Search

Lymphocyte antigen 6 complex, locus E (LY6E) has been implicated in the malignant progression of various types of cancers; however, the underlying mechanism remains unclear. Here, we identified LY6E as an activator of HIF-1 and revealed their mechanistic and functional links in malignant tumor growth. The aberrant overexpression of LY6E increased HIF-1α gene expression principally at the transcription level. This, in turn, led to the expression of the pro-angiogenic factors, VEGFA and PDGFB, through decreases in the expression levels of PTEN mRNA and subsequent activation of the PI3K/Akt pathway. The LY6E-HIF-1 axis functioned to increase tumor blood vessel density and promoted tumor growth in immunodeficient mice. LY6E expression levels were significantly higher in human breast cancers than in normal breast tissues, and were strongly associated with the poor prognoses of various cancer patients. Our results characterized LY6E as a novel conductor of tumor growth through its modulation of the PTEN/PI3K/Akt/HIF-1 axis and demonstrated the validity of targeting this pathway for cancer therapy.

Worldwide obesity and related comorbidities are increasing, but identifying new therapeutic targets remains a challenge. A plethora of microarray studies in diet-induced obesity models has provided large datasets of obesity associated genes. In this review, we describe an approach to examine the underlying molecular network regulating obesity, and we discuss interactions between obesity candidate genes. We conducted network analysis on functional protein-protein interactions associated with 25 obesity candidate genes identified in a literature-driven approach based on published microarray studies of diet-induced obesity. The obesity candidate genes were closely associated with lipid metabolism and inflammation. Peroxisome proliferator activated receptor gamma (Pparg) appeared to be a core obesity gene, and obesity candidate genes were highly interconnected, suggesting a coordinately regulated molecular network in adipose tissue. In conclusion, the current network analysis approach may help elucidate the underlying molecular network regulating obesity and identify anti-obesity targets for therapeutic intervention.

Obesity and its related complications have emerged as global health problems; however, the pathophysiological mechanism of obesity is still not fully understood. In this study, C57BL/6J mice were fed a normal (ND) or high-fat diet (HFD) for 0, 2, 4, 6, 8, 12, 20, and 24 weeks and the time course was systemically analyzed specifically for the hepatic transcriptome profile. Genes that were differentially expressed in the HFD-fed mice were clustered into 49 clusters and further classified into 8 different expression patterns: long-term up-regulated (pattern 1), long-term down-regulated (pattern 2), early up-regulated (pattern 3), early down-regulated (pattern 4), late up-regulated (pattern 5), late down-regulated (pattern 6), early up-regulated and late down-regulated (pattern 7), and early down-regulated and late up-regulated (pattern 8) HFD-responsive genes. Within each pattern, genes related with inflammation, insulin resistance, and lipid metabolism were extracted, and then, a protein-protein interaction network was generated. The pattern specific sub-network was as follows: pattern 1, cellular assembly and organization, and immunological disease, pattern 2, lipid metabolism, pattern 3, gene expression and inflammatory response, pattern 4, cell signaling, pattern 5, lipid metabolism, molecular transport, and small molecule biochemistry, pattern 6, protein synthesis and cell-to cell signaling and interaction and pattern 7, cell-to cell signaling, cellular growth and proliferation, and cell death. For pattern 8, no significant sub-networks were identified. Taken together, this suggests that genes involved in regulating gene expression and inflammatory response are up-regulated whereas genes involved in lipid metabolism and protein synthesis are down-regulated during diet-induced obesity development.

The simple sequence repeats (SSRs) are short tandem arrayed sequence motifs consisting of 2–6 bp, which are not only involved in causing human fatal diseases but also have various applications in plant genetic studies. Thanks to the advancements made in sequencing technology, now we can easily generate genomic/transcriptomic sequences in a shorter period of time. Therefore, trend to identify SSR markers needs up gradation to handle these high-throughput data. Unfortunately, existing web programs for identifying SSR markers are useful but they are unable to process high-throughput data. To overcome this disadvantage, we have constructed a web-based tool, RISA (http://sol.kribb.re.kr/RISA/), with a goal of one-click service to identify SSR markers from high-throughput data (up to 200 Mbp). RISA controls automatic input and output pipeline by demon which combines the SSR classification and investigation by Robert Kofler (SciRoKo) to search SSRs and Primer3 to identify primers specific to SSRs simultaneously. In our test, 45,495 qualified primer sets specific to 47,070 SSRs were identified by RISA from whole Arabidopsis lyrata genome (about 207 Mbp) in 15 minutes. In results, it includes SSR statistics generated from user’s queries and SSR markers information along with primers suitable for their amplification. To support handling of large amount of results, RISA provides various filtering options such as motif length, repeat units, total length and PCR product size. Therefore, we propose that RISA minimizes labour-intensive works or any other considerations which can be required during the development of SSR markers without having deep understanding of computer system and/or algorithms.

The identification of true causal loci to unravel the statistical evidence of genotype-phenotype correlations and the biological relevance of selected single-nucleotide polymorphisms (SNPs) is a challenging issue in genome-wide association studies (GWAS). Here, we introduced a novel method for the prioritization of SNPs based on p-values from GWAS. The method uses functional evidence from populations, including phenotype-associated gene expressions. Based on the concept of genetic interactions, such as perturbation of gene expression by genetic variation, phenotype and gene expression related SNPs were prioritized by adjusting the p-values of SNPs. We applied our method to GWAS data related to drug-induced cytotoxicity. Then, we prioritized loci that potentially play a role in drug-induced cytotoxicity. By generating an interaction model, our approach allowed us not only to identify causal loci, but also to find intermediate nodes that regulate the flow of information among causal loci, perturbed gene expression, and resulting phenotypic variation.

