diff --git a/src/MrGameEng.Content/Genetics/Allele.cs b/src/MrGameEng.Content/Genetics/Allele.cs
new file mode 100644
index 0000000..a05de50
--- /dev/null
+++ b/src/MrGameEng.Content/Genetics/Allele.cs
@@ -0,0 +1,16 @@
+namespace MrGameEng.Genetics;
+
+/// <summary>
+/// A diploid gene slot: the two allele values an individual carries for one gene. Stored as floats
+/// for both gene kinds — a <see cref="GeneKind.Discrete"/> gene simply holds integral variant
+/// indices. How the pair becomes a single phenotype value is decided by the gene's
+/// <see cref="GeneKind"/> (see <see cref="Genome.Express"/>).
+/// </summary>
+public readonly record struct Allele(float A, float B)
+{
+    /// <summary>The average of the two alleles — the phenotype of a numeric gene.</summary>
+    public float Mean => (A + B) * 0.5f;
+
+    /// <summary>The lower (dominant) of the two alleles — the phenotype of a discrete gene.</summary>
+    public float Dominant => MathF.Min(A, B);
+}
diff --git a/src/MrGameEng.Content/Genetics/GeneDef.cs b/src/MrGameEng.Content/Genetics/GeneDef.cs
new file mode 100644
index 0000000..044fae1
--- /dev/null
+++ b/src/MrGameEng.Content/Genetics/GeneDef.cs
@@ -0,0 +1,97 @@
+using System.Text.Json.Serialization;
+using MrGameEng.Formulas;
+using MrGameEng.Mods;
+
+namespace MrGameEng.Genetics;
+
+/// <summary>How a gene's two alleles are stored and expressed into a phenotype value.</summary>
+public enum GeneKind
+{
+    /// <summary>A continuous value; the phenotype is the average of the two alleles (hybrid blending).</summary>
+    Numeric,
+
+    /// <summary>
+    /// A discrete allele index in <c>[0, Variants)</c>; the lower index is dominant, so the
+    /// phenotype is <c>min(a, b)</c> — a higher (recessive) variant shows only when homozygous.
+    /// A two-variant discrete gene is effectively a flag.
+    /// </summary>
+    Discrete,
+}
+
+/// <summary>
+/// An organism-agnostic gene definition — the unit the whole gene system is built from. A
+/// <see cref="GeneDef"/> describes how to generate an individual's two alleles, how they mutate
+/// when bred, and how the gene <see cref="Effects"/> contribute to named phenotype traits via
+/// <see cref="Formula"/> expressions. Nothing here is plant-, animal- or human-specific, so the
+/// same machinery drives any organism and arbitrary hybrids (a genome can carry any mix of genes).
+/// </summary>
+public sealed class GeneDef : Def
+{
+    /// <summary>Whether the gene is continuous or a discrete dominant/recessive allele.</summary>
+    public GeneKind Kind { get; init; } = GeneKind.Numeric;
+
+    /// <summary>Numeric: the central value an allele is generated around.</summary>
+    public float Default { get; init; }
+
+    /// <summary>Numeric: lower clamp for generated and mutated allele values.</summary>
+    public float Min { get; init; } = float.NegativeInfinity;
+
+    /// <summary>Numeric: upper clamp for generated and mutated allele values.</summary>
+    public float Max { get; init; } = float.PositiveInfinity;
+
+    /// <summary>Numeric: relative spread of generated alleles around <see cref="Default"/> (allele = Default ± Spread·|Default|).</summary>
+    public float Spread { get; init; }
+
+    /// <summary>Numeric: relative magnitude of a mutation step (value ± Magnitude·|value|).</summary>
+    public float MutationMagnitude { get; init; } = 0.1f;
+
+    /// <summary>Discrete: number of allele variants, valued <c>0..Variants-1</c>.</summary>
+    public int Variants { get; init; } = 2;
+
+    /// <summary>
+    /// Discrete: relative weights for generating each variant (length <see cref="Variants"/>).
+    /// Empty means a uniform distribution.
