Expressed Sequence Tag Dataset Research Articles

Large-scale Transcriptome Analyses Reveal New Genetic Marker Candidates of Head, Neck, and Thyroid Cancer

A detailed genome mapping analysis of 213,636 expressed sequence tags (EST) derived from nontumor and tumor tissues of the oral cavity, larynx, pharynx, and thyroid was done. Transcripts matching known human genes were identified; potential new splice variants were flagged and subjected to manual curation, pointing to 788 putatively new alternative splicing isoforms, the majority (75%) being insertion events. A subset of 34 new splicing isoforms (5% of 788 events) was selected and 23 (68%) were confirmed by reverse transcription-PCR and DNA sequencing. Putative new genes were revealed, including six transcripts mapped to well-studied chromosomes such as 22, as well as transcripts that mapped to 253 intergenic regions. In addition, 2,251 noncoding intronic RNAs, eventually involved in transcriptional regulation, were found. A set of 250 candidate markers for loss of heterozygosis or gene amplification was selected by identifying transcripts that mapped to genomic regions previously known to be frequently amplified or deleted in head, neck, and thyroid tumors. Three of these markers were evaluated by quantitative reverse transcription-PCR in an independent set of individual samples. Along with detailed clinical data about tumor origin, the information reported here is now publicly available on a dedicated Web site as a resource for further biological investigation. This first in silico reconstruction of the head, neck, and thyroid transcriptomes points to a wealth of new candidate markers that can be used for future studies on the molecular basis of these tumors. Similar analysis is warranted for a number of other tumors for which large EST data sets are available.

Floral gene resources from basal angiosperms for comparative genomics research

BackgroundThe Floral Genome Project was initiated to bridge the genomic gap between the most broadly studied plant model systems. Arabidopsis and rice, although now completely sequenced and under intensive comparative genomic investigation, are separated by at least 125 million years of evolutionary time, and cannot in isolation provide a comprehensive perspective on structural and functional aspects of flowering plant genome dynamics. Here we discuss new genomic resources available to the scientific community, comprising cDNA libraries and Expressed Sequence Tag (EST) sequences for a suite of phylogenetically basal angiosperms specifically selected to bridge the evolutionary gaps between model plants and provide insights into gene content and genome structure in the earliest flowering plants.ResultsRandom sequencing of cDNAs from representatives of phylogenetically important eudicot, non-grass monocot, and gymnosperm lineages has so far (as of 12/1/04) generated 70,514 ESTs and 48,170 assembled unigenes. Efficient sorting of EST sequences into putative gene families based on whole Arabidopsis/rice proteome comparison has permitted ready identification of cDNA clones for finished sequencing. Preliminarily, (i) proportions of functional categories among sequenced floral genes seem representative of the entire Arabidopsis transcriptome, (ii) many known floral gene homologues have been captured, and (iii) phylogenetic analyses of ESTs are providing new insights into the process of gene family evolution in relation to the origin and diversification of the angiosperms.ConclusionInitial comparisons illustrate the utility of the EST data sets toward discovery of the basic floral transcriptome. These first findings also afford the opportunity to address a number of conspicuous evolutionary genomic questions, including reproductive organ transcriptome overlap between angiosperms and gymnosperms, genome-wide duplication history, lineage-specific gene duplication and functional divergence, and analyses of adaptive molecular evolution. Since not all genes in the floral transcriptome will be associated with flowering, these EST resources will also be of interest to plant scientists working on other functions, such as photosynthesis, signal transduction, and metabolic pathways.

Development of an expressed sequence tag (EST) resource for wheat (Triticum aestivum L.): EST generation, unigene analysis, probe selection and bioinformatics for a 16,000-locus bin-delineated map.

This report describes the rationale, approaches, organization, and resource development leading to a large-scale deletion bin map of the hexaploid (2n = 6x = 42) wheat genome (Triticum aestivum L.). Accompanying reports in this issue detail results from chromosome bin-mapping of expressed sequence tags (ESTs) representing genes onto the seven homoeologous chromosome groups and a global analysis of the entire mapped wheat EST data set. Among the resources developed were the first extensive public wheat EST collection (113,220 ESTs). Described are protocols for sequencing, sequence processing, EST nomenclature, and the assembly of ESTs into contigs. These contigs plus singletons (unassembled ESTs) were used for selection of distinct sequence motif unigenes. Selected ESTs were rearrayed, validated by 5' and 3' sequencing, and amplified for probing a series of wheat aneuploid and deletion stocks. Images and data for all Southern hybridizations were deposited in databases and were used by the coordinators for each of the seven homoeologous chromosome groups to validate the mapping results. Results from this project have established the foundation for future developments in wheat genomics.

