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      Genome-wide noninvasive prenatal diagnosis of monogenic disorders: Current and future trends

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          Abstract

          Noninvasive prenatal diagnosis (NIPD) is a risk-free alternative to invasive methods for prenatal diagnosis, e.g. amniocentesis. NIPD is based on the presence of fetal DNA within the mother’s plasma cell-free DNA (cfDNA). Though currently available for various monogenic diseases through detection of point mutations, NIPD is limited to detecting one mutation or up to several genes simultaneously. Noninvasive prenatal whole exome/genome sequencing (WES/WGS) has demonstrated genome-wide detection of fetal point mutations in a few studies. However, Genome-wide NIPD of monogenic disorders currently has several challenges and limitations, mainly due to the small amounts of cfDNA and fetal-derived fragments, and the deep coverage required. Several approaches have been suggested for addressing these hurdles, based on various technologies and algorithms. The first relevant software tool, Hoobari, recently became available. Here we review the approaches proposed and the paths required to make genome-wide monogenic NIPD widely available in the clinic.

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          Most cited references35

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          Toward better understanding of artifacts in variant calling from high-coverage samples.

          Heng Li (2014)
          Whole-genome high-coverage sequencing has been widely used for personal and cancer genomics as well as in various research areas. However, in the lack of an unbiased whole-genome truth set, the global error rate of variant calls and the leading causal artifacts still remain unclear even given the great efforts in the evaluation of variant calling methods. We made 10 single nucleotide polymorphism and INDEL call sets with two read mappers and five variant callers, both on a haploid human genome and a diploid genome at a similar coverage. By investigating false heterozygous calls in the haploid genome, we identified the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample as the two major sources of errors, which press for continued improvements in these two areas. We estimated that the error rate of raw genotype calls is as high as 1 in 10-15 kb, but the error rate of post-filtered calls is reduced to 1 in 100-200 kb without significant compromise on the sensitivity. BWA-MEM alignment and raw variant calls are available at http://bit.ly/1g8XqRt scripts and miscellaneous data at https://github.com/lh3/varcmp. hengli@broadinstitute.org Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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            Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood.

            We directly sequenced cell-free DNA with high-throughput shotgun sequencing technology from plasma of pregnant women, obtaining, on average, 5 million sequence tags per patient sample. This enabled us to measure the over- and underrepresentation of chromosomes from an aneuploid fetus. The sequencing approach is polymorphism-independent and therefore universally applicable for the noninvasive detection of fetal aneuploidy. Using this method, we successfully identified all nine cases of trisomy 21 (Down syndrome), two cases of trisomy 18 (Edward syndrome), and one case of trisomy 13 (Patau syndrome) in a cohort of 18 normal and aneuploid pregnancies; trisomy was detected at gestational ages as early as the 14th week. Direct sequencing also allowed us to study the characteristics of cell-free plasma DNA, and we found evidence that this DNA is enriched for sequences from nucleosomes.
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              Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants.

              We compared whole-exome sequencing (WES) and whole-genome sequencing (WGS) in six unrelated individuals. In the regions targeted by WES capture (81.5% of the consensus coding genome), the mean numbers of single-nucleotide variants (SNVs) and small insertions/deletions (indels) detected per sample were 84,192 and 13,325, respectively, for WES, and 84,968 and 12,702, respectively, for WGS. For both SNVs and indels, the distributions of coverage depth, genotype quality, and minor read ratio were more uniform for WGS than for WES. After filtering, a mean of 74,398 (95.3%) high-quality (HQ) SNVs and 9,033 (70.6%) HQ indels were called by both platforms. A mean of 105 coding HQ SNVs and 32 indels was identified exclusively by WES whereas 692 HQ SNVs and 105 indels were identified exclusively by WGS. We Sanger-sequenced a random selection of these exclusive variants. For SNVs, the proportion of false-positive variants was higher for WES (78%) than for WGS (17%). The estimated mean number of real coding SNVs (656 variants, ∼3% of all coding HQ SNVs) identified by WGS and missed by WES was greater than the number of SNVs identified by WES and missed by WGS (26 variants). For indels, the proportions of false-positive variants were similar for WES (44%) and WGS (46%). Finally, WES was not reliable for the detection of copy-number variations, almost all of which extended beyond the targeted regions. Although currently more expensive, WGS is more powerful than WES for detecting potential disease-causing mutations within WES regions, particularly those due to SNVs.
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                Author and article information

                Contributors
                Journal
                Comput Struct Biotechnol J
                Comput Struct Biotechnol J
                Computational and Structural Biotechnology Journal
                Research Network of Computational and Structural Biotechnology
                2001-0370
                14 September 2020
                2020
                14 September 2020
                : 18
                : 2463-2470
                Affiliations
                Faculty of Medicine and Edmond J Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv 69978, Israel
                Author notes
                [* ]Corresponding author. nshomron@ 123456tauex.tau.ac.il
                Article
                S2001-0370(20)30387-1
                10.1016/j.csbj.2020.09.003
                7509788
                33005308
                e2dfda58-ff12-4b6e-9f71-85fd6a8ce79a
                © 2020 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 22 April 2020
                : 17 August 2020
                : 1 September 2020
                Categories
                Review

                genome-wide,noninvasive prenatal diagnosis,nipd,nipt,monogenic disorders

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