Spliced synthetic genes as internal controls in RNA sequencing experiments
Synthetic spike-in standards (‘sequins’), representing spliced mRNA isoforms, provide internal controls for assessing transcript assembly and quantification within and between RNA sequencing libraries. Sequins representing fused genes can be used to determine the sensitivity limit for oncogenic fusi...
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Veröffentlicht in: | Nature methods 2016-09, Vol.13 (9), p.792-798 |
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Sprache: | eng |
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Zusammenfassung: | Synthetic spike-in standards (‘sequins’), representing spliced mRNA isoforms, provide internal controls for assessing transcript assembly and quantification within and between RNA sequencing libraries. Sequins representing fused genes can be used to determine the sensitivity limit for oncogenic fusions in cancer samples.
RNA sequencing (RNA-seq) can be used to assemble spliced isoforms, quantify expressed genes and provide a global profile of the transcriptome. However, the size and diversity of the transcriptome, the wide dynamic range in gene expression and inherent technical biases confound RNA-seq analysis. We have developed a set of spike-in RNA standards, termed 'sequins' (sequencing spike-ins), that represent full-length spliced mRNA isoforms. Sequins have an entirely artificial sequence with no homology to natural reference genomes, but they align to gene loci encoded on an artificial
in silico
chromosome. The combination of multiple sequins across a range of concentrations emulates alternative splicing and differential gene expression, and it provides scaling factors for normalization between samples. We demonstrate the use of sequins in RNA-seq experiments to measure sample-specific biases and determine the limits of reliable transcript assembly and quantification in accompanying human RNA samples. In addition, we have designed a complementary set of sequins that represent fusion genes arising from rearrangements of the
in silico
chromosome to aid in cancer diagnosis. RNA sequins provide a qualitative and quantitative reference with which to navigate the complexity of the human transcriptome. |
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ISSN: | 1548-7091 1548-7105 |
DOI: | 10.1038/nmeth.3958 |