18.02.07 Other arrays Flashcards
What is the principle of array CGH?
Array Comparative Genomic Hybridisation (CGH) is a molecular technique based upon competitive hybridisation of a test sample and a control sample to identify any possible gains or losses at particular sites of interest.
In a genetic context, what can arrays be used for?
Within a genetic context, arrays can be used on either DNA or RNA samples in order to:
- determine copy number changes of genomic regions across the genome
- genotype multiple genomic loci (SNP arrays)
- measure expression levels of multiple genes (expression profiling)
- sequence various genomic regions in parallel (sequence capture array)
- determine epigenetic changes (methylation profiling)
What are the advantages of BAC arrays
- Less CNVs detected on uncertain significance
- High signal to noise ratio
- Accurate copy number information
- BAC clones spotted multiple times
- Detects segmental mosaicism
- Detect mosaicism as low as 10%
- Follow up FISH work quick as BACs available (same as imbalanced clone)
- Targets mapped to the human reference sequence produced by the International Human Genome Sequencing Consortium
- Interpretation of results (gains/losses etc) straight forward
- Able to target disease regions
What are the disadvantages of BAC arrays?
- Abnormalities may be missed as unable to distinguish gains/losses <85kb or those which fall in 600kb gaps
- LOH/UPD not detected
- Less sub arrays per slide therefore expensive
- Expensive dye swap required
- Only one patient per slide
- Relatively low resolution compared to other arrays therefore lower abnormality detection rate
- Design of array with dense genome coverage limited by the availability of BACs and presence of genomic architecture (eg segmental duplications)
- Gaps in clones prevents precise determination of breakpoints and gene content of the region (max and min coordinates may be quite different)
- Largely superseded by oligo and SNP arrays
- Difficult to reproduce (batch-batch variation)
- Single BAC CNVs may be false positives and need confirmation
What are the principles of a BAC array?
Large PAC, cosmid and fosmid clones of approx. 150-200kb in size are used (derived from the mapping stages of the human genome project).
BAC clones are propagated in vectors in bacteria, purified and amplified and then spotted onto a glass slide using ultra fine needles. Multiple copies of each BAC are spotted onto the array and distributed across the array. Two ‘sub-arrays’ of the same clone set can be spotted onto each slide.
Due to the large size, BACs are very stable and hybridisation is specific (high signal to noise ratio).
Whole genome BAC arrays developed which include a backbone clone set spaced at 500kb-1Mb intervals across the genome. The greater coverage of whole genome arrays compared to the initial targeted arrays developed increased the abnormality detection rate.
Dye swap tests (test and reference labelled in opposite dyes on each sub array) confirm abnormalities and exclude artificial results.
BAC arrays are used less now with the introduction of higher resolution oligo and SNP arrays (Neill et al, 2010). No reason to use them in modern diagnostic labs (some PGD labs may still use them for embryos
Describe some of the features of oligonucleotide arrays.
Made from synthetic single-stranded oligonucleotide fragments, ranging from 25- 85bp in size.
Platform manufacture methods (arraying strategies) include:
a) pre-synthesized oligos spotted on glass slides (usually used to produce custom-made oligo-arrays)
b) oligos are synthesized directly onto a silica surface (in situ synthesis) using laser-directed photochemistry (Nimblgen/Affymetrix eg Gene Chips) or inkjet technologies (Agilent/OGT)
bead technology where oligos, with a unique sequence of ~ 25bp (address) at the 3’ end, are attached to silica beads. The beads are then randomly deposited into wells on a substrate (i.e glass slide). The beads become immobilised in the wells, and the sample can be hybridised. When the array is scanned, the address sequence allows the oligonucleotide-bead combination to be identified. Each bead carries 100k x 70bp of single specific oligo (Illumina).
What is the average size and number of oligos in an oligo array?
Oligos small size (on average ~60mer) allows them to be packed more densely onto an array slide, therefore achieving a far greater number of probes, giving a much higher resolution – approx. 50-200Kb depending on the platform used.
How many arrays can be performed from the same slide? What is the advantage of this?