Plants express resistance (R) genes to recognize invaders and prevent the spread of pathogens. To analyze nucleotide binding site, leucine-rich repeat (NB-LRR) genes, we constructed a fast pipeline to predict and classify the R gene analogs (RGAs) by applying in-house matrices. With predicted ~37,000 RGAs, we can directly compare RGA contents across entire plant lineages, from green algae to flowering plants. We focused on the highly divergent NBLRRs in land plants following the emergence of mosses. We identified entire loss of Toll/Interleukin-1 receptor, NBLRR (TNL) in Poaceae family of monocots and interestingly from Mimulus guttatus (a dicot), which leads to the possibility of species-specific TNL loss in other sequenced flowering plants. Using RGA maps, we have elucidated a positive correlation between the cluster sizes of NB-LRRs and their numbers. The cluster members were observed to consist of the same class of NB-LRRs or their variants, which were probably generated from a single locus for an R gene. Our website ( http://sol.kribb.re.kr/PRGA/ ), called plant resistance gene analog (PRGA), provides useful information, such as RGA annotations, tools for predicting RGAs, and analyzing domain profiles. Therefore, PRGA provides new insights into R-gene evolution and is useful in applying RGA as markers in breeding and or systematic studies.

Microsomal delta-12 fatty acid desaturase (FAD2) functions in the first committed step of the biosynthesis of polyunsaturated fatty acids via the desaturation of oleic acid to linoleic acid. In this study, two FAD2 genes were identified through genome-wide analysis of Brassica rapa. One BrFAD2-1 gene harbors functional sequence information, but another BrFAD2-2 gene has mutations that generated a premature stop codon, rendering it nonfunctional. From a database of 120,000 B. rapa expressed sequence tags, we determined that all sequences coding for FAD2 corresponded to the BrFAD2-1 gene. The BrFAD2-1 protein was shown to share high sequence homology (71-99%) with FAD2 proteins from other plant species. An intron in the 5'-untranslated region and three histidine boxes in the protein, which are characteristic of plant FAD2 genes, have been well-conserved. BrFAD2-1 transcripts were detected in various organs of B. rapa. When a pBrFAD2-1:mRFP construct was introduced into tobacco epidermal cells, the fluorescent signal was noted in the endoplasmic reticulum. Ectopic expression of BrFAD2-1:mRFP complemented the Arabidopsis fad2-2 mutant. Finally, transgenic Korean rapeseed Tammi containing high oleic acid contents (78 mol%) was developed via the expression of the BrFAD2-1 gene in an antisense orientation. The data demonstrate that B. rapa harbors only one functional FAD2 that can be utilized for the development of the high-oleic acid Korean rapeseed cultivar Tammi, which might be useful for both human consumption and industrial applications.

Escherichia coli K-12 and B strains have most widely been employed for scientific studies as well as industrial applications. Recently, the complete genome sequences of two representative descendants of E. coli B strains, REL606 and BL21(DE3), have been determined. Here, we report the subproteome reference maps of E. coli B REL606 by analyzing cytoplasmic, periplasmic, inner and outer membrane, and extracellular proteomes based on the genome information using experimental and computational approaches. Among the total of 3487 spots, 651 proteins including 410 non-redundant proteins were identified and characterized by 2-DE and LC-MS/MS; they include 440 cytoplasmic, 45 periplasmic, 50 inner membrane, 61 outer membrane, and 55 extracellular proteins. In addition, subcellular localizations of all 4205 ORFs of E. coli B were predicted by combined computational prediction methods. The subcellular localizations of 1812 (43.09%) proteins of currently unknown function were newly assigned. The results of computational prediction were also compared with the experimental results, showing that overall precision and recall were 92.16 and 92.16%, respectively. This work represents the most comprehensive analyses of the subproteomes of E. coli B, and will be useful as a reference for proteome profiling studies under various conditions. The complete proteome data are available online (http://ecolib.kaist.ac.kr).

MicroRNAs (miRNAs) are a class of small, single-stranded, noncoding RNAs ranging from 19 to 25 nucleotides. The miRNA control various cellular functions by negatively regulating gene expression at the post-transcriptional level. The miRNA regulation over their target genes has a central role in regulating plant growth and development; however, only a few reports have been published on the function of miRNAs in the family Solanaceae. We identified Solanaceae miRNAs and their target genes by analyzing expressed sequence tag (EST) data from five different Solanaceae species. A comprehensive bioinformatic analysis of EST data of Solanaceae species revealed the presence of at least 11 miRNAs and 54 target genes in pepper (Capsicum annuum L.), 22 miRNAs and 221 target genes in potato (Solanum tuberosum L.), 12 miRNAs and 417 target genes in tomato (Solanum lycopersicum L.), 46 miRNAs and 60 target genes in tobacco (Nicotiana tabacum L.), and 7 miRNAs and 28 target genes in Nicotiana benthamiana. The identified Solanaceae miRNAs and their target genes were deposited in the SolmiRNA database, which is freely available for academic research only at http://genepool.kribb.re.kr/SolmiRNA . Our data indicate that the Solanaceae family has both conserved and specific miRNAs and that their target genes may play important roles in growth and development of Solanaceae plants.

A simple sequence repeat–functional domain marker (SSR-FDM) relies on development of molecular markers for putative functional domains using simple sequence repeats and in silico annotated information of those sequences using biological databases. A total of 148,921 tomato ESTs and 115,598 pepper ESTs were analyzed, resulting in the identification of 439 tomato SSR-FDMs and 489 pepper SSR-FDMs. Among them, 54 pepper SSR-FDMs were tested on pepper. Several genomic databases were used for the in silico annotation of the SSR-FDM sequences that revealed a wide range of candidate genes. This study demonstrates that SSR-FDMs provide information regarding transcribed genetic markers and putative function as a genomic resource database for Solanaceae. This system could be applied to the development of a functional marker database for any crop species.

