapidly to a local optimum and that its ability to identify meaningful clusters is comparable, and sometimes superior, to that of more sophisticated algorithms. In addition, it is well suited for use in conjunction with data driven internal validation measures and, in particular, the FOM methodology.

An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

Science.gov (United States)

Booma, P M; Prabhakaran, S; Dhanalakshmi, R

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters

Directory of Open Access Journals (Sweden)

Louw Abraham I

2008-02-01

Full Text Available Abstract Background Microarray technology makes it possible to identify changes in gene expression of an organism, under various conditions. Data mining is thus essential for deducing significant biological information such as the identification of new biological mechanisms or putative drug targets. While many algorithms and software have been developed for analysing gene expression, the extraction of relevant information from experimental data is still a substantial challenge, requiring significant time and skill. Description MADIBA (MicroArray Data Interface for Biological Annotation facilitates the assignment of biological meaning to gene expression clusters by automating the post-processing stage. A relational database has been designed to store the data from gene to pathway for Plasmodium, rice and Arabidopsis. Tools within the web interface allow rapid analyses for the identification of the Gene Ontology terms relevant to each cluster; visualising the metabolic pathways where the genes are implicated, their genomic localisations, putative common transcriptional regulatory elements in the upstream sequences, and an analysis specific to the organism being studied. Conclusion MADIBA is an integrated, online tool that will assist researchers in interpreting their results and understand the meaning of the co-expression of a cluster of genes. Functionality of MADIBA was validated by analysing a number of gene clusters from several published experiments – expression profiling of the Plasmodium life cycle, and salt stress treatments of Arabidopsis and rice. In most of the cases, the same conclusions found by the authors were quickly and easily obtained after analysing the gene clusters with MADIBA.

Two Gene Clusters Coordinate Galactose and Lactose Metabolism in Streptococcus gordonii

Science.gov (United States)

Zeng, Lin; Martino, Nicole C.

2012-01-01

Streptococcus gordonii is an early colonizer of the human oral cavity and an abundant constituent of oral biofilms. Two tandemly arranged gene clusters, designated lac and gal, were identified in the S. gordonii DL1 genome, which encode genes of the tagatose pathway (lacABCD) and sugar phosphotransferase system (PTS) enzyme II permeases. Genes encoding a predicted phospho-β-galactosidase (LacG), a DeoR family transcriptional regulator (LacR), and a transcriptional antiterminator (LacT) were also present in the clusters. Growth and PTS assays supported that the permease designated EIILac transports lactose and galactose, whereas EIIGal transports galactose. The expression of the gene for EIIGal was markedly upregulated in cells growing on galactose. Using promoter-cat fusions, a role for LacR in the regulation of the expressions of both gene clusters was demonstrated, and the gal cluster was also shown to be sensitive to repression by CcpA. The deletion of lacT caused an inability to grow on lactose, apparently because of its role in the regulation of the expression of the genes for EIILac, but had little effect on galactose utilization. S. gordonii maintained a selective advantage over Streptococcus mutans in a mixed-species competition assay, associated with its possession of a high-affinity galactose PTS, although S. mutans could persist better at low pHs. Collectively, these results support the concept that the galactose and lactose systems of S. gordonii are subject to complex regulation and that a high-affinity galactose PTS may be advantageous when S. gordonii is competing against the caries pathogen S. mutans in oral biofilms. PMID:22660715

Differential Retention of Gene Functions in a Secondary Metabolite Cluster.

Science.gov (United States)

Reynolds, Hannah T; Slot, Jason C; Divon, Hege H; Lysøe, Erik; Proctor, Robert H; Brown, Daren W

2017-08-01

In fungi, distribution of secondary metabolite (SM) gene clusters is often associated with host- or environment-specific benefits provided by SMs. In the plant pathogen Alternaria brassicicola (Dothideomycetes), the DEP cluster confers an ability to synthesize the SM depudecin, a histone deacetylase inhibitor that contributes weakly to virulence. The DEP cluster includes genes encoding enzymes, a transporter, and a transcription regulator. We investigated the distribution and evolution of the DEP cluster in 585 fungal genomes and found a wide but sporadic distribution among Dothideomycetes, Sordariomycetes, and Eurotiomycetes. We confirmed DEP gene expression and depudecin production in one fungus, Fusarium langsethiae. Phylogenetic analyses suggested 6-10 horizontal gene transfers (HGTs) of the cluster, including a transfer that led to the presence of closely related cluster homologs in Alternaria and Fusarium. The analyses also indicated that HGTs were frequently followed by loss/pseudogenization of one or more DEP genes. Independent cluster inactivation was inferred in at least four fungal classes. Analyses of transitions among functional, pseudogenized, and absent states of DEP genes among Fusarium species suggest enzyme-encoding genes are lost at higher rates than the transporter (DEP3) and regulatory (DEP6) genes. The phenotype of an experimentally-induced DEP3 mutant of Fusarium did not support the hypothesis that selective retention of DEP3 and DEP6 protects fungi from exogenous depudecin. Together, the results suggest that HGT and gene loss have contributed significantly to DEP cluster distribution, and that some DEP genes provide a greater fitness benefit possibly due to a differential tendency to form network connections. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution 2017. This work is written by US Government employees and is in the public domain in the US.

Functional clustering of time series gene expression data by Granger causality

Science.gov (United States)

2012-01-01

Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

MeSH key terms for validation and annotation of gene expression clusters

Energy Technology Data Exchange (ETDEWEB)

Rechtsteiner, A. (Andreas); Rocha, L. M. (Luis Mateus)

2004-01-01

Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert who had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes

Two Horizontally Transferred Xenobiotic Resistance Gene Clusters Associated with Detoxification of Benzoxazolinones by Fusarium Species

Science.gov (United States)

Glenn, Anthony E.; Davis, C. Britton; Gao, Minglu; Gold, Scott E.; Mitchell, Trevor R.; Proctor, Robert H.; Stewart, Jane E.; Snook, Maurice E.

2016-01-01

Microbes encounter a broad spectrum of antimicrobial compounds in their environments and often possess metabolic strategies to detoxify such xenobiotics. We have previously shown that Fusarium verticillioides, a fungal pathogen of maize known for its production of fumonisin mycotoxins, possesses two unlinked loci, FDB1 and FDB2, necessary for detoxification of antimicrobial compounds produced by maize, including the γ-lactam 2-benzoxazolinone (BOA). In support of these earlier studies, microarray analysis of F. verticillioides exposed to BOA identified the induction of multiple genes at FDB1 and FDB2, indicating the loci consist of gene clusters. One of the FDB1 cluster genes encoded a protein having domain homology to the metallo-β-lactamase (MBL) superfamily. Deletion of this gene (MBL1) rendered F. verticillioides incapable of metabolizing BOA and thus unable to grow on BOA-amended media. Deletion of other FDB1 cluster genes, in particular AMD1 and DLH1, did not affect BOA degradation. Phylogenetic analyses and topology testing of the FDB1 and FDB2 cluster genes suggested two horizontal transfer events among fungi, one being transfer of FDB1 from Fusarium to Colletotrichum, and the second being transfer of the FDB2 cluster from Fusarium to Aspergillus. Together, the results suggest that plant-derived xenobiotics have exerted evolutionary pressure on these fungi, leading to horizontal transfer of genes that enhance fitness or virulence. PMID:26808652

A robust approach based on Weibull distribution for clustering gene expression data

Directory of Open Access Journals (Sweden)

Gong Binsheng

2011-05-01

Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

Heterologous expression of pikromycin biosynthetic gene cluster using Streptomyces artificial chromosome system.

Science.gov (United States)

Pyeon, Hye-Rim; Nah, Hee-Ju; Kang, Seung-Hoon; Choi, Si-Sun; Kim, Eung-Soo

2017-05-31

Heterologous expression of biosynthetic gene clusters of natural microbial products has become an essential strategy for titer improvement and pathway engineering of various potentially-valuable natural products. A Streptomyces artificial chromosomal conjugation vector, pSBAC, was previously successfully applied for precise cloning and tandem integration of a large polyketide tautomycetin (TMC) biosynthetic gene cluster (Nah et al. in Microb Cell Fact 14(1):1, 2015), implying that this strategy could be employed to develop a custom overexpression scheme of natural product pathway clusters present in actinomycetes. To validate the pSBAC system as a generally-applicable heterologous overexpression system for a large-sized polyketide biosynthetic gene cluster in Streptomyces, another model polyketide compound, the pikromycin biosynthetic gene cluster, was preciously cloned and heterologously expressed using the pSBAC system. A unique HindIII restriction site was precisely inserted at one of the border regions of the pikromycin biosynthetic gene cluster within the chromosome of Streptomyces venezuelae, followed by site-specific recombination of pSBAC into the flanking region of the pikromycin gene cluster. Unlike the previous cloning process, one HindIII site integration step was skipped through pSBAC modification. pPik001, a pSBAC containing the pikromycin biosynthetic gene cluster, was directly introduced into two heterologous hosts, Streptomyces lividans and Streptomyces coelicolor, resulting in the production of 10-deoxymethynolide, a major pikromycin derivative. When two entire pikromycin biosynthetic gene clusters were tandemly introduced into the S. lividans chromosome, overproduction of 10-deoxymethynolide and the presence of pikromycin, which was previously not detected, were both confirmed. Moreover, comparative qRT-PCR results confirmed that the transcription of pikromycin biosynthetic genes was significantly upregulated in S. lividans containing tandem

Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

Science.gov (United States)

Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of EOperon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

Characterization of the biosynthetic gene cluster for cryptic phthoxazolin A in Streptomyces avermitilis.

Directory of Open Access Journals (Sweden)

Dian Anggraini Suroto

Full Text Available Phthoxazolin A, an oxazole-containing polyketide, has a broad spectrum of anti-oomycete activity and herbicidal activity. We recently identified phthoxazolin A as a cryptic metabolite of Streptomyces avermitilis that produces the important anthelmintic agent avermectin. Even though genome data of S. avermitilis is publicly available, no plausible biosynthetic gene cluster for phthoxazolin A is apparent in the sequence data. Here, we identified and characterized the phthoxazolin A (ptx biosynthetic gene cluster through genome sequencing, comparative genomic analysis, and gene disruption. Sequence analysis uncovered that the putative ptx biosynthetic genes are laid on an extra genomic region that is not found in the public database, and 8 open reading frames in the extra genomic region could be assigned roles in the biosynthesis of the oxazole ring, triene polyketide and carbamoyl moieties. Disruption of the ptxA gene encoding a discrete acyltransferase resulted in a complete loss of phthoxazolin A production, confirming that the trans-AT type I PKS system is responsible for the phthoxazolin A biosynthesis. Based on the predicted functional domains in the ptx assembly line, we propose the biosynthetic pathway of phthoxazolin A.

Identification and functional analysis of gene cluster involvement in biosynthesis of the cyclic lipopeptide antibiotic pelgipeptin produced by Paenibacillus elgii

Directory of Open Access Journals (Sweden)

Qian Chao-Dong

2012-09-01

Full Text Available Abstract Background Pelgipeptin, a potent antibacterial and antifungal agent, is a non-ribosomally synthesised lipopeptide antibiotic. This compound consists of a β-hydroxy fatty acid and nine amino acids. To date, there is no information about its biosynthetic pathway. Results A potential pelgipeptin synthetase gene cluster (plp was identified from Paenibacillus elgii B69 through genome analysis. The gene cluster spans 40.8 kb with eight open reading frames. Among the genes in this cluster, three large genes, plpD, plpE, and plpF, were shown to encode non-ribosomal peptide synthetases (NRPSs, with one, seven, and one module(s, respectively. Bioinformatic analysis of the substrate specificity of all nine adenylation domains indicated that the sequence of the NRPS modules is well collinear with the order of amino acids in pelgipeptin. Additional biochemical analysis of four recombinant adenylation domains (PlpD A1, PlpE A1, PlpE A3, and PlpF A1 provided further evidence that the plp gene cluster involved in pelgipeptin biosynthesis. Conclusions In this study, a gene cluster (plp responsible for the biosynthesis of pelgipeptin was identified from the genome sequence of Paenibacillus elgii B69. The identification of the plp gene cluster provides an opportunity to develop novel lipopeptide antibiotics by genetic engineering.

Gene structure and expression characteristic of a novel odorant receptor gene cluster in the parasitoid wasp Microplitis mediator (Hymenoptera: Braconidae).

Science.gov (United States)

Wang, S-N; Shan, S; Zheng, Y; Peng, Y; Lu, Z-Y; Yang, Y-Q; Li, R-J; Zhang, Y-J; Guo, Y-Y

2017-08-01

Odorant receptors (ORs) expressed in the antennae of parasitoid wasps are responsible for detection of various lipophilic airborne molecules. In the present study, 107 novel OR genes were identified from Microplitis mediator antennal transcriptome data. Phylogenetic analysis of the set of OR genes from M. mediator and Microplitis demolitor revealed that M. mediator OR (MmedOR) genes can be classified into different subfamilies, and the majority of MmedORs in each subfamily shared high sequence identities and clear orthologous relationships to M. demolitor ORs. Within a subfamily, six MmedOR genes, MmedOR98, 124, 125, 126, 131 and 155, shared a similar gene structure and were tightly linked in the genome. To evaluate whether the clustered MmedOR genes share common regulatory features, the transcription profile and expression characteristics of the six closely related OR genes were investigated in M. mediator. Rapid amplification of cDNA ends-PCR experiments revealed that the OR genes within the cluster were transcribed as single mRNAs, and a bicistronic mRNA for two adjacent genes (MmedOR124 and MmedOR98) was also detected in female antennae by reverse transcription PCR. In situ hybridization experiments indicated that each OR gene within the cluster was expressed in a different number of cells. Moreover, there was no co-expression of the two highly related OR genes, MmedOR124 and MmedOR98, which appeared to be individually expressed in a distinct population of neurons. Overall, there were distinct expression profiles of closely related MmedOR genes from the same cluster in M. mediator. These data provide a basic understanding of the olfactory coding in parasitoid wasps. © 2017 The Royal Entomological Society.

Genome-Wide Analysis of Secondary Metabolite Gene Clusters in Ophiostoma ulmi and Ophiostoma novo-ulmi Reveals a Fujikurin-Like Gene Cluster with a Putative Role in Infection

Directory of Open Access Journals (Sweden)

Nicolau Sbaraini

2017-06-01

Full Text Available The emergence of new microbial pathogens can result in destructive outbreaks, since their hosts have limited resistance and pathogens may be excessively aggressive. Described as the major ecological incident of the twentieth century, Dutch elm disease, caused by ascomycete fungi from the Ophiostoma genus, has caused a significant decline in elm tree populations (Ulmus sp. in North America and Europe. Genome sequencing of the two main causative agents of Dutch elm disease (Ophiostoma ulmi and Ophiostoma novo-ulmi, along with closely related species with different lifestyles, allows for unique comparisons to be made to identify how pathogens and virulence determinants have emerged. Among several established virulence determinants, secondary metabolites (SMs have been suggested to play significant roles during phytopathogen infection. Interestingly, the secondary metabolism of Dutch elm pathogens remains almost unexplored, and little is known about how SM biosynthetic genes are organized in these species. To better understand the metabolic potential of O. ulmi and O. novo-ulmi, we performed a deep survey and description of SM biosynthetic gene clusters (BGCs in these species and assessed their conservation among eight species from the Ophiostomataceae family. Among 19 identified BGCs, a fujikurin-like gene cluster (OpPKS8 was unique to Dutch elm pathogens. Phylogenetic analysis revealed that orthologs for this gene cluster are widespread among phytopathogens and plant-associated fungi, suggesting that OpPKS8 may have been horizontally acquired by the Ophiostoma genus. Moreover, the detailed identification of several BGCs paves the way for future in-depth research and supports the potential impact of secondary metabolism on Ophiostoma genus’ lifestyle.

Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

Science.gov (United States)

Wan, B; Yarbrough, J W; Schultz, T W

2008-01-01

This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.

Increasing Power by Sharing Information from Genetic Background and Treatment in Clustering of Gene Expression Time Series

Directory of Open Access Journals (Sweden)

Sura Zaki Alrashid

2018-02-01

Full Text Available Clustering of gene expression time series gives insight into which genes may be co-regulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different conditions or genetic background. This paper develops
a new clustering method that allows each cluster to be parameterised according to whether the behaviour of the genes across conditions is correlated or anti-correlated. By specifying correlation between such genes,more information is gain within the cluster about how the genes interrelate. Amyotrophic lateral sclerosis (ALS is an irreversible neurodegenerative disorder that kills the motor neurons and results in death within 2 to 3 years from the symptom onset. Speed of progression for different patients are heterogeneous with significant variability. The SOD1G93A transgenic mice from different backgrounds (129Sv and C57 showed consistent phenotypic differences for disease progression. A hierarchy of Gaussian isused processes to model condition-specific and gene-specific temporal co-variances. This study demonstrated about finding some significant gene expression profiles and clusters of associated or co-regulated gene expressions together from four groups of data (SOD1G93A and Ntg from 129Sv and C57 backgrounds. Our study shows the effectiveness of sharing information between replicates and different model conditions when modelling gene expression time series. Further gene enrichment score analysis and ontology pathway analysis of some specified clusters for a particular group may lead toward identifying features underlying the differential speed of disease progression.

Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

Directory of Open Access Journals (Sweden)

Olszewski Kellen L

2007-07-01

Full Text Available Abstract Background The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes. Results We developed Nearest Neighbor Networks (NNN, a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods. Conclusion The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the

Unusual Gene Order and Organization of the Sea Urchin HoxCluster

Energy Technology Data Exchange (ETDEWEB)

Richardson, Paul M.; Lucas, Susan; Cameron, R. Andrew; Rowen,Lee; Nesbitt, Ryan; Bloom, Scott; Rast, Jonathan P.; Berney, Kevin; Arenas-Mena, Cesar; Martinez, Pedro; Davidson, Eric H.; Peterson, KevinJ.; Hood, Leroy

2005-05-10

The highly consistent gene order and axial colinear expression patterns found in vertebrate hox gene clusters are less well conserved across the rest of bilaterians. We report the first deuterostome instance of an intact hox cluster with a unique gene order where the paralog groups are not expressed in a sequential manner. The finished sequence from BAC clones from the genome of the sea urchin, Strongylocentrotus purpuratus, reveals a gene order wherein the anterior genes (Hox1, Hox2 and Hox3) lie nearest the posterior genes in the cluster such that the most 3' gene is Hox5. (The gene order is : 5'-Hox1,2, 3, 11/13c, 11/13b, '11/13a, 9/10, 8, 7, 6, 5 - 3)'. The finished sequence result is corroborated by restriction mapping evidence and BAC-end scaffold analyses. Comparisons with a putative ancestral deuterostome Hox gene cluster suggest that the rearrangements leading to the sea urchin gene order were many and complex.

A recently transferred cluster of bacterial genes in Trichomonas vaginalis - lateral gene transfer and the fate of acquired genes

Science.gov (United States)

2014-01-01

Background Lateral Gene Transfer (LGT) has recently gained recognition as an important contributor to some eukaryote proteomes, but the mechanisms of acquisition and fixation in eukaryotic genomes are still uncertain. A previously defined norm for LGTs in microbial eukaryotes states that the majority are genes involved in metabolism, the LGTs are typically localized one by one, surrounded by vertically inherited genes on the chromosome, and phylogenetics shows that a broad collection of bacterial lineages have contributed to the transferome. Results A unique 34 kbp long fragment with 27 clustered genes (TvLF) of prokaryote origin was identified in the sequenced genome of the protozoan parasite Trichomonas vaginalis. Using a PCR based approach we confirmed the presence of the orthologous fragment in four additional T. vaginalis strains. Detailed sequence analyses unambiguously suggest that TvLF is the result of one single, recent LGT event. The proposed donor is a close relative to the firmicute bacterium Peptoniphilus harei. High nucleotide sequence similarity between T. vaginalis strains, as well as to P. harei, and the absence of homologs in other Trichomonas species, suggests that the transfer event took place after the radiation of the genus Trichomonas. Some genes have undergone pseudogenization and degradation, indicating that they may not be retained in the future. Functional annotations reveal that genes involved in informational processes are particularly prone to degradation. Conclusions We conclude that, although the majority of eukaryote LGTs are single gene occurrences, they may be acquired in clusters of several genes that are subsequently cleansed of evolutionarily less advantageous genes. PMID:24898731

Hox gene cluster of the ascidian, Halocynthia roretzi, reveals multiple ancient steps of cluster disintegration during ascidian evolution.

Science.gov (United States)

Sekigami, Yuka; Kobayashi, Takuya; Omi, Ai; Nishitsuji, Koki; Ikuta, Tetsuro; Fujiyama, Asao; Satoh, Noriyuki; Saiga, Hidetoshi

2017-01-01

Hox gene clusters with at least 13 paralog group (PG) members are common in vertebrate genomes and in that of amphioxus. Ascidians, which belong to the subphylum Tunicata (Urochordata), are phylogenetically positioned between vertebrates and amphioxus, and traditionally divided into two groups: the Pleurogona and the Enterogona. An enterogonan ascidian, Ciona intestinalis ( Ci ), possesses nine Hox genes localized on two chromosomes; thus, the Hox gene cluster is disintegrated. We investigated the Hox gene cluster of a pleurogonan ascidian, Halocynthia roretzi ( Hr ) to investigate whether Hox gene cluster disintegration is common among ascidians, and if so, how such disintegration occurred during ascidian or tunicate evolution. Our phylogenetic analysis reveals that the Hr Hox gene complement comprises nine members, including one with a relatively divergent Hox homeodomain sequence. Eight of nine Hr Hox genes were orthologous to Ci-Hox1 , 2, 3, 4, 5, 10, 12 and 13. Following the phylogenetic classification into 13 PGs, we designated Hr Hox genes as Hox1, 2, 3, 4, 5, 10, 11/12/13.a , 11/12/13.b and HoxX . To address the chromosomal arrangement of the nine Hox genes, we performed two-color chromosomal fluorescent in situ hybridization, which revealed that the nine Hox genes are localized on a single chromosome in Hr , distinct from their arrangement in Ci . We further examined the order of the nine Hox genes on the chromosome by chromosome/scaffold walking. This analysis suggested a gene order of Hox1 , 11/12/13.b, 11/12/13.a, 10, 5, X, followed by either Hox4, 3, 2 or Hox2, 3, 4 on the chromosome. Based on the present results and those previously reported in Ci , we discuss the establishment of the Hox gene complement and disintegration of Hox gene clusters during the course of ascidian or tunicate evolution. The Hox gene cluster and the genome must have experienced extensive reorganization during the course of evolution from the ancestral tunicate to Hr and Ci

Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters

NARCIS (Netherlands)

Cimermancic, P.; Medema, Marnix; Claesen, J.; Kurika, K.; Wieland Brown, L.C.; Mavrommatis, K.; Pati, A.; Godfrey, P.A.; Koehrsen, M.; Clardy, J.; Birren, B. W.; Takano, Eriko; Sali, A.; Linington, R.G.; Fischbach, M.A.

2014-01-01

Although biosynthetic gene clusters (BGCs) have been discovered for hundreds of bacterial metabolites, our knowledge of their diversity remains limited. Here, we used a novel algorithm to systematically identify BGCs in the extensive extant microbial sequencing data. Network analysis of the

In silico analysis highlights the frequency and diversity of type 1 lantibiotic gene clusters in genome sequenced bacteria

LENUS (Irish Health Repository)

Marsh, Alan J

2010-11-30

Abstract Background Lantibiotics are lanthionine-containing, post-translationally modified antimicrobial peptides. These peptides have significant, but largely untapped, potential as preservatives and chemotherapeutic agents. Type 1 lantibiotics are those in which lanthionine residues are introduced into the structural peptide (LanA) through the activity of separate lanthionine dehydratase (LanB) and lanthionine synthetase (LanC) enzymes. Here we take advantage of the conserved nature of LanC enzymes to devise an in silico approach to identify potential lantibiotic-encoding gene clusters in genome sequenced bacteria. Results In total 49 novel type 1 lantibiotic clusters were identified which unexpectedly were associated with species, genera and even phyla of bacteria which have not previously been associated with lantibiotic production. Conclusions Multiple type 1 lantibiotic gene clusters were identified at a frequency that suggests that these antimicrobials are much more widespread than previously thought. These clusters represent a rich repository which can yield a large number of valuable novel antimicrobials and biosynthetic enzymes.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

Science.gov (United States)

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

A phylogenomic gene cluster resource: The phylogeneticallyinferred groups (PhlGs) database

Energy Technology Data Exchange (ETDEWEB)

Dehal, Paramvir S.; Boore, Jeffrey L.

2005-08-25

We present here the PhIGs database, a phylogenomic resource for sequenced genomes. Although many methods exist for clustering gene families, very few attempt to create truly orthologous clusters sharing descent from a single ancestral gene across a range of evolutionary depths. Although these non-phylogenetic gene family clusters have been used broadly for gene annotation, errors are known to be introduced by the artifactual association of slowly evolving paralogs and lack of annotation for those more rapidly evolving. A full phylogenetic framework is necessary for accurate inference of function and for many studies that address pattern and mechanism of the evolution of the genome. The automated generation of evolutionary gene clusters, creation of gene trees, determination of orthology and paralogy relationships, and the correlation of this information with gene annotations, expression information, and genomic context is an important resource to the scientific community.

Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

Directory of Open Access Journals (Sweden)

Paules Richard S

2007-11-01

Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

Evaluation of potential regulatory elements identified as DNase I hypersensitive sites in the CFTR gene

DEFF Research Database (Denmark)

Phylactides, M.; Rowntree, R.; Nuthall, H.

2002-01-01

hypersensitive sites (DHS) within the locus. We previously identified at least 12 clusters of DHS across the CFTR gene and here further evaluate DHS in introns 2,3,10,16,17a, 18, 20 and 21 to assess their functional importance in regulation of CFTR gene expression. Transient transfections of enhancer/reporter...

Lampreys, the jawless vertebrates, contain only two ParaHox gene clusters.

Science.gov (United States)

Zhang, Huixian; Ravi, Vydianathan; Tay, Boon-Hui; Tohari, Sumanty; Pillai, Nisha E; Prasad, Aravind; Lin, Qiang; Brenner, Sydney; Venkatesh, Byrappa

2017-08-22

ParaHox genes ( Gsx , Pdx , and Cdx ) are an ancient family of developmental genes closely related to the Hox genes. They play critical roles in the patterning of brain and gut. The basal chordate, amphioxus, contains a single ParaHox cluster comprising one member of each family, whereas nonteleost jawed vertebrates contain four ParaHox genomic loci with six or seven ParaHox genes. Teleosts, which have experienced an additional whole-genome duplication, contain six ParaHox genomic loci with six ParaHox genes. Jawless vertebrates, represented by lampreys and hagfish, are the most ancient group of vertebrates and are crucial for understanding the origin and evolution of vertebrate gene families. We have previously shown that lampreys contain six Hox gene loci. Here we report that lampreys contain only two ParaHox gene clusters (designated as α- and β-clusters) bearing five ParaHox genes ( Gsxα , Pdxα , Cdxα , Gsxβ , and Cdxβ ). The order and orientation of the three genes in the α-cluster are identical to that of the single cluster in amphioxus. However, the orientation of Gsxβ in the β-cluster is inverted. Interestingly, Gsxβ is expressed in the eye, unlike its homologs in jawed vertebrates, which are expressed mainly in the brain. The lamprey Pdxα is expressed in the pancreas similar to jawed vertebrate Pdx genes, indicating that the pancreatic expression of Pdx was acquired before the divergence of jawless and jawed vertebrate lineages. It is likely that the lamprey Pdxα plays a crucial role in pancreas specification and insulin production similar to the Pdx of jawed vertebrates.

Gene expression analysis to identify molecular correlates of pre- and post-conditioning derived neuroprotection.

Science.gov (United States)

Prasad, Shiv S; Russell, Marsha; Nowakowska, Margeryta; Williams, Andrew; Yauk, Carole

2012-06-01

Mild ischaemic exposures before or after severe injurious ischaemia that elicit neuroprotective responses are referred to as preconditioning and post-conditioning. The corresponding molecular mechanisms of neuroprotection are not completely understood. Identification of the genes and associated pathways of corresponding neuroprotection would provide insight into neuronal survival, potential therapeutic approaches and assessments of therapies for stroke. The objectives of this study were to use global gene expression approach to infer the molecular mechanisms in pre- and post-conditioning-derived neuroprotection in cortical neurons following oxygen and glucose deprivation (OGD) in vitro and then to apply these findings to predict corresponding functional pathways. To this end, microarray analysis was applied to rat cortical neurons with or without the pre- and post-conditioning treatments at 3-h post-reperfusion, and differentially expressed transcripts were subjected to statistical, hierarchical clustering and pathway analyses. The expression patterns of 3,431 genes altered under all conditions of ischaemia (with and without pre- or post-conditioning). We identified 1,595 genes that were commonly regulated within both the pre- and post-conditioning treatments. Cluster analysis revealed that transcription profiles clustered tightly within controls, non-conditioned OGD and neuroprotected groups. Two clusters defining neuroprotective conditions associated with up- and downregulated genes were evident. The five most upregulated genes within the neuroprotective clusters were Tagln, Nes, Ptrf, Vim and Adamts9, and the five most downregulated genes were Slc7a3, Bex1, Brunol4, Nrxn3 and Cpne4. Pathway analysis revealed that the intracellular and second messenger signalling pathways in addition to cell death were predominantly associated with downregulated pre- and post-conditioning associated genes, suggesting that modulation of cell death and signal transduction pathways

Fine Mapping of Two Wheat Powdery Mildew Resistance Genes Located at the Pm1 Cluster

Directory of Open Access Journals (Sweden)

Junchao Liang

2016-07-01

Full Text Available Powdery mildew caused by (DC. f. sp. ( is a globally devastating foliar disease of wheat ( L.. More than a dozen genes against this disease, identified from wheat germplasms of different ploidy levels, have been mapped to the region surrounding the locus on the long arm of chromosome 7A, which forms a resistance (-gene cluster. and from einkorn wheat ( L. were two of the genes belonging to this cluster. This study was initiated to fine map these two genes toward map-based cloning. Comparative genomics study showed that macrocolinearity exists between L. chromosome 1 (Bd1 and the – region, which allowed us to develop markers based on the wheat sequences orthologous to genes contained in the Bd1 region. With these and other newly developed and published markers, high-resolution maps were constructed for both and using large F populations. Moreover, a physical map of was constructed through chromosome walking with bacterial artificial chromosome (BAC clones and comparative mapping. Eventually, and were restricted to a 0.12- and 0.86-cM interval, respectively. Based on the closely linked common markers, , , and (another powdery mildew resistance gene in the cluster were not allelic to one another. Severe recombination suppression and disruption of synteny were noted in the region encompassing . These results provided useful information for map-based cloning of the genes in the cluster and interpretation of their evolution.

Comprehensive annotation of secondary metabolite biosynthetic genes and gene clusters of Aspergillus nidulans, A. fumigatus, A. niger and A. oryzae

Science.gov (United States)

2013-01-01

Background Secondary metabolite production, a hallmark of filamentous fungi, is an expanding area of research for the Aspergilli. These compounds are potent chemicals, ranging from deadly toxins to therapeutic antibiotics to potential anti-cancer drugs. The genome sequences for multiple Aspergilli have been determined, and provide a wealth of predictive information about secondary metabolite production. Sequence analysis and gene overexpression strategies have enabled the discovery of novel secondary metabolites and the genes involved in their biosynthesis. The Aspergillus Genome Database (AspGD) provides a central repository for gene annotation and protein information for Aspergillus species. These annotations include Gene Ontology (GO) terms, phenotype data, gene names and descriptions and they are crucial for interpreting both small- and large-scale data and for aiding in the design of new experiments that further Aspergillus research. Results We have manually curated Biological Process GO annotations for all genes in AspGD with recorded functions in secondary metabolite production, adding new GO terms that specifically describe each secondary metabolite. We then leveraged these new annotations to predict roles in secondary metabolism for genes lacking experimental characterization. As a starting point for manually annotating Aspergillus secondary metabolite gene clusters, we used antiSMASH (antibiotics and Secondary Metabolite Analysis SHell) and SMURF (Secondary Metabolite Unknown Regions Finder) algorithms to identify potential clusters in A. nidulans, A. fumigatus, A. niger and A. oryzae, which we subsequently refined through manual curation. Conclusions This set of 266 manually curated secondary metabolite gene clusters will facilitate the investigation of novel Aspergillus secondary metabolites. PMID:23617571

Hotspots of missense mutation identify novel neurodevelopmental disorder genes and functional domains

Science.gov (United States)

Geisheker, Madeleine R.; Heymann, Gabriel; Wang, Tianyun; Coe, Bradley P.; Turner, Tychele N.; Stessman, Holly A.F.; Hoekzema, Kendra; Kvarnung, Malin; Shaw, Marie; Friend, Kathryn; Liebelt, Jan; Barnett, Christopher; Thompson, Elizabeth M.; Haan, Eric; Guo, Hui; Anderlid, Britt-Marie; Nordgren, Ann; Lindstrand, Anna; Vandeweyer, Geert; Alberti, Antonino; Avola, Emanuela; Vinci, Mirella; Giusto, Stefania; Pramparo, Tiziano; Pierce, Karen; Nalabolu, Srinivasa; Michaelson, Jacob J.; Sedlacek, Zdenek; Santen, Gijs W.E.; Peeters, Hilde; Hakonarson, Hakon; Courchesne, Eric; Romano, Corrado; Kooy, R. Frank; Bernier, Raphael A.; Nordenskjöld, Magnus; Gecz, Jozef; Xia, Kun; Zweifel, Larry S.; Eichler, Evan E.

2017-01-01

Although de novo missense mutations have been predicted to account for more cases of autism than gene-truncating mutations, most research has focused on the latter. We identified the properties of de novo missense mutations in patients with neurodevelopmental disorders (NDDs) and highlight 35 genes with excess missense mutations. Additionally, 40 amino acid sites were recurrently mutated in 36 genes, and targeted sequencing of 20 sites in 17,689 NDD patients identified 21 new patients with identical missense mutations. One recurrent site (p.Ala636Thr) occurs in a glutamate receptor subunit, GRIA1. This same amino acid substitution in the homologous but distinct mouse glutamate receptor subunit Grid2 is associated with Lurcher ataxia. Phenotypic follow-up in five individuals with GRIA1 mutations shows evidence of specific learning disabilities and autism. Overall, we find significant clustering of de novo mutations in 200 genes, highlighting specific functional domains and synaptic candidate genes important in NDD pathology. PMID:28628100

Comparative analysis of clustering methods for gene expression time course data

Directory of Open Access Journals (Sweden)

Ivan G. Costa

2004-01-01

Full Text Available This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series. Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification.

The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

Directory of Open Access Journals (Sweden)

Chen Yidong

2004-01-01

Full Text Available An unsupervised data clustering method, called the local maximum clustering (LMC method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the -mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999.

Gene Clusters for Insecticidal Loline Alkaloids in the Grass-Endophytic Fungus Neotyphodium uncinatum

OpenAIRE

Spiering, Martin J.; Moon, Christina D.; Wilkinson, Heather H.; Schardl, Christopher L.

2005-01-01

Loline alkaloids are produced by mutualistic fungi symbiotic with grasses, and they protect the host plants from insects. Here we identify in the fungal symbiont, Neotyphodium uncinatum, two homologous gene clusters (LOL-1 and LOL-2) associated with loline-alkaloid production. Nine genes were identified in a 25-kb region of LOL-1 and designated (in order) lolF-1, lolC-1, lolD-1, lolO-1, lolA-1, lolU-1, lolP-1, lolT-1, and lolE-1. LOL-2 contained the homologs lolC-2 through lolE-2 in the same ...

