GO Molecular Function Research Articles

Integrating Genome-Wide Association Studies With Pathway Analysis and Gene Expression Analysis Highlights Novel Osteoarthritis Risk Pathways and Genes.

Osteoarthritis (OA) is the most common degenerative joint disorder worldwide. To identify more genetic signals, genome-wide association study (GWAS) has been widely used and elucidated some OA susceptibility genes. However, these susceptibility genes could only explain only a small part of heritability of OA. It is suggested that the identification of disease-related pathways may contribute to understand the genomic etiology of OA. Here, we integrated the GWAS into pathway analysis to identify novel OA risk pathways. In this study, we first selected 187 independent genetic variants identified by GWAS (P < 1.00E−05) and found that most of these genetic variants are noncoding mutations. We then conducted an expression quantitative trait loci analysis and found that 165 of these 187 genetic variants could significantly regulate the expression of nearby genes. Third, we identified OA susceptibility genes corresponding to these genetic variants, conducted a pathway analysis, and identified novel OA-related KEGG pathways, GO biological processes, GO molecular functions, and GO cellular components. In KEGG database, transforming growth factor β signaling pathway is the most significant signal (P = 5.98E−05) and is the only pathway after the BH multiple-test adjustment with false discovery rate (FDR) = 0.02. In GO database, we identified 24 statistically significant GO biological processes, one statistically significant GO molecular function, and five statistically significant GO cellular components (FDR < 0.05). These signals are related with chondrocyte differentiation and development, which are all known biological pathways associated with OA. Finally, we conducted an OA case–control gene expression analysis to evaluate the differential expression of these OA risk genes. Using an OA case–control gene expression analysis, we showed that 44 risk genes were suggestively differentially expressed in OA cases compared with controls (P < 0.05). Three genes, WWP2, COG5, and MAPT, were statistically differentially expressed in OA cases compared with controls (P < 0.05/122 = 4.10E−04). Hence, our findings may contribute to understanding the genomic etiology of OA.

Gastric Cancer MicroRNAs Meta-signature.

Gastric cancer (GC) isone of the most common types of cancer and the second leading cause of cancer-associated mortality.Identification of novel biomarkers is critical to prolonging patient survival. MicroRNAs (miRNAs) proved to play diverse roles in the physiological and pathological state in cancers including GC. Herein we aimed at performing a meta-analysis on miRNA profiling studies that used microarray platforms. Relevant studies were retrieved from PubMed and GEO databases. We used the robust rank aggregation to perform the meta-analysis. Moreover, for meta-signature miRNAs target genes, we performed pathway enrichment and GO molecular function enrichment analysis. A total of 19 upregulated miRNAs and seven downregulated miRNAs in GC samples were identified. However, only three upregulated and one downregulated miRNA reached statistical significance after multiple test correction. Here we showed that hsa-miR-21-5p, hsa-miR-93-5p, hsa-miR-25-3p, and hsa-miR-375 are differentially expressed in GC samples.

Development of sequence-based markers for seed protein content in pigeonpea.

Pigeonpea is an important source of dietary protein to over a billion people globally, but genetic enhancement of seed protein content (SPC) in the crop has received limited attention for a long time. Use of genomics-assisted breeding would facilitate accelerating genetic gain for SPC. However, neither genetic markers nor genes associated with this important trait have been identified in this crop. Therefore, the present study exploited whole genome re-sequencing (WGRS) data of four pigeonpea genotypes (~ 12X coverage) to identify sequence-based markers and associated candidate genes for SPC. By combining a common variant filtering strategy on available WGRS data with knowledge of gene functions in relation to SPC, 108 sequence variants from 57 genes were identified. These genes were assigned to 19 GO molecular function categories with 56% belonging to only two categories. Furthermore, Sanger sequencing confirmed presence of 75.4% of the variants in 37 genes. Out of 30 sequence variants converted into CAPS/dCAPS markers, 17 showed high level of polymorphism between low and high SPC genotypes. Assay of 16 of the polymorphic CAPS/dCAPS markers on an F2 population of the cross ICP 5529 (high SPC) × ICP 11605 (low SPC), resulted in four of the CAPS/dCAPS markers significantly (P < 0.05) co-segregated with SPC. In summary, four markers derived from mutations in four genes will be useful for enhancing/regulating SPC in pigeonpea crop improvement programs.