+    /// </summary>
+    public float[] VariantWeights { get; init; } = [];
+
+    /// <summary>Probability, per allele, that a mutation occurs when this gene is passed to a child.</summary>
+    public float MutationChance { get; init; }
+
+    /// <summary>
+    /// The gene's contributions to phenotype traits: trait name → formula. Each formula may use the
+    /// variable <c>value</c> (this gene's expressed phenotype), any other gene's id (its expressed
+    /// value) and any environment variable the caller supplies. Contributions to the same trait
+    /// across genes are summed.
+    /// </summary>
+    public Dictionary<string, string> Effects { get; init; } = new();
+
+    /// <summary>Free-form category tags for grouping genes (used by formula grouping and content tooling).</summary>
+    public string[] Tags { get; init; } = [];
+
+    private IReadOnlyDictionary<string, Formula>? _compiled;
+
+    /// <summary>The <see cref="Effects"/> compiled once into evaluable formulas (lazy, cached).</summary>
+    [JsonIgnore]
+    public IReadOnlyDictionary<string, Formula> CompiledEffects => _compiled ??= CompileEffects();
+
+    private Dictionary<string, Formula> CompileEffects()
+    {
+        var compiled = new Dictionary<string, Formula>(StringComparer.Ordinal);
+        foreach (var (trait, expression) in Effects)
+        {
+            try
+            {
+                compiled[trait] = Formula.Compile(expression);
+            }
+            catch (FormulaException error)
+            {
+                throw new InvalidDataException(
+                    $"Gene '{DefName}' effect on trait '{trait}' has an invalid formula "
+                        + $"\"{expression}\": {error.Message}"
+                );
+            }
+        }
+
+        return compiled;
+    }
+}
diff --git a/src/MrGameEng.Content/Genetics/Genome.cs b/src/MrGameEng.Content/Genetics/Genome.cs
new file mode 100644
index 0000000..64ebbb9
--- /dev/null
+++ b/src/MrGameEng.Content/Genetics/Genome.cs
@@ -0,0 +1,190 @@
+namespace MrGameEng.Genetics;
+
+/// <summary>
+/// An individual's managed genome: a variable-composition map from gene id to the
+/// <see cref="Allele"/> pair it carries. Because composition is open, two organisms need not share
+/// the same gene set and a genome can gain "foreign" genes — the basis for arbitrary hybrids. The
+/// genome is generated from a set of <see cref="GeneDef"/>s, bred meiotically with mutation, and
+/// expressed into phenotype values; all randomness flows through a caller-owned seeded
+/// <see cref="Random"/> so the simulation stays deterministic.
+/// </summary>
+public sealed class Genome
+{
+    private readonly Dictionary<string, Allele> _alleles;
+
+    /// <summary>Creates an empty genome.</summary>
+    public Genome() => _alleles = new Dictionary<string, Allele>(StringComparer.Ordinal);
+
+    /// <summary>Creates a genome from an existing allele map (copied).</summary>
+    public Genome(IReadOnlyDictionary<string, Allele> alleles) =>
+        _alleles = new Dictionary<string, Allele>(alleles, StringComparer.Ordinal);
+
+    /// <summary>The carried genes and their allele pairs.</summary>
+    public IReadOnlyDictionary<string, Allele> Alleles => _alleles;
+
+    /// <summary>Whether the genome carries the gene <paramref name="geneId"/>.</summary>
+    public bool Has(string geneId) => _alleles.ContainsKey(geneId);
+
+    /// <summary>Gets or sets the allele pair for <paramref name="geneId"/>.</summary>
+    public Allele this[string geneId]
+    {
+        get => _alleles[geneId];
+        set => _alleles[geneId] = value;
+    }
+
+    /// <summary>Removes a gene from the genome; returns whether it was present.</summary>
+    public bool Remove(string geneId) => _alleles.Remove(geneId);
+
+    /// <summary>
+    /// Expresses the gene's phenotype value: the mean of the alleles for a numeric gene, the
+    /// dominant (lower) allele for a discrete one. Throws if the genome does not carry the gene.