Analysis of pan-genome to identify the core genes and essential genes of Brucella spp.

Science.gov (United States)

Yang, Xiaowen; Li, Yajie; Zang, Juan; Li, Yexia; Bie, Pengfei; Lu, Yanli; Wu, Qingmin

2016-04-01

Brucella spp. are facultative intracellular pathogens, that cause a contagious zoonotic disease, that can result in such outcomes as abortion or sterility in susceptible animal hosts and grave, debilitating illness in humans. For deciphering the survival mechanism of Brucella spp. in vivo, 42 Brucella complete genomes from NCBI were analyzed for the pan-genome and core genome by identification of their composition and function of Brucella genomes. The results showed that the total 132,143 protein-coding genes in these genomes were divided into 5369 clusters. Among these, 1710 clusters were associated with the core genome, 1182 clusters with strain-specific genes and 2477 clusters with dispensable genomes. COG analysis indicated that 44 % of the core genes were devoted to metabolism, which were mainly responsible for energy production and conversion (COG category C), and amino acid transport and metabolism (COG category E). Meanwhile, approximately 35 % of the core genes were in positive selection. In addition, 1252 potential essential genes were predicted in the core genome by comparison with a prokaryote database of essential genes. The results suggested that the core genes in Brucella genomes are relatively conservation, and the energy and amino acid metabolism play a more important role in the process of growth and reproduction in Brucella spp. This study might help us to better understand the mechanisms of Brucella persistent infection and provide some clues for further exploring the gene modules of the intracellular survival in Brucella spp.

Evaluation of gene-expression clustering via mutual information distance measure

Directory of Open Access Journals (Sweden)

Maimon Oded

2007-03-01

Full Text Available Abstract Background The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compare different clustering solutions when using the Mutual Information (MI measure versus the use of the well known Euclidean distance and Pearson correlation coefficient. Results Relying on several public gene expression datasets, we evaluate the homogeneity and separation scores of different clustering solutions. It was found that the use of the MI measure yields a more significant differentiation among erroneous clustering solutions. The proposed measure was also used to analyze the performance of several known clustering algorithms. A comparative study of these algorithms reveals that their "best solutions" are ranked almost oppositely when using different distance measures, despite the found correspondence between these measures when analysing the averaged scores of groups of solutions. Conclusion In view of the results, further attention should be paid to the selection of a proper distance measure for analyzing the clustering of gene expression data.

A highly divergent gene cluster in honey bees encodes a novel silk family

OpenAIRE

Sutherland, Tara D.; Campbell, Peter M.; Weisman, Sarah; Trueman, Holly E.; Sriskantha, Alagacone; Wanjura, Wolfgang J.; Haritos, Victoria S.

2006-01-01

The pupal cocoon of the domesticated silk moth Bombyx mori is the best known and most extensively studied insect silk. It is not widely known that Apis mellifera larvae also produce silk. We have used a combination of genomic and proteomic techniques to identify four honey bee fiber genes (AmelFibroin1–4) and two silk-associated genes (AmelSA1 and 2). The four fiber genes are small, comprise a single exon each, and are clustered on a short genomic region where the open reading frames are GC-r...

Minimum Information about a Biosynthetic Gene cluster : commentary

NARCIS (Netherlands)

Medema, Marnix H; Kottmann, Renzo; Yilmaz, Pelin; Cummings, Matthew; Biggins, John B; Blin, Kai; de Bruijn, Irene; Chooi, Yit Heng; Claesen, Jan; Coates, R Cameron; Cruz-Morales, Pablo; Duddela, Srikanth; Dusterhus, Stephanie; Edwards, Daniel J; Fewer, David P; Garg, Neha; Geiger, Christoph; Gomez-Escribano, Juan Pablo; Greule, Anja; Hadjithomas, Michalis; Haines, Anthony S; Helfrich, Eric J N; Hillwig, Matthew L; Ishida, Keishi; Jones, Adam C; Jones, Carla S; Jungmann, Katrin; Kegler, Carsten; Kim, Hyun Uk; Kotter, Peter; Krug, Daniel; Masschelein, Joleen; Melnik, Alexey V; Mantovani, Simone M; Monroe, Emily A; Moore, Marcus; Moss, Nathan; Nutzmann, Hans-Wilhelm; Pan, Guohui; Pati, Amrita; Petras, Daniel; Reen, F Jerry; Rosconi, Federico; Rui, Zhe; Tian, Zhenhua; Tobias, Nicholas J; Tsunematsu, Yuta; Wiemann, Philipp; Wyckoff, Elizabeth; Yan, Xiaohui; Yim, Grace; Yu, Fengan; Xie, Yunchang; Aigle, Bertrand; Apel, Alexander K; Balibar, Carl J; Balskus, Emily P; Barona-Gomez, Francisco; Bechthold, Andreas; Bode, Helge B; Borriss, Rainer; Brady, Sean F; Brakhage, Axel A; Caffrey, Patrick; Cheng, Yi-Qiang; Clardy, Jon; Cox, Russell J; De Mot, Rene; Donadio, Stefano; Donia, Mohamed S; van der Donk, Wilfred A; Dorrestein, Pieter C; Doyle, Sean; Driessen, Arnold J M; Ehling-Schulz, Monika; Entian, Karl-Dieter; Fischbach, Michael A; Gerwick, Lena; Gerwick, William H; Gross, Harald; Gust, Bertolt; Hertweck, Christian; Hofte, Monica; Jensen, Susan E; Ju, Jianhua; Katz, Leonard; Kaysser, Leonard; Klassen, Jonathan L; Keller, Nancy P; Kormanec, Jan; Kuipers, Oscar P; Kuzuyama, Tomohisa; Kyrpides, Nikos C; Kwon, Hyung-Jin; Lautru, Sylvie; Lavigne, Rob; Lee, Chia Y; Linquan, Bai; Liu, Xinyu; Liu, Wen; Luzhetskyy, Andriy; Mahmud, Taifo; Mast, Yvonne; Mendez, Carmen; Metsa-Ketela, Mikko; Micklefield, Jason; Mitchell, Douglas A; Moore, Bradley S; Moreira, Leonilde M; Muller, Rolf; Neilan, Brett A; Nett, Markus; Nielsen, Jens; O'Gara, Fergal; Oikawa, Hideaki; Osbourn, Anne; Osburne, Marcia S; Ostash, Bohdan; Payne, Shelley M; Pernodet, Jean-Luc; Petricek, Miroslav; Piel, Jorn; Ploux, Olivier; Raaijmakers, Jos M; Salas, Jose A; Schmitt, Esther K; Scott, Barry; Seipke, Ryan F; Shen, Ben; Sherman, David H; Sivonen, Kaarina; Smanski, Michael J; Sosio, Margherita; Stegmann, Evi; Sussmuth, Roderich D; Tahlan, Kapil; Thomas, Christopher M; Tang, Yi; Truman, Andrew W; Viaud, Muriel; Walton, Jonathan D; Walsh, Christopher T; Weber, Tilmann; van Wezel, Gilles P; Wilkinson, Barrie; Willey, Joanne M; Wohlleben, Wolfgang; Wright, Gerard D; Ziemert, Nadine; Zhang, Changsheng; Zotchev, Sergey B; Breitling, Rainer; Takano, Eriko; Glockner, Frank Oliver

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit.

VRprofile: gene-cluster-detection-based profiling of virulence and antibiotic resistance traits encoded within genome sequences of pathogenic bacteria.

Science.gov (United States)

Li, Jun; Tai, Cui; Deng, Zixin; Zhong, Weihong; He, Yongqun; Ou, Hong-Yu

2017-01-10

VRprofile is a Web server that facilitates rapid investigation of virulence and antibiotic resistance genes, as well as extends these trait transfer-related genetic contexts, in newly sequenced pathogenic bacterial genomes. The used backend database MobilomeDB was firstly built on sets of known gene cluster loci of bacterial type III/IV/VI/VII secretion systems and mobile genetic elements, including integrative and conjugative elements, prophages, class I integrons, IS elements and pathogenicity/antibiotic resistance islands. VRprofile is thus able to co-localize the homologs of these conserved gene clusters using HMMer or BLASTp searches. With the integration of the homologous gene cluster search module with a sequence composition module, VRprofile has exhibited better performance for island-like region predictions than the other widely used methods. In addition, VRprofile also provides an integrated Web interface for aligning and visualizing identified gene clusters with MobilomeDB-archived gene clusters, or a variety set of bacterial genomes. VRprofile might contribute to meet the increasing demands of re-annotations of bacterial variable regions, and aid in the real-time definitions of disease-relevant gene clusters in pathogenic bacteria of interest. VRprofile is freely available at http://bioinfo-mml.sjtu.edu.cn/VRprofile. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

IGSA: Individual Gene Sets Analysis, including Enrichment and Clustering.

Science.gov (United States)

Wu, Lingxiang; Chen, Xiujie; Zhang, Denan; Zhang, Wubing; Liu, Lei; Ma, Hongzhe; Yang, Jingbo; Xie, Hongbo; Liu, Bo; Jin, Qing

2016-01-01

Analysis of gene sets has been widely applied in various high-throughput biological studies. One weakness in the traditional methods is that they neglect the heterogeneity of genes expressions in samples which may lead to the omission of some specific and important gene sets. It is also difficult for them to reflect the severities of disease and provide expression profiles of gene sets for individuals. We developed an application software called IGSA that leverages a powerful analytical capacity in gene sets enrichment and samples clustering. IGSA calculates gene sets expression scores for each sample and takes an accumulating clustering strategy to let the samples gather into the set according to the progress of disease from mild to severe. We focus on gastric, pancreatic and ovarian cancer data sets for the performance of IGSA. We also compared the results of IGSA in KEGG pathways enrichment with David, GSEA, SPIA, ssGSEA and analyzed the results of IGSA clustering and different similarity measurement methods. Notably, IGSA is proved to be more sensitive and specific in finding significant pathways, and can indicate related changes in pathways with the severity of disease. In addition, IGSA provides with significant gene sets profile for each sample.

Pichia stipitis genomics, transcriptomics, and gene clusters

Science.gov (United States)

Thomas W. Jeffries; Jennifer R. Headman Van Vleet

2009-01-01

Genome sequencing and subsequent global gene expression studies have advanced our understanding of the lignocellulose-fermenting yeast Pichia stipitis. These studies have provided an insight into its central carbon metabolism, and analysis of its genome has revealed numerous functional gene clusters and tandem repeats. Specialized physiological traits are often the...

Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features

Directory of Open Access Journals (Sweden)

Bissell MJ

2006-03-01

Full Text Available Abstract Background Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a user-defined list of genes and/or proteins. The strategy exploits annotation data present in gene-centered corpora and utilizes ideas from statistical information retrieval to discover and characterize properties shared by subsets of the list. The practical utility of this method is demonstrated by employing it in a retrospective study of two non-overlapping sets of genes defined by a published investigation as markers for normal human breast luminal epithelial cells and myoepithelial cells. Results Each genetic locus was characterized using a finite set of biological properties and represented as a vector of features indicating attributes associated with the locus (a gene attribute profile. In this study, the vector space models for a pre-defined list of genes were constructed from the Gene Ontology (GO terms and the Conserved Domain Database (CDD protein domain terms assigned to the loci by the gene-centered corpus LocusLink. This data set of GO- and CDD-based gene attribute profiles, vectors of binary random variables, was used to estimate multiple finite mixture models and each ensuing model utilized to partition the profiles into clusters. The resultant partitionings were combined using a unanimous voting scheme to produce consensus clusters, sets of profiles that co-occured consistently in the same cluster. Attributes that were important in defining the genes assigned to a consensus cluster were identified. The clusters and their attributes were inspected to ascertain the GO and CDD terms most associated with subsets of genes and in conjunction with external knowledge such as chromosomal location, used to gain functional insights into human breast biology. The 52 luminal epithelial cell markers and 89 myoepithelial cell markers are disjoint sets of genes. Ensemble attribute profile clustering-based analysis indicated that both lists

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

Science.gov (United States)

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering.

Science.gov (United States)

Liu, Ying; Ciliax, Brian J; Borges, Karin; Dasigi, Venu; Ram, Ashwin; Navathe, Shamkant B; Dingledine, Ray

2004-01-01

One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete clusters.

CAR gene cluster and transcript levels of carotenogenic genes in Rhodotorula mucilaginosa.

Science.gov (United States)

Landolfo, Sara; Ianiri, Giuseppe; Camiolo, Salvatore; Porceddu, Andrea; Mulas, Giuliana; Chessa, Rossella; Zara, Giacomo; Mannazzu, Ilaria

2018-01-01

A molecular approach was applied to the study of the carotenoid biosynthetic pathway of Rhodotorula mucilaginosa. At first, functional annotation of the genome of R. mucilaginosa C2.5t1 was carried out and gene ontology categories were assigned to 4033 predicted proteins. Then, a set of genes involved in different steps of carotenogenesis was identified and those coding for phytoene desaturase, phytoene synthase/lycopene cyclase and carotenoid dioxygenase (CAR genes) proved to be clustered within a region of ~10 kb. Quantitative PCR of the genes involved in carotenoid biosynthesis showed that genes coding for 3-hydroxy-3-methylglutharyl-CoA reductase and mevalonate kinase are induced during exponential phase while no clear trend of induction was observed for phytoene synthase/lycopene cyclase and phytoene dehydrogenase encoding genes. Thus, in R. mucilaginosa the induction of genes involved in the early steps of carotenoid biosynthesis is transient and accompanies the onset of carotenoid production, while that of CAR genes does not correlate with the amount of carotenoids produced. The transcript levels of genes coding for carotenoid dioxygenase, superoxide dismutase and catalase A increased during the accumulation of carotenoids, thus suggesting the activation of a mechanism aimed at the protection of cell structures from oxidative stress during carotenoid biosynthesis. The data presented herein, besides being suitable for the elucidation of the mechanisms that underlie carotenoid biosynthesis, will contribute to boosting the biotechnological potential of this yeast by improving the outcome of further research efforts aimed at also exploring other features of interest.

Comparison of loline alkaloid gene clusters across fungal endophytes: predicting the co-regulatory sequence motifs and the evolutionary history.

Science.gov (United States)

Kutil, Brandi L; Greenwald, Charles; Liu, Gang; Spiering, Martin J; Schardl, Christopher L; Wilkinson, Heather H

2007-10-01

LOL, a fungal secondary metabolite gene cluster found in Epichloë and Neotyphodium species, is responsible for production of insecticidal loline alkaloids. To analyze the genetic architecture and to predict the evolutionary history of LOL, we compared five clusters from four fungal species (single clusters from Epichloë festucae, Neotyphodium sp. PauTG-1, Neotyphodium coenophialum, and two clusters we previously characterized in Neotyphodium uncinatum). Using PhyloCon to compare putative lol gene promoter regions, we have identified four motifs conserved across the lol genes in all five clusters. Each motif has significant similarity to known fungal transcription factor binding sites in the TRANSFAC database. Conservation of these motifs is further support for the hypothesis that the lol genes are co-regulated. Interestingly, the history of asexual Neotyphodium spp. includes multiple interspecific hybridization events. Comparing clusters from three Neotyphodium species and E. festucae allowed us to determine which Epichloë ancestors are the most likely contributors of LOL in these asexual species. For example, while no present day Epichloë typhina isolates are known to produce lolines, our data support the hypothesis that the E. typhina ancestor(s) of three asexual endophyte species contained a LOL gene cluster. Thus, these data support a model of evolution in which the polymorphism in loline alkaloid production phenotypes among endophyte species is likely due to the loss of the trait over time.

G-NEST: A gene neighborhood scoring tool to identify co-conserved, co-expressed genes

Science.gov (United States)

In previous studies, gene neighborhoods--spatial clusters of co-expressed genes in the genome--have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Sc...

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

Directory of Open Access Journals (Sweden)

Landfors Mattias

2010-10-01

Full Text Available Abstract Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered, missing value imputation (2, standardization of data (2, gene selection (19 or clustering method (11. The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

Science.gov (United States)

2010-01-01

Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is

A method to identify differential expression profiles of time-course gene data with Fourier transformation.

Science.gov (United States)

Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong

2013-10-18

Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be

Recursive expectation-maximization clustering: A method for identifying buffering mechanisms composed of phenomic modules

Science.gov (United States)

Guo, Jingyu; Tian, Dehua; McKinney, Brett A.; Hartman, John L.

2010-06-01

Interactions between genetic and/or environmental factors are ubiquitous, affecting the phenotypes of organisms in complex ways. Knowledge about such interactions is becoming rate-limiting for our understanding of human disease and other biological phenomena. Phenomics refers to the integrative analysis of how all genes contribute to phenotype variation, entailing genome and organism level information. A systems biology view of gene interactions is critical for phenomics. Unfortunately the problem is intractable in humans; however, it can be addressed in simpler genetic model systems. Our research group has focused on the concept of genetic buffering of phenotypic variation, in studies employing the single-cell eukaryotic organism, S. cerevisiae. We have developed a methodology, quantitative high throughput cellular phenotyping (Q-HTCP), for high-resolution measurements of gene-gene and gene-environment interactions on a genome-wide scale. Q-HTCP is being applied to the complete set of S. cerevisiae gene deletion strains, a unique resource for systematically mapping gene interactions. Genetic buffering is the idea that comprehensive and quantitative knowledge about how genes interact with respect to phenotypes will lead to an appreciation of how genes and pathways are functionally connected at a systems level to maintain homeostasis. However, extracting biologically useful information from Q-HTCP data is challenging, due to the multidimensional and nonlinear nature of gene interactions, together with a relative lack of prior biological information. Here we describe a new approach for mining quantitative genetic interaction data called recursive expectation-maximization clustering (REMc). We developed REMc to help discover phenomic modules, defined as sets of genes with similar patterns of interaction across a series of genetic or environmental perturbations. Such modules are reflective of buffering mechanisms, i.e., genes that play a related role in the maintenance

Merging K-means with hierarchical clustering for identifying general-shaped groups.

Science.gov (United States)

Peterson, Anna D; Ghosh, Arka P; Maitra, Ranjan

2018-01-01

Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and K -means clustering are two approaches but have different strengths and weaknesses. For instance, hierarchical clustering identifies groups in a tree-like structure but suffers from computational complexity in large datasets while K -means clustering is efficient but designed to identify homogeneous spherically-shaped clusters. We present a hybrid non-parametric clustering approach that amalgamates the two methods to identify general-shaped clusters and that can be applied to larger datasets. Specifically, we first partition the dataset into spherical groups using K -means. We next merge these groups using hierarchical methods with a data-driven distance measure as a stopping criterion. Our proposal has the potential to reveal groups with general shapes and structure in a dataset. We demonstrate good performance on several simulated and real datasets.

Clinical Characteristics of Exacerbation-Prone Adult Asthmatics Identified by Cluster Analysis.

Science.gov (United States)

Kim, Mi Ae; Shin, Seung Woo; Park, Jong Sook; Uh, Soo Taek; Chang, Hun Soo; Bae, Da Jeong; Cho, You Sook; Park, Hae Sim; Yoon, Ho Joo; Choi, Byoung Whui; Kim, Yong Hoon; Park, Choon Sik

2017-11-01

Asthma is a heterogeneous disease characterized by various types of airway inflammation and obstruction. Therefore, it is classified into several subphenotypes, such as early-onset atopic, obese non-eosinophilic, benign, and eosinophilic asthma, using cluster analysis. A number of asthmatics frequently experience exacerbation over a long-term follow-up period, but the exacerbation-prone subphenotype has rarely been evaluated by cluster analysis. This prompted us to identify clusters reflecting asthma exacerbation. A uniform cluster analysis method was applied to 259 adult asthmatics who were regularly followed-up for over 1 year using 12 variables, selected on the basis of their contribution to asthma phenotypes. After clustering, clinical profiles and exacerbation rates during follow-up were compared among the clusters. Four subphenotypes were identified: cluster 1 was comprised of patients with early-onset atopic asthma with preserved lung function, cluster 2 late-onset non-atopic asthma with impaired lung function, cluster 3 early-onset atopic asthma with severely impaired lung function, and cluster 4 late-onset non-atopic asthma with well-preserved lung function. The patients in clusters 2 and 3 were identified as exacerbation-prone asthmatics, showing a higher risk of asthma exacerbation. Two different phenotypes of exacerbation-prone asthma were identified among Korean asthmatics using cluster analysis; both were characterized by impaired lung function, but the age at asthma onset and atopic status were different between the two. Copyright © 2017 The Korean Academy of Asthma, Allergy and Clinical Immunology · The Korean Academy of Pediatric Allergy and Respiratory Disease

Bacillus sp.CDB3 isolated from cattle dip-sites possesses two ars gene clusters

Institute of Scientific and Technical Information of China (English)

Somanath Bhat; Xi Luo; Zhiqiang Xu; Lixia Liu; Ren Zhang

2011-01-01

Contamination of soil and water by arsenic is a global problem.In Australia, the dipping of cattle in arsenic-containing solution to control cattle ticks in last centenary has left many sites heavily contaminated with arsenic and other toxicants.We had previously isolated five soil bacterial strains (CDB1-5) highly resistant to arsenic.To understand the resistance mechanism, molecular studies have been carried out.Two chromosome-encoded arsenic resistance (ars) gene clusters have been cloned from CDB3 (Bacillus sp.).They both function in Escherichia coli and cluster 1 exerts a much higher resistance to the toxic metalloid.Cluster 2 is smaller possessing four open reading frames (ORFs) arsRorf2BC, similar to that identified in Bacillus subtilis Skin element.Among the eight ORFs in cluster 1 five are analogs of common ars genes found in other bacteria, however, organized in a unique order arsRBCDA instead of arsRDABC.Three other putative genes are located directly downstream and designated as arsTIP based on the homologies of their theoretical translation sequences respectively to thioredoxin reductases, iron-sulphur cluster proteins and protein phosphatases.The latter two are novel of any known ars operons.The arsD gene from Bacillus species was cloned for the first time and the predict protein differs from the well studied E.coli ArsD by lacking two pairs of C-terrninal cysteine residues.Its functional involvement in arsenic resistance has been confirmed by a deletion experiment.There exists also an inverted repeat in the intergenic region between arsC and arsD implying some unknown transcription regulation.

Dominant control region of the human β- like globin gene cluster

NARCIS (Netherlands)

Blom van Assendelft, Margaretha van

1989-01-01

The structure and regulation of the human β -like globin gene cluster has been studied extensively. Genetic disorders connected with this gene cluster are responsible for human diseases associated with high levels of morbidity and mortality, such as β-thalassaemia and sickle cell anaemia. The work

Gene expression profile identifies potential biomarkers for human intervertebral disc degeneration.

Science.gov (United States)

Guo, Wei; Zhang, Bin; Li, Yan; Duan, Hui-Quan; Sun, Chao; Xu, Yun-Qiang; Feng, Shi-Qing

2017-12-01

The present study aimed to reveal the potential genes associated with the pathogenesis of intervertebral disc degeneration (IDD) by analyzing microarray data using bioinformatics. Gene expression profiles of two regions of the intervertebral disc were compared between patients with IDD and controls. GSE70362 containing two groups of gene expression profiles, 16 nucleus pulposus (NP) samples from patients with IDD and 8 from controls, and 16 annulus fibrosus (AF) samples from patients with IDD and 8 from controls, was downloaded from the Gene Expression Omnibus database. A total of 93 and 114 differentially expressed genes (DEGs) were identified in NP and AF samples, respectively, using a limma software package for the R programming environment. Gene Ontology (GO) function enrichment analysis was performed to identify the associated biological functions of DEGs in IDD, which indicated that the DEGs may be involved in various processes, including cell adhesion, biological adhesion and extracellular matrix organization. Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that the identified DEGs were potentially involved in focal adhesion and the p53 signaling pathway. Further analysis revealed that there were 35 common DEGs observed between the two regions (NP and AF), which may be further regulated by 6 clusters of microRNAs (miRNAs) retrieved with WebGestalt. The genes in the DEG‑miRNA regulatory network were annotated using GO function and KEGG pathway enrichment analysis, among which extracellular matrix organization was the most significant disrupted biological process and focal adhesion was the most significant dysregulated pathway. In addition, the result of protein‑protein interaction network modules demonstrated the involvement of inflammatory cytokine interferon signaling in IDD. These findings may not only advance the understanding of the pathogenesis of IDD, but also identify novel potential

Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

Science.gov (United States)

Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

2013-01-01

Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

Cluster analysis of clinical data identifies fibromyalgia subgroups.

Directory of Open Access Journals (Sweden)

Elisa Docampo

Full Text Available INTRODUCTION: Fibromyalgia (FM is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. MATERIAL AND METHODS: 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. RESULTS: VARIABLES CLUSTERED INTO THREE INDEPENDENT DIMENSIONS: "symptomatology", "comorbidities" and "clinical scales". Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1, high symptomatology and comorbidities (Cluster 2, and high symptomatology but low comorbidities (Cluster 3, showing differences in measures of disease severity. CONCLUSIONS: We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment.

The human TREM gene cluster at 6p21.1 encodes both activating and inhibitory single IgV domain receptors and includes NKp44.

Science.gov (United States)

Allcock, Richard J N; Barrow, Alexander D; Forbes, Simon; Beck, Stephan; Trowsdale, John

2003-02-01

We have characterized a cluster of single immunoglobulin variable (IgV) domain receptors centromeric of the major histocompatibility complex (MHC) on human chromosome 6. In addition to triggering receptor expressed on myeloid cells (TREM)-1 and TREM2, the cluster contains NKp44, a triggering receptor whose expression is limited to NK cells. We identified three new related genes and two gene fragments within a cluster of approximately 200 kb. Two of the three new genes lack charged residues in their transmembrane domain tails. Further, one of the genes contains two potential immunotyrosine Inhibitory motifs in its cytoplasmic tail, suggesting that it delivers inhibitory signals. The human and mouse TREM clusters appear to have diverged such that there are unique sequences in each species. Finally, each gene in the TREM cluster was expressed in a different range of cell types.

Genetic variations and haplotype diversity of the UGT1 gene cluster in the Chinese population.

Directory of Open Access Journals (Sweden)

Jing Yang

Full Text Available Vertebrates require tremendous molecular diversity to defend against numerous small hydrophobic chemicals. UDP-glucuronosyltransferases (UGTs are a large family of detoxification enzymes that glucuronidate xenobiotics and endobiotics, facilitating their excretion from the body. The UGT1 gene cluster contains a tandem array of variable first exons, each preceded by a specific promoter, and a common set of downstream constant exons, similar to the genomic organization of the protocadherin (Pcdh, immunoglobulin, and T-cell receptor gene clusters. To assist pharmacogenomics studies in Chinese, we sequenced nine first exons, promoter and intronic regions, and five common exons of the UGT1 gene cluster in a population sample of 253 unrelated Chinese individuals. We identified 101 polymorphisms and found 15 novel SNPs. We then computed allele frequencies for each polymorphism and reconstructed their linkage disequilibrium (LD map. The UGT1 cluster can be divided into five linkage blocks: Block 9 (UGT1A9, Block 9/7/6 (UGT1A9, UGT1A7, and UGT1A6, Block 5 (UGT1A5, Block 4/3 (UGT1A4 and UGT1A3, and Block 3' UTR. Furthermore, we inferred haplotypes and selected their tagSNPs. Finally, comparing our data with those of three other populations of the HapMap project revealed ethnic specificity of the UGT1 genetic diversity in Chinese. These findings have important implications for future molecular genetic studies of the UGT1 gene cluster as well as for personalized medical therapies in Chinese.

Identifying clusters of active transportation using spatial scan statistics.

Science.gov (United States)

Huang, Lan; Stinchcomb, David G; Pickle, Linda W; Dill, Jennifer; Berrigan, David

2009-08-01

There is an intense interest in the possibility that neighborhood characteristics influence active transportation such as walking or biking. The purpose of this paper is to illustrate how a spatial cluster identification method can evaluate the geographic variation of active transportation and identify neighborhoods with unusually high/low levels of active transportation. Self-reported walking/biking prevalence, demographic characteristics, street connectivity variables, and neighborhood socioeconomic data were collected from respondents to the 2001 California Health Interview Survey (CHIS; N=10,688) in Los Angeles County (LAC) and San Diego County (SDC). Spatial scan statistics were used to identify clusters of high or low prevalence (with and without age-adjustment) and the quantity of time spent walking and biking. The data, a subset from the 2001 CHIS, were analyzed in 2007-2008. Geographic clusters of significantly high or low prevalence of walking and biking were detected in LAC and SDC. Structural variables such as street connectivity and shorter block lengths are consistently associated with higher levels of active transportation, but associations between active transportation and socioeconomic variables at the individual and neighborhood levels are mixed. Only one cluster with less time spent walking and biking among walkers/bikers was detected in LAC, and this was of borderline significance. Age-adjustment affects the clustering pattern of walking/biking prevalence in LAC, but not in SDC. The use of spatial scan statistics to identify significant clustering of health behaviors such as active transportation adds to the more traditional regression analysis that examines associations between behavior and environmental factors by identifying specific geographic areas with unusual levels of the behavior independent of predefined administrative units.

Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes.

Science.gov (United States)

Jensen, Philip J; Fazio, Gennaro; Altman, Naomi; Praul, Craig; McNellis, Timothy W

2014-04-04

Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F1 breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). Transcription profiling was performed for 48 individual F1 apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. Gene expression profiling

Genome scan identifies a locus affecting gamma-globin expression in human beta-cluster YAC transgenic mice

Energy Technology Data Exchange (ETDEWEB)

Lin, S.D.; Cooper, P.; Fung, J.; Weier, H.U.G.; Rubin, E.M.

2000-03-01

Genetic factors affecting post-natal g-globin expression - a major modifier of the severity of both b-thalassemia and sickle cell anemia, have been difficult to study. This is especially so in mice, an organism lacking a globin gene with an expression pattern equivalent to that of human g-globin. To model the human b-cluster in mice, with the goal of screening for loci affecting human g-globin expression in vivo, we introduced a human b-globin cluster YAC transgene into the genome of FVB mice . The b-cluster contained a Greek hereditary persistence of fetal hemoglobin (HPFH) g allele resulting in postnatal expression of human g-globin in transgenic mice. The level of human g-globin for various F1 hybrids derived from crosses between the FVB transgenics and other inbred mouse strains was assessed. The g-globin level of the C3HeB/FVB transgenic mice was noted to be significantly elevated. To map genes affecting postnatal g-globin expression, a 20 centiMorgan (cM) genome scan of a C3HeB/F VB transgenics [prime] FVB backcross was performed, followed by high-resolution marker analysis of promising loci. From this analysis we mapped a locus within a 2.2 cM interval of mouse chromosome 1 at a LOD score of 4.2 that contributes 10.4% of variation in g-globin expression level. Combining transgenic modeling of the human b-globin gene cluster with quantitative trait analysis, we have identified and mapped a murine locus that impacts on human g-globin expression in vivo.

Hessian regularization based non-negative matrix factorization for gene expression data clustering.

Science.gov (United States)

Liu, Xiao; Shi, Jun; Wang, Congzhi

2015-01-01

Since a key step in the analysis of gene expression data is to detect groups of genes that have similar expression patterns, clustering technique is then commonly used to analyze gene expression data. Data representation plays an important role in clustering analysis. The non-negative matrix factorization (NMF) is a widely used data representation method with great success in machine learning. Although the traditional manifold regularization method, Laplacian regularization (LR), can improve the performance of NMF, LR still suffers from the problem of its weak extrapolating power. Hessian regularization (HR) is a newly developed manifold regularization method, whose natural properties make it more extrapolating, especially for small sample data. In this work, we propose the HR-based NMF (HR-NMF) algorithm, and then apply it to represent gene expression data for further clustering task. The clustering experiments are conducted on five commonly used gene datasets, and the results indicate that the proposed HR-NMF outperforms LR-based NMM and original NMF, which suggests the potential application of HR-NMF for gene expression data.

The Cremeomycin Biosynthetic Gene Cluster Encodes a Pathway for Diazo Formation.

Science.gov (United States)

Waldman, Abraham J; Pechersky, Yakov; Wang, Peng; Wang, Jennifer X; Balskus, Emily P

2015-10-12

Diazo groups are found in a range of natural products that possess potent biological activities. Despite longstanding interest in these metabolites, diazo group biosynthesis is not well understood, in part because of difficulties in identifying specific genes linked to diazo formation. Here we describe the discovery of the gene cluster that produces the o-diazoquinone natural product cremeomycin and its heterologous expression in Streptomyces lividans. We used stable isotope feeding experiments and in vitro characterization of biosynthetic enzymes to decipher the order of events in this pathway and establish that diazo construction involves late-stage N-N bond formation. This work represents the first successful production of a diazo-containing metabolite in a heterologous host, experimentally linking a set of genes with diazo formation. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MethylMix 2.0: an R package for identifying DNA methylation genes.

Science.gov (United States)

Cedoz, Pierre-Louis; Prunello, Marcos; Brennan, Kevin; Gevaert, Olivier

2018-04-14

DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is a major mechanism of gene expression deregulation in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. We developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes. Here we present a new version of MethylMix that automates the construction of DNA-methylation and gene expression datasets from The Cancer Genome Atlas (TCGA). More precisely, MethylMix 2.0 incorporates two major updates: the automated downloading of DNA methylation and gene expression datasets from TCGA and the automated preprocessing of such datasets: value imputation, batch correction and CpG sites clustering within each gene. The resulting datasets can subsequently be analyzed with MethylMix to identify transcriptionally predictive methylation states. We show that the Differential Methylation Values created by MethylMix can be used for cancer subtyping. olivier.gevaert@stanford.edu. https://bioconductor.org/packages/release/bioc/manuals/MethylMix/man/MethylMix.pdf. MethylMix 2.0 was implemented as an R package and is available in bioconductor.

Transcriptome analysis identifies genes involved in ethanol response of Saccharomyces cerevisiae in Agave tequilana juice.

Science.gov (United States)

Ramirez-Córdova, Jesús; Drnevich, Jenny; Madrigal-Pulido, Jaime Alberto; Arrizon, Javier; Allen, Kirk; Martínez-Velázquez, Moisés; Alvarez-Maya, Ikuri

2012-08-01

During ethanol fermentation, yeast cells are exposed to stress due to the accumulation of ethanol, cell growth is altered and the output of the target product is reduced. For Agave beverages, like tequila, no reports have been published on the global gene expression under ethanol stress. In this work, we used microarray analysis to identify Saccharomyces cerevisiae genes involved in the ethanol response. Gene expression of a tequila yeast strain of S. cerevisiae (AR5) was explored by comparing global gene expression with that of laboratory strain S288C, both after ethanol exposure. Additionally, we used two different culture conditions, cells grown in Agave tequilana juice as a natural fermentation media or grown in yeast-extract peptone dextrose as artificial media. Of the 6368 S. cerevisiae genes in the microarray, 657 genes were identified that had different expression responses to ethanol stress due to strain and/or media. A cluster of 28 genes was found over-expressed specifically in the AR5 tequila strain that could be involved in the adaptation to tequila yeast fermentation, 14 of which are unknown such as yor343c, ylr162w, ygr182c, ymr265c, yer053c-a or ydr415c. These could be the most suitable genes for transforming tequila yeast to increase ethanol tolerance in the tequila fermentation process. Other genes involved in response to stress (RFC4, TSA1, MLH1, PAU3, RAD53) or transport (CYB2, TIP20, QCR9) were expressed in the same cluster. Unknown genes could be good candidates for the development of recombinant yeasts with ethanol tolerance for use in industrial tequila fermentation.

Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data.

