SEARCH · PubMed Health

Results for “Bioinformatics analysis”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,153 records · Page 64Linked to original sources

PubMed2005

Novel strategy for protein exploration: high-throughput screening assisted with fuzzy neural network.

To engineer proteins with desirable characteristics from a naturally occurring protein, high-throughput screening (HTS) combined with directed evolutional approach is the essential technology. However, most HTS techniques are simple positive screenings. The information obtained from the positive candidates is used only as results but rarely as clues for understanding the structural rules, which may explain the protein activity. In here, we have attempted to establish a novel strategy for exploring functional proteins associated with computational analysis. As a model case, we explored lipases with inverted enantioselectivity for a substrate p-nitrophenyl 3-phenylbutyrate from the wild-type lipase of Burkhorderia cepacia KWI-56, which is originally selective for (S)-configuration of the substrate. Data from our previous work on (R)-enantioselective lipase screening were applied to fuzzy neural network (FNN), bioinformatic algorithm, to extract guidelines for screening and engineering processes to be followed. FNN has an advantageous feature of extracting hidden rules that lie between sequences of variants and their enzyme activity to gain high prediction accuracy. Without any prior knowledge, FNN predicted a rule indicating that "size at position L167," among four positions (L17, F119, L167, and L266) in the substrate binding core region, is the most influential factor for obtaining lipase with inverted (R)-enantioselectivity. Based on the guidelines obtained, newly engineered novel variants, which were not found in the actual screening, were experimentally proven to gain high (R)-enantioselectivity by engineering the size at position L167. We also designed and assayed two novel variants, namely FIGV (L17F, F119I, L167G, and L266V) and FFGI (L17F, L167G, and L266I), which were compatible with the guideline obtained from FNN analysis, and confirmed that these designed lipases could acquire high inverted enantioselectivity. The results have shown that with the aid of bioinformatic analysis, high-throughput screening can expand its potential for exploring vast combinatorial sequence spaces of proteins.

Fuzzy Logic↗

PubMed2003

Genome-based bioinformatic selection of chromosomal Bacillus anthracis putative vaccine candidates coupled with proteomic identification of surface-associated antigens.

Bacillus anthracis (Ames strain) chromosome-derived open reading frames (ORFs), predicted to code for surface exposed or virulence related proteins, were selected as B. anthracis-specific vaccine candidates by a multistep computational screen of the entire draft chromosome sequence (February 2001 version, 460 contigs, The Institute for Genomic Research, Rockville, Md.). The selection procedure combined preliminary annotation (sequence similarity searches and domain assignments), prediction of cellular localization, taxonomical and functional screen and additional filtering criteria (size, number of paralogs). The reductive strategy, combined with manual curation, resulted in selection of 240 candidate ORFs encoding proteins with putative known function, as well as 280 proteins of unknown function. Proteomic analysis of two-dimensional gels of a B. anthracis membrane fraction, verified the expression of some gene products. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry analyses allowed identification of 38 spots cross-reacting with sera from B. anthracis immunized animals. These spots were found to represent eight in vivo immunogens, comprising of EA1, Sap, and 6 proteins whose expression and immunogenicity was not reported before. Five of these 8 immunogens were preselected by the bioinformatic analysis (EA1, Sap, 2 novel SLH proteins and peroxiredoxin/AhpC), as vaccine candidates. This study demonstrates that a combination of the bioinformatic and proteomic strategies may be useful in promoting the development of next generation anthrax vaccine.

Adhesins, Bacterial↗

PubMed2025

Comprehensive analysis of a novel LYST mutation in a Tunisian patient with Chediak-Higashi syndrome.

