Piecing together the problems in diagnosing low-level chromosomal mosaicism

Low-level somatic chromosomal mosaicism, which usually arises from post-zygotic errors, is a known cause of several well defined genetic syndromes and has been implicated in various multifactorial diseases. It is, however, not easy to diagnose, as various physical and technical factors complicate its identification

Direct fluorescent labelling of clones by DOP PCR

<p>Abstract</p> <p>Background</p> <p>Array Comparative Genomic Hybridisation (array CGH) is a powerful technique for the analysis of constitutional chromosomal anomalies. Chromosomal duplications or deletions detected by array CGH need subsequently to be validated by other methods. One method of validation is Fluorescence <it>in situ </it>Hybridisation (FISH). Traditionally, fluorophores or hapten labelling is performed by nick translation or random prime labelling of purified Bacterial Artificial Chromosome (BAC) products. However, since the array targets have been generated from Degenerate Oligonucleotide Primed (DOP) amplified BAC clones, we aimed to use these DOP amplified BAC clones as the basis of an automated FISH labelling protocol. Unfortunately, labelling of DOP amplified BAC clones by traditional labelling methods resulted in high levels of background.</p> <p>Results</p> <p>We designed an improved labelling method, by means of degenerate oligonucleotides that resulted in optimal FISH probes with low background.</p> <p>Conclusion</p> <p>We generated an improved labelling method for FISH which enables the rapid generation of FISH probes without the need for isolating BAC DNA. We labelled about 900 clones with this method with a success rate of 97%.</p

Single-cell copy number variation detection

Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data

Somatic Genomic Variations in Early Human Prenatal Development

Only 25 to 30% of conceptions result in a live birth. There is mounting evidence that the cause for this low fecundity is an extremely high incidence of chromosomal rearrangements occurring in the cleavage stage embryo. In this review, we gather all recent evidence for an extraordinary degree of mosaicisms in early embryogenesis. The presence of the rearrangements seen in the cleavage stage embryos can explain the origins of the placental mosaicisms seen during chorion villi sampling as well as the chromosomal anomalies seen in early miscarriages. Whereas these rearrangements often lead to implantation failure and early miscarriages, natural selection of the fittest cells in the embryo is the likely mechanism leading to healthy fetuses

New Array Approaches to Explore Single Cells Genomes

Microarray analysis enables the genome-wide detection of copy number variations and the investigation of chromosomal instability. Whereas array techniques have been well established for the analysis of unamplified DNA derived from many cells, it has been more challenging to enable the accurate analysis of single cell genomes. In this review, we provide an overview of single cell DNA amplification techniques, the different array approaches, and discuss their potential applications to study human embryos

Small supernumerary marker chromosomes (sSMC) in humans; are there B chromosomes hidden among them

<p>Abstract</p> <p>Background</p> <p>Small supernumerary marker chromosomes (sSMC) and B-chromosomes represent a heterogeneous collection of chromosomes added to the typical karyotype, and which are both small in size. They may consist of heterochromatic and/or euchromatic material. Also a predominance of maternal transmission was reported for both groups. Even though sSMC and B-chromosomes show some similarity it is still an open question if B-chromosomes are present among the heterogeneous group of sSMC. According to current theories, sSMC would need drive, drift or beneficial effects to increase in frequency in order to become B chromosome. However, up to now no B-chromosomes were described in human.</p> <p>Results</p> <p>Here we provide first evidence and discuss, that among sSMC B-chromosomes might be hidden. We present two potential candidates which may already be, or may in future evolve into B chromosomes in human: (i) sSMC cases where the marker is stainable only by DNA derived from itself; and (ii) acrocentric-derived inverted duplication sSMC without associated clinical phenotype. Here we report on the second sSMC stainable exclusively by its own DNA and show that for acrocentric derived sSMC 3.9× more are familial cases than reported for other sSMC.</p> <p>Conclusion</p> <p>The majority of sSMC are not to be considered as B-chromosomes. Nonetheless, a minority of sSMC show similarities to B-chromosomes. Further studies are necessary to come to final conclusions for that problem.</p

An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH

<p>Abstract</p> <p>Background</p> <p>Comparative genomic hybridization microarrays for the detection of constitutional chromosomal aberrations is the application of microarray technology coming fastest into routine clinical application. Through genotype-phenotype association, it is also an important technique towards the discovery of disease causing genes and genomewide functional annotation in human. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient against a normal reference sample. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the "normal" reference instead of a patient aberration. Instead, we apply an experimental loop design that compares three patients in three hybridizations.</p> <p>Results</p> <p>We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of 27 patients seen at our genetics center, we observed that the linear models of the log ratios are advantageous over the mixed models of the absolute intensities.</p> <p>Conclusion</p> <p>The loop design and the performance of the statistical analysis contribute to the quick adoption of array CGH as a routine diagnostic tool. They lower the detection limit of mosaicisms and improve the assignment of copy number variation for genetic association studies.</p

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

A small supernumerary marker chromosome present in a Turner syndrome patient not derived from X- or Y-chromosome: a case report

<p>Abstract</p> <p>Background</p> <p>Small supernumerary marker chromosomes (sSMC) can be present in numerically abnormal karyotypes like in a 'Turner-syndrome karyotype' mos 45,X/46,X,+mar.</p> <p>Results</p> <p>Here we report the first case of an sSMC found in Turner syndrome karyotypes (sSMC^T) derived from chromosome 14 in a Turner syndrome patient. According to cytogenetic and molecular cytogenetic characterization the karyotype was 46,X,+del(14)(q11.1). The present case is the third Turner syndrome case with an sSMC^Tnot derived from the X- or the Y-chromosome.</p> <p>Conclusion</p> <p>More comprehensive characterization of such sSMC^Tmight identify them to be more frequent than only ~0.6% in Turner syndrome cases according to available data.</p

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