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Study Compares Ability of Expression Arrays, RNA-seq to Profile Cell-free Fetal RNA Transcriptome


NEW YORK (GenomeWeb) — A team of researchers from Tufts Medical Center recently assessed the ability of microarrays and next-generation sequencing to profile gene expression in cell-free fetal RNA obtained from amniotic fluid supernatant.

They found that expression microarrays provided a broader view of gene expression, particularly in low-concentration or degraded samples, an area where RNA-seq suffered from "technical challenges." At the same time, they noted that RNA-seq data provided a better focus on alternative splicing and specific biological pathways relevant to the developing fetus.

The results are detailed in a paper published last week in the journal Prenatal Diagnosis.

"What we learned at the end of the day is that it's really not that bad to be working with microarrays because you do get more sequences identified," said Diana Bianchi, executive director of Tufts' Mother Infant Research Institute and corresponding author on the paper. "It seems like you need better quality RNA to detect the extra sequences that you'd expect to see with RNA-seq," she told BioArray News.

Bianchi said that she and her colleagues were motivated to compare expression arrays with RNA-seq in part because of the perception that microarrays are an "outdated technology." In the past they had used expression microarrays in their research, in particular Affymetrix's HG-U133 Plus 2.0 Gene Chip. Because the researchers were so invested in that chip, they did not opt to compare RNA-seq with Affy's newer, 6-million-probe Human Transcriptome Array, which would have provided more similar coverage to RNA-seq.

"We consciously made a decision to look at those arrays because we are interested in applying gene lists to developing therapies for prenatal treatment," said Bianchi. She noted that researchers continue to use The Broad Institute's Connectivity Map, a collection of genome-wide transcriptional Affymetrix U133 expression data from cultured human cells treated with bioactive small molecules. By uploading differentially regulated genes from a particular condition into the Connectivity Map, they can learn which therapy might reverse an abnormal transcriptome.

"That's the array that once you begin to build a database you are almost handcuffed to it in the short term," said Bianchi of the U133.

To compare the U133 with RNA-seq, Bianchi and colleagues divided and prepared for analysis the cell-free fetal RNA from the amniotic fluid supernatant of five euploid mid-trimester samples. Analysis was carried out using the U133 and the Illumina HiSeq, and transcriptomes were assembled and compared on the basis of presence of signal, rank-order gene expression, and pathway enrichment using Ingenuity Pathway Analysis. RNA-Seq data were also examined for evidence of alternative splicing, she said.

Within individual samples, gene expression was strongly correlated, according to the paper. At the same time, 8,842 expressed genes were observed using the Affymetrix microarrays versus 4,158 using Illumina sequencing. Most of the top pathways in the IPA software's Physiological Systems Development and Function category were shared between platforms, although RNA-seq yielded more significant p-values, the authors wrote. Also, using RNA-seq, examples of known alternative splicing were detected in several genes including H19 and IGF2.

Bianchi attributed the performance of RNA-seq to sample degradation issues. She noted that cell-free fetal RNA is a "very interesting material," in that the sequences detected are from multiple different organs. If the researchers had extracted RNA from a specific organism, RNA-seq would likely have provided higher quality data, she said.

"There was significant overlap, but mainly in higher-expressed genes," said Bianchi of the two approaches. "In the lower-expressed genes, though, microarray was a bit more resilient than RNA-seq," she said. "So RNA-seq is a bit more affected by technical issues."

Still, Bianchi cautioned that improvements could be made in RNA-seq library preparation process that would lead to better quality data. She also noted that the researchers had settled on a read depth of 50 million to make the comparison with the U133 more direct, and that deeper sequencing might have yielded different results.

"I would say that this study is not the be all, end all," said Bianchi. "It did provide reassurance, though, that by continuing to use the arrays we were not using a tremendously outdated technology," she said. "Arrays still provide very valuable information on material that is unique and is obtained from a living fetus," she said.

As for the ability of RNA-seq to detect alternative splicing events, Bianchi said that splicing information is not yet clinically applicable, though it could become helpful in some situations in the future. She added that both expression microarrays and RNA-seq are used as research tools only, and that the majority of her laboratory's diagnostics work is carried out using DNA sequencing.