Article

Detection of=1?Mb microdeletions and microduplications in a single cell using custom oligonucleotide arrays

Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Prenatal Diagnosis (Impact Factor: 2.51). 01/2012; 32(1):10-20. DOI: 10.1002/pd.2855
Source: PubMed

ABSTRACT High resolution detection of genomic copy number abnormalities in a single cell is relevant to preimplantation genetic diagnosis and potentially to noninvasive prenatal diagnosis. Our objective is to develop a reliable array comparative genomic hybridization (CGH) platform to detect genomic imbalances as small as ~1Mb ina single cell.
We empirically optimized the conditions for oligonucleotide-based array CGH using single cells from multiple lymphoblastoid cell lines with known copy number abnormalities. To improve resolution, we designed custom arrays with high density probes covering clinically relevant genomic regions.
The detection of megabase-sized copy number variations (CNVs) in a single cell was influenced by the number of probes clustered in the interrogated region. Using our custom array, we reproducibly detected multiple chromosome abnormalities including trisomy 21, a 1.2Mb Williams syndrome deletion, and a 1.3Mb CMT1A duplication. Replicate analyses yielded consistent results.
Aneuploidy and genomic imbalances with CNVs as small as 1.2Mb in a single cell are detectable by array CGH using arrays with high-density coverage in the targeted regions. This approach has the potential to be applied for preimplantation genetic diagnosis to detect aneuploidy and common microdeletion/duplication syndromes and for noninvasive prenatal diagnosis if single fetal cells can be isolated.

1 Follower
 · 
307 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Comprehensive chromosome analysis techniques such as metaphase-Comparative Genomic Hybridisation (CGH) and array-CGH are available for single-cell analysis. However, while metaphase-CGH and BAC array-CGH have been widely used for Preimplantation Genetic Diagnosis, oligonucleotide array-CGH has not been used in an extensive way. A comparison between oligonucleotide array-CGH and metaphase-CGH has been performed analysing 15 single fibroblasts from aneuploid cell-lines and 18 single blastomeres from human cleavage-stage embryos. Afterwards, oligonucleotide array-CGH and BAC array-CGH were also compared analysing 16 single blastomeres from human cleavage-stage embryos. All three comprehensive analysis techniques provided broadly similar cytogenetic profiles; however, non-identical profiles appeared when extensive aneuploidies were present in a cell. Both array techniques provided an optimised analysis procedure and a higher resolution than metaphase-CGH. Moreover, oligonucleotide array-CGH was able to define extra segmental imbalances in 14.7% of the blastomeres and it better determined the specific unbalanced chromosome regions due to a higher resolution of the technique (≈20 kb). Applicability of oligonucleotide array-CGH for Preimplantation Genetic Diagnosis has been demonstrated in two cases of Robertsonian translocation carriers 45,XY,der(13;14)(q10;q10). Transfer of euploid embryos was performed in both cases and pregnancy was achieved by one of the couples. This is the first time that an oligonucleotide array-CGH approach has been successfully applied to Preimplantation Genetic Diagnosis for balanced chromosome rearrangement carriers.
    PLoS ONE 11/2014; 9(11):e113223. DOI:10.1371/journal.pone.0113223 · 3.53 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Disseminated cancer cells (DCCs) and circulating tumor cells (CTCs) are extremely rare, but comprise the precursors cells of distant metastases or therapy resistant cells. The detailed molecular analysis of these cells may help to identify key events of cancer cell dissemination, metastatic colony formation and systemic therapy escape. Using the Ampli1™ whole genome amplification (WGA) technology and high-resolution oligonucleotide aCGH microarrays we optimized conditions for the analysis of structural copy number changes. The protocol presented here enables reliable detection of numerical genomic alterations as small as 0.1 Mb in a single cell. Analysis of single cells from well-characterized cell lines and single normal cells confirmed the stringent quantitative nature of the amplification and hybridization protocol. Importantly, fixation and staining procedures used to detect DCCs showed no significant impact on the outcome of the analysis, proving the clinical usability of our method. In a proof-of-principle study we tracked the chromosomal changes of single DCCs over a full course of high-dose chemotherapy treatment by isolating and analyzing DCCs of an individual breast cancer patient at four different time points. The protocol enables detailed genome analysis of DCCs and thereby assessment of the clonal evolution during the natural course of the disease and under selection pressures. The results from an exemplary patient provide evidence that DCCs surviving selective therapeutic conditions may be recruited from a pool of genomically less advanced cells, which display a stable subset of specific genomic alterations.
    PLoS ONE 01/2014; 9(1):e85907. DOI:10.1371/journal.pone.0085907 · 3.53 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Advances in whole-genome and whole-transcriptome amplification have permitted the sequencing of the minute amounts of DNA and RNA present in a single cell, offering a window into the extent and nature of genomic and transcriptomic heterogeneity which occurs in both normal development and disease. Single-cell approaches stand poised to revolutionise our capacity to understand the scale of genomic, epigenomic, and transcriptomic diversity that occurs during the lifetime of an individual organism. Here, we review the major technological and biological breakthroughs achieved, describe the remaining challenges to overcome, and provide a glimpse into the promise of recent and future developments.
    PLoS Genetics 01/2014; 10(1):e1004126. DOI:10.1371/journal.pgen.1004126 · 8.17 Impact Factor

Full-text

Download
178 Downloads
Available from
May 17, 2014