outline how microarrays are used in the analysis of genomes and in detecting mRNA in studies of gene expression

Genetic Technology – Chapter Overview (Cambridge International AS & A Level Biology 9700)

Why micro‑arrays matter for genetics

DNA is the molecule of heredity; its sequence determines genotype, which together with the environment produces phenotype.

Micro‑arrays provide a rapid, high‑throughput way to compare genotypes (e.g., SNP or copy‑number differences) and phenotypes (gene‑expression patterns) across thousands of loci in a single experiment. This makes them invaluable for:

• Identifying disease‑associated mutations or copy‑number changes.
• Studying population structure and natural selection through genome‑wide SNP surveys.
• Profiling how cells respond to drugs, stress, or developmental cues.

Although the syllabus focuses on DNA‑based arrays, similar solid‑phase platforms exist for proteins (protein microarrays) and for detecting other biomolecules – a useful context for broader scientific literacy.

1. What is a micro‑array?

• A solid‑phase platform (glass slide, silicon chip or nylon membrane) that carries thousands of immobilised DNA probes arranged in a precise grid.
• Each probe is a known sequence that will hybridise only with a complementary target sequence.
• Because many probes are present on one surface, a single experiment can interrogate the whole genome or the whole transcriptome at once.

Key Principle – Complementary Hybridisation

The reversible reaction can be written as

\$\text{Probe} + \text{Labelled target} \rightleftharpoons \text{Probe–target duplex}\$

2. Principles that govern hybridisation

• Melting temperature (T_m) – the temperature at which 50 % of probe–target duplexes dissociate.

  \$T_m \approx 2^\circ\text{C}\times(\text{A+T}) + 4^\circ\text{C}\times(\text{G+C})\$

  Higher T_m → more stable duplex. Hybridisation is normally performed ~5 °C below T_m to promote specific binding.

• Stringency – controlled by temperature and ionic strength. High stringency (high temperature, low salt) reduces cross‑hybridisation but may also lower signal intensity.
• Equilibrium considerations – the ratio of bound to unbound target depends on probe concentration, target concentration and the free‑energy change (ΔG) of duplex formation.

3. Workflow – Step‑by‑Step with “Purpose” boxes

1. Probe design & spotting

   • Probes are either long cDNA fragments (500–2000 bp) or short synthetic oligonucleotides (25–70 mer).
   • Robotic printers or photolithographic methods immobilise probes at defined coordinates.

   Purpose: Provide a known, sequence‑specific “bait” that will capture the complementary target from the sample.

2. Sample preparation

   • Genome analysis – extract high‑quality genomic DNA.
   • Expression analysis – extract total RNA, treat with DNase, assess integrity (gel or Bioanalyzer).
   • Reverse‑transcribe RNA to cDNA (for expression) and incorporate a fluorescent dye (Cy3 – green, Cy5 – red) during labelling.

   Purpose: Produce a labelled nucleic‑acid target that can be visualised after hybridisation.

3. Hybridisation

   • Apply labelled sample(s) to the array; incubate 16–24 h at a temperature ~5 °C below the probe T_m.
   • Stringency washes (varying salt concentration and temperature) remove mismatched duplexes.

   Purpose: Allow complementary probe–target pairs to form stable duplexes while eliminating non‑specific binding.

4. Washing & drying

   Purpose: Eliminate residual unbound label and preserve only specific probe–target duplexes for detection.

5. Scanning

   • A laser scanner excites the fluorophores; emitted light is captured as a digital image.
   • Intensity at each spot reflects the amount of bound target.

   Purpose: Convert the pattern of hybridisation into quantitative numerical data.

6. Data analysis

   • Quality‑control → background subtraction → normalisation → statistical testing → biological interpretation.

   Purpose: Turn raw fluorescence values into reliable conclusions about genotype or gene expression.

4. Types of micro‑arrays

5. Applications in genome analysis

5.1 SNP genotyping

• Each SNP is represented by two allele‑specific probes (e.g., A‑probe and B‑probe).
• Hybridisation of a Cy3‑labelled reference and a Cy5‑labelled test DNA produces a colour ratio that reveals the genotype:

  • AA – strong Cy3, weak Cy5
  • AB – intermediate Cy3/Cy5 (yellow)
  • BB – strong Cy5, weak Cy3

5.2 Comparative Genomic Hybridisation (CGH)

• Test DNA (often tumour) is labelled with Cy5 (red); reference DNA (normal) with Cy3 (green).
• Both are co‑hybridised to a genomic‑DNA array.
• Fluorescence ratio at each spot is expressed as log₂ R where R = (Cy5 intensity)/(Cy3 intensity).

  • log₂ R > 0 → copy‑number gain (amplification).
  • log₂ R < 0 → copy‑number loss (deletion).

• CGH maps sub‑microscopic deletions/duplications that underlie many genetic disorders.