Alternative splicing is generally accepted as a mechanism that explains the discrepancy between the number of genes and proteins. We used peptide mass fingerprinting with a theoretical database and scoring method to discover and identify alternative splicing isoforms. Our theoretical database was built using published alternative splicing databases such as ECgene, H-DBAS, and TISA. According to our theoretical database of 190,529 isoforms, 37% of human genes have multiple isoforms. The isoforms produced from a gene partially share common peptide fragments because they have common exons, making it difficult to distinguish isoforms. Therefore, we developed a new method that effectively distinguishes a true isoform among multiple isoforms in a gene. In order to evaluate our algorithm, we made test sets for 4226 protein isoforms extracted from our theoretical database randomly. Consequently, 94% of true isoforms were identified by our scoring algorithm.

Sesame ( Sesamum indicum ) is an important oilseed crop; approximately 50% of the seed dry weight is storage oil. In a previous report, developing sesame seed expressed sequence tags (ESTs) revealed that ESTs encoding lipid transfer protein (LTPs) were one of the most abundant groups of sesame ESTs. LTP functions in the transfer of wax or cutin monomers and in the defense response against pathogen attack. To study the biological role of the abundant LTP isoforms in developing seeds, 122 ESTs out of 3328 sesame ESTs were analyzed against Arabidopsis and rice proteome databases. LTP fraction, which was partially purified from developing sesame seeds, actively transferred fluorescent phospholipids and bound to fatty acids. Full-length cDNAs of five out of 21 LTP isoforms were isolated and named SiLTP1 – SiLTP5 . The predicted amino acid sequences of the five SiLTPs harbor typical characteristics of LTPs, including conserved arrangement of cysteine residues. Northern blot analysis revealed that the five SiLTP isoforms were most abundantly expressed in developing seeds, but were also detected in flower tissues. Also, SiLTP3 and SiLTP4 transcripts were expressed in leaves and seed-pot walls, respectively. In addition, SiLTP2 and SiLTP4 transcripts were significantly induced in 6-day-old sesame seedlings by application of NaCl, mannitol, and abscisic acid (ABA). Transient expression of green fluorescent protein (GFP)-fusion constructs in Arabidopsis protoplasts revealed that SiLTP1 and SiLTP2 were secreted by different pathways. Taken together, the abundant LTPs in developing sesame seeds are involved in lipid transfer into the extracellular matrix. Possible biological roles of SiLTPs related to organ-specific expression and abiotic stresses are discussed.

G protein-coupled receptors (GPCRs) constitute the largest family of cell surface receptors and play a central role in cellular signaling pathways. The importance of GPCRs has led to their becoming the targets of more than 50% of prescription drugs. However, drug compounds that do not differentiate between receptor subtypes can have considerable side effects and efficacy problems. An accurate classification of GPCRs can solve the side effect problems and raise the efficacy of drugs. Here, we introduce an approach that combines a fingerprint method, statistical profiles and physicochemical properties of transmembrane (TM) domains for a highly accurate classification of the receptors. The approach allows both the recognition and classification for GPCRs at the subfamily and subtype level, and allows the identification of splice variants. We found that the approach demonstrates an overall accuracy of 97.88% for subfamily classification, and 94.57% for subtype classification.

Pathogenicity islands (PAIs) are genetic elements whose products are essential to the process of disease development. They have been horizontally (laterally) transferred from other microbes and are important in evolution of pathogenesis. In this study, a comprehensive database and search engines specialized for PAIs were established. The pathogenicity island database (PAIDB) is a comprehensive relational database of all the reported PAIs and potential PAI regions which were predicted by a method that combines feature-based analysis and similarity-based analysis. Also, using the PAI Finder search application, a multi-sequence query can be analyzed onsite for the presence of potential PAIs. As of April 2006, PAIDB contains 112 types of PAIs and 889 GenBank accessions containing either partial or all PAI loci previously reported in the literature, which are present in 497 strains of pathogenic bacteria. The database also offers 310 candidate PAIs predicted from 118 sequenced prokaryotic genomes. With the increasing number of prokaryotic genomes without functional inference and sequenced genetic regions of suspected involvement in diseases, this web-based, user-friendly resource has the potential to be of significant use in pathogenomics. PAIDB is freely accessible at http://www.gem.re.kr/paidb.

애기 장대와 벼의 전체 게놈 염기서열 분석이 완료되었고, 다량의 EST 데이터가 많은 식물에서 이용 가능하게 되었다. 또한, 방대한 양의 다양한 생물학적 데이터들이 transcriptomics, proteomics, metabolomics와 같은 여러 '-omics' 기술에 의하여 만들어져 왔다. 생물정보학은 이런 방대한 양의 생물학적 데이터로부터 유용한 정보를 얻는데 필수적이고도 매우 중요한 역할을 수행한다. 이 총설에서, 우리는 대량의 데이터를 생성하는 실험적 방법들과, 식물 병 저항성과 분자 육종과 같은 식물 연구분야로의 응용, 그리고 식물 생명공학의 연구 개발에 유용한 생물정보학적 기술과. 인터넷 정보 사이트들을 소개하였다. 우리는 새로운 실험 방법들과 생물정보학적 분석 기술들이 식물 생명공학 발전에 중요하게 기여할 것으로 기대하고 있으며, 생물정보학은 식물 생명공학의 연구 개발에 있어서 결정적인 요소가 될 것이라 생각한다. 【The whole genome sequence was completed in arabidopsis and rice. Large amounts of EST data have been available from many other plants. Also, vast quantities of diverse biological data have been generated by various '-omics' technologies such as transcriptomics, proteomics, and metabolomics. Bioinformatics plays an essential role in extracting useful information from these tremendous amounts of biological data. In this review we introduced experimental methods to generate massive data, applications to plant science such as plant disease resistance and molecular breeding and bioinformatics tools and web sites available in plant biotechnology R&D. We concluded that new experimental methods and bioinfomation analysis techniques have made major contributions to the development of plant biotechnology and that bioinformatics has become a critical factor in plant biotechnology R&D.】

