← Back to CoursesGenetics: PhD Level

Neuroanatomy Explorer

Drag to rotate · scroll to zoom · click regions to explore

View
Loading 3D model…

Click a region
to explore it

Memory Deck

Flip each card and rate whether you knew it. Your score is saved.

Term
Definition

Deck complete — score saved.

Match the Pairs

Match each term to its definition. Finish the board to earn your score.

All matched — score saved.

Concept Constellation

Every key idea in this course, mapped as an explorable 3D constellation. Drag to rotate, scroll to zoom, click a node.

Click a node to read its definition.

Genomic Technologies: Sequencing, Mapping, and Functional Assays

Manual: General · Subject: Genetics

Survey the experimental toolbox that powers modern genetics, from short-read sequencing to single-cell and perturbational screens.

Technologies that define contemporary genetics

Sequencing paradigms

Short-read sequencing remains powerful for variant discovery at scale, while long-read platforms improve assembly, phasing, structural variant detection, and haplotype reconstruction. Each technology has characteristic biases in read length, accuracy, throughput, and cost.

Major sequencing strategies

Short-read sequencing

  • High throughput and mature analytics
  • Strong for SNVs and small indels
  • Limited in repetitive and highly rearranged regions

Long-read sequencing

  • Superior for structural variation and assembly
  • Useful for phasing and repeat-rich loci
  • Typically higher per-base cost and distinct error modes

Functional genomics assays

RNA-seq
Measures transcript abundance and isoform usage.
ATAC-seq
Profiles open chromatin and regulatory accessibility.
ChIP-seq
Maps protein-DNA interactions or histone marks.
Hi-C
Measures three-dimensional chromatin contacts.
CRISPR screens
Systematically perturb genes or regulatory elements and measure phenotypic effects.
⚠️

Methodological caution

Every assay has batch effects, capture bias, and an implicit definition of signal. A good geneticist asks what the assay cannot see before interpreting what it can.

From association to mechanism

GWAS identifies statistical associations, but mechanism often requires fine-mapping, epigenomic annotation, saturation mutagenesis, reporter assays, perturb-seq, and causal modeling. The field is shifting from locus discovery toward functional dissection of variant effects in relevant cell states.

Which technique is best suited to identify chromatin accessibility at single-cell resolution?

Why is phasing important in variant interpretation?

Typical modern functional-genomics workflow

  1. 1

    Map variants or candidate loci by sequencing or association.

  2. 2

    Prioritize candidates using annotation and evolutionary constraint.

  3. 3

    Perturb candidates using CRISPR, base editing, or epigenome editing.

  4. 4

    Read out the molecular or phenotypic response in relevant cell types.

  5. 5

    Validate the strongest causal hypothesis with orthogonal assays.

What is a major advantage of CRISPR screening over one-variant-at-a-time testing?