BACKGROUND: Chediak-Higashi Syndrome (CHS) is a rare autosomal recessive disorder characterized by oculocutaneous albinism, recurrent infections, bleeding tendencies, and progressive neurological impairment. The syndrome is caused by mutations in the LYST gene, which plays a crucial role in lysosomal trafficking. OBJECTIVE: This study aims to characterize the molecular basis of CHS in a Tunisian patient by identifying mutations in the LYST gene and analyzing their impact on the protein function, correlating these findings with the patient's clinical presentation. METHODS: A comprehensive clinical assessment was conducted on the patient, followed by biochemical, hematological, and microbiological analyses. Additionally, LYST protein levels were quantified in the patient and their parents using an ELISA assay. Genomic DNA was extracted from the patient's blood, and Whole Exome Sequencing (WES) was performed to identify mutations in the LYST gene. The findings were confirmed through Sanger sequencing, and bioinformatic tools were employed to predict the functional consequences of the detected mutations. RESULTS: The patient presented with classical symptoms of CHS, including silver hair, hypopigmented skin, recurrent infections, and neurological decline, with an unusually late onset at 18 years. ELISA results demonstrated significantly reduced LYST levels in the patient (1.8 ng/ml) compared to heterozygous parents (7.8 ng/ml and 8.1 ng/ml) and controls (9.2 ng/ml). Genetic analysis revealed a novel homozygous deletion, c.10269_10275del (p.Gly3424SerfsTer15), in the LYST gene, leading to a frameshift mutation and premature termination of the protein. Bioinformatic analysis demonstrated that this mutation leads to the deletion of five out of sven WD40 repeats in the protein's C-terminal region, which are critical for protein-protein interactions and lysosomal trafficking. CONCLUSION: The study identifies a novel LYST mutation in a Tunisian patient with CHS, expanding the spectrum of known genetic variants associated with the disease. The findings highlight the importance of genetic screening in populations with high consanguinity and underscore the need for targeted therapies to address the molecular defects in CHS.

Adolescent↗

PubMed2003

Diagnosis of Ovarian Cancer Using Decision Tree Classification of Mass Spectral Data.

Recent reports from our laboratory and others support the SELDI ProteinChip technology as a potential clinical diagnostic tool when combined with $n$ -dimensional analyses algorithms. The objective of this study was to determine if the commercially available classification algorithm biomarker patterns software (BPS), which is based on a classification and regression tree (CART), would be effective in discriminating ovarian cancer from benign diseases and healthy controls. Serum protein mass spectrum profiles from 139 patients with either ovarian cancer, benign pelvic diseases, or healthy women were analyzed using the BPS software. A decision tree, using five protein peaks resulted in an accuracy of 81.5% in the cross-validation analysis and 80%in a blinded set of samples in differentiating the ovarian cancer from the control groups. The potential, advantages, and drawbacks of the BPS system as a bioinformatic tool for the analysis of the SELDI high-dimensional proteomic data are discussed.

Journal Article↗

PubMed2000

Functional genomic analysis in arthritis-affected cartilage: yin-yang regulation of inflammatory mediators by alpha 5 beta 1 and alpha V beta 3 integrins.

Osteoarthritis-affected cartilage exhibits enhanced expression of fibronectin (FN) and osteopontin (OPN) mRNA in differential display and bioinformatics screen. Functional genomic analysis shows that the engagement of the integrin receptors alpha 5 beta 1 and alpha v beta 3 of FN and OPN, respectively, have profound effects on chondrocyte functions. Ligation of alpha 5 beta 1 using activating mAb JBS5 (which acts as agonist similar to FN N-terminal fragment) up-regulates the inflammatory mediators such as NO and PGE2 as well as the cytokines, IL-6 and IL-8. Furthermore, up-regulation of these proinflammatory mediators by alpha 5 beta1 integrin ligation is mediated via induction and autocrine production of IL-1 beta, because type II soluble IL-1 decoy receptor inhibits their production. In contrast, alpha v beta 3 complex-specific function-blocking mAb (LM609), which acts as an agonist similar to OPN, attenuates the production of IL-1 beta, NO, and PGE2 (triggered by alpha 5 beta 1, IL-1 beta, IL-18, or IL-1 beta, TNF-alpha, plus LPS) in a dominant negative fashion by osteoarthritis-affected cartilage and activated bovine chondrocytes. These data demonstrate a cross-talk in signaling mechanisms among integrins and show that integrin-mediated "outside in" and "inside out" signaling very likely influences cartilage homeostasis, and its deregulation may play a role in the pathogenesis of osteoarthritis.

Adult↗

PubMed2001

A classification of tasks in bioinformatics.

MOTIVATION: This paper reports on a survey of bioinformatics tasks currently undertaken by working biologists. The aim was to find the range of tasks that need to be supported and the components needed to do this in a general query system. This enabled a set of evaluation criteria to be used to assess both the biology and mechanical nature of general query systems. RESULTS: A classification of the biological content of the tasks gathered offers a checklist for those tasks (and their specialisations) that should be offered in a general bioinformatics query system. This semantic analysis was contrasted with a syntactic analysis that revealed the small number of components required to describe all bioinformatics questions. Both the range of biological tasks and syntactic task components can be seen to provide a set of bioinformatics requirements for general query systems. These requirements were used to evaluate two bioinformatics query systems.

