19 research outputs found
Computational Estimation of Fetal DNA Fraction in Low Coverage Whole Genome Sequencing Data
Käesoleva töö eesmärk oli leida ja kalibreerida arvutuslik metoodika loote rakuvaba DNA fraktsiooni määramiseks raseda naise vereproovis. Tegemist on rakendusliku teadusuuringuga, mis on eeltingimuseks NIPT testi usaldusväärseks rakendamiseks tervishoiusüsteemis. NIPT on kõige täpsem ja kaasaegsem mitteinvasiivne loote sünnieelne kromosoomihaiguste sõeluuring, mis põhineb madala katvusega täisgenoomi sekveneerimisandmete analüüsil. Metoodika võimaldab määrata loote rakuvaba DNA hulka raseda naise vereproovis nii poiss- kui ka tüdruklootele, mis on vajalik, et iga raseduse rakuvaba DNA analüüsi tulemus oleks usaldusväärne ja arstile ning patsiendile edastatud tulemus tõene. Käesolevas töös kasutati madala katvusega üle-genoomsetest Illumina platvormiga läbiviidud sekveneerimise katsetest saadud 416 Eesti päritolu naise NIPT proove, et välja töötada Y-kromosoomi põhine loote rakuvaba DNA hulga määramine poiss-loodetele. Välja töötatud Y-kromosoomi põhist meetodit kasutati SeqFF arvutusliku metoodika valideerimiseks Eesti NIPT proovidel. SeqFF rakendamine Eesti NIPT proovidel võimaldab määrata loote rakuvaba DNA hulka nii poiss- kui ka tüdrukloodetel. Väljatöötatud algoritm on integreeritud Eestis pakutavasse NIPT täppismeditsiini teenusesse NIPTIFY.The aim of this thesis was to find and 'calibrate' computational methodology for estimating the proportion of cell-free fetal DNA (cffDNA) in pregnant women’s blood sample. This work was done as part of an applied research project aimed to develop a whole genome sequencing (WGS) based non-invasive prenatal testing (NIPT) medical screening test. NIPT is the most up-to-date, accurate and easily applied (non-invasive) prenatal screening method to detect fetal aneuploidies (for example trisomy 21, that causes Down syndrome) with high confidence and already during the first trimester of pregnancy. Commonly, NIPT is based on the low coverage WGS data, generated by the means of Illumina or some another platform technology. Computational tools used for aneuploidy detection can also estimate the proportion of cffDNA in maternal blood for both male and female fetus pregnancies. Fetal fraction calculation is a prerequisite to assure the technical credibility of NIPT screening test. In the current study, low coverage cell-free whole genome sequencing data from 416 pregnant women were used to develop a chromosome Y based estimator for the proportion of cffDNA in male-fetus pregnancy cases. Next, the chromosome Y based estimator was used to validate the credibility of SeqFF computational method with Estonian NIPT samples. This developed approach using SeqFF method on Estonian NIPT samples enables to estimate the proportion of cffDNA in both male and female fetus pregnancies. The SeqFF method is now integrated into the NIPT computation workflow service, validated and in daily practical use as part of the NIPTIFY® screening test
Database with Web Interface for Prenatal Genetic Screening
Bakalaureusetöö raames valmis uudne tarkvara Tervisetehnoloogiate Arenduskeskuse AS (Tervise-TAK) poolt väljatöötamisel oleva tervishoiuteenuse – geenitesti jaoks. Teenus sisaldab lapseootel naise ehk patsiendi varajast geneetilist sõeluuringut, et tuvastada loote kromosoomi võimalikke väärarenguid.Loodud tarkvara on multidistsiplinaarne, hõlmates endas patsiendi kliinilise proovi ja isikuandmete teekonda arsti kabinetist laborisse, läbi andmeanalüüsi protsesside kuni automaatse raporti genereerimiseni. Protsess lõpeb arsti teavitamisega, et geenitest on valmis ja tulemused on koondatud raportisse. Andmeanalüüsi algoritmi välja töötamine ei olnud autori ülesanne, kuid autor tegi andmeanalüüsi väljatöötajatega koostööd, et luua koos toimiva lahenduse testversioon.Tarkvara kiirendab geenitesti tulemuste jõudmist patsiendini, vähendab andmete dubleerimist ja sellest tekkivate sisestusvigade tõenäosust. Lisaks hõlbustab tarkvara geenitesti tellimist, tulemuste verifitseerimist ning on veebipõhise lahendusena tervishoiuteenuse pakkujatele hõlpsalt kasutusele võetav.Tegu on unikaalse veebirakendusega Eestis, sest töö kirjutamise hetkel tellivad tervishoiuteenuse pakkujad analoogseid geeniteste ilma tarkvaralahenduseta. Eelnevale toetudes tõstab loodud lahendus tervishoiu üldist kvaliteeti.The main goal of this Bachelor’s thesis was to create a software solution for a soon to be available service by the Competence Centre on Health Technologies (CCHT). The service includes early genetic screening for pregnant women to identify the most common fetal chromosomal anomalies.The created software solution is multi-disciplinary, covering the entire testing procedure from biological sampling from the doctor's office to automatic report generation. Data analysis software development was not author’s responsibility, but required author’s cooperation to create a workable test version of the given solution.The web application accelerates the screening process and reduces the duplication of data and the number of errors caused by this. This solution can be easily introduced to healthcare providers as it is web-based.It is a unique solution in Estonia as at the time of the writing, no alternative software exists for such fetal screening. On this basis, this solution can heighten the Estonian health care quality
Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples
Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no prior comprehensive, head-to-head accuracy comparison of the various tools has been published. Here, we compared the outcome accuracies obtained for clinically validated samples with five commonly used computational NIPT aneuploidy analysis tools (WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq) across various sequencing depths (coverage) and fetal DNA fractions. The sample set included cases of fetal trisomy 21 (Down syndrome), trisomy 18 (Edwards syndrome), and trisomy 13 (Patau syndrome). We determined that all of the compared tools were considerably affected by lower sequencing depths, such that increasing proportions of undetected trisomy cases (false negatives) were observed as the sequencing depth decreased. We summarised our benchmarking results and highlighted the advantages and disadvantages of each computational NIPT software. To conclude, trisomy detection for lower coverage NIPT samples (e.g. 2.5M reads per sample) is technically possible but can, with some NIPT tools, produce troubling rates of inaccurate trisomy detection, especially in low-FF samples.Author summaryNon-invasive prenatal testing analysis relies on computational algorithms that are used for inferring chromosomal aneuploidies, such as chromosome 21 triploidy in the case of Down syndrome. However, the performance of these algorithms has not been compared on the same clinically validated data. Here we conducted a head-to-head comparison of WGS-based NIPT aneuploidy detection tools. Our findings indicate that at and below 2.5M reads per sample, the least accurate algorithm would miss detection of almost a third of trisomy cases. Furthermore, we describe and quantify a previously undocumented aneuploidy risk uncertainty that is mainly relevant in cases of very low sequencing coverage (at and below 1.25M reads per sample) and could, in the worst-case scenario, lead to a false negative rate of 245 undetected trisomies per 1,000 trisomy cases. Our findings underscore the importance of the informed selection of NIPT software tools in combination with sequencing coverage, which directly impacts NIPT sequencing cost and accuracy
Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples
Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no prior comprehensive, head-to-head accuracy comparison of the various tools has been published. Here, we compared the outcome accuracies obtained for clinically validated samples with five commonly used computational NIPT aneuploidy analysis tools (WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq) across various sequencing depths (coverage) and fetal DNA fractions. The sample set included cases of fetal trisomy 21 (Down syndrome), trisomy 18 (Edwards syndrome), and trisomy 13 (Patau syndrome). We determined that all of the compared tools were considerably affected by lower sequencing depths, such that increasing proportions of undetected trisomy cases (false negatives) were observed as the sequencing depth decreased. We summarised our benchmarking results and highlighted the advantages and disadvantages of each computational NIPT software. To conclude, trisomy detection for lower coverage NIPT samples (e.g. 2.5M reads per sample) is technically possible but can, with some NIPT tools, produce troubling rates of inaccurate trisomy detection, especially in low-FF samples. Author summaryNon-invasive prenatal testing analysis relies on computational algorithms that are used for inferring chromosomal aneuploidies, such as chromosome 21 triploidy in the case of Down syndrome. However, the performance of these algorithms has not been compared on the same clinically validated data. Here we conducted a head-to-head comparison of WGS-based NIPT aneuploidy detection tools. Our findings indicate that at and below 2.5M reads per sample, the least accurate algorithm would miss detection of almost a third of trisomy cases. Furthermore, we describe and quantify a previously undocumented aneuploidy risk uncertainty that is mainly relevant in cases of very low sequencing coverage (at and below 1.25M reads per sample) and could, in the worst-case scenario, lead to a false negative rate of 245 undetected trisomies per 1,000 trisomy cases. Our findings underscore the importance of the informed selection of NIPT software tools in combination with sequencing coverage, which directly impacts NIPT sequencing cost and accuracy.Peer reviewe
Computational framework for targeted high-coverage sequencing based NIPT
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 (35 kg/m2). 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.Peer reviewe
Identification of fetal unmodified and 5-hydroxymethylated CG sites in maternal cell-free DNA for non-invasive prenatal testing
