Molecular Biology Flashcards

Week 1: Introduction to Molecular Biology and Bioinformatics

• Bioinformatics:

  • Interdisciplinary science: biology, computer science, and mathematics.

  • Analyzes and interprets biological data, especially sequence data (DNA, RNA, proteins).

  • Extracts insights from large-scale datasets from sequencing technologies.

• Biological Sequence Databases:

  • INSDC (International Nucleotide Sequence Database Collaboration):

    • DDBJ (DNA Data Bank of Japan).

    • GenBank (NCBI, USA).

    • EMBL-EBI (Europe).

  • Synchronized daily and freely accessible.

• Major Sequence Browsers:

  • NCBI Genome Database: Broad access to DNA/protein sequences.

  • Ensembl Genome Browser: Gene annotations, comparative genomics tools.

  • UCSC Genome Browser: Track-based visualization and analysis.

• Sequence Formats:

  • FASTA: > followed by the sequence.

  • GenBank: Includes annotations; "LOCUS," "ORIGIN," and "//" syntax.

  • ENSEMBL: Uses "ID," "SQ," and annotation lines.

• Navigating NCBI, ENSEMBL, and UCSC Genome Browser:

  • NCBI: BLAST, PubMed, GenBank, protein/gene databases.

  • ENSEMBL: Searchable by gene symbol, chromosome coordinates, phenotypic data.

  • UCSC: Browser tracks with genomic annotations, comparative genomics, sequence searches.

• Homologues, Orthologues, Paralogues:

  • Homologues: Genes sharing common ancestry.

    • Orthologues: Different species, similar function.

    • Paralogues: Duplicated within the same genome, may evolve new functions.

  • Examples:

    • Human globin gene cluster: multiple paralogues (HBB, HBD).

    • α- and β-globin genes (humans, frogs): orthologous relationships.

• Sequence Alignments:

  • Compare sequences to identify similarities/differences.

    • Mismatches: different nucleotides/amino acids.

    • Gaps: insertions/deletions.

  • Protein alignments: consider chemical similarities.

    • Conservative substitutions: similar side-chain properties (e.g., Leu → Ile).

    • Radical substitutions: different properties (e.g., Gly → Glu).

• BLAST (Basic Local Alignment Search Tool):

  • Compares a query sequence to a database.

  • Types: blastn, blastp, blastx, etc.

  • Helps determine:

    • Organism origin of a sequence.

    • Gene identity and mutations.

    • Potential disease associations.

Week 2: Advanced PCR Techniques & Bioinformatics Workshop 2 (BW2)

• Polymerase Chain Reaction (PCR):

  • Standard PCR amplifies a specific DNA fragment.

    • Denaturation: Heating to separate strands.

    • Annealing: Primers bind to target DNA.

    • Extension: DNA polymerase synthesizes new strands.

  • Advanced PCR techniques:

    • RT-PCR (Reverse Transcription PCR): RNA → cDNA before amplification.

    • qPCR (Quantitative PCR): Real-time measurement using fluorescent dyes/probes; quantifies gene expression.

    • Multiplex PCR: Multiple primer sets to amplify different targets.

    • Nested PCR: Two rounds of PCR to improve specificity.

    • Touchdown PCR: Gradually lowering annealing temperature to improve specificity.

• Primer Design:

  • Length: 18–25 nucleotides; longer = increased specificity.

  • Melting temperature (Tm): Similar for both primers (55–65°C).

  • GC content: 40–60% is optimal.

  • Avoid:

    • Hairpin loops.

    • Primer dimers.

    • Complementarity at 3’ ends (mis-priming).

• Reagents Impact on PCR:

  • dNTPs: Building blocks of DNA; optimal concentration is crucial.

  • Mg^{2+} ions: Cofactor for DNA polymerase; too little = low yield, too much = non-specific products.

  • DNA polymerase: Taq is standard, Pfu offers higher accuracy.

  • Template quality: Impurities inhibit PCR.

• Bioinformatics Tools for PCR Assay Development (BW2):

  • NCBI Primer-BLAST: Designs primers/checks specificity.

  • BLASTn: Ensures target region is unique.

  • OligoCalc: Calculates Tm, GC%, and primer self-complementarity.

• Experimental Contexts for Different PCR Methods:

  • RT-qPCR:

    • Gene expression studies.

