DNA Civ v10: Biological Edition RESEARCH READY

1. System Overview

1.1 Research Applications

DNA Civ v10 provides a platform for investigating:

• Population genetics: Allele frequency dynamics, genetic drift, selective sweeps
• Host-pathogen coevolution: Arms race dynamics, virulence evolution
• Immunology: Innate vs. adaptive immunity, herd immunity thresholds
• Horizontal gene transfer: Viral integration, endogenous retrovirus formation
• Social evolution: Deme formation, kin selection, cooperation
• Predator-prey dynamics: Trophic interactions, niche partitioning
• Speciation: Reproductive isolation, hybrid zones

1.2 Version History

2. Terminology Mapping v10

Version 10 replaces all game-style terminology with standard biological vocabulary suitable for peer-reviewed publication.

2.1 Core Gene Names

2.2 Latent Gene Names

2.3 Social & Environmental Terms

3. Genetic Architecture

3.1 Genome Structure

Each organism carries a 64-bit binary genome organized into 16 loci of 4 bits each (values 0-15, normalized to 0.0-1.0).

Bit Position:  0         16        32        48        64
               |----+----|----+----|----+----|----+----|
               [ ACTIVE GENES  ]   [   LATENT GENES    ]
               Loci 0-7 (express)  Loci 8-15 (require unlock)

3.2 Active Genes (Loci 0-7)

3.3 Latent Genes (Loci 8-15)

Latent genes require activation via mutagen exposure. Once unlocked, they are heritable with 70% transmission probability.

3.4 Genetic Operators

Crossover (Meiotic Recombination)

CONFIG.CROSSOVER_POINTS = 2

Parent A: 1111000011110000111100001111000011110000111100001111000011110000
Parent B: 0000111100001111000011110000111100001111000011110000111100001111
                    ↑              ↑
            Crossover points (random)
                    
Child:    1111000011001111000011110000111100001111000011110000111100001111

Point Mutation

MUTATION_RATE = 0.02 (2% per bit)
Expected mutations per offspring: 64 × 0.02 = 1.28

4. Environmental Systems

4.1 Resource Dynamics

4.2 Seasonal Modulation

TICKS_PER_SEASON = 80 → Full year = 320 ticks

4.3 Environmental Zones v10

5. Microorganism Ecology

5.1 Microbe Types

5.2 Microbe Genome (v7+)

Microbes have their own heritable traits that evolve over generations:

5.3 Horizontal Gene Transfer

When viruses infect, there is a 15% chance of HGT—viral genetic payload integrates into host genome:

if (random() < 0.15) {
    viralInsert = {
        sequence: micro.genome.payload,  // 4 bits
        insertPoint: targetGene.bits[0],
        sourceStrainId: micro.strainId
    };
    entity.viralDNA.push(viralInsert);
    entity.dna = integrateViralDNA(entity.dna, viralInsert);
}

Integrated viral DNA is heritable (80% transmission) and becomes a permanent part of the lineage—analogous to endogenous retroviruses in vertebrate genomes.

6. Immune System Modeling

6.1 Innate Immunity (Hardiness Gene)

innate_resistance = Hardiness × 0.5
// Maximum 50% resistance from genetics alone

6.2 Adaptive Immunity (Immune Memory)

Organisms build strain-specific resistance from surviving infections:

entity.immuneMemory = Map<strainId, {
    resistance: 0.0-0.9,    // Learned resistance
    encounters: count,       // Times exposed
    lastEncounter: tick,     // For decay calculation
    strainType: 'virus'|'symbiont'|'mutagen'
}>

6.3 Combined Resistance

total_resistance = min(0.95, innate_resistance + adaptive_resistance)
// 95% cap prevents complete immunity

6.4 Maternal Antibody Transfer

Offspring inherit 30% of mother's resistance for strains where maternal resistance exceeds 0.3:

for each [strainId, memory] in parent.immuneMemory:
    if memory.resistance > 0.3:
        child.immuneMemory.set(strainId, {
            resistance: memory.resistance × 0.3,
            inherited: true
        })

7. Behavioral & Social Systems

7.1 Goal-Directed Behavior

7.2 Deme Formation v10 TERM

Requirements:

• Sociality > 0.4
• ≥ DEME_MIN_SIZE (3) organisms within DEME_DISTANCE (18)
• All unaffiliated

Demes are named systematically: Deme-α, Deme-β, Deme-γ, etc.

7.3 Predator-Prey System

// Trigger: Aggression > 0.4, random check passes
hunt_chance = Aggression × 0.02

// Target selection: Nearest non-deme member
target = nearest(entities.filter(e => e.deme !== predator.deme))

// Attack roll
attack_power = Aggression × phenotype_bonuses
defense = target.Hardiness + target.Motility × 0.5
success = random() < (attack_power / (attack_power + defense))

// Energy transfer on successful kill
if success:
    damage = 10 + attack_power × 15
    energy_gained = damage × 0.4

7.4 Speciation

hamming_distance = count_different_bits(dna1, dna2)
can_mate = hamming_distance <= SPECIATION_THRESHOLD (20)

// Exception: Hybridizer phenotype bypasses threshold

8. Epistasis & Phenotype Expression

Gene-gene interactions produce emergent phenotypes when trait thresholds are met:

9. Closed System Mode v10

Closed System Mode disables primordial emergence, creating a controlled experimental environment where populations can go extinct.