Alternative splicing (AS) is a mechanism by which multiple transcripts are produced from a single gene and is thought to be an important mechanism for tissue-specific expression of transcript isoforms. Here, we report a novel graphing method for transcript reconstruction and statistical prediction of tissue-specific AS. We applied three selection steps to generate the splice graph and predict the transcript isoforms: (i) a custom scoring rule for exon/intron sets, (ii) binomial statistics for selecting valid alternative splicing with a frequency of at least 1% for the predominant form and (iii) evaluation of transcript structure. We obtained 97 286 and 66 022 valid transcripts from 26 143 human and 27 741 mouse genes, respectively. In addition, we discovered 33 481 AS events for nine types of AS patterns in human. The statistical significance of tissue specificity for each gene, transcript and AS event was assessed based on EST tissue information, followed by a multiple testing correction procedure. In human, 12 711 genes, 16 016 transcripts and 1035 AS events were predicted to be tissue-specific (false discovery rate

Harmful algal blooms, caused by rapid growth and accumulation of certain microalgae in the ocean, pose considerable impacts on marine environments, aquatic industries and even public health. Here, we present the 7.2-megabase genome of the marine bacterium Hahella chejuensis including genes responsible for the biosynthesis of a pigment which has the lytic activity against a red-tide dinoflagellate. H.chejuensis is the first sequenced species in the Oceanospiralles clade, and sequence analysis revealed its distant relationship to the Pseudomonas group. The genome was well equipped with genes for basic metabolic capabilities and contained a large number of genes involved in regulation or transport as well as with characteristics as a marine heterotroph. Sequence analysis also revealed a multitude of genes of functional equivalence or of possible foreign origin. Functions encoded in the genomic islands include biosynthesis of exopolysacchrides, toxins, polyketides or non-ribosomal peptides, iron utilization, motility, type III protein secretion and pigmentation. Molecular structure of the algicidal pigment, which was determined through LC-ESI-MS/MS and NMR analyses, indicated that it is prodigiosin. In conclusion, our work provides new insights into mitigating algal blooms in addition to genetic make-up, physiology, biotic interactions and biological roles in the community of a marine bacterium.

The rumen represents the first section of a ruminant animal's stomach, where feed is collected and mixed with microorganisms for initial digestion. The major gas produced in the rumen is CO(2) (65.5 mol%), yet the metabolic characteristics of capnophilic (CO(2)-loving) microorganisms are not well understood. Here we report the 2,314,078 base pair genome sequence of Mannheimia succiniciproducens MBEL55E, a recently isolated capnophilic Gram-negative bacterium from bovine rumen, and analyze its genome contents and metabolic characteristics. The metabolism of M. succiniciproducens was found to be well adapted to the oxygen-free rumen by using fumarate as a major electron acceptor. Genome-scale metabolic flux analysis indicated that CO(2) is important for the carboxylation of phosphoenolpyruvate to oxaloacetate, which is converted to succinic acid by the reductive tricarboxylic acid cycle and menaquinone systems. This characteristic metabolism allows highly efficient production of succinic acid, an important four-carbon industrial chemical.

14-3-3 proteins are a family of conserved proteins expressed in all eukaryotes. They function as regulators in signaling pathways through protein-protein interaction. These proteins have been implicated in plant metabolism, development, and responses to abiotic and biotic stresses. Here, we isolated six cDNAs encoding 14-3-3 proteins ofPanax ginseng, designated asPg14-3-3, by searching the ginseng EST database. Their degree of amino acid identity ranged from 53 to 84%. Phylogenetic analysis showed that thePg14-3-3 isoforms can be divided into two groups by early duplication, with one group being further split into three subgroups because of subsequent duplication events.Pg14-3-3s are differentially expressed in various root tissues and leaves, and their transcript levels are up-or down-regulated by either cold or drought stresses. These results suggest a possible role for Pg14-3-3 proteins in abiotic stress responses.

Expressed sequence tags (ESTs) provide a valuable tool that can be used to identify genes in secondary metabolite biosynthesis. Ginseng (Panax ginseng C.A Meyer) is a medicinal plant that accumulates ginsenosides in roots. We sequenced 11,636 ESTs from five ginseng libraries in order to create a gene resource for biosynthesis of ginsenosides, which are thought to be the major active component in roots. Only 59% of the ginseng ESTs exhibited significant homology to previously known polypeptide sequences. Stress- and pathogen-response proteins were most abundant in 4-year-old ginseng roots. ESTs involved in ginsenoside biosynthesis were identified by a keyword search of BLASTX results and a domain search of ginseng ESTs. We identified 4 oxidosqualene cyclase candidates involved in the cyclization reaction of 2,3-oxidosqualene, 9 nine cytochrome P450 and 12 glycosyltransferse candidates, which may be involved in modification of the triterpene backbone.

Researchers have widely adopted the hairy root culture system as a means for producing secondary metabolites, including ginsenosides from ginseng. Although bacterial genes are involved, the aspects of plant gene expression are unclear. Using a cDNA microarray approach, we identified genes that are differentially expressed in ginseng hairy roots afterAgrobacterium rhizogenes infection. Our goal was to gain an initial understanding of the correlation between hairy root morphology and ginsenoside production. Among the 250 genes analyzed here, 63 (including 14 that are unclassified) were differentially expressed in a hairy root line containing a high level of ginsenosides. Of the genes that had been functionally categorized, 29% and 17% were active in metabolism and stress responses, respectively. Most were primarily associated with ribosomal proteins, thereby functioning in protein synthesis and destination. Their expression was down-regulated in hairy roots having less lateral branching. This phenotype may have resulted from the manipulation of metabolic activities by the translational machinery.