5.3 Copy‑Number Variation (CNV) mapping

High‑density CGH arrays can resolve CNVs as small as a few kilobases, enabling population‑genetics studies of genetic diversity and selection.

5.4 Example – population genetics

Researchers used a 650 000‑SNP array to compare allele frequencies in two *Arabidopsis* populations. The resulting F_ST values identified loci under divergent selection, illustrating how micro‑arrays link genotype to evolutionary processes.

6. Detecting mRNA – Gene‑expression profiling

1. Isolate total RNA from the tissue/cell type of interest.
2. Remove contaminating genomic DNA (DNase) and check integrity (gel or Bioanalyzer).
3. Reverse‑transcribe RNA to cDNA, incorporating fluorescent nucleotides (Cy3 for control, Cy5 for treated).
4. Hybridise the two labelled cDNA samples to the same array (dual‑colour experiment).
5. Wash, scan and obtain two fluorescence images (green = control, red = treated).
6. For each spot calculate the Cy5/Cy3 intensity ratio:

   • Ratio > 1 → up‑regulation in the treated sample.
   • Ratio < 1 → down‑regulation.

Example

A cancer‑cell line (Cy5) is compared with normal tissue (Cy3). After normalisation, the gene BCL2 shows a Cy5/Cy3 ratio of 3.2 → ~3‑fold up‑regulation in the tumour sample.

7. Data handling – From raw image to biological meaning

7.1 Quality‑control checklist

• Inspect the scanned image for dust, scratches, uneven hybridisation.
• Check spot morphology (circular, uniform intensity) with analysis software (e.g., GenePix).
• Include technical replicates (duplicate spots) and biological replicates (independent RNA/DNA samples).
• Assess dye‑bias by plotting Cy3 vs. Cy5 intensities for control spots.
• Perform a “dye‑swap” or “label‑swap” in a subset of arrays to detect systematic dye effects.

7.2 Background subtraction

Subtract the local background fluorescence (median of surrounding pixels) from each spot’s raw intensity.

7.3 Normalisation methods

7.4 Statistical evaluation (AO3)

1. Background subtraction → normalisation → log₂ transformation of ratios.
2. Identify differentially expressed genes:

   • t‑test (two‑sample) for simple pairwise comparisons.
   • ANOVA for experiments with > 2 conditions (e.g., dose‑response).

3. Correct for multiple testing (False Discovery Rate or Bonferroni adjustment).
4. Set significance thresholds – commonly |log₂ ratio| ≥ 1 (≥ 2‑fold change) and adjusted p‑value ≤ 0.05.

7.5 Design considerations for reliable micro‑array experiments (AO3)

• Biological replicates – at least three independent samples per treatment to capture natural variation.
• Technical replicates – duplicate spots on the same array and/or repeat hybridisations.
• Dye‑swap (label‑swap) – reverse the colours (Cy3 ↔ Cy5) in half the replicates to control for dye bias.
• Randomisation & blocking – randomise the order of sample loading and, if possible, block arrays by batch to minimise systematic errors.
• Sample quality control – RNA integrity number (RIN) ≥ 7; DNA purity (A₂₆₀/A₂₈₀ ≈ 1.8).

7.6 Interpreting the results

• Cluster analysis (heat‑maps, hierarchical clustering) groups genes with similar expression patterns.
• Pathway enrichment tools (GO, KEGG) highlight biological processes that are over‑represented among regulated genes.

8. Advantages and limitations (AO3)

9. Ethical, social & economic considerations (syllabus requirement)

• Privacy of genetic information: Whole‑genome or transcriptome data can reveal disease susceptibility; strict confidentiality and informed consent are essential.
• Commercialisation: Companies may patent array designs or disease‑signature panels, potentially limiting access for low‑resource settings.
• Clinical reliability: False‑positive or false‑negative results can lead to inappropriate treatment decisions; validation with independent methods (e.g., qPCR) is recommended.
• Environmental impact: Production of fluorescent dyes and disposable slides generates chemical waste; laboratories should follow hazardous‑waste disposal protocols.
• Equity of access: High equipment costs can widen the gap between well‑funded research centres and schools in developing regions.

10. Key points to remember (AO1)

• Micro‑arrays exploit complementary base‑pairing; fluorescence enables detection of hybridisation events.
• Two main applications: (a) genome analysis (SNP genotyping, CGH, CNV, population genetics) and (b) transcriptome analysis (gene‑expression profiling).
• Critical steps for reliable data: careful labelling, appropriate hybridisation temperature, stringent washes, rigorous quality control, and proper normalisation/statistical analysis.
• Advantages: high‑throughput, simultaneous DNA/RNA analysis, digital data storage. Limitations: need for known sequences, limited dynamic range, possible cross‑hybridisation, ethical concerns about data privacy.
• Experimental design (replicates, dye‑swap, randomisation) is essential for trustworthy conclusions.
• Ethical issues centre on privacy, commercial patents, clinical impact, environmental waste, and equitable access.