RESUMO
GeneTag is a novel expression profiling method that allows the visualization, quantification and identification of expressed genes-whether known or novel-in any species, tissue or cell type, independent of knowledge of the underlying sequence. Here we describe the application of this method to determine variation of gene expression in individual human liver samples and the identification of tissue-specific genes by comparing expression patterns across several human organs. Expression data are stored in a database for future reference and data analysis relies on proprietary software, which allows complex comparisons to be performed. Differentially expressed genes are quickly identified through a link to a sequence database. The results from our study underscore the importance of knowledge of individual variation of gene expression for the design and interpretation of transcript profiling experiments in the context of any biological question.
Assuntos
Perfilação da Expressão Gênica/métodos , Expressão Gênica/genética , Fígado/química , Técnica de Amplificação ao Acaso de DNA Polimórfico/métodos , Alinhamento de Sequência/métodos , Encéfalo , Química Encefálica , Impressões Digitais de DNA/métodos , DNA Complementar/análise , Feminino , Humanos , Fígado/embriologia , Pulmão/química , Masculino , Especificidade de Órgãos , Placenta/química , Polimorfismo de Fragmento de Restrição , Gravidez , RNA Mensageiro/análise , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Transcrição Gênica/genéticaRESUMO
A highly automated RT-PCR-based approach has been established to validate novel human gene predictions with no prior experimental evidence of mRNA splicing (ab initio predictions). Ab initio gene predictions were selected for high-throughput validation using predicted protein classification, sequence similarity to other genomes, colocalization with an MPSS tag, or microarray expression. Initial microarray prioritization followed by RT-PCR validation was the most efficient combination, resulting in approximately 35% of the ab initio predictions being validated by RT-PCR. Of the 7252 novel genes that were prioritized and processed, 796 constituted real transcripts. In addition, high-throughput RACE successfully extended the 5' and/or 3' ends of >60% of RT-PCR-validated genes. Reevaluation of these transcripts produced 574 novel transcripts using RefSeq as a reference. RT-PCR sequencing in combination with RACE on ab initio gene predictions could be used to define the transcriptome across all species.