ObjectivesThe aims of this study were to test the utility of benchtop NGS platforms for NIPT for trisomy 21 using previously published z score calculation methods and to optimize the sample preparation and data analysis with use of in silico and physical size selection methods.MethodsSamples from 130 pregnant women were analyzed by whole genome sequencing on benchtop NGS systems Ion Torrent PGM and MiSeq. The targeted yield of 3 million raw reads on each platform was used for z score calculation. The impact of in silico and physical size selection on analytical performance of the test was studied.ResultsUsing a z score value of 3 as the cut-off, 98.11% - 100% (104-106/106) specificity and 100% (24/24) sensitivity and 99.06% - 100% (105-106/106) specificity and 100% (24/24) sensitivity were observed for Ion Torrent PGM and MiSeq, respectively. After in silico based size selection both platforms reached 100% specificity and sensitivity. Following the physical size selection z scores of tested trisomic samples increased significantly—p = 0.0141 and p = 0.025 for Ion Torrent PGM and MiSeq, respectively.ConclusionsNoninvasive prenatal testing for chromosome 21 trisomy with the utilization of benchtop NGS systems led to results equivalent to previously published studies performed on high-to-ultrahigh throughput NGS systems. The in silico size selection led to higher specificity of the test. Physical size selection performed on isolated DNA led to significant increase in z scores. The observed results could represent a basis for increasing of cost effectiveness of the test and thus help with its penetration worldwide.

Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensitive and accurate approaches for detecting CNVs. In our previous work, we described a non-invasive prenatal test (NIPT) based on low-coverage massively parallel whole-genome sequencing of total plasma DNA for detection of CNV aberrations ≥600 kbp. We reanalyzed NIPT genomic data from 5018 patients to evaluate CNV aberrations in the Slovak population. Our analysis of autosomal chromosomes identified 225 maternal CNVs (47 deletions; 178 duplications) ranging from 600 to 7820 kbp. According to the ClinVar database, 137 CNVs (60.89%) were fully overlapping with previously annotated variants, 66 CNVs (29.33%) were in partial overlap, and 22 CNVs (9.78%) did not overlap with any previously described variant. Identified variants were further classified with the AnnotSV method. In summary, we identified 129 likely benign variants, 13 variants of uncertain significance, and 83 likely pathogenic variants. In this study, we use NIPT as a valuable source of population specific data. Our results suggest the utility of genomic data from commercial CNV analysis test as background for a population study.

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Low-coverage massively parallel genome sequencing for non-invasive prenatal testing (NIPT) of common aneuploidies is one of the most rapidly adopted and relatively low-cost DNA tests. Since aggregation of reads from a large number of samples allows overcoming the problems of extremely low coverage of individual samples, we describe the possible re-use of the data generated during NIPT testing for genome scale population specific frequency determination of small DNA variants, requiring no additional costs except of those for the NIPT test itself. We applied our method to a data set comprising of 1,548 original NIPT test results and evaluated the findings on different levels, from in silico population frequency comparisons up to wet lab validation analyses using a gold-standard method. The revealed high reliability of variant calling and allelic frequency determinations suggest that these NIPT data could serve as valuable alternatives to large scale population studies even for smaller countries around the world. Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nature methods frequencies of variants in our sample set and six different ExAC populations. Results are shown separately for (a) SNVs based on 68,326 variants; and (b) indels based on 2,909. In both cases, only those variants were used, which were simultaneously identified in each data subset with MAF higher than 5%. AFR = African/African American, AMR = American (Latino), EAS = East Asian, FIN = Finnish, NFE = Non-Finnish European, SAS = South Asian, SVK = Slovak. 2 7 SupplementaryTable 1 (uploaded as a separate Excel sheet of the Supplementary Table file):List of variants identified in the region of the CLCN1 (chloride voltage-gated channel 1, OMIM * 118425) gene in ExAC populations, dbSNP and in our data set. Only 17 of them had ExAC frequencies above 5% (highlighted in yellow). All but five were identified in our data set too with very similar calculated population frequencies. The exceptions, rs34904831, rs191902231, rs182668076, rs2280663 and rs73726622, were found to have ExAC frequencies +/-5% (depending on population). Originally three of these variants were identified in our data set too, although they were filtered out due slightly lower than 5% frequency (Suppl.Tab.1), further suggesting the feasibility of lowering our frequency restrictions. Our data contained also 89 variants missing from ExAC (highlighted in red), but found to have each of them deep intronic positions falling outside ExAC´s BED file. AFR = African/African American, AMR = American, EAS = East Asian, FIN = Finnish, NFE = Non-Finnish European, SAS = South Asian, SVK = Slovak. Supplementary Table 2 (uploaded as a separate Excel sheet of the Supplementary Table file): Verification of 87 positions in five polymorphic genomic loci of 58 randomly selected samples of our sample set from which genomic DNA was available to validation purposes. Reads from positions covered by multiple reads in individual samples (such in case of sample ID4730, where both alleles we...