For the hairy root of Panax ginseng, we have got mass spectrums from MALDI/TOF/MS analysis and Tandem mass spectrums from ESI/Q-TOF/MS analysis. While mass spectrum provides the molecular weights of peptide fragments digested by protease such as trypsin, tandem mass spectrum produces amino acid sequence of digested peptides. Each amino acid sequences can be a query sequence in BLAST search to identify proteins. For the specimens of animals or plants of which genome sequences were known, we can easily identify expressed proteins from mass spectrums with high accuracy. However, for the other specimens such as ginseng, it is difficult to identify proteins with accuracy since all the protein sequences are not available yet. Here we compared the mass spectrums and the peptide amino acid sequences with ginseng expressed sequence tag (EST) DB. The matched EST sequence was used as a query in BLAST search for protein identification. They could offer the correct protein information by the sequence alignment with EST sequences. 90% of peptide sequences of ESI/Q-TOF/MS are matched with EST sequences. Comparing 68% matches of the same sequences with the nr database of NCBI, we got more matches by 22% from ginseng EST sequence search. In case of peptide mass fingerprinting from MALDI/TOF/MS, only about 19% (9 proteins of 47 spots) among peptide matches from nr DB were correlated with ginseng EST DB. From these results, we suggest that amino acid sequencing using tandem mass spectrum analysis may be necessary for protein identification in ginseng proteome analysis.

We previously demonstrated that the chronic consumption of a high-fat diet (HFD) promotes lung and liver metastases of 4T1 mammary carcinoma cells in obesity-resistant BALB/c mice. To examine early transcriptional responses to tumour progression in the liver and lungs of HFD-fed mice, 4-week-old female BALB/c mice were divided into four groups: sham-injected, control diet (CD)-fed; sham-injected, HFD-fed (SH); 4T1 cell-injected, CD-fed (TC); 4T1 cell-injected, HFD-fed (TH). Following 16 weeks of either a CD or HFD, 4T1 cells were injected into the mammary fat pads of mice in the TC and TH groups and all mice were continuously fed identical diets. At 14 d post-injection, RNA was isolated from hepatic and pulmonary tissues for microarray analysis of mRNA expression. Functional annotation and core network analyses were conducted for the TH/SH Unique gene set. Inflammation in hepatic tissues and cell mitosis in pulmonary tissues were the most significant biological functions in the TH/SH Unique gene set. The biological core networks of the hepatic TH/SH Unique gene set were characterised as those genes involved in the activation of acute inflammatory responses (Orm1, Lbp, Hp and Cfb), disordered lipid metabolism and deregulated cell cycle progression. Networks of the pulmonary Unique gene set displayed the deregulation of cell cycle progression (Cdc20, Cdk1 and Bub1b). These HFD-influenced alterations may have led to favourable conditions for the formation of both pro-inflammatory and pro-mitotic microenvironments in the target organs that promote immune cell infiltration and differentiation, as well as the infiltration and proliferation of metastatic tumour cells.

The pathophysiological mechanisms underlying the development of obesity and metabolic diseases are not well understood. To gain more insight into the genetic mediators associated with the onset and progression of diet-induced obesity and metabolic diseases, we studied the molecular changes in response to a high-fat diet (HFD) by using a mode-of-action by network identification (MNI) analysis. Oligo DNA microarray analysis was performed on visceral and subcutaneous adipose tissues and muscles of male C57BL/6N mice fed a normal diet or HFD for 2, 4, 8, and 12 weeks. Each of these data was queried against the MNI algorithm, and the lists of top 5 highly ranked genes and gene ontology (GO)-annotated pathways that were significantly overrepresented among the 100 highest ranked genes at each time point in the 3 different tissues of mice fed the HFD were considered in the present study. The 40 highest ranked genes identified by MNI analysis at each time point in the different tissues of mice with diet-induced obesity were subjected to clustering based on their temporal patterns. On the basis of the above-mentioned results, we investigated the sequential induction of distinct olfactory receptors and the stimulation of cancer-related genes during the development of obesity in both adipose tissues and muscles. The top 5 genes recognized using the MNI analysis at each time point and gene cluster identified based on their temporal patterns in the peripheral tissues of mice provided novel and often surprising insights into the potential genetic mediators for obesity progression.

Constitutive overexpression of transgenes occasionally interferes with normal growth and developmental processes in plants. Thus, the development of tissue-specific promoters that drive transgene expression has become agriculturally important. To identify tomato tissue-specific promoters, tissue-specific genes were screened using a series of in silico-based and experimental procedures, including genome-wide orthologue searches of tomato and Arabidopsis databases, isolation of tissue-specific candidates using an Arabidopsis microarray database, and validation of tissue specificity by reverse transcription-polymerase chain reaction (RT-PCR) analysis and promoter assay. Using these procedures, we found 311 tissue-specific candidate genes and validated 10 tissue-specific genes by RT-PCR. Among these identified genes, histochemical analysis of five isolated promoter::GUS transgenic tomato and Arabidopsis plants revealed that their promoters have different but distinct tissue-specific activities in anther, fruit, and root, respectively. Therefore, it appears these in silico-based screening approaches in addition to the identification of new tissue-specific genes and promoters will be helpful for the further development of tailored crop development.

Prolonged high-fat diet leads to the development of obesity and multiple comorbidities including non-alcoholic steatohepatitis (NASH), but the underlying molecular basis is not fully understood. We combine molecular networks and time course gene expression profiles to reveal the dynamic changes in molecular networks underlying diet-induced obesity and NASH. We also identify hub genes associated with the development of NASH. Core diet-induced obesity networks were constructed using Ingenuity pathway analysis (IPA) based on 332 high-fat diet responsive genes identified in liver by time course microarray analysis (8 time points over 24 weeks) of high-fat diet-fed mice compared to normal diet-fed mice. IPA identified five core diet-induced obesity networks with time-dependent gene expression changes in liver. These networks were associated with cell-to-cell signaling and interaction (Network 1), lipid metabolism (Network 2), hepatic system disease (Network 3 and 5), and inflammatory response (Network 4). When we merged these core diet-induced obesity networks, Tlr2, Cd14, and Ccnd1 emerged as hub genes associated with both liver steatosis and inflammation and were altered in a time-dependent manner. Further, protein–protein interaction network analysis revealed Tlr2, Cd14, and Ccnd1 were interrelated through the ErbB/insulin signaling pathway. Dynamic changes occur in molecular networks underlying diet-induced obesity. Tlr2, Cd14, and Ccnd1 appear to be hub genes integrating molecular interactions associated with the development of NASH. Therapeutics targeting hub genes and core diet-induced obesity networks may help ameliorate diet-induced obesity and NASH.