    • Diagnostic testing (e.g., viral load quantification).

  • Multiplex PCR:

    • Pathogen panels.

    • Forensic identification.

  • Touchdown PCR:

    • Difficult templates.

    • Low-abundance targets.

Week 3: Measuring Gene Expression & Introduction to Practicals

• Gene Expression Measurement:

  • Gene expression: Genetic instructions used to synthesize RNA (and usually protein).

  • Allows comparison of gene activity across tissues, conditions, or time points.

  • Methods:

    • RT-qPCR:

      • RNA extraction → reverse transcription (mRNA → cDNA).

      • Real-time quantification: SYBR Green dye or TaqMan probes.

      • Results: Amplification curves; normalized to housekeeping genes (GAPDH, ACTB).

      • Outputs: Ct (threshold cycle) values; lower Ct = higher gene expression.

    • Microarrays:

      • Thousands of DNA probes are immobilized on a chip.

      • Fluorescently labeled cDNA is hybridized.

      • Relative fluorescence intensity reflects expression level.

      • Requires known gene sequences.

    • RNA-Seq (High-throughput sequencing):

      • Whole transcriptome coverage: non-coding RNAs and splice variants.

      • Raw reads undergo quality control (FastQC), alignment (HISAT2, STAR), quantification (FeatureCounts, HTSeq), and differential expression analysis (DESeq2, edgeR).

      • Outputs: Counts per gene, FPKM, or TPM values.

• Biological Relevance of Gene Expression Data:

  • Comparing expression across conditions:

    • Identify biomarkers or therapeutic targets.

    • Reveal upregulated pathways in diseases (e.g., cancer).

    • Study regulatory mechanisms (transcription factors, epigenetic marks).

  • Example: BRCA1 downregulation in tumor tissue suggests compromised role in genomic stability.

• Introduction to Practical Skills:

  • Learn sterile technique, pipette calibration, reagent handling.

  • Understand lab notebook structure.

  • Technical replicates (same sample, repeated measurement) vs. biological replicates (different samples, same treatment).

• Bioinformatics Link: Using BLAST

  • BLASTn: Nucleotide query vs. nucleotide databases.

  • BLASTp: Protein vs. protein database.

  • blastx: Translates a nucleotide query into protein before comparison.

  • Use cases:

    • Identify unknown gene sequences.

    • Confirm cloning insert identity.

    • Compare homologous genes across species.

Week 4: Cloning Genes I

• Gene Cloning:

  • Creating multiple, identical copies of a particular gene or DNA fragment.

  • Cornerstone of molecular biology and biotechnology.

  • Why clone genes?

    • To study gene function and expression.

    • To produce recombinant proteins (e.g., insulin, growth hormone).

    • To modify genomes (e.g., in gene therapy or genetic engineering).

• Restriction Enzymes:

  • Recognize specific short DNA sequences (usually palindromes) and cut DNA at/near these sites.

  • Types of ends:

    • Sticky ends: Staggered cuts with overhangs; better for directional cloning. Example: EcoRI cuts between G and A in GAATTC.

    • Blunt ends: Straight cuts with no overhangs; less efficient but more flexible.

  • Multiple Cloning Site (MCS):

    • A short sequence in plasmids containing several restriction sites.

    • Offers versatility in inserting DNA fragments using different enzymes.

• Cloning Vectors:

  • A DNA molecule used as a vehicle to transfer foreign genetic material into a host cell.

  • Common vector features:

    • Origin of replication (Ori): Allows replication inside the host.

    • Selectable marker: Antibiotic resistance gene (e.g., amp^R).

    • Reporter gene: E.g., lacZ for blue/white screening.

    • MCS region: For insertion of the target gene.

  • Plasmid vectors (e.g., pUC19, pGEM-T) are most commonly used in basic cloning.

  • Other specialized vectors:

    • Expression vectors: Enable protein production.

    • Shuttle vectors: Replicate in multiple species (e.g., E. coli and yeast).

    • Viral vectors: Used in gene therapy or transfection of animal cells.

• Inserting DNA Fragments into Vectors:

  • Restriction digestion:

    • Vector and insert DNA are digested with the same or compatible enzymes to produce matching ends.

  • Ligation:

    • DNA ligase joins the insert and vector by forming phosphodiester bonds.

    • Requires ATP or NAD^+ as a cofactor.