Gene Expression Profile of the Mouse Organ of Corti at the Onset of Hearing

We describe the generation of an expressed sequence tag (EST) database of the mouse organ of Corti (OC). Over 20,000 independent clones were isolated, analyzed, and grouped into 8690 unique gene clusters. A large pool of novel genes unique to the OC was identified. Sequence alignments frequently revealed alternatively spliced forms of known genes potentially relevant in the OC function. We have also electronically mapped a subset of OC mouse ESTs to several syntenic regions associated with human autosomal and recessive deafness, which may prove useful for the identification of new positional candidates for these human diseases. The EST dataset is available as an interactive Web-based public database at http://neibank.nei.nih.gov. This resource provides both a view of the profile of gene expression in the OC at the onset of hearing and a tool to identify novel genes of importance in hearing.

Expressed sequence tags: analysis and annotation.

Expressed sequence tags (ESTs) present a special set of problems for bioinformatic analysis. They are partial and error-prone, and large datasets can have significant internal redundancy. To facilitate analysis of small EST datasets from in-house projects, we present an integrated "pipeline" of tools that take EST data from sequence trace to database submission. These tools also can be used to provide clustering of ESTs into putative genes and to annotate these genes with preliminary sequence similarity searches. The systems are written to use the public-domain LINUX environment and other openly available analytical tools.

Large-scale identification and analysis of genome-wide single-nucleotide polymorphisms for mapping in Arabidopsis thaliana.

Genetic markers such as single nucleotide polymorphisms (SNPs) are essential tools for positional cloning, association, or quantitative trait locus mapping and the determination of genetic relationships between individuals. We identified and characterized a genome-wide set of SNP markers by generating 10,706 expressed sequence tags (ESTs) from cDNA libraries derived from 6 different accessions, and by analysis of 606 sequence tagged sites (STS) from up to 12 accessions of the model flowering plant Arabidopsis thaliana. The cDNA libraries for EST sequencing were made from individuals that were stressed by various means to enrich for transcripts from genes expressed under such conditions. SNPs discovered in these sequences may be useful markers for mapping genes involved in interactions with the biotic and abiotic environment. The STS loci are distributed randomly over the genome. By comparison with the Col-0 genome sequence, we identified a total of 8051 SNPs and 637 insertion/deletion polymorphisms (InDel). Analysis of STS-derived SNPs shows that most SNPs are rare, but that it is possible to identify intermediate frequency framework markers that can be used for genetic mapping in many different combinations of accessions. A substantial proportion of SNPs located in ORFs caused a change of the encoded amino acid. A comparison of the density of our SNP markers among accessions in both the EST and STS datasets, revealed that Cvi-0 is the most divergent accession from Col-0 among the 12 accessions studied. All of these markers are freely available via the internet.

Refined annotation of the Arabidopsis genome by complete expressed sequence tag mapping.

Expressed sequence tags (ESTs) currently encompass more entries in the public databases than any other form of sequence data. Thus, EST data sets provide a vast resource for gene identification and expression profiling. We have mapped the complete set of 176,915 publicly available Arabidopsis EST sequences onto the Arabidopsis genome using GeneSeqer, a spliced alignment program incorporating sequence similarity and splice site scoring. About 96% of the available ESTs could be properly aligned with a genomic locus, with the remaining ESTs deriving from organelle genomes and non-Arabidopsis sources or displaying insufficient sequence quality for alignment. The mapping provides verified sets of EST clusters for evaluation of EST clustering programs. Analysis of the spliced alignments suggests corrections to current gene structure annotation and provides examples of alternative and non-canonical pre-mRNA splicing. All results of this study were parsed into a database and are accessible via a flexible Web interface at http://www.plantgdb.org/AtGDB/.

TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets.