Background Roses (Rosa sp.), which belong to the family Rosaceae, are the most economically important ornamental plants—making up 30% of the floriculture market. However, given high demand for roses, rose breeding programs are limited in molecular resources which can greatly enhance and speed breeding efforts. A better understanding of important genes that contribute to important floral development and desired phenotypes will lead to improved rose cultivars. For this study, we analyzed rose miRNAs and the rose flower transcriptome in order to generate a database to expound upon current knowledge regarding regulation of important floral characteristics. A rose genetic database will enable comprehensive analysis of gene expression and regulation via miRNA among different Rosa cultivars. Results We produced more than 0.5 million reads from expressed sequences, totalling more than 110 million bp. From these, we generated 35,657, 31,434, 34,725, and 39,722 flower unigenes from Rosa hybrid: ‘Vital’, ‘Maroussia’, and ‘Sympathy’ and Rosa rugosa Thunb. , respectively. The unigenes were assigned functional annotations, domains, metabolic pathways, Gene Ontology (GO) terms, Plant Ontology (PO) terms, and MIPS Functional Catalogue (FunCat) terms. Rose flower transcripts were compared with genes from whole genome sequences of Rosaceae members (apple, strawberry, and peach) and grape. We also produced approximately 40 million small RNA reads from flower tissue for Rosa, representing 267 unique miRNA tags. Among identified miRNAs, 25 of them were novel and 242 of them were conserved miRNAs. Statistical analyses of miRNA profiles revealed both shared and species-specific miRNAs, which presumably effect flower development and phenotypes. Conclusions In this study, we constructed a Rose miRNA and transcriptome database, and we analyzed the miRNAs and transcriptome generated from the flower tissues of four Rosa cultivars. The database provides a comprehensive genetic resource which can be used to better understand rose flower development and to identify candidate genes for important phenotypes.

In multicellular organisms, including humans, understanding expression specificity at the tissue level is essential for interpreting protein function, such as tissue differentiation. We developed a prediction approach via generated sequence features from overrepresented patterns in housekeeping (HK) and tissue-specific (TS) genes to classify TS expression in humans. Using TS domains and transcriptional factor binding sites (TFBSs), sequence characteristics were used as indices of expressed tissues in a Random Forest algorithm by scoring exclusive patterns considering the biological intuition; TFBSs regulate gene expression, and the domains reflect the functional specificity of a TS gene. Our proposed approach displayed better performance than previous attempts and was validated using computational and experimental methods.

Scope: This study investigated the global transcriptional and metabolic changes occurring at multiple time points over 24wk in response to a high-fat diet (HFD). Methods and results: C57BL/6J mice were fed a HFD or normal diet (ND) over 24 wk. HFD-fed mice developed early clinical indicators of obesity-related co-morbidities including fatty liver, insulin resistance, hyperglycemia and hypercholesterolemia. Time-course microarray analysis at eight time points over 24 wk identified 332 HFD responsive genes as potential targets to counteract diet-induced obesity (DIO) and related co-morbidities. Glucose regulating enzyme activity and gene expression were altered early in the HFD-fed mice. Fatty acid (FA) and triglyceride (TG) accumulation in combination with inflammatory changes appear to be likely candidates contributing to hepatic insulin resistance. Cidea seemed to be one of representative genes related to these changes. Conclusion: Global transcriptional and metabolic profiling across multiple time points in liver revealed potential targets for nutritional interventions to reverse DIO. In future, new approaches targeting HFD responsive genes and hepatic metabolism could help ameliorate the deleterious effects of an HFD and DIO-related complication.

Variovorax paradoxus is a microorganism of special interest due to its diverse metabolic capabilities, including the biodegradation of both biogenic compounds and anthropogenic contaminants. V. paradoxus also engages in mutually beneficial interactions with both bacteria and plants. The complete genome sequence of V. paradoxus S110 is composed of 6,754,997 bp with 6,279 predicted protein-coding sequences within two circular chromosomes. Genomic analysis has revealed multiple metabolic features for autotrophic and heterotrophic lifestyles. These metabolic diversities enable independent survival, as well as a symbiotic lifestyle. Consequently, S110 appears to have evolved into a superbly adaptable microorganism that is able to survive in ever-changing environmental conditions. Based on our findings, we suggest V. paradoxus S110 as a potential candidate for agrobiotechnological applications, such as biofertilizer and biopesticide. Because it has many associations with other biota, it is also suited to serve as an additional model system for studies of microbe-plant and microbe-microbe interactions.

Tandemly repeated DNAs, referred to as satellite DNAs, often occur in a genome in a genus-specific manner. However, the mechanisms for generation and evolution for these sequences are largely unknown because of the uncertain origins of the satellite DNAs. We found highly divergent genus-specific satellite DNAs that showed sequence similarity with genus-specific intergenic spacers (IGSs) in the family Solanaceae, which includes the genera Nicotiana, Solanum and Capsicum. The conserved position of the IGS between 25S and 18S rDNA facilitates comparison of IGS sequences across genera, even in the presence of very low sequence similarity. Sequence comparison of IGS may elucidate the procedure of the genesis of complex monomer units of the satellite DNAs. Within the IGS of Capsicum species, base substitutions and copy number variation of subrepeat monomers were causes of monomer divergence in IGS sequences. At the level of inter-generic IGS sequences of the family Solanaceae, however, genus-specific motif selection, motif shuffling between subrepeats and differential amplification among motifs were involved in formation of genus-specific IGS. Therefore, the genus-specific satellite DNAs in Solanaceae plants can be generated from differentially organized repeat monomers of the IGS rather than by accumulation of mutations from pre-existent satellite DNAs.

