Accurate detection of segmental aneuploidy in preimplantation genetic screening using targeted next-generation DNA sequencing

Umbarger, Mark A.; Germain, K.; Gore, Athurva; Breton, Benjamin; Walters-Sen, Lauren; Mullen, T.; Faulkner, Nicole

doi:10.1016/j.fertnstert.2016.07.449

Cited by 3 publications

(6 citation statements)

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“…Precision was 98% for replicate samples within individual test batches and 100% for replicate samples split across multiple test batches. These results were similar to three validation studies conducted previously in our Cambridge, MA laboratory (Gole et al, 2016;Umbarger et al, 2017Umbarger et al, , 2016.…”

Section: Fast-seqs Assay Validation and Concordance With Veriseqsupporting

confidence: 91%

“…A custom-designed bioinformatics pipeline and visualization software package (Circular Binary Segmentation [CerBeruS]) was implemented to predict copy number along the length of each chromosome based on sequence read depth and to infer ploidy status based on SNP genotyping (Olshen et al, 2004;Umbarger et al, 2017Umbarger et al, , 2016. In brief, each chromosome is computationally "circularized," and segments of sequence are compared to neighboring segments for significant differences in copy number proportions.…”

Section: Fast-seqs Assay Designmentioning

confidence: 99%

“…With the goal of improving access to PGT-A by lowering cost while maintaining clinically robust performance, the FAST-SeqS assay, originally developed for non-invasive prenatal screening (Kinde et al, 2012), was adapted and validated for PGT-A in 2016 (Gole et al, 2016;Umbarger et al, 2016). The goal of assay development was to ensure performance at a level equal to or better than the gold standard market assay at the time (aCGH).…”

Section: Introductionmentioning

confidence: 99%

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Experience analysing over 190,000 embryo trophectoderm biopsies using a novel FAST-SeqS preimplantation genetic testing assay

Walters-Sen

Neitzel

Bristow

et al. 2022

Reproductive BioMedicine Online

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Research Question: Is FAST-SeqS an accurate methodology for preimplantation genetic testing for whole-chromosome aneuploidy (PGT-A), what additional types of chromosomal abnormalities can be assessed, and what are the observed aneuploidy rates in a large clinical cohort?Design: FAST-SeqS, a next-generation sequencing-(NGS-) based assay amplifying genomewide LINE1 repetitive sequences, was validated using reference samples. Sensitivity and specificity were calculated. Clinically-derived trophectoderm biopsies submitted for PGT-A were assessed, and aneuploidy and mosaicism rates among biopsies were determined. Clinicianprovided outcome rates were calculated.Results: Sensitivity and specificity were >95% for all aneuploidy types tested in the validation.Comparison of FAST-SeqS to VeriSeq showed high concordance (98.5%). Among embryos with actionable results (n=182,827), 46.2% were aneuploid. Whole-chromosome aneuploidies were most commonly observed (72.9% without or 8.7% with a segmental aneuploidy [SA]), with rates increasing with egg age, while SA rates did not. SAs (n=20,557) were observed on all chromosomes (most commonly deletions), with frequencies roughly correlated with chromosome length. Mosaic-only abnormalities constituted 10.1% (n=3,862/38,145) of samples. Abnormal ploidy constituted 1.8% (n=2,370/128,991) of samples, triploidy being the most common (73.6%). Across 3,297 frozen embryo transfers, the mean clinical pregnancy rate was 62% (range 38-80%); the mean combined ongoing pregnancy and live birth rate was 57% (range 38-72%). Conclusion:FAST-SeqS is a clinically reliable and scalable method for PGT-A, is comparable to whole genome amplification-based platforms, and detects additional information related to ploidy using SNP analysis. Clinical outcomes suggest an ongoing benefit of PGT-A using FAST-SeqS, consistent with other platforms.

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Section: Fast-seqs Assay Validation and Concordance With Veriseqsupporting

confidence: 91%

Section: Fast-seqs Assay Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Experience analysing over 190,000 embryo trophectoderm biopsies using a novel FAST-SeqS preimplantation genetic testing assay

Walters-Sen

Neitzel

Bristow

et al. 2022

Reproductive BioMedicine Online

View full text Add to dashboard Cite

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“…An alternative approach is to model a chromosome as a hidden Markov model (HMM) of sequential loci and determine the most likely chromosomal copy number status at each locus and consequently the overall chromosomal ploidy. Kermany and colleagues used HMM to detect fetal trisomy using high-density SNP markers from a trisomic individual and one parent [20], and similar HMM-based approaches have been previously used to detect both full and sub-chromosomal aneuploidies using binned read counts [21,22].…”