+    /// </summary>
+    public float Express(GeneDef gene)
+    {
+        if (!_alleles.TryGetValue(gene.DefName, out var allele))
+        {
+            throw new KeyNotFoundException($"Genome does not carry gene '{gene.DefName}'.");
+        }
+
+        return gene.Kind == GeneKind.Numeric ? allele.Mean : allele.Dominant;
+    }
+
+    /// <summary>Builds the allele map for serialization (a copy).</summary>
+    public Dictionary<string, Allele> ToDictionary() => new(_alleles, StringComparer.Ordinal);
+
+    /// <summary>
+    /// Generates a fresh genome carrying every gene in <paramref name="genes"/>, each allele drawn
+    /// independently around the gene's default with its spread (numeric) or from its variant
+    /// distribution (discrete).
+    /// </summary>
+    public static Genome Generate(IEnumerable<GeneDef> genes, Random random)
+    {
+        var genome = new Genome();
+        foreach (var gene in genes)
+        {
+            genome._alleles[gene.DefName] = new Allele(
+                GenerateAllele(gene, random),
+                GenerateAllele(gene, random)
+            );
+        }
+
+        return genome;
+    }
+
+    /// <summary>
+    /// Breeds a child genome from two parents (meiosis): the child carries every gene either parent
+    /// has. For a gene both carry, one allele is drawn from each parent; for a gene only one parent
+    /// carries, it is inherited (from that parent, on both sides) with 50% probability. Every
+    /// inherited allele may then mutate per its <see cref="GeneDef"/>. <paramref name="registry"/>
+    /// supplies the def for each gene id; genes absent from it are skipped.
+    /// </summary>
+    public static Genome Breed(
+        Genome a,
+        Genome b,
+        IReadOnlyDictionary<string, GeneDef> registry,
+        Random random
+    )
+    {
+        var child = new Genome();
+        foreach (var geneId in UnionKeys(a, b))
+        {
+            if (!registry.TryGetValue(geneId, out var gene))
+            {
+                continue;
+            }
+
+            var inA = a.Has(geneId);
+            var inB = b.Has(geneId);
+            if (inA && inB)
+            {
+                child._alleles[geneId] = new Allele(
+                    Meiosis(gene, a[geneId], random),
+                    Meiosis(gene, b[geneId], random)
+                );
+            }
+            else if (random.NextSingle() < 0.5f)
+            {
+                var parent = inA ? a : b;
+                child._alleles[geneId] = new Allele(
+                    Meiosis(gene, parent[geneId], random),
+                    Meiosis(gene, parent[geneId], random)
+                );
+            }
+        }
+
+        return child;
+    }
+
+    // One inherited allele: pick one of the parent slot's two alleles, then maybe mutate it.
+    private static float Meiosis(GeneDef gene, Allele parent, Random random)
+    {
+        var inherited = random.NextSingle() < 0.5f ? parent.A : parent.B;
+        if (random.NextSingle() >= gene.MutationChance)
+        {
+            return inherited;
+        }
+
+        if (gene.Kind == GeneKind.Discrete)
+        {
+            return PickVariant(gene, random);
+        }
+
+        var shifted =
+            inherited
+            + (random.NextSingle() * 2f - 1f) * gene.MutationMagnitude * MathF.Abs(inherited);
+        return Math.Clamp(shifted, gene.Min, gene.Max);
+    }
+
+    private static float GenerateAllele(GeneDef gene, Random random)
+    {
+        if (gene.Kind == GeneKind.Discrete)
+        {
+            return PickVariant(gene, random);
+        }
+
+        var value =
+            gene.Default + (random.NextSingle() * 2f - 1f) * gene.Spread * MathF.Abs(gene.Default);
+        return Math.Clamp(value, gene.Min, gene.Max);
+    }
+
+    private static float PickVariant(GeneDef gene, Random random)
+    {
+        var variants = Math.Max(1, gene.Variants);
+        if (gene.VariantWeights.Length != variants)
+        {
+            return random.Next(variants);
+        }
+
+        var total = 0f;
+        foreach (var w in gene.VariantWeights)
+        {
+            total += MathF.Max(0f, w);
+        }
+
+        if (total <= 0f)
+        {
+            return random.Next(variants);
+        }
+
+        var roll = random.NextSingle() * total;
+        for (var i = 0; i < variants; i++)
+        {
+            roll -= MathF.Max(0f, gene.VariantWeights[i]);
+            if (roll < 0f)
+            {
+                return i;
+            }
+        }
+
+        return variants - 1;
+    }
+
+    // Deterministic union of both parents' gene ids (ordered) so breeding is reproducible.
