Non-invasive prenatal testing of beta-hemoglobinopathies using next generation sequencing, in-silico sequence size selection, and haplotyping.
Publication Year:
2024
PubMed ID:
38868964
Funding Grants:
Public Summary:
We developed a non-invasive prenatal test for identifying fetuses that will develop sickle cell disease (SCD) or beta-thalassemia (B-Thal), both of which result from inheriting two mutated copies of the hemoglobin beta (HBB) gene. Our method is used when both parents are known to be carriers for either of these diseases, and involves "next generation sequencing" of short DNA fragments found in the blood plasma of pregnant mothers at risk for carrying a child that might develop SCD or B-Thal, and "long range sequencing" of DNA isolated from the blood of both parents to determine the full DNA sequence of the HBB gene.
We used a bioinformatic method to increase the proportion of fetal DNA fragments (the fetal fraction or FF), relative to maternal DNA fragments. In some cases, this increased FF alone allows us to accurately predict if the fetus will develop SCD or B-Thal. However, combined use of the increased FF and the full sequence of the HBB genes of the parents allowed us to correctly predict wether or not the fetus will develop SCD or B-Thal in cases where use of the increased FF alone was incorrect.
Scientific Abstract:
AIM: To develop a non-invasive prenatal test for beta-hemoglobinopathies based on analyzing maternal plasma by using next generation sequencing. METHODS: We applied next generation sequencing (NGS) of maternal plasma to the non-invasive prenatal testing (NIPT) of autosomal recessive diseases, sickle cell disease and beta-thalassemia. Using the Illumina MiSeq, we sequenced plasma libraries obtained via a Twist Bioscience probe capture panel covering 4 Kb of chromosome 11, including the beta-globin (HBB) gene and >450 genomic single-nucleotide polymorphisms (SNPs) used to estimate the fetal fraction (FF). The FF is estimated by counting paternally transmitted allelic sequence reads present in the plasma but absent in the mother. We inferred fetal beta-globin genotypes by comparing the observed mutation (Mut) and reference (Ref) read ratios to those expected for the three possible fetal genotypes (Mut/Mut; Mut/Ref; Ref/Ref), based on the FF. RESULTS: We bioinformatically enriched the FF by excluding reads over a specified length via in-silico size selection (ISS), favoring the shorter fetal reads, which increased fetal genotype prediction accuracy. Finally, we determined the parental HBB haplotypes, which allowed us to use the read ratios observed at linked SNPs to help predict the fetal genotype at the mutation site(s). We determined HBB haplotypes via Oxford Nanopore MinION sequencing of a 2.2 kb amplicon and aligned these sequences using Soft Genetics' NextGENe LR software. CONCLUSION: The combined use of ISS and HBB haplotypes enabled us to correctly predict fetal genotypes in cases where the prediction based on variant read ratios alone was incorrect.