Abstract
PurposeThis study is aimed at increasing the accuracy of preimplantation genetic test for monogenic defects (PGT-M).MethodsWe applied Bayesian statistics to optimize data analyses of the mutated allele revealed by sequencing with aneuploidy and linkage analyses (MARSALA) method for PGT-M. In doing so, we developed a Bayesian algorithm for linkage analyses incorporating PCR SNV detection with genome sequencing around the known mutation sites in order to determine quantitatively the probabilities of having the disease-carrying alleles from parents with monogenic diseases. Both recombination events and sequencing errors were taken into account in calculating the probability.ResultsData of 28 in vitro fertilized embryos from three couples were retrieved from two published research articles by Yan et al. (Proc Natl Acad Sci. 112:15964–9, 2015) and Wilton et al. (Hum Reprod. 24:1221–8, 2009). We found the embryos deemed “normal” and selected for transfer in the previous publications were actually different in error probability of 10−4–4%. Notably, our Bayesian model reduced the error probability to 10−6–10−4%. Furthermore, a proband sample is no longer required by our new method, given a minimum of four embryos or sperm cells.ConclusionThe error probability of PGT-M can be significantly reduced by using the Bayesian statistics approach, increasing the accuracy of selecting healthy embryos for transfer with or without a proband sample.
Highlights
Luoxing Xiong and Lei Huang contributed to this work.Electronic supplementary material The online version of this article contains supplementary material, which is available to authorized users.There are 6000–7000 monogenic diseases, affecting millions of people [1]
In 2015, we reported mutated allele revealed by sequencing with aneuploidy and linkage analyses (MARSALA), an improved method for preimplantation genetic test for monogenic defects (PGT-M)
To evaluate previous MARSALA analyses, the error probability was calculated for every embryo using Bayesian model with the same ten sites as the previous MARSALA analyses and the disease causal mutation site together
Summary
Luoxing Xiong and Lei Huang contributed to this work. There are 6000–7000 monogenic diseases, affecting millions of people [1]. Most of these genetic disorders are severe and effective therapies against them are rare [1]. Because specific mutations for the monogenic diseases are usually heterozygous, couples affected can have healthy embryos that can be selected for implantation through in vitro fertilization(IVF) with PGT-M [2]. IVF embryos need to be selected against aneuploidy, which is caused by abnormal chromosome numbers and often leads to live birth failure, by preimplantation genetic testing for aneuploidies (PGT-A) [3,4,5]. To conduct PGT-M and PGT-A at the same time, SNP arrays [6] and generation sequencing (NGS) [7,8,9,10,11] have been used previously
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