Abstract
Noninvasive prenatal diagnosis (NIPD) has become a common, safe, and effective procedure for detection of inherited diseases early in pregnancy. It is based on the analysis of fetal cell-free DNA (cffDNA) derived from the placenta, circulating in the maternal plasma. De novo mutations, although rare, cause a considerable number of dominant genetic disorders. Due to the sparse representation of fetal-derived sequences in the blood, the challenge of detecting low frequency fetal de novo mutations becomes preponderant. Hence, this detection type requires deep genome-wide sequencing of cffDNA from maternal plasma and a unique analysis approach. Here we suggest and discuss a method for identifying de novo mutations based on whole genome sequencing (WGS) of cell-free DNA (cfDNA) from maternal plasma samples. Our method consists of an augmented pipeline for analysis of de novo mutation candidates. It begins with an enhanced noninvasive fetal variant calling step, followed by a candidate de novo mutation filtration, and then finally, a supervised machine learning approach is utilized for reduction of false positive rates. Overall, this study provides a basis for genome-wide de novo mutation analysis in NIPD procedures, which could be used in any procedure where rare de novo mutations should be carefully picked out of a sea of data.
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References
Conrad DF, Keebler JEM, DePristo MA et al (2011) Variation in genome-wide mutation rates within and between human families. Nat Genet 43:712–714. https://doi.org/10.1038/ng.862
Veltman JA, Brunner HG (2012) De novo mutations in human genetic disease. Nat Rev Genet 13:565–575. https://doi.org/10.1038/nrg3241
Hayward J, Chitty LS (2018) Beyond screening for chromosomal abnormalities: advances in non-invasive diagnosis of single gene disorders and fetal exome sequencing. Semin Fetal Neonatal Med 23:94–101. https://doi.org/10.1016/j.siny.2017.12.002
Akolekar R, Beta J, Picciarelli G et al (2015) Procedure-related risk of miscarriage following amniocentesis and chorionic villus sampling: a systematic review and meta-analysis. Ultrasound Obstet Gynecol 45:16–26. https://doi.org/10.1002/uog.14636
Tabor A, Alfirevic Z (2010) Update on procedure-related risks for prenatal diagnosis techniques. Fetal Diagn Ther 27:1–7. https://doi.org/10.1159/000271995
Lo YMD, Lun FMF, Chan KCA et al (2007) Digital PCR for the molecular detection of fetal chromosomal aneuploidy. Proc Natl Acad Sci 104:13116. https://doi.org/10.1073/pnas.0705765104
Fan HC, Blumenfeld YJ, Chitkara U et al (2008) Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood. Proc Natl Acad Sci 105:16266. https://doi.org/10.1073/pnas.0808319105
Hill M, Compton C, Lewis C et al (2012) Determination of foetal sex in pregnancies at risk of haemophilia: a qualitative study exploring the clinical practices and attitudes of health professionals in the United Kingdom. Haemophilia 18:575–583. https://doi.org/10.1111/j.1365-2516.2011.02653.x
Lewis C, Hill M, Skirton H, Chitty LS (2012) Non-invasive prenatal diagnosis for fetal sex determination: benefits and disadvantages from the service users’ perspective. Eur J Hum Genet 20:1127–1133. https://doi.org/10.1038/ejhg.2012.50
Lam K-WG, Jiang P, Liao GJW et al (2012) Noninvasive prenatal diagnosis of monogenic diseases by targeted massively parallel sequencing of maternal plasma: application to β-thalassemia. Clin Chem 58:1467–1475. https://doi.org/10.1373/clinchem.2012.189589
Chitty LS, Mason S, Barrett AN et al (2015) Non-invasive prenatal diagnosis of achondroplasia and thanatophoric dysplasia: next-generation sequencing allows for a safer, more accurate, and comprehensive approach. Prenat Diagn 35:656–662. https://doi.org/10.1002/pd.4583
Rabinowitz T, Polsky A, Golan D et al (2019) Bayesian-based noninvasive prenatal diagnosis of single-gene disorders. Genome Res 29:428–438. https://doi.org/10.1101/gr.235796.118
Kitzman JO, Snyder MW, Ventura M et al (2012) Non-invasive whole genome sequencing of a human fetus. Sci Transl Med 4:137ra76. https://doi.org/10.1126/scitranslmed.3004323
Chan KCA, Jiang P, Sun K et al (2016) Second generation noninvasive fetal genome analysis reveals de novo mutations, single-base parental inheritance, and preferred DNA ends. Proc Natl Acad Sci 113:E8159–E8168. https://doi.org/10.1073/pnas.1615800113
