Laure Fresard is a senior computational biologist at Invitae, focusing on developing and evaluating methods and metrics to support the interpretation of variants, especially those that potentially impact splicing and gene expression. She holds a BS/MS in Animal Genetics from Agrocampus Rennes in France and a Ph.D. in Molecular Genetics from the University of Toulouse, France. As a PhD student, Laure used RNA-seq to characterize genomic imprinting and RNA editing in birds. Between 2015 and 2020, she was a postdoc at Stanford University in Dr Stephen Montgomery’s lab, focusing on using whole blood RNA-seq in conjunction with whole exome or whole genome sequencing to help pinpoint causal variants in patients affected by rare Mendelian diseases.
Laure is dedicated to using her knowledge and understanding of regulation of gene expression and splicing to impact patient lives.
Laure Fresard, Keith Nykamp, Nick Kamp-Hughes, John Vincent, Sarah Albritton, Victoria Carlton, Hio Chung Kang, Kate Krempely, Carolina Pardo
Invitae, San Francisco, CA, USA
Introduction: To help resolve the clinical significance of variants predicted to alter splicing, and identify splice-altering variants in regions outside of the reportable range of our routine hereditary cancer DNA sequencing tests, we initiated an IRB-approved RNA-sequencing research study at Invitae.
Methods: We developed an RNA-sequencing assay run on whole blood for 63 transcripts from the Invitae Multi-Cancer panel and an algorithm for detecting alterations in splicing caused by nearby DNA variants. Our algorithm was designed to detect statistically significant alterations in splicing of a specific transcript relative to a panel of controls. Samples with previously determined positive (n=52) or negative RNA effects (n=70) were used for validation. RNA analysis was also prospectively performed for >13000 patients.
Results: Accuracy was 99.7%, with 97.8% sensitivity and 99.7% specificity for the 122 validation samples. Reproducibility was 100%. 723/13175 (5.5%) were found to have a significant splicing-alteration associated with a DNA variant. Thirty-four patients (0.26%) were found to have a cryptic exon (32) or an intron inclusion event (2) associated with a DNA variant beyond our standard reportable range (+/- 20 bp around each exon). RNA analysis led to a more definitive classification in 4.9% of individuals (Likely Pathogenic/Pathogenic=0.4%; Likely Benign/Benign=4.5%).
Conclusions: Invitae’s RNA sequencing assay is improving the accuracy of variant classification within the reportable range of our tests, and enabling new variant discovery in regions outside our reportable range. These results support the integration of RNA analysis into the genetic testing workflow.