Directory of Open Access Journals (Sweden)

Manal Helal

Full Text Available BACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52% corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra

Hierarchical clustering of breast cancer methylomes revealed differentially methylated and expressed breast cancer genes.

Directory of Open Access Journals (Sweden)

I-Hsuan Lin

Full Text Available Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs and the hypomethylation of the megabase-sized partially methylated domains (PMDs are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.

Glycosulfatase-Encoding Gene Cluster in Bifidobacterium breve UCC2003.

Science.gov (United States)

Egan, Muireann; Jiang, Hao; O'Connell Motherway, Mary; Oscarson, Stefan; van Sinderen, Douwe

2016-11-15

Bifidobacteria constitute a specific group of commensal bacteria typically found in the gastrointestinal tract (GIT) of humans and other mammals. Bifidobacterium breve strains are numerically prevalent among the gut microbiota of many healthy breastfed infants. In the present study, we investigated glycosulfatase activity in a bacterial isolate from a nursling stool sample, B. breve UCC2003. Two putative sulfatases were identified on the genome of B. breve UCC2003. The sulfated monosaccharide N-acetylglucosamine-6-sulfate (GlcNAc-6-S) was shown to support the growth of B. breve UCC2003, while N-acetylglucosamine-3-sulfate, N-acetylgalactosamine-3-sulfate, and N-acetylgalactosamine-6-sulfate did not support appreciable growth. By using a combination of transcriptomic and functional genomic approaches, a gene cluster designated ats2 was shown to be specifically required for GlcNAc-6-S metabolism. Transcription of the ats2 cluster is regulated by a repressor open reading frame kinase (ROK) family transcriptional repressor. This study represents the first description of glycosulfatase activity within the Bifidobacterium genus. Bifidobacteria are saccharolytic organisms naturally found in the digestive tract of mammals and insects. Bifidobacterium breve strains utilize a variety of plant- and host-derived carbohydrates that allow them to be present as prominent members of the infant gut microbiota as well as being present in the gastrointestinal tract of adults. In this study, we introduce a previously unexplored area of carbohydrate metabolism in bifidobacteria, namely, the metabolism of sulfated carbohydrates. B. breve UCC2003 was shown to metabolize N-acetylglucosamine-6-sulfate (GlcNAc-6-S) through one of two sulfatase-encoding gene clusters identified on its genome. GlcNAc-6-S can be found in terminal or branched positions of mucin oligosaccharides, the glycoprotein component of the mucous layer that covers the digestive tract. The results of this study provide

Genetic homogeneity of Clostridium botulinum type A1 strains with unique toxin gene clusters.

Science.gov (United States)

Raphael, Brian H; Luquez, Carolina; McCroskey, Loretta M; Joseph, Lavin A; Jacobson, Mark J; Johnson, Eric A; Maslanka, Susan E; Andreadis, Joanne D

2008-07-01

A group of five clonally related Clostridium botulinum type A strains isolated from different sources over a period of nearly 40 years harbored several conserved genetic properties. These strains contained a variant bont/A1 with five nucleotide polymorphisms compared to the gene in C. botulinum strain ATCC 3502. The strains also had a common toxin gene cluster composition (ha-/orfX+) similar to that associated with bont/A in type A strains containing an unexpressed bont/B [termed A(B) strains]. However, bont/B was not identified in the strains examined. Comparative genomic hybridization demonstrated identical genomic content among the strains relative to C. botulinum strain ATCC 3502. In addition, microarray data demonstrated the absence of several genes flanking the toxin gene cluster among the ha-/orfX+ A1 strains, suggesting the presence of genomic rearrangements with respect to this region compared to the C. botulinum ATCC 3502 strain. All five strains were shown to have identical flaA variable region nucleotide sequences. The pulsed-field gel electrophoresis patterns of the strains were indistinguishable when digested with SmaI, and a shift in the size of at least one band was observed in a single strain when digested with XhoI. These results demonstrate surprising genomic homogeneity among a cluster of unique C. botulinum type A strains of diverse origin.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

Energy Technology Data Exchange (ETDEWEB)

Data Analysis and Visualization (IDAV) and the Department of Computer Science, University of California, Davis, One Shields Avenue, Davis CA 95616, USA,; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,' ' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA; Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA; Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA,; Computer Science Division,University of California, Berkeley, CA, USA,; Computer Science Department, University of California, Irvine, CA, USA,; All authors are with the Berkeley Drosophila Transcription Network Project, Lawrence Berkeley National Laboratory,; Rubel, Oliver; Weber, Gunther H.; Huang, Min-Yu; Bethel, E. Wes; Biggin, Mark D.; Fowlkes, Charless C.; Hendriks, Cris L. Luengo; Keranen, Soile V. E.; Eisen, Michael B.; Knowles, David W.; Malik, Jitendra; Hagen, Hans; Hamann, Bernd

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii) evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.

HOXA genes cluster: clinical implications of the smallest deletion

OpenAIRE

Pezzani, Lidia; Milani, Donatella; Manzoni, Francesca; Baccarin, Marco; Silipigni, Rosamaria; Guerneri, Silvana; Esposito, Susanna

2015-01-01

Background HOXA genes cluster plays a fundamental role in embryologic development. Deletion of the entire cluster is known to cause a clinically recognizable syndrome with mild developmental delay, characteristic facies, small feet with unusually short and big halluces, abnormal thumbs, and urogenital malformations. The clinical manifestations may vary with different ranges of deletions of HOXA cluster and flanking regions. Case presentation We report a girl with the smallest deletion reporte...

Identifying Candidate Reprogramming Genes in Mouse Induced Pluripotent Stem Cells.

Science.gov (United States)

Gao, Fang; Li, Jingyu; Zhang, Heng; Yang, Xu; An, Tiezhu

2017-08-01

Factor-based induced reprogramming approaches have tremendous potential for human regenerative medicine, but the efficiencies of these approaches are still low. In this study, we analyzed the global transcriptional profiles of mouse induced pluripotent stem cells (miPSCs) and mouse embryonic stem cells (mESCs) from seven different labs and present here the first successful clustering according to cell type, not by lab of origin. We identified 2131 different expression genes (DEs) as candidate pluripotency-associated genes by comparing mESCs/miPSCs with somatic cells and 720 DEs between miPSCs and mESCs. Interestingly, there was a significant overlap between the two DE sets. Therefore, we defined the overlap DEs as "consensus DEs" including 313 miPSC-specific genes expressed at a higher level in miPSCs versus mESCs and 184 mESC-specific genes in total and reasoned that these may contribute to the differences in pluripotency between mESCs and miPSCs. A classification of "consensus DEs" according to their different expression levels between somatic cells and mESCs/miPSCs shows that 86% of the miPSC-specific genes are more highly expressed in somatic cells, while 73% of mESC-specific genes are highly expressed in mESCs/miPSCs, indicating that the miPSCs have not efficiently silenced the expression pattern of the somatic cells from which they are derived and failed to completely induce the genes with high expression levels in mESCs. We further revealed a strong correlation between oocyte-enriched factors and insufficiently induced mESC-specific genes and identified 11 hub genes via network analysis. In light of these findings, we postulated that these key hub genes might not only drive somatic cell nuclear transfer (SCNT) reprogramming but also augment the efficiency and quality of miPSC reprogramming.

A Metabolic Gene Cluster in the Wheat W1 and the Barley Cer-cqu Loci Determines β-Diketone Biosynthesis and Glaucousness.

Science.gov (United States)

Hen-Avivi, Shelly; Savin, Orna; Racovita, Radu C; Lee, Wing-Sham; Adamski, Nikolai M; Malitsky, Sergey; Almekias-Siegl, Efrat; Levy, Matan; Vautrin, Sonia; Bergès, Hélène; Friedlander, Gilgi; Kartvelishvily, Elena; Ben-Zvi, Gil; Alkan, Noam; Uauy, Cristobal; Kanyuka, Kostya; Jetter, Reinhard; Distelfeld, Assaf; Aharoni, Asaph

2016-06-01

The glaucous appearance of wheat (Triticum aestivum) and barley (Hordeum vulgare) plants, that is the light bluish-gray look of flag leaf, stem, and spike surfaces, results from deposition of cuticular β-diketone wax on their surfaces; this phenotype is associated with high yield, especially under drought conditions. Despite extensive genetic and biochemical characterization, the molecular genetic basis underlying the biosynthesis of β-diketones remains unclear. Here, we discovered that the wheat W1 locus contains a metabolic gene cluster mediating β-diketone biosynthesis. The cluster comprises genes encoding proteins of several families including type-III polyketide synthases, hydrolases, and cytochrome P450s related to known fatty acid hydroxylases. The cluster region was identified in both genetic and physical maps of glaucous and glossy tetraploid wheat, demonstrating entirely different haplotypes in these accessions. Complementary evidence obtained through gene silencing in planta and heterologous expression in bacteria supports a model for a β-diketone biosynthesis pathway involving members of these three protein families. Mutations in homologous genes were identified in the barley eceriferum mutants defective in β-diketone biosynthesis, demonstrating a gene cluster also in the β-diketone biosynthesis Cer-cqu locus in barley. Hence, our findings open new opportunities to breed major cereal crops for surface features that impact yield and stress response. © 2016 American Society of Plant Biologists. All rights reserved.

Organization of nif gene cluster in Frankia sp. EuIK1 strain, a symbiont of Elaeagnus umbellata.

Science.gov (United States)

Oh, Chang Jae; Kim, Ho Bang; Kim, Jitae; Kim, Won Jin; Lee, Hyoungseok; An, Chung Sun

2012-01-01

The nucleotide sequence of a 20.5-kb genomic region harboring nif genes was determined and analyzed. The fragment was obtained from Frankia sp. EuIK1 strain, an indigenous symbiont of Elaeagnus umbellata. A total of 20 ORFs including 12 nif genes were identified and subjected to comparative analysis with the genome sequences of 3 Frankia strains representing diverse host plant specificities. The nucleotide and deduced amino acid sequences showed highest levels of identity with orthologous genes from an Elaeagnus-infecting strain. The gene organization patterns around the nif gene clusters were well conserved among all 4 Frankia strains. However, characteristic features appeared in the location of the nifV gene for each Frankia strain, depending on the type of host plant. Sequence analysis was performed to determine the transcription units and suggested that there could be an independent operon starting from the nifW gene in the EuIK strain. Considering the organization patterns and their total extensions on the genome, we propose that the nif gene clusters remained stable despite genetic variations occurring in the Frankia genomes.

Human major histocompatibility complex contains a minimum of 19 genes between the complement cluster and HLA-B

International Nuclear Information System (INIS)

Spies, T.; Bresnahan, M.; Strominger, J.L.

1989-01-01

A 600-kilobase (kb) DNA segment from the human major histocompatibility complex (MHC) class III region was isolated by extension of a previous 435-kb chromosome walk. The contiguous series of cloned overlapping cosmids contains the entire 555-kb interval between C2 in the complement gene cluster and HLA-B. This region is known to encode the tumor necrosis factors (TNFs) α and β, B144, and the major heat shock protein HSP70. Moreover, a cluster of genes, BAT1-BAT5 (HLA-B-associated transcripts) have been localized in the vicinity of the genes for TNFα and TNFβ. An additional four genes were identified by isolation of corresponding cDNA clones with cosmid DNA probes. These genes for BAT6-BAT9 were mapped near the gene for C2 within a 120-kb region that includes a HSP70 gene pair. These results, together with complementary data from a similar recent study, indicated the presence of a minimum of 19 genes within the C2-HLA-B interval of the MHC class III region. Although the functional properties of most of these genes are yet unknown, they may be involved in some aspects of immunity. This idea is supported by the genetic mapping of the hematopoietic histocompatibility locus-1 (Hh-1) in recombinant mice between TNFα and H-2S, which is homologous to the complement gene cluster in humans

Characterization and detection of a widely distributed gene cluster that predicts anaerobic choline utilization by human gut bacteria.

Science.gov (United States)

Martínez-del Campo, Ana; Bodea, Smaranda; Hamer, Hilary A; Marks, Jonathan A; Haiser, Henry J; Turnbaugh, Peter J; Balskus, Emily P

2015-04-14

Elucidation of the molecular mechanisms underlying the human gut microbiota's effects on health and disease has been complicated by difficulties in linking metabolic functions associated with the gut community as a whole to individual microorganisms and activities. Anaerobic microbial choline metabolism, a disease-associated metabolic pathway, exemplifies this challenge, as the specific human gut microorganisms responsible for this transformation have not yet been clearly identified. In this study, we established the link between a bacterial gene cluster, the choline utilization (cut) cluster, and anaerobic choline metabolism in human gut isolates by combining transcriptional, biochemical, bioinformatic, and cultivation-based approaches. Quantitative reverse transcription-PCR analysis and in vitro biochemical characterization of two cut gene products linked the entire cluster to growth on choline and supported a model for this pathway. Analyses of sequenced bacterial genomes revealed that the cut cluster is present in many human gut bacteria, is predictive of choline utilization in sequenced isolates, and is widely but discontinuously distributed across multiple bacterial phyla. Given that bacterial phylogeny is a poor marker for choline utilization, we were prompted to develop a degenerate PCR-based method for detecting the key functional gene choline TMA-lyase (cutC) in genomic and metagenomic DNA. Using this tool, we found that new choline-metabolizing gut isolates universally possessed cutC. We also demonstrated that this gene is widespread in stool metagenomic data sets. Overall, this work represents a crucial step toward understanding anaerobic choline metabolism in the human gut microbiota and underscores the importance of examining this microbial community from a function-oriented perspective. Anaerobic choline utilization is a bacterial metabolic activity that occurs in the human gut and is linked to multiple diseases. While bacterial genes responsible for

Identifying seizure clusters in patients with psychogenic nonepileptic seizures.

Science.gov (United States)

Baird, Grayson L; Harlow, Lisa L; Machan, Jason T; Thomas, Dave; LaFrance, W C

2017-08-01

The present study explored how seizure clusters may be defined for those with psychogenic nonepileptic seizures (PNES), a topic for which there is a paucity of literature. The sample was drawn from a multisite randomized clinical trial for PNES; seizure data are from participants' seizure diaries. Three possible cluster definitions were examined: 1) common clinical definition, where ≥3 seizures in a day is considered a cluster, along with two novel statistical definitions, where ≥3 seizures in a day are considered a cluster if the observed number of seizures statistically exceeds what would be expected relative to a patient's: 1) average seizure rate prior to the trial, 2) observed seizure rate for the previous seven days. Prevalence of clusters was 62-68% depending on cluster definition used, and occurrence rate of clusters was 6-19% depending on cluster definition. Based on these data, clusters seem to be common in patients with PNES, and more research is needed to identify if clusters are related to triggers and outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression values.

Science.gov (United States)

Bhattacharya, Anindya; De, Rajat K

2010-08-01

Distance based clustering algorithms can group genes that show similar expression values under multiple experimental conditions. They are unable to identify a group of genes that have similar pattern of variation in their expression values. Previously we developed an algorithm called divisive correlation clustering algorithm (DCCA) to tackle this situation, which is based on the concept of correlation clustering. But this algorithm may also fail for certain cases. In order to overcome these situations, we propose a new clustering algorithm, called average correlation clustering algorithm (ACCA), which is able to produce better clustering solution than that produced by some others. ACCA is able to find groups of genes having more common transcription factors and similar pattern of variation in their expression values. Moreover, ACCA is more efficient than DCCA with respect to the time of execution. Like DCCA, we use the concept of correlation clustering concept introduced by Bansal et al. ACCA uses the correlation matrix in such a way that all genes in a cluster have the highest average correlation values with the genes in that cluster. We have applied ACCA and some well-known conventional methods including DCCA to two artificial and nine gene expression datasets, and compared the performance of the algorithms. The clustering results of ACCA are found to be more significantly relevant to the biological annotations than those of the other methods. Analysis of the results show the superiority of ACCA over some others in determining a group of genes having more common transcription factors and with similar pattern of variation in their expression profiles. Availability of the software: The software has been developed using C and Visual Basic languages, and can be executed on the Microsoft Windows platforms. The software may be downloaded as a zip file from http://www.isical.ac.in/~rajat. Then it needs to be installed. Two word files (included in the zip file) need to

Correlation-based iterative clustering methods for time course data: The identification of temporal gene response modules for influenza infection in humans

Directory of Open Access Journals (Sweden)

Michelle Carey

2016-10-01

Full Text Available Many pragmatic clustering methods have been developed to group data vectors or objects into clusters so that the objects in one cluster are very similar and objects in different clusters are distinct based on some similarity measure. The availability of time course data has motivated researchers to develop methods, such as mixture and mixed-effects modelling approaches, that incorporate the temporal information contained in the shape of the trajectory of the data. However, there is still a need for the development of time-course clustering methods that can adequately deal with inhomogeneous clusters (some clusters are quite large and others are quite small. Here we propose two such methods, hierarchical clustering (IHC and iterative pairwise-correlation clustering (IPC. We evaluate and compare the proposed methods to the Markov Cluster Algorithm (MCL and the generalised mixed-effects model (GMM using simulation studies and an application to a time course gene expression data set from a study containing human subjects who were challenged by a live influenza virus. We identify four types of temporal gene response modules to influenza infection in humans, i.e., single-gene modules (SGM, small-size modules (SSM, medium-size modules (MSM and large-size modules (LSM. The LSM contain genes that perform various fundamental biological functions that are consistent across subjects. The SSM and SGM contain genes that perform either different or similar biological functions that have complex temporal responses to the virus and are unique to each subject. We show that the temporal response of the genes in the LSM have either simple patterns with a single peak or trough a consequence of the transient stimuli sustained or state-transitioning patterns pertaining to developmental cues and that these modules can differentiate the severity of disease outcomes. Additionally, the size of gene response modules follows a power-law distribution with a consistent

The Genome Sequence of the Cyanobacterium Oscillatoria sp. PCC 6506 Reveals Several Gene Clusters Responsible for the Biosynthesis of Toxins and Secondary Metabolites▿

Science.gov (United States)

Méjean, Annick; Mazmouz, Rabia; Mann, Stéphane; Calteau, Alexandra; Médigue, Claudine; Ploux, Olivier

2010-01-01

We report a draft sequence of the genome of Oscillatoria sp. PCC 6506, a cyanobacterium that produces anatoxin-a and homoanatoxin-a, two neurotoxins, and cylindrospermopsin, a cytotoxin. Beside the clusters of genes responsible for the biosynthesis of these toxins, we have found other clusters of genes likely involved in the biosynthesis of not-yet-identified secondary metabolites. PMID:20675499

Comparative transcriptional profiling of the axolotl limb identifies a tripartite regeneration-specific gene program.

Directory of Open Access Journals (Sweden)

Dunja Knapp

Full Text Available Understanding how the limb blastema is established after the initial wound healing response is an important aspect of regeneration research. Here we performed parallel expression profile time courses of healing lateral wounds versus amputated limbs in axolotl. This comparison between wound healing and regeneration allowed us to identify amputation-specific genes. By clustering the expression profiles of these samples, we could detect three distinguishable phases of gene expression - early wound healing followed by a transition-phase leading to establishment of the limb development program, which correspond to the three phases of limb regeneration that had been defined by morphological criteria. By focusing on the transition-phase, we identified 93 strictly amputation-associated genes many of which are implicated in oxidative-stress response, chromatin modification, epithelial development or limb development. We further classified the genes based on whether they were or were not significantly expressed in the developing limb bud. The specific localization of 53 selected candidates within the blastema was investigated by in situ hybridization. In summary, we identified a set of genes that are expressed specifically during regeneration and are therefore, likely candidates for the regulation of blastema formation.

Aromatic Polyketide GTRI-02 is a Previously Unidentified Product of the act Gene Cluster in Streptomyces coelicolor A3(2).

Science.gov (United States)

Wu, Changsheng; Ichinose, Koji; Choi, Young Hae; van Wezel, Gilles P

2017-07-18

The biosynthesis of aromatic polyketides derived from type II polyketide synthases (PKSs) is complex, and it is not uncommon that highly similar gene clusters give rise to diverse structural architectures. The act biosynthetic gene cluster (BGC) of the model actinomycete Streptomyces coelicolor A3(2) is an archetypal type II PKS. Here we show that the act BGC also specifies the aromatic polyketide GTRI-02 (1) and propose a mechanism for the biogenesis of its 3,4-dihydronaphthalen-1(2H)-one backbone. Polyketide 1 was also produced by Streptomyces sp. MBT76 after activation of the act-like qin gene cluster by overexpression of the pathway-specific activator. Mining of this strain also identified dehydroxy-GTRI-02 (2), which most likely originated from dehydration of 1 during the isolation process. This work shows that even extensively studied model gene clusters such as act of S. coelicolor can still produce new chemistry, offering new perspectives for drug discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials

Directory of Open Access Journals (Sweden)

Andrew Williams

2015-12-01

previously defined, functionally relevant gene sets, the present study also identified two novel genes sets: a gene set associated with pulmonary fibrosis and a gene set associated with ROS, underlining the advantage of using a data-driven approach to identify novel, functionally related gene sets. The results can be used in future gene set enrichment analysis studies involving NMs or as features for clustering and classifying NMs of diverse properties.

An Integrated Approach Identifies Nhlh1 and Insm1 as Sonic Hedgehog-regulated Genes in Developing Cerebellum and Medulloblastoma

Directory of Open Access Journals (Sweden)

Enrico De Smaele

2008-01-01

Full Text Available Medulloblastoma (MB is the most common malignant brain tumor of childhood arising from deregulated cerebellar development. Sonic Hedgehog (Shh pathway plays a critical role in cerebellar development and its aberrant expression has been identified in MB. Gene expression profiling of cerebella from 1- to 14-day-old mice unveiled a cluster of genes whose expression correlates with the levels of Hedgehog (HH activity. From this cluster, we identified Insm1 and Nhlh1/NSCL1 as novel HH targets induced by Shh treatment in cultured cerebellar granule cell progenitors. Nhlh1 promoter was found to be bound and activated by Gli1 transcription factor. Remarkably, the expression of these genes is also upregulated in mouse and human HH-dependent MBs, suggesting that they may be either a part of the HH-induced tumorigenic process or a specific trait of HH-dependent tumor cells.

Genomic organization, tissue distribution and functional characterization of the rat Pate gene cluster.

Directory of Open Access Journals (Sweden)

Angireddy Rajesh

Full Text Available The cysteine rich prostate and testis expressed (Pate proteins identified till date are thought to resemble the three fingered protein/urokinase-type plasminogen activator receptor proteins. In this study, for the first time, we report the identification, cloning and characterization of rat Pate gene cluster and also determine the expression pattern. The rat Pate genes are clustered on chromosome 8 and their predicted proteins retained the ten cysteine signature characteristic to TFP/Ly-6 protein family. PATE and PATE-F three dimensional protein structure was found to be similar to that of the toxin bucandin. Though Pate gene expression is thought to be prostate and testis specific, we observed that rat Pate genes are also expressed in seminal vesicle and epididymis and in tissues beyond the male reproductive tract. In the developing rats (20-60 day old, expression of Pate genes seem to be androgen dependent in the epididymis and testis. In the adult rat, androgen ablation resulted in down regulation of the majority of Pate genes in the epididymides. PATE and PATE-F proteins were found to be expressed abundantly in the male reproductive tract of rats and on the sperm. Recombinant PATE protein exhibited potent antibacterial activity, whereas PATE-F did not exhibit any antibacterial activity. Pate expression was induced in the epididymides when challenged with LPS. Based on our results, we conclude that rat PATE proteins may contribute to the reproductive and defense functions.

A Link-Based Cluster Ensemble Approach For Improved Gene Expression Data Analysis

Directory of Open Access Journals (Sweden)

P.Balaji

2015-01-01

Full Text Available Abstract It is difficult from possibilities to select a most suitable effective way of clustering algorithm and its dataset for a defined set of gene expression data because we have a huge number of ways and huge number of gene expressions. At present many researchers are preferring to use hierarchical clustering in different forms this is no more totally optimal. Cluster ensemble research can solve this type of problem by automatically merging multiple data partitions from a wide range of different clusterings of any dimensions to improve both the quality and robustness of the clustering result. But we have many existing ensemble approaches using an association matrix to condense sample-cluster and co-occurrence statistics and relations within the ensemble are encapsulated only at raw level while the existing among clusters are totally discriminated. Finding these missing associations can greatly expand the capability of those ensemble methodologies for microarray data clustering. We propose general K-means cluster ensemble approach for the clustering of general categorical data into required number of partitions.

Biosynthesis of Akaeolide and Lorneic Acids and Annotation of Type I Polyketide Synthase Gene Clusters in the Genome of Streptomyces sp. NPS554

Directory of Open Access Journals (Sweden)

Tao Zhou

2015-01-01

Full Text Available The incorporation pattern of biosynthetic precursors into two structurally unique polyketides, akaeolide and lorneic acid A, was elucidated by feeding experiments with 13C-labeled precursors. In addition, the draft genome sequence of the producer, Streptomyces sp. NPS554, was performed and the biosynthetic gene clusters for these polyketides were identified. The putative gene clusters contain all the polyketide synthase (PKS domains necessary for assembly of the carbon skeletons. Combined with the 13C-labeling results, gene function prediction enabled us to propose biosynthetic pathways involving unusual carbon-carbon bond formation reactions. Genome analysis also indicated the presence of at least ten orphan type I PKS gene clusters that might be responsible for the production of new polyketides.

Activation and clustering of a Plasmodium falciparum var gene are affected by subtelomeric sequences.

Science.gov (United States)

Duffy, Michael F; Tang, Jingyi; Sumardy, Fransisca; Nguyen, Hanh H T; Selvarajah, Shamista A; Josling, Gabrielle A; Day, Karen P; Petter, Michaela; Brown, Graham V

2017-01-01

The Plasmodium falciparum var multigene family encodes the cytoadhesive, variant antigen PfEMP1. P. falciparum antigenic variation and cytoadhesion specificity are controlled by epigenetic switching between the single, or few, simultaneously expressed var genes. Most var genes are maintained in perinuclear clusters of heterochromatic telomeres. The active var gene(s) occupy a single, perinuclear var expression site. It is unresolved whether the var expression site forms in situ at a telomeric cluster or whether it is an extant compartment to which single chromosomes travel, thus controlling var switching. Here we show that transcription of a var gene did not require decreased colocalisation with clusters of telomeres, supporting var expression site formation in situ. However following recombination within adjacent subtelomeric sequences, the same var gene was persistently activated and did colocalise less with telomeric clusters. Thus, participation in stable, heterochromatic, telomere clusters and var switching are independent but are both affected by subtelomeric sequences. The var expression site colocalised with the euchromatic mark H3K27ac to a greater extent than it did with heterochromatic H3K9me3. H3K27ac was enriched within the active var gene promoter even when the var gene was transiently repressed in mature parasites and thus H3K27ac may contribute to var gene epigenetic memory. © 2016 Federation of European Biochemical Societies.

Identification of the Biosynthetic Gene Clusters for the Lipopeptides Fusaristatin A and W493 B in Fusarium graminearum and F. pseudograminearum

DEFF Research Database (Denmark)

Sørensen, Jens Laurids; Sondergaard, Teis Esben; Covarelli, Lorenzo

2014-01-01

The closely related species Fusarium graminearum and Fusarium pseudograminearum differ in that each contains a gene cluster with a polyketide synthase (PKS) and a nonribosomal peptide synthetase (NRPS) that is not present in the other species. To identify their products, we deleted PKS6 and NRPS7...... Fusarium species. On the basis of genes in the putative gene clusters we propose a model for biosynthesis where the polyketide product is shuttled to the NPRS via a CoA ligase and a thioesterase in F. pseudograminearum. In F. graminearum the polyketide is proposed to be directly assimilated by the NRPS....

Physical and genetic map of the major nif gene cluster from Azotobacter vinelandii.

OpenAIRE

Jacobson, M R; Brigle, K E; Bennett, L T; Setterquist, R A; Wilson, M S; Cash, V L; Beynon, J; Newton, W E; Dean, D R

1989-01-01

Determination of a 28,793-base-pair DNA sequence of a region from the Azotobacter vinelandii genome that includes and flanks the nitrogenase structural gene region was completed. This information was used to revise the previously proposed organization of the major nif cluster. The major nif cluster from A. vinelandii encodes 15 nif-specific genes whose products bear significant structural identity to the corresponding nif-specific gene products from Klebsiella pneumoniae. These genes include ...

Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

Science.gov (United States)

Gruben, Birgit S; Mäkelä, Miia R; Kowalczyk, Joanna E; Zhou, Miaomiao; Benoit-Gelber, Isabelle; De Vries, Ronald P

2017-11-23

The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ΔxlnR, ΔaraR, ΔamyR, ΔrhaR and ΔgalX that were grown on their specific inducing compounds. The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far. Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In

Evolution of the C-Type Lectin-Like Receptor Genes of the DECTIN-1 Cluster in the NK Gene Complex

Directory of Open Access Journals (Sweden)

Susanne Sattler

2012-01-01

Full Text Available Pattern recognition receptors are crucial in initiating and shaping innate and adaptive immune responses and often belong to families of structurally and evolutionarily related proteins. The human C-type lectin-like receptors encoded in the DECTIN-1 cluster within the NK gene complex contain prominent receptors with pattern recognition function, such as DECTIN-1 and LOX-1. All members of this cluster share significant homology and are considered to have arisen from subsequent gene duplications. Recent developments in sequencing and the availability of comprehensive sequence data comprising many species showed that the receptors of the DECTIN-1 cluster are not only homologous to each other but also highly conserved between species. Even in Caenorhabditis elegans, genes displaying homology to the mammalian C-type lectin-like receptors have been detected. In this paper, we conduct a comprehensive phylogenetic survey and give an up-to-date overview of the currently available data on the evolutionary emergence of the DECTIN-1 cluster genes.

Transcriptional profiling of whole blood identifies a unique 5-gene signature for myelofibrosis and imminent myelofibrosis transformation.

Directory of Open Access Journals (Sweden)

Hans Carl Hasselbalch

Full Text Available Identifying a distinct gene signature for myelofibrosis may yield novel information of the genes, which are responsible for progression of essential thrombocythemia and polycythemia vera towards myelofibrosis. We aimed at identifying a simple gene signature - composed of a few genes - which were selectively and highly deregulated in myelofibrosis patients. Gene expression microarray studies have been performed on whole blood from 69 patients with myeloproliferative neoplasms. Amongst the top-20 of the most upregulated genes in PMF compared to controls, we identified 5 genes (DEFA4, ELA2, OLFM4, CTSG, and AZU1, which were highly significantly deregulated in PMF only. None of these genes were significantly regulated in ET and PV patients. However, hierarchical cluster analysis showed that these genes were also highly expressed in a subset of patients with ET (n = 1 and PV (n = 4 transforming towards myelofibrosis and/or being featured by an aggressive phenotype. We have identified a simple 5-gene signature, which is uniquely and highly significantly deregulated in patients in transitional stages of ET and PV towards myelofibrosis and in patients with PMF only. Some of these genes are considered to be responsible for the derangement of bone marrow stroma in myelofibrosis. Accordingly, this gene-signature may reflect key processes in the pathogenesis and pathophysiology of myelofibrosis development.

NIH Researchers Identify OCD Risk Gene

Science.gov (United States)

... News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer 2006 Table of Contents For ... and Alcoholism (NIAAA) have identified a previously unknown gene variant that doubles an individual's risk for obsessive- ...

The complete coenzyme B12 biosynthesis gene cluster of Lactobacillus reuteri CRL 1098

NARCIS (Netherlands)

Santos, dos F.; Vera, J.L.; Heijden, van der R.; Valdez, G.F.; Vos, de W.M.; Sesma, F.; Hugenholtz, J.

2008-01-01

The coenzyme B12 production pathway in Lactobacillus reuteri has been deduced using a combination of genetic, biochemical and bioinformatics approaches. The coenzyme B12 gene cluster of Lb. reuteri CRL1098 has the unique feature of clustering together the cbi, cob and hem genes. It consists of 29

Identifying probable suicide clusters in wales using national mortality data.

Directory of Open Access Journals (Sweden)

Phillip Jones

Full Text Available Up to 2% of suicides in young people may occur in clusters i.e., close together in time and space. In early 2008 unprecedented attention was given by national and international news media to a suspected suicide cluster among young people living in Bridgend, Wales. This paper investigates the strength of statistical evidence for this apparent cluster, its size, and temporal and geographical limits.The analysis is based on official mortality statistics for Wales for 2000-2009 provided by the UK's Office for National Statistics (ONS. Temporo-spatial analysis was performed using Space Time Permutation Scan Statistics with SaTScan v9.1 for suicide deaths aged 15 and over, with a sub-group analysis focussing on cases aged 15-34 years. These analyses were conducted for deaths coded by ONS as: (i suicide or of undetermined intent (probable suicides and (ii for a combination of suicide, undetermined, and accidental poisoning and hanging (possible suicides. The temporo-spatial analysis did not identify any clusters of suicide or undetermined intent deaths (probable suicides. However, analysis of all deaths by suicide, undetermined intent, accidental poisoning and accidental hanging (possible suicides identified a temporo-spatial cluster (p = 0.029 involving 10 deaths amongst 15-34 year olds centred on the County Borough of Bridgend for the period 27(th December 2007 to 19(th February 2008. Less than 1% of possible suicides in younger people in Wales in the ten year period were identified as being cluster-related.There was a possible suicide cluster in young people in Bridgend between December 2007 and February 2008. This cluster was smaller, shorter in duration, and predominantly later than the phenomenon that was reported in national and international print media. Further investigation of factors leading to the onset and termination of this series of deaths, in particular the role of the media, is required.

Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress

Directory of Open Access Journals (Sweden)

He eLiu

2014-10-01

Full Text Available Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay (EMSA demonstrated that TetR regulator bound directly to the promoter of this gene cluster. Consistently, the results of quantitative real-time PCR also showed alterations in expression of associated genes. Moreover, the proteins affected by TetR under oxidative stress were revealed by comparing proteomic profiles of wild-type and mutant strains via 1D SDS-PAGE and LC-MS/MS analyses. Taken together, our results demonstrated that tetR gene in this novel gene cluster contributed to cell survival under oxidative stress, and TetR protein played an important regulatory role in growth kinetics, biofilm-forming capability, SOD and catalase activity, and oxide detoxicating ability.

Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress.

Science.gov (United States)

Liu, He; Yang, Chun-Lan; Ge, Meng-Yu; Ibrahim, Muhammad; Li, Bin; Zhao, Wen-Jun; Chen, Gong-You; Zhu, Bo; Xie, Guan-Lin

2014-01-01

Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay demonstrated that TetR regulator bound directly to the promoter of this gene cluster. Consistently, the results of quantitative real-time PCR also showed alterations in expression of associated genes. Moreover, the proteins affected by TetR under oxidative stress were revealed by comparing proteomic profiles of wild-type and mutant strains via 1D SDS-PAGE and LC-MS/MS analyses. Taken together, our results demonstrated that tetR gene in this novel gene cluster contributed to cell survival under oxidative stress, and TetR protein played an important regulatory role in growth kinetics, biofilm-forming capability, superoxide dismutase and catalase activity, and oxide detoxicating ability.

Genome-wide methylation analysis identifies a core set of hypermethylated genes in CIMP-H colorectal cancer.