Zhang J, Li J, Saucier JB et al (2019) Non-invasive prenatal sequencing for multiple Mendelian monogenic disorders using circulating cell-free fetal DNA. Nat Med 25:439–447. https://doi.org/10.1038/s41591-018-0334-x
DePristo MA, Banks E, Poplin RE et al (2011) A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43:491–498. https://doi.org/10.1038/ng.806
O’Fallon BD, Wooderchak-Donahue W, Crockett DK (2013) A support vector machine for identification of single-nucleotide polymorphisms from next-generation sequencing data. Bioinformatics 29:1361–1366. https://doi.org/10.1093/bioinformatics/btt172
Yadong Wang YL (2014) A gradient-boosting approach for filtering de novo mutations in parent–offspring trios. Bioinformatics 30(13):1830–1836. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4071207/. Accessed 4 Mar 2019
Wan N, Weinberg D, Liu T-Y et al (2018) Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA. Cancer Biol
Ramu A, Noordam MJ, Schwartz RS et al (2013) DeNovoGear: de novo indel and point mutation discovery and phasing. Nat Methods 10:985–987. https://doi.org/10.1038/nmeth.2611
Ashoor G, Syngelaki A, Poon LCY et al (2013) Fetal fraction in maternal plasma cell-free DNA at 11–13 weeks’ gestation: relation to maternal and fetal characteristics. Ultrasound Obstet Gynecol 41:26–32. https://doi.org/10.1002/uog.12331
Hu P, Liang D, Chen Y et al (2019) An enrichment method to increase cell-free fetal DNA fraction and significantly reduce false negatives and test failures for non-invasive prenatal screening: a feasibility study. J Transl Med 17:124. https://doi.org/10.1186/s12967-019-1871-x
Sillence K (2016) Cell-free fetal DNA (cffDNA) enrichment for non-invasive prenatal testing (NIPT): a comparison of molecular techniques
Jorgez CJ, Bischoff FZ (2009) Improving enrichment of circulating fetal DNA for genetic testing: size fractionation followed by whole gene amplification. Fetal Diagn Ther 25:314–319. https://doi.org/10.1159/000235877
Webb A, Madgett T, Miran T et al (2012) Non invasive prenatal diagnosis of aneuploidy: next generation sequencing or fetal DNA enrichment? Balk J Med Genet BJMG 15:17–26. https://doi.org/10.2478/v10034-012-0013-z
Peng XL, Jiang P (2017) Bioinformatics approaches for fetal DNA fraction estimation in noninvasive prenatal testing. Int J Mol Sci 18:453. https://doi.org/10.3390/ijms18020453
Kong A, Frigge ML, Masson G et al (2012) Rate of de novo mutations and the importance of father’s age to disease risk. Nature 488:471–475. https://doi.org/10.1038/nature11396
Arnheim N, Calabrese P (2009) Understanding what determines the frequency and pattern of human germline mutations. Nat Rev Genet 10:478–488. https://doi.org/10.1038/nrg2529
Shang J, Zhu F, Vongsangnak W et al (2014) Evaluation and comparison of multiple aligners for next-generation sequencing data analysis. Biomed Res Int 2014:1–16. https://www.hindawi.com/journals/bmri/2014/309650/abs/. Accessed 8 Jan 2020
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25:1754–1760. https://doi.org/10.1093/bioinformatics/btp324
Faust GG, Hall IM (2014) SAMBLASTER: fast duplicate marking and structural variant read extraction. Bioinformatics 30:2503–2505. https://doi.org/10.1093/bioinformatics/btu314
Li H, Handsaker B, Wysoker A et al (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078–2079. https://doi.org/10.1093/bioinformatics/btp352
Tarasov A, Vilella AJ, Cuppen E et al (2015) Sambamba: fast processing of NGS alignment formats. Bioinformatics 31:2032–2034. https://doi.org/10.1093/bioinformatics/btv098
Garrison E (2012) freebayes: Bayesian haplotype-based genetic polymorphism discovery and genotyping
Danecek P, Auton A, Abecasis G et al (2011) The variant call format and VCFtools. Bioinformatics 27:2156–2158. https://doi.org/10.1093/bioinformatics/btr330
Buitinck L, Louppe G, Blondel M, et al (2013) API design for machine learning software: experiences from the scikit-learn project. ArXiv13090238 Cs
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Peretz-Machluf, R., Rabinowitz, T., Shomron, N. (2021). Genome-Wide Noninvasive Prenatal Diagnosis of De Novo Mutations. In: Shomron, N. (eds) Deep Sequencing Data Analysis. Methods in Molecular Biology, vol 2243. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1103-6_12
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DOI: https://doi.org/10.1007/978-1-0716-1103-6_12
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