  • T/A cloning (alternative method):

    • PCR products made with Taq polymerase often have single “A” overhangs.

    • Inserted into “T” overhang vectors without restriction digestion.

• Transformation and Selection:

  • Transformation: Introducing recombinant DNA into bacteria (commonly E. coli).

    • Heat shock method: Cells briefly exposed to 42°C to encourage DNA uptake.

    • Electroporation: Electric field opens pores in bacterial membrane.

  • Selection strategies:

    • Plating on antibiotic-containing agar ensures only transformed cells survive.

    • Blue-white screening (lacZ system):

      • Insert disrupts lacZ → colonies turn white (successful clone).

      • No insert → functional lacZ → blue colonies with X-gal.

• Controls in Gene Cloning Experiments:

  • Negative control: Plasmid-only (no insert) to assess background ligation.

  • Positive control: A known successful insert to validate the system.

  • No-enzyme control: Detects contamination or background resistance.

Week 5: Cloning Genes II

• Ligation and Transformation Process:

  • Ligation:

    • Key enzyme: T4 DNA ligase catalyzes phosphodiester bonds.

    • Sticky-end ligation is more efficient than blunt-end.

    • Ligation reaction setup:

      • Vector-to-insert molar ratio: ~1:3.

      • Buffer with ATP is essential.

      • Incubated at 16°C overnight or room temp for 10–15 minutes (quick ligation).

    • Controls:

      • No-insert (vector only): Detects self-ligation background.

      • Insert-only: Should show no growth.

      • Uncut vector: Should yield only blue colonies (non-recombinant).

  • Transformation:

    • Uptake of recombinant DNA by competent E. coli cells.

    • Chemical transformation (heat shock):

      • Chill cells + plasmid DNA on ice.

      • Heat shock at 42°C for 30–60 seconds.

      • Cells recover in SOC or LB broth.

    • Electroporation:

      • Delivers electrical pulses (~1.8 kV).

      • Must use salt-free buffer.

    • Selection methods:

      • Antibiotic selection: E.g., ampicillin resistance (bla gene).

      • Blue-white screening:

        • Vector contains lacZα fragment; insertion disrupts it.

        • X-gal substrate turns blue in presence of active β-galactosidase.

        • White colonies = successful insert integration.

        • Blue colonies = no insert (intact lacZ).

• Screening Colonies to Verify Correct Cloning:

  • Colony PCR:

    • Pick colonies, use a portion directly as PCR template.

    • Primers flank MCS region.

  • Restriction digest of miniprep DNA:

    • Digest plasmid from cultured colony using the same enzymes used during cloning.

    • Run on agarose gel.

  • Sequencing confirmation:

    • Sequence with vector-specific primers (e.g., T7, SP6, M13).

    • Essential to confirm: correct sequence, proper orientation, no PCR-induced mutations.

• Troubleshooting Cloning Experiments:

  • No colonies:

    • Did the ligase buffer or competent cells expire?

    • Incorrect antibiotic concentration?

    • Low transformation efficiency?

  • Lots of blue colonies:

    • Likely vector self-ligation or uncut vector contamination.

    • Use dephosphorylation (alkaline phosphatase) to prevent re-ligation.

  • All white colonies, but no insert detected:

    • Primers may have amplified a different or truncated fragment.

    • Confirm primer specificity and gel-purify PCR product before cloning.

Week 6: The Human Genome, Sanger Sequencing & Microarrays

• Human Genome Structure and Composition:

  • ~3 billion base pairs across 23 pairs of chromosomes.

  • ~20,000–25,000 protein-coding genes (~1.5% of the genome).

  • Remainder includes: introns, intergenic regions, regulatory sequences, repeats (satellite DNA, transposons, retroelements).

  • Functional non-coding DNA: regulates gene expression, includes non-coding RNAs (miRNA, lncRNA, etc.), and supports structural/chromosomal organization.

• Impact of the Human Genome Project (HGP):

  • Timeline: 1990–2003.

  • Aims: Sequence the entire human genome, identify all human genes, improve technologies, and explore genetic variation.

  • Key Outcomes: Kickstarted precision medicine, databases (NCBI GenBank, Ensembl, UCSC), and revealed complexity of gene regulation.

• Sanger Sequencing:

  • Based on selective incorporation of chain-terminating dideoxynucleotides (ddNTPs) during DNA synthesis.