Science.gov (United States)

McInnes, Tyler; Zou, Donghui; Rao, Dasari S; Munro, Francesca M; Phillips, Vicky L; McCall, John L; Black, Michael A; Reeve, Anthony E; Guilford, Parry J

2017-03-28

Aberrant DNA methylation profiles are a characteristic of all known cancer types, epitomized by the CpG island methylator phenotype (CIMP) in colorectal cancer (CRC). Hypermethylation has been observed at CpG islands throughout the genome, but it is unclear which factors determine whether an individual island becomes methylated in cancer. DNA methylation in CRC was analysed using the Illumina HumanMethylation450K array. Differentially methylated loci were identified using Significance Analysis of Microarrays (SAM) and the Wilcoxon Signed Rank (WSR) test. Unsupervised hierarchical clustering was used to identify methylation subtypes in CRC. In this study we characterized the DNA methylation profiles of 94 CRC tissues and their matched normal counterparts. Consistent with previous studies, unsupervized hierarchical clustering of genome-wide methylation data identified three subtypes within the tumour samples, designated CIMP-H, CIMP-L and CIMP-N, that showed high, low and very low methylation levels, respectively. Differential methylation between normal and tumour samples was analysed at the individual CpG level, and at the gene level. The distribution of hypermethylation in CIMP-N tumours showed high inter-tumour variability and appeared to be highly stochastic in nature, whereas CIMP-H tumours exhibited consistent hypermethylation at a subset of genes, in addition to a highly variable background of hypermethylated genes. EYA4, TFPI2 and TLX1 were hypermethylated in more than 90% of all tumours examined. One-hundred thirty-two genes were hypermethylated in 100% of CIMP-H tumours studied and these were highly enriched for functions relating to skeletal system development (Bonferroni adjusted p value =2.88E-15), segment specification (adjusted p value =9.62E-11), embryonic development (adjusted p value =1.52E-04), mesoderm development (adjusted p value =1.14E-20), and ectoderm development (adjusted p value =7.94E-16). Our genome-wide characterization of DNA

Transcriptional analysis of the jamaicamide gene cluster from the marine cyanobacterium Lyngbya majuscula and identification of possible regulatory proteins

Directory of Open Access Journals (Sweden)

Dorrestein Pieter C

2009-12-01

Full Text Available Abstract Background The marine cyanobacterium Lyngbya majuscula is a prolific producer of bioactive secondary metabolites. Although biosynthetic gene clusters encoding several of these compounds have been identified, little is known about how these clusters of genes are transcribed or regulated, and techniques targeting genetic manipulation in Lyngbya strains have not yet been developed. We conducted transcriptional analyses of the jamaicamide gene cluster from a Jamaican strain of Lyngbya majuscula, and isolated proteins that could be involved in jamaicamide regulation. Results An unusually long untranslated leader region of approximately 840 bp is located between the jamaicamide transcription start site (TSS and gene cluster start codon. All of the intergenic regions between the pathway ORFs were transcribed into RNA in RT-PCR experiments; however, a promoter prediction program indicated the possible presence of promoters in multiple intergenic regions. Because the functionality of these promoters could not be verified in vivo, we used a reporter gene assay in E. coli to show that several of these intergenic regions, as well as the primary promoter preceding the TSS, are capable of driving β-galactosidase production. A protein pulldown assay was also used to isolate proteins that may regulate the jamaicamide pathway. Pulldown experiments using the intergenic region upstream of jamA as a DNA probe isolated two proteins that were identified by LC-MS/MS. By BLAST analysis, one of these had close sequence identity to a regulatory protein in another cyanobacterial species. Protein comparisons suggest a possible correlation between secondary metabolism regulation and light dependent complementary chromatic adaptation. Electromobility shift assays were used to evaluate binding of the recombinant proteins to the jamaicamide promoter region. Conclusion Insights into natural product regulation in cyanobacteria are of significant value to drug discovery

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

Directory of Open Access Journals (Sweden)

Kristopher J. L. Irizarry

2016-01-01

Full Text Available Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1 that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons.

Lactobacillus plantarum gene clusters encoding putative cell-surface protein complexes for carbohydrate utilization are conserved in specific gram-positive bacteria

Directory of Open Access Journals (Sweden)

Muscariello Lidia

2006-05-01

Full Text Available Abstract Background Genomes of gram-positive bacteria encode many putative cell-surface proteins, of which the majority has no known function. From the rapidly increasing number of available genome sequences it has become apparent that many cell-surface proteins are conserved, and frequently encoded in gene clusters or operons, suggesting common functions, and interactions of multiple components. Results A novel gene cluster encoding exclusively cell-surface proteins was identified, which is conserved in a subgroup of gram-positive bacteria. Each gene cluster generally has one copy of four new gene families called cscA, cscB, cscC and cscD. Clusters encoding these cell-surface proteins were found only in complete genomes of Lactobacillus plantarum, Lactobacillus sakei, Enterococcus faecalis, Listeria innocua, Listeria monocytogenes, Lactococcus lactis ssp lactis and Bacillus cereus and in incomplete genomes of L. lactis ssp cremoris, Lactobacillus casei, Enterococcus faecium, Pediococcus pentosaceus, Lactobacillius brevis, Oenococcus oeni, Leuconostoc mesenteroides, and Bacillus thuringiensis. These genes are neither present in the genomes of streptococci, staphylococci and clostridia, nor in the Lactobacillus acidophilus group, suggesting a niche-specific distribution, possibly relating to association with plants. All encoded proteins have a signal peptide for secretion by the Sec-dependent pathway, while some have cell-surface anchors, novel WxL domains, and putative domains for sugar binding and degradation. Transcriptome analysis in L. plantarum shows that the cscA-D genes are co-expressed, supporting their operon organization. Many gene clusters are significantly up-regulated in a glucose-grown, ccpA-mutant derivative of L. plantarum, suggesting catabolite control. This is supported by the presence of predicted CRE-sites upstream or inside the up-regulated cscA-D gene clusters. Conclusion We propose that the CscA, CscB, CscC and Csc

Characterization and transcriptional analysis of two gene clusters for type IV secretion machinery in Wolbachia of Armadillidium vulgare

DEFF Research Database (Denmark)

Félix, Christine; Pichon, Samuel; Braquart-Varnier, Christine

2008-01-01

Wolbachia are maternally inherited alpha-proteobacteria that induce feminization of genetic males in most terrestrial crustacean isopods. Two clusters of vir genes for a type IV secretion machinery have been identified at two separate loci and characterized for the first time in a feminizing Wolb...

Sequencing and Transcriptional Analysis of the Biosynthesis Gene Cluster of Putrescine-Producing Lactococcus lactis ▿ †

Science.gov (United States)

Ladero, Victor; Rattray, Fergal P.; Mayo, Baltasar; Martín, María Cruz; Fernández, María; Alvarez, Miguel A.

2011-01-01

Lactococcus lactis is a prokaryotic microorganism with great importance as a culture starter and has become the model species among the lactic acid bacteria. The long and safe history of use of L. lactis in dairy fermentations has resulted in the classification of this species as GRAS (General Regarded As Safe) or QPS (Qualified Presumption of Safety). However, our group has identified several strains of L. lactis subsp. lactis and L. lactis subsp. cremoris that are able to produce putrescine from agmatine via the agmatine deiminase (AGDI) pathway. Putrescine is a biogenic amine that confers undesirable flavor characteristics and may even have toxic effects. The AGDI cluster of L. lactis is composed of a putative regulatory gene, aguR, followed by the genes (aguB, aguD, aguA, and aguC) encoding the catabolic enzymes. These genes are transcribed as an operon that is induced in the presence of agmatine. In some strains, an insertion (IS) element interrupts the transcription of the cluster, which results in a non-putrescine-producing phenotype. Based on this knowledge, a PCR-based test was developed in order to differentiate nonproducing L. lactis strains from those with a functional AGDI cluster. The analysis of the AGDI cluster and their flanking regions revealed that the capacity to produce putrescine via the AGDI pathway could be a specific characteristic that was lost during the adaptation to the milk environment by a process of reductive genome evolution. PMID:21803900

Genome-wide significant localization for working and spatial memory: Identifying genes for psychosis using models of cognition.

Science.gov (United States)

Knowles, Emma E M; Carless, Melanie A; de Almeida, Marcio A A; Curran, Joanne E; McKay, D Reese; Sprooten, Emma; Dyer, Thomas D; Göring, Harald H; Olvera, Rene; Fox, Peter; Almasy, Laura; Duggirala, Ravi; Kent, Jack W; Blangero, John; Glahn, David C

2014-01-01

It is well established that risk for developing psychosis is largely mediated by the influence of genes, but identifying precisely which genes underlie that risk has been problematic. Focusing on endophenotypes, rather than illness risk, is one solution to this problem. Impaired cognition is a well-established endophenotype of psychosis. Here we aimed to characterize the genetic architecture of cognition using phenotypically detailed models as opposed to relying on general IQ or individual neuropsychological measures. In so doing we hoped to identify genes that mediate cognitive ability, which might also contribute to psychosis risk. Hierarchical factor models of genetically clustered cognitive traits were subjected to linkage analysis followed by QTL region-specific association analyses in a sample of 1,269 Mexican American individuals from extended pedigrees. We identified four genome wide significant QTLs, two for working and two for spatial memory, and a number of plausible and interesting candidate genes. The creation of detailed models of cognition seemingly enhanced the power to detect genetic effects on cognition and provided a number of possible candidate genes for psychosis. © 2013 Wiley Periodicals, Inc.

Identifying clinical course patterns in SMS data using cluster analysis

DEFF Research Database (Denmark)

Kent, Peter; Kongsted, Alice

2012-01-01

ABSTRACT: BACKGROUND: Recently, there has been interest in using the short message service (SMS or text messaging), to gather frequent information on the clinical course of individual patients. One possible role for identifying clinical course patterns is to assist in exploring clinically important...... showed that clinical course patterns can be identified by cluster analysis using all SMS time points as cluster variables. This method is simple, intuitive and does not require a high level of statistical skill. However, there are alternative ways of managing SMS data and many different methods...

The Genome of Tolypocladium inflatum: Evolution, Organization, and Expression of the Cyclosporin Biosynthetic Gene Cluster

Science.gov (United States)

Bushley, Kathryn E.; Raja, Rajani; Jaiswal, Pankaj; Cumbie, Jason S.; Nonogaki, Mariko; Boyd, Alexander E.; Owensby, C. Alisha; Knaus, Brian J.; Elser, Justin; Miller, Daniel; Di, Yanming; McPhail, Kerry L.; Spatafora, Joseph W.

2013-01-01

The ascomycete fungus Tolypocladium inflatum, a pathogen of beetle larvae, is best known as the producer of the immunosuppressant drug cyclosporin. The draft genome of T. inflatum strain NRRL 8044 (ATCC 34921), the isolate from which cyclosporin was first isolated, is presented along with comparative analyses of the biosynthesis of cyclosporin and other secondary metabolites in T. inflatum and related taxa. Phylogenomic analyses reveal previously undetected and complex patterns of homology between the nonribosomal peptide synthetase (NRPS) that encodes for cyclosporin synthetase (simA) and those of other secondary metabolites with activities against insects (e.g., beauvericin, destruxins, etc.), and demonstrate the roles of module duplication and gene fusion in diversification of NRPSs. The secondary metabolite gene cluster responsible for cyclosporin biosynthesis is described. In addition to genes necessary for cyclosporin biosynthesis, it harbors a gene for a cyclophilin, which is a member of a family of immunophilins known to bind cyclosporin. Comparative analyses support a lineage specific origin of the cyclosporin gene cluster rather than horizontal gene transfer from bacteria or other fungi. RNA-Seq transcriptome analyses in a cyclosporin-inducing medium delineate the boundaries of the cyclosporin cluster and reveal high levels of expression of the gene cluster cyclophilin. In medium containing insect hemolymph, weaker but significant upregulation of several genes within the cyclosporin cluster, including the highly expressed cyclophilin gene, was observed. T. inflatum also represents the first reference draft genome of Ophiocordycipitaceae, a third family of insect pathogenic fungi within the fungal order Hypocreales, and supports parallel and qualitatively distinct radiations of insect pathogens. The T. inflatum genome provides additional insight into the evolution and biosynthesis of cyclosporin and lays a foundation for further investigations of the role

A scan statistic to extract causal gene clusters from case-control genome-wide rare CNV data

Directory of Open Access Journals (Sweden)

Scherer Stephen W

2011-05-01

Full Text Available Abstract Background Several statistical tests have been developed for analyzing genome-wide association data by incorporating gene pathway information in terms of gene sets. Using these methods, hundreds of gene sets are typically tested, and the tested gene sets often overlap. This overlapping greatly increases the probability of generating false positives, and the results obtained are difficult to interpret, particularly when many gene sets show statistical significance. Results We propose a flexible statistical framework to circumvent these problems. Inspired by spatial scan statistics for detecting clustering of disease occurrence in the field of epidemiology, we developed a scan statistic to extract disease-associated gene clusters from a whole gene pathway. Extracting one or a few significant gene clusters from a global pathway limits the overall false positive probability, which results in increased statistical power, and facilitates the interpretation of test results. In the present study, we applied our method to genome-wide association data for rare copy-number variations, which have been strongly implicated in common diseases. Application of our method to a simulated dataset demonstrated the high accuracy of this method in detecting disease-associated gene clusters in a whole gene pathway. Conclusions The scan statistic approach proposed here shows a high level of accuracy in detecting gene clusters in a whole gene pathway. This study has provided a sound statistical framework for analyzing genome-wide rare CNV data by incorporating topological information on the gene pathway.

Gene cluster analysis for the biosynthesis of elgicins, novel lantibiotics produced by paenibacillus elgii B69

Directory of Open Access Journals (Sweden)

Teng Yi

2012-03-01

Full Text Available Abstract Background The recent increase in bacterial resistance to antibiotics has promoted the exploration of novel antibacterial materials. As a result, many researchers are undertaking work to identify new lantibiotics because of their potent antimicrobial activities. The objective of this study was to provide details of a lantibiotic-like gene cluster in Paenibacillus elgii B69 and to produce the antibacterial substances coded by this gene cluster based on culture screening. Results Analysis of the P. elgii B69 genome sequence revealed the presence of a lantibiotic-like gene cluster composed of five open reading frames (elgT1, elgC, elgT2, elgB, and elgA. Screening of culture extracts for active substances possessing the predicted properties of the encoded product led to the isolation of four novel peptides (elgicins AI, AII, B, and C with a broad inhibitory spectrum. The molecular weights of these peptides were 4536, 4593, 4706, and 4820 Da, respectively. The N-terminal sequence of elgicin B was Leu-Gly-Asp-Tyr, which corresponded to the partial sequence of the peptide ElgA encoded by elgA. Edman degradation suggested that the product elgicin B is derived from ElgA. By correlating the results of electrospray ionization-mass spectrometry analyses of elgicins AI, AII, and C, these peptides are deduced to have originated from the same precursor, ElgA. Conclusions A novel lantibiotic-like gene cluster was shown to be present in P. elgii B69. Four new lantibiotics with a broad inhibitory spectrum were isolated, and these appear to be promising antibacterial agents.

CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes.

Science.gov (United States)

Kong, Hualei; Tong, Pan; Zhao, Xiaodong; Sun, Jielin; Li, Hua

2018-03-01

In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and

New gene cluster from the thermophile Bacillus fordii MH602 in the conversion of DL-5-substituted hydantoins to L-amino acids.

Science.gov (United States)

Mei, Yan-Zhen; Wan, Yong-Min; He, Bing-Fang; Ying, Han-Jie; Ouyang, Ping-Kai

2009-12-01

The thermophile Bacillus fordii MH602 was screened for stereospecifically hydrolyzing DL-5-substituted hydantoins to L-alpha-amino acids. Since the reaction at higher temperature, the advantageous for enhancement of substrate solubility and for racemization of DL-5-substituted hydantoins during the conversion were achieved. The hydantoin metabolism gene cluster from thermophile was firstly reported in this paper. The genes involved in hydantoin utilization (hyu) were isolated on an 8.2 kb DNA fragment by Restriction Site-dependent PCR, and six ORFs were identified by DNA sequence analysis. The hyu gene cluster contained four genes with novel cluster organization characteristics: the hydantoinase gene hyuH, putative transport protein hyuP, hyperprotein hyuHP, and L-carbamoylase gene hyuC. The hyuH and hyuC genes were heterogeneously expressed in E. coli. The results indicated that hyuH and hyuC are involved in the conversion of DL-5-substituted hydantoins to an N-carbamyl intermediate that is subsequently converted to L-alpha-amino acids. Hydantoinase and carbamoylase from B. fordii MH602 comparing respectively with reported hydantoinase and carbamoylase showed the highest identities of 71% and 39%. The novel cluster organization characteristics and the difference of the key enzymes between thermopile B. fordii MH602 and other mesophiles were presumed to be related to the evolutionary origins of concerned metabolism.

SPINE: SParse eIgengene NEtwork linking gene expression clusters in Dehalococcoides mccartyi to perturbations in experimental conditions.

Directory of Open Access Journals (Sweden)

Cresten B Mansfeldt

Full Text Available We present a statistical model designed to identify the effect of experimental perturbations on the aggregate behavior of the transcriptome expressed by the bacterium Dehalococcoides mccartyi strain 195. Strains of Dehalococcoides are used in sub-surface bioremediation applications because they organohalorespire tetrachloroethene and trichloroethene (common chlorinated solvents that contaminate the environment to non-toxic ethene. However, the biochemical mechanism of this process remains incompletely described. Additionally, the response of Dehalococcoides to stress-inducing conditions that may be encountered at field-sites is not well understood. The constructed statistical model captured the aggregate behavior of gene expression phenotypes by modeling the distinct eigengenes of 100 transcript clusters, determining stable relationships among these clusters of gene transcripts with a sparse network-inference algorithm, and directly modeling the effect of changes in experimental conditions by constructing networks conditioned on the experimental state. Based on the model predictions, we discovered new response mechanisms for DMC, notably when the bacterium is exposed to solvent toxicity. The network identified a cluster containing thirteen gene transcripts directly connected to the solvent toxicity condition. Transcripts in this cluster include an iron-dependent regulator (DET0096-97 and a methylglyoxal synthase (DET0137. To validate these predictions, additional experiments were performed. Continuously fed cultures were exposed to saturating levels of tetrachloethene, thereby causing solvent toxicity, and transcripts that were predicted to be linked to solvent toxicity were monitored by quantitative reverse-transcription polymerase chain reaction. Twelve hours after being shocked with saturating levels of tetrachloroethene, the control transcripts (encoding for a key hydrogenase and the 16S rRNA did not significantly change. By contrast

Assessment of clusters of transcription factor binding sites in relationship to human promoter, CpG islands and gene expression

Directory of Open Access Journals (Sweden)

Sakaki Yoshiyuki

2004-02-01

Full Text Available Abstract Background Gene expression is regulated mainly by transcription factors (TFs that interact with regulatory cis-elements on DNA sequences. To identify functional regulatory elements, computer searching can predict TF binding sites (TFBS using position weight matrices (PWMs that represent positional base frequencies of collected experimentally determined TFBS. A disadvantage of this approach is the large output of results for genomic DNA. One strategy to identify genuine TFBS is to utilize local concentrations of predicted TFBS. It is unclear whether there is a general tendency for TFBS to cluster at promoter regions, although this is the case for certain TFBS. Also unclear is the identification of TFs that have TFBS concentrated in promoters and to what level this occurs. This study hopes to answer some of these questions. Results We developed the cluster score measure to evaluate the correlation between predicted TFBS clusters and promoter sequences for each PWM. Non-promoter sequences were used as a control. Using the cluster score, we identified a PWM group called PWM-PCP, in which TFBS clusters positively correlate with promoters, and another PWM group called PWM-NCP, in which TFBS clusters negatively correlate with promoters. The PWM-PCP group comprises 47% of the 199 vertebrate PWMs, while the PWM-NCP group occupied 11 percent. After reducing the effect of CpG islands (CGI against the clusters using partial correlation coefficients among three properties (promoter, CGI and predicted TFBS cluster, we identified two PWM groups including those strongly correlated with CGI and those not correlated with CGI. Conclusion Not all PWMs predict TFBS correlated with human promoter sequences. Two main PWM groups were identified: (1 those that show TFBS clustered in promoters associated with CGI, and (2 those that show TFBS clustered in promoters independent of CGI. Assessment of PWM matches will allow more positive interpretation of TFBS in

Variation in sequence and location of the fumonisin mycotoxin niosynthetic gene cluster in Fusarium

NARCIS (Netherlands)

Proctor, R.H.; Hove, van F.; Susca, A.; Stea, A.; Busman, M.; Lee, van der T.A.J.; Waalwijk, C.; Moretti, A.

2010-01-01

In Fusarium, the ability to produce fumonisins is governed by a 17-gene fumonisin biosynthetic gene (FUM) cluster. Here, we examined the cluster in F. oxysporum strain O-1890 and nine other species selected to represent a wide range of the genetic diversity within the GFSC.

Genome mining of the sordarin biosynthetic gene cluster from Sordaria araneosa Cain ATCC 36386: characterization of cycloaraneosene synthase and GDP-6-deoxyaltrose transferase.

Science.gov (United States)

Kudo, Fumitaka; Matsuura, Yasunori; Hayashi, Takaaki; Fukushima, Masayuki; Eguchi, Tadashi

2016-07-01

Sordarin is a glycoside antibiotic with a unique tetracyclic diterpene aglycone structure called sordaricin. To understand its intriguing biosynthetic pathway that may include a Diels-Alder-type [4+2]cycloaddition, genome mining of the gene cluster from the draft genome sequence of the producer strain, Sordaria araneosa Cain ATCC 36386, was carried out. A contiguous 67 kb gene cluster consisting of 20 open reading frames encoding a putative diterpene cyclase, a glycosyltransferase, a type I polyketide synthase, and six cytochrome P450 monooxygenases were identified. In vitro enzymatic analysis of the putative diterpene cyclase SdnA showed that it catalyzes the transformation of geranylgeranyl diphosphate to cycloaraneosene, a known biosynthetic intermediate of sordarin. Furthermore, a putative glycosyltransferase SdnJ was found to catalyze the glycosylation of sordaricin in the presence of GDP-6-deoxy-d-altrose to give 4'-O-demethylsordarin. These results suggest that the identified sdn gene cluster is responsible for the biosynthesis of sordarin. Based on the isolated potential biosynthetic intermediates and bioinformatics analysis, a plausible biosynthetic pathway for sordarin is proposed.

Identifying Patient Attitudinal Clusters Associated with Asthma Control: The European REALISE Survey.

Science.gov (United States)

van der Molen, Thys; Fletcher, Monica; Price, David

Asthma is a highly heterogeneous disease that can be classified into different clinical phenotypes, and treatment may be tailored accordingly. However, factors beyond purely clinical traits, such as patient attitudes and behaviors, can also have a marked impact on treatment outcomes. The objective of this study was to further analyze data from the REcognise Asthma and LInk to Symptoms and Experience (REALISE) Europe survey, to identify distinct patient groups sharing common attitudes toward asthma and its management. Factor analysis of respondent data (N = 7,930) from the REALISE Europe survey consolidated the 34 attitudinal variables provided by the study population into a set of 8 summary factors. Cluster analyses were used to identify patient clusters that showed similar attitudes and behaviors toward each of the 8 summary factors. Five distinct patient clusters were identified and named according to the key characteristics comprising that cluster: "Confident and self-managing," "Confident and accepting of their asthma," "Confident but dependent on others," "Concerned but confident in their health care professional (HCP)," and "Not confident in themselves or their HCP." Clusters showed clear variability in attributes such as degree of confidence in managing their asthma, use of reliever and preventer medication, and level of asthma control. The 5 patient clusters identified in this analysis displayed distinctly different personal attitudes that would require different approaches in the consultation room certainly for asthma but probably also for other chronic diseases. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Clustering analysis of water distribution systems: identifying critical components and community impacts.

Science.gov (United States)

Diao, K; Farmani, R; Fu, G; Astaraie-Imani, M; Ward, S; Butler, D

2014-01-01

Large water distribution systems (WDSs) are networks with both topological and behavioural complexity. Thereby, it is usually difficult to identify the key features of the properties of the system, and subsequently all the critical components within the system for a given purpose of design or control. One way is, however, to more explicitly visualize the network structure and interactions between components by dividing a WDS into a number of clusters (subsystems). Accordingly, this paper introduces a clustering strategy that decomposes WDSs into clusters with stronger internal connections than external connections. The detected cluster layout is very similar to the community structure of the served urban area. As WDSs may expand along with urban development in a community-by-community manner, the correspondingly formed distribution clusters may reveal some crucial configurations of WDSs. For verification, the method is applied to identify all the critical links during firefighting for the vulnerability analysis of a real-world WDS. Moreover, both the most critical pipes and clusters are addressed, given the consequences of pipe failure. Compared with the enumeration method, the method used in this study identifies the same group of the most critical components, and provides similar criticality prioritizations of them in a more computationally efficient time.

Development and mapping of SSR markers linked to resistance-gene homologue clusters in common bean

Institute of Scientific and Technical Information of China (English)

Luz; Nayibe; Garzon; Matthew; Wohlgemuth; Blair

2014-01-01

Common bean is an important but often a disease-susceptible legume crop of temperate,subtropical and tropical regions worldwide. The crop is affected by bacterial, fungal and viral pathogens. The strategy of resistance-gene homologue(RGH) cloning has proven to be an efficient tool for identifying markers and R(resistance) genes associated with resistances to diseases. Microsatellite or SSR markers can be identified by physical association with RGH clones on large-insert DNA clones such as bacterial artificial chromosomes(BACs). Our objectives in this work were to identify RGH-SSR in a BAC library from the Andean genotype G19833 and to test and map any polymorphic markers to identify associations with known positions of disease resistance genes. We developed a set of specific probes designed for clades of common bean RGH genes and then identified positive BAC clones and developed microsatellites from BACs having SSR loci in their end sequences. A total of 629 new RGH-SSRs were identified and named BMr(bean microsatellite RGH-associated markers). A subset of these markers was screened for detecting polymorphism in the genetic mapping population DOR364 × G19833. A genetic map was constructed with a total of 264 markers,among which were 80 RGH loci anchored to single-copy RFLP and SSR markers. Clusters of RGH-SSRs were observed on most of the linkage groups of common bean and in positions associated with R-genes and QTL. The use of these new markers to select for disease resistance is discussed.

Parkinson's Disease Subtypes Identified from Cluster Analysis of Motor and Non-motor Symptoms.

Science.gov (United States)

Mu, Jesse; Chaudhuri, Kallol R; Bielza, Concha; de Pedro-Cuesta, Jesus; Larrañaga, Pedro; Martinez-Martin, Pablo

2017-01-01

Parkinson's disease is now considered a complex, multi-peptide, central, and peripheral nervous system disorder with considerable clinical heterogeneity. Non-motor symptoms play a key role in the trajectory of Parkinson's disease, from prodromal premotor to end stages. To understand the clinical heterogeneity of Parkinson's disease, this study used cluster analysis to search for subtypes from a large, multi-center, international, and well-characterized cohort of Parkinson's disease patients across all motor stages, using a combination of cardinal motor features (bradykinesia, rigidity, tremor, axial signs) and, for the first time, specific validated rater-based non-motor symptom scales. Two independent international cohort studies were used: (a) the validation study of the Non-Motor Symptoms Scale ( n = 411) and (b) baseline data from the global Non-Motor International Longitudinal Study ( n = 540). k -means cluster analyses were performed on the non-motor and motor domains (domains clustering) and the 30 individual non-motor symptoms alone (symptoms clustering), and hierarchical agglomerative clustering was performed to group symptoms together. Four clusters are identified from the domains clustering supporting previous studies: mild, non-motor dominant, motor-dominant, and severe. In addition, six new smaller clusters are identified from the symptoms clustering, each characterized by clinically-relevant non-motor symptoms. The clusters identified in this study present statistical confirmation of the increasingly important role of non-motor symptoms (NMS) in Parkinson's disease heterogeneity and take steps toward subtype-specific treatment packages.

Sequencing, physical organization and kinetic expression of the patulin biosynthetic gene cluster from Penicillium expansum

International Nuclear Information System (INIS)

Tannous, J.; El Khoury, R.; El Khoury, A.; Lteif, R.; Snini, S.; Lippi, Y.; Oswald, I.; Olivier, P.; Atoui, A.

2014-01-01

Patulin is a polyketide-derived mycotoxin produced by numerous filamentous fungi. Among them, Penicillium expansum is by far the most problematic species. This fungus is a destructive phytopathogen capable of growing on fruit, provoking the blue mold decay of apples and producing significant amounts of patulin. The biosynthetic pathway of this mycotoxin is chemically well-characterized, but its genetic bases remain largely unknown with only few characterized genes in less economic relevant species. The present study consisted of the identification and positional organization of the patulin gene cluster in P. expansum strain NRRL 35695. Several amplification reactions were performed with degenerative primers that were designed based on sequences from the orthologous genes available in other species. An improved genome Walking approach was used in order to sequence the remaining adjacent genes of the cluster. RACE-PCR was also carried out from mRNAs to determine the start and stop codons of the coding sequences. The patulin gene cluster in P. expansum consists of 15 genes in the following order: patH, patG, patF, patE, patD, patC, patB, patA, patM, patN, patO, patL, patI, patJ, and patK. These genes share 60–70% of identity with orthologous genes grouped differently, within a putative patulin cluster described in a non-producing strain of Aspergillus clavatus. The kinetics of patulin cluster genes expression was studied under patulin-permissive conditions (natural apple-based medium) and patulin-restrictive conditions (Eagle's minimal essential medium), and demonstrated a significant association between gene expression and patulin production. In conclusion, the sequence of the patulin cluster in P. expansum constitutes a key step for a better understanding of themechanisms leading to patulin production in this fungus. It will allow the role of each gene to be elucidated, and help to define strategies to reduce patulin production in apple-based products

Output ordering and prioritisation system (OOPS): ranking biosynthetic gene clusters to enhance bioactive metabolite discovery.

Science.gov (United States)

Peña, Alejandro; Del Carratore, Francesco; Cummings, Matthew; Takano, Eriko; Breitling, Rainer

2017-12-18

The rapid increase of publicly available microbial genome sequences has highlighted the presence of hundreds of thousands of biosynthetic gene clusters (BGCs) encoding valuable secondary metabolites. The experimental characterization of new BGCs is extremely laborious and struggles to keep pace with the in silico identification of potential BGCs. Therefore, the prioritisation of promising candidates among computationally predicted BGCs represents a pressing need. Here, we propose an output ordering and prioritisation system (OOPS) which helps sorting identified BGCs by a wide variety of custom-weighted biological and biochemical criteria in a flexible and user-friendly interface. OOPS facilitates a judicious prioritisation of BGCs using G+C content, coding sequence length, gene number, cluster self-similarity and codon bias parameters, as well as enabling the user to rank BGCs based upon BGC type, novelty, and taxonomic distribution. Effective prioritisation of BGCs will help to reduce experimental attrition rates and improve the breadth of bioactive metabolites characterized.

Genes involved in degradation of para-nitrophenol are differentially arranged in form of non-contiguous gene clusters in Burkholderia sp. strain SJ98.

Directory of Open Access Journals (Sweden)

Surendra Vikram

Full Text Available Biodegradation of para-Nitrophenol (PNP proceeds via two distinct pathways, having 1,2,3-benzenetriol (BT and hydroquinone (HQ as their respective terminal aromatic intermediates. Genes involved in these pathways have already been studied in different PNP degrading bacteria. Burkholderia sp. strain SJ98 degrades PNP via both the pathways. Earlier, we have sequenced and analyzed a ~41 kb fragment from the genomic library of strain SJ98. This DNA fragment was found to harbor all the lower pathway genes; however, genes responsible for the initial transformation of PNP could not be identified within this fragment. Now, we have sequenced and annotated the whole genome of strain SJ98 and found two ORFs (viz., pnpA and pnpB showing maximum identity at amino acid level with p-nitrophenol 4-monooxygenase (PnpM and p-benzoquinone reductase (BqR. Unlike the other PNP gene clusters reported earlier in different bacteria, these two ORFs in SJ98 genome are physically separated from the other genes of PNP degradation pathway. In order to ascertain the identity of ORFs pnpA and pnpB, we have performed in-vitro assays using recombinant proteins heterologously expressed and purified to homogeneity. Purified PnpA was found to be a functional PnpM and transformed PNP into benzoquinone (BQ, while PnpB was found to be a functional BqR which catalyzed the transformation of BQ into hydroquinone (HQ. Noticeably, PnpM from strain SJ98 could also transform a number of PNP analogues. Based on the above observations, we propose that the genes for PNP degradation in strain SJ98 are arranged differentially in form of non-contiguous gene clusters. This is the first report for such arrangement for gene clusters involved in PNP degradation. Therefore, we propose that PNP degradation in strain SJ98 could be an important model system for further studies on differential evolution of PNP degradation functions.

Gene-based Association Approach Identify Genes Across Stress Traits in Fruit Flies

DEFF Research Database (Denmark)

Rohde, Palle Duun; Edwards, Stefan McKinnon; Sarup, Pernille Merete

Identification of genes explaining variation in quantitative traits or genetic risk factors of human diseases requires both good phenotypic- and genotypic data, but also efficient statistical methods. Genome-wide association studies may reveal association between phenotypic variation and variation...... approach grouping variants accordingly to gene position, thus lowering the number of statistical tests performed and increasing the probability of identifying genes with small to moderate effects. Using this approach we identify numerous genes associated with different types of stresses in Drosophila...... melanogaster, but also identify common genes that affects the stress traits....

Horizontal transfer of a nitrate assimilation gene cluster and ecological transitions in fungi: a phylogenetic study.

Directory of Open Access Journals (Sweden)

Jason C Slot

Full Text Available High affinity nitrate assimilation genes in fungi occur in a cluster (fHANT-AC that can be coordinately regulated. The clustered genes include nrt2, which codes for a high affinity nitrate transporter; euknr, which codes for nitrate reductase; and NAD(PH-nir, which codes for nitrite reductase. Homologs of genes in the fHANT-AC occur in other eukaryotes and prokaryotes, but they have only been found clustered in the oomycete Phytophthora (heterokonts. We performed independent and concatenated phylogenetic analyses of homologs of all three genes in the fHANT-AC. Phylogenetic analyses limited to fungal sequences suggest that the fHANT-AC has been transferred horizontally from a basidiomycete (mushrooms and smuts to an ancestor of the ascomycetous mold Trichoderma reesei. Phylogenetic analyses of sequences from diverse eukaryotes and eubacteria, and cluster structure, are consistent with a hypothesis that the fHANT-AC was assembled in a lineage leading to the oomycetes and was subsequently transferred to the Dikarya (Ascomycota+Basidiomycota, which is a derived fungal clade that includes the vast majority of terrestrial fungi. We propose that the acquisition of high affinity nitrate assimilation contributed to the success of Dikarya on land by allowing exploitation of nitrate in aerobic soils, and the subsequent transfer of a complete assimilation cluster improved the fitness of T. reesei in a new niche. Horizontal transmission of this cluster of functionally integrated genes supports the "selfish operon" hypothesis for maintenance of gene clusters.

Comparison of Expression of Secondary Metabolite Biosynthesis Cluster Genes in Aspergillus flavus, A. parasiticus, and A. oryzae

OpenAIRE

Ehrlich, Kenneth C.; Mack, Brian M.

2014-01-01

Fifty six secondary metabolite biosynthesis gene clusters are predicted to be in the Aspergillus flavus genome. In spite of this, the biosyntheses of only seven metabolites, including the aflatoxins, kojic acid, cyclopiazonic acid and aflatrem, have been assigned to a particular gene cluster. We used RNA-seq to compare expression of secondary metabolite genes in gene clusters for the closely related fungi A. parasiticus, A. oryzae, and A. flavus S and L sclerotial morphotypes. The data help ...