Paenibacillus polymyxa E681, a spore-forming, low-G+C, Gram-positive bacterium isolated from the rhizosphere of winter barley grown in South Korea, has great potential for agricultural applications due to its ability to promote plant growth and suppress plant diseases. Here we present the complete genome sequence of P. polymyxa E681. Its 5.4-Mb genome encodes functions specialized to the plant-associated lifestyle and characteristics that are beneficial to plants, such as the production of a plant growth hormone, antibiotics, and hydrolytic enzymes.

Plants in the family Solanaceae are used as model systems in comparative and evolutionary genomics. The complete chloroplast genomes of seven solanaceous species have been sequenced, including tobacco, potato and tomato, but not peppers. We analyzed the complete chloroplast genome sequence of the hot pepper, Capsicum annuum. The pepper chloroplast genome was 156,781 bp in length, including a pair of inverted repeats (IR) of 25,783 bp. The content and the order of 133 genes in the pepper chloroplast genome were identical to those of other solanaceous plastomes. To characterize pepper plastome sequence, we performed comparative analysis using complete plastome sequences of pepper and seven solanaceous plastomes. Frequency and contents of large indels and tandem repeat sequences and distribution pattern of genome-wide sequence variations were investigated. In addition, a phylogenetic analysis using concatenated alignments of coding sequences was performed to determine evolutionary position of pepper in Solanaceae. Our results revealed two distinct features of pepper plastome compared to other solanaceous plastomes. Firstly, large indels, including insertions on accD and rpl20 gene sequences, were predominantly detected in the pepper plastome compared to other solanaceous plastomes. Secondly, tandem repeat sequences were particularly frequent in the pepper plastome. Taken together, our study represents unique features of evolution of pepper plastome among solanaceous plastomes.

Obesity and its associated complications, including diabetes, dyslipidemia, atherosclerosis, and some cancers, have been a global health problem with a rapid increase of the obese population. In this study, we selected 31 obesity candidate genes in the liver of high-fat-induced obese C57BL/6J mice through investigation of literature search and analyzed functional protein-protein interaction of the genes using the STRING database. Most of the obesity candidate genes were closely connected through lipid metabolism, and in particular acyl-coenzyme A oxidase 1 appeared to be a core obesity gene. Overall, genes involved in fatty acid beta-oxidation, fatty acid synthesis, and gluconeogenesis were up-regulated, and genes involved in sterol biosynthesis, insulin signaling, and oxidative stress defense system were down-regulated with a high-fat diet. Future identification of core obesity genes and their functional targets is expected to provide a new way to prevent obesity by phytochemicals or functional foods on the basis of food and nutritional genomics.

Escherichia coli K-12 and B have been the subjects of classical experiments from which much of our understanding of molecular genetics has emerged. We present here complete genome sequences of two E. coli B strains, REL606, used in a long-term evolution experiment, and BL21(DE3), widely used to express recombinant proteins. The two genomes differ in length by 72,304 bp and have 426 single base pair differences, a seemingly large difference for laboratory strains having a common ancestor within the last 67 years. Transpositions by IS1 and IS150 have occurred in both lineages. Integration of the DE3 prophage in BL21(DE3) apparently displaced a defective prophage in the lambda attachment site of B. As might have been anticipated from the many genetic and biochemical experiments comparing B and K-12 over the years, the B genomes are similar in size and organization to the genome of E. coli K-12 MG1655 and have >99% sequence identity over approximately 92% of their genomes. E. coli B and K-12 differ considerably in distribution of IS elements and in location and composition of larger mobile elements. An unexpected difference is the absence of a large cluster of flagella genes in B, due to a 41 kbp IS1-mediated deletion. Gene clusters that specify the LPS core, O antigen, and restriction enzymes differ substantially, presumably because of horizontal transfer. Comparative analysis of 32 independently isolated E. coli and Shigella genomes, both commensals and pathogenic strains, identifies a minimal set of genes in common plus many strain-specific genes that constitute a large E. coli pan-genome.

Background Tandemly repeated DNA, also called as satellite DNA, is a common feature of eukaryotic genomes. Satellite repeats can expand and contract dramatically, which may cause genome size variation among genetically-related species. However, the origin and expansion mechanism are not clear yet and needed to be elucidated. Results FISH analysis revealed that the satellite repeat showing homology with intergenic spacer (IGS) of rDNA present in the tomato genome. By comparing the sequences representing distinct stages in the divergence of rDNA repeat with those of canonical rDNA arrays, the molecular mechanism of the evolution of satellite repeat is described. Comprehensive sequence analysis and phylogenetic analysis demonstrated that a long terminal repeat retrotransposon was interrupted into each copy of the 18S rDNA and polymerized by recombination rather than transposition via an RNA intermediate. The repeat was expanded through doubling the number of IGS into the 25S rRNA gene, and also greatly increasing the copy number of type I subrepeat in the IGS of 25-18S rDNA by segmental duplication. Homogenization to a single type of subrepeat in the satellite repeat was achieved as the result of amplifying copy number of the type I subrepeat but eliminating neighboring sequences including the type II subrepeat and rRNA coding sequence from the array. FISH analysis revealed that the satellite repeats are commonly present in closely-related Solanum species, but vary in their distribution and abundance among species. Conclusion These results represent that the dynamic satellite repeats were originated from intergenic spacer of rDNA unit in the tomato genome. This result could serve as an example towards understanding the initiation and the expansion of the satellite repeats in complex eukaryotic genome.

