Transcriptomics
Transcriptomics: Past and Present
Introduction The transcriptome is defined as the complete set of transcripts in a cell, and their quantity, for a specific developmental stage or physiological condition. It includes all the mRNA transcripts in a cell, reflecting genes that are actively expressed at any given time. An understanding of the transcriptome is essential for interpreting the functional elements of the genome and the development and disease. The key aims of transcriptomics are: cataloguing all species of transcript; determining gene transcriptional structure; and quantifying expression levels of each transcript during development and under different conditions (Marguerat, S, 2008).
Transcriptomic technologies have been developed to quantify the transcriptome, which can be categorized as hybridization-based or sequencing based approaches. The sequencing-based technologies can be further classified into the classical Sanger sequencing and next-generation sequencing methods.
Figure 1: gives an overview of the different transcriptomic techniques. Figure taken from (Marguerat, S, 2008)
Hybridization-Based Approaches Hybridization-based approaches involve incubating fluorescently labeled cDNA with custommade microarrays or commercial high-density oligo microarrays. While these approaches are high throughput and relatively inexpensive, they rely upon existing knowledge about genome sequence. They provide a limited dynamic range of detection owing to both background and saturation of signals. Sequencing-Based Approaches These approaches directly determine the cDNA sequence. Initially, Sanger sequencing of cDNA or EST libraries was used, but this is relatively low throughput, expensive and generally not quantitative. Tag-based methods based on Sanger technology were developed to overcome these limitations, including Serial Analysis of Gene Expression (SAGE), Cap Analysis of Gene Expression (CAGE) and Massively Parallel Signature Sequencing (MPSS). They
Introduction The transcriptome is defined as the complete set of transcripts in a cell, and their quantity, for a specific developmental stage or physiological condition. It includes all the mRNA transcripts in a cell, reflecting genes that are actively expressed at any given time. An understanding of the transcriptome is essential for interpreting the functional elements of the genome and the development and disease. The key aims of transcriptomics are: cataloguing all species of transcript; determining gene transcriptional structure; and quantifying expression levels of each transcript during development and under different conditions (Marguerat, S, 2008).
Transcriptomic technologies have been developed to quantify the transcriptome, which can be categorized as hybridization-based or sequencing based approaches. The sequencing-based technologies can be further classified into the classical Sanger sequencing and next-generation sequencing methods.
Figure 1: gives an overview of the different transcriptomic techniques. Figure taken from (Marguerat, S, 2008)
Hybridization-Based Approaches Hybridization-based approaches involve incubating fluorescently labeled cDNA with custommade microarrays or commercial high-density oligo microarrays. While these approaches are high throughput and relatively inexpensive, they rely upon existing knowledge about genome sequence. They provide a limited dynamic range of detection owing to both background and saturation of signals. Sequencing-Based Approaches These approaches directly determine the cDNA sequence. Initially, Sanger sequencing of cDNA or EST libraries was used, but this is relatively low throughput, expensive and generally not quantitative. Tag-based methods based on Sanger technology were developed to overcome these limitations, including Serial Analysis of Gene Expression (SAGE), Cap Analysis of Gene Expression (CAGE) and Massively Parallel Signature Sequencing (MPSS). They