TGICL is a pipeline for analysis of large Expressed Sequence Tags (EST) and mRNA databases in which the sequences are first clustered based on pairwise sequence similarity, and then assembled by individual clusters (optionally with quality values) to produce longer, more complete consensus sequences. The system can run on multi-CPU architectures including SMP and PVM.

A novel algorithm for computational identification of contaminated EST libraries.

A key goal of the Human Genome Project was to understand the complete set of human proteins, the proteome. Since the genome sequence by itself is not sufficient for predicting new genes and alternative splicing events that lead to new proteins, expressed sequence tags (ESTs) are used as the primary tool for these purposes. The high prevalence of artifacts in dbEST, however, often leads to invalid predictions. Here we describe a novel method for recognizing genomic DNA contamination and other artifacts that cannot be identified using current EST cleaning techniques. Our method uses the alignment of the entire set of ESTs to the human genome to identify highly contaminated EST libraries. We discovered 53 highly contaminated libraries and a subset of 24 766 ESTs from these libraries that probably represent contamination with genomic DNA, pre-mRNA, and ESTs that span non-canonical introns. Although this is only a small fraction of the entire EST dataset, each contaminating sequence could create a spurious transcript prediction. Indeed, in the clustering and assembly tool that we used, these sequences would have caused incorrect inference of 9575 new splice variants and 6370 new genes. Conclusions based on EST analysis, including prediction of alternative splicing, should be re-evaluated in light of these results. Our method, along with the identified set of contaminated sequences, will be essential for applications that depend on large EST datasets.

PipeOnline 2.0: automated EST processing and functional data sorting.

Expressed sequence tags (ESTs) are generated and deposited in the public domain, as redundant, unannotated, single-pass reactions, with virtually no biological content. PipeOnline automatically analyses and transforms large collections of raw DNA-sequence data from chromatograms or FASTA files by calling the quality of bases, screening and removing vector sequences, assembling and rewriting consensus sequences of redundant input files into a unigene EST data set and finally through translation, amino acid sequence similarity searches, annotation of public databases and functional data. PipeOnline generates an annotated database, retaining the processed unigene sequence, clone/file history, alignments with similar sequences, and proposed functional classification, if available. Functional annotation is automatic and based on a novel method that relies on homology of amino acid sequence multiplicity within GenBank records. Records are examined through a function ordered browser or keyword queries with automated export of results. PipeOnline offers customization for individual projects (MyPipeOnline), automated updating and alert service. PipeOnline is available at http://stress-genomics.org.

Assessment of the parallelization approach of d2_cluster for high-performance sequence clustering.

The exponential increase in expressed sequence tag (EST) sequence data amplifies the computational cost of clustering sequences such that new algorithms are required to analyze data at a greater rate. We have parallelized d2_cluster on a SGI Origin 2000 multiprocessor and observed a speedup of approximately 100x on 126 processors when processing a 15,876 EST dataset. The parallelized d2_cluster code is obtainable from the SANBI website (http://www.sanbi.ac.za/CODES).

Making sense of EST sequences by CLOBBing them

BackgroundExpressed sequence tags (ESTs) are single pass reads from randomly selected cDNA clones. They provide a highly cost-effective method to access and identify expressed genes. However, they are often prone to sequencing errors and typically define incomplete transcripts. To increase the amount of information obtainable from ESTs and reduce sequencing errors, it is necessary to cluster ESTs into groups sharing significant sequence similarity.ResultsAs part of our ongoing EST programs investigating 'orphan' genomes, we have developed a clustering algorithm, CLOBB (Cluster on the basis of BLAST similarity) to identify and cluster ESTs. CLOBB may be used incrementally, preserving original cluster designations. It tracks cluster-specific events such as merging, identifies 'superclusters' of related clusters and avoids the expansion of chimeric clusters. Based on the Perl scripting language, CLOBB is highly portable relying only on a local installation of NCBI's freely available BLAST executable and can be usefully applied to > 95 % of the current EST datasets. Analysis of the Danio rerio EST dataset demonstrates that CLOBB compares favourably with two less portable systems, UniGene and TIGR Gene Indices.ConclusionsCLOBB provides a highly portable EST clustering solution and is freely downloaded from: http://www.nematodes.org/CLOBB