+    private static IEnumerable<string> UnionKeys(Genome a, Genome b)
+    {
+        var keys = new SortedSet<string>(StringComparer.Ordinal);
+        keys.UnionWith(a._alleles.Keys);
+        keys.UnionWith(b._alleles.Keys);
+        return keys;
+    }
+}
diff --git a/src/MrGameEng.Content/Genetics/Phenotype.cs b/src/MrGameEng.Content/Genetics/Phenotype.cs
new file mode 100644
index 0000000..ffe1dec
--- /dev/null
+++ b/src/MrGameEng.Content/Genetics/Phenotype.cs
@@ -0,0 +1,75 @@
+using MrGameEng.Formulas;
+
+namespace MrGameEng.Genetics;
+
+/// <summary>
+/// Computes the trait layer — the phenotype the simulation actually reads — from a
+/// <see cref="Genome"/>. Each gene's <see cref="GeneDef.Effects"/> formulas are evaluated and their
+/// results summed per trait name, so systems never touch genes directly: one fruiting system reads
+/// a <c>fruitYield</c> trait whether it comes from a tree or a human carrying a "fruit" gene.
+/// Formulas see the variable <c>value</c> (the contributing gene's expressed phenotype), any other
+/// carried gene's id, and whatever environment variables the caller supplies.
+/// </summary>
+public static class Phenotype
+{
+    /// <summary>
+    /// Evaluates every carried gene's effects against the genome and an optional
+    /// <paramref name="environment"/>, summing contributions into a trait map. Genes missing from
+    /// <paramref name="registry"/> are skipped.
+    /// </summary>
+    public static Dictionary<string, float> Compute(
+        Genome genome,
+        IReadOnlyDictionary<string, GeneDef> registry,
+        IFormulaContext? environment = null
+    )
+    {
+        var traits = new Dictionary<string, float>(StringComparer.Ordinal);
+        var context = new GenomeContext(genome, registry, environment);
+        foreach (var geneId in genome.Alleles.Keys)
+        {
+            if (!registry.TryGetValue(geneId, out var gene) || gene.CompiledEffects.Count == 0)
+            {
+                continue;
+            }
+
+            context.Self = genome.Express(gene);
+            foreach (var (trait, formula) in gene.CompiledEffects)
+            {
+                traits[trait] = traits.GetValueOrDefault(trait) + formula.Evaluate(context);
+            }
+        }
+
+        return traits;
+    }
+
+    // Resolves formula variables for a gene effect: 'value' is the current gene's phenotype, any
+    // carried gene's id resolves to its phenotype, anything else falls through to the environment.