Computational Biology↗

PubMed1999

Disruption of six novel ORFs on the left arm of chromosome XII reveals one gene essential for vegetative growth of Saccharomyces cerevisiae.

Deletion via PCR-mediated gene replacement, together with basic functional and bioinformatic analyses, have been performed on six novel open reading-frames (ORFs) on the left arm of chromosome XII of Saccharomyces cerevisiae(YLL033w, YLL032c, YLL031c, YLL030c, YLL029w and YLL028w). ORF deletion was realized using either a short-flanking homology (SFH) or a long-flanking homology (LFH) replacement cassette in the diploid strain FY1679. Sporulation and tetrad analysis showed that YLL031c is the only essential gene of the six. Microscopic examination of the non-growing spores carrying a disrupted copy of the essential gene showed that most of them were blocked after one or two cell divisions with heterogeneous bud size. The standard EUROFAN growth tests failed to reveal any obvious phenotype resulting from the deletion of each the five non-essential ORFs. Bioinformatic analysis revealed that YLL029w is probably an aminopeptidase for mitochondrial or nuclear protein processing and YLL028w may be involved in drug resistance in S. cerevisiae. Replacement cassettes, comprising the promoter and terminator regions of each of the six ORFs, were cloned into pUG7 and demonstrated to efficiently mediate gene replacement in an alternative diploid strain, W303. All the cognate gene clones were constructed, using either PCR products amplified from genomic DNA, or gap-repair. All clones and strains generated have been deposited in the EUROFAN genetic stock centre (EUROSCARF, Frankfurt).

Alleles↗

PubMed2005

Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice.

Activation of the mesolimbic dopamine reward pathway by acute ethanol produces reinforcement and changes in gene expression that appear to be crucial to the molecular basis for adaptive behaviors and addiction. The inbred mouse strains DBA/2J and C57BL/6J exhibit contrasting acute behavioral responses to ethanol. We used oligonucleotide microarrays and bioinformatics methods to characterize patterns of gene expression in three brain regions of the mesolimbic reward pathway of these strains. Expression profiling included examination of both differences in gene expression 4 h after saline injection or acute ethanol (2 g/kg). Using a rigorous stepwise method for microarray analysis, we identified 788 genes differentially expressed in control DBA/2J versus C57BL/6J mice and 307 ethanol-regulated genes in the nucleus accumbens, prefrontal cortex, and ventral tegmental area. There were strikingly divergent patterns of ethanol-responsive gene expression in the two strains. Ethanol-responsive genes also showed clustering at discrete chromosomal regions, suggesting local chromatin effects in regulation. Ethanol-regulated genes were generally related to neuroplasticity, but regulation of discrete functional groups and pathways was brain region specific: glucocorticoid signaling, neurogenesis, and myelination in the prefrontal cortex; neuropeptide signaling and developmental genes, including factor Bdnf, in the nucleus accumbens; and retinoic acid signaling in the ventral tegmental area. Bioinformatics analysis identified several potential candidate genes for quantitative trait loci linked to ethanol behaviors, further supporting a role for expression profiling in identifying genes for complex traits. Brain region-specific changes in signaling and neuronal plasticity may be critical components in development of lasting ethanol behavioral phenotypes such as dependence, sensitization, and craving.

Animals↗

PubMed2005

Bioinformatics approaches and resources for single nucleotide polymorphism functional analysis.

Since the initial sequencing of the human genome, many projects are underway to understand the effects of genetic variation between individuals. Predicting and understanding the downstream effects of genetic variation using computational methods are becoming increasingly important for single nucleotide polymorphism (SNP) selection in genetics studies and understanding the molecular basis of disease. According to the NIH, there are now more than four million validated SNPs in the human genome. The volume of known genetic variations lends itself well to an informatics approach. Bioinformaticians have become very good at functional inference methods derived from functional and structural genomics. This review will present a broad overview of the tools and resources available to collect and understand functional variation from the perspective of structure, expression, evolution and phenotype. Additionally, public resources available for SNP identification and characterisation are summarised.

Algorithms↗

PubMedDate not supplied

Molecular profiling of temporal lobe epilepsy: comparison of data from human tissue samples and animal models.

