AI Laboratory Replication & Heredity

Replication & Heredity

For life to evolve, molecules must copy themselves. Explore how RNA strands can template their own replication, how copying errors drive evolution, and how information begins to be passed from one generation to the next.

Understanding Replication

The RNA World hypothesis proposes that before DNA and proteins, RNA served as both the genetic material and the catalyst. RNA can store information in its base sequence (like DNA) and fold into shapes that catalyse chemical reactions (like protein enzymes). These catalytic RNAs are called ribozymes.

Template Strand A C G U A C G Copy Strand U G C A U Errors → Evolution Parent: A C G U A C G Copy 1: A C G U A C G ✓ faithful Copy 2: A U G U A C G ✗ mutation! Mutations create variation → natural selection acts

Key Concepts

The RNA World

RNA can both store genetic information and catalyse reactions. Before DNA and proteins evolved, RNA may have done both jobs. Evidence includes ribosomes (which are fundamentally RNA machines) and numerous natural ribozymes that cut, join, and replicate RNA strands.

Eigen's Error Threshold

Manfred Eigen showed that there's a maximum genome length that can be maintained given a certain copying accuracy. If errors are too frequent, information is lost across generations — an "error catastrophe." Early replicators had to be short until copying fidelity improved.

Non-Enzymatic Copying

Before ribozyme replicases evolved, RNA may have been copied without enzymes — using mineral surfaces as templates and activated nucleotides that spontaneously base-pair. This process is slow and error-prone but has been demonstrated in the lab.

From Chemistry to Information

The transition from chemical replication (compositional inheritance) to informational replication (template copying) is one of life's greatest mysteries. This "digital takeover" is when true Darwinian evolution became possible.

AI Analysis Tools

Template-Directed Polymerisation

Simulate non-enzymatic RNA copying on mineral surfaces. AI optimises monomer activation chemistry, template sequence, and environmental cycling.

Sequence OptimisationKinetic Model

Error Threshold Analysis

Calculate Eigen's error threshold for the current system. Determine maximum genome length sustainable given the observed copying fidelity.

QuasispeciesError Catastrophe

Ribozyme Evolution

Run evolutionary search for catalytic RNA sequences. Fitness landscape exploration via genetic algorithms with structure prediction (secondary structure folding).

Genetic AlgorithmRNA Folding

Heredity Emergence

Model the transition from statistical (compositional) inheritance to template-based (digital) heredity. Track information content over generations.

Information TheoryPhase Transition
Ready — explore replication mechanisms and the emergence of heredity.