+    private sealed class GenomeContext(
+        Genome genome,
+        IReadOnlyDictionary<string, GeneDef> registry,
+        IFormulaContext? environment
+    ) : IFormulaContext
+    {
+        public float Self;
+
+        public float Resolve(string name)
+        {
+            if (name == "value")
+            {
+                return Self;
+            }
+
+            if (genome.Has(name) && registry.TryGetValue(name, out var gene))
+            {
+                return genome.Express(gene);
+            }
+
+            if (environment is not null)
+            {
+                return environment.Resolve(name);
+            }
+
+            throw new FormulaException($"Unknown variable '{name}' while computing traits.");
+        }
+    }
+}
diff --git a/src/MrGameEng.Content/Mods/ModInfo.cs b/src/MrGameEng.Content/Mods/ModInfo.cs
index 948116f..63f2dd6 100644
--- a/src/MrGameEng.Content/Mods/ModInfo.cs
+++ b/src/MrGameEng.Content/Mods/ModInfo.cs
@@ -1,4 +1,5 @@
 using System.Text.Json;
+using System.Text.Json.Serialization;
 
 namespace MrGameEng.Mods;
 
@@ -14,6 +15,7 @@ public sealed class ModInfo
         ReadCommentHandling = JsonCommentHandling.Skip,
         AllowTrailingCommas = true,
         WriteIndented = true,
+        Converters = { new JsonStringEnumConverter() },
     };
 
     /// <summary>Unique mod id, referenced by <see cref="Dependencies"/> of other mods.</summary>
diff --git a/tests/MrGameEng.Content.Tests/Genetics/GeneDefLoadTests.cs b/tests/MrGameEng.Content.Tests/Genetics/GeneDefLoadTests.cs
new file mode 100644
index 0000000..1e2e61d
--- /dev/null
+++ b/tests/MrGameEng.Content.Tests/Genetics/GeneDefLoadTests.cs
@@ -0,0 +1,68 @@
+using MrGameEng.Genetics;
+using MrGameEng.Mods;
+using Xunit;
+
+namespace MrGameEng.Genetics.Tests;
+
+/// <summary>
+/// Verifies <see cref="GeneDef"/> loads through the real <see cref="DefDatabase"/> the way the game
+/// loads <c>genes.json</c>: string-named <see cref="GeneKind"/>, parent inheritance and effect maps.
+/// </summary>
+public sealed class GeneDefLoadTests : IDisposable
+{
+    private readonly string _root = Directory.CreateTempSubdirectory("mrge-gene-tests-").FullName;
+
+    public void Dispose() => Directory.Delete(_root, recursive: true);
+
+    private DefDatabase Load(string defsJson)
+    {
+        var modDir = Path.Combine(_root, "mod");
+        Directory.CreateDirectory(Path.Combine(modDir, "Defs"));
+        File.WriteAllText(Path.Combine(modDir, "Defs", "genes.json"), defsJson);
+        var database = new DefDatabase();
+        database.RegisterType<GeneDef>("Gene");
+        database.Load([new Mod(new ModInfo { Id = "mod" }, modDir)]);
+        return database;
+    }
+
+    [Fact]
+    public void Load_NumericGeneWithParentAndEffects_Resolves()
+    {
+        var database = Load(
+            """
+            { "type": "Gene", "defs": [
+                { "defName": "BaseGene", "abstract": true, "spread": 0.1, "mutationChance": 0.05 },
+                { "defName": "GeneVigor", "parent": "BaseGene", "default": 1.0, "min": 0.1, "max": 3.0,
+                  "tags": ["growth"], "effects": { "vigor": "value" } }
+            ]}
+            """
+        );
+
+        var gene = database.Get<GeneDef>("GeneVigor");
+        Assert.Equal(GeneKind.Numeric, gene.Kind);
+        Assert.Equal(0.1f, gene.Spread); // inherited from parent
+        Assert.Equal(0.05f, gene.MutationChance); // inherited
+        Assert.Equal(3.0f, gene.Max);
+        Assert.Equal(["growth"], gene.Tags);
+        Assert.Equal("value", gene.Effects["vigor"]);
+        Assert.Single(gene.CompiledEffects); // formula compiles
+    }
+
+    [Fact]
+    public void Load_DiscreteKindByName_Parses()
+    {
+        var database = Load(
+            """
+            { "type": "Gene", "defs": [
+                { "defName": "GeneMorph", "kind": "Discrete", "variants": 2,
+                  "variantWeights": [0.8, 0.2], "effects": { "variant": "value" } }
+            ]}