Exploring genetic susceptibility to obesity through genome functional pathway analysis.

Obesity has been reaching epidemic levels in recent decades, with a growing body of research identifying predisposing genetic components. To explore the relationship of genetic factors contributing to obesity, an analytical computer-based gene-profiling approach utilizing an updated list of clinically relevant and known obesity-related genes was undertaken. An updated list of 494 genes reportedly associated with obesity was compiled, and the GeneAnalytics profiling software was utilized to interrogate genomic databases from GeneCards® to cross-reference obesity gene sets against tissues and cells, diseases, genetic pathways, gene ontology (GO)-biological processes and GO-molecular functions, phenotypes, and compounds. Obesity-related fields identified by GeneAnalytics algorithms included 8 diseases, 46 pathways, 62 biological processes, 22 molecular functions, 148 phenotypes, and 286 compounds impacting adipogenesis, signal transduction by G-protein coupled receptors, and lipid metabolism involving insulin-related genes (IGF1, INS, IRS1). GO-biological processes identified feeding behavior, cholesterol metabolic process, and glucose and cholesterol homeostasis pathways, while GO-molecular processes pertained to receptor binding, affecting glucose homeostasis, body weight, and circulating insulin and triglyceride levels. The gene-profiling model suggests that pathogenesis of obesity relates to the coordination of biological responses to glucose and intracellular lipids possibly through a disruption of biochemical cascades and cellular signaling arising from affected receptors.

Target genes prediction and functional analysis of microRNAs differentially expressed in gastric cancer stem cells MKN-45.

Since mechanisms of microRNAs (miRNAs) in gastric cancer stem cells (CSCs) and their signaling pathways remain unknown, our aim was to predict the miRNA target genes that differentially expressed in gastric CSCs. Using miRanda, PicTar, and TargetScan algorithm, target genes of miRNAs differentially expressed in gastric CSCs versus parental cells were predicted. Afterward, signaling pathways and biological functions of miRNAs in gastric CSCs were analyzed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) database and DIANA tools. Gene ontology (GO) tool indicated that most of miRNA target genes involved in regulation of cell cycle, apoptosis, cell migration, vasculogenesis, angiogenesis, etc. Some of miRNA target genes are connected to pivotal signaling pathways of the "stem cell genes," such as Notch, Wnt/β-catenin. Bioinformatics analysis such as DAVID database, GO biological process, GO molecular function, Kyoto encyclopedia of genes and genomes pathways, BioCarta pathway, Panther pathway, and Reactome pathway revealed that target genes of differentially expressed miRNAs in gastric CSCs were connected to pivotal biological pathways that involved in cell cycle regulation, stemness properties, and differentiation.

Serum MicroRNA Profiling and Bioinformatics of Patients with Spleen-Deficiency Syndrome.

To investigate serum microRNA (miRNA) profile and bioinformatics of patients with spleen-deficiency syndrome (SDS) and explore pathogenesis of SDS patients from miRNA levels, 10 patients with type 2 diabetes mellitus (T2DM), within which 5 patients were with SDS and the remaining were with blood stasis syndrome (BSS), and 5 healthy volunteers were recruited. Serum miRNA profiles of SDS patients were identified by quantitative PCR array. Target prediction and functional annotation for miRNAs were performed by miRSystem database. The present study identified 11 candidate serum miRNAs for SDS patients, and their targets were significantly enriched in 18 KEGG pathways and 7 GO molecular functions. Those enriched KEGG pathways included (1) metabolisms of carbohydrate, protein, amino acid, and fatty acid, (2) signaling pathways of insulin, ErbB, chemokine, calcium, and type II diabetes mellitus, (3) invasions of bacterium, Escherichia coli, and Shigella (Shigellosis), and (4) endocytosis and phagocytosis. Those enriched GO molecular functions were mainly involved in transcription regulation and regulation of metabolism. Our findings might elucidate the pathogenesis of SDS patients with disorders of substance metabolism and hypoimmunity from miRNA levels, as well as providing some miRNA biomarkers for clinical syndrome differentiation of SDS.

Bioinformatics-Based Identification of MicroRNA-Regulated and Rheumatoid Arthritis-Associated Genes.