The advent of gene chip technology and the era of functional genomics have initially been accompanied by huge anticipations to quickly unravel the molecular pathogenesis of multifactorial diseases. Expectations have, today, given way to some concerns about this non-hypothesis driven approach. However, the careful and controlled application of expression microarrays in concert with refined bioinformatic tools may provide novel insights in major disorders particularly of highly complex organs such as the central nervous system (CNS). Epilepsies are among the most frequent CNS disorders affecting approximately 1.5% of the population worldwide. In temporal lobe epilepsy (TLE), the seizure origin typically involves the hippocampal formation, a structure located in the mesial temporal lobe. Many TLE patients develop pharmacoresistance, i.e. seizures can no more be controlled by antiepileptic drugs. In order to achieve seizure control, surgical removal of the epileptogenic focus has been established as successful therapeutic strategy. Hippocampal biopsy tissue of pharmacoresistant TLE patients represents an excellent substrate to analyze molecular mechanisms related to structural and cellular reorganization in epilepsy. The complexity of alterations in TLE hippocampi suggests numerous genes and signaling cascades to be involved in the pathogenesis. By microarrays, genome wide expression profiles can be constituted from TLE tissues. However, hippocampi of pharmacoresistant TLE patients represent an advanced stage of the disease. Early stages of epilepsy development are not available for functional genome analysis in humans. Animal models of TLE appear particularly helpful to study molecular mechanisms of highly dynamic processes such as the development of hyperexcitability and pharmacoresistance. In this review, we summarize recent data of gene expression profiles in human and experimental TLE and discuss the relevance of novel tools for bioinformatic analysis and data mining.

Animals↗

PubMed2004

Principle component analysis in F/10 and G/11 xylanase.

A bioinformatics method was used to analyze F/10 and G/11 xylanase basing on principle component analysis, and a model was made to classify between these two folds with an ideal result. The principle components were predicated to be secondary structures, the components were analyzed with the architecture of each family, and found comparable with (beta/alpha)(8)-barrel of F/10 xylanase and right-hand structure of G/11 xylanase. Compared with sequence similarities, this method gave discriminating features a clear meaning. The largest component did not appear in the model, which revealed no difference between these two families.

Amino Acid Sequence↗

PubMed2003

Bioinformatics research on inter-racial difference in drug metabolism II. Analysis on relationship between enzyme activities of CYP2D6 and CYP2C19 and their relevant genotypes.

The enzyme activities of CYP2D6 and CYP2C19 show a genetic polymorphism, and the frequency of poor metabolizers (PMs) on these enzymes depends on races. We have analyzed frequencies of mutant alleles and PMs based on the published data in previous study (Shimizu, T. et al.: Bioinformatics research on inter-racial difference in drug metabolism, I. Analysis on frequencies of mutant alleles and poor metabolizers on CYP2D6 and CYP2C19.). The study shows that there were racial differences in the frequencies of each mutant allele and PMs. In the present study, the correlation between genotypes and drug-metabolizing enzyme activities was investigated. The result showed that enzyme activities varied according to the genotypes of subjects even in the same race. On the other hand, if subjects had the same genotypes, almost no racial differences were observed in drug-metabolizing enzyme activities. From these results, it was supposed that the racial differences in activities of these enzymes could be explained by the differences in distribution of genotypes. It would be possible to explain the racial differences in drug-metabolizing enzyme activities based on the differences on individual pharmacogenetic background information, not merely by comparison of frameworks such as races and nations.

Journal Article↗

PubMed2005

Databases, models, and algorithms for functional genomics: a bioinformatics perspective.

A variety of patterns have been observed on the DNA and protein sequences that serve as control points for gene expression and cellular functions. Owing to the vital role of such patterns discovered on biological sequences, they are generally cataloged and maintained within internationally shared databases. Furthermore,the variability in a family of observed patterns is often represented using computational models in order to facilitate their search within an uncharacterized biological sequence. As the biological data is comprised of a mosaic of sequence-levels motifs, it is significant to unravel the synergies of macromolecular coordination utilized in cell-specific differential synthesis of proteins. This article provides an overview of the various pattern representation methodologies and the surveys the pattern databases available for use to the molecular biologists. Our aim is to describe the principles behind the computational modeling and analysis techniques utilized in bioinformatics research, with the objective of providing insight necessary to better understand and effectively utilize the available databases and analysis tools. We also provide a detailed review of DNA sequence level patterns responsible for structural conformations within the Scaffold or Matrix Attachment Regions (S/MARs).

Animals↗

PubMed2005

Support vector machines for prediction and analysis of beta and gamma-turns in proteins.

