Transcriptome sequencing provides quick, direct access to the mRNA. With this information, one can design primers for PCR of thousands of different genes, SNP markers, probes for microarrays and qPCR, or just use the sequence data itself in comparative studies. Transcriptome sequencing, while getting cheaper, is still an expensive endeavor, with an examination of data quality and its assembly infrequently performed in depth. Here, we outline many of the important issues we think need consideration when starting a transcriptome sequencing project. We also walk the reader through a detailed analysis of an example transcriptome dataset, highlighting the importance of both within-dataset analysis and comparative inferences. Our hope is that with greater attention focused upon assessing assembly performance, advances in transcriptome assembly will increase as prices continue to drop and new technologies, such as Illumina sequencing, start to be used.
CITATION STYLE
Wheat, C. W., & Vogel, H. (2011). Transcriptome Sequencing Goals, Assembly, and Assessment. In Methods in Molecular Biology (Vol. 772, pp. 129–144). Humana Press Inc. https://doi.org/10.1007/978-1-61779-228-1_7
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