Researchers at Baylor College of Medicine have developed and validated a clinical diagnostic RNA sequencing test, marking a significant advancement in the field of genetic disorder diagnosis. The study, published in the American Journal of Human Genetics, details the creation of a comprehensive transcriptome sequencing pipeline for clinical use.
"This validation represents the first attempt to unleash the full transcriptome potential of RNA sequencing for clinical diagnostics," said Dr. Pengfei Liu, associate professor of molecular and human genetics and director of the Medical Genetics and Multiomics Laboratory (MGML) at Baylor. He explained that while RNA sequencing has been used in clinical testing before, it was limited to targeted gene analysis. The team collaborated with the College of American Pathologists to establish whole-transcriptome sequencing as a reportable assay.
The newly developed RNA-seq test analyzes samples from fibroblasts or blood to identify outliers in gene expression and splicing patterns. It was validated using 130 samples—40 with positive molecular diagnoses and 90 negative controls from healthy individuals. Benchmarks were established using data from a lymphoblastoid sample provided by the Genome in a Bottle Consortium.
To evaluate its clinical performance, researchers tested samples with known diagnostic findings from the Undiagnosed Diseases Network (UDN). The study confirmed that the assay could detect diagnostic RNA findings through both transcriptome-driven and DNA-driven modes, indicating its potential to improve molecular diagnosis.
This is MGML's first launched test now available for clinical RNA sequencing within UDN. Contributors to this research include Sen Zhao, Kristina Macakova, Jefferson C. Sinson, Hongzheng Dai, Jill Rosenfeld, Gladys E. Zapata, Shenglan Li, Patricia Ward, Christiana Wang, Chunjing Qu, Becky Maywald, Brendan Lee and Christine Eng from institutions such as Baylor College of Medicine and University of Texas MD Anderson Cancer Center School of Health Professions.
The project received support from grants by the National Institutes of Health Common Fund (U01HG007709 and U01HG007942) and National Human Genome Research Institute (R35HG011311).
