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Simultaneous detection of genomic imbalance in patients receiving preimplantation genetic testing for monogenic diseases (PGT-M).
- Source :
- Frontiers in Genetics; 9/29/2022, Vol. 13, p1-14, 14p
- Publication Year :
- 2022
-
Abstract
- Background: Preimplantation genetic test for monogenic disorders (PGT-M) has been used to select genetic disease-free embryos for implantation during in vitro fertilization (IVF) treatment. However, embryos tested by PGT-M have risks of harboring chromosomal aneuploidy. Hence, a universal method to detect monogenic diseases and genomic imbalances is required. Methods: Here, we report a novel PGT-A/M procedure allowing simultaneous detection of monogenic diseases and genomic imbalances in one experiment. Library was prepared in a special way that multiplex polymerase chain reaction (PCR) was integrated into the process of whole genome amplification. The resulting library was used for one-step low-pass whole genome sequencing (WGS) and high-depth target enrichment sequencing (TES). Results: The TAGs-seq PGT-A/M was first validated with genomic DNA (gDNA) and the multiple displacement amplification (MDA) products of a cell line. Over 90% of sequencing reads covered the whole-genome region with around 0.3-0.4 × depth, while around 5.4%-7.3% of reads covered target genes with >10000 × depth. Then, for clinical validation, 54 embryos from 8 women receiving PGT-M of β-thalassemia were tested by the TAGs-seq PGT-A/M. In each embryo, an average of 20.0 million reads with 0.3 × depth of the whole-genome region was analyzed for genomic imbalance, while an average of 0.9 million reads with 11260.0 × depth of the target gene HBB were analyzed for β-thalassemia. Eventually, 18 embryos were identified with genomic imbalance with 81.1% consistency to karyomapping results. 10 embryos contained β-thalassemia with 100% consistency to conventional PGT-M method. Conclusion: TAGs-seq PGT-A/M simultaneously detected genomic imbalance and monogenic disease in embryos without dramatic increase of sequencing data output. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 16648021
- Volume :
- 13
- Database :
- Complementary Index
- Journal :
- Frontiers in Genetics
- Publication Type :
- Academic Journal
- Accession number :
- 159678883
- Full Text :
- https://doi.org/10.3389/fgene.2022.976131