2023 ACMG Annual Clinical Genetics Meeting Digital Edition: Poster Gallery-Recommendations for the improvement of diagnostic yields in rare disease cases through the integration of structural variants into analytical pipelines

Recommendations for the improvement of diagnostic yields in rare disease cases through the integration of structural variants into analytical pipelines

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This document discusses recommendations for improving diagnostic yields in rare disease cases by integrating structural variants (SVs) into analytical pipelines. SVs are genetic variations that can alter DNA copy number or structure and play a role in various human diseases. Therefore, considering SVs is crucial in rare disease analysis.<br /><br />To identify SVs, a SV Calling Pipeline is used, which involves whole genome sequencing, reference alignments, variant calling, annotations, quality control, and filtering. Software tools such as Manta and smoove are used for variant calling, and IGV and samplot are used for visualization and analysis.<br /><br />The document provides two examples of SV identification and their impact on rare diseases. In the first example, a proband presented with congenital diaphragmatic hernia (CDH). SV analysis identified a complex inversion flanked by deletions on chromosome 8, disrupting the ZFPM2 gene, which is known to be associated with CDH.<br /><br />In the second example, a proband with global developmental delay and other symptoms had a sibling with a different diagnosis but sharing the same TBCK variants. SV analysis revealed a maternal deletion that deleted exon 23 of the TBCK gene and a paternal variant in the splice-donor site of the TBCK gene. This updated diagnosis highlights the importance of considering SVs in understanding complex genetic conditions.<br /><br />The document also mentions the use of the RUFUS tool for alignment-free variant calling and provides a figure illustrating the SV signals from alignments.<br /><br />In conclusion, integrating SV analysis into rare disease analytical pipelines can improve diagnostic yields by uncovering important genetic variations and their impact on disease phenotypes. The document emphasizes the significance of considering and properly analyzing structural variants for an accurate understanding of rare diseases.

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Presenting Author - Thomas J. Nicholas; Co-Author - Andrew Farrell, PHD; Co-Author - Shawn Rynearson, BS; Co-Author - Carson Holt, PHD; Co-Author - Steven E. Boyden, PhD; Co-Author - Barry Moore, MS; Co-Author - Najla Al-Sweel, PhD, MS; Co-Author - Christine E. Miller, MS, LCGC; Co-Author - Lucilla Pizzo, PhD; Co-Author - Chelsea Solorzano, BSN, RN; Co-Author - Rachel Palmquist, MS, CGC; Co-Author - Ashley Andrews, MSN, CPNP; Co-Author - Rong Mao, MD; Co-Author - Pinar Bayrak-Toydemir; Co-Author - Eric Fredrickson, PhD; Co-Author - Katherine Noble, PHD; Co-Author - Brian J. Shayota, MD, MPH; Co-Author - Joshua L. Bonkowsky, MD; Co-Author - John C. Carey, MD; Co-Author - Sabrina Malone Jenkins, MD; Co-Author - Lorenzo D. Botto, MD, FACMG; Co-Author - Aaron R. Quinlan, PhD;

Meta Tag

Bioinformatics

Genome sequencing

Genomic Methodologies

NextGen Sequencing

Sequencing

Co-Author Andrew Farrell, PHD

Co-Author Shawn Rynearson, BS

Co-Author Carson Holt, PHD

Co-Author Steven E. Boyden, PhD

Co-Author Barry Moore, MS

Co-Author Najla Al-Sweel, PhD, MS

Co-Author Christine E. Miller, MS, LCGC

Co-Author Lucilla Pizzo, PhD

Co-Author Chelsea Solorzano, BSN, RN

Co-Author Rachel Palmquist, MS, CGC

Co-Author Ashley Andrews, MSN, CPNP

Co-Author Rong Mao, MD

Co-Author Pinar Bayrak-Toydemir

Co-Author Eric Fredrickson, PhD

Co-Author Katherine Noble, PHD

Co-Author Brian J. Shayota, MD, MPH

Co-Author Joshua L. Bonkowsky, MD

Co-Author John C. Carey, MD

Co-Author Sabrina Malone Jenkins, MD

Co-Author Lorenzo D. Botto, MD, FACMG

Co-Author Aaron R. Quinlan, PhD

Presenting Author Thomas J. Nicholas

Keywords

diagnostic yields

rare disease cases

structural variants

SVs

genetic variations

DNA copy number

whole genome sequencing

variant calling

annotations

quality control