+            """
+        );
+
+        var gene = database.Get<GeneDef>("GeneMorph");
+        Assert.Equal(GeneKind.Discrete, gene.Kind);
+        Assert.Equal(2, gene.Variants);
+        Assert.Equal([0.8f, 0.2f], gene.VariantWeights);
+    }
+}
diff --git a/tests/MrGameEng.Content.Tests/Genetics/GeneticsTests.cs b/tests/MrGameEng.Content.Tests/Genetics/GeneticsTests.cs
new file mode 100644
index 0000000..d59a619
--- /dev/null
+++ b/tests/MrGameEng.Content.Tests/Genetics/GeneticsTests.cs
@@ -0,0 +1,194 @@
+using MrGameEng.Formulas;
+using MrGameEng.Genetics;
+using Xunit;
+
+namespace MrGameEng.Genetics.Tests;
+
+public class GeneticsTests
+{
+    private static GeneDef Numeric(
+        string name,
+        float def,
+        float spread = 0f,
+        float min = float.NegativeInfinity,
+        float max = float.PositiveInfinity,
+        float mutationChance = 0f,
+        float mutationMagnitude = 0.1f,
+        Dictionary<string, string>? effects = null
+    ) =>
+        new()
+        {
+            DefName = name,
+            Kind = GeneKind.Numeric,
+            Default = def,
+            Spread = spread,
+            Min = min,
+            Max = max,
+            MutationChance = mutationChance,
+            MutationMagnitude = mutationMagnitude,
+            Effects = effects ?? new(),
+        };
+
+    private static GeneDef Discrete(string name, int variants = 2, float mutationChance = 0f) =>
+        new()
+        {
+            DefName = name,
+            Kind = GeneKind.Discrete,
+            Variants = variants,
+            MutationChance = mutationChance,
+        };
+
+    private static Dictionary<string, GeneDef> Registry(params GeneDef[] genes) =>
+        genes.ToDictionary(g => g.DefName, g => g, StringComparer.Ordinal);
+
+    [Fact]
+    public void Generate_NumericAlleles_StayWithinSpreadAndClamp()
+    {
+        var gene = Numeric("vigor", def: 1f, spread: 0.2f, min: 0f, max: 2f);
+        var random = new Random(7);
+
+        for (var i = 0; i < 200; i++)
+        {
+            var genome = Genome.Generate([gene], random);
+            var allele = genome["vigor"];
+            Assert.InRange(allele.A, 0.8f, 1.2f);
+            Assert.InRange(allele.B, 0.8f, 1.2f);
+        }
+    }
+
+    [Fact]
+    public void Generate_SameSeed_IsDeterministic()
+    {
+        var genes = new[] { Numeric("a", 1f, 0.3f), Discrete("morph", 2) };
+
+        var first = Genome.Generate(genes, new Random(42));
+        var second = Genome.Generate(genes, new Random(42));
+
+        Assert.Equal(first["a"], second["a"]);
+        Assert.Equal(first["morph"], second["morph"]);
+    }
+
+    [Fact]
+    public void Express_Numeric_IsAlleleMean()
+    {
+        var gene = Numeric("opt", 0f);
+        var genome = new Genome { ["opt"] = new Allele(0.4f, 0.8f) };
+
+        Assert.Equal(0.6f, genome.Express(gene), 5);
+    }
+
+    [Fact]
+    public void Express_Discrete_DominantIsLowerIndex()
+    {
+        var gene = Discrete("morph", 2);
+
+        Assert.Equal(0f, new Genome { ["morph"] = new Allele(0f, 1f) }.Express(gene)); // heterozygous → dominant 0
+        Assert.Equal(1f, new Genome { ["morph"] = new Allele(1f, 1f) }.Express(gene)); // homozygous recessive
+    }
+
+    [Fact]
+    public void Breed_WithoutMutation_InheritsOneAlleleFromEachParent()
+    {
+        var gene = Numeric("g", 0f, mutationChance: 0f);
+        var registry = Registry(gene);
+        var a = new Genome { ["g"] = new Allele(1f, 2f) };
+        var b = new Genome { ["g"] = new Allele(3f, 4f) };
+
+        var child = Genome.Breed(a, b, registry, new Random(1));
+
+        Assert.Contains(child["g"].A, new[] { 1f, 2f }); // first allele from parent a
+        Assert.Contains(child["g"].B, new[] { 3f, 4f }); // second allele from parent b
+    }
+
+    [Fact]
+    public void Breed_UnionOfGenes_ProducesHybridComposition()
+    {
+        // a carries only "leaf", b carries only "root" — a child can carry both (hybrid).
