ABSTRACT
MOTIVATION: Genes are often characterized dichotomously as either housekeeping or single-tissue specific. We conjectured that crucial functional information resides in genes with midrange profiles of expression. RESULTS: To obtain such novel information genome-wide, we have determined the mRNA expression levels for one of the largest hitherto analyzed set of 62 839 probesets in 12 representative normal human tissues. Indeed, when using a newly defined graded tissue specificity index tau, valued between 0 for housekeeping genes and 1 for tissue-specific genes, genes with midrange profiles having 0.15< tau<0.85 were found to constitute >50% of all expression patterns. We developed a binary classification, indicating for every gene the I(B) tissues in which it is overly expressed, and the 12-I(B) tissues in which it shows low expression. The 85 dominant midrange patterns with I(B)=2-11 were found to be bimodally distributed, and to contribute most significantly to the definition of tissue specification dendrograms. Our analyses provide a novel route to infer expression profiles for presumed ancestral nodes in the tissue dendrogram. Such definition has uncovered an unsuspected correlation, whereby de novo enhancement and diminution of gene expression go hand in hand. These findings highlight the importance of gene suppression events, with implications to the course of tissue specification in ontogeny and phylogeny. AVAILABILITY: All data and analyses are publically available at the GeneNote website, http://genecards.weizmann.ac.il/genenote/ and, GEO accession GSE803. CONTACT: doron.lancet@weizmann.ac.il SUPPLEMENTARY INFORMATION: Four tables available at the above site.
Subject(s)
Algorithms , Chromosome Mapping/methods , Gene Expression Profiling/methods , Oligonucleotide Array Sequence Analysis/methods , Proteome/metabolism , Software , Transcription Factors/metabolism , Humans , Organ Specificity , Proteome/genetics , Tissue Distribution , Transcription Factors/geneticsABSTRACT
GeneCards is an automatically mined database of human genes that strives to create, along with its auxiliary databases--GeneLoc, GeneNote and GeneAnnot--the most inclusive resource of gene-centered information of the human genome. GeneTide, the Gene Terra Incognita Discovery Endeavor (http://genecards.weizmann.ac.il/genetide/), the newest addition to this family, is a transcriptome-focused database which aims to enhance GeneCards with additional expressed sequence tag (EST)-based genes. This is achieved by comprehensively mapping >85% of the approximately 5.6 million human ESTs currently available at dbEST to known genes by means of data mining and integration of genomic resources including UniGene, DoTS, AceView and in-house resources. GeneTide thus creates comprehensive links between ESTs and GeneCards genes. Furthermore, groups of unassociated transcripts serve as a basis for defining novel EST-based GeneCards Candidates (EGCs). These EGCs, nearly 25,000 of which were defined in version 0.3 of GeneTide, are further annotated with various parameters, including splicing evidence and expression data extracted from the GeneNote database, to determine their validity as possible de novo genes.
Subject(s)
Databases, Genetic , Expressed Sequence Tags , Genomics , Transcription, Genetic , Gene Expression Profiling , Genes , Genome, Human , Humans , Oligonucleotide Array Sequence Analysis , Systems IntegrationABSTRACT
MOTIVATION: High density oligonucleotide arrays are usually annotated in a one-to-one fashion, with each probeset assigned to one gene. However, in reality, subsets of oligonucleotides in a probeset may match sequences within more than one gene, potentially leading to misinterpretations. Moreover, a gene is often represented by more than one probeset, and analyzing probe matches at the mRNA level can help one deduce whether these probesets are derived from the same or different splice variants. RESULTS: The GeneAnnot system comprehensively documents the many-to-many relationship between oligonucleotide array probesets and annotated genes in GeneCards. It performs pairwise alignments between the probe sequences and gene transcripts, and assigns sensitivity and specificity scores to each probeset/gene pair. AVAILABILITY: http://genecards.weizmann.ac.il/geneannot/ SUPPLEMENTARY INFORMATION: Program description and statistics http://genecards.weizmann.ac.il/geneannot/DOC/index.html
Subject(s)
Algorithms , Chromosome Mapping/methods , Documentation/methods , Oligonucleotide Array Sequence Analysis/methods , Sequence Alignment/methods , Software , Sequence Analysis, DNA/methodsABSTRACT
MOTIVATION: Despite the numerous available whole-genome mapping resources, no comprehensive, integrated map of the human genome yet exists. RESULTS: GeneLoc, software adjunct to GeneCards and UDB, integrates gene lists by comparing genomic coordinates at the exon level and assigns unique and meaningful identifiers to each gene.