MicroRNAs (miRNAs) act as epigenetic markers and regulate the expression of their target genes, including those characterized as regulators in autoimmune diseases. Rheumatoid arthritis (RA) is one of the most common autoimmune diseases. The potential roles of miRNA-regulated genes in RA pathogenesis have greatly aroused the interest of clinicians and researchers in recent years. In the current study, RA-related miRNAs records were obtained from PubMed through conditional literature retrieval. After analyzing the selected records, miRNA targeted genes were predicted. We identified 14 RA-associated miRNAs, and their sub-analysis in 5 microarray or RNA sequencing (RNA-seq) datasets was performed. The microarray and RNA-seq data of RA were also downloaded from NCBI Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA), analyzed, and annotated. Using a bioinformatics approach, we identified a series of differentially expressed genes (DEGs) by comparing studies on RA and the controls. The RA-related gene expression profile was thus obtained and the expression of miRNA-regulated genes was analyzed. After functional annotation analysis, we found GO molecular function (MF) terms significantly enriched in calcium ion binding (GO: 0005509). Moreover, some novel dysregulated target genes were identified in RA through integrated analysis of miRNA/mRNA expression. The result revealed that the expression of a number of genes, including ROR2, ABI3BP, SMOC2, etc., was not only affected by dysregulated miRNAs, but also altered in RA. Our findings indicate that there is a close association between negatively correlated mRNA/miRNA pairs and RA. These findings may be applied to identify genetic markers for RA diagnosis and treatment in the future.

Using CATH-Gene3D to Analyze the Sequence, Structure, and Function of Proteins.

The CATH database is a classification of protein structures found in the Protein Data Bank (PDB). Protein structures are chopped into individual units of structural domains, and these domains are grouped together into superfamilies if there is sufficient evidence that they have diverged from a common ancestor during the process of evolution. A sister resource, Gene3D, extends this information by scanning sequence profiles of these CATH domain superfamilies against many millions of known proteins to identify related sequences. Thus the combined CATH-Gene3D resource provides confident predictions of the likely structural fold, domain organisation, and evolutionary relatives of these proteins. In addition, this resource incorporates annotations from a large number of external databases such as known enzyme active sites, GO molecular functions, physical interactions, and mutations. This unit details how to access and understand the information contained within the CATH-Gene3D Web pages, the downloadable data files, and the remotely accessible Web services.

Assessing the impact of case sensitivity and term information gain on biomedical concept recognition.

Concept recognition (CR) is a foundational task in the biomedical domain. It supports the important process of transforming unstructured resources into structured knowledge. To date, several CR approaches have been proposed, most of which focus on a particular set of biomedical ontologies. Their underlying mechanisms vary from shallow natural language processing and dictionary lookup to specialized machine learning modules. However, no prior approach considers the case sensitivity characteristics and the term distribution of the underlying ontology on the CR process. This article proposes a framework that models the CR process as an information retrieval task in which both case sensitivity and the information gain associated with tokens in lexical representations (e.g., term labels, synonyms) are central components of a strategy for generating term variants. The case sensitivity of a given ontology is assessed based on the distribution of so-called case sensitive tokens in its terms, while information gain is modelled using a combination of divergence from randomness and mutual information. An extensive evaluation has been carried out using the CRAFT corpus. Experimental results show that case sensitivity awareness leads to an increase of up to 0.07 F1 against a non-case sensitive baseline on the Protein Ontology and GO Cellular Component. Similarly, the use of information gain leads to an increase of up to 0.06 F1 against a standard baseline in the case of GO Biological Process and Molecular Function and GO Cellular Component. Overall, subject to the underlying token distribution, these methods lead to valid complementary strategies for augmenting term label sets to improve concept recognition.

RNA-seq analysis reveals significant effects of EGFR signalling on the secretome of mesenchymal stem cells.