9.1 Experimental Applications

• Founder effect studies: Start with specific genotypes, observe drift
• Competition experiments: Two defined lineages competing
• Lineage tracking: Follow descendants of specific individuals
• Extinction dynamics: Identify conditions causing population collapse

9.2 Workflow for Lab-Created Populations

10. Batch Experiment Runner

10.1 Configuration Options

10.2 Testable Variables

• MUTATION_RATE (0.005 - 0.1)
• ENERGY_DECAY (0.1 - 0.5)
• SPECIATION_THRESHOLD (10 - 40)
• INITIAL_POPULATION (3 - 50)
• RESOURCE_CLUSTERS (3 - 12)
• MICROBE_SPAWN_CHANCE (0.001 - 0.01)

10.3 Headless Execution

tickHeadless() runs full simulation logic with zero rendering—10-100× faster than visual mode. Browser remains responsive via chunked execution yielding every 50ms.

11. Data Formats & Export

11.1 Export Buttons

11.2 JSON Export Structure

{
  "meta": {
    "id": "run-m4k7x2-a3b9c",
    "seed": "experiment-42",
    "configHash": "3f8a2b1c",
    "version": "10.0.0"
  },
  "config": { ... },
  "summary": {
    "finalPopulation": 45,
    "totalBorn": 523,
    "demes": 3
  },
  "timeSeries": [ ... ],
  "genePoolHistory": [ ... ],
  "events": [ ... ],
  "finalCensus": [ ... ],
  "microbes": [ ... ]
}

11.3 Batch Summary CSV

variable_value,runs,avg_final_pop,std_final_pop,avg_max_gen,extinction_rate
0.01,25,45.30,12.40,8.50,0.04
0.02,25,42.10,15.60,9.20,0.08
0.05,25,38.40,18.20,11.30,0.12

12. Experimental Protocols

12.1 Protocol: Mutation Rate Effect

VARIABLE: MUTATION_RATE
VALUES: 0.005, 0.01, 0.02, 0.04, 0.08
RUNS_PER_VALUE: 30
TICKS_PER_RUN: 5000
MEASUREMENTS:
  - Final genetic diversity
  - Extinction rate
  - Average max generation
ANALYSIS:
  - One-way ANOVA for diversity
  - Chi-square for extinction rate

12.2 Protocol: Founder Effect (Closed System)

VARIABLE: INITIAL_POPULATION
VALUES: 3, 5, 10, 25
SETUP: CLOSED_SYSTEM = true
RUNS_PER_VALUE: 50
TICKS_PER_RUN: 4000
MEASUREMENTS:
  - Time to first extinction
  - Diversity at tick 2000 vs 4000
  - Trait variance reduction
ANALYSIS:
  - Survival analysis
  - ANOVA for diversity

12.3 Protocol: Speciation Threshold

VARIABLE: SPECIATION_THRESHOLD
VALUES: 10, 15, 20, 25, 30, 40
RUNS_PER_VALUE: 25
TICKS_PER_RUN: 6000
MEASUREMENTS:
  - Reproductively isolated clusters
  - Within-cluster diversity
  - Hybridizer phenotype frequency
ANALYSIS:
  - Cluster analysis on final DNA
  - ANOVA for species count

13. Glossary

Adaptive immunity

Learned resistance from surviving infection; strain-specific

Chemosense

Latent gene enabling enhanced resource detection (analogous to chemotaxis)

Closed System

Experimental mode disabling primordial emergence; population can go extinct

Crypsis

Latent gene providing camouflage/detection evasion

Deme

Local breeding population; standard term in population genetics (Wright, 1943)

Epistasis

Gene-gene interaction producing emergent phenotypes

Fecundity

Reproductive capacity; affects offspring probability

Hardiness

Innate pathogen resistance; contrasts with adaptive immunity

HGT

Horizontal Gene Transfer; genetic material moving between organisms outside reproduction

Hybridizer

Phenotype enabling mating across speciation barrier

K-Strategist

Phenotype emphasizing longevity and exploration over reproduction (r/K selection theory)

Motility

Movement velocity trait

Plasticity

Latent gene enabling phenotypic drift over lifespan

Senescence⁻

Latent gene reducing aging effects (negative senescence)

Sociality

Trait governing deme affinity and group joining behavior

Toxicosis

Latent gene enabling toxic defense against pathogens

14. Configuration Reference

CONFIG = {
    // World
    WORLD_WIDTH: 280,
    WORLD_HEIGHT: 200,
    
    // Population
    INITIAL_POPULATION: 25,
    MAX_POPULATION: 150,
    
    // Time
    TICK_INTERVAL: 120,
    TICKS_PER_SEASON: 80,
    
    // DNA
    GENOME_LENGTH: 64,
    MUTATION_RATE: 0.02,
    CROSSOVER_POINTS: 2,
    
    // Survival
    BASE_ENERGY: 80,
    MAX_ENERGY: 120,
    REPRODUCTION_THRESHOLD: 60,
    REPRODUCTION_COST: 30,
    ENERGY_DECAY: 0.25,
    
    // Resources
    RESOURCE_CLUSTERS: 6,
    RESOURCE_BASE_RICHNESS: 1.2,
    
    // Microorganisms
    MAX_MICROBES: 20,
    MICROBE_SPAWN_CHANCE: 0.003,
    
    // Social (Demes)
    DEME_DISTANCE: 18,
    DEME_MIN_SIZE: 3,
    
    // Predation
    PREDATION_ENABLED: true,
    PREDATION_ENERGY_TRANSFER: 0.4,
    
    // Speciation
    SPECIATION_ENABLED: true,
    SPECIATION_THRESHOLD: 20,
    
    // Environmental Zones
    BIOMES_ENABLED: true,
    
    // System Mode (v10)
    CLOSED_SYSTEM: false,
    
    // Research
    SEED: null,
    TIME_SERIES_INTERVAL: 10,
    GENE_POOL_INTERVAL: 100,
}