Subject(s)
Chromosome Mapping/methods , Databases, Genetic , Exons/genetics , Genome, Human , Sequence Alignment/methods , Sequence Analysis, DNA/methods , Software , Database Management Systems , Human Genome Project , Humans , Information Storage and Retrieval/methods , Sequence Homology, Nucleic Acid , Systems IntegrationABSTRACT
Recent enhancements and current research in the GeneCards (GC) (http://bioinfo.weizmann.ac.il/cards/) project are described, including the addition of gene expression profiles and integrated gene locations. Also highlighted are the contributions of specialized associated human gene-centric databases developed at the Weizmann Institute. These include the Unified Database (UDB) (http://bioinfo.weizmann.ac.il/udb) for human genome mapping, the human Chromosome 21 database at the Weizmann Insti-tute (CroW 21) (http://bioinfo.weizmann.ac.il/crow21), and the Human Olfactory Receptor Data Explora-torium (HORDE) (http://bioinfo.weizmann.ac.il/HORDE). The synergistic relationships amongst these efforts have positively impacted the quality, quantity and usefulness of the GeneCards gene compendium.
Subject(s)
Chromosomes, Human, Pair 21 , Databases, Genetic , Genome, Human , Receptors, Odorant/genetics , Algorithms , Chromosome Mapping , Gene Expression Profiling , Humans , IsraelABSTRACT
The interpretation of microarray expression results often includes extensive efforts to identify and annotate the gene representatives immobilised on the arrays. In this paper we describe the usage of our automatic GeneAnnot system, which links between Affymetrix arrays and the rich human gene annotations available in GeneCards. We explain GeneCards search options and results display; elaborate on the presentation of expression information in GeneCards, including both our whole-genome GeneNote project and external expression resources; describe the various parameters and displays used by GeneAnnot to assess the annotation quality and probeset specificity; and show how to search GeneAnnot and GeneNote websites directly.
Subject(s)
Data Interpretation, Statistical , Oligonucleotide Array Sequence Analysis , SoftwareABSTRACT
A novel data set, GeneNote (Gene Normal Tissue Expression), was produced to portray complete gene expression profiles in healthy human tissues using the Affymetrix GeneChip HG-U95 set, which includes 62 839 probe-sets. The hybridization intensities of two replicates were processed and analyzed to yield the complete transcriptome for twelve human tissues. Abundant novel information on tissue specificity provides a baseline for past and future expression studies related to diseases. The data is posted in GeneNote (http://genecards.weizmann.ac.il/genenote/), a widely used compendium of human genes (http://bioinfo.weizmann.ac.il/genecards).
Subject(s)
Gene Expression , Genome, Human , HumansABSTRACT
MOTIVATION: In the post-genomic era, functional analysis of genes requires a sophisticated interdisciplinary arsenal. Comprehensive resources are challenged to provide consistently improving, state-of-the-art tools. RESULTS: GeneCards (Rebhan et al., 1998) has made innovative strides: (a). regular updates and enhancements incorporating new genes enriched with sequences, genomic locations, cDNA assemblies, orthologies, medical information, 3D protein structures, gene expression, and focused SNP summaries; (b). restructured software using object-oriented Perl, migration to schema-driven XML, and (c). pilot studies, introducing methods to produce cards for novel and predicted genes.