Increasing Power by Sharing Information from Genetic Background and Treatment in Clustering of Gene Expression Time Series

OpenAIRE

Sura Zaki Alrashid; Muhammad Arifur Rahman; Nabeel H Al-Aaraji; Neil D Lawrence; Paul R Heath

2018-01-01

Clustering of gene expression time series gives insight into which genes may be co-regulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different conditions or genetic background. This paper develops
a new clustering method that allows each cluster to be parameterised according to whether the behaviour of the genes across conditions is correlated or anti-correlated. By specifying correlati...

Identification of the Regulator Gene Responsible for the Acetone-Responsive Expression of the Binuclear Iron Monooxygenase Gene Cluster in Mycobacteria ▿

Science.gov (United States)

Furuya, Toshiki; Hirose, Satomi; Semba, Hisashi; Kino, Kuniki

2011-01-01

The mimABCD gene cluster encodes the binuclear iron monooxygenase that oxidizes propane and phenol in Mycobacterium smegmatis strain MC2 155 and Mycobacterium goodii strain 12523. Interestingly, expression of the mimABCD gene cluster is induced by acetone. In this study, we investigated the regulator gene responsible for this acetone-responsive expression. In the genome sequence of M. smegmatis strain MC2 155, the mimABCD gene cluster is preceded by a gene designated mimR, which is divergently transcribed. Sequence analysis revealed that MimR exhibits amino acid similarity with the NtrC family of transcriptional activators, including AcxR and AcoR, which are involved in acetone and acetoin metabolism, respectively. Unexpectedly, many homologs of the mimR gene were also found in the sequenced genomes of actinomycetes. A plasmid carrying a transcriptional fusion of the intergenic region between the mimR and mimA genes with a promoterless green fluorescent protein (GFP) gene was constructed and introduced into M. smegmatis strain MC2 155. Using a GFP reporter system, we confirmed by deletion and complementation analyses that the mimR gene product is the positive regulator of the mimABCD gene cluster expression that is responsive to acetone. M. goodii strain 12523 also utilized the same regulatory system as M. smegmatis strain MC2 155. Although transcriptional activators of the NtrC family generally control transcription using the σ54 factor, a gene encoding the σ54 factor was absent from the genome sequence of M. smegmatis strain MC2 155. These results suggest the presence of a novel regulatory system in actinomycetes, including mycobacteria. PMID:21856847

Digital gene expression profiling of flax (Linum usitatissimum L.) stem peel identifies genes enriched in fiber-bearing phloem tissue.

Science.gov (United States)

Guo, Yuan; Qiu, Caisheng; Long, Songhua; Chen, Ping; Hao, Dongmei; Preisner, Marta; Wang, Hui; Wang, Yufu

2017-08-30

To better understand the molecular mechanisms and gene expression characteristics associated with development of bast fiber cell within flax stem phloem, the gene expression profiling of flax stem peels and leaves were screened, using Illumina's Digital Gene Expression (DGE) analysis. Four DGE libraries (2 for stem peel and 2 for leaf), ranging from 6.7 to 9.2 million clean reads were obtained, which produced 7.0 million and 6.8 million mapped reads for flax stem peel and leave, respectively. By differential gene expression analysis, a total of 975 genes, of which 708 (73%) genes have protein-coding annotation, were identified as phloem enriched genes putatively involved in the processes of polysaccharide and cell wall metabolism. Differential expression genes (DEGs) was validated using quantitative RT-PCR, the expression pattern of all nine genes determined by qRT-PCR fitted in well with that obtained by sequencing analysis. Cluster and Gene Ontology (GO) analysis revealed that a large number of genes related to metabolic process, catalytic activity and binding category were expressed predominantly in the stem peels. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the phloem enriched genes suggested approximately 111 biological pathways. The large number of genes and pathways produced from DGE sequencing will expand our understanding of the complex molecular and cellular events in flax bast fiber development and provide a foundation for future studies on fiber development in other bast fiber crops. Copyright © 2017 Elsevier B.V. All rights reserved.

antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification

DEFF Research Database (Denmark)

Blin, Kai; Wolf, Thomas; Chevrette, Marc G.

2017-01-01

Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding...... the production of such compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features...

IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

Science.gov (United States)

Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita

2015-07-14

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to

Form gene clustering method about pan-ethnic-group products based on emotional semantic

Science.gov (United States)

Chen, Dengkai; Ding, Jingjing; Gao, Minzhuo; Ma, Danping; Liu, Donghui

2016-09-01

The use of pan-ethnic-group products form knowledge primarily depends on a designer's subjective experience without user participation. The majority of studies primarily focus on the detection of the perceptual demands of consumers from the target product category. A pan-ethnic-group products form gene clustering method based on emotional semantic is constructed. Consumers' perceptual images of the pan-ethnic-group products are obtained by means of product form gene extraction and coding and computer aided product form clustering technology. A case of form gene clustering about the typical pan-ethnic-group products is investigated which indicates that the method is feasible. This paper opens up a new direction for the future development of product form design which improves the agility of product design process in the era of Industry 4.0.

Heterologous expression of the Halothiobacillus neapolitanus carboxysomal gene cluster in Corynebacterium glutamicum.

Science.gov (United States)

Baumgart, Meike; Huber, Isabel; Abdollahzadeh, Iman; Gensch, Thomas; Frunzke, Julia

2017-09-20

Compartmentalization represents a ubiquitous principle used by living organisms to optimize metabolic flux and to avoid detrimental interactions within the cytoplasm. Proteinaceous bacterial microcompartments (BMCs) have therefore created strong interest for the encapsulation of heterologous pathways in microbial model organisms. However, attempts were so far mostly restricted to Escherichia coli. Here, we introduced the carboxysomal gene cluster of Halothiobacillus neapolitanus into the biotechnological platform species Corynebacterium gluta-micum. Transmission electron microscopy, fluorescence microscopy and single molecule localization microscopy suggested the formation of BMC-like structures in cells expressing the complete carboxysome operon or only the shell proteins. Purified carboxysomes consisted of the expected protein components as verified by mass spectrometry. Enzymatic assays revealed the functional production of RuBisCO in C. glutamicum both in the presence and absence of carboxysomal shell proteins. Furthermore, we could show that eYFP is targeted to the carboxysomes by fusion to the large RuBisCO subunit. Overall, this study represents the first transfer of an α-carboxysomal gene cluster into a Gram-positive model species supporting the modularity and orthogonality of these microcompartments, but also identified important challenges which need to be addressed on the way towards biotechnological application. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of expression of secondary metabolite biosynthesis cluster genes in Aspergillus flavus, A. parasiticus, and A. oryzae.

Science.gov (United States)

Ehrlich, Kenneth C; Mack, Brian M

2014-06-23

Fifty six secondary metabolite biosynthesis gene clusters are predicted to be in the Aspergillus flavus genome. In spite of this, the biosyntheses of only seven metabolites, including the aflatoxins, kojic acid, cyclopiazonic acid and aflatrem, have been assigned to a particular gene cluster. We used RNA-seq to compare expression of secondary metabolite genes in gene clusters for the closely related fungi A. parasiticus, A. oryzae, and A. flavus S and L sclerotial morphotypes. The data help to refine the identification of probable functional gene clusters within these species. Our results suggest that A. flavus, a prevalent contaminant of maize, cottonseed, peanuts and tree nuts, is capable of producing metabolites which, besides aflatoxin, could be an underappreciated contributor to its toxicity.

Analysis of Pigeon (Columba) Ovary Transcriptomes to Identify Genes Involved in Blue Light Regulation

Science.gov (United States)

Wang, Ying; Ding, Jia-tong; Yang, Hai-ming; Yan, Zheng-jie; Cao, Wei; Li, Yang-bai

2015-01-01

Monochromatic light is widely applied to promote poultry reproductive performance, yet little is currently known regarding the mechanism by which light wavelengths affect pigeon reproduction. Recently, high-throughput sequencing technologies have been used to provide genomic information for solving this problem. In this study, we employed Illumina Hiseq 2000 to identify differentially expressed genes in ovary tissue from pigeons under blue and white light conditions and de novo transcriptome assembly to construct a comprehensive sequence database containing information on the mechanisms of follicle development. A total of 157,774 unigenes (mean length: 790 bp) were obtained by the Trinity program, and 35.83% of these unigenes were matched to genes in a non-redundant protein database. Gene description, gene ontology, and the clustering of orthologous group terms were performed to annotate the transcriptome assembly. Differentially expressed genes between blue and white light conditions included those related to oocyte maturation, hormone biosynthesis, and circadian rhythm. Furthermore, 17,574 SSRs and 533,887 potential SNPs were identified in this transcriptome assembly. This work is the first transcriptome analysis of the Columba ovary using Illumina technology, and the resulting transcriptome and differentially expressed gene data can facilitate further investigations into the molecular mechanism of the effect of blue light on follicle development and reproduction in pigeons and other bird species. PMID:26599806

Analysis of Pigeon (Columba Ovary Transcriptomes to Identify Genes Involved in Blue Light Regulation.

Directory of Open Access Journals (Sweden)

Ying Wang

Full Text Available Monochromatic light is widely applied to promote poultry reproductive performance, yet little is currently known regarding the mechanism by which light wavelengths affect pigeon reproduction. Recently, high-throughput sequencing technologies have been used to provide genomic information for solving this problem. In this study, we employed Illumina Hiseq 2000 to identify differentially expressed genes in ovary tissue from pigeons under blue and white light conditions and de novo transcriptome assembly to construct a comprehensive sequence database containing information on the mechanisms of follicle development. A total of 157,774 unigenes (mean length: 790 bp were obtained by the Trinity program, and 35.83% of these unigenes were matched to genes in a non-redundant protein database. Gene description, gene ontology, and the clustering of orthologous group terms were performed to annotate the transcriptome assembly. Differentially expressed genes between blue and white light conditions included those related to oocyte maturation, hormone biosynthesis, and circadian rhythm. Furthermore, 17,574 SSRs and 533,887 potential SNPs were identified in this transcriptome assembly. This work is the first transcriptome analysis of the Columba ovary using Illumina technology, and the resulting transcriptome and differentially expressed gene data can facilitate further investigations into the molecular mechanism of the effect of blue light on follicle development and reproduction in pigeons and other bird species.

Identification of new genes in a cell envelope-cell division gene cluster of Escherichia coli: cell envelope gene murG.

Science.gov (United States)

Salmond, G P; Lutkenhaus, J F; Donachie, W D

1980-01-01

We report the identification, cloning, and mapping of a new cell envelope gene, murG. This lies in a group of five genes of similar phenotype (in the order murE murF murG murC ddl) all concerned with peptidoglycan biosynthesis. This group is in a larger cluster of at least 10 genes, all of which are involved in some way with cell envelope growth. Images PMID:6998962

Genes associated with thermosensitive genic male sterility in rice identified by comparative expression profiling.

Science.gov (United States)

Pan, Yufang; Li, Qiaofeng; Wang, Zhizheng; Wang, Yang; Ma, Rui; Zhu, Lili; He, Guangcun; Chen, Rongzhi

2014-12-16

Thermosensitive genic male sterile (TGMS) lines and photoperiod-sensitive genic male sterile (PGMS) lines have been successfully used in hybridization to improve rice yields. However, the molecular mechanisms underlying male sterility transitions in most PGMS/TGMS rice lines are unclear. In the recently developed TGMS-Co27 line, the male sterility is based on co-suppression of a UDP-glucose pyrophosphorylase gene (Ugp1), but further study is needed to fully elucidate the molecular mechanisms involved. Microarray-based transcriptome profiling of TGMS-Co27 and wild-type Hejiang 19 (H1493) plants grown at high and low temperatures revealed that 15462 probe sets representing 8303 genes were differentially expressed in the two lines, under the two conditions, or both. Environmental factors strongly affected global gene expression. Some genes important for pollen development were strongly repressed in TGMS-Co27 at high temperature. More significantly, series-cluster analysis of differentially expressed genes (DEGs) between TGMS-Co27 plants grown under the two conditions showed that low temperature induced the expression of a gene cluster. This cluster was found to be essential for sterility transition. It includes many meiosis stage-related genes that are probably important for thermosensitive male sterility in TGMS-Co27, inter alia: Arg/Ser-rich domain (RS)-containing zinc finger proteins, polypyrimidine tract-binding proteins (PTBs), DEAD/DEAH box RNA helicases, ZOS (C2H2 zinc finger proteins of Oryza sativa), at least one polyadenylate-binding protein and some other RNA recognition motif (RRM) domain-containing proteins involved in post-transcriptional processes, eukaryotic initiation factor 5B (eIF5B), ribosomal proteins (L37, L1p/L10e, L27 and L24), aminoacyl-tRNA synthetases (ARSs), eukaryotic elongation factor Tu (eEF-Tu) and a peptide chain release factor protein involved in translation. The differential expression of 12 DEGs that are important for pollen

Identification of an extensive gene cluster among a family of PPOs in Trifolium pratense L. (red clover using a large insert BAC library

Directory of Open Access Journals (Sweden)

Thomas Ann

2009-07-01

Full Text Available Abstract Background Polyphenol oxidase (PPO activity in plants is a trait with potential economic, agricultural and environmental impact. In relation to the food industry, PPO-induced browning causes unacceptable discolouration in fruit and vegetables: from an agriculture perspective, PPO can protect plants against pathogens and environmental stress, improve ruminant growth by increasing nitrogen absorption and decreasing nitrogen loss to the environment through the animal's urine. The high PPO legume, red clover, has a significant economic and environmental role in sustaining low-input organic and conventional farms. Molecular markers for a range of important agricultural traits are being developed for red clover and improved knowledge of PPO genes and their structure will facilitate molecular breeding. Results A bacterial artificial chromosome (BAC library comprising 26,016 BAC clones with an average 135 Kb insert size, was constructed from Trifolium pratense L. (red clover, a diploid legume with a haploid genome size of 440–637 Mb. Library coverage of 6–8 genome equivalents ensured good representation of genes: the library was screened for polyphenol oxidase (PPO genes. Two single copy PPO genes, PPO4 and PPO5, were identified to add to a family of three, previously reported, paralogous genes (PPO1–PPO3. Multiple PPO1 copies were identified and characterised revealing a subfamily comprising three variants PPO1/2, PPO1/4 and PPO1/5. Six PPO genes clustered within the genome: four separate BAC clones could be assembled onto a predicted 190–510 Kb single BAC contig. Conclusion A PPO gene family in red clover resides as a cluster of at least 6 genes. Three of these genes have high homology, suggesting a more recent evolutionary event. This PPO cluster covers a longer region of the genome than clusters detected in rice or previously reported in tomato. Full-length coding sequences from PPO4, PPO5, PPO1/5 and PPO1/4 will facilitate

Expression profiling identifies genes involved in emphysema severity

Directory of Open Access Journals (Sweden)

Bowman Rayleen V

2009-09-01

Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressed genes (p p Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.

Identifying At-Risk Students in General Chemistry via Cluster Analysis of Affective Characteristics

Science.gov (United States)

Chan, Julia Y. K.; Bauer, Christopher F.

2014-01-01

The purpose of this study is to identify academically at-risk students in first-semester general chemistry using affective characteristics via cluster analysis. Through the clustering of six preselected affective variables, three distinct affective groups were identified: low (at-risk), medium, and high. Students in the low affective group…

Fuzzy C-means method for clustering microarray data.

Science.gov (United States)

Dembélé, Doulaye; Kastner, Philippe

2003-05-22

Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes. A major problem in applying the FCM method for clustering microarray data is the choice of the fuzziness parameter m. We show that the commonly used value m = 2 is not appropriate for some data sets, and that optimal values for m vary widely from one data set to another. We propose an empirical method, based on the distribution of distances between genes in a given data set, to determine an adequate value for m. By setting threshold levels for the membership values, genes which are tigthly associated to a given cluster can be selected. Using a yeast cell cycle data set as an example, we show that this selection increases the overall biological significance of the genes within the cluster. Supplementary text and Matlab functions are available at http://www-igbmc.u-strasbg.fr/fcm/

Genomic organization of the rat alpha 2u-globulin gene cluster.

Science.gov (United States)

McFadyen, D A; Addison, W; Locke, J

1999-05-01

The alpha 2u-globulin are a group of similar proteins, belonging to the lipocalin superfamily of proteins, that are synthesized in a subset of secretory tissues in rats. The many alpha 2u-globulin isoforms are encoded by a multigene family that exhibits extensive homology. Despite a high degree of sequence identity, individual family members show diverse expression patterns involving complex hormonal, tissue-specific, and developmental regulation. Analysis suggests that there are approximately 20 alpha 2u-globulin genes in the rat genome. We have used fluorescence in situ hybridization (FISH) to show that the alpha 2u-globulin genes are clustered at a single site on rat Chromosome (Chr) 5 (5q22-24). Southern blots of rat genomic DNA separated by pulsed field gel electrophoresis indicated that the alpha 2u-globulin genes are contained on two NruI fragments with a total size of 880 kbp. Analysis of three P1 clones containing alpha 2u-globulin genes indicated that the alpha 2u-globulin genes are tandemly arranged in a head-to-tail fashion. The organization of the alpha 2u-globulin genes in the rat as a tandem array of single genes differs from the homologous major urinary protein genes in the mouse, which are organized as tandem arrays of divergently oriented gene pairs. The structure of these gene clusters may have consequences for the proposed function, as a pheromone transporter, for the protein products encoded by these genes.

Stick–slip behavior identified in helium cluster growth in the subsurface of tungsten: effects of cluster depth

International Nuclear Information System (INIS)

Wang, Jinlong; Niu, Liang-Liang; Shu, Xiaolin; Zhang, Ying

2015-01-01

We have performed a molecular dynamics study on the growth of helium (He) clusters in the subsurface of tungsten (W) (1 0 0) at 300 K, focusing on the role of cluster depth. Irregular ‘stick–slip’ behavior exhibited during the evolution of the He cluster growth is identified, which is due to the combined effects of the continuous cluster growth and the loop punching induced pressure relief. We demonstrate that the He cluster grows via trap-mutation and loop punching mechanisms. Initially, the self-interstitial atom SIA clusters are almost always attached to the He cluster; while they are instantly emitted to the surface once a critical cluster pressure is reached. The repetition of this process results in the He cluster approaching the surface via a ‘stop-and-go’ manner and the formation of surface adatom islands (surface roughening), ultimately leading to cluster bursting and He escape. We reveal that, for the Nth loop punching event, the critical size of the He cluster to trigger loop punching and the size of the emitted SIA clusters are correspondingly increased with the increasing initial cluster depth. We tentatively attribute the observed depth effects to the lower formation energies of Frenkel pairs and the greatly reduced barriers for loop punching in the stress field of the W subsurface. In addition, some intriguing features emerge, such as the morphological transformation of the He cluster from ‘platelet-like’ to spherical, to ellipsoidal with a ‘bullet-like’ tip, and finally to a ‘bottle-like’ shape after cluster rupture. (paper)

De Novo Assembly and Genome Analyses of the Marine-Derived Scopulariopsis brevicaulis Strain LF580 Unravels Life-Style Traits and Anticancerous Scopularide Biosynthetic Gene Cluster.

Science.gov (United States)

Kumar, Abhishek; Henrissat, Bernard; Arvas, Mikko; Syed, Muhammad Fahad; Thieme, Nils; Benz, J Philipp; Sørensen, Jens Laurids; Record, Eric; Pöggeler, Stefanie; Kempken, Frank

2015-01-01

The marine-derived Scopulariopsis brevicaulis strain LF580 produces scopularides A and B, which have anticancerous properties. We carried out genome sequencing using three next-generation DNA sequencing methods. De novo hybrid assembly yielded 621 scaffolds with a total size of 32.2 Mb and 16298 putative gene models. We identified a large non-ribosomal peptide synthetase gene (nrps1) and supporting pks2 gene in the same biosynthetic gene cluster. This cluster and the genes within the cluster are functionally active as confirmed by RNA-Seq. Characterization of carbohydrate-active enzymes and major facilitator superfamily (MFS)-type transporters lead to postulate S. brevicaulis originated from a soil fungus, which came into contact with the marine sponge Tethya aurantium. This marine sponge seems to provide shelter to this fungus and micro-environment suitable for its survival in the ocean. This study also builds the platform for further investigations of the role of life-style and secondary metabolites from S. brevicaulis.

Prevalence of the lmo0036-0043 gene cluster encoding arginine deiminase and agmatine deiminase systems in Listeria monocytogenes.

Science.gov (United States)

Chen, Jianshun; Chen, Fan; Cheng, Changyong; Fang, Weihuan

2013-04-01

Arginine deiminase and agmatine deiminase systems are involved in acid tolerance, and their encoding genes form the cluster lmo0036-0043 in Listeria monocytogenes. While lmo0042 and lmo0043 were conserved in all L. monocytogenes strains, the lmo0036-0041 region of this cluster was identified in all lineages I and II, and the majority of lineage IV (83.3%) strains, but absent in all lineage III and a small fraction of lineage IV (16.7%) strains, suggesting that the presence of the complete lmo0036-0043 cluster is dependent on lineages. lmo0036-0043-complete and -deficient lineage IV strains exhibit specific ascB-dapE profiles, which might represent two subpopulations with distinct genetic characteristics.

Acinetobacter baumannii K27 and K44 capsular polysaccharides have the same K unit but different structures due to the presence of distinct wzy genes in otherwise closely related K gene clusters.

Science.gov (United States)

Shashkov, Alexander S; Kenyon, Johanna J; Senchenkova, Sof'ya N; Shneider, Mikhail M; Popova, Anastasiya V; Arbatsky, Nikolay P; Miroshnikov, Konstantin A; Volozhantsev, Nikolay V; Hall, Ruth M; Knirel, Yuriy A

2016-05-01

Capsular polysaccharides (CPSs), from Acinetobacter baumannii isolates 1432, 4190 and NIPH 70, which have related gene content at the K locus, were examined, and the chemical structures established using 2D(1)H and(13)C NMR spectroscopy. The three isolates produce the same pentasaccharide repeat unit, which consists of 5-N-acetyl-7-N-[(S)-3-hydroxybutanoyl] (major) or 5,7-di-N-acetyl (minor) derivatives of 5,7-diamino-3,5,7,9-tetradeoxy-D-glycero-D-galacto-non-2-ulosonic (legionaminic) acid (Leg5Ac7R), D-galactose, N-acetyl-D-galactosamine and N-acetyl-D-glucosamine. However, the linkage between repeat units in NIPH 70 was different to that in 1432 and 4190, and this significantly alters the CPS structure. The KL27 gene cluster in 4190 and KL44 gene cluster in NIPH 70 are organized identically and contain lga genes for Leg5Ac7R synthesis, genes for the synthesis of the common sugars, as well as anitrA2 initiating transferase and four glycosyltransferases genes. They share high-level nucleotide sequence identity for corresponding genes, but differ in the wzy gene encoding the Wzy polymerase. The Wzy proteins, which have different lengths and share no similarity, would form the unrelated linkages in the K27 and K44 structures. The linkages formed by the four shared glycosyltransferases were predicted by comparison with gene clusters that synthesize related structures. These findings unambiguously identify the linkages formed by WzyK27 and WzyK44, and show that the presence of different wzy genes in otherwise closely related K gene clusters changes the structure of the CPS. This may affect its capacity as a protective barrier for A. baumannii. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Acquisition and evolution of plant pathogenesis-associated gene clusters and candidate determinants of tissue-specificity in xanthomonas.

Directory of Open Access Journals (Sweden)

Hong Lu

Full Text Available Xanthomonas is a large genus of plant-associated and plant-pathogenic bacteria. Collectively, members cause diseases on over 392 plant species. Individually, they exhibit marked host- and tissue-specificity. The determinants of this specificity are unknown.To assess potential contributions to host- and tissue-specificity, pathogenesis-associated gene clusters were compared across genomes of eight Xanthomonas strains representing vascular or non-vascular pathogens of rice, brassicas, pepper and tomato, and citrus. The gum cluster for extracellular polysaccharide is conserved except for gumN and sequences downstream. The xcs and xps clusters for type II secretion are conserved, except in the rice pathogens, in which xcs is missing. In the otherwise conserved hrp cluster, sequences flanking the core genes for type III secretion vary with respect to insertion sequence element and putative effector gene content. Variation at the rpf (regulation of pathogenicity factors cluster is more pronounced, though genes with established functional relevance are conserved. A cluster for synthesis of lipopolysaccharide varies highly, suggesting multiple horizontal gene transfers and reassortments, but this variation does not correlate with host- or tissue-specificity. Phylogenetic trees based on amino acid alignments of gum, xps, xcs, hrp, and rpf cluster products generally reflect strain phylogeny. However, amino acid residues at four positions correlate with tissue specificity, revealing hpaA and xpsD as candidate determinants. Examination of genome sequences of xanthomonads Xylella fastidiosa and Stenotrophomonas maltophilia revealed that the hrp, gum, and xcs clusters are recent acquisitions in the Xanthomonas lineage.Our results provide insight into the ancestral Xanthomonas genome and indicate that differentiation with respect to host- and tissue-specificity involved not major modifications or wholesale exchange of clusters, but subtle changes in a small

Haplotypes in the APOA1-C3-A4-A5 gene cluster affect plasma lipids in both humans and baboons

Energy Technology Data Exchange (ETDEWEB)

Wang, Qian-fei; Liu, Xin; O' Connell, Jeff; Peng, Ze; Krauss, Ronald M.; Rainwater, David L.; VandeBerg, John L.; Rubin, Edward M.; Cheng, Jan-Fang; Pennacchio, Len A.

2003-09-15

Genetic studies in non-human primates serve as a potential strategy for identifying genomic intervals where polymorphisms impact upon human disease-related phenotypes. It remains unclear, however, whether independently arising polymorphisms in orthologous regions of non-human primates leads to similar variation in a quantitative trait found in both species. To explore this paradigm, we studied a baboon apolipoprotein gene cluster (APOA1/C3/A4/A5) for which the human gene orthologs have well established roles in influencing plasma HDL-cholesterol and triglyceride concentrations. Our extensive polymorphism analysis of this 68 kb gene cluster in 96 pedigreed baboons identified several haplotype blocks each with limited diversity, consistent with haplotype findings in humans. To determine whether baboons, like humans, also have particular haplotypes associated with lipid phenotypes, we genotyped 634 well characterized baboons using 16 haplotype tagging SNPs. Genetic analysis of single SNPs, as well as haplotypes, revealed an association of APOA5 and APOC3 variants with HDL cholesterol and triglyceride concentrations, respectively. Thus, independent variation in orthologous genomic intervals does associate with similar quantitative lipid traits in both species, supporting the possibility of uncovering human QTL genes in a highly controlled non-human primate model.

Identifying novel phenotypes of acute heart failure using cluster analysis of clinical variables.

Science.gov (United States)

Horiuchi, Yu; Tanimoto, Shuzou; Latif, A H M Mahbub; Urayama, Kevin Y; Aoki, Jiro; Yahagi, Kazuyuki; Okuno, Taishi; Sato, Yu; Tanaka, Tetsu; Koseki, Keita; Komiyama, Kota; Nakajima, Hiroyoshi; Hara, Kazuhiro; Tanabe, Kengo

2018-07-01

Acute heart failure (AHF) is a heterogeneous disease caused by various cardiovascular (CV) pathophysiology and multiple non-CV comorbidities. We aimed to identify clinically important subgroups to improve our understanding of the pathophysiology of AHF and inform clinical decision-making. We evaluated detailed clinical data of 345 consecutive AHF patients using non-hierarchical cluster analysis of 77 variables, including age, sex, HF etiology, comorbidities, physical findings, laboratory data, electrocardiogram, echocardiogram and treatment during hospitalization. Cox proportional hazards regression analysis was performed to estimate the association between the clusters and clinical outcomes. Three clusters were identified. Cluster 1 (n=108) represented "vascular failure". This cluster had the highest average systolic blood pressure at admission and lung congestion with type 2 respiratory failure. Cluster 2 (n=89) represented "cardiac and renal failure". They had the lowest ejection fraction (EF) and worst renal function. Cluster 3 (n=148) comprised mostly older patients and had the highest prevalence of atrial fibrillation and preserved EF. Death or HF hospitalization within 12-month occurred in 23% of Cluster 1, 36% of Cluster 2 and 36% of Cluster 3 (p=0.034). Compared with Cluster 1, risk of death or HF hospitalization was 1.74 (95% CI, 1.03-2.95, p=0.037) for Cluster 2 and 1.82 (95% CI, 1.13-2.93, p=0.014) for Cluster 3. Cluster analysis may be effective in producing clinically relevant categories of AHF, and may suggest underlying pathophysiology and potential utility in predicting clinical outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

Identifying influential individuals on intensive care units: using cluster analysis to explore culture.

Science.gov (United States)

Fong, Allan; Clark, Lindsey; Cheng, Tianyi; Franklin, Ella; Fernandez, Nicole; Ratwani, Raj; Parker, Sarah Henrickson

2017-07-01

The objective of this paper is to identify attribute patterns of influential individuals in intensive care units using unsupervised cluster analysis. Despite the acknowledgement that culture of an organisation is critical to improving patient safety, specific methods to shift culture have not been explicitly identified. A social network analysis survey was conducted and an unsupervised cluster analysis was used. A total of 100 surveys were gathered. Unsupervised cluster analysis was used to group individuals with similar dimensions highlighting three general genres of influencers: well-rounded, knowledge and relational. Culture is created locally by individual influencers. Cluster analysis is an effective way to identify common characteristics among members of an intensive care unit team that are noted as highly influential by their peers. To change culture, identifying and then integrating the influencers in intervention development and dissemination may create more sustainable and effective culture change. Additional studies are ongoing to test the effectiveness of utilising these influencers to disseminate patient safety interventions. This study offers an approach that can be helpful in both identifying and understanding influential team members and may be an important aspect of developing methods to change organisational culture. © 2017 John Wiley & Sons Ltd.

Comparative Transcriptome Analysis Identifies Putative Genes Involved in Steroid Biosynthesis in Euphorbia tirucalli

Directory of Open Access Journals (Sweden)

Weibo Qiao

2018-01-01

Full Text Available Phytochemical analysis of different Euphorbia tirucalli tissues revealed a contrasting tissue-specificity for the biosynthesis of euphol and β-sitosterol, which represent the two pharmaceutically active steroids in E. tirucalli. To uncover the molecular mechanism underlying this tissue-specificity for phytochemicals, a comprehensive E. tirucalli transcriptome derived from its root, stem, leaf and latex was constructed, and a total of 91,619 unigenes were generated with 51.08% being successfully annotated against the non-redundant (Nr protein database. A comparison of the transcriptome from different tissues discovered members of unigenes in the upstream steps of sterol backbone biosynthesis leading to this tissue-specific sterol biosynthesis. Among them, the putative oxidosqualene cyclase (OSC encoding genes involved in euphol synthesis were notably identified, and their expressions were significantly up-regulated in the latex. In addition, genome-wide differentially expressed genes (DEGs in the different E. tirucalli tissues were identified. The cluster analysis of those DEGs showed a unique expression pattern in the latex compared with other tissues. The DEGs identified in this study would enrich the insights of sterol biosynthesis and the regulation mechanism of this latex-specificity.

A highly divergent gene cluster in honey bees encodes a novel silk family.

Science.gov (United States)

Sutherland, Tara D; Campbell, Peter M; Weisman, Sarah; Trueman, Holly E; Sriskantha, Alagacone; Wanjura, Wolfgang J; Haritos, Victoria S

2006-11-01

The pupal cocoon of the domesticated silk moth Bombyx mori is the best known and most extensively studied insect silk. It is not widely known that Apis mellifera larvae also produce silk. We have used a combination of genomic and proteomic techniques to identify four honey bee fiber genes (AmelFibroin1-4) and two silk-associated genes (AmelSA1 and 2). The four fiber genes are small, comprise a single exon each, and are clustered on a short genomic region where the open reading frames are GC-rich amid low GC intergenic regions. The genes encode similar proteins that are highly helical and predicted to form unusually tight coiled coils. Despite the similarity in size, structure, and composition of the encoded proteins, the genes have low primary sequence identity. We propose that the four fiber genes have arisen from gene duplication events but have subsequently diverged significantly. The silk-associated genes encode proteins likely to act as a glue (AmelSA1) and involved in silk processing (AmelSA2). Although the silks of honey bees and silkmoths both originate in larval labial glands, the silk proteins are completely different in their primary, secondary, and tertiary structures as well as the genomic arrangement of the genes encoding them. This implies independent evolutionary origins for these functionally related proteins.

Cataloging the Praesepe Cluster: Identifying Interlopers and Binary Systems

Science.gov (United States)

Lucey, Madeline R.; Gosnell, Natalie M.; Mann, Andrew; Douglas, Stephanie

2018-01-01

We present radial velocity measurements from an ongoing survey of the Praesepe open cluster using the WIYN 3.5m Telescope. Our target stars include 229 early-K to mid-M dwarfs with proper motion memberships that have been observed by the repurposed Kepler mission, K2. With this survey, we will provide a well-constrained membership list of the cluster. By removing interloping stars and determining the cluster binary frequency we can avoid systematic errors in our analysis of the K2 findings and more accurately determine exoplanet properties in the Praesepe cluster. Obtaining accurate exoplanet parameters in open clusters allows us to study the temporal dimension of exoplanet parameter space. We find Praesepe to have a mean radial velocity of 34.09 km/s and a velocity dispersion of 1.13 km/s, which is consistent with previous studies. We derive radial velocity membership probabilities for stars with ≥3 radial velocity measurements and compare against published membership probabilities. We also identify radial velocity variables and potential double-lined spectroscopic binaries. We plan to obtain more observations to determine the radial velocity membership of all the stars in our sample, as well as follow up on radial velocity variables to determine binary orbital solutions.

Clustering Gene Expression Time Series with Coregionalization: Speed propagation of ALS

OpenAIRE

Rahman, Muhammad Arifur; Heath, Paul R.; Lawrence, Neil D.

2018-01-01

Clustering of gene expression time series gives insight into which genes may be coregulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different model conditions or genetic background. Amyotrophic lateral sclerosis (ALS), an irreversible diverse neurodegenerative disorder showed consistent phenotypic differences and the disease progression is heterogeneous with significant variability. Thi...

Regulation of the Apolipoprotein Gene Cluster by a Long Noncoding RNA

Directory of Open Access Journals (Sweden)

Paul Halley

2014-01-01

Full Text Available Apolipoprotein A1 (APOA1 is the major protein component of high-density lipoprotein (HDL in plasma. We have identified an endogenously expressed long noncoding natural antisense transcript, APOA1-AS, which acts as a negative transcriptional regulator of APOA1 both in vitro and in vivo. Inhibition of APOA1-AS in cultured cells resulted in the increased expression of APOA1 and two neighboring genes in the APO cluster. Chromatin immunoprecipitation (ChIP analyses of a ∼50 kb chromatin region flanking the APOA1 gene demonstrated that APOA1-AS can modulate distinct histone methylation patterns that mark active and/or inactive gene expression through the recruitment of histone-modifying enzymes. Targeting APOA1-AS with short antisense oligonucleotides also enhanced APOA1 expression in both human and monkey liver cells and induced an increase in hepatic RNA and protein expression in African green monkeys. Furthermore, the results presented here highlight the significant local modulatory effects of long noncoding antisense RNAs and demonstrate the therapeutic potential of manipulating the expression of these transcripts both in vitro and in vivo.

Identifying the ideal profile of French yogurts for different clusters of consumers.

