Digital gene expression for non-model organisms.
Department of Genetics, Stanford University;
Next-generation sequencing technologies offer new approaches for global measurements of gene expression, but are mostly limited to organisms for which a high-quality assembled reference genome sequence is available. We present a method for gene expression profiling called EDGE, or EcoP15I-tagged Digital Gene Expression, based on ultra high-throughput sequencing of 27 bp cDNA fragments that uniquely tag the corresponding gene, thereby allowing direct quantification of transcript abundance. We show that EDGE is capable of assaying for expression in >99% of genes in the genome and achieves saturation after 6 - 8 million reads. EDGE exhibits very little technical noise, reveals a large (106) dynamic range of gene expression, and is particularly suited for quantification of transcript abundance in non-model organisms where a high quality annotated genome is not available. In a direct comparison with RNA-seq, both methods provide similar assessments of relative transcript abundance, but EDGE does better at detecting gene expression differences for poorly expressed genes, and does not exhibit transcript length bias. Applying EDGE to laboratory mice, we show that a loss-of-function mutation in the Melanocortin 1 receptor (Mc1r), recognized as a Mendelian determinant of yellow hair color in many different mammals, also causes reduced expression of genes involved in the interferon response. To illustrate the application of EDGE to a non-model organism, we examine skin biopsy samples from a cheetah (Acinonyx jubatus), and identify genes likely to control differences in the color of spot vs. non-spotted regions.
- [PubMed - as supplied by publisher]