Downloaded from genome.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press Digital gene expression for non-model organisms Lewis Z. Hong1, Jun Li2, Anne Schmidt-Küntzel3, Wesley C. Warren4 and Gregory S. Barsh1,5§ 1Department of Genetics, Stanford University, Stanford, CA 94305, USA; 2Department of Statistics, Stanford University, Stanford, CA 94305, USA; 3Applied Biosystems Genetic Conservation Laboratory, Cheetah Conservation Fund, Otjiwarongo, Namibia; 4The Genome Center, Washington University School of Medicine, St. Louis, MO 63108, USA; 5HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA. §Address correspondence to: Greg Barsh HudsonAlpha Institute for Biotechnology Huntsville, AL, 35763 (256) 327 5266
[email protected] Running title: Digital gene expression for non-model organisms Keywords: EDGE, RNA-seq, melanocortin-1-receptor, cheetah Downloaded from genome.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract 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.