  • Each ddNTP is fluorescently labeled.

  • Generates DNA fragments of varying lengths.

  • Fragments separated by capillary electrophoresis.

  • Reaction Components: Template DNA, primer, DNA polymerase, dNTPs + ddNTPs (labeled).

  • Advantages: High accuracy (~99.99%), excellent for small-scale projects.

  • Limitations: Low throughput, Max read length ~800–1000 bp, inefficient for large genomes.

• Microarrays for Gene Expression Profiling:

  • A chip contains thousands of DNA probes attached in a grid.

  • Fluorescently labeled cDNA is hybridized to the chip.

  • Signal intensity corresponds to gene expression level.

  • Applications: Global gene expression analysis, comparing expression profiles, discovery of co-regulated genes.

  • Strengths: Simultaneous profiling of thousands of genes, established bioinformatics pipelines.

  • Weaknesses: Limited to known genes, cross-hybridization can reduce accuracy, replaced by RNA-Seq in many applications.

• Linking Sequencing and Expression Analysis:

  • Sanger sequencing confirms gene identity and detects mutations.

  • Microarrays profile gene expression changes.

Week 7: Advanced DNA Sequencing Techniques

• Next Generation Sequencing (NGS):

  • High-throughput sequencing technologies that allow millions to billions of DNA fragments to be sequenced simultaneously.

  • NGS Workflow Overview:

    • Library Preparation: Genomic DNA is fragmented, adapters are ligated, and library fragments may be barcoded.

    • Amplification: Bridge PCR (Illumina) or Emulsion PCR (Ion Torrent).

    • Sequencing by Synthesis: Each base is read as it's added to the growing strand using Fluorescence (Illumina), pH (Ion Torrent), or real-time detection (Nanopore/PacBio).

    • Image/Data Capture & Base Calling: Signals are converted into raw sequences (FASTQ files).

    • Bioinformatics Processing: Sequence alignment, variant calling, and downstream analysis.

• Key NGS Platforms:

  • Illumina: High accuracy, short reads (100–300 bp), industry standard. Short reads may miss structural variants

  • Ion Torrent: Fast turnaround, semiconductor-based, 200-400 bp. Prone to indel errors (homopolymer runs)

  • PacBio (HiFi): Long reads (10–25 kb), ideal for structural insights. Lower throughput; expensive

  • Oxford Nanopore: Ultra-long reads (Up to 2 Mb+), portable, real-time. Higher error rates; improving rapidly

    • PacBio and Nanopore are used for de novo genome assembly, isoform resolution, and detecting large insertions/deletions.

• Applications and Advantages of NGS over traditional methods:

  • Whole genome sequencing (WGS): Identify rare mutations and structural changes.

  • Whole exome sequencing (WES): Focus on protein-coding regions (~1% of genome).

  • RNA-Seq: Quantifies gene expression and splicing patterns.

  • ChIP-Seq: Maps transcription factor binding and epigenetic marks.

  • Targeted sequencing: Panels for cancer mutations, inherited disease genes.

  • Advantages over Sanger: higher throughput, cost-efficiency, and sensitivity.

• Data Quality and Bioinformatics:

  • Phred quality scores (Q-scores): Indicate confidence in base calls (e.g., Q30 = 99.9% accuracy).

  • FASTQ files store both sequence and quality.

  • Adapter trimming and quality filtering are critical first steps.

  • Downstream tools: Alignment, variant calling, visualization, and functional annotation.

• Emerging Trends in Sequencing Technology:

  • Single-cell sequencing: Profiles gene expression at individual cell level.

  • Spatial transcriptomics: Adds spatial context to gene expression.

  • Epigenetic sequencing: Methylation and chromatin accessibility.

  • Clinical NGS: Routine in cancer diagnostics, prenatal screening, and pharmacogenomics.

Week 9: The Cell Cycle, DNA Replication & Cancer

• Eukaryotic Cell Cycle:

  • Interphase:

    • G₁ phase: Cell grows and prepares for DNA replication.

    • S phase: DNA is replicated.

    • G₂ phase: Checks for errors and prepares for mitosis.

  • M phase (Mitosis): Prophase, metaphase, anaphase, telophase, and cytokinesis; results in two identical daughter cells.

  • G₀ phase: Resting state; non-dividing cells may remain here permanently.