Science.gov (United States)

Masson, M; Saint-Eve, A; Delarue, J; Blumenthal, D

2016-05-01

Identifying the sensory properties that affect consumer preferences for food products is an important feature of product development. Different methods, such as external preference mapping or partial least squares regression, are used to establish relationships between sensory data and consumer preferences and to identify sensory attributes that drive consumer preferences, by highlighting optimum products. Plain French yogurts were evaluated by a sensory profiling method performed by 12 trained judges. In parallel, 180 consumers were asked to score their overall liking and complete a cognitive restraint questionnaire. After hierarchical cluster analysis on the liking scores, preference mapping using a quadratic regression model was performed. Five clusters of consumers were identified as a function of different preference patterns. Contrary to our expectations, fat levels were not discriminating. For each cluster, the results of preference mapping enabled the identification of optimum products. A comparison of the 5 sensory profiles revealed numerous differences between key sensory attributes. For example, one consumer cluster had a strong preference for products perceived as very thick, grainy, but with a less flowing texture, less sticky, whey presence and color, in contrast to other clusters. In addition, each segment of consumers was characterized according to the results of the cognitive restraint questionnaire. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The gsdf gene locus harbors evolutionary conserved and clustered genes preferentially expressed in fish previtellogenic oocytes.

Science.gov (United States)

Gautier, Aude; Le Gac, Florence; Lareyre, Jean-Jacques

2011-02-01

display a different cellular localization compared to that of the gsdf gene indicating that the later gene is not co-regulated. Interestingly, our study identifies new clustered genes that are specifically expressed in previtellogenic oocytes (nup54, aff1, klhl8, sdad1). Copyright © 2010 Elsevier B.V. All rights reserved.

Integrated pathway clusters with coherent biological themes for target prioritisation.

Directory of Open Access Journals (Sweden)

Yi-An Chen

Full Text Available Prioritising candidate genes for further experimental characterisation is an essential, yet challenging task in biomedical research. One way of achieving this goal is to identify specific biological themes that are enriched within the gene set of interest to obtain insights into the biological phenomena under study. Biological pathway data have been particularly useful in identifying functional associations of genes and/or gene sets. However, biological pathway information as compiled in varied repositories often differs in scope and content, preventing a more effective and comprehensive characterisation of gene sets. Here we describe a new approach to constructing biologically coherent gene sets from pathway data in major public repositories and employing them for functional analysis of large gene sets. We first revealed significant overlaps in gene content between different pathways and then defined a clustering method based on the shared gene content and the similarity of gene overlap patterns. We established the biological relevance of the constructed pathway clusters using independent quantitative measures and we finally demonstrated the effectiveness of the constructed pathway clusters in comparative functional enrichment analysis of gene sets associated with diverse human diseases gathered from the literature. The pathway clusters and gene mappings have been integrated into the TargetMine data warehouse and are likely to provide a concise, manageable and biologically relevant means of functional analysis of gene sets and to facilitate candidate gene prioritisation.

Patterns of genetic diversity and differentiation in resistance gene clusters of two hybridizing European Populus species

OpenAIRE

Casey, Céline; Stölting, Kai N.; Barbará, Thelma; González-Martínez, Santiago C.; Lexer, Christian

2015-01-01

Resistance genes (R-genes) are essential for long-lived organisms such as forest trees, which are exposed to diverse herbivores and pathogens. In short-lived model species, R-genes have been shown to be involved in species isolation. Here, we studied more than 400 trees from two natural hybrid zones of the European Populus species Populus alba and Populus tremula for microsatellite markers located in three R-gene clusters, including one cluster situated in the incipient sex chromosome region....

Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

Directory of Open Access Journals (Sweden)

Victor M. Bii

2016-10-01

Full Text Available Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types.

Mouse Nkrp1-Clr gene cluster sequence and expression analyses reveal conservation of tissue-specific MHC-independent immunosurveillance.

Directory of Open Access Journals (Sweden)

Qiang Zhang

Full Text Available The Nkrp1 (Klrb1-Clr (Clec2 genes encode a receptor-ligand system utilized by NK cells as an MHC-independent immunosurveillance strategy for innate immune responses. The related Ly49 family of MHC-I receptors displays extreme allelic polymorphism and haplotype plasticity. In contrast, previous BAC-mapping and aCGH studies in the mouse suggest the neighboring and related Nkrp1-Clr cluster is evolutionarily stable. To definitively compare the relative evolutionary rate of Nkrp1-Clr vs. Ly49 gene clusters, the Nkrp1-Clr gene clusters from two Ly49 haplotype-disparate inbred mouse strains, BALB/c and 129S6, were sequenced. Both Nkrp1-Clr gene cluster sequences are highly similar to the C57BL/6 reference sequence, displaying the same gene numbers and order, complete pseudogenes, and gene fragments. The Nkrp1-Clr clusters contain a strikingly dissimilar proportion of repetitive elements compared to the Ly49 clusters, suggesting that certain elements may be partly responsible for the highly disparate Ly49 vs. Nkrp1 evolutionary rate. Focused allelic polymorphisms were found within the Nkrp1b/d (Klrb1b, Nkrp1c (Klrb1c, and Clr-c (Clec2f genes, suggestive of possible immune selection. Cell-type specific transcription of Nkrp1-Clr genes in a large panel of tissues/organs was determined. Clr-b (Clec2d and Clr-g (Clec2i showed wide expression, while other Clr genes showed more tissue-specific expression patterns. In situ hybridization revealed specific expression of various members of the Clr family in leukocytes/hematopoietic cells of immune organs, various tissue-restricted epithelial cells (including intestinal, kidney tubular, lung, and corneal progenitor epithelial cells, as well as myocytes. In summary, the Nkrp1-Clr gene cluster appears to evolve more slowly relative to the related Ly49 cluster, and likely regulates innate immunosurveillance in a tissue-specific manner.

Comprehensive Analysis of Gene Expression Profiles of Sepsis-Induced Multiorgan Failure Identified Its Valuable Biomarkers.

Science.gov (United States)

Wang, Yumei; Yin, Xiaoling; Yang, Fang

2018-02-01

Sepsis is an inflammatory-related disease, and severe sepsis would induce multiorgan dysfunction, which is the most common cause of death of patients in noncoronary intensive care units. Progression of novel therapeutic strategies has proven to be of little impact on the mortality of severe sepsis, and unfortunately, its mechanisms still remain poorly understood. In this study, we analyzed gene expression profiles of severe sepsis with failure of lung, kidney, and liver for the identification of potential biomarkers. We first downloaded the gene expression profiles from the Gene Expression Omnibus and performed preprocessing of raw microarray data sets and identification of differential expression genes (DEGs) through the R programming software; then, significantly enriched functions of DEGs in lung, kidney, and liver failure sepsis samples were obtained from the Database for Annotation, Visualization, and Integrated Discovery; finally, protein-protein interaction network was constructed for DEGs based on the STRING database, and network modules were also obtained through the MCODE cluster method. As a result, lung failure sepsis has the highest number of DEGs of 859, whereas the number of DEGs in kidney and liver failure sepsis samples is 178 and 175, respectively. In addition, 17 overlaps were obtained among the three lists of DEGs. Biological processes related to immune and inflammatory response were found to be significantly enriched in DEGs. Network and module analysis identified four gene clusters in which all or most of genes were upregulated. The expression changes of Icam1 and Socs3 were further validated through quantitative PCR analysis. This study should shed light on the development of sepsis and provide potential therapeutic targets for sepsis-induced multiorgan failure.

The Widespread Multidrug-Resistant Serotype O12 Pseudomonas aeruginosa Clone Emerged through Concomitant Horizontal Transfer of Serotype Antigen and Antibiotic Resistance Gene Clusters

DEFF Research Database (Denmark)

Thrane, Sandra Wingaard; Taylor, Véronique L.; Freschi, Luca

2015-01-01

. aeruginosa O12 OSA gene cluster, an antibiotic resistance determinant (gyrAC248T), and other genes that have been transferred between P. aeruginosa strains with distinct core genome architectures. We showed that these genes were likely acquired from an O12 serotype strain that is closely related to P...... in clinical settings and outbreaks. These serotype O12 isolates exhibit high levels of resistance to various classes of antibiotics. Here, we explore how the P. aeruginosa OSA biosynthesis gene clusters evolve in the population by investigating the association between the phylogenetic relationships among 83 P....... aeruginosa strains and their serotypes. While most serotypes were closely linked to the core genome phylogeny, we observed horizontal exchange of OSA biosynthesis genes among phylogenetically distinct P. aeruginosa strains. Specifically, we identified a "serotype island" ranging from 62 kb to 185 kb containing the P...

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

Science.gov (United States)

Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis

Gene expression data clustering and it’s application in differential analysis of leukemia

Directory of Open Access Journals (Sweden)

M. Vahedi

2008-02-01

Full Text Available Introduction: DNA microarray technique is one of the most important categories in bioinformatics,which allows the possibility of monitoring thousands of expressed genes has been resulted in creatinggiant data bases of gene expression data, recently. Statistical analysis of such databases includednormalization, clustering, classification and etc.Materials and Methods: Golub et al (1999 collected data bases of leukemia based on the method ofoligonucleotide. The data is on the internet. In this paper, we analyzed gene expression data. It wasclustered by several methods including multi-dimensional scaling, hierarchical and non-hierarchicalclustering. Data set included 20 Acute Lymphoblastic Leukemia (ALL patients and 14 Acute MyeloidLeukemia (AML patients. The results of tow methods of clustering were compared with regard to realgrouping (ALL & AML. R software was used for data analysis.Results: Specificity and sensitivity of divisive hierarchical clustering in diagnosing of ALL patientswere 75% and 92%, respectively. Specificity and sensitivity of partitioning around medoids indiagnosing of ALL patients were 90% and 93%, respectively. These results showed a wellaccomplishment of both methods of clustering. It is considerable that, due to clustering methodsresults, one of the samples was placed in ALL groups, which was in AML group in clinical test.Conclusion: With regard to concordance of the results with real grouping of data, therefore we canuse these methods in the cases where we don't have accurate information of real grouping of data.Moreover, Results of clustering might distinct subgroups of data in such a way that would be necessaryfor concordance with clinical outcomes, laboratory results and so on.

A novel polyketide biosynthesis gene cluster is involved in fruiting body morphogenesis in the filamentous fungi Sordaria macrospora and Neurospora crassa.

Science.gov (United States)

Nowrousian, Minou

2009-04-01

During fungal fruiting body development, hyphae aggregate to form multicellular structures that protect and disperse the sexual spores. Analysis of microarray data revealed a gene cluster strongly upregulated during fruiting body development in the ascomycete Sordaria macrospora. Real time PCR analysis showed that the genes from the orthologous cluster in Neurospora crassa are also upregulated during development. The cluster encodes putative polyketide biosynthesis enzymes, including a reducing polyketide synthase. Analysis of knockout strains of a predicted dehydrogenase gene from the cluster showed that mutants in N. crassa and S. macrospora are delayed in fruiting body formation. In addition to the upregulated cluster, the N. crassa genome comprises another cluster containing a polyketide synthase gene, and five additional reducing polyketide synthase (rpks) genes that are not part of clusters. To study the role of these genes in sexual development, expression of the predicted rpks genes in S. macrospora (five genes) and N. crassa (six genes) was analyzed; all but one are upregulated during sexual development. Analysis of knockout strains for the N. crassa rpks genes showed that one of them is essential for fruiting body formation. These data indicate that polyketides produced by RPKSs are involved in sexual development in filamentous ascomycetes.

The ergot alkaloid gene cluster: Functional analyses and evolutionary aspects

Czech Academy of Sciences Publication Activity Database

Lorenz, N.; Haarmann, T.; Pažoutová, Sylvie; Jung, M.; Tudzynski, P.

2009-01-01

Roč. 70, 15-16 (2009), s. 1822-1832 ISSN 0031-9422 Institutional research plan: CEZ:AV0Z50200510 Keywords : Claviceps purpurea * Ergot fungus * Ergot alkaloid gene cluster Subject RIV: EE - Microbiology, Virology Impact factor: 3.104, year: 2009

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

Directory of Open Access Journals (Sweden)

Jeban Ganesalingam

2009-09-01

Full Text Available Amyotrophic lateral sclerosis (ALS is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes.Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method.The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001. Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb and time from symptom onset to diagnosis (p<0.00001.The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.

Transcriptional dissection of melanoma identifies a high-risk subtype underlying TP53 family genes and epigenome deregulation

Science.gov (United States)

Badal, Brateil; Solovyov, Alexander; Di Cecilia, Serena; Chan, Joseph Minhow; Chang, Li-Wei; Iqbal, Ramiz; Aydin, Iraz T.; Rajan, Geena S.; Chen, Chen; Abbate, Franco; Arora, Kshitij S.; Tanne, Antoine; Gruber, Stephen B.; Johnson, Timothy M.; Fullen, Douglas R.; Phelps, Robert; Bhardwaj, Nina; Bernstein, Emily; Ting, David T.; Brunner, Georg; Schadt, Eric E.; Greenbaum, Benjamin D.; Celebi, Julide Tok

2017-01-01

BACKGROUND. Melanoma is a heterogeneous malignancy. We set out to identify the molecular underpinnings of high-risk melanomas, those that are likely to progress rapidly, metastasize, and result in poor outcomes. METHODS. We examined transcriptome changes from benign states to early-, intermediate-, and late-stage tumors using a set of 78 treatment-naive melanocytic tumors consisting of primary melanomas of the skin and benign melanocytic lesions. We utilized a next-generation sequencing platform that enabled a comprehensive analysis of protein-coding and -noncoding RNA transcripts. RESULTS. Gene expression changes unequivocally discriminated between benign and malignant states, and a dual epigenetic and immune signature emerged defining this transition. To our knowledge, we discovered previously unrecognized melanoma subtypes. A high-risk primary melanoma subset was distinguished by a 122-epigenetic gene signature (“epigenetic” cluster) and TP53 family gene deregulation (TP53, TP63, and TP73). This subtype associated with poor overall survival and showed enrichment of cell cycle genes. Noncoding repetitive element transcripts (LINEs, SINEs, and ERVs) that can result in immunostimulatory signals recapitulating a state of “viral mimicry” were significantly repressed. The high-risk subtype and its poor predictive characteristics were validated in several independent cohorts. Additionally, primary melanomas distinguished by specific immune signatures (“immune” clusters) were identified. CONCLUSION. The TP53 family of genes and genes regulating the epigenetic machinery demonstrate strong prognostic and biological relevance during progression of early disease. Gene expression profiling of protein-coding and -noncoding RNA transcripts may be a better predictor for disease course in melanoma. This study outlines the transcriptional interplay of the cancer cell’s epigenome with the immune milieu with potential for future therapeutic targeting. FUNDING

Leveraging long sequencing reads to investigate R-gene clustering and variation in sugar beet

Science.gov (United States)

Host-pathogen interactions are of prime importance to modern agriculture. Plants utilize various types of resistance genes to mitigate pathogen damage. Identification of the specific gene responsible for a specific resistance can be difficult due to duplication and clustering within R-gene families....

Complete re-sequencing of a 2Mb topological domain encompassing the FTO/IRXB genes identifies a novel obesity-associated region upstream of IRX5

DEFF Research Database (Denmark)

Hunt, Lilian E; Noyvert, Boris; Bhaw-Rosun, Leena

2015-01-01

BACKGROUND: Association studies have identified a number of loci that contribute to an increased body mass index (BMI), the strongest of which is in the first intron of the FTO gene on human chromosome 16q12.2. However, this region is both non-coding and under strong linkage disequilibrium, making...... it recalcitrant to functional interpretation. Furthermore, the FTO gene is located within a complex cis-regulatory landscape defined by a topologically associated domain that includes the IRXB gene cluster, a trio of developmental regulators. Consequently, at least three genes in this interval have been...... implicated in the aetiology of obesity. METHODS: Here, we sequence a 2 Mb region encompassing the FTO, RPGRIP1L and IRXB cluster genes in 284 individuals from a well-characterised study group of Danish men containing extremely overweight young adults and controls. We further replicate our findings both...

Sequencing and transcriptional analysis of the Streptococcus thermophilus histamine biosynthesis gene cluster: factors that affect differential hdcA expression

DEFF Research Database (Denmark)

Calles-Enríquez, Marina; Hjort, Benjamin Benn; Andersen, Pia Skov

2010-01-01

to produce histamine. The hdc clusters of S. thermophilus CHCC1524 and CHCC6483 were sequenced, and the factors that affect histamine biosynthesis and histidine-decarboxylating gene (hdcA) expression were studied. The hdc cluster began with the hdcA gene, was followed by a transporter (hdcP), and ended...... with the hdcB gene, which is of unknown function. The three genes were orientated in the same direction. The genetic organization of the hdc cluster showed a unique organization among the lactic acid bacterial group and resembled those of Staphylococcus and Clostridium species, thus indicating possible...... acquisition through a horizontal transfer mechanism. Transcriptional analysis of the hdc cluster revealed the existence of a polycistronic mRNA covering the three genes. The histidine-decarboxylating gene (hdcA) of S. thermophilus demonstrated maximum expression during the stationary growth phase, with high...

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

Science.gov (United States)

Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

2015-03-01

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Strategies to regulate transcription factor-mediated gene positioning and interchromosomal clustering at the nuclear periphery.

Science.gov (United States)

Randise-Hinchliff, Carlo; Coukos, Robert; Sood, Varun; Sumner, Michael Chas; Zdraljevic, Stefan; Meldi Sholl, Lauren; Garvey Brickner, Donna; Ahmed, Sara; Watchmaker, Lauren; Brickner, Jason H

2016-03-14

In budding yeast, targeting of active genes to the nuclear pore complex (NPC) and interchromosomal clustering is mediated by transcription factor (TF) binding sites in the gene promoters. For example, the binding sites for the TFs Put3, Ste12, and Gcn4 are necessary and sufficient to promote positioning at the nuclear periphery and interchromosomal clustering. However, in all three cases, gene positioning and interchromosomal clustering are regulated. Under uninducing conditions, local recruitment of the Rpd3(L) histone deacetylase by transcriptional repressors blocks Put3 DNA binding. This is a general function of yeast repressors: 16 of 21 repressors blocked Put3-mediated subnuclear positioning; 11 of these required Rpd3. In contrast, Ste12-mediated gene positioning is regulated independently of DNA binding by mitogen-activated protein kinase phosphorylation of the Dig2 inhibitor, and Gcn4-dependent targeting is up-regulated by increasing Gcn4 protein levels. These different regulatory strategies provide either qualitative switch-like control or quantitative control of gene positioning over different time scales. © 2016 Randise-Hinchliff et al.

Spatial expression of Hox cluster genes in the ontogeny of a sea urchin

Science.gov (United States)

Arenas-Mena, C.; Cameron, A. R.; Davidson, E. H.

2000-01-01

The Hox cluster of the sea urchin Strongylocentrous purpuratus contains ten genes in a 500 kb span of the genome. Only two of these genes are expressed during embryogenesis, while all of eight genes tested are expressed during development of the adult body plan in the larval stage. We report the spatial expression during larval development of the five 'posterior' genes of the cluster: SpHox7, SpHox8, SpHox9/10, SpHox11/13a and SpHox11/13b. The five genes exhibit a dynamic, largely mesodermal program of expression. Only SpHox7 displays extensive expression within the pentameral rudiment itself. A spatially sequential and colinear arrangement of expression domains is found in the somatocoels, the paired posterior mesodermal structures that will become the adult perivisceral coeloms. No such sequential expression pattern is observed in endodermal, epidermal or neural tissues of either the larva or the presumptive juvenile sea urchin. The spatial expression patterns of the Hox genes illuminate the evolutionary process by which the pentameral echinoderm body plan emerged from a bilateral ancestor.

Some statistical properties of gene expression clustering for array data

DEFF Research Database (Denmark)

Abreu, G C G; Pinheiro, A; Drummond, R D

2010-01-01

DNA array data without a corresponding statistical error measure. We propose an easy-to-implement and simple-to-use technique that uses bootstrap re-sampling to evaluate the statistical error of the nodes provided by SOM-based clustering. Comparisons between SOM and parametric clustering are presented...... for simulated as well as for two real data sets. We also implement a bootstrap-based pre-processing procedure for SOM, that improves the false discovery ratio of differentially expressed genes. Code in Matlab is freely available, as well as some supplementary material, at the following address: https...

Genomic and expression analysis of the vanG-like gene cluster of Clostridium difficile.

Science.gov (United States)

Peltier, Johann; Courtin, Pascal; El Meouche, Imane; Catel-Ferreira, Manuella; Chapot-Chartier, Marie-Pierre; Lemée, Ludovic; Pons, Jean-Louis

2013-07-01

Primary antibiotic treatment of Clostridium difficile intestinal diseases requires metronidazole or vancomycin therapy. A cluster of genes homologous to enterococcal glycopeptides resistance vanG genes was found in the genome of C. difficile 630, although this strain remains sensitive to vancomycin. This vanG-like gene cluster was found to consist of five ORFs: the regulatory region consisting of vanR and vanS and the effector region consisting of vanG, vanXY and vanT. We found that 57 out of 83 C. difficile strains, representative of the main lineages of the species, harbour this vanG-like cluster. The cluster is expressed as an operon and, when present, is found at the same genomic location in all strains. The vanG, vanXY and vanT homologues in C. difficile 630 are co-transcribed and expressed to a low level throughout the growth phases in the absence of vancomycin. Conversely, the expression of these genes is strongly induced in the presence of subinhibitory concentrations of vancomycin, indicating that the vanG-like operon is functional at the transcriptional level in C. difficile. Hydrophilic interaction liquid chromatography (HILIC-HPLC) and MS analysis of cytoplasmic peptidoglycan precursors of C. difficile 630 grown without vancomycin revealed the exclusive presence of a UDP-MurNAc-pentapeptide with an alanine at the C terminus. UDP-MurNAc-pentapeptide [d-Ala] was also the only peptidoglycan precursor detected in C. difficile grown in the presence of vancomycin, corroborating the lack of vancomycin resistance. Peptidoglycan structures of a vanG-like mutant strain and of a strain lacking the vanG-like cluster did not differ from the C. difficile 630 strain, indicating that the vanG-like cluster also has no impact on cell-wall composition.

Comprehensive identification and clustering of CLV3/ESR-related (CLE) genes in plants finds groups with potentially shared function.

Science.gov (United States)

Goad, David M; Zhu, Chuanmei; Kellogg, Elizabeth A

2017-10-01

CLV3/ESR (CLE) proteins are important signaling peptides in plants. The short CLE peptide (12-13 amino acids) is cleaved from a larger pre-propeptide and functions as an extracellular ligand. The CLE family is large and has resisted attempts at classification because the CLE domain is too short for reliable phylogenetic analysis and the pre-propeptide is too variable. We used a model-based search for CLE domains from 57 plant genomes and used the entire pre-propeptide for comprehensive clustering analysis. In total, 1628 CLE genes were identified in land plants, with none recognizable from green algae. These CLEs form 12 groups within which CLE domains are largely conserved and pre-propeptides can be aligned. Most clusters contain sequences from monocots, eudicots and Amborella trichopoda, with sequences from Picea abies, Selaginella moellendorffii and Physcomitrella patens scattered in some clusters. We easily identified previously known clusters involved in vascular differentiation and nodulation. In addition, we found a number of discrete groups whose function remains poorly characterized. Available data indicate that CLE proteins within a cluster are likely to share function, whereas those from different clusters play at least partially different roles. Our analysis provides a foundation for future evolutionary and functional studies. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Burkholderia thailandensis harbors two identical rhl gene clusters responsible for the biosynthesis of rhamnolipids

Directory of Open Access Journals (Sweden)

Woods Donald E

2009-12-01

Full Text Available Abstract Background Rhamnolipids are surface active molecules composed of rhamnose and β-hydroxydecanoic acid. These biosurfactants are produced mainly by Pseudomonas aeruginosa and have been thoroughly investigated since their early discovery. Recently, they have attracted renewed attention because of their involvement in various multicellular behaviors. Despite this high interest, only very few studies have focused on the production of rhamnolipids by Burkholderia species. Results Orthologs of rhlA, rhlB and rhlC, which are responsible for the biosynthesis of rhamnolipids in P. aeruginosa, have been found in the non-infectious Burkholderia thailandensis, as well as in the genetically similar important pathogen B. pseudomallei. In contrast to P. aeruginosa, both Burkholderia species contain these three genes necessary for rhamnolipid production within a single gene cluster. Furthermore, two identical, paralogous copies of this gene cluster are found on the second chromosome of these bacteria. Both Burkholderia spp. produce rhamnolipids containing 3-hydroxy fatty acid moieties with longer side chains than those described for P. aeruginosa. Additionally, the rhamnolipids produced by B. thailandensis contain a much larger proportion of dirhamnolipids versus monorhamnolipids when compared to P. aeruginosa. The rhamnolipids produced by B. thailandensis reduce the surface tension of water to 42 mN/m while displaying a critical micelle concentration value of 225 mg/L. Separate mutations in both rhlA alleles, which are responsible for the synthesis of the rhamnolipid precursor 3-(3-hydroxyalkanoyloxyalkanoic acid, prove that both copies of the rhl gene cluster are functional, but one contributes more to the total production than the other. Finally, a double ΔrhlA mutant that is completely devoid of rhamnolipid production is incapable of swarming motility, showing that both gene clusters contribute to this phenotype. Conclusions Collectively, these

Histone and ribosomal RNA repetitive gene clusters of the boll weevil are linked in a tandem array.

Science.gov (United States)

Roehrdanz, R; Heilmann, L; Senechal, P; Sears, S; Evenson, P

2010-08-01

Histones are the major protein component of chromatin structure. The histone family is made up of a quintet of proteins, four core histones (H2A, H2B, H3 & H4) and the linker histones (H1). Spacers are found between the coding regions. Among insects this quintet of genes is usually clustered and the clusters are tandemly repeated. Ribosomal DNA contains a cluster of the rRNA sequences 18S, 5.8S and 28S. The rRNA genes are separated by the spacers ITS1, ITS2 and IGS. This cluster is also tandemly repeated. We found that the ribosomal RNA repeat unit of at least two species of Anthonomine weevils, Anthonomus grandis and Anthonomus texanus (Coleoptera: Curculionidae), is interspersed with a block containing the histone gene quintet. The histone genes are situated between the rRNA 18S and 28S genes in what is known as the intergenic spacer region (IGS). The complete reiterated Anthonomus grandis histone-ribosomal sequence is 16,248 bp.

Molecular population genetics of the β-esterase gene cluster of ...

Indian Academy of Sciences (India)

We suggest that the demographic history (bottleneck and admixture of genetically differentiated populations) is the major factor shaping the pattern of nucleotide polymorphism in the -esterase gene cluster. However there are some 'footprints' of directional and balancing selection shaping specific distribution of nucleotide ...

Genetic clusters and sex-biased gene flow in a unicolonial Formica ant

Directory of Open Access Journals (Sweden)

Chapuisat Michel

2009-03-01

Full Text Available Abstract Background Animal societies are diverse, ranging from small family-based groups to extraordinarily large social networks in which many unrelated individuals interact. At the extreme of this continuum, some ant species form unicolonial populations in which workers and queens can move among multiple interconnected nests without eliciting aggression. Although unicoloniality has been mostly studied in invasive ants, it also occurs in some native non-invasive species. Unicoloniality is commonly associated with very high queen number, which may result in levels of relatedness among nestmates being so low as to raise the question of the maintenance of altruism by kin selection in such systems. However, the actual relatedness among cooperating individuals critically depends on effective dispersal and the ensuing pattern of genetic structuring. In order to better understand the evolution of unicoloniality in native non-invasive ants, we investigated the fine-scale population genetic structure and gene flow in three unicolonial populations of the wood ant F. paralugubris. Results The analysis of geo-referenced microsatellite genotypes and mitochondrial haplotypes revealed the presence of cryptic clusters of genetically-differentiated nests in the three populations of F. paralugubris. Because of this spatial genetic heterogeneity, members of the same clusters were moderately but significantly related. The comparison of nuclear (microsatellite and mitochondrial differentiation indicated that effective gene flow was male-biased in all populations. Conclusion The three unicolonial populations exhibited male-biased and mostly local gene flow. The high number of queens per nest, exchanges among neighbouring nests and restricted long-distance gene flow resulted in large clusters of genetically similar nests. The positive relatedness among clustermates suggests that kin selection may still contribute to the maintenance of altruism in unicolonial

Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress

OpenAIRE

Liu, He; Yang, Chun-Lan; Ge, Meng-Yu; Ibrahim, Muhammad; Li, Bin; Zhao, Wen-Jun; Chen, Gong-You; Zhu, Bo; Xie, Guan-Lin

2014-01-01

Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay demonstrated that TetR regulator bound directly to the promoter of ...

Liver regeneration signature in hepatitis B virus (HBV-associated acute liver failure identified by gene expression profiling.

Directory of Open Access Journals (Sweden)

Oriel Nissim

Full Text Available The liver has inherent regenerative capacity via mitotic division of mature hepatocytes or, when the hepatic loss is massive or hepatocyte proliferation is impaired, through activation of hepatic stem/progenitor cells (HSPC. The dramatic clinical course of acute liver failure (ALF has posed major limitations to investigating the molecular mechanisms of liver regeneration and the role of HSPC in this setting. We investigated the molecular mechanisms of liver regeneration in 4 patients who underwent liver transplantation for hepatitis B virus (HBV-associated ALF.Gene expression profiling of 17 liver specimens from the 4 ALF cases and individual specimens from 10 liver donors documented a distinct gene signature for ALF. However, unsupervised multidimensional scaling and hierarchical clustering identified two clusters of ALF that segregated according to histopathological severity massive hepatic necrosis (MHN; 2 patients and submassive hepatic necrosis (SHN; 2 patients. We found that ALF is characterized by a strong HSPC gene signature, along with ductular reaction, both of which are more prominent in MHN. Interestingly, no evidence of further lineage differentiation was seen in MHN, whereas in SHN we detected cells with hepatocyte-like morphology. Strikingly, ALF was associated with a strong tumorigenesis gene signature. MHN had the greatest upregulation of stem cell genes (EpCAM, CK19, CK7, whereas the most up-regulated genes in SHN were related to cellular growth and proliferation. The extent of liver necrosis correlated with an overriding fibrogenesis gene signature, reflecting the wound-healing process.Our data provide evidence for a distinct gene signature in HBV-associated ALF whose intensity is directly correlated with the histopathological severity. HSPC activation and fibrogenesis positively correlated with the extent of liver necrosis. Moreover, we detected a tumorigenesis gene signature in ALF, emphasizing the close relationship between

Candidate chemosensory genes identified in the endoparasitoid Meteorus pulchricornis (Hymenoptera: Braconidae) by antennal transcriptome analysis.

Science.gov (United States)

Sheng, Sheng; Liao, Cheng-Wu; Zheng, Yu; Zhou, Yu; Xu, Yan; Song, Wen-Miao; He, Peng; Zhang, Jian; Wu, Fu-An

2017-06-01

Meteorus pulchricornis is an endoparasitoid wasp which attacks the larvae of various lepidopteran pests. We present the first antennal transcriptome dataset for M. pulchricornis. A total of 48,845,072 clean reads were obtained and 34,967 unigenes were assembled. Of these, 15,458 unigenes showed a significant similarity (E-value <10 -5 ) to known proteins in the NCBI non-redundant protein database. Gene ontology (GO) and cluster of orthologous groups (COG) analyses were used to classify the functions of M. pulchricornis antennae genes. We identified 16 putative odorant-binding protein (OBP) genes, eight chemosensory protein (CSP) genes, 99 olfactory receptor (OR) genes, 19 ionotropic receptor (IR) genes and one sensory neuron membrane protein (SNMP) gene. BLASTx best hit results and phylogenetic analysis both indicated that these chemosensory genes were most closely related to those found in other hymenopteran species. Real-time quantitative PCR assays showed that 14 MpulOBP genes were antennae-specific. Of these, MpulOBP6, MpulOBP9, MpulOBP10, MpulOBP12, MpulOBP15 and MpulOBP16 were found to have greater expression in the antennae than in other body parts, while MpulOBP2 and MpulOBP3 were expressed predominately in the legs and abdomens, respectively. These results might provide a foundation for future studies of olfactory genes and chemoreception in M. pulchricornis. Copyright © 2017 Elsevier Inc. All rights reserved.

Clustering of two genes putatively involved in cyanate detoxification evolved recently and independently in multiple fungal lineages

Science.gov (United States)

Fungi that have the enzymes cyanase and carbonic anhydrase show a limited capacity to detoxify cyanate, a fungicide employed by both plants and humans. Here, we describe a novel two-gene cluster that comprises duplicated cyanase and carbonic anhydrase copies, which we name the CCA gene cluster, trac...

Protein-protein association and cellular localization of four essential gene products encoded by tellurite resistance-conferring cluster "ter" from pathogenic Escherichia coli.

Science.gov (United States)

Valkovicova, Lenka; Vavrova, Silvia Minarikova; Mravec, Jozef; Grones, Jozef; Turna, Jan

2013-12-01

Gene cluster "ter" conferring high tellurite resistance has been identified in various pathogenic bacteria including Escherichia coli O157:H7. However, the precise mechanism as well as the molecular function of the respective gene products is unclear. Here we describe protein-protein association and localization analyses of four essential Ter proteins encoded by minimal resistance-conferring fragment (terBCDE) by means of recombinant expression. By using a two-plasmid complementation system we show that the overproduced single Ter proteins are not able to mediate tellurite resistance, but all Ter members play an irreplaceable role within the cluster. We identified several types of homotypic and heterotypic protein-protein associations among the Ter proteins by in vitro and in vivo pull-down assays and determined their cellular localization by cytosol/membrane fractionation. Our results strongly suggest that Ter proteins function involves their mutual association, which probably happens at the interface of the inner plasma membrane and the cytosol.

Ortholog-based screening and identification of genes related to intracellular survival.

Science.gov (United States)

Yang, Xiaowen; Wang, Jiawei; Bing, Guoxia; Bie, Pengfei; De, Yanyan; Lyu, Yanli; Wu, Qingmin

2018-04-20

Bioinformatics and comparative genomics analysis methods were used to predict unknown pathogen genes based on homology with identified or functionally clustered genes. In this study, the genes of common pathogens were analyzed to screen and identify genes associated with intracellular survival through sequence similarity, phylogenetic tree analysis and the λ-Red recombination system test method. The total 38,952 protein-coding genes of common pathogens were divided into 19,775 clusters. As demonstrated through a COG analysis, information storage and processing genes might play an important role intracellular survival. Only 19 clusters were present in facultative intracellular pathogens, and not all were present in extracellular pathogens. Construction of a phylogenetic tree selected 18 of these 19 clusters. Comparisons with the DEG database and previous research revealed that seven other clusters are considered essential gene clusters and that seven other clusters are associated with intracellular survival. Moreover, this study confirmed that clusters screened by orthologs with similar function could be replaced with an approved uvrY gene and its orthologs, and the results revealed that the usg gene is associated with intracellular survival. The study improves the current understanding of intracellular pathogens characteristics and allows further exploration of the intracellular survival-related gene modules in these pathogens. Copyright © 2018. Published by Elsevier B.V.

Identification and analysis of the paulomycin biosynthetic gene cluster and titer improvement of the paulomycins in Streptomyces paulus NRRL 8115.

Directory of Open Access Journals (Sweden)

Jine Li

Full Text Available The paulomycins are a group of glycosylated compounds featuring a unique paulic acid moiety. To locate their biosynthetic gene clusters, the genomes of two paulomycin producers, Streptomyces paulus NRRL 8115 and Streptomyces sp. YN86, were sequenced. The paulomycin biosynthetic gene clusters were defined by comparative analyses of the two genomes together with the genome of the third paulomycin producer Streptomyces albus J1074. Subsequently, the identity of the paulomycin biosynthetic gene cluster was confirmed by inactivation of two genes involved in biosynthesis of the paulomycose branched chain (pau11 and the ring A moiety (pau18 in Streptomyces paulus NRRL 8115. After determining the gene cluster boundaries, a convergent biosynthetic model was proposed for paulomycin based on the deduced functions of the pau genes. Finally, a paulomycin high-producing strain was constructed by expressing an activator-encoding gene (pau13 in S. paulus, setting the stage for future investigations.