Bone marrow-derived mesenchymal stem cells (MSCs) contribute to breast cancer progression by releasing soluble factors that sustain tumor progression. MSCs express functional epidermal growth factor receptor (EGFR) and breast cancer cells secrete EGFR-ligands including transforming growth factor-α (TGFα). Using RNA-sequencing, we analysed the whole transcriptome of MSCs stimulated with TGFα. We identified 1,640 highly differentially regulated genes: 967 genes up-regulated with Fold Induction (FI) ≥ 1.50 and 673 genes down-regulated with FI ≤ 0.50. When highly regulated genes were categorized according to GO molecular function classification and KEGG pathways analysis, a large number of genes coding for potentially secreted proteins or surface receptors resulted enriched following TGFα treatment, including VEGFA, IL6, EREG, HB-EGF, LIF, NGF, NRG1, CCL19, CCL2, CCL25 and CXCL3. Secretion of corresponding proteins was confirmed for selected factors. Finally, we identified 4,377 and 4,262 alternatively spliced genes in untreated and TGFα-treated MSCs, respectively. Among these, an unannotated splice variant of VEGFA coding for a secreted VEGF protein of 172 amino acids (VEGFA(172)), was found only in MSCs stimulated with TGFα. These findings suggest that EGFR activation in MSCs leads to a significant change in the expression of a wide array of genes coding for secreted proteins that can significantly enhance tumor progression.

Genetic and cytokine changes associated with symptomatic stages of CLL

The pathogenesis and drug resistance of symptomatic CLL patients involves genetic changes associated with the CLL clone as well as changes within the microenvironment. To further understand these processes, we compared early stage CLL to symptomatic late stage using gene expression and serum cytokine profiling to gain insight of the genetic and microenvironment changes associated with the most severe form of the disease. Patients were classified into low stage (Rai stage 0/I/II) and high stage (Rai stage III/IV). Gene expression profiles were obtained on pretreatment samples using the HG-U133A 2.0 Affymetrix platform. A comparison of low versus high stage CLL revealed a set of 21 genes differentially expressed genes. 15 genes were up regulated in the high stage compared to low stage while 6 genes were down regulated. Analysis of GO molecular function revealed 9 of 21 genes were involved in transcription factor activity. Serum cytokine profiles showed six cytokines to be significantly different in high stage patients. Two chemokines, SDF-1/CXCL12 and uPAR known to be involved in stem cell mobilization and homing were increased in serum of high stage patients. This study has identified therapeutic targets for symptomatic CLL patients.

Development of an expressed gene catalogue and molecular markers from the de novo assembly of short sequence reads of the lentil (Lens culinaris Medik.) transcriptome

Genomic resources such as ESTs, molecular markers and linkage maps are essential for crop improvement. However, these resources are still limited in important legumes such as lentil (Lens culinaris Medik.), which is valued world wide as a rich source of dietary protein. In this study, the de novo transcriptome assembly of 119,855,798 short reads, generated by Illumina paired-end sequencing, was performed using various assembly programs. This resulted in 42,196 nonredundant high-quality transcripts of average length 810 bases, N50 value of 1,432 and an average expression per transcript of 26.21 rpkm reads per kilobase per million(RPKM). Similarity search with the unigenes and protein sequences of other plants resulted in maximum similarity with soybean. A total of 20,009 nonredundant transcripts showed similarity with the UniProtKB database and of these, 18,064 transcripts were grouped into three main GO categories, that is, biological process (15,126), molecular function (15,505) and cellular component (9,434). Annotated transcripts were mapped to 289 predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 8,893 transcripts were classified into 24 functional categories based on Cluster of Orthologous Groups (COG) of proteins. Mining the data set for the presence of SSRs resulted in 8,722 SSRs with a frequency occurrence of one SSR per 3.92 kb. From these, 5,673 SSR primer pairs were designed, and a subset of these were utilized for diversity analysis. This study, which provides a large data set of annotated transcripts and gene-based SSR markers, would serve as a foundation for various applications in lentil breeding and genetics.

FIDEA: a server for the functional interpretation of differential expression analysis

The results of differential expression analyses provide scientists with hundreds to thousands of differentially expressed genes that need to be interpreted in light of the biology of the specific system under study. This requires mapping the genes to functional classifications that can be, for example, the KEGG pathways or InterPro families they belong to, their GO Molecular Function, Biological Process or Cellular Component. A statistically significant overrepresentation of one or more category terms in the set of differentially expressed genes is an essential step for the interpretation of the biological significance of the results. Ideally, the analysis should be performed by scientists who are well acquainted with the biological problem, as they have a wealth of knowledge about the system and can, more easily than a bioinformatician, discover less obvious and, therefore, more interesting relationships. To allow experimentalists to explore their data in an easy and at the same time exhaustive fashion within a single tool and to test their hypothesis quickly and effortlessly, we developed FIDEA. The FIDEA server is located at http://www.biocomputing.it/fidea; it is free and open to all users, and there is no login requirement.