The Brugia malayi genome project: expressed sequence tags and gene discovery

To advance and facilitate molecular studies of Brugia malayi, one of the causative agents of human lymphatic filariasis, an expressed sequence tag (EST)-based gene discovery programme has been carried out. Over 22 000 ESTs have been produced and deposited in the public databases by a consortium of laboratories from endemic and non-endemic countries. The ESTs have been analysed using custom informatic tools to reveal patterns of individual gene expression that may point to potential targets for future research on anti-filarial drugs and vaccines. Many genes first discovered as ESTs are now being analysed by researchers for immunodiagnostic, vaccine and drug target potential. Building on the success of the B. malayi EST programme, significant EST datasets are being generated for a number of other major parasites of humans and domesticated animals, and model parasitic species.

High-throughput identification, database storage and analysis of SNPs in EST sequences.

Single nucleotide polymorphisms (SNPs) are the most frequent form of DNA variation and disease-causing mutations in many genes. Due to their abundance and slow mutation rate within generations, they are thought to be the next generation of genetic markers that can be used in a myriad of important biological, genetic, pharmacological, and medical applications. There are several strategies both experimental, and in-silico for SNP discovery and mapping. Experimental SNP discovery consists of a number of labourious steps that make this process complex and expensive. In-silico discovery has been proposed as an alternative discovery method that makes use and takes advantage of large data sets with potential SNP information that have been generated with other purposes and have not been used as a SNP information source yet. However, in order to successfully apply the in-silico method to large data sets, the following challenges need to be addressed: First it is necessary to build an integrated SNP pipeline that handles data processing steps smoothly from the beginning (collecting sequence information) to end (SNPs in the database). Also, SNP detection tool parameters have to be optimized to satisfy specific goals of the project. Finally, SNP data could not be fully used until the in-silico method is validated experimentally. In this paper we present a design and implementation of an in-silico SNP detection software pipeline that exploits the existence of large EST (expressed sequence tag) data sets and effectively addresses the above challenges. First, the pipeline allows for smooth data transition between its different components by implementing data interfaces that translate the data formats of the different tools in the different stages. Second, we optimized PolyBayes parameters for SNP detection in maize EST. Finally, we implemented a user interface that along with the database structure created allows the scientist to perform preliminary analysis of the data and to perform basic statistics on the SNP data prior to experimental validation. The pipeline works with two different types of sequence assemblers (PHRAP (http://www.phrap.org/) and CAT from DoubleTwist (http://www.doubletwist.com/). It uses a Bayesian engine for SNP detection (PolyBayes), selects relevant polymorphism information which is then uploaded into a database. We detected 2439 SNPs and 822 insertion deletions (INDELs) with a PolyBayes probability higher than 0.99 on the public set of 68,000 maize ESTs. The user interface allowed us analyzing the polymorphism information right after discovery in several ways that allowed us to gain insight into the distribution and significance of the newly acquired data.

Gene expression in CD34(+) cells from normal bone marrow and leukemic origins.

To address the molecular regulation of hematopoiesis and the complex mechanism in leukemogenesis, we established the first catalogs of genes expressed in normal bone marrow and leukemia CD34(+) cells. CD34(+) cell cDNA libraries were constructed using mRNA from adult bone marrow and from a case of acute myeloid leukemia-M5 transformed from myelodysplastic syndrome (MDS-AML). Expressed sequence tags (ESTs) and full-length cDNAs were generated by sequencing and were annotated using bioinformatic tools. From a total of 4142 ESTs obtained from normal bone marrow, 3424 meaningful tags were integrated into 1630 clusters, representing 622 known genes, 522 dbEST entries and 486 novel sequences. Out of 5382 ESTs from MDS-AML, 1985 clusters were produced based on the analysis of 4321 useful ESTs, including 711 known genes, 657 known ESTs and 617 novel sequences. Among 251 transcripts found in both bone marrow and MDS-AML EST datasets and those present in only one dataset, 58 showed statistically significant differences in EST copy numbers between the two tissues (P<0.05). Twenty putative full-length cDNAs for novel genes were also cloned from the MDS-AML library. The distinct gene expression patterns in MDS-AML-CD34(+) cells as compared to normal control cells may contribute to the development and/or maintenance of the malignant phenotypes of leukemia cells.