• Molecular Regulators of the Cell Cycle:

  • Cyclins: Regulatory proteins whose levels fluctuate cyclically.

  • Cyclin-Dependent Kinases (CDKs): Enzymes activated by binding to cyclins; cyclin-CDK complexes drive the cell through each phase.

    • Example: Cyclin D/CDK4/6 in G₁; Cyclin E/CDK2 in G₁/S; Cyclin B/CDK1 in G₂/M.

  • CDK inhibitors (CKIs): Halt the cell cycle in response to DNA damage or stress. E.g., p21, p27, p16.

  • Checkpoints: G₁/S, G₂/M, and Spindle checkpoints.

• DNA Replication and Telomere Maintenance:

  • DNA replication: Begins at origins of replication; Helicase unwinds the double helix; DNA polymerase synthesizes new strands (leading and lagging).

  • Telomeres: Repetitive sequences at chromosome ends (e.g., TTAGGG in humans); Shorten with every division unless maintained by telomerase.

• Disruptions in Regulation Linked to Cancer:

  • Proto-oncogenes: Normal genes that promote growth; When mutated result in oncogenes (Ras, Myc, HER2).

  • Tumor suppressor genes: Regulate checkpoints, repair DNA, or initiate apoptosis; Loss-of-function mutations remove cell cycle brakes (p53, RB, BRCA1/2).

  • Mutations in DNA repair machinery: Lead to accumulated damage and mutation burden; Mismatch repair defects result in microsatellite instability.

• Clinical Implications and Therapeutic Targets:

  • Many cancer drugs target the cell cycle: CDK inhibitors and Microtubule inhibitors.

  • Checkpoint loss can contribute to resistance or aggressive phenotypes.

Week 10: DNA Repair Mechanisms

• Sources and Types of DNA Damage:

  • Endogenous: Reactive oxygen species (ROS), replication errors, spontaneous base deamination.

  • Exogenous: UV radiation (thymine dimers), ionizing radiation (SSBs/DSBs), Chemicals and toxins.

• DNA Repair Pathways:

  • Direct Reversal: Photolyases in bacteria repair UV-induced dimers using light; MGMT reverses alkylation damage directly.

  • Base Excision Repair (BER): Repairs small, non-distorting lesions; Key enzymes: DNA glycosylases, AP endonuclease, DNA polymerase β, and ligase.

  • Nucleotide Excision Repair (NER): Removes bulky distortions like thymine dimers; Involves DNA helicase, endonucleases, and gap-filling synthesis.

  • Mismatch Repair (MMR): Fixes replication errors; Key proteins: MSH2, MLH1, and their complexes.

  • Double-Strand Break Repair:

    • Non-Homologous End Joining (NHEJ): Quick but error-prone; DNA ends are trimmed and ligated.

    • Homologous Recombination (HR): High-fidelity; uses a sister chromatid as template; Key players: BRCA1, BRCA2, RAD51.

• Clinical Syndromes Caused by Defective Repair:

  • Xeroderma Pigmentosum (XP): NER deficiency -> extreme sensitivity to sunlight, high risk of skin cancer.

  • Lynch Syndrome (HNPCC): MMR gene mutations -> microsatellite instability and colorectal/endometrial cancers.

  • Ataxia Telangiectasia: Defect in ATM kinase (DSB sensing) -> immunodeficiency, cerebellar ataxia, radiation sensitivity.

  • BRCA1/2 mutations: Impair HR repair -> increased risk of breast, ovarian, and prostate cancers.

• Connecting DNA Repair to Cancer Treatment Strategies:

  • Cancer therapies exploit defective repair mechanisms via synthetic lethality.

  • PARP inhibitors: Inhibit base excision repair; Tumor cells with BRCA mutations rely heavily on BER -> Inhibiting BER causes collapse of replication forks.

  • Chemotherapies and radiation: Cause DNA breaks or crosslinks; More toxic to rapidly dividing cells but also harm normal proliferative tissues.

Week 11: Gene Editing Using CRISPR

• Origins and Natural Role of CRISPR-Cas Systems:

  • Discovered as a bacterial immune system.

  • Bacteria capture viral DNA snippets and integrate them into their own genome as spacer sequences.

  • If reinfected, bacteria transcribe these spacers into crRNAs, which guide the Cas9 protein to recognize and cleave matching viral DNA.

  • This natural system was engineered into a gene-editing tool.