COPRED: prediction of fold, GO molecular function and functional residues at the domain level

Only recently the first resources devoted to the functional annotation of proteins at the domain level started to appear. The next step is to develop specific methodologies for predicting function at the domain level based on these resources, and to implement them in web servers to be used by the community. In this work, we present COPRED, a web server for the concomitant prediction of fold, molecular function and functional sites at the domain level, based on a methodology for domain molecular function prediction and a resource of domain functional annotations previously developed and benchmarked. COPRED can be freely accessed at http://csbg.cnb.csic.es/copred. The interface works in all standard web browsers. WebGL (natively supported by most browsers) is required for the in-line preview and manipulation of protein 3D structures. The website includes a detailed help section and usage examples. pazos@cnb.csic.es.

Genetic and cytokine profiles associated with symptomatic stage of CLL.

7062 Background: Pathogenesis of symptomatic CLL involves genetic changes associated with the CLL clone and changes within the microenvironment which contribute to chemo-resistance. To further understand these processes we compared early stage CLL to symptomatic late stage CLL using gene expression profiling as well as serum cytokine profiling for a better insight of the genetic and microenvironment changes associated with the most severe forms of the disease. Methods: We obtained pretreatment blood samples from CLL patients (10 low stage and 14 high stage) at the time of diagnosis. Patients were classified as low stage (Rai stage 0/I/II) and high stage (Rai stage III/IV). Gene expression profiles were obtained on a subset of patients using the HG-U133A 2.0 Affymetrix platform and analyzed for differential gene expression profiles. Serum from a subset of patients was used to perform cytokine profiling using the Raybiotech Cytokine Array platform (AAH-CYT-G1000) that allows for simultaneous measurement of &gt;100 different cytokines. Results: Comparison of low versus high stage CLL revealed a set of 21 differentially expressed genes. 15 genes were up regulated in the high stage versus low stage, while 6 genes were down regulated. GO Molecular function analysis revealed that 9 of the 21 genes are involved in transcription factor activity. Other genes up regulated in the high stage group include CSNK1- shown to be involved in Myc derived oncogenesis and SETD8- a histone lysine methyltransferase previously implicated in several cancers. Serum cytokine profiles showed 6 cytokines to be significantly different in high stage patients. Two chemokines SDF-1/CXCL12 and uPAR known to be involved in stem cell mobilization and homing are increased in the serum of high stage patients. IGFBP-2, BMP-4 and MCP-4 were lower among high stage patients. Conclusions: Our study revealed a novel group of transcription factors are associated with higher stage CLL. Cytokine profiling showed increased levels of SDF-1/CXCL12, a chemokine that plays a key role in mobilization and homing of hematopoietic stem and CLL cells in high stage patients. Our study identifies putative therapeutic targets including CSNK1, SDF-1 and SETD8 for patients with high stage CLL.

48 IL-6 is Required for Microbiome-Mediated and Innate Immune-Dependent Recruitment of Neutrophils and Macrophages and is Necessary for Mucosal Repair After Intestinal Injury

