O-271 Two component resolution of mosaic samples in PGT-A: primary template amplification (PTA) and independent analysis using copy-number variation and allelic balance
Authors: Weier C , Griffith A , McKissock K , Brown K 
Published: July 2024

Study question

How does accurate, unbiased whole genome amplification and tiered, independent, two component analysis impact PGT-A results?

Summary answer

When compared to previous methods a PGT-A workflow utilizing PTA followed by a CNV and allelic balance-based analysis generated more conclusive results.

What is known already

Accurate PGT-A results require unbiased error-free whole genome amplification from the trophectoderm biopsy and smart bioinformatics utilities to fully analyze and consider the large complex datasets. PTA generates fewer errors, greater coverage, and reduced allele drop-out offering the best starting point to interpret the genome of each embryo. Current PGT-A platforms leverage either normalized CNV data OR allelic balance at single nucleotide polymorphisms (SNPs), to detect alterations in the embryonic genome. A pipeline leveraging improved amplification technology and consolidated CNV and SNP data, particularly for putative mosaic and segmental mosaic calls, could reduce uncertainty and provide more accurate PGT-A results.

Study design, size, duration

A retrospective analysis of PGT-A results was undertaken with samples originating from multiple clinics and processed in a single laboratory, from January through December, 2023. Approximately 500 samples were processed simultaneously through two independent PGT-A pipelines. The primary objective was to compare the performance of CNV-only PGT-A with a test leveraging both CNV and SNP data. A secondary objective was to observe the resolution of mosaic embryos.

Participants/materials, setting, methods

De-identified samples were amplified with PTA and sequenced with both shotgun (coverage-based CNV) and capture (SNP-based)-approaches. Method specific analysis was applied to the resulting data. An initial bioinformatics approach analyzed CNV data only for variations in copy-number along the genome, proposing stretches of aneuploidy or mosaicism. A second, tiered analysis extended this data and incorporated SNP-based allelic balance to evaluate candidate regions and confirm the presence of aneuploidy and/or quantify mosaic levels.

Main results and the role of chance

Genome-wide read coverage and SNP data confirmed that PTA accurately and completely amplified the genetic material in each sample with broad distribution of informative data and a low allele drop-out rate. High concordance (95%) was observed for euploid and full aneuploid (whole chromosome and segmental) embryos classified with CNV-alone and CNV/SNV combined analysis. SNP data was processed, and B-allele ratios were used to confirm aneuploidies with particular utility in resolving the location of segmental changes. The classification of mosaic samples was altered in the pipeline leveraging both CNV and SNP data. Of 54 mosaic samples tested, 75% remained mosaic after independent consideration of SNP data, ∼15% and 6% of high-level mosaics were resolved to full aneuploid and euploid, respectively, and ∼25% of low-level mosaics reverted to a euploid classification. The deep SNP data produced during targeted sequencing confirmed the altered allele ratio predicted by CNV data and re-confirmed the presence and proportion of aneuploid cells. Mosaic levels were highly correlated in 90% of re-confirmed mosaic samples. This suggests that the classification of these samples as mosaic is precise and accurate and suggests a strong utility for a two component PGT-A pipeline leveraging CNV and SNV data generated from PTA embryos.

Limitations, reasons for caution

This was a retrospective study with limited sample numbers.

Wider implications of the findings

The study highlights the strong advantages of a hybrid PGT-A pipeline, leveraging PTA and two component analysis of coverage and allelic balance, particularly to resolve mosaic embryos more accurately. Overall, this could reduce uncertainty and deliver more confident PGT-A results for embryo transfer decision making.

Trial registration number

not applicable