David A Zeevi1, Fouad Zahdeh2, Yehuda Kling2, Shai Carmi3, Gheona Altarescu2. 1. Medical Genetics Institute, Shaare Zedek Medical Center (SZMC), Bayit Str. 12, P.O.Box 3235, 91031, Jerusalem, Israel. zeevidavid@szmc.org.il. 2. Medical Genetics Institute, Shaare Zedek Medical Center (SZMC), Bayit Str. 12, P.O.Box 3235, 91031, Jerusalem, Israel. 3. Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
Abstract
PURPOSE: Pre-implantation genetic diagnosis (PGD) for molecular disorders requires the construction of parental haplotypes. Classically, haplotype resolution ("phasing") is obtained by genotyping multiple polymorphic markers in both parents and at least one additional relative. However, this process is time-consuming, and immediate family members are not always available. The recent availability of massive genomic data for many populations promises to eliminate the needs for developing family-specific assays and for recruiting additional family members. In this study, we aimed to validate population-assisted haplotype phasing for PGD. METHODS: Targeted sequencing of CFTR gene variants and ~ 1700 flanking polymorphic SNPs (± 2 Mb) was performed on 54 individuals from 12 PGD families of (a) Full Ashkenazi (FA; n = 16), (b) mixed Ashkenazi (MA; n = 23 individuals with at least one Ashkenazi and one non-Ashkenazi grandparents), or (c) non-Ashkenazi (NA; n = 15) descent. Heterozygous genotype calls in each individual were phased using various whole genome reference panels and appropriate computational models. All computationally derived haplotype predictions were benchmarked against trio-based phasing. RESULTS: Using the Ashkenazi reference panel, phasing of FA was highly accurate (99.4% ± 0.2% accuracy); phasing of MA was less accurate (95.4% ± 4.5% accuracy); and phasing of NA was predictably low (83.4% ± 6.6% accuracy). Strikingly, for founder mutation carriers, our haplotyping approach facilitated near perfect phasing accuracy (99.9% ± 0.1% and 98.2% ± 2.8% accuracy for W1282X and delF508 carriers, respectively). CONCLUSIONS: Our results demonstrate the feasibility of replacing classical haplotype phasing with population-based phasing with uncompromised accuracy.
PURPOSE: Pre-implantation genetic diagnosis (PGD) for molecular disorders requires the construction of parental haplotypes. Classically, haplotype resolution ("phasing") is obtained by genotyping multiple polymorphic markers in both parents and at least one additional relative. However, this process is time-consuming, and immediate family members are not always available. The recent availability of massive genomic data for many populations promises to eliminate the needs for developing family-specific assays and for recruiting additional family members. In this study, we aimed to validate population-assisted haplotype phasing for PGD. METHODS: Targeted sequencing of CFTR gene variants and ~ 1700 flanking polymorphic SNPs (± 2 Mb) was performed on 54 individuals from 12 PGD families of (a) Full Ashkenazi (FA; n = 16), (b) mixed Ashkenazi (MA; n = 23 individuals with at least one Ashkenazi and one non-Ashkenazi grandparents), or (c) non-Ashkenazi (NA; n = 15) descent. Heterozygous genotype calls in each individual were phased using various whole genome reference panels and appropriate computational models. All computationally derived haplotype predictions were benchmarked against trio-based phasing. RESULTS: Using the Ashkenazi reference panel, phasing of FA was highly accurate (99.4% ± 0.2% accuracy); phasing of MA was less accurate (95.4% ± 4.5% accuracy); and phasing of NA was predictably low (83.4% ± 6.6% accuracy). Strikingly, for founder mutation carriers, our haplotyping approach facilitated near perfect phasing accuracy (99.9% ± 0.1% and 98.2% ± 2.8% accuracy for W1282X and delF508 carriers, respectively). CONCLUSIONS: Our results demonstrate the feasibility of replacing classical haplotype phasing with population-based phasing with uncompromised accuracy.
Entities:
Keywords:
CFTR; Haplotype phasing; Identity by descent; PGD; Population-based phasing
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