The effect of alcohol on the differential expression of cluster of differentiation 14 gene, associated pathways, and genetic network.

Directory of Open Access Journals (Sweden)

Diana X Zhou

Full Text Available Alcohol consumption affects human health in part by compromising the immune system. In this study, we examined the expression of the Cd14 (cluster of differentiation 14 gene, which is involved in the immune system through a proinflammatory cascade. Expression was evaluated in BXD mice treated with saline or acute 1.8 g/kg i.p. ethanol (12.5% v/v. Hippocampal gene expression data were generated to examine differential expression and to perform systems genetics analyses. The Cd14 gene expression showed significant changes among the BXD strains after ethanol treatment, and eQTL mapping revealed that Cd14 is a cis-regulated gene. We also identified eighteen ethanol-related phenotypes correlated with Cd14 expression related to either ethanol responses or ethanol consumption. Pathway analysis was performed to identify possible biological pathways involved in the response to ethanol and Cd14. We also constructed a genetic network for Cd14 using the top 20 correlated genes and present several genes possibly involved in Cd14 and ethanol responses based on differential gene expression. In conclusion, we found Cd14, along with several other genes and pathways, to be involved in ethanol responses in the hippocampus, such as increased susceptibility to lipopolysaccharides and neuroinflammation.

Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

Science.gov (United States)

Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

2017-08-01

This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

Gravitation field algorithm and its application in gene cluster

Directory of Open Access Journals (Sweden)

Zheng Ming

2010-09-01

Full Text Available Abstract Background Searching optima is one of the most challenging tasks in clustering genes from available experimental data or given functions. SA, GA, PSO and other similar efficient global optimization methods are used by biotechnologists. All these algorithms are based on the imitation of natural phenomena. Results This paper proposes a novel searching optimization algorithm called Gravitation Field Algorithm (GFA which is derived from the famous astronomy theory Solar Nebular Disk Model (SNDM of planetary formation. GFA simulates the Gravitation field and outperforms GA and SA in some multimodal functions optimization problem. And GFA also can be used in the forms of unimodal functions. GFA clusters the dataset well from the Gene Expression Omnibus. Conclusions The mathematical proof demonstrates that GFA could be convergent in the global optimum by probability 1 in three conditions for one independent variable mass functions. In addition to these results, the fundamental optimization concept in this paper is used to analyze how SA and GA affect the global search and the inherent defects in SA and GA. Some results and source code (in Matlab are publicly available at http://ccst.jlu.edu.cn/CSBG/GFA.

Hierarchical clustering of gene expression patterns in the Eomes + lineage of excitatory neurons during early neocortical development

Directory of Open Access Journals (Sweden)

Cameron David A

2012-08-01

Full Text Available Abstract Background Cortical neurons display dynamic patterns of gene expression during the coincident processes of differentiation and migration through the developing cerebrum. To identify genes selectively expressed by the Eomes + (Tbr2 lineage of excitatory cortical neurons, GFP-expressing cells from Tg(Eomes::eGFP Gsat embryos were isolated to > 99% purity and profiled. Results We report the identification, validation and spatial grouping of genes selectively expressed within the Eomes + cortical excitatory neuron lineage during early cortical development. In these neurons 475 genes were expressed ≥ 3-fold, and 534 genes ≤ 3-fold, compared to the reference population of neuronal precursors. Of the up-regulated genes, 328 were represented at the Genepaint in situ hybridization database and 317 (97% were validated as having spatial expression patterns consistent with the lineage of differentiating excitatory neurons. A novel approach for quantifying in situ hybridization patterns (QISP across the cerebral wall was developed that allowed the hierarchical clustering of genes into putative co-regulated groups. Forty four candidate genes were identified that show spatial expression with Intermediate Precursor Cells, 49 candidate genes show spatial expression with Multipolar Neurons, while the remaining 224 genes achieved peak expression in the developing cortical plate. Conclusions This analysis of differentiating excitatory neurons revealed the expression patterns of 37 transcription factors, many chemotropic signaling molecules (including the Semaphorin, Netrin and Slit signaling pathways, and unexpected evidence for non-canonical neurotransmitter signaling and changes in mechanisms of glucose metabolism. Over half of the 317 identified genes are associated with neuronal disease making these findings a valuable resource for studies of neurological development and disease.

Draft genome sequence of Streptomyces coelicoflavus ZG0656 reveals the putative biosynthetic gene cluster of acarviostatin family α-amylase inhibitors.

Science.gov (United States)

Guo, X; Geng, P; Bai, F; Bai, G; Sun, T; Li, X; Shi, L; Zhong, Q

2012-08-01

The aims of this study are to obtain the draft genome sequence of Streptomyces coelicoflavus ZG0656, which produces novel acarviostatin family α-amylase inhibitors, and then to reveal the putative acarviostatin-related gene cluster and the biosynthetic pathway. The draft genome sequence of S. coelicoflavus ZG0656 was generated using a shotgun approach employing a combination of 454 and Solexa sequencing technologies. Genome analysis revealed a putative gene cluster for acarviostatin biosynthesis, termed sct-cluster. The cluster contains 13 acarviostatin synthetic genes, six transporter genes, four starch degrading or transglycosylation enzyme genes and two regulator genes. On the basis of bioinformatic analysis, we proposed a putative biosynthetic pathway of acarviostatins. The intracellular steps produce a structural core, acarviostatin I00-7-P, and the extracellular assemblies lead to diverse acarviostatin end products. The draft genome sequence of S. coelicoflavus ZG0656 revealed the putative biosynthetic gene cluster of acarviostatins and a putative pathway of acarviostatin production. To our knowledge, S. coelicoflavus ZG0656 is the first strain in this species for which a genome sequence has been reported. The analysis of sct-cluster provided important insights into the biosynthesis of acarviostatins. This work will be a platform for producing novel variants and yield improvement. © 2012 The Authors. Letters in Applied Microbiology © 2012 The Society for Applied Microbiology.

Diverse and Abundant Secondary Metabolism Biosynthetic Gene Clusters in the Genomes of Marine Sponge Derived Streptomyces spp. Isolates

Directory of Open Access Journals (Sweden)

Stephen A. Jackson

2018-02-01

Full Text Available The genus Streptomyces produces secondary metabolic compounds that are rich in biological activity. Many of these compounds are genetically encoded by large secondary metabolism biosynthetic gene clusters (smBGCs such as polyketide synthases (PKS and non-ribosomal peptide synthetases (NRPS which are modular and can be highly repetitive. Due to the repeats, these gene clusters can be difficult to resolve using short read next generation datasets and are often quite poorly predicted using standard approaches. We have sequenced the genomes of 13 Streptomyces spp. strains isolated from shallow water and deep-sea sponges that display antimicrobial activities against a number of clinically relevant bacterial and yeast species. Draft genomes have been assembled and smBGCs have been identified using the antiSMASH (antibiotics and Secondary Metabolite Analysis Shell web platform. We have compared the smBGCs amongst strains in the search for novel sequences conferring the potential to produce novel bioactive secondary metabolites. The strains in this study recruit to four distinct clades within the genus Streptomyces. The marine strains host abundant smBGCs which encode polyketides, NRPS, siderophores, bacteriocins and lantipeptides. The deep-sea strains appear to be enriched with gene clusters encoding NRPS. Marine adaptations are evident in the sponge-derived strains which are enriched for genes involved in the biosynthesis and transport of compatible solutes and for heat-shock proteins. Streptomyces spp. from marine environments are a promising source of novel bioactive secondary metabolites as the abundance and diversity of smBGCs show high degrees of novelty. Sponge derived Streptomyces spp. isolates appear to display genomic adaptations to marine living when compared to terrestrial strains.

Molecular comparison of the structural proteins encoding gene clusters of two related Lactobacillus delbrueckii bacteriophages.

Science.gov (United States)

Vasala, A; Dupont, L; Baumann, M; Ritzenthaler, P; Alatossava, T

1993-01-01

Virulent phage LL-H and temperate phage mv4 are two related bacteriophages of Lactobacillus delbrueckii. The gene clusters encoding structural proteins of these two phages have been sequenced and further analyzed. Six open reading frames (ORF-1 to ORF-6) were detected. Protein sequencing and Western immunoblotting experiments confirmed that ORF-3 (g34) encoded the main capsid protein Gp34. The presence of a putative late promoter in front of the phage LL-H g34 gene was suggested by primer extension experiments. Comparative sequence analysis between phage LL-H and phage mv4 revealed striking similarities in the structure and organization of this gene cluster, suggesting that the genes encoding phage structural proteins belong to a highly conservative module. Images PMID:8497043

Identification and manipulation of the pleuromutilin gene cluster from Clitopilus passeckerianus for increased rapid antibiotic production

Science.gov (United States)

Bailey, Andy M.; Alberti, Fabrizio; Kilaru, Sreedhar; Collins, Catherine M.; de Mattos-Shipley, Kate; Hartley, Amanda J.; Hayes, Patrick; Griffin, Alison; Lazarus, Colin M.; Cox, Russell J.; Willis, Christine L.; O'Dwyer, Karen; Spence, David W.; Foster, Gary D.

2016-05-01

Semi-synthetic derivatives of the tricyclic diterpene antibiotic pleuromutilin from the basidiomycete Clitopilus passeckerianus are important in combatting bacterial infections in human and veterinary medicine. These compounds belong to the only new class of antibiotics for human applications, with novel mode of action and lack of cross-resistance, representing a class with great potential. Basidiomycete fungi, being dikaryotic, are not generally amenable to strain improvement. We report identification of the seven-gene pleuromutilin gene cluster and verify that using various targeted approaches aimed at increasing antibiotic production in C. passeckerianus, no improvement in yield was achieved. The seven-gene pleuromutilin cluster was reconstructed within Aspergillus oryzae giving production of pleuromutilin in an ascomycete, with a significant increase (2106%) in production. This is the first gene cluster from a basidiomycete to be successfully expressed in an ascomycete, and paves the way for the exploitation of a metabolically rich but traditionally overlooked group of fungi.

Molecular evolution of the nif gene cluster carrying nifI1 and nifI2 genes in the Gram-positive phototrophic bacterium Heliobacterium chlorum.

Science.gov (United States)

Enkh-Amgalan, Jigjiddorj; Kawasaki, Hiroko; Seki, Tatsuji

2006-01-01

A major nif cluster was detected in the strictly anaerobic, Gram-positive phototrophic bacterium Heliobacterium chlorum. The cluster consisted of 11 genes arranged within a 10 kb region in the order nifI1, nifI2, nifH, nifD, nifK, nifE, nifN, nifX, fdx, nifB and nifV. The phylogenetic position of Hbt. chlorum was the same in the NifH, NifD, NifK, NifE and NifN trees; Hbt. chlorum formed a cluster with Desulfitobacterium hafniense, the closest neighbour of heliobacteria based on the 16S rRNA phylogeny, and two species of the genus Geobacter belonging to the Deltaproteobacteria. Two nifI genes, known to occur in the nif clusters of methanogenic archaea between nifH and nifD, were found upstream of the nifH gene of Hbt. chlorum. The organization of the nif operon and the phylogeny of individual and concatenated gene products showed that the Hbt. chlorum nif operon carrying nifI genes upstream of the nifH gene was an intermediate between the nif operon with nifI downstream of nifH (group II and III of the nitrogenase classification) and the nif operon lacking nifI (group I). Thus, the phylogenetic position of Hbt. chlorum nitrogenase may reflect an evolutionary stage of a divergence of the two nitrogenase groups, with group I consisting of the aerobic diazotrophs and group II consisting of strictly anaerobic prokaryotes.

Association of paraoxonase gene cluster polymorphisms with ALS in France, Quebec, and Sweden.

Science.gov (United States)

Valdmanis, P N; Kabashi, E; Dyck, A; Hince, P; Lee, J; Dion, P; D'Amour, M; Souchon, F; Bouchard, J-P; Salachas, F; Meininger, V; Andersen, P M; Camu, W; Dupré, N; Rouleau, G A

2008-08-12

The paraoxonase gene cluster on chromosome 7 comprising the PON1-3 genes is an attractive candidate for association in amyotrophic lateral sclerosis (ALS) given the role of paraoxonase genes during the response to oxidative stress and their contribution to the enzymatic break down of nerve toxins. Oxidative stress is considered one of the mechanisms involved in ALS pathogenesis. Evidence for this includes the fact that mutations of SOD1, which normally reduce the production of toxic superoxide anion, account for 12% to 23% of familial cases in ALS. In addition, PON variants were shown to be associated with susceptibility to ALS in several North American and European populations. We extended this analysis to examine 20 single nucleotide polymorphisms (SNPs) across the PON gene cluster in a set of patients from France (480 cases, 475 controls), Quebec (159 cases, 95 controls), and Sweden (558 cases, 506 controls). Although individual SNPs were not considered associated on their own, a haplotype of SNPs at the C-terminal portion of PON2 that includes the PON2 C311S amino acid change was significant in the French (p value 0.0075) and Quebec (p value 0.026) populations as well as all three populations combined (p value 1.69 x 10(-6)). Stratification of the samples showed that this variation was pertinent to ALS susceptibility as a whole, and not to a particular subset of patients. These findings contribute to the increasing weight of evidence that genetic variants in the paraoxonase gene cluster are associated with amyotrophic lateral sclerosis.

Genetic interrelations in the actinomycin biosynthetic gene clusters of Streptomyces antibioticus IMRU 3720 and Streptomyces chrysomallus ATCC11523, producers of actinomycin X and actinomycin C

Science.gov (United States)

Crnovčić, Ivana; Rückert, Christian; Semsary, Siamak; Lang, Manuel; Kalinowski, Jörn; Keller, Ullrich

2017-01-01

Sequencing the actinomycin (acm) biosynthetic gene cluster of Streptomyces antibioticus IMRU 3720, which produces actinomycin X (Acm X), revealed 20 genes organized into a highly similar framework as in the bi-armed acm C biosynthetic gene cluster of Streptomyces chrysomallus but without an attached additional extra arm of orthologues as in the latter. Curiously, the extra arm of the S. chrysomallus gene cluster turned out to perfectly match the single arm of the S. antibioticus gene cluster in the same order of orthologues including the the presence of two pseudogenes, scacmM and scacmN, encoding a cytochrome P450 and its ferredoxin, respectively. Orthologues of the latter genes were both missing in the principal arm of the S. chrysomallus acm C gene cluster. All orthologues of the extra arm showed a G +C-contents different from that of their counterparts in the principal arm. Moreover, the similarities of translation products from the extra arm were all higher to the corresponding translation products of orthologue genes from the S. antibioticus acm X gene cluster than to those encoded by the principal arm of their own gene cluster. This suggests that the duplicated structure of the S. chrysomallus acm C biosynthetic gene cluster evolved from previous fusion between two one-armed acm gene clusters each from a different genetic background. However, while scacmM and scacmN in the extra arm of the S. chrysomallus acm C gene cluster are mutated and therefore are non-functional, their orthologues saacmM and saacmN in the S. antibioticus acm C gene cluster show no defects seemingly encoding active enzymes with functions specific for Acm X biosynthesis. Both acm biosynthetic gene clusters lack a kynurenine-3-monooxygenase gene necessary for biosynthesis of 3-hydroxy-4-methylanthranilic acid, the building block of the Acm chromophore, which suggests participation of a genome-encoded relevant monooxygenase during Acm biosynthesis in both S. chrysomallus and S

TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

Science.gov (United States)

Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

2017-12-01

Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. Supplementary data are available at

A Gene Cluster for Biosynthesis of Mannosylerythritol Lipids Consisted of 4-O-β-D-Mannopyranosyl-(2R,3S-Erythritol as the Sugar Moiety in a Basidiomycetous Yeast Pseudozyma tsukubaensis.

Directory of Open Access Journals (Sweden)

Azusa Saika

Full Text Available Mannosylerythritol lipids (MELs belong to the glycolipid biosurfactants and are produced by various fungi. The basidiomycetous yeast Pseudozyma tsukubaensis produces diastereomer type of MEL-B, which contains 4-O-β-D-mannopyranosyl-(2R,3S-erythritol (R-form as the sugar moiety. In this respect it differs from conventional type of MELs, which contain 4-O-β-D-mannopyranosyl-(2S,3R-erythritol (S-form as the sugar moiety. While the biosynthetic gene cluster for conventional type of MELs has been previously identified in Ustilago maydis and Pseudozyma antarctica, the genetic basis for MEL biosynthesis in P. tsukubaensis is unknown. Here, we identified a gene cluster involved in MEL biosynthesis in P. tsukubaensis. Among these genes, PtEMT1, which encodes erythritol/mannose transferase, had greater than 69% identity with homologs from strains in the genera Ustilago, Melanopsichium, Sporisorium and Pseudozyma. However, phylogenetic analysis placed PtEMT1p in a separate clade from the other proteins. To investigate the function of PtEMT1, we introduced the gene into a P. antarctica mutant strain, ΔPaEMT1, which lacks MEL biosynthesis ability owing to the deletion of PaEMT1. Using NMR spectroscopy, we identified the biosynthetic product as MEL-A with altered sugar conformation. These results indicate that PtEMT1p catalyzes the sugar conformation of MELs. This is the first report of a gene cluster for the biosynthesis of diastereomer type of MEL.

G-NEST: a gene neighborhood scoring tool to identify co-conserved, co-expressed genes

Directory of Open Access Journals (Sweden)

Lemay Danielle G

2012-09-01

Full Text Available Abstract Background In previous studies, gene neighborhoods—spatial clusters of co-expressed genes in the genome—have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Scoring Tool (G-NEST which combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all possible window sizes simultaneously. Results Using G-NEST on atlases of mouse and human tissue expression data, we found that large neighborhoods of ten or more genes are extremely rare in mammalian genomes. When they do occur, neighborhoods are typically composed of families of related genes. Both the highest scoring and the largest neighborhoods in mammalian genomes are formed by tandem gene duplication. Mammalian gene neighborhoods contain highly and variably expressed genes. Co-localized noisy gene pairs exhibit lower evolutionary conservation of their adjacent genome locations, suggesting that their shared transcriptional background may be disadvantageous. Genes that are essential to mammalian survival and reproduction are less likely to occur in neighborhoods, although neighborhoods are enriched with genes that function in mitosis. We also found that gene orientation and protein-protein interactions are partially responsible for maintenance of gene neighborhoods. Conclusions Our experiments using G-NEST confirm that tandem gene duplication is the primary driver of non-random gene order in mammalian genomes. Non-essentiality, co-functionality, gene orientation, and protein-protein interactions are additional forces that maintain gene neighborhoods, especially those formed by tandem duplicates. We expect G-NEST to be useful for other applications such as the identification of core regulatory modules, common transcriptional backgrounds, and chromatin domains. The

Genetic interrelations in the actinomycin biosynthetic gene clusters of Streptomyces antibioticus IMRU 3720 and Streptomyces chrysomallus ATCC11523, producers of actinomycin X and actinomycin C

Directory of Open Access Journals (Sweden)

Crnovčić I

2017-04-01

Full Text Available Ivana Crnovčić,1 Christian Rückert,2 Siamak Semsary,1 Manuel Lang,1 Jörn Kalinowski,2 Ullrich Keller1 1Institut für Chemie, Technische Universität Berlin, Berlin-Charlottenburg, 2Technology Platform Genomics, Center for Biotechnology, Bielefeld University, Bielefeld, Germany Abstract: Sequencing the actinomycin (acm biosynthetic gene cluster of Streptomyces antibioticus IMRU 3720, which produces actinomycin X (Acm X, revealed 20 genes organized into a highly similar framework as in the bi-armed acm C biosynthetic gene cluster of Streptomyces chrysomallus but without an attached additional extra arm of orthologues as in the latter. Curiously, the extra arm of the S. chrysomallus gene cluster turned out to perfectly match the single arm of the S. antibioticus gene cluster in the same order of orthologues including the the presence of two pseudogenes, scacmM and scacmN, encoding a cytochrome P450 and its ferredoxin, respectively. Orthologues of the latter genes were both missing in the principal arm of the S. chrysomallus acm C gene cluster. All orthologues of the extra arm showed a G +C-contents different from that of their counterparts in the principal arm. Moreover, the similarities of translation products from the extra arm were all higher to the corresponding translation products of orthologue genes from the S. antibioticus acm X gene cluster than to those encoded by the principal arm of their own gene cluster. This suggests that the duplicated structure of the S. chrysomallus acm C biosynthetic gene cluster evolved from previous fusion between two one-armed acm gene clusters each from a different genetic background. However, while scacmM and scacmN in the extra arm of the S. chrysomallus acm C gene cluster are mutated and therefore are non-functional, their orthologues saacmM and saacmN in the S. antibioticus acm C gene cluster show no defects seemingly encoding active enzymes with functions specific for Acm X biosynthesis. Both acm

Phylogeography of var gene repertoires reveals fine-scale geospatial clustering of Plasmodium falciparum populations in a highly endemic area.

Science.gov (United States)

Tessema, Sofonias K; Monk, Stephanie L; Schultz, Mark B; Tavul, Livingstone; Reeder, John C; Siba, Peter M; Mueller, Ivo; Barry, Alyssa E

2015-01-01

Plasmodium falciparum malaria is a major global health problem that is being targeted for progressive elimination. Knowledge of local disease transmission patterns in endemic countries is critical to these elimination efforts. To investigate fine-scale patterns of malaria transmission, we have compared repertoires of rapidly evolving var genes in a highly endemic area. A total of 3680 high-quality DBLα-sequences were obtained from 68 P. falciparum isolates from ten villages spread over two distinct catchment areas on the north coast of Papua New Guinea (PNG). Modelling of the extent of var gene diversity in the two parasite populations predicts more than twice as many var gene alleles circulating within each catchment (Mugil = 906; Wosera = 1094) than previously recognized in PNG (Amele = 369). In addition, there were limited levels of var gene sharing between populations, consistent with local parasite population structure. Phylogeographic analyses demonstrate that while neutrally evolving microsatellite markers identified population structure only at the catchment level, var gene repertoires reveal further fine-scale geospatial clustering of parasite isolates. The clustering of parasite isolates by village in Mugil, but not in Wosera was consistent with the physical and cultural isolation of the human populations in the two catchments. The study highlights the microheterogeneity of P. falciparum transmission in highly endemic areas and demonstrates the potential of var genes as markers of local patterns of parasite population structure. © 2014 John Wiley & Sons Ltd.

Heterologous Reconstitution of the Intact Geodin Gene Cluster in Aspergillus nidulans through a Simple and Versatile PCR Based Approach

DEFF Research Database (Denmark)

Nielsen, Morten Thrane; Nielsen, Jakob Blæsbjerg; Anyaogu, Dianna Chinyere

2013-01-01

was transferred in a two step procedure to an expression platform in A. nidulans. The individual cluster fragments were generated by PCR and assembled via efficient USER fusion prior to ransformation and integration via re-iterative gene targeting. A total of 13 open reading frames contained in 25 kb of DNA were...... of solid methodology for genetic manipulation of most species severely hampers pathway haracterization. Here we present a simple PCR based approach for heterologous reconstitution of intact gene clusters. Specifically, the putative gene cluster responsible for geodin production from Aspergillus terreus...... successfully transferred between the two species enabling geodin synthesis in A. nidulans. Subsequently, functions of three genes in the cluster were validated by genetic and chemical analyses. Specifically, ATEG_08451 (gedC) encodes a polyketide synthase, ATEG_08453 (gedR) encodes a transcription factor...

Comprehensive cluster analysis with Transitivity Clustering.

Science.gov (United States)

Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

2011-03-01

Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

Transcriptional interference networks coordinate the expression of functionally related genes clustered in the same genomic loci.

Science.gov (United States)

Boldogköi, Zsolt

2012-01-01

The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organization, transcription, various post-transcriptional processes, and translation. In this study, the Transcriptional Interference Network (TIN) hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighboring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronized cascade of gene expression in functionally linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular organisms too.

Transcriptional interference networks coordinate the expression of functionally-related genes clustered in the same genomic loci

Directory of Open Access Journals (Sweden)

Zsolt eBoldogkoi

2012-07-01

Full Text Available The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organisation, transcription, various post-transcriptional processes and translation. In this study, the Transcriptional Interference Network (TIN hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighbouring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally-linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly-arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely-oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronised cascade of gene expression in functionally-linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular

Gene expression analysis reveals new possible mechanisms of vancomycin-induced nephrotoxicity and identifies gene markers candidates.

Science.gov (United States)

Dieterich, Christine; Puey, Angela; Lin, Sylvia; Lyn, Sylvia; Swezey, Robert; Furimsky, Anna; Fairchild, David; Mirsalis, Jon C; Ng, Hanna H

2009-01-01

Vancomycin, one of few effective treatments against methicillin-resistant Staphylococcus aureus, is nephrotoxic. The goals of this study were to (1) gain insights into molecular mechanisms of nephrotoxicity at the genomic level, (2) evaluate gene markers of vancomycin-induced kidney injury, and (3) compare gene expression responses after iv and ip administration. Groups of six female BALB/c mice were treated with seven daily iv or ip doses of vancomycin (50, 200, and 400 mg/kg) or saline, and sacrificed on day 8. Clinical chemistry and histopathology demonstrated kidney injury at 400 mg/kg only. Hierarchical clustering analysis revealed that kidney gene expression profiles of all mice treated at 400 mg/kg clustered with those of mice administered 200 mg/kg iv. Transcriptional profiling might thus be more sensitive than current clinical markers for detecting kidney damage, though the profiles can differ with the route of administration. Analysis of transcripts whose expression was changed by at least twofold compared with vehicle saline after high iv and ip doses of vancomycin suggested the possibility of oxidative stress and mitochondrial damage in vancomycin-induced toxicity. In addition, our data showed changes in expression of several transcripts from the complement and inflammatory pathways. Such expression changes were confirmed by relative real-time reverse transcription-polymerase chain reaction. Finally, our results further substantiate the use of gene markers of kidney toxicity such as KIM-1/Havcr1, as indicators of renal injury.

Identifying resistance gene analogs associated with resistances to different pathogens in common bean.

Science.gov (United States)

López, Camilo E; Acosta, Iván F; Jara, Carlos; Pedraza, Fabio; Gaitán-Solís, Eliana; Gallego, Gerardo; Beebe, Steve; Tohme, Joe

2003-01-01

ABSTRACT A polymerase chain reaction approach using degenerate primers that targeted the conserved domains of cloned plant disease resistance genes (R genes) was used to isolate a set of 15 resistance gene analogs (RGAs) from common bean (Phaseolus vulgaris). Eight different classes of RGAs were obtained from nucleotide binding site (NBS)-based primers and seven from not previously described Toll/Interleukin-1 receptor-like (TIR)-based primers. Putative amino acid sequences of RGAs were significantly similar to R genes and contained additional conserved motifs. The NBS-type RGAs were classified in two subgroups according to the expected final residue in the kinase-2 motif. Eleven RGAs were mapped at 19 loci on eight linkage groups of the common bean genetic map constructed at Centro Internacional de Agricultura Tropical. Genetic linkage was shown for eight RGAs with partial resistance to anthracnose, angular leaf spot (ALS) and Bean golden yellow mosaic virus (BGYMV). RGA1 and RGA2 were associated with resistance loci to anthracnose and BGYMV and were part of two clusters of R genes previously described. A new major cluster was detected by RGA7 and explained up to 63.9% of resistance to ALS and has a putative contribution to anthracnose resistance. These results show the usefulness of RGAs as candidate genes to detect and eventually isolate numerous R genes in common bean.

A Cluster of Five Genes Essential for the Utilization of Dihydroxamate Xenosiderophores in Synechocystis sp. PCC 6803.

Science.gov (United States)

Obando S, Tobias A; Babykin, Michael M; Zinchenko, Vladislav V

2018-05-21

The unicellular freshwater cyanobacterium Synechocystis sp. PCC 6803 is capable of using dihydroxamate xenosiderophores, either ferric schizokinen (FeSK) or a siderophore of the filamentous cyanobacterium Anabaena variabilis ATCC 29413 (SAV), as the sole source of iron in the TonB-dependent manner. The fecCDEB1-schT gene cluster encoding a siderophore transport system that is involved in the utilization of FeSK and SAV in Synechocystis sp. PCC 6803 was identified. The gene schT encodes TonB-dependent outer membrane transporter, whereas the remaining four genes encode the ABC-type transporter FecB1CDE formed by the periplasmic binding protein FecB1, the transmembrane permease proteins FecC and FecD, and the ATPase FecE. Inactivation of any of these genes resulted in the inability of cells to utilize FeSK and SAV. Our data strongly suggest that Synechocystis sp. PCC 6803 can readily internalize Fe-siderophores via the classic TonB-dependent transport system.

A cluster merging method for time series microarray with production values.

Science.gov (United States)

Chira, Camelia; Sedano, Javier; Camara, Monica; Prieto, Carlos; Villar, Jose R; Corchado, Emilio

2014-09-01

A challenging task in time-course microarray data analysis is to cluster genes meaningfully combining the information provided by multiple replicates covering the same key time points. This paper proposes a novel cluster merging method to accomplish this goal obtaining groups with highly correlated genes. The main idea behind the proposed method is to generate a clustering starting from groups created based on individual temporal series (representing different biological replicates measured in the same time points) and merging them by taking into account the frequency by which two genes are assembled together in each clustering. The gene groups at the level of individual time series are generated using several shape-based clustering methods. This study is focused on a real-world time series microarray task with the aim to find co-expressed genes related to the production and growth of a certain bacteria. The shape-based clustering methods used at the level of individual time series rely on identifying similar gene expression patterns over time which, in some models, are further matched to the pattern of production/growth. The proposed cluster merging method is able to produce meaningful gene groups which can be naturally ranked by the level of agreement on the clustering among individual time series. The list of clusters and genes is further sorted based on the information correlation coefficient and new problem-specific relevant measures. Computational experiments and results of the cluster merging method are analyzed from a biological perspective and further compared with the clustering generated based on the mean value of time series and the same shape-based algorithm.

GOClonto: an ontological clustering approach for conceptualizing PubMed abstracts.

Science.gov (United States)

Zheng, Hai-Tao; Borchert, Charles; Kim, Hong-Gee

2010-02-01

Concurrent with progress in biomedical sciences, an overwhelming of textual knowledge is accumulating in the biomedical literature. PubMed is the most comprehensive database collecting and managing biomedical literature. To help researchers easily understand collections of PubMed abstracts, numerous clustering methods have been proposed to group similar abstracts based on their shared features. However, most of these methods do not explore the semantic relationships among groupings of documents, which could help better illuminate the groupings of PubMed abstracts. To address this issue, we proposed an ontological clustering method called GOClonto for conceptualizing PubMed abstracts. GOClonto uses latent semantic analysis (LSA) and gene ontology (GO) to identify key gene-related concepts and their relationships as well as allocate PubMed abstracts based on these key gene-related concepts. Based on two PubMed abstract collections, the experimental results show that GOClonto is able to identify key gene-related concepts and outperforms the STC (suffix tree clustering) algorithm, the Lingo algorithm, the Fuzzy Ants algorithm, and the clustering based TRS (tolerance rough set) algorithm. Moreover, the two ontologies generated by GOClonto show significant informative conceptual structures.

Structure and gene cluster of the O-antigen of Escherichia coli O54.

Science.gov (United States)

Naumenko, Olesya I; Guo, Xi; Senchenkova, Sof'ya N; Geng, Peng; Perepelov, Andrei V; Shashkov, Alexander S; Liu, Bin; Knirel, Yuriy A

2018-06-15

Mild acid hydrolysis of the lipopolysaccharide of Escherichia coli O54 afforded an O-polysaccharide, which was studied by sugar analysis, solvolysis with anhydrous trifluoroacetic acid, and 1 H and 13 C NMR spectroscopy. Solvolysis cleaved predominantly the linkage of β-d-Ribf and, to a lesser extent, that of β-d-GlcpNAc, whereas the other linkages, including the linkage of α-l-Rhap, were stable under selected conditions (40 °C, 5 h). The following structure of the O-polysaccharide was established: →4)-α-d-GalpA-(1 → 2)-α-l-Rhap-(1 → 2)-β-d-Ribf-(1 → 4)-β-d-Galp-(1 → 3)-β-d-GlcpNAc-(1→ The O-antigen gene cluster of E. coli O54 was analyzed and found to be consistent in general with the O-polysaccharide structure established but there were two exceptions: i) in the cluster, there were genes for phosphoserine phosphatase and serine transferase, which have no apparent role in the O-polysaccharide synthesis, and ii) no ribofuranosyltransferase gene was present in the cluster. Both uncommon features are shared by some other enteric bacteria. Copyright © 2018 Elsevier Ltd. All rights reserved.

An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

Science.gov (United States)

Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

2017-04-12

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

Mutation of the RDR1 gene caused genome-wide changes in gene expression, regional variation in small RNA clusters and localized alteration in DNA methylation in rice.

Science.gov (United States)

Wang, Ningning; Zhang, Di; Wang, Zhenhui; Xun, Hongwei; Ma, Jian; Wang, Hui; Huang, Wei; Liu, Ying; Lin, Xiuyun; Li, Ning; Ou, Xiufang; Zhang, Chunyu; Wang, Ming-Bo; Liu, Bao

2014-06-30

Endogenous small (sm) RNAs (primarily si- and miRNAs) are important trans/cis-acting regulators involved in diverse cellular functions. In plants, the RNA-dependent RNA polymerases (RDRs) are essential for smRNA biogenesis. It has been established that RDR2 is involved in the 24 nt siRNA-dependent RNA-directed DNA methylation (RdDM) pathway. Recent studies have suggested that RDR1 is involved in a second RdDM pathway that relies mostly on 21 nt smRNAs and functions to silence a subset of genomic loci that are usually refractory to the normal RdDM pathway in Arabidopsis. Whether and to what extent the homologs of RDR1 may have similar functions in other plants remained unknown. We characterized a loss-of-function mutant (Osrdr1) of the OsRDR1 gene in rice (Oryza sativa L.) derived from a retrotransposon Tos17 insertion. Microarray analysis identified 1,175 differentially expressed genes (5.2% of all expressed genes in the shoot-tip tissue of rice) between Osrdr1 and WT, of which 896 and 279 genes were up- and down-regulated, respectively, in Osrdr1. smRNA sequencing revealed regional alterations in smRNA clusters across the rice genome. Some of the regions with altered smRNA clusters were associated with changes in DNA methylation. In addition, altered expression of several miRNAs was detected in Osrdr1, and at least some of which were associated with altered expression of predicted miRNA target genes. Despite these changes, no phenotypic difference was identified in Osrdr1 relative to WT under normal condition; however, ephemeral phenotypic fluctuations occurred under some abiotic stress conditions. Our results showed that OsRDR1 plays a role in regulating a substantial number of endogenous genes with diverse functions in rice through smRNA-mediated pathways involving DNA methylation, and which participates in abiotic stress response.

Epidemiological analysis of Salmonella clusters identified by whole genome sequencing, England and Wales 2014.

