Design considerations for array CGH to oligonucleotide arrays

Functional performance of aCGH design for clinical cytogenetics

Array-comparative genomic hybridization (aCGH) technology enables rapid, high-resolution analysis of genomic rearrangements. With the use of it, genome copy number changes and rearrangement breakpoints can be detected and analyzed at resolutions down to a few kilobases. An exon array CGH approach proposed recently accurately measures copy-number changes of individual exons in the human genome. The crucial and highly non-trivial starting task is the design of an array, i.e. the choice of appropriate (multi)set of oligos. The success of the whole high-level analysis depends on the quality of the design. Also, the comparison of several alternative designs of array CGH constitutes an important step in development of new diagnostic chip. In this paper, we deal with these two often neglected issues. We propose a new approach to measure the quality of array CGH designs. Our measures reflect the robustness of rearrangements detection to the noise (mostly experimental measurement error). The method is parametrized by the segmentation algorithm used to identify aberrations. We implemented the efficient Monte Carlo method for testing noise robustness within DNAcopy procedure. Developed framework has been applied to evaluation of functional quality of several optimized array designs.

Experimental analysis of oligonucleotide microarray design criteria to detect deletions by comparative genomic hybridization

Background

Microarray comparative genomic hybridization (CGH) is currently one of the most powerful techniques to measure DNA copy number in large genomes. In humans, microarray CGH is widely used to assess copy number variants in healthy individuals and copy number aberrations associated with various diseases, syndromes and disease susceptibility. In model organisms such as Caenorhabditis elegans (C. elegans) the technique has been applied to detect mutations, primarily deletions, in strains of interest. Although various constraints on oligonucleotide properties have been suggested to minimize non-specific hybridization and improve the data quality, there have been few experimental validations for CGH experiments. For genomic regions where strict design filters would limit the coverage it would also be useful to quantify the expected loss in data quality associated with relaxed design criteria.

Results

We have quantified the effects of filtering various oligonucleotide properties by measuring the resolving power for detecting deletions in the human and C. elegans genomes using NimbleGen microarrays. Approximately twice as many oligonucleotides are typically required to be affected by a deletion in human DNA samples in order to achieve the same statistical confidence as one would observe for a deletion in C. elegans. Surprisingly, the ability to detect deletions strongly depends on the oligonucleotide 15-mer count, which is defined as the sum of the genomic frequency of all the constituent 15-mers within the oligonucleotide. A similarity level above 80% to non-target sequences over the length of the probe produces significant cross-hybridization. We recommend the use of a fairly large melting temperature window of up to 10°C, the elimination of repeat sequences, the elimination of homopolymers longer than 5 nucleotides, and a threshold of -1 kcal/mol on the oligonucleotide self-folding energy. We observed very little difference in data quality when varying the oligonucleotide length between 50 and 70, and even when using an isothermal design strategy.

Conclusion

We have determined experimentally the effects of varying several key oligonucleotide microarray design criteria for detection of deletions in C. elegans and humans with NimbleGen's CGH technology. Our oligonucleotide design recommendations should be applicable for CGH analysis in most species.

A study of the relationships between oligonucleotide properties and hybridization signal intensities from NimbleGen microarray datasets

Well-defined relationships between oligonucleotide properties and hybridization signal intensities (HSI) can aid chip design, data normalization and true biological knowledge discovery. We clarify these relationships using the data from two microarray experiments containing over three million probes from 48 high-density chips. We find that melting temperature (T_m) has the most significant effect on HSI while length for the long oligonucleotides studied has very little effect. Analysis of positional effect using a linear model provides evidence that the protruding ends of probes contribute more than tethered ends to HSI, which is further validated by specifically designed match fragment sliding and extension experiments. The impact of sequence similarity (SeqS) on HSI is not significant in comparison with other oligonucleotide properties. Using regression and regression tree analysis, we prioritize these oligonucleotide properties based on their effects on HSI. The implications of our discoveries for the design of unbiased oligonucleotides are discussed. We propose that isothermal probes designed by varying the length is a viable strategy to reduce sequence bias, though imposing selection constraints on other oligonucleotide properties is also essential.

Optimal design of oligonucleotide microarrays for measurement of DNA copy-number

Copy-number variants (CNVs) occur frequently within the human genome, and may be associated with many human phenotypes. If disease association studies of CNVs are to be performed routinely, it is essential that the copy-number status be accurately genotyped. We systematically assessed the dynamic range response of an oligonucleotide microarray platform to accurately predict copy-number in a set of seven patients who had previously been shown to carry between 1 and 6 copies of an approximately 4 Mb region of 15q12.2-q13.1. We identify probe uniqueness, probe length, uniformity of probe melting temperature, overlap with SNPs and common repeats (particularly Alu elements) and guanine homopolymer content as parameters that significantly affect probe performance. Further, we prove the influence of these criteria on array performance by using these parameters to prospectively filter data from a second array design covering an independent genomic region and observing significant improvements in data quality. The informed selection of probes which have superior performance characteristics allows the prospective design of oligonucleotide arrays which show increased sensitivity and specificity compared with current designs. Although based on the analysis of data from comparative genomic hybridization experiments, we anticipate that our results are relevant to the design of improved oligonucleotide arrays for high-throughput copy-number genotyping of complex regions of the human genome.

Clinical implementation of chromosomal microarray analysis: summary of 2513 postnatal cases

BACKGROUND

Array Comparative Genomic Hybridization (a-CGH) is a powerful molecular cytogenetic tool to detect genomic imbalances and study disease mechanism and pathogenesis. We report our experience with the clinical implementation of this high resolution human genome analysis, referred to as Chromosomal Microarray Analysis (CMA).

METHODS AND FINDINGS

CMA was performed clinically on 2513 postnatal samples from patients referred with a variety of clinical phenotypes. The initial 775 samples were studied using CMA array version 4 and the remaining 1738 samples were analyzed with CMA version 5 containing expanded genomic coverage. Overall, CMA identified clinically relevant genomic imbalances in 8.5% of patients: 7.6% using V4 and 8.9% using V5. Among 117 cases referred for additional investigation of a known cytogenetically detectable rearrangement, CMA identified the majority (92.5%) of the genomic imbalances. Importantly, abnormal CMA findings were observed in 5.2% of patients (98/1872) with normal karyotypes/FISH results, and V5, with expanded genomic coverage, enabled a higher detection rate in this category than V4. For cases without cytogenetic results available, 8.0% (42/524) abnormal CMA results were detected; again, V5 demonstrated an increased ability to detect abnormality. Improved diagnostic potential of CMA is illustrated by 90 cases identified with 51 cryptic microdeletions and 39 predicted apparent reciprocal microduplications in 13 specific chromosomal regions associated with 11 known genomic disorders. In addition, CMA identified copy number variations (CNVs) of uncertain significance in 262 probands; however, parental studies usually facilitated clinical interpretation. Of these, 217 were interpreted as familial variants and 11 were determined to be de novo; the remaining 34 await parental studies to resolve the clinical significance.

CONCLUSIONS

This large set of clinical results demonstrates the significantly improved sensitivity of CMA for the detection of clinically relevant genomic imbalances and highlights the need for comprehensive genetic counseling to facilitate accurate clinical correlation and interpretation.