• How CRISPR-Cas9 Performs Genome Editing:

  • Essential components: Cas9 nuclease and Single-guide RNA (sgRNA).

  • Mechanism: sgRNA binds a ~20-nucleotide DNA sequence adjacent to a PAM; Cas9 induces a double-stranded break (DSB). Cell then repairs via Non-Homologous End Joining (NHEJ) or Homology-Directed Repair (HDR).

• Comparison of CRISPR to Older Editing Tools (ZFNs and TALENs):

  • CRISPR’s RNA-guided targeting makes it more flexible and scalable.

• Advanced CRISPR Variants:

  • Base Editing: Uses deactivated Cas9 (dCas9) fused to a deaminase enzyme. Converts one base to another without cutting the DNA.

  • Prime Editing: Combines Cas9 nickase and reverse transcriptase. Enables “search-and-replace” editing.

  • CRISPR Interference/Activation (CRISPRi/a): dCas9 fused to repressors or activators can modulate gene expression without altering sequence.

• Applications in Research and Medicine:

  • Basic science: Create knockouts to study gene function; Generate disease models.

  • Clinical trials and therapies (sickle cell disease, cancer immunotherapy, retinal disease, HIV).

  • Gene drives (mosquito control).

• Ethical and Safety Considerations:

  • Off-target effects: Cas9 may cleave similar sequences, potentially introducing unintended mutations.

  • Germline editing: Heritable changes raise ethical concerns.

Week 12: Genetic Epidemiology & GWAS

• Purpose and Foundation of Genetic Epidemiology:

  • Studies how genetic factors contribute to disease prevalence and trait variation in populations.

  • Integrates population genetics, disease risk modeling, and inheritance patterns.

  • Core concepts: Penetrance, Expressivity, Heritability (h^2).

• Study Designs: Linkage, Association, Candidate Gene vs. GWAS

  • Linkage Analysis: Families/pedigree -> Mendelian traits -> Broad (~Mb scale) -> Few markers.

  • Association Studies (incl. GWAS): Unrelated individuals (case-control) -> Complex/multifactorial traits -> Fine (~kb scale) -> High-density genome-wide SNP arrays.

  • Candidate gene approach: Focus on specific gene(s) suspected to influence a trait.

  • GWAS: Hypothesis-free scan of the genome.

• GWAS Methodology:

  • Sample selection (cases vs. controls), Genotyping (SNP microarrays), Statistical testing (logistic regression or chi-squared tests), and Multiple testing correction (Bonferroni correction or False Discovery Rate (FDR); p < 5 × 10⁻⁸).

• Interpreting GWAS Results and Visualizations:

  • Manhattan plot: X-axis shows chromosomal position; Y-axis shows –log₁₀(p-value).

  • QQ plot: Compares expected vs. observed p-values.

• Population Stratification and Bias:

  • Stratification = allele frequency differences due to ancestry, not trait. Corrected using principal component analysis (PCA)

• Post-GWAS Interpretation and Tools:

  • Fine mapping, eQTL analysis, and Functional annotation.

• Clinical and Research Applications of GWAS:

  • Identification of risk alleles, Development of polygenic risk scores (PRS), and Discovery of therapeutic targets.

Week 13: Revision & Exam Strategy

• Unit’s Learning Outcomes Holistically:

  • Characterize and manipulate DNA using PCR, cloning, sequencing, and CRISPR.

  • Apply bioinformatics tools to analyze sequences.

  • Integrate wet lab and dry lab skills.

  • Understand molecular genetics in a disease context.

  • Use data analytics to extract insights from sequence datasets.

• Core Experimental Techniques & Their Logic (PCR, Cloning, Sanger, NGS, CRISPR). Principle & Purpose -> Interpreting Results

• Master Bioinformatics Workflows & Databases (BLAST, Ensembl/NCBI/UCSC, GeneCards & OMIM, etc.)

• Revise Data Interpretation from Lab-Based Workshops (qPCR plot, Microarray heatmap, GWAS Manhattan plot, CRISPR edit confirmation, etc).

• Exam strategy tips:

  • Expect a mix of MCQs and short answer questions.

  • Scenario-style questions may require: diagnosing experimental errors, designing PCR primers, choosing best sequencing approach, interpreting output plots or sequences.

  • Study hacks: concept maps, flashcards, practice explaining terms aloud.