Science.gov (United States)

Waldram, Alison; Dolan, Gayle; Ashton, Philip M; Jenkins, Claire; Dallman, Timothy J

2018-05-01

The unprecedented level of bacterial strain discrimination provided by whole genome sequencing (WGS) presents new challenges with respect to the utility and interpretation of the data. Whole genome sequences from 1445 isolates of Salmonella belonging to the most commonly identified serotypes in England and Wales isolated between April and August 2014 were analysed. Single linkage single nucleotide polymorphism thresholds at the 10, 5 and 0 level were explored for evidence of epidemiological links between clustered cases. Analysis of the WGS data organised 566 of the 1445 isolates into 32 clusters of five or more. A statistically significant epidemiological link was identified for 17 clusters. The clusters were associated with foreign travel (n = 8), consumption of Chinese takeaways (n = 4), chicken eaten at home (n = 2), and one each of the following; eating out, contact with another case in the home and contact with reptiles. In the same time frame, one cluster was detected using traditional outbreak detection methods. WGS can be used for the highly specific and highly sensitive detection of biologically related isolates when epidemiological links are obscured. Improvements in the collection of detailed, standardised exposure information would enhance cluster investigations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cloning and Characterization of the Polyether Salinomycin Biosynthesis Gene Cluster of Streptomyces albus XM211

Science.gov (United States)

Jiang, Chunyan; Wang, Hougen; Kang, Qianjin; Liu, Jing

2012-01-01

Salinomycin is widely used in animal husbandry as a food additive due to its antibacterial and anticoccidial activities. However, its biosynthesis had only been studied by feeding experiments with isotope-labeled precursors. A strategy with degenerate primers based on the polyether-specific epoxidase sequences was successfully developed to clone the salinomycin gene cluster. Using this strategy, a putative epoxidase gene, slnC, was cloned from the salinomycin producer Streptomyces albus XM211. The targeted replacement of slnC and subsequent trans-complementation proved its involvement in salinomycin biosynthesis. A 127-kb DNA region containing slnC was sequenced, including genes for polyketide assembly and release, oxidative cyclization, modification, export, and regulation. In order to gain insight into the salinomycin biosynthesis mechanism, 13 gene replacements and deletions were conducted. Including slnC, 7 genes were identified as essential for salinomycin biosynthesis and putatively responsible for polyketide chain release, oxidative cyclization, modification, and regulation. Moreover, 6 genes were found to be relevant to salinomycin biosynthesis and possibly involved in precursor supply, removal of aberrant extender units, and regulation. Sequence analysis and a series of gene replacements suggest a proposed pathway for the biosynthesis of salinomycin. The information presented here expands the understanding of polyether biosynthesis mechanisms and paves the way for targeted engineering of salinomycin activity and productivity. PMID:22156425

ENU Mutagenesis in Mice Identifies Candidate Genes For Hypogonadism

Science.gov (United States)

Weiss, Jeffrey; Hurley, Lisa A.; Harris, Rebecca M.; Finlayson, Courtney; Tong, Minghan; Fisher, Lisa A.; Moran, Jennifer L.; Beier, David R.; Mason, Christopher; Jameson, J. Larry

2012-01-01

Genome-wide mutagenesis was performed in mice to identify candidate genes for male infertility, for which the predominant causes remain idiopathic. Mice were mutagenized using N-ethyl-N-nitrosourea (ENU), bred, and screened for phenotypes associated with the male urogenital system. Fifteen heritable lines were isolated and chromosomal loci were assigned using low density genome-wide SNP arrays. Ten of the fifteen lines were pursued further using higher resolution SNP analysis to narrow the candidate gene regions. Exon sequencing of candidate genes identified mutations in mice with cystic kidneys (Bicc1), cryptorchidism (Rxfp2), restricted germ cell deficiency (Plk4), and severe germ cell deficiency (Prdm9). In two other lines with severe hypogonadism candidate sequencing failed to identify mutations, suggesting defects in genes with previously undocumented roles in gonadal function. These genomic intervals were sequenced in their entirety and a candidate mutation was identified in SnrpE in one of the two lines. The line harboring the SnrpE variant retains substantial spermatogenesis despite small testis size, an unusual phenotype. In addition to the reproductive defects, heritable phenotypes were observed in mice with ataxia (Myo5a), tremors (Pmp22), growth retardation (unknown gene), and hydrocephalus (unknown gene). These results demonstrate that the ENU screen is an effective tool for identifying potential causes of male infertility. PMID:22258617

Identifying multiple influential spreaders by a heuristic clustering algorithm

International Nuclear Information System (INIS)

Bao, Zhong-Kui; Liu, Jian-Guo; Zhang, Hai-Feng

2017-01-01

The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very “negligible”. Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant. - Highlights: • A heuristic clustering algorithm is proposed to identify the multiple influential spreaders in complex networks. • The algorithm can not only guarantee the selected spreaders are sufficiently scattered but also avoid to be “insignificant”. • The performance of our algorithm is generally better than other methods, regardless of real networks or synthetic networks.

Identifying multiple influential spreaders by a heuristic clustering algorithm

Energy Technology Data Exchange (ETDEWEB)

Bao, Zhong-Kui [School of Mathematical Science, Anhui University, Hefei 230601 (China); Liu, Jian-Guo [Data Science and Cloud Service Research Center, Shanghai University of Finance and Economics, Shanghai, 200133 (China); Zhang, Hai-Feng, E-mail: haifengzhang1978@gmail.com [School of Mathematical Science, Anhui University, Hefei 230601 (China); Department of Communication Engineering, North University of China, Taiyuan, Shan' xi 030051 (China)

2017-03-18

The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very “negligible”. Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant. - Highlights: • A heuristic clustering algorithm is proposed to identify the multiple influential spreaders in complex networks. • The algorithm can not only guarantee the selected spreaders are sufficiently scattered but also avoid to be “insignificant”. • The performance of our algorithm is generally better than other methods, regardless of real networks or synthetic networks.

Characterization of the fumonisin B2 biosynthetic gene cluster in Aspergillus niger and A. awamori.

Science.gov (United States)

Aspergillus niger and A. awamori strains isolated from grapes cultivated in Mediterranean basin were examined for fumonisin B2 (FB2) production and presence/absence of sequences within the fumonisin biosynthetic gene (fum) cluster. Presence of 13 regions in the fum cluster was evaluated by PCR assay...

Extensive polycistronism and antisense transcription in the mammalian Hox clusters.

Directory of Open Access Journals (Sweden)

Gaëll Mainguy

Full Text Available The Hox clusters play a crucial role in body patterning during animal development. They encode both Hox transcription factor and micro-RNA genes that are activated in a precise temporal and spatial sequence that follows their chromosomal order. These remarkable collinear properties confer functional unit status for Hox clusters. We developed the TranscriptView platform to establish high resolution transcriptional profiling and report here that transcription in the Hox clusters is far more complex than previously described in both human and mouse. Unannotated transcripts can represent up to 60% of the total transcriptional output of a cluster. In particular, we identified 14 non-coding Transcriptional Units antisense to Hox genes, 10 of which (70% have a detectable mouse homolog. Most of these Transcriptional Units in both human and mouse present conserved sizeable sequences (>40 bp overlapping Hox transcripts, suggesting that these Hox antisense transcripts are functional. Hox clusters also display at least seven polycistronic clusters, i.e., different genes being co-transcribed on long isoforms (up to 30 kb. This work provides a reevaluated framework for understanding Hox gene function and dys-function. Such extensive transcriptions may provide a structural explanation for Hox clustering.

Clustering of transcriptional profiles identifies changes to insulin signaling as an early event in a mouse model of Alzheimer's disease.

Science.gov (United States)

Jackson, Harriet M; Soto, Ileana; Graham, Leah C; Carter, Gregory W; Howell, Gareth R

2013-11-25

Alzheimer's disease affects more than 35 million people worldwide but there is no known cure. Age is the strongest risk factor for Alzheimer's disease but it is not clear how age-related changes impact the disease. Here, we used a mouse model of Alzheimer's disease to identify age-specific changes that occur prior to and at the onset of traditional Alzheimer-related phenotypes including amyloid plaque formation. To identify these early events we used transcriptional profiling of mouse brains combined with computational approaches including singular value decomposition and hierarchical clustering. Our study identifies three key events in early stages of Alzheimer's disease. First, the most important drivers of Alzheimer's disease onset in these mice are age-specific changes. These include perturbations of the ribosome and oxidative phosphorylation pathways. Second, the earliest detectable disease-specific changes occur to genes commonly associated with the hypothalamic-adrenal-pituitary (HPA) axis. These include the down-regulation of genes relating to metabolism, depression and appetite. Finally, insulin signaling, in particular the down-regulation of the insulin receptor substrate 4 (Irs4) gene, may be an important event in the transition from age-related changes to Alzheimer's disease specific-changes. A combination of transcriptional profiling combined with computational analyses has uncovered novel features relevant to Alzheimer's disease in a widely used mouse model and offers avenues for further exploration into early stages of AD.

Two different secondary metabolism gene clusters occupied the same ancestral locus in fungal dermatophytes of the arthrodermataceae.

Science.gov (United States)

Zhang, Han; Rokas, Antonis; Slot, Jason C

2012-01-01

Dermatophyte fungi of the family Arthrodermataceae (Eurotiomycetes) colonize keratinized tissue, such as skin, frequently causing superficial mycoses in humans and other mammals, reptiles, and birds. Competition with native microflora likely underlies the propensity of these dermatophytes to produce a diversity of antibiotics and compounds for scavenging iron, which is extremely scarce, as well as the presence of an unusually large number of putative secondary metabolism gene clusters, most of which contain non-ribosomal peptide synthetases (NRPS), in their genomes. To better understand the historical origins and diversification of NRPS-containing gene clusters we examined the evolution of a variable locus (VL) that exists in one of three alternative conformations among the genomes of seven dermatophyte species. The first conformation of the VL (termed VLA) contains only 539 base pairs of sequence and lacks protein-coding genes, whereas the other two conformations (termed VLB and VLC) span 36 Kb and 27 Kb and contain 12 and 10 genes, respectively. Interestingly, both VLB and VLC appear to contain distinct secondary metabolism gene clusters; VLB contains a NRPS gene as well as four porphyrin metabolism genes never found to be physically linked in the genomes of 128 other fungal species, whereas VLC also contains a NRPS gene as well as several others typically found associated with secondary metabolism gene clusters. Phylogenetic evidence suggests that the VL locus was present in the ancestor of all seven species achieving its present distribution through subsequent differential losses or retentions of specific conformations. We propose that the existence of variable loci, similar to the one we studied, in fungal genomes could potentially explain the dramatic differences in secondary metabolic diversity between closely related species of filamentous fungi, and contribute to host adaptation and the generation of metabolic diversity.

Identification and Analysis of a Novel Gene Cluster Involves in Fe2+ Oxidation in Acidithiobacillus ferrooxidans ATCC 23270, a Typical Biomining Acidophile.

Science.gov (United States)

Ai, Chenbing; Liang, Yuting; Miao, Bo; Chen, Miao; Zeng, Weimin; Qiu, Guanzhou

2018-07-01

Iron-oxidizing Acidithiobacillus spp. are applied worldwide in biomining industry to extract metals from sulfide minerals. They derive energy for survival through Fe 2+ oxidation and generate Fe 3+ for the dissolution of sulfide minerals. However, molecular mechanisms of their iron oxidation still remain elusive. A novel two-cytochrome-encoding gene cluster (named tce gene cluster) encoding a high-molecular-weight cytochrome c (AFE_1428) and a c 4 -type cytochrome c 552 (AFE_1429) in A. ferrooxidans ATCC 23270 was first identified in this study. Bioinformatic analysis together with transcriptional study showed that AFE_1428 and AFE_1429 were the corresponding paralog of Cyc2 (AFE_3153) and Cyc1 (AFE_3152) which were encoded by the extensively studied rus operon and had been proven involving in ferrous iron oxidation. Both AFE_1428 and AFE_1429 contained signal peptide and the classic heme-binding motif(s) as their corresponding paralog. The modeled structure of AFE_1429 showed high resemblance to Cyc1. AFE_1428 and AFE_1429 were preferentially transcribed as their corresponding paralogs in the presence of ferrous iron as sole energy source as compared with sulfur. The tce gene cluster is highly conserved in the genomes of four phylogenetic-related A. ferrooxidans strains that were originally isolated from different sites separated with huge geographical distance, which further implies the importance of this gene cluster. Collectively, AFE_1428 and AFE_1429 involve in Fe 2+ oxidation like their corresponding paralog by integrating with the metalloproteins encoded by rus operon. This study provides novel insights into the Fe 2+ oxidation mechanism in Fe 2+ -oxidizing A. ferrooxidans ssp.

Analysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level.

Directory of Open Access Journals (Sweden)

Andrew R Dalby

Full Text Available Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that sub-classes were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC.

Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

Directory of Open Access Journals (Sweden)

Bing Jiang

2017-01-01

Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

Back to the sea twice: identifying candidate plant genes for molecular evolution to marine life

Directory of Open Access Journals (Sweden)

Reusch Thorsten BH

2011-01-01

Full Text Available Abstract Background Seagrasses are a polyphyletic group of monocotyledonous angiosperms that have adapted to a completely submerged lifestyle in marine waters. Here, we exploit two collections of expressed sequence tags (ESTs of two wide-spread and ecologically important seagrass species, the Mediterranean seagrass Posidonia oceanica (L. Delile and the eelgrass Zostera marina L., which have independently evolved from aquatic ancestors. This replicated, yet independent evolutionary history facilitates the identification of traits that may have evolved in parallel and are possible instrumental candidates for adaptation to a marine habitat. Results In our study, we provide the first quantitative perspective on molecular adaptations in two seagrass species. By constructing orthologous gene clusters shared between two seagrasses (Z. marina and P. oceanica and eight distantly related terrestrial angiosperm species, 51 genes could be identified with detection of positive selection along the seagrass branches of the phylogenetic tree. Characterization of these positively selected genes using KEGG pathways and the Gene Ontology uncovered that these genes are mostly involved in translation, metabolism, and photosynthesis. Conclusions These results provide first insights into which seagrass genes have diverged from their terrestrial counterparts via an initial aquatic stage characteristic of the order and to the derived fully-marine stage characteristic of seagrasses. We discuss how adaptive changes in these processes may have contributed to the evolution towards an aquatic and marine existence.

Back to the sea twice: identifying candidate plant genes for molecular evolution to marine life.

Science.gov (United States)

Wissler, Lothar; Codoñer, Francisco M; Gu, Jenny; Reusch, Thorsten B H; Olsen, Jeanine L; Procaccini, Gabriele; Bornberg-Bauer, Erich

2011-01-12

Seagrasses are a polyphyletic group of monocotyledonous angiosperms that have adapted to a completely submerged lifestyle in marine waters. Here, we exploit two collections of expressed sequence tags (ESTs) of two wide-spread and ecologically important seagrass species, the Mediterranean seagrass Posidonia oceanica (L.) Delile and the eelgrass Zostera marina L., which have independently evolved from aquatic ancestors. This replicated, yet independent evolutionary history facilitates the identification of traits that may have evolved in parallel and are possible instrumental candidates for adaptation to a marine habitat. In our study, we provide the first quantitative perspective on molecular adaptations in two seagrass species. By constructing orthologous gene clusters shared between two seagrasses (Z. marina and P. oceanica) and eight distantly related terrestrial angiosperm species, 51 genes could be identified with detection of positive selection along the seagrass branches of the phylogenetic tree. Characterization of these positively selected genes using KEGG pathways and the Gene Ontology uncovered that these genes are mostly involved in translation, metabolism, and photosynthesis. These results provide first insights into which seagrass genes have diverged from their terrestrial counterparts via an initial aquatic stage characteristic of the order and to the derived fully-marine stage characteristic of seagrasses. We discuss how adaptive changes in these processes may have contributed to the evolution towards an aquatic and marine existence.

Heterologous reconstitution of the intact geodin gene cluster in Aspergillus nidulans through a simple and versatile PCR based approach.

Directory of Open Access Journals (Sweden)

Morten Thrane Nielsen

Full Text Available Fungal natural products are a rich resource for bioactive molecules. To fully exploit this potential it is necessary to link genes to metabolites. Genetic information for numerous putative biosynthetic pathways has become available in recent years through genome sequencing. However, the lack of solid methodology for genetic manipulation of most species severely hampers pathway characterization. Here we present a simple PCR based approach for heterologous reconstitution of intact gene clusters. Specifically, the putative gene cluster responsible for geodin production from Aspergillus terreus was transferred in a two step procedure to an expression platform in A. nidulans. The individual cluster fragments were generated by PCR and assembled via efficient USER fusion prior to transformation and integration via re-iterative gene targeting. A total of 13 open reading frames contained in 25 kb of DNA were successfully transferred between the two species enabling geodin synthesis in A. nidulans. Subsequently, functions of three genes in the cluster were validated by genetic and chemical analyses. Specifically, ATEG_08451 (gedC encodes a polyketide synthase, ATEG_08453 (gedR encodes a transcription factor responsible for activation of the geodin gene cluster and ATEG_08460 (gedL encodes a halogenase that catalyzes conversion of sulochrin to dihydrogeodin. We expect that our approach for transferring intact biosynthetic pathways to a fungus with a well developed genetic toolbox will be instrumental in characterizing the many exciting pathways for secondary metabolite production that are currently being uncovered by the fungal genome sequencing projects.

Early and long-standing rheumatoid arthritis: distinct molecular signatures identified by gene-expression profiling in synovia

Science.gov (United States)

Lequerré, Thierry; Bansard, Carine; Vittecoq, Olivier; Derambure, Céline; Hiron, Martine; Daveau, Maryvonne; Tron, François; Ayral, Xavier; Biga, Norman; Auquit-Auckbur, Isabelle; Chiocchia, Gilles; Le Loët, Xavier; Salier, Jean-Philippe

2009-01-01

Introduction Rheumatoid arthritis (RA) is a heterogeneous disease and its underlying molecular mechanisms are still poorly understood. Because previous microarray studies have only focused on long-standing (LS) RA compared to osteoarthritis, we aimed to compare the molecular profiles of early and LS RA versus control synovia. Methods Synovial biopsies were obtained by arthroscopy from 15 patients (4 early untreated RA, 4 treated LS RA and 7 controls, who had traumatic or mechanical lesions). Extracted mRNAs were used for large-scale gene-expression profiling. The different gene-expression combinations identified by comparison of profiles of early, LS RA and healthy synovia were linked to the biological processes involved in each situation. Results Three combinations of 719, 116 and 52 transcripts discriminated, respectively, early from LS RA, and early or LS RA from healthy synovia. We identified several gene clusters and distinct molecular signatures specifically expressed during early or LS RA, thereby suggesting the involvement of different pathophysiological mechanisms during the course of RA. Conclusions Early and LS RA have distinct molecular signatures with different biological processes participating at different times during the course of the disease. These results suggest that better knowledge of the main biological processes involved at a given RA stage might help to choose the most appropriate treatment. PMID:19563633

Variations in CCL3L gene cluster sequence and non-specific gene copy numbers

Directory of Open Access Journals (Sweden)

Edberg Jeffrey C

2010-03-01

Full Text Available Abstract Background Copy number variations (CNVs of the gene CC chemokine ligand 3-like1 (CCL3L1 have been implicated in HIV-1 susceptibility, but the association has been inconsistent. CCL3L1 shares homology with a cluster of genes localized to chromosome 17q12, namely CCL3, CCL3L2, and, CCL3L3. These genes are involved in host defense and inflammatory processes. Several CNV assays have been developed for the CCL3L1 gene. Findings Through pairwise and multiple alignments of these genes, we have shown that the homology between these genes ranges from 50% to 99% in complete gene sequences and from 70-100% in the exonic regions, with CCL3L1 and CCL3L3 being identical. By use of MEGA 4 and BioEdit, we aligned sense primers, anti-sense primers, and probes used in several previously described assays against pre-multiple alignments of all four chemokine genes. Each set of probes and primers aligned and matched with overlapping sequences in at least two of the four genes, indicating that previously utilized RT-PCR based CNV assays are not specific for only CCL3L1. The four available assays measured median copies of 2 and 3-4 in European and African American, respectively. The concordance between the assays ranged from 0.44-0.83 suggesting individual discordant calls and inconsistencies with the assays from the expected gene coverage from the known sequence. Conclusions This indicates that some of the inconsistencies in the association studies could be due to assays that provide heterogenous results. Sequence information to determine CNV of the three genes separately would allow to test whether their association with the pathogenesis of a human disease or phenotype is affected by an individual gene or by a combination of these genes.

Contribution of the Pmra Promoter to Expression of Genes in the Escherichia coli mra Cluster of Cell Envelope Biosynthesis and Cell Division Genes

Science.gov (United States)

Mengin-Lecreulx, Dominique; Ayala, Juan; Bouhss, Ahmed; van Heijenoort, Jean; Parquet, Claudine; Hara, Hiroshi

1998-01-01

Recently, a promoter for the essential gene ftsI, which encodes penicillin-binding protein 3 of Escherichia coli, was precisely localized 1.9 kb upstream from this gene, at the beginning of the mra cluster of cell division and cell envelope biosynthesis genes (H. Hara, S. Yasuda, K. Horiuchi, and J. T. Park, J. Bacteriol. 179:5802–5811, 1997). Disruption of this promoter (Pmra) on the chromosome and its replacement by the lac promoter (Pmra::Plac) led to isopropyl-β-d-thiogalactopyranoside (IPTG)-dependent cells that lysed in the absence of inducer, a defect which was complemented only when the whole region from Pmra to ftsW, the fifth gene downstream from ftsI, was provided in trans on a plasmid. In the present work, the levels of various proteins involved in peptidoglycan synthesis and cell division were precisely determined in cells in which Pmra::Plac promoter expression was repressed or fully induced. It was confirmed that the Pmra promoter is required for expression of the first nine genes of the mra cluster: mraZ (orfC), mraW (orfB), ftsL (mraR), ftsI, murE, murF, mraY, murD, and ftsW. Interestingly, three- to sixfold-decreased levels of MurG and MurC enzymes were observed in uninduced Pmra::Plac cells. This was correlated with an accumulation of the nucleotide precursors UDP–N-acetylglucosamine and UDP–N-acetylmuramic acid, substrates of these enzymes, and with a depletion of the pool of UDP–N-acetylmuramyl pentapeptide, resulting in decreased cell wall peptidoglycan synthesis. Moreover, the expression of ftsZ, the penultimate gene from this cluster, was significantly reduced when Pmra expression was repressed. It was concluded that the transcription of the genes located downstream from ftsW in the mra cluster, from murG to ftsZ, is also mainly (but not exclusively) dependent on the Pmra promoter. PMID:9721276

De Novo assembly of the Japanese flounder (Paralichthys olivaceus spleen transcriptome to identify putative genes involved in immunity.

Directory of Open Access Journals (Sweden)

Lin Huang

Full Text Available Japanese flounder (Paralichthys olivaceus is an economically important marine fish in Asia and has suffered from disease outbreaks caused by various pathogens, which requires more information for immune relevant genes on genome background. However, genomic and transcriptomic data for Japanese flounder remain scarce, which limits studies on the immune system of this species. In this study, we characterized the Japanese flounder spleen transcriptome using an Illumina paired-end sequencing platform to identify putative genes involved in immunity.A cDNA library from the spleen of P. olivaceus was constructed and randomly sequenced using an Illumina technique. The removal of low quality reads generated 12,196,968 trimmed reads, which assembled into 96,627 unigenes. A total of 21,391 unigenes (22.14% were annotated in the NCBI Nr database, and only 1.1% of the BLASTx top-hits matched P. olivaceus protein sequences. Approximately 12,503 (58.45% unigenes were categorized into three Gene Ontology groups, 19,547 (91.38% were classified into 26 Cluster of Orthologous Groups, and 10,649 (49.78% were assigned to six Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, 40,928 putative simple sequence repeats and 47, 362 putative single nucleotide polymorphisms were identified. Importantly, we identified 1,563 putative immune-associated unigenes that mapped to 15 immune signaling pathways.The P. olivaceus transciptome data provides a rich source to discover and identify new genes, and the immune-relevant sequences identified here will facilitate our understanding of the mechanisms involved in the immune response. Furthermore, the plentiful potential SSRs and SNPs found in this study are important resources with respect to future development of a linkage map or marker assisted breeding programs for the flounder.

Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in Linum usitatissimum identified genes with varied expression patterns

Science.gov (United States)

2012-01-01

Background The glycosylation process, catalyzed by ubiquitous glycosyltransferase (GT) family enzymes, is a prevalent modification of plant secondary metabolites that regulates various functions such as hormone homeostasis, detoxification of xenobiotics and biosynthesis and storage of secondary metabolites. Flax (Linum usitatissimum L.) is a commercially grown oilseed crop, important because of its essential fatty acids and health promoting lignans. Identification and characterization of UDP glycosyltransferase (UGT) genes from flax could provide valuable basic information about this important gene family and help to explain the seed specific glycosylated metabolite accumulation and other processes in plants. Plant genome sequencing projects are useful to discover complexity within this gene family and also pave way for the development of functional genomics approaches. Results Taking advantage of the newly assembled draft genome sequence of flax, we identified 137 UDP glycosyltransferase (UGT) genes from flax using a conserved signature motif. Phylogenetic analysis of these protein sequences clustered them into 14 major groups (A-N). Expression patterns of these genes were investigated using publicly available expressed sequence tag (EST), microarray data and reverse transcription quantitative real time PCR (RT-qPCR). Seventy-three per cent of these genes (100 out of 137) showed expression evidence in 15 tissues examined and indicated varied expression profiles. The RT-qPCR results of 10 selected genes were also coherent with the digital expression analysis. Interestingly, five duplicated UGT genes were identified, which showed differential expression in various tissues. Of the seven intron loss/gain positions detected, two intron positions were conserved among most of the UGTs, although a clear relationship about the evolution of these genes could not be established. Comparison of the flax UGTs with orthologs from four other sequenced dicot genomes indicated that

Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in Linum usitatissimum identified genes with varied expression patterns

Directory of Open Access Journals (Sweden)

Barvkar Vitthal T

2012-05-01

Full Text Available Abstract Background The glycosylation process, catalyzed by ubiquitous glycosyltransferase (GT family enzymes, is a prevalent modification of plant secondary metabolites that regulates various functions such as hormone homeostasis, detoxification of xenobiotics and biosynthesis and storage of secondary metabolites. Flax (Linum usitatissimum L. is a commercially grown oilseed crop, important because of its essential fatty acids and health promoting lignans. Identification and characterization of UDP glycosyltransferase (UGT genes from flax could provide valuable basic information about this important gene family and help to explain the seed specific glycosylated metabolite accumulation and other processes in plants. Plant genome sequencing projects are useful to discover complexity within this gene family and also pave way for the development of functional genomics approaches. Results Taking advantage of the newly assembled draft genome sequence of flax, we identified 137 UDP glycosyltransferase (UGT genes from flax using a conserved signature motif. Phylogenetic analysis of these protein sequences clustered them into 14 major groups (A-N. Expression patterns of these genes were investigated using publicly available expressed sequence tag (EST, microarray data and reverse transcription quantitative real time PCR (RT-qPCR. Seventy-three per cent of these genes (100 out of 137 showed expression evidence in 15 tissues examined and indicated varied expression profiles. The RT-qPCR results of 10 selected genes were also coherent with the digital expression analysis. Interestingly, five duplicated UGT genes were identified, which showed differential expression in various tissues. Of the seven intron loss/gain positions detected, two intron positions were conserved among most of the UGTs, although a clear relationship about the evolution of these genes could not be established. Comparison of the flax UGTs with orthologs from four other sequenced dicot

Progeny Clustering: A Method to Identify Biological Phenotypes

Science.gov (United States)

Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

2015-01-01

Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

An elm EST database for identifying leaf beetle egg-induced defense genes

Directory of Open Access Journals (Sweden)

Büchel Kerstin

2012-06-01

Full Text Available Abstract Background Plants can defend themselves against herbivorous insects prior to the onset of larval feeding by responding to the eggs laid on their leaves. In the European field elm (Ulmus minor, egg laying by the elm leaf beetle ( Xanthogaleruca luteola activates the emission of volatiles that attract specialised egg parasitoids, which in turn kill the eggs. Little is known about the transcriptional changes that insect eggs trigger in plants and how such indirect defense mechanisms are orchestrated in the context of other biological processes. Results Here we present the first large scale study of egg-induced changes in the transcriptional profile of a tree. Five cDNA libraries were generated from leaves of (i untreated control elms, and elms treated with (ii egg laying and feeding by elm leaf beetles, (iii feeding, (iv artificial transfer of egg clutches, and (v methyl jasmonate. A total of 361,196 ESTs expressed sequence tags (ESTs were identified which clustered into 52,823 unique transcripts (Unitrans and were stored in a database with a public web interface. Among the analyzed Unitrans, 73% could be annotated by homology to known genes in the UniProt (Plant database, particularly to those from Vitis, Ricinus, Populus and Arabidopsis. Comparative in silico analysis among the different treatments revealed differences in Gene Ontology term abundances. Defense- and stress-related gene transcripts were present in high abundance in leaves after herbivore egg laying, but transcripts involved in photosynthesis showed decreased abundance. Many pathogen-related genes and genes involved in phytohormone signaling were expressed, indicative of jasmonic acid biosynthesis and activation of jasmonic acid responsive genes. Cross-comparisons between different libraries based on expression profiles allowed the identification of genes with a potential relevance in egg-induced defenses, as well as other biological processes, including signal transduction

An elm EST database for identifying leaf beetle egg-induced defense genes.

Science.gov (United States)

Büchel, Kerstin; McDowell, Eric; Nelson, Will; Descour, Anne; Gershenzon, Jonathan; Hilker, Monika; Soderlund, Carol; Gang, David R; Fenning, Trevor; Meiners, Torsten

2012-06-15

Plants can defend themselves against herbivorous insects prior to the onset of larval feeding by responding to the eggs laid on their leaves. In the European field elm (Ulmus minor), egg laying by the elm leaf beetle ( Xanthogaleruca luteola) activates the emission of volatiles that attract specialised egg parasitoids, which in turn kill the eggs. Little is known about the transcriptional changes that insect eggs trigger in plants and how such indirect defense mechanisms are orchestrated in the context of other biological processes. Here we present the first large scale study of egg-induced changes in the transcriptional profile of a tree. Five cDNA libraries were generated from leaves of (i) untreated control elms, and elms treated with (ii) egg laying and feeding by elm leaf beetles, (iii) feeding, (iv) artificial transfer of egg clutches, and (v) methyl jasmonate. A total of 361,196 ESTs expressed sequence tags (ESTs) were identified which clustered into 52,823 unique transcripts (Unitrans) and were stored in a database with a public web interface. Among the analyzed Unitrans, 73% could be annotated by homology to known genes in the UniProt (Plant) database, particularly to those from Vitis, Ricinus, Populus and Arabidopsis. Comparative in silico analysis among the different treatments revealed differences in Gene Ontology term abundances. Defense- and stress-related gene transcripts were present in high abundance in leaves after herbivore egg laying, but transcripts involved in photosynthesis showed decreased abundance. Many pathogen-related genes and genes involved in phytohormone signaling were expressed, indicative of jasmonic acid biosynthesis and activation of jasmonic acid responsive genes. Cross-comparisons between different libraries based on expression profiles allowed the identification of genes with a potential relevance in egg-induced defenses, as well as other biological processes, including signal transduction, transport and primary metabolism

Novel algorithms reveal streptococcal transcriptomes and clues about undefined genes.

Science.gov (United States)

Ryan, Patricia A; Kirk, Brian W; Euler, Chad W; Schuch, Raymond; Fischetti, Vincent A

2007-07-01

Bacteria-host interactions are dynamic processes, and understanding transcriptional responses that directly or indirectly regulate the expression of genes involved in initial infection stages would illuminate the molecular events that result in host colonization. We used oligonucleotide microarrays to monitor (in vitro) differential gene expression in group A streptococci during pharyngeal cell adherence, the first overt infection stage. We present neighbor clustering, a new computational method for further analyzing bacterial microarray data that combines two informative characteristics of bacterial genes that share common function or regulation: (1) similar gene expression profiles (i.e., co-expression); and (2) physical proximity of genes on the chromosome. This method identifies statistically significant clusters of co-expressed gene neighbors that potentially share common function or regulation by coupling statistically analyzed gene expression profiles with the chromosomal position of genes. We applied this method to our own data and to those of others, and we show that it identified a greater number of differentially expressed genes, facilitating the reconstruction of more multimeric proteins and complete metabolic pathways than would have been possible without its application. We assessed the biological significance of two identified genes by assaying deletion mutants for adherence in vitro and show that neighbor clustering indeed provides biologically relevant data. Neighbor clustering provides a more comprehensive view of the molecular responses of streptococci during pharyngeal cell adherence.

Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering.

Science.gov (United States)

Chang, Jinyuan; Zhou, Wen; Zhou, Wen-Xin; Wang, Lan

2017-03-01

Comparing large covariance matrices has important applications in modern genomics, where scientists are often interested in understanding whether relationships (e.g., dependencies or co-regulations) among a large number of genes vary between different biological states. We propose a computationally fast procedure for testing the equality of two large covariance matrices when the dimensions of the covariance matrices are much larger than the sample sizes. A distinguishing feature of the new procedure is that it imposes no structural assumptions on the unknown covariance matrices. Hence, the test is robust with respect to various complex dependence structures that frequently arise in genomics. We prove that the proposed procedure is asymptotically valid under weak moment conditions. As an interesting application, we derive a new gene clustering algorithm which shares the same nice property of avoiding restrictive structural assumptions for high-dimensional genomics data. Using an asthma gene expression dataset, we illustrate how the new test helps compare the covariance matrices of the genes across different gene sets/pathways between the disease group and the control group, and how the gene clustering algorithm provides new insights on the way gene clustering patterns differ between the two groups. The proposed methods have been implemented in an R-package HDtest and are available on CRAN. © 2016, The International Biometric Society.

Automatically identifying gene/protein terms in MEDLINE abstracts.

Science.gov (United States)

Yu, Hong; Hatzivassiloglou, Vasileios; Rzhetsky, Andrey; Wilbur, W John

2002-01-01

Natural language processing (NLP) techniques are used to extract information automatically from computer-readable literature. In biology, the identification of terms corresponding to biological substances (e.g., genes and proteins) is a necessary step that precedes the application of other NLP systems that extract biological information (e.g., protein-protein interactions, gene regulation events, and biochemical pathways). We have developed GPmarkup (for "gene/protein-full name mark up"), a software system that automatically identifies gene/protein terms (i.e., symbols or full names) in MEDLINE abstracts. As a part of marking up process, we also generated automatically a knowledge source of paired gene/protein symbols and full names (e.g., LARD for lymphocyte associated receptor of death) from MEDLINE. We found that many of the pairs in our knowledge source do not appear in the current GenBank database. Therefore our methods may also be used for automatic lexicon generation. GPmarkup has 73% recall and 93% precision in identifying and marking up gene/protein terms in MEDLINE abstracts. A random sample of gene/protein symbols and full names and a sample set of marked up abstracts can be viewed at http://www.cpmc.columbia.edu/homepages/yuh9001/GPmarkup/. Contact. hy52@columbia.edu. Voice: 212-939-7028; fax: 212-666-0140.

Identifying key genes associated with acute myocardial infarction.

Science.gov (United States)

Cheng, Ming; An, Shoukuan; Li, Junquan

2017-10-01

This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21-5p and hsa-miR-30c-5p were obviously decreased in AMI. A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs.

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes.

Science.gov (United States)

Hadjithomas, Michalis; Chen, I-Min A; Chu, Ken; Huang, Jinghua; Ratner, Anna; Palaniappan, Krishna; Andersen, Evan; Markowitz, Victor; Kyrpides, Nikos C; Ivanova, Natalia N

2017-01-04

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic gene clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.