Cross-referencing eukaryotic genomes: TIGR Orthologous Gene Alignments (TOGA)

GeneHopper: a web-based search engine to link gene-expression platforms through GenBank accession numbers

Global gene-expression analysis is carried out using different technologies that are either array- or sequence-tag-based. To compare experiments that are performed on these different platforms, array probes and sequence tags need to be linked. An additional challenge is cross-referencing between species, to compare human profiles with those obtained in a mouse model, for example. We have developed the web-based search engine GeneHopper to link different expression resources based on UniGene clusters and HomoloGene orthologs databases of the National Center for Biotechnology Information (NCBI).

Gene homology resources on the World Wide Web

As the amount of information available to biologists increases exponentially, data analysis becomes progressively more challenging. Sequence homology has been a traditional tool in the researchers' armamentarium; it is a very versatile instrument and can be employed to assist in numerous tasks, from establishing the function of a gene to determination of the evolutionary development of an organism. Consequently, numerous specialized tools have been established in the public domain (most commonly, the World Wide Web) to help investigators use sequence homology in their research. These homology databases differ both in techniques they use to compare sequences as well as in the size of the unit of analysis, which can be the whole gene, a domain, or a motif. In this paper, we aim to present a systematic review of the inner details of the most commonly used databases as well as to offer guidelines for their use.

Gene expression profiling of embryo-derived stem cells reveals candidate genes associated with pluripotency and lineage specificity

Large-scale gene expression profiling was performed on embryo-derived stem cell lines to identify molecular signatures of pluripotency and lineage specificity. Analysis of pluripotent embryonic stem (ES) cells, extraembryonic-restricted trophoblast stem (TS) cells, and terminally-differentiated mouse embryo fibroblast (MEF) cells identified expression profiles unique to each cell type, as well as genes common only to ES and TS cells. Whereas most of the MEF-specific genes had been characterized previously, the majority (67%) of the ES-specific genes were novel and did not include known differentiated cell markers. Comparison with microarray data from embryonic material demonstrated that ES-specific genes were underrepresented in all stages sampled, whereas TS-specific genes included known placental markers. Investigation of four novel TS-specific genes showed trophoblast-restricted expression in cell lines and in vivo, whereas one uncharacterized ES-specific gene, Esg-1, was found to be exclusively associated with pluripotency. We suggest that pluripotency requires a set of genes not expressed in other cell types, whereas lineage-restricted stem cells, like TS cells, express genes predictive of their differentiated lineage.

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.

Identification of Src transformation fingerprint in human colon cancer

We used a classical rodent model of transformation to understand the transcriptional processes, and hence the molecular and cellular events a given cell undergoes when progressing from a normal to a transformed phenotype. Src activation is evident in 80% of human colon cancer, yet the myriad of cellular processes effected at the level of gene expression has yet to be fully documented. We identified a Src 'transformation fingerprint' within the gene expression profiles of Src-transformed rat 3Y1 fibroblasts demonstrating a progression in transformation characteristics. To evaluate the role of this gene set in human cancer development and progression, we extracted the orthologous genes present on the Affymetrix Hu95A GeneChip (12k named genes) and compared expression profiles between the Src-induced rodent cell line model of transformation and staged colon tumors where Src is known to be activated. A similar gene expression pattern between the cell line model and staged colon tumors for components of the cell cycle, cytoskeletal associated proteins, transcription factors and lysosomal proteins suggests the need for co-regulation of several cellular processes in the progression of cancer. Genes not previously implicated in tumorigenesis were detected, as well as a set of 14 novel, highly conserved genes with here-to-fore unknown function. These studies define a set of transformation associated genes whose up-regulation has implications for understanding Src mediated transformation and strengthens the role of Src in the development and progression of human colon cancer. Supportive Supplemental Data can be viewed at http://pga.tigr.org/PGApubs.shtml.