Tight turns have long been recognized as one of the three important features of proteins, together with alpha-helix and beta-sheet. Tight turns play an important role in globular proteins from both the structural and functional points of view. More than 90% tight turns are beta-turns and most of the rest are gamma-turns. Analysis and prediction of beta-turns and gamma-turns is very useful for design of new molecules such as drugs, pesticides, and antigens. In this paper we investigated two aspects of applying support vector machine (SVM), a promising machine learning method for bioinformatics, to prediction and analysis of beta-turns and gamma-turns. First, we developed two SVM-based methods, called BTSVM and GTSVM, which predict beta-turns and gamma-turns in a protein from its sequence. When compared with other methods, BTSVM has a superior performance and GTSVM is competitive. Second, we used SVMs with a linear kernel to estimate the support of amino acids for the formation of beta-turns and gamma-turns depending on their position in a protein. Our analysis results are more comprehensive and easier to use than the previous results in designing turns in proteins.

Algorithms↗

PubMed2026

Molecular Evolution and Expression Analysis of the ADH Gene Family in Apple Bud Mutants.

Alcohol dehydrogenase (ADH) catalyzes the reduction of aldehydes to alcohols, key precursor substrates for volatile ester biosynthesis, which determines the characteristic aroma of apple fruit. However, a comprehensive genome-wide investigation of the ADH gene family in apple has been lacking. In this study, we systematically identified ADH genes in the apple genome using integrated bioinformatics approaches, including phylogenetic analysis, synteny evaluation, promoter cis-element prediction, codon usage bias assessment, and protein interaction network modeling. Expression patterns were examined through transcriptomic data and validated by RT-qPCR analysis across different organs and among 'Red Delicious' and its four bud mutant lines. We identified 44 ADH genes, with 12 forming a prominent cluster on chromosome 1. RT-qPCR analysis revealed that MdADH20 was dramatically upregulated in the 'Red Chief' mutant (relative expression of 59.38), suggesting its pivotal role. Phylogenetic analysis revealed a close evolutionary relationship with wild strawberry. The encoded proteins were generally stable and predominantly localized to the cytoplasm. Promoter analysis showed enrichment of growth/development-related and ARE elements, while codon usage analysis identified AGA, GCU, GUU, and CUU as preferred codons. Protein interaction prediction suggested MdADH19 and MdADH20 as hub proteins. Expression profiling and RT-qPCR further identified MdADH20 as a core candidate gene, characterized by its stable and high expression, particularly in the 'Red Delicious' mutant. Its central position in the predicted protein-protein interaction network suggests a potential regulatory role in the aroma biosynthesis pathway of apple fruit. This study provides the first systematic genome-wide characterization of the apple ADH gene family, establishing a theoretical groundwork for deciphering aroma biosynthesis mechanisms and offering potential target genes for flavor improvement through bud mutation breeding strategies.

ADH gene family↗

PubMed2025

NRG-P0074 Viral Sample RU1 from Unclassified Mosigvirus Genomic Characterization and Host Range Analysis.

BACKGROUND: Machine learning models for phage-host range prediction and design require comprehensive training data on phage genomes and host ranges to predict phage-host interactions effectively. MATERIALS AND METHODS: This study characterizes phage sample NRG-P0074 viral sample RU1 from unclassified Mosigvirus, originally isolated by the Betty Kutter. The complete genome of NRG-P0074 was sequenced, annotated, and analyzed using various bioinformatic tools. Host range analysis was conducted using the Escherichia coli Reference (ECOR) Library and nine Escherichia coli (E. coli) K12 strains (Keio Knockout Collection) with single nonessential gene deletions. RESULTS: The genome of NRG-P0074 spans 168,357 base pairs with a guanine-cytosine (GC) content of 37.5%. NRG-P0074 exhibited permissiveness in 15.28% of the ECOR isolates and all 9 Keio knockout strains. Comparative genomic analysis revealed that NRG-P0074 is closely related to E. coli phage a20. Its genome is comprised of 270 coding sequences, 153 known genes, 16 terminators, 3 ribosomal-binding sites, 0 tRNAs, and 117 hypothetical proteins. CONCLUSIONS: This research provides valuable data for developing machine learning models to predict phage-host interactions, aiding the development of targeted phage therapies against antibiotic-resistant bacteria.

ECOR Library↗

PubMed2026

Non-small cell lung cancer and tumor-educated platelets: screening of biomarkers and construction of a prognostic model.