The genome of tomato (Solanum lycopersicum L.) is being sequenced by an international consortium of 10 countries (Korea, China, the United Kingdom, India, the Netherlands, France, Japan, Spain, Italy, and the United States) as part of the larger “International Solanaceae Genome Project (SOL): Systems Approach to Diversity and Adaptation” initiative. The tomato genome sequencing project uses an ordered bacterial artificial chromosome (BAC) approach to generate a high-quality tomato euchromatic genome sequence for use as a reference genome for the Solanaceae and euasterids. Sequence is deposited at GenBank and at the SOL Genomics Network (SGN). Currently, there are around 1000 BACs finished or in progress, representing more than a third of the projected euchromatic portion of the genome. An annotation effort is also underway by the International Tomato Annotation Group. The expected number of genes in the euchromatin is ∼40,000, based on an estimate from a preliminary annotation of 11% of finished sequence. Here, we present this first snapshot of the emerging tomato genome and its annotation, a short comparison with potato (Solanum tuberosum L.) sequence data, and the tools available for the researchers to exploit this new resource are also presented. In the future, whole-genome shotgun techniques will be combined with the BAC-by-BAC approach to cover the entire tomato genome. The high-quality reference euchromatic tomato sequence is expected to be near completion by 2010.

The genomewide gene expression profiling of the methylotrophic yeast Hansenula polymorpha exposed to cadmium (Cd) allowed us to identify novel genes responsive to Cd treatment. To select genes whose promoters can be useful for construction of a cellular Cd biosensor, we further analyzed a set of H. polymorpha genes that exhibited >6-fold induction upon treatment with 300 μM Cd for 2 h. The putative promoters, about 1,000-bp upstream fragments, of these genes were fused with the yeast-enhanced green fluorescence protein (GFP) gene. The resultant reporter cassettes were introduced into H. polymorpha to evaluate promoter strength and specificity. The promoter derived from the H. polymorpha SEO1 gene (Hp SEO1 ) was shown to drive most strongly the expression of GFP upon Cd treatment among the tested promoters. The Cd-inducible activity was retained in the 500-bp deletion fragment of the Hp SEO1 promoter but was abolished in the further truncated 250-bp fragment. The 500-bp Hp SEO1 promoter directed specific expression of GFP upon exposure to Cd in a dose-dependent manner, with Cd detection ranging from 1 to 900 μM. Comparative analysis of the Saccharomyces cerevisiae SEO1 (Sc SEO1 ) promoter revealed that the Sc SEO1 promoter has a broader specificity for heavy metals and is responsive to arsenic and mercury in addition to Cd. Our data demonstrate the potential use of the Hp SEO1 promoter as a bioelement in whole-cell biosensors to monitor heavy metal contamination, particularly Cd.

MELDB is a comprehensive protein database of microbial esterases and lipases which are hydrolytic enzymes important in the modern industry. Proteins in MELDB are clustered into groups according to their sequence similarities based on a local pairwise alignment algorithm and a graph clustering algorithm (TribeMCL). This differs from traditional approaches that use global pairwise alignment and joining methods. Our procedure was able to reduce the noise caused by dubious alignment in the distantly related or unrelated regions in the sequences. In the database, 883 esterase and lipase sequences derived from microbial sources are deposited and conserved parts of each protein are identified. HMM profiles of each cluster were generated to classify unknown sequences. Contents of the database can be keyword-searched and query sequences can be aligned to sequence profiles and sequences themselves.

Background Pathogenicity islands (PAIs), distinct genomic segments of pathogens encoding virulence factors, represent a subgroup of genomic islands (GIs) that have been acquired by horizontal gene transfer event. Up to now, computational approaches for identifying PAIs have been focused on the detection of genomic regions which only differ from the rest of the genome in their base composition and codon usage. These approaches often lead to the identification of genomic islands, rather than PAIs. Results We present a computational method for detecting potential PAIs in complete prokaryotic genomes by combining sequence similarities and abnormalities in genomic composition. We first collected 207 GenBank accessions containing either part or all of the reported PAI loci. In sequenced genomes, strips of PAI-homologs were defined based on the proximity of the homologs of genes in the same PAI accession. An algorithm reminiscent of sequence-assembly procedure was then devised to merge overlapping or adjacent genomic strips into a large genomic region. Among the defined genomic regions, PAI-like regions were identified by the presence of homolog(s) of virulence genes. Also, GIs were postulated by calculating G+C content anomalies and codon usage bias. Of 148 prokaryotic genomes examined, 23 pathogenic and 6 non-pathogenic bacteria contained 77 candidate PAIs that partly or entirely overlap GIs. Conclusion Supporting the validity of our method, included in the list of candidate PAIs were thirty four PAIs previously identified from genome sequencing papers. Furthermore, in some instances, our method was able to detect entire PAIs for those only partial sequences are available. Our method was proven to be an efficient method for demarcating the potential PAIs in our study. Also, the function(s) and origin(s) of a candidate PAI can be inferred by investigating the PAI queries comprising it. Identification and analysis of potential PAIs in prokaryotic genomes will broaden our knowledge on the structure and properties of PAIs and the evolution of bacterial pathogenesis.

We address Quintet, an R-based unified cDNA microarray data analysis system with GUI. Five principal categories of microarray data analysis have been coherently integrated in Quintet: data processing steps such as faulty spot filtering and normalization, data quality assessment (QA), identification of differentially expressed genes (DEGs), clustering of gene expression profiles, and classification of samples. Though many microarray data analysis systems normally consider DEG identification and clustering/classification the most important problems, we emphasize that data processing and QA are equally important and should be incorporated into the regular-base data analysis practices because microarray data are very noisy. In each analysis category, customized plots and statistical summaries are also given for users convenience. Using these plots and summaries, analysis results can be easily examined for their biological plausibility and compared with other results. Since Quintet is written in R, it is highly extendable so that users can insert new algorithms and experiment them with minimal efforts. Also, the GUI makes it easy to learn and use and since R-language and its GUI engine, Tcl/Tk, are available in all operating systems, Quintet is OS-independent too.