Affymetrix Inc recently announced commercialization of the next-generation human transcriptome array demonstrated by Stanford University researchers to be superior to mRNA sequencing (RNA-Seq) in gene expression profiling studies. In multiple experiments using a clinically relevant transcriptome discovered by deep sequencing, the research scientists compared the throughput and performance of both profiling technologies and found the new GeneChip Human Transcriptome and Splice Junction Array outperformed RNA-Seq in most all parameters when detecting exonic changes implicated in human disease and genetic disorders.

According to results of Stanford’s recently published study, the Human Transcriptome Array detected the same number of genes and two times the number of exons, had lower variance over a wide range of expression levels, improved the percentage of true-positive detections in alternative splicing analysis, and measured more non-coding RNA than RNA-Seq. With 99% coverage of human genes and 95% coverage of transcript isoforms, researchers determined that the high density microarray is a better profiling array for clinical studies.

In typical large-scale studies of 5,000 samples, Stanford researchers estimated it would take RNA-Seq 10 times longer to analyze one percent of the number of genes processed by the new array and 20 times longer to analyze one-half percent of exons. Moreover, to achieve the same level of reproducibility as the new array, RNA-Seq would require 150 million mappable reads for genes and 200 million for exons (3711). Based on this level of power and performance, the researchers concluded the Human Transcriptome Array is more reproducible, faster, and cost-effective than RNA-Seq for detecting and characterizing low-level expression changes of clinically relevant transcripts.

The new array is the 6.9 million-feature Glue Grant Human Transcriptome (GG-H) Array developed with Stanford as part of the NIH Glue Grants program, a three-year multicenter effort to answer clinical questions requiring a translational bench to bedside strategy. Led by Stanford’s Genome Technology Center and Department of Biochemistry research scientists, the performance of the GG-H Array was examined and compared with RNA-Seq results over multiple independent replicates of liver and muscle samples. The findings, recently published in the journal of Proceedings of the National Academy of Sciences (PNAS), determined "the GG-H Array was highly reproducible in estimating gene and exon abundance and more sensitive at the exon level" when compared with RNA-Seq of 46 million uniquely mappable reads per replicate (3707).

Source: Affymetrix Inc