Haplotype-aware inference of human chromosome abnormalities

Area of Science:

• Genetics
• Reproductive Biology
• Bioinformatics

Background:

• Aneuploidy, the presence of extra or missing chromosomes, is a primary cause of pregnancy loss and in vitro fertilization (IVF) failure.
• Current preimplantation genetic testing for aneuploidy (PGT-A) methods, often based on sequencing, cannot detect large-scale abnormalities like triploidy or distinguish between meiotic and mitotic aneuploidies.

Purpose of the Study:

• To develop and validate a statistical method for distinguishing meiotic and mitotic aneuploidies and genome-wide ploidy abnormalities using low-coverage whole-genome sequencing data.
• To enhance the accuracy and scope of preimplantation genetic testing for aneuploidy (PGT-A) for improved IVF success rates.

Main Methods:

• Developed a statistical approach, LD-informed PGT-A (LD-PGTA), leveraging allele frequencies and linkage disequilibrium (LD) from population reference panels.
• Applied the method to low-coverage whole-genome sequencing data, assessing accuracy at varying coverage levels (down to 0.05 ×).
• Evaluated the method's ability to differentiate meiosis I and meiosis II errors at higher coverage based on centromeric signatures.

Main Results:

• LD-PGTA demonstrates high accuracy in distinguishing aneuploidy types even with very low sequencing coverage.
• The method can differentiate between meiosis I and meiosis II errors, providing deeper insights into chromosome abnormality origins.
• LD-PGTA offers a practical tool for improving genetic testing in IVF settings.

Conclusions:

• LD-informed PGT-A (LD-PGTA) is a robust statistical method for analyzing low-coverage sequencing data to identify various forms of aneuploidy.
• This approach has the potential to significantly improve preimplantation genetic testing for aneuploidy (PGT-A), leading to better IVF outcomes.
• LD-PGTA provides valuable insights into the mechanisms underlying human chromosome abnormalities.