Digital gene expression for non-model organisms

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-highthroughput 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 (10 6 ) 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 spotted versus non-spotted regions.

Comparative motif discovery combined with comparative transcriptomics yields accurate targetome and enhancer predictions

“…Sequencing-based expression profiling using RNA-seq or Tag-seq provides the opportunity to obtain genome-wide quantitative gene expression levels in any tissue and in any species (McManus et al 2010;Hong et al 2011). Here we use comparative transcriptomics in combination with comparative motif discovery.…”

“…Here we use comparative transcriptomics in combination with comparative motif discovery. The comparative transcriptomics was performed during retinal determination in three Drosophila species (D. melanogaster, D. yakuba, and D. virilis) using Tag-sequencing (Tag-seq, sometimes also called EDGE) (Saha et al 2002;Hong et al 2011). By using Tag-seq, the expression levels are based on one expressed sequence tag (EST) per transcript, corresponding to the 21 bp downstream from the most 39-located NlaIII restriction site.…”

PAT-seq: a method to study the integration of 3′-UTR dynamics with gene expression in the eukaryotic transcriptome

“…Most of these have been selectively interrogated by high-throughput sequencing technologies to capture snapshots of systemwide control of gene expression. The convenient "hook" provided by the poly(A) tail on the vast majority of mRNA has also given rise to digital gene expression approaches that use 3 ′ focused sequencing based around SAGE (Velculescu et al 1995) as a means to quantify the composition of the transcriptome (Ruzanov and Riddle 2010;Wu et al 2010;Hong et al 2011). Such approaches provide inexpensive and relatively simple tools to monitor eukaryotic gene expression.…”

Cloning and Expression of the Pathogenicity-Related Genes of Oidium heveae in the Infection Process

“…DGE method uses data of relative tag frequencies to show gene expression differences [13]. Transcriptomic analysis has also been used to study pathogenicity-related genes [5].…”