28. KARYOMAPPING USING WHOLE GENOME SEQUENCING DATA: PRECLINICAL VALIDATION OF A PERSONALISED APPROACH TO PGT-M

Abstract

Introduction Karyomapping utilises microarray technology to track informative single nucleotide polymorphisms (SNPs) and assign haplotypes to embryos without the need for direct mutation detection (Handyside et al. 2010). Although suitable for most couples undergoing PGT-M, the use of a fixed set of SNPs may provide inadequate information in certain genetic regions or in consanguineous couples (Konstantinidis et al. 2015). Whole genome sequencing (WGS) has the potential to individualise informative SNP detection and perform concurrent direct mutation detection. However, no studies have evaluated the potential for application of the karyomapping algorithm to WGS data. Material and Methods The Platinum Genomes dataset ( https://sapac.illumina.com/platinumgenomes.html ) was analysed as a model for the application of karyomapping to WGS data. Variant call format (VCF) files were analysed according to the principles of karyomapping to create a map of informative biallelic SNPs in each grandparental haplotype. A model of embryo biopsy was created by diluting DNA from one of the family members (NA12878) to 30pg and whole genome amplification was performed with the Repli-G single cell kit (Qiagen, Hilden, Germany) as a model of trophectoderm biopsy. Whole genome sequencing was performed in triplicate on a high output NextSeq 2500 run (Illumina, California, USA) at average 15x coverage and the number of informative SNPs detected compared to the karyomapping SNP microarray. Comparison of variant calling methods was performed using the Genome Analysis Toolkit v3.4 (Broad Institute, Massachusetts, USA) and DeepVariant (Google, California, USA). Results Analysis of WGS data from the Platinum Genomes family revealed a total of 2,338,158 informative SNPs distributed evenly between grandparental haplotypes, of which 85,053 (3.6%) would have been detectable using the karyomapping SNP array. Analysis of the karyomapping window around common genes requiring PGT-M demonstrated an average 32x increase in the number of targets available for analysis in a PGT-M cycle. Analysis of 15x coverage WGS data in a model of embryo biopsy demonstrated an average 279,851 informative SNPs detected using standard variant calling and an average 285,107 using AI-based variant calling. The median distance between informative SNPs was reduced from 26,782 nucleotides to 1,212 nucleotides when comparing WGS-based karyomapping to SNP array-based karyomapping. Conclusions This study provides preclinical validation for the application of the karyomapping algorithm to WGS data. The markedly increased number of informative SNPs will allow successful feasibility studies for all couples presenting for PGT-M. The decreased distance between informative SNPs detected in a model embryo biopsy will improve diagnostic accuracy, particularly in detecting small double crossover events and reducing the number of cycles in which inadequate informative markers have been detected in the embryo sample. Finally, the use of WGS for diagnostic purposes, especially for rare and undiagnosed genetic disease, will allow the creation of a high resolution digital karyomap for couples with an affected child and improve the transition to IVF and PGT-M.