BackgroundMassively parallel sequencing of maternal cell-free DNA (cfDNA) is widely used to test fetal genetic abnormalities in non-invasive prenatal testing (NIPT). However, sequencing-based approaches are still of high cost. Building upon previous knowledge that placenta, the main source of fetal circulating DNA, is hypomethylated in comparison to maternal tissue counterparts of cfDNA, we propose that targeting either unmodified or 5-hydroxymethylated CG sites specifically enriches fetal genetic material and reduces numbers of required analytical sequencing reads thereby decreasing cost of a test.MethodsWe employed uTOPseq and hmTOP-seq approaches which combine covalent derivatization of unmodified or hydroxymethylated CG sites, respectively, with next generation sequencing, or quantitative real-time PCR.ResultsWe detected increased 5-hydroxymethylcytosine (5hmC) levels in fetal chorionic villi (CV) tissue samples as compared with peripheral blood. Using our previously developed uTOP-seq and hmTOP-seq approaches we obtained whole-genome uCG and 5hmCG maps of 10 CV tissue and 38 cfDNA samples in total. Our results indicated that, in contrast to conventional whole genome sequencing, such epigenomic analysis highly specifically enriches fetal DNA fragments from maternal cfDNA. While both our approaches yielded 100% accuracy in detecting Down syndrome in fetuses, hmTOP-seq maintained such accuracy at ultra-low sequencing depths using only one million reads. We identified 2164 and 1589 placenta-specific differentially modified and 5-hydroxymethylated regions, respectively, in chromosome 21, as well as 3490 and 2002 Down syndrome-specific differentially modified and 5-hydroxymethylated regions, respectively, that can be used as biomarkers for identification of Down syndrome or other epigenetic diseases of a fetus.ConclusionsuTOP-seq and hmTOP-seq approaches provide a cost-efficient and sensitive epigenetic analysis of fetal abnormalities in maternal cfDNA. The results demonstrated that T21 fetuses contain a perturbed epigenome and also indicated that fetal cfDNA might originate from fetal tissues other than placental chorionic villi. Robust covalent derivatization followed by targeted analysis of fetal DNA by sequencing or qPCR presents an attractive strategy that could help achieve superior sensitivity and specificity in prenatal diagnostics.Peer reviewe
NIPTmer : rapid k-mer-based software package for detection of fetal aneuploidies
Non-invasive prenatal testing (NIPT) is a recent and rapidly evolving method for detecting genetic lesions, such as aneuploidies, of a fetus. However, there is a need for faster and cheaper laboratory and analysis methods to make NIPT more widely accessible. We have developed a novel software package for detection of fetal aneuploidies from next-generation low-coverage whole genome sequencing data. Our tool - NIPTmer - is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data, and applying linear regression model on the counts. Additionally, the filtering process used for k-mer list creation allows one to take into account the genetic variance in a specific sample, thus reducing the source of uncertainty. The processing time of one sample is less than 10 CPU-minutes on a high-end workstation. NIPTmer was validated on a cohort of 583 NIPT samples and it correctly predicted 37 non-mosaic fetal aneuploidies. NIPTmer has the potential to reduce significantly the time and complexity of NIPT post-sequencing analysis compared to mapping-based methods. For non-commercial users the software package is freely available at http://bioinfo.ut.ee/NIPTMer/.Peer reviewe
Creating basis for introducing non‐invasive prenatal testing in the Estonian public health setting
Objective
The study aimed to validate a whole‐genome sequencing‐based NIPT laboratory method and our recently developed NIPTmer aneuploidy detection software with the potential to integrate the pipeline into prenatal clinical care in Estonia.
Method
In total, 424 maternal blood samples were included. Analysis pipeline involved cell‐free DNA extraction, library preparation and massively parallel sequencing on Illumina platform. Aneuploidies were determined with NIPTmer software, which is based on counting pre‐defined per‐chromosome sets of unique k‐mers from sequencing raw data. SeqFF was implemented to estimate cell‐free fetal DNA (cffDNA) fraction.
Results
NIPTmer identified correctly all samples of non‐mosaic trisomy 21 (T21, 15/15), T18 (9/9), T13 (4/4) and monosomy X (4/4) cases, with the 100% sensitivity. However, one mosaic T18 remained undetected. Six false‐positive (FP) results were observed (FP rate of 1.5%, 6/398), including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). The level of cffDNA of <4% was estimated in eight samples, including one sample with T13 and T18. Despite low cffDNA level, these two samples were determined as aneuploid.
Conclusion
We believe that the developed NIPT method can successfully be used as a universal primary screening test in combination with ultrasound scan for the first trimester fetal examination
A molecular tool for menstrual cycle phase dating of endometrial samples in endometriosis transcriptome studies
Correction: Volume: 101 Issue: 4 Pages: 868-868 DOI: 10.1093/biolre/ioz092Non peer reviewe
DUX4 is a multifunctional factor priming human embryonic genome activation
Double homeobox 4 (DUX4) is expressed at the early pre-implantation stage in human embryos. Here we show that induced human DUX4 expression substantially alters the chromatin accessibility of non-coding DNA and activates thousands of newly identified transcribed enhance-like regions, preferentially located within ERVL-MaLR repeat elements. CRISPR activation of transcribed enhancers by C-terminal DUX4 motifs results in the increased expression of target embryonic genome activation (EGA) genes ZSCAN4 and KHDC1P1. We show that DUX4 is markedly enriched in human zygotes, followed by intense nuclear DUX4 localization preceding and coinciding Kith minor EGA. DUX4 knockdown in human zygotes led to changes in the EGA transcriptome but did not terminate the embryos. We also show that the DUX4 protein interacts with the Mediator complex via the C-terminal KIX binding motif. Our findings contribute to the understanding of DUX4 as a regulator of the non-coding genome.Peer reviewe