Multiple sub-arrays can be packed onto the same array slide e.g. 1x1M, 4x180K, 2x400K, 8x60K, allowing multiple patients to be run on a single slide, therefore reducing cost. Examples of available oligo arrays include the SurePrint G3 Human CGH Microarray Kit, 8x60K by Agilent (has eight sub-arrays of 55,000 probes per slide with a median probe spacing of 41Kb over the whole genome with increased coverage at RefSeq gene at specific disease targeted regions) and the Cytosure ISCA array by OGT in collaboration with the International Standards for Cytogenomic Arrays (ISCA) Consortium (this utilises 60,000 oligonucleotide probes in multiples of eight arrays per slide (8x60 K format) and has high coverage of ISCA defined regions with a median probe spacing of 48 kb.
What are the advantages of an oligo array?
- Multiple patients can be run on a single slide reducing costs and improving consistency.
- Most cost effective platform is 8x60k array (
What are the disadvantages of an oligo array?
- Low detection frequency of mosaicism (<30% of abnormal cells)
- A greater number of aberrant probes are required in order to accurately identify a copy number alteration. This reduces the functional resolution of the array slightly.
- Poor signal to noise ratio due to small probe size, which can result to a significant number of false-positive outliers.
- Some imbalances are too small to be verified by FISH and alternative methods are required (QPCR, custom MLPA etc).
- Cannot detect UPD or LOH.
However, hybrid SNP/oligo arrays (20-60mer) have been developed allowing for the simultaneous, high-resolution detection of copy number and copy-neutral variations, including LOH and UPD (Agilent). - The detection of variants of unclear clinical significance (VOUS; CNV) occurs more frequently with high-resolution oligo arrays – interpretation of these variants can impose a burden on laboratories and clinicians. Several databases are available to help in the interpretation of VOUS (Database of Genomic Variants, dbVar, DECIPHER and ISCA). As this data set grows, the frequency of VOUS results should be reduced.
What are expression arrays?
Expression arrays allow the simultaneous investigation of the expression of thousands of genes by typically comparing two or more highly related cellular or tissue sources that differ in an informative way e.g. expression of genes at different time points in embryonic development, expression of genes in cultured cells after exposure to drugs, expression of genes in tumour cells at different stages of malignancy, expression profiles for disease and normal phenotypes
What are the processes involved in an expression array?
- RNA –> cDNA (reverse transcription)
- cDNA labelled with Cy3, Cy5 or biotin
- Labelled DNA applied to array and hybridised. Intensity of hybridisation is quantitative
4, Compare different populations on the same or different chips - Expression data analysis using clustered algorithms that group genes and samples based on expression profiles
Give an example of an application of an expression array in human disease.
Expression profiling in tumours: historically, tumours were classified using TNM classification - tumour size (T), involvement of lymph nodes (N) and presence of metastases (M). Molecular methods have been used to further characterise tumours, i.e. FISH and PCR to identify characteristic rearrangement, especially in leukaemia.
In other cancers, characteristic chromosomal rearrangements have proved more difficult to identify, although some progress has been made using massively parallel sequencing technologies. E
xpression profiling of tumours using microarrays has been used as an alternative approach, to identify genes that are upregulated or downregulated compared to the normal tissue, and may be used to predict clinical outcome or response to a given treatment e.g. in breast cancer. Microarrays are now widely applied to the study of human cancer: delineating molecular subtypes, disease progression and treatment response.
How can expression arrays be utilised in breast cancer patients?
Two research groups have identified prognostic signatures for breast tumours i.e. factors that provide information on the natural course and outcome of the cancer, unrelated to therapeutic interventions
o 70-gene prognostic signature (Mammaprint) developed on Agilent platform found to be strong predictor for metastasis-free survival
o 76-gene expression signature developed on Affymetrix technology - comparable predictive power for remission to Mammaprint. For examples of study and technology see
Why isn’t expression profiling of breast tumour samples performed in a diagnostic setting?
Despite potential for improving breast cancer management and increased understanding of disease biology, molecular signatures have not yet been used in a diagnostic setting - not yet accurate and reproducible enough to be advantageous over traditional methods. The major challenge remains the identification of potential new molecular targets for the development of new therapeutic strategies.
Expression profiling should be used in conjunction with other methods to analyse genetic and epigenetic changes in DNA, microRNAs, proteins and functional proteins, some of which are detailed below