Section: Introductionmentioning

confidence: 99%

Computational framework for targeted high-coverage sequencing based NIPT

et al. 2019

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Non-invasive prenatal testing (NIPT) enables accurate detection of fetal chromosomal trisomies. The majority of publicly available computational methods for sequencing-based NIPT analyses rely on low-coverage whole-genome sequencing (WGS) data and are not applicable for targeted high-coverage sequencing data from cell-free DNA samples. Here, we present a novel computational framework for a targeted high-coverage sequencing-based NIPT analysis. The developed framework uses a hidden Markov model (HMM) in conjunction with a supplemental machine learning model, such as decision tree (DT) or support vector machine (SVM), to detect fetal trisomy and parental origin of additional fetal chromosomes. These models were developed using simulated datasets covering a wide range of biologically relevant scenarios with various chromosomal quantities, parental origins of extra chromosomes, fetal DNA fractions, and sequencing read depths. Developed models were tested on simulated and experimental targeted sequencing datasets. Consequently, we determined the functional feasibility and limitations of each proposed approach and demonstrated that read count-based HMM achieved the best overall classification accuracy of 0.89 for detecting fetal euploidies and trisomies on simulated dataset. Furthermore, we show that by using the DT and SVM on the HMM classification results, it was possible to increase the final trisomy classification accuracy to 0.98 and 0.99, respectively. We demonstrate that read count and allelic ratio-based models can achieve a high accuracy (up to 0.98) for detecting fetal trisomy even if the fetal fraction is as low as 2%. Currently, existing commercial NIPT analysis requires at least 4% of fetal fraction, which can be possibly a challenge in case of early gestational age (<10 weeks) or high maternal body mass index (>35 kg/m 2 ). More accurate detection can be achieved at higher sequencing depth using HMM in conjunction with supplemental models, which significantly improve the trisomy detection especially in borderline scenarios (e.g., very low fetal fraction) and enables to perform NIPT even earlier than 10 weeks of pregnancy.

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“…An alternative approach is to model a chromosome as hidden Markov model (HMM) of sequential loci and determine the most likely chromosomal copy number status at each locus and consequently the overall chromosomal ploidy. Kermany and colleagues used HMM to detect fetal trisomy using high-density SNP markers from a trisomic individual and one parent (19), and similar HMM-based approaches have been previously used to detect both full and sub-chromosomal aneuploidies using binned read counts (20,21).…”

Section: Introductionmentioning

confidence: 99%

Computational framework for targeted high-coverage sequencing based NIPT

Teder

Paluoja

Salumets

et al. 2018

Preprint

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23 Non-invasive prenatal testing (NIPT) enables accurate detection of fetal chromosomal 24 trisomies. The majority of existing computational methods for sequencing-based NIPT 25 analyses rely on low-coverage whole-genome sequencing (WGS) data and are not applicable 26 for targeted high-coverage sequencing data from cell-free DNA samples. 2728 Here, we present a novel computational framework for a targeted high-coverage sequencing-29 based NIPT analysis. The developed methods use a hidden Markov model (HMM)-based 30 approach in conjunction with supplemental machine learning methods, such as decision tree 31 (DT) and support vector machine (SVM), to detect fetal trisomy and parental origin of 32 additional fetal chromosomes. These methods were tested with simulated datasets covering a 33 wide range of biologically relevant scenarios with various chromosomal quantities, parental 34 origins of extra chromosomes, fetal DNA fractions and sequencing read depths.35 Consequently, we determined the functional feasibility and limitations of each proposed 36 approach and demonstrated that read count-based HMM achieved the best overall 37 classification accuracy of 0.89 for detecting fetal euploidies and trisomies. Furthermore, we 38 show that by using the DT and SVM methods on the HMM state classification results, it was 39 possible to increase the final trisomy classification accuracy to 0.98 and 0.99, respectively. 40 41 We demonstrated that read count and allelic ratio-based models can achieve a high accuracy 42 (up to 0.98) for detecting fetal trisomy even if the fetal fraction is as low as 2%. Currently 43 existing methods require at least 4% fetal fraction, which can be an issue in the case of early 44 gestational age (<10 weeks) or elevated maternal body mass index (>35 kg/m 2 ). More 45 accurate detection can be achieved at higher sequencing depth using HMM in conjunction 46 with supplemental methods, which significantly improve the trisomy detection especially in 3 47 borderline scenarios (e.g., very low fetal fraction) and can enable to perform NIPT even 48 earlier than 10 weeks of pregnancy. 49 4 50

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Accurate detection of segmental aneuploidy in preimplantation genetic screening using targeted next-generation DNA sequencing

Cited by 3 publications

References 0 publications

Experience analysing over 190,000 embryo trophectoderm biopsies using a novel FAST-SeqS preimplantation genetic testing assay

Experience analysing over 190,000 embryo trophectoderm biopsies using a novel FAST-SeqS preimplantation genetic testing assay

Computational framework for targeted high-coverage sequencing based NIPT

Computational framework for targeted high-coverage sequencing based NIPT

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