BACKGROUND: Lung cancer is a leading cause of cancer-related mortality worldwide, emphasizing the urgent need for effective early detection strategies. Traditional Chinese medicine (TCM) provides a unique perspective on tumor pathogenesis, focusing on concepts such as "long-term stasis leading to accumulation". Tumor-educated platelets (TEPs) offer potential as biomarkers due to their ability to reflect cancer heterogeneity and facilitate less invasive diagnostic approaches. This study aims to identify TEP-related prognostic biomarkers for non-small cell lung cancer (NSCLC) and to construct and validate a multigene prognostic model by integrating platelet transcriptomic data with tumor tissue datasets. METHODS: We performed comprehensive analysis of gene expression datasets obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories to characterize transcriptomic differences among lung cancer specimens, normal tissue samples, and TEPs. Using R software, we identified Differentially expressed genes (DEGs) and subsequently applied a multi-stage analytical pipeline to TEP-associated DEGs, incorporating univariate Cox proportional hazards regression, least absolute shrinkage and selection operator (LASSO) regression, multivariate Cox regression, and stepwise regression modeling to pinpoint genes with prognostic significance. These prognostically relevant genes served as the foundation for developing a risk stratification model. We computed individual risk scores across both training and validation cohorts, enabling patient stratification into high- and low-risk categories. Model robustness was assessed through internal cross-validation and external validation procedures, while predictive performance was quantified using risk calibration metrics and receiver operating characteristic (ROC) curve analysis. RESULTS: Through systematic bioinformatics screening, we identified a four-gene prognostic signature comprising NELL2, C4orf48, PRAM1, and KLHL35, which served as the foundation for developing our risk stratification algorithm. Rigorous internal cross-validation and external cohort validation substantiated the moderate predictive performance of this signature. Comprehensive clinicopathological correlation analysis revealed that elevated risk indices, advanced pathological staging (stage III-IV), increased primary tumor dimensions, regional lymph node metastasis, and distant organ dissemination each demonstrated statistically significant associations with diminished overall survival (OS) outcomes in lung cancer patients. The clinical nomogram exhibited acceptable calibration, with calibration plots showing reasonable concordance between predicted and observed survival probabilities across all time points. Discriminative capacity assessment via time-dependent ROC analysis yielded area under the curve (AUC) values consistently surpassing 0.6, confirming moderate prognostic discrimination. Furthermore, decision curve analysis (DCA) demonstrated that our integrated multi-gene model conferred potential net clinical benefit compared to individual prognostic variables across the full spectrum of clinically relevant threshold probabilities (0-1 range), thereby establishing its potential utility for risk-informed clinical decision-making. CONCLUSIONS: This study identified NELL2, C4orf48, PRAM1, and KLHL35 as candidate TEP-related prognostic biomarkers for non-small cell lung cancer (NSCLC). The developed prognostic model shows preliminary potential for patient stratification, but its clinical application, particularly as a platelet-based liquid biopsy tool, requires further validation in independent TEP-based cohorts.

Tumor-educated platelets (TEPs)↗

PubMed2005

Expressed sequence tag analysis of zebrafish eye tissues for NEIBank.

PURPOSE: To characterize gene expression patterns in various tissues of the zebrafish (Danio rerio) eye and identify zebrafish orthologs of human genes by expressed sequence tag (EST) analysis for NEIBank. METHODS: mRNA was extracted from adult zebrafish eye tissues, including lenses, anterior segments (minus lens), retinas, posterior segments lacking retinas, and whole eyes. Five different cDNA libraries were constructed in the pCMVSport6 vector. Approximately 4,000 clones from each library were sequenced and analyzed using various bioinformatics programs. RESULTS: The analysis yielded approximately 2,500 different gene clusters for each library. Combining data from the five libraries produced 10,392 unique gene clusters. GenBank accession numbers were identified for 37.6% (3,906) of the total gene clusters in the combined libraries and approximately 50% were linked to Unigene clusters in the current database. Several new crystallin genes, including two gammaN-crystallins, and a second major intrinsic protein (MIP) were identified in the lens library. In addition, a zebrafish homolog of cochlin (COCH), a gene that may play a role in the pathogenesis of human glaucoma, was identified in the anterior segment library. Surprisingly, no clear ortholog of the major retinal transcription factor Nrl was identified. CONCLUSIONS: The zebrafish eye tissue cDNA libraries are a useful resource for comparative gene expression analysis. These libraries will complement the cDNA libraries made for the Zebrafish Gene Collection (ZGC) and provide an additional source for gene identification and characterization in the vertebrate eye.

Animals↗