Explain epigenomics at the genome scale

What IS Epigenomics?

WHY genome-wide matters: A liver cell and neuron have identical DNA, but completely different epigenomic landscapes. Only by seeing the full pattern can we understand cell identity, development, and disease.

The Three Pillars of Epigenomic Marks

1. DNA Methylation (5-methylcytosine, 5mC)

   • WHERE: Cytosines in CpG dinucleotides (~28 million sites in human genome)
   • WHAT: Methyl group (CH₃) added to cytosine base
   • EFFECT: Generally silences genes when in promoters

2. Histone Modifications (100+ types)

   • WHERE: On histone protein tails (8 histones per nucleosome)
   • WHAT: Acetylation, methylation, phosphoryl ubiquitination
   • EFFECT: Opens or closes chromatin structure

3. Chromatin Accessibility

   • WHERE: Regions where DNA is unwound from histones
   • WHAT: Physical access for transcription factors
   • EFFECT: Marks active regulatory regions

HOW We Map the Epigenome: Key Technologies

1. Whole-Genome Bisulfite Sequencing (WGBS)

THE PRINCIPLE: Unmethylated cytosines convert to uracil under bisulfite treatment; methylated cytosines don't.

DERIVATION FROM SCRATCH:

Starting point: DNA has two cytosine states

• Unmethylated C
• 5-methylcytosine (5mC)

Step 1: Bisulfite chemistry $\text{Bisulfite} + \text{C} \rightarrow \text{U (uracil)}$ $\text{Bisulfite} + \text{5mC} \rightarrow \text{5mC (protected)}$

Step 2: PCR amplification replaces U with T $\text{U} \xrightarrow{\text{PCR}} \text{T}$

Step 3: Sequencing reads

• Original unmethylated C → reads as T
• Original methylated 5mC → reads as C

Step 4: Calculate methylation level at each CpG $\beta\text{-value} = \frac{\text{Methylated reads (C)}}{\text{Methylated reads (C) + Unmethylated reads (T)}}$

Range: 0 (completely unmethylated) to 1 (fully methylated)

WHY this works: Chemical discrimination creates a sequence signature we can read with standard sequencing.

Solution: $\beta = \frac{80}{80 + 20} = \frac{80}{100} = 0.80$

Interpretation: 80% of cells have this CpG methylated. Likely a partially silenced promoter or mixed cell population.

WHY this step? The ratio directly reflects the proportion of methylated DNA molecules in the sample.

2. ChIP-seq for Histone Marks

THE PRINCIPLE: Antibodies capture specific histone modifications + their bound DNA; sequencing reveals genome-wide locations.

DERIVATION:

Step 1: Cross-link proteins to DNA (formaldehyde) $\text{Histone-DNA complex} \xrightarrow{\text{CH}_2\text{O}} \text{Covalent bonds}$

Step 2: Sonicate chromatin → 200-500 bp fragments

Step 3: Immunoprecipitation with specific antibody $\text{H3K27ac antibody} + \text{All fragments} \rightarrow \text{H3K27ac-bound fragments only}$

Step 4: Reverse cross-links, sequence DNA

Step 5: Map reads to genome → enrichment peaks = modification sites

QUANTIFYING SIGNAL: $\text{Enrichment} = \log_2\left(\frac{\text{ChIP reads}}{\text{Input control reads}}\right)$

Peaks with enrichment >2 (4-fold increase) = true modification sites.

WHY this works: The antibody is molecular filter—only DNA attached to the target histone modification gets captured.

What we learn:

1. This region is an active enhancer (H3K27ac marks active regulatory elements)
2. Gene XYZ likely has high expression in this cell type
3. Disrupting this region would reduce XYZ expression

WHY this inference? H3K27ac is catalyzed by p300/CBP acetyltransferases recruited to active enhancers. The spatial proximity suggests regulatory control.

3. ATAC-seq for Chromatin Accessibility

THE PRINCIPLE: Hyperactive Tn5 transposase inserts sequencing adapters into open chromatin only.

MECHANISM:

Step 1: Tn5 loaded with sequencing adapters $\text{Tn5} + \text{Adapter DNA} \rightarrow \text{Tn5-adapter complex}$

Step 2: Tn5 cuts accessible DNA and inserts adapters ("tagmentation") $\text{Open chromatin} \xrightarrow{\text{Tn5}} \text{Adapter-flanked fragments}$

Step 3: PCR amplify and sequence

Step 4: Map reads → peaks = accessible regions

ENRICHMENT CALCULATION: $\text{Accessibility score} = \frac{\text{Reads in region}}{\text{Total reads}} \times 10^6$ (Reads per million, RPM)

WHY this works: Nucleosome-free regions (like active promoters/enhancers) allow Tn5 access; closed chromatin is physically blocked.

Analysis:

• Peak presence → nucleosome-depleted region (NDR)
• Location (-200 bp) → likely the promoter
• Peak height (RPM = 500) → highly accessible

Prediction: Gene ABC is actively transcribed in this cell type. Transcription factors can bind this promoter.

WHY this matters? 98% of active promoters show ATAC-seq peaks. This is a functional signature.

