Affymetrix, Inc. (NASDAQ:AFFX) today 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 percent coverage of human genes and 95 percent coverage of transcript isoforms, researchers determined that the high density microarray is a better profiling array for clinical studies.
"With unparalleled sensitivity, reproducibility, and ease of use, arrays of this type will be the platform of choice for patient profiling in clinical trials," said Stanford Professor of Biochemistry and Genetics Ronald W. Davis, PhD, a pioneer in the development and application of recombinant-DNA techniques and the study's lead researcher. "The power of next-generation sequencing (NGS) harnessed into a clinically viable platform, like the Affymetrix Human Transcriptome Array, will be what changes the face of patient care."
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.
"An emerging approach for large-scale clinical genomic studies is to first use RNA-Seq to the sufficient depth of 200 million or greater reads for the discovery of transcriptome elements relevant to the disease process, followed by high-throughput and reliable screening of these elements on thousands of patient samples using custom designed arrays," added Dr. Davis, winner of this year's Gruber Genetics Prize for distinguished contributions to genetics research.
Until its worldwide rollout, Affymetrix is selling the Human Transcriptome Array through an early-access program to pharmaceutical and research institutions using microarrays or NGS for basic discovery or whole transcriptome analyses. Designed in collaboration with Stanford researchers, it has attracted worldwide attention from pharmaceutical and research institutions seeking a tool sensitive enough to reproducibly measure low abundance transcripts in complex disease and reproducible enough to take their de novo research to the clinical level—enabling them to leverage the power of NGS in a clinical setting.
"Human transcript diversity has been well characterized—there are more than 65 million expressed sequence tags now available in public databases and during the last 15 years, they've been instrumental in gene discovery and gene sequence determination," said Frank Witney, PhD, Affymetrix President and CEO. "Researchers and clinicians are demanding solutions like our new array to go beyond simply identifying transcripts, to actually measuring the differences in their abundance in large clinical studies."
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).
"Research like Stanford's really demonstrates how to use multiple technologies effectively in large scale clinical studies where detection and measurement of low-abundance transcripts is essential," said Kevin Cannon, PhD, Vice President of Gene Expression at Affymetrix. "These observations provide researchers practical guidance on using the right technology at the right time; first NGS for discovery, then high density next-generation transcriptome microarrays for high volume profiling."