DNA mutations drive a number of cellular pathophysiologies such as cancer.
These mutations can either be highly focused in the case of a single nucleotide polymorphism (SNP) or more broad in the case of a DNA deletion, amplification, or inversion.
Some mutations are silent (as is the case with a number of SNPs) but can still provide information as to linkage with specific cellular traits.
The PMGC provides solutions that help to identify and characterize these structural anomalies, with resolution down to the single nucleotide.
Identification of SNPs can be carried out in a couple different ways – either using arrays to profile known SNPs or sequencing to detect both known and novel SNPs. Array technologies provide a means to profile a large number (hundreds of thousands) of known SNPs for determination of mutation status, or identification of copy number variation in a cost effect manner. Deep sequencing approaches can either be used to look at the entire exome (all coding regions) or at defined sections of the genome (such as a selection of key genes).
Larger structural rearrangements can be detected either through array comparative genomic hybridization (aCGH) or deep sequencing. aCGH is a microarray-based technique used to identify chromosomal copy number changes (deletions, amplifications, and micro-amplifications) genome-wide. This technique can also be used to characterize various carcinomas and to identify and map disease genes involved with schizophrenia, depression, autism, and developmental delay. Alternatively, HTS can be used to identify many of these changes, either at the whole exome level, or at the level of a specific set of genes. Again, the PMGC offers a number of solutions and would be happy to discuss the best approach for your particular project.
aCGH services are available using the Agilent platform.
Agilent has CGH arrays for a number of species, including human, mouse, rat, chicken, rhesus monkey, canine, bovine, chimpanzee and rice.
Custom CGH arrays for other species are also available.
SNP analysis is available using Affymetrix array, Illumina array and Illumina sequencing platforms. Not sure which platform is best suited to your experimental needs? Click here.
The amount of sample required for hybridization depends on the platform. For example, most oligonucleotide arrays require at least 100 ng of DNA and some have developed a PCR amplification procedure that allows as a little as 10 ng of input genomic DNA. Most labelling protocols for cDNA and BAC arrays require 1-3 μg of genomic DNA for hybridization, which may limit the use of these arrays to large tumours and cell lines.
As the names suggest, disease-specific arrays survey regions of the genome that are often altered in certain disease states and chromosome-specific arrays contain elements specific to a particular chromosome. The disadvantage of these arrays is that they require a priori knowledge of the regions of interest. Genome-wide arrays cover the entire genome allowing for identification of chromosomal changes in suspected and novel regions.
aCGH provides rapid genome-wide analysis at high resolution and the information provided by aCGH experiments can be directly linked to physical and genetic maps of the human genome. Traditional CGH has limited resolution and data analysis requires expertise in cytogenetics.
SeGA stands for Segmental Genomic Alterations and it is SeGAs that aCGH is used to detect. Identifying these genomic alterations will yield molecular targets for diagnosing diseases and treating patients.
In terms of the spotted elements, there are two main types of aCGH arrays. One type is spotted with PCR amplified cDNA or bacterial artificial chromosome (BAC), that are usually in the range of 150 to 200 kb. Another type is spotted with synthetic oligonucleotides in the range of 25-85 bp in length.
A marker-based array is one that consists of elements that do not sequentially overlap. The resolution of this type of array is dependent on the distances between the clones and the size of the clones.
A tiling array is one that contiguously covers the genome using overlapping clones. The very high resolution of this type of array allows gains or losses of 40-80 kb regions to be detected.
SMRT stands for Sub-Megabase Resolution Tiling array.
A genome complexity reduction step is a measure that amplifies the genomic sequences of interest, and thus minimizes the inherent "noise" generated by the remaining sequence of the genome. In terms of experiments involving microarrays, genome reduction can improve hybridization kinetics and signal-to-noise ratios and reduce cross-hybridization of the array elements to multiple genomic loci. Genomic complexity reduction can be achieved by target amplification by PCR and by strategies that use polymerase extension and probe ligation.
ROMA stands for Representative Oligonucleotide Microarray Analysis. This method reduces the complexity of the genomic DNA sample to about 2.5% of the genome by a restriction enzyme digest and linker-mediated PCR amplification.
Fluorescent in situ hybridizations (FISH) experiments are done to confirm deletions and duplications identified by microarray analysis.