The use of EST expression matrixes for the quality control of gene expression data

EST expression profiling provides an attractive tool for studying differential gene expression, but cDNA libraries' origins and EST data quality are not always known or reported. Libraries may originate from pooled or mixed tissues; EST clustering, EST counts, library annotations and analysis algorithms may contain errors. Traditional data analysis methods, including research into tissue-specific gene expression, assume EST counts to be correct and libraries to be correctly annotated, which is not always the case. Therefore, a method capable of assessing the quality of expression data based on that data alone would be invaluable for assessing the quality of EST data and determining their suitability for mRNA expression analysis. Here we report an approach to the selection of a small generic subset of 244 UniGene clusters suitable for identification of the tissue of origin for EST libraries and quality control of the expression data using EST expression information alone. We created a small expression matrix of UniGene IDs using two rounds of selection followed by two rounds of optimisation. Our selection procedures differ from traditional approaches to finding "tissue-specific" genes and our matrix yields consistency high positive correlation values for libraries with confirmed tissues of origin and can be applied for tissue typing and quality control of libraries as small as just a few hundred total ESTs. Furthermore, we can pick up tissue correlations between related tissues e.g. brain and peripheral nervous tissue, heart and muscle tissues and identify tissue origins for a few libraries of uncharacterised tissue identity. It was possible to confirm tissue identity for some libraries which have been derived from cancer tissues or have been normalised. Tissue matching is affected strongly by cancer progression or library normalisation and our approach may potentially be applied for elucidating the stage of normalisation in normalised libraries or for cancer staging.     

Allelic variation in gene expression identified through computational analysis of the dbEST database

Differential expression between the two alleles of an individual and between people with different genotypes has been commonly observed. Quantitative differences in gene expression between people may provide the genetic basis for the phenotypic difference between individuals and may be the primary cause of complex diseases. In this paper, we developed a computational method to identify genes that displayed allelic variation in gene expression in human EST libraries. To model allele-specific gene expression, we first identified EST libraries in which both A and B alleles were expressed and then identified allelic variation in gene expression based on the EST counts for each allele using a binomial test. Among 1107 SNPs that had a sufficient number of ESTs for the analysis, 524 (47%) displayed allelic variation in at least one cDNA library. We verified experimentally the allelic variation in gene expression for 6 of these SNPs. The frequency of allelic variation observed in EST libraries was similar to the previous studies using the SNP chip and primer extension method. We found that genes that displayed allelic variation were distributed throughout the human genome and were enriched in certain chromosome regions. The SNPs and genes identified in this study will provide a rich source for evaluating the effects of those SNPs and associated haplotypes in human health and diseases.     

Computational analysis of Ciona intestinalis operons

Operons are clusters of genes that are co-regulated from a common promoter. Operons are typically associated with prokaryotes, although a small number of eukaryotes have been shown to possess them. Among metazoans, operons have been extensively characterized in the nematode Caenorhabditis elegans in which ～15% of the total genes are organized into operons. The most recent genome assembly for the ascidian Ciona intestinalis placed ～20% of the genes (2909 total) into 1310 operons. The majority of these operons are composed of two genes, while the largest are composed of six. Here is reported a computational analysis of the genes that comprise the Ciona operons. Gene ontology (GO) terms were identified for about two-thirds of the operon-encoded genes. Using the extensive collection of public EST libraries, estimates of temporal patterns of gene expression were generated for the operon-encoded genes. Lastly, conservation of operons was analyzed by determining how many operon-encoded genes were present in the ascidian Ciona savignyi and whether these genes were organized in orthologous operons. Over 68% of the operon-encoded genes could be assigned one or more GO terms and 697 of the 1310 operons contained genes in which all genes had at least one GO term. Of these 697 operons, GO terms were shared by all of the genes within 146 individual operons, suggesting that most operons encode genes with unrelated functions. An analysis of operon gene expression from nine different EST libraries indicated that for 587 operons, all of the genes that comprise an individual operon were expressed together in at least one EST library, suggesting that these genes may be co-regulated. About 50% (74/146) of the operons with shared GO terms also showed evidence of gene co-regulation. Comparisons with the C. savignyi genome identified orthologs for 1907 of 2909 operon genes. About 38% (504/1310) of the operons are conserved between the two Ciona species. These results suggest that like C. elegans, operons in Ciona are comprised of a variety of genes that are not necessarily related in function. The genes in only 50% of the operons appear to be co-regulated, suggesting that more complex gene regulatory mechanisms are likely operating.     

A genomewide survey of developmentally relevant genes in Ciona intestinalis. IX. Genes for muscle structural proteins

Ascidians are simple chordates that are related to, and may resemble, vertebrate ancestors. Comparison of ascidian and vertebrate genomes is expected to provide insight into the molecular genetic basis of chordate/vertebrate evolution. We annotated muscle structural (contractile protein) genes in the completely determined genome sequence of the ascidian Ciona intestinalis, and examined gene expression patterns through extensive EST analysis. Ascidian muscle protein isoform families are generally of similar, or lesser, complexity in comparison with the corresponding vertebrate isoform families, and are based on gene duplication histories and alternative splicing mechanisms that are largely or entirely distinct from those responsible for generating the vertebrate isoforms. Although each of the three ascidian muscle types - larval tail muscle, adult body-wall muscle and heart - expresses a distinct profile of contractile protein isoforms, none of these isoforms are strictly orthologous to the smooth-muscle-specific, fast or slow skeletal muscle-specific, or heart-specific isoforms of vertebrates. Many isoform families showed larval-versus-adult differential expression and in several cases numerous very similar genes were expressed specifically in larval muscle. This may reflect different functional requirements of the locomotor larval muscle as opposed to the non-locomotor muscles of the sessile adult, and/or the biosynthetic demands of extremely rapid larval development.     

New experimental and computational approaches to the analysis of gene expression.

Public and private EST (Expressed Sequence Tag) programs provide access to a large number of ESTs from a number of plant species, including Arabidopsis, corn, soybean, rice, wheat. In addition to the homology of each EST to genes in GenBank, information about homology to all other ESTs in the data base can be obtained. To estimate expression levels of genes represented in the DuPont EST data base we count the number of times each gene has been seen in different cDNA libraries, from different tissues, developmental stages or induction conditions. This quantitation of message levels is quite accurate for highly expressed messages and, unlike conventional Northern blots, allows comparison of expression levels between different genes. Lists of most highly expresses genes in different libraries can be compiled. Also, if EST data is available for cDNA libraries derived from different developmental stages, gene expression profiles across development can be assembled. We present an example of such a profile for soybean seed development. Gene expression data obtained from Electronic Northern analysis can be confirmed and extended beyond the realm of highly expressed genes by using high density DNA arrays. The ESTs identified as interesting can be arrayed on nylon or glass and probed with total labeled cDNA first strand from the tissue of interest. Two-color fluorescent labeling allows accurate mRNA ratio measurements. We are currently using the DNA array technology to study chemical induction of gene expression and the biosynthesis of oil, carbohydrate and protein in developing seeds.