+        var registry = Registry(Numeric("leaf", 1f), Numeric("root", 1f));
+        var a = new Genome { ["leaf"] = new Allele(1f, 1f) };
+        var b = new Genome { ["root"] = new Allele(2f, 2f) };
+
+        var carriedBoth = false;
+        for (var seed = 0; seed < 50 && !carriedBoth; seed++)
+        {
+            var child = Genome.Breed(a, b, registry, new Random(seed));
+            carriedBoth = child.Has("leaf") && child.Has("root");
+        }
+
+        Assert.True(carriedBoth, "single-parent genes should sometimes both be inherited");
+    }
+
+    [Fact]
+    public void Breed_HighMutation_DiscreteCanFlipVariant()
+    {
+        var gene = Discrete("morph", variants: 2, mutationChance: 1f);
+        var registry = Registry(gene);
+        var parent = new Genome { ["morph"] = new Allele(0f, 0f) };
+
+        var sawOne = false;
+        for (var seed = 0; seed < 50 && !sawOne; seed++)
+        {
+            var child = Genome.Breed(parent, parent, registry, new Random(seed));
+            var allele = child["morph"];
+            sawOne = allele.A == 1f || allele.B == 1f;
+        }
+
+        Assert.True(sawOne, "with full mutation a 0/0 parent should sometimes yield variant 1");
+    }
+
+    [Fact]
+    public void Compute_GeneEffect_UsesValueVariable()
+    {
+        var gene = Numeric("vigor", 0f, effects: new() { ["growth"] = "value * 2" });
+        var genome = new Genome { ["vigor"] = new Allele(1.5f, 2.5f) }; // mean 2
+
+        var traits = Phenotype.Compute(genome, Registry(gene));
+
+        Assert.Equal(4f, traits["growth"], 5); // 2 * 2
+    }
+
+    [Fact]
+    public void Compute_MultipleGenes_SumContributionsPerTrait()
+    {
+        var a = Numeric("a", 0f, effects: new() { ["yield"] = "value" });
+        var b = Numeric("b", 0f, effects: new() { ["yield"] = "value" });
+        var genome = new Genome { ["a"] = new Allele(3f, 3f), ["b"] = new Allele(4f, 4f) };
+
+        var traits = Phenotype.Compute(genome, Registry(a, b));
+
+        Assert.Equal(7f, traits["yield"], 5);
+    }
+
+    [Fact]
+    public void Compute_FormulaReadsEnvironmentAndOtherGenes()
+    {
+        var opt = Numeric("optLight", 0.5f);
+        var vigor = Numeric(
+            "vigor",
+            1f,
+            effects: new() { ["rate"] = "value * (1 - abs(light - optLight))" }
+        );
+        var genome = new Genome
+        {
+            ["optLight"] = new Allele(0.5f, 0.5f),
+            ["vigor"] = new Allele(1f, 1f),
+        };
+        var env = new DelegateFormulaContext(n =>
+            n == "light" ? 0.7f : throw new FormulaException(n)
+        );
+
+        var traits = Phenotype.Compute(genome, Registry(opt, vigor), env);
+
+        Assert.Equal(0.8f, traits["rate"], 5); // 1 * (1 - |0.7 - 0.5|)
+    }
+
+    [Fact]
+    public void CompiledEffects_InvalidFormula_ThrowsWithGeneAndTrait()
+    {
+        var gene = Numeric("bad", 0f, effects: new() { ["t"] = "value *" });
+
+        var error = Assert.Throws<InvalidDataException>(() => _ = gene.CompiledEffects);
+        Assert.Contains("bad", error.Message);
+        Assert.Contains("t", error.Message);
+    }
+}