Background: Current evidence indicates that inflammatory bowel diseases (IBD) may be caused in part by aberrant immune responses to commensal intestinal microbes including Bacteroides thetaiotaomicron (B. theta). Healthy, germ-free HLA-B27 transgenic (Tg) rats develop chronic colitis when colonized with complex gut commensal bacteria or Bacteroides vulgatus whereas non-transgenic (nTg) rats remain disease-free. However, the role of B. theta, a well-characterized anaerobic commensal bacterium, in causing disease in Tg rats is unknown. Moreover, while host immune responses to the gut microbiota have been extensively studied, relatively little is known about how microbes respond to host inflammation. Hypothesis: B. theta monoassociated Tg rats develop chronic, immune-mediated colitis that is associated with transcriptional responses in the bacteria that initiate and perpetuate disease. Methods: Four Tg and five nTg rats were monoassociated with a human isolate of B. theta (VPI-5482) for six weeks. Colonic inflammation was quantified by blinded histological scoring and real-time RT-PCR assays of pro-inflammatory cytokines. Cecal bacterial concentrations were measured by quantitative plating on BHI agar. Whole genome transcriptional profiling of B. theta recovered from the cecum was performed using custom GeneChips and data analyzed using DChip, Significance Analysis of Microarrays, and Gene Set Enrichment Analysis (GSEA) software. Results: B. theta monoassociated Tg rats had significantly more colonic inflammation and increased colonic levels of pro-inflammatory cytokine mRNAs than nTg controls (Table). Transcriptional profiles of cecal B. theta were significantly different in Tg vs. nTg rats (329 transcripts representing 44 KEGG canonical pathways). GSEA revealed that the GO molecular function of receptor activity, which is comprised mainly of genes that encode nutrient binding proteins, was significantly enriched with genes upregulated in B. theta from Tg rats [GSEA false discovery rate (FDR)=0.148]. KEGG canonical pathways of ribosome (FDR=0.048), oxidative phosphorylation (FDR=0.098), pyrimidine metabolism (FDR=0.081), purine metabolism (FDR=0.197), peptidoglycan biosynthesis (FDR=0.184), and metabolism (FDR=0.191) were significantly enriched with genes downregulated in B. theta from Tg rats. Numbers of viable bacteria/gram cecal contents in Tg vs. nTg rats were not significantly different. Conclusions: A well-characterized human isolate of B. theta induces mild colitis in HLA-B27 Tg rats and colitis is associated with changes in the expression of microbial metabolic and nutrient binding pathways, but no difference in concentrations of viable cecal bacteria. Mechanistic studies of differentially expressed B. theta genes may reveal novel pathways that initiate and/or perpetuate IBD.

The zebrafish transcriptome during early development

BackgroundThe transition from fertilized egg to embryo is accompanied by a multitude of changes in gene expression, and the transcriptional events that underlie these processes have not yet been fully characterized. In this study RNA-Seq is used to compare the transcription profiles of four early developmental stages in zebrafish (Danio rerio) on a global scale.ResultsAn average of 79 M total reads were detected from the different stages. Out of the total number of reads 65% - 73% reads were successfully mapped and 36% - 44% out of those were uniquely mapped. The total number of detected unique gene transcripts was 11187, of which 10096 were present at 1-cell stage. The largest number of common transcripts was observed between 1-cell stage and 16-cell stage. An enrichment of gene transcripts with molecular functions of DNA binding, protein folding and processing as well as metal ion binding was observed with progression of development. The sequence data (accession number ERP000635) is available at the European Nucleotide Archive.ConclusionClustering of expression profiles shows that a majority of the detected gene transcripts are present at steady levels, and thus a minority of the gene transcripts clusters as increasing or decreasing in expression over the four investigated developmental stages. The three earliest developmental stages were similar when comparing highly expressed genes, whereas the 50% epiboly stage differed from the other three stages in the identity of highly expressed genes, number of uniquely expressed genes and enrichment of GO molecular functions. Taken together, these observations indicate a major transition in gene regulation and transcriptional activity taking place between the 512-cell and 50% epiboly stages, in accordance with previous studies.

Insights into shell deposition in the Antarctic bivalve Laternula elliptica: gene discovery in the mantle transcriptome using 454 pyrosequencing

BackgroundThe Antarctic clam, Laternula elliptica, is an infaunal stenothermal bivalve mollusc with a circumpolar distribution. It plays a significant role in bentho-pelagic coupling and hence has been proposed as a sentinel species for climate change monitoring. Previous studies have shown that this mollusc displays a high level of plasticity with regard to shell deposition and damage repair against a background of genetic homogeneity. The Southern Ocean has amongst the lowest present-day CaCO3 saturation rate of any ocean region, and is predicted to be among the first to become undersaturated under current ocean acidification scenarios. Hence, this species presents as an ideal candidate for studies into the processes of calcium regulation and shell deposition in our changing ocean environments.Results454 sequencing of L. elliptica mantle tissue generated 18,290 contigs with an average size of 535 bp (ranging between 142 bp-5.591 kb). BLAST sequence similarity searching assigned putative function to 17% of the data set, with a significant proportion of these transcripts being involved in binding and potentially of a secretory nature, as defined by GO molecular function and biological process classifications. These results indicated that the mantle is a transcriptionally active tissue which is actively proliferating. All transcripts were screened against an in-house database of genes shown to be involved in extracellular matrix formation and calcium homeostasis in metazoans. Putative identifications were made for a number of classical shell deposition genes, such as tyrosinase, carbonic anhydrase and metalloprotease 1, along with novel members of the family 2 G-Protein Coupled Receptors (GPCRs). A membrane transport protein (SEC61) was also characterised and this demonstrated the utility of the clam sequence data as a resource for examining cold adapted amino acid substitutions. The sequence data contained 46,235 microsatellites and 13,084 Single Nucleotide Polymorphisms(SNPs/INDELS), providing a resource for population and also gene function studies.ConclusionsThis is the first 454 data from an Antarctic marine invertebrate. Sequencing of mantle tissue from this non-model species has considerably increased resources for the investigation of the processes of shell deposition and repair in molluscs in a changing environment. A number of promising candidate genes were identified for functional analyses, which will be the subject of further investigation in this species and also used in model-hopping experiments in more tractable and economically important model aquaculture species, such as Crassostrea gigas and Mytilus edulis.