A survey of genes in Eimeria tenella merozoites by EST sequencing

A study of about 500 expressed sequence tags (ESTs), derived from a merozoite cDNA library, was initiated as an approach to generate a larger pool of gene information on Eimeria tenella. Of the ESTs, 47.7% had matches with entries in the databases, including ribosomal proteins, metabolic enzymes and proteins with other functions, of which 14.3% represented previously known E. tenella genes. Thus over 50% of the ESTs had no significant database matches. The E. tenella EST dataset contained a range of highly abundant genes comparable with that found in the EST dataset of T. gondii and may thus reflect the importance of such molecules in the biology of the apicomplexan organisms. However, comparison of the two datasets revealed very few homologies between sequences of apical organelle molecules, and provides evidence for sequence divergence between these closely-related parasites. The data presented underpin the potential value of the EST strategy for the discovery of novel genes and may allow for a more rapid increase in the knowledge and understanding of gene expression in the merozoite life cycle stage of Eimeria spp.

Mining SNPs From EST Databases

There is considerable interest in the discovery and characterization of single nucleotide polymorphisms (SNPs) to enable the analysis of the potential relationships between human genotype and phenotype. Here we present a strategy that permits the rapid discovery of SNPs from publicly available expressed sequence tag (EST) databases. From a set of ESTs derived from 19 different cDNA libraries, we assembled 300,000 distinct sequences and identified 850 mismatches from contiguous EST data sets (candidate SNP sites), without de novo sequencing. Through a polymerase-mediated, single-base, primer extension technique, Genetic Bit Analysis (GBA), we confirmed the presence of a subset of these candidate SNP sites and have estimated the allele frequencies in three human populations with different ethnic origins. Altogether, our approach provides a basis for rapid and efficient regional and genome-wide SNP discovery using data assembled from sequences from different libraries of cDNAs.

Identification of Sequence-Tagged Transcripts Differentially Expressed within the Human Hematopoietic Hierarchy

Hematopoiesis is regulated by a complex gene expression program. To gain further insight into the molecular mechanisms underlying this process in humans, we sampled the transcriptional activity of the CD34+hematopoietic progenitor line KG1a by single-pass sequencing the 5′ ends of 1018 clones from a unidirectional cDNA library. Searches of public databases with the resulting expressed sequence tags (ESTs) identified 101 clones that showed no sequence similarity to any of the existing entries and that were therefore considered to derive from previously undescribed genes. Of the remaining 917 ESTs, 553 (a total of 485 distinct transcripts) corresponded to known genes. A further 279 KG1a ESTs matched or exhibited sequence similarity to ESTs or genomic sequences from humans and other species. Among the latter were putative human orthologs of developmental and cell cycle control genes fromCaenorhabditis elegans, Drosophila,and yeast, as well as genes whose predicted amino acid sequences showed similarity to mammalian transcription factors. Hybridization of selected novel KG1a ESTs to globally amplified cDNAs prepared from single primary human hematopoietic precursors and homogeneous populations of terminally maturing hematopoietic cells revealed transcripts that are expressed preferentially at a specific stage or in a particular lineage within the hematopoietic hierarchy. Thus, included in the KG1a EST dataset are candidates for new human genes that may play roles in hematopoietic differentiative progression and lineage commitment.

A quality control algorithm for DNA sequencing projects.

Heterologous DNA sequences from rearrangements with the genomes of host cells, genomic fragments from hybrid cells, or impure tissue sources can threaten the purity of libraries that are derived from RNA or DNA. Hybridization methods can only detect contaminants from known or suspected heterologous sources, and whole library screening is technically very difficult. Detection of contaminating heterologous clones by sequence alignment is only possible when related sequences are present in a known database. We have developed a statistical test to identify heterologous sequences that is based on the differences in hexamer composition of DNA from different organisms. This test does not require that sequences similar to potential heterologous contaminants are present in the database, and can in principle detect contamination by previously unknown organisms. We have applied this test to the major public expressed sequence tag (EST) data sets to evaluate its utility as a quality control measure and a peer evaluation tool. There is detectable heterogeneity in most human and C.elegans EST data sets but it is not apparently associated with cross-species contamination. However, there is direct evidence for both yeast and bacterial sequence contamination in some public database sequences annotated as human. Results obtained with the hexamer test have been confirmed with similarity searches using sequences from the relevant data sets.