The Epigenomic Landscape: Integration

The Histone Code: Combinations Define Function

Different histone marks create distinct chromatin states:

DERIVATION OF CHROMATIN STATE:

If we observe marks M₁, M₂, .., Mₙ at a locus, the chromatin state S is: $S = f(M_1, M_2, \ldots, M_n)$

Example: Promoter with H3K4me3 + H3K27ac + accessible chromatin: $S = f(\text{H3K4me3}, \text{H3K27ac}, \text{ATAC}) = \text{Active Promoter}$

Promoter with H3K4me3 + H3K27me3 (both!): $S = f(\text{H3K4me3}, \text{H3K27me3}) = \text{Bivalent/Poised}$

WHY bivalent domains? Stem cells keep developmental genes poised—ready to activate OR silence quickly during differentiation.

Genome-Wide Analysis: The Numbers

Human genome epigenomics at scale:

$\text{Total CpG sites} \approx 28 \times 10^6$ $\text{Regulatory elements (ENCODE)} \approx 4 \times 10^5\text{ to } 10^6$ $\text{Cell-type-specific enhancers} \approx 5 \times 10^4\text{ to } 10^5 \text{ per cell type}$

COVERAGE CALCULATION:

For WGBS at 30× coverage: $\text{Reads needed} = 3 \times 10^9 \text{ bp} \times 30 = 9 \times 10^{10} \text{ reads}$ $\text{Data size} \approx 9 \text{ TB raw data}$

WHY so much data? Every one of 28 million CpGs needs30 reads to accurately measure methylation. This is why epigenomics requires computational infrastructure.

Findings:

1. DNA hypermethylation at tumor suppressor promoters

   • MLH1 methylation: Normal β = 0.05→ Cancer β = 0.85
   • Effect: Silences DNA repair gene → microsatellite instability

2. Histone mark changes

   • Loss of H3K27ac at enhancers of differentiation genes
   • Gain of H3K27me3 at same enhancers
   • Effect: Cells lose differentiated identity

3. Chromatin accessibility

   • New ATAC peaks at oncogene enhancers (MYC, KRAS)
   • Effect: Oncogenes become hyperactive

QUANTIFYING DIFFERENTIAL METHYLATION: $\Delta\beta = \beta_{\text{cancer}} - \beta_{\text{normal}} = 0.85 - 0.05 = 0.80$

Any Δβ > 0.25 is considered significantly hypermethylated.

WHY this pattern? Cancer cells need to silence tumor suppressors AND activate growth genes. Epigenomic reprogramming achieves both without mutating DNA—that's why it's a therapeutic target (epigenetic drugs can reverse it).

WHY it feels right: Most examples show promoter methylation silencing genes (like tumor suppressors).

The reality:

• Methylation in gene bodies actually correlates with active transcription
• Methylation of enhancers can increase OR decrease activity depending on context
• Only promoter CpG island methylation reliably silences

STEEL-MANNING: The idea captures the most common pattern (promoter silencing), which is crucial for X-inactivation, imprinting, and tumor suppression. But biology uses methylation as a context-dependent mark.

THE FIX: Always specify WHERE methylation occurs: "Promoter hypermethylation silences genes; gene body methylation marks active transcription."

WHY it's tempting: Peaks correlate with gene expression 80% of the time.

The trap: Correlation isn't causality. The peak might be:

• A consequence of transcription (active transcription keeps chromatin open)
• An inactive enhancer (accessible but not bound by activators)
• Regulating a distant gene via 3D chromatin loping

THE FIX: Combine ATAC-seq with:

• ChIP-seq for active marks (H3K27ac) → confirms enhancer is active, not just open
• Hi-C or ChIA-PET → maps physical enhancer-promoter contacts
• CRISPR deletion → tests if enhancer is required for gene expression

Epigenomics is like making a MAP of the entire library showing:

• Which sections are locked (methylation on promoters)
• Which books have bookmarks and sticky notes (histone modifications)
• Which aisles have wide-open doors (accessible chromatin)

A brain cell and a liver cell both have the same library card (same DNA), but totally different maps! The brain cell has the "neuron books" section wide open with tons of bookmarks, while those same books are locked away in the liver cell.

Scientists use special chemicals (like bisulfite for DNA methylation) to "tag" all the modifications at once across millions of spots in your genome. It's like using a highlighter that only glows on bookmarks under UV light—then we photograph the entire library from above to see the pattern.

When something goes wrong (like cancer), it's like someone randomly locked important books and unlocked books that teach "how to grow without stopping." By mapping these changes, doctors can figure out which locks need to be opened again with special drugs.

ChIP-seq memory: Capture Histones with Immuno-Precipitation, then sequence

WGBS memory: Whole Genome Bisulfite Sequencing—bisulfite turns Bare Cytosines to Thymines

Connections

• DNA Structure and Replication - epigenetic marks modify bases/histones without changing sequence
• Gene Expression Regulation - epigenomics reveals the regulatory code at genome scale
• Chromatin Structure - histone modifications and accessibility define chromatin states
• Cell Differentiation - epigenomic reprogramming drives cell fate decisions
• Cancer Biology - epigenomic dysregulation is a hallmark of cancer
• CRISPR and Genome Editing - epigenome editing (dCas9-DNMT, dCas9-TET) enables targeted modification
• Stem Cells - bivalent domains keep developmental genes poised
• Evolution and Comparative Genomics - epigenomic variation contributes to phenotypic diversity

#flashcards/biology

What is epigenomics and how does it differ from epigenetics? :: Epigenomics is the genome-wide study of all epigenetic modifications (DNA methylation, histone modifications, chromatin accessibility) across all chromosomes simultaneously. Epigenetics studies single genes; epigenomics examines the complete regulatory landscape across3 billion base pairs to understand cell identity and function.

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Hinglish (regional understanding)