한우 cDNA 라이브러리에서 발현된 ESTs의 기능분석

본 연구는 한우의 지방, 간, 등심조직에서 유전자 염기서열을 확보하여 생산된 57,598개의 유전자 발현단편 데이터의 기능규명을 실시하였다. 유전자 발현단편 서열은 Assembly 과정을 통하여 unique한 서열인 4,759 contigs와 7,587 singletons을 확보하였으며, 얻어진 전사체를 이용하여 NCBI의 non-redundant 단백질 데이터베이스에 대하여 서열유사성 검색 (BLAST)을 하여 유전자의 기능을 예측할 수 있었다. 또한 기능에 대한 모호성을 확실히 하기 위해 Gene Ontology 용어를 사용하여 한우의 세 조직에서 확보된 서열들의 생물학적 특성을 기술하였다. Gene Ontology 는 모든 기능이 계층적으로 표현되어 있기 때문에, 각 계층에 대하여 유의적인 기능 여부를 확인하기 위하여 통계 분석인 Pearson's chi-square test를 실시하여 통계적으로 유의한 기능들을 산출할 수 있었다. 그 결과, Molecular function, Biological process, Cellular component 각각의 GO category에서 13, 16, 8개의 유의적인 GO terms이 검출되었다. 또한, 한우의 세 조직에 대하여 조직특이적 유전자의 존재여부를 판단하기 위하여 Audic's test를 실시하여 세 조직에서 각각 조직특이적으로 발현되는 유전자들을 검출할 수 있었다. 이러한 생물정보학적 방법들을 사용하여 한우의 세 조직에서 발현된 대량의 서열들에 대한 기능을 예측할 수 있었으며, 통계 검증을 통하여 유의적으로 검출된 유전자들은 추후에 실험적 검증을 실시하여 충분한 정보를 확보할 수 있을 것으로 사료된다. We generated 57,598 expressed sequence tags (ESTs) from 3 cDNA libraries of Hanwooo (Korean Cattle), fat, loin, liver. Liver, intermuscular fat and longissimus dorsi tissues were obtained from a 24-month-old Hanwoo steer immediately after slaughter. cDNA library was constructed according to the oligocapped method. The EST data were clustered and assembled into unique sequences, 4,759 contigs and 7,587 singletons. To carry out functional analysis, Gene Ontology annotation and identification of significant leaf nodes were performed that were detected by searching significant p-values from <TEX>$2^{nd}$</TEX> level GO terms to leaf nodes using Bonferroni correction. We found that 13, 26 and 8 significant leaf nodes are unique in the transcripts according to 3 GO categories, molecular function, biological process and cellular component. Also digital gene expression profiling using the Audic's test was performed and tissue specific genes were detected in the above 3 libraries.

GO molecular function coding based protein subcellular localization prediction

Subcellular localization is an important feature of proteins which is closely correlated to their function. In this work, we tried to develop a new coding method of using those location predictive molecular function terms of protein as the input for the prediction of subcellular localization. Combined with the amino acid pair composition of the sequence, this coding system is proved to be efficient for support vector machine (SVM) and to have satisfied performance when tested on the RH dataset. Meanwhile, the model also shows robustness against N-terminal uncertainties in sequences.