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Endosymbiotic gene transfer moves genetic material from an endosymbiont or its descendant organelle into the host genome, notably the nuclear genome. A transferred DNA segment can remain silent. For a transferred gene to replace an organelle-encoded function, nuclear gene expression must work and its protein must reach the right compartment through organelle protein import. Transfer of DNA and transport of proteins are distinct processes in opposite directions. ^[ref]

Gene loss and endosymbiotic gene transfer are different: absence from an organelle genome does not by itself show that a functional nuclear copy exists. Conversely, an imported protein may derive from a host gene rather than a transferred gene. The surviving organelle genome is therefore a partial record, not a complete inventory of either ancestral bacteria or the modern organelle's machinery. ^[ref]

A eukaryote is an organism belonging to the lineage characterized by a membrane-bounded cell nucleus and extensive cellular compartmentalization. A nuclear envelope surrounds the nuclear genome; nuclear chromosomes are typically linear. Ribosomes perform biological translation outside the cell nucleus. See OpenStax Microbiology, 3.4: nuclear organization and protein synthesis. Specialized biological cells can lose their cell nucleus, as mature mammalian red blood cells do, while remaining parts of eukaryotic organisms; see OpenStax Biology 2e, 40.2: mature red blood cells.

Yeasts, plants and animals are all eukaryotes. Typical cells in these groups have mitochondria, but chloroplasts belong to photosynthetic plant and algae lineages, not to every eukaryote. A cell wall occurs in typical plant and fungus cells but is absent from animal cells. These are comparisons of representative cells, not a checklist every specialized cell must satisfy. See OpenStax Biology 2e, 4.3: nucleus, organelles and representative cells.

The interesting feature is controlled separation: cell membranes and organelle membranes let different cellular processes occupy distinct compartments while membrane transport connects them. The evolution of eukaryotes also involved partnership: mitochondria descend from a bacterial endosymbiosis. Modern phylogenetics supports an archaeal ancestry for the nuclear lineage, alongside this bacterial contribution; see two-domain system. Thus the history of a whole eukaryote cannot be read as the history of just one of its genes.

Resemblance is a clue, not sufficient evidence of common descent. A small size, two surrounding membranes, division, retained DNA or bacterial-looking ribosomes does not uniquely identify an ancestor. Internal membranes exist outside these organelles, and a similar function can favor similar structures. The stronger question is whether independently examined molecular characters support the same historical relationship.

A concrete genomic observation is the mitochondrial sequence reported in 1997 for Reclinomonas americana: $69,034$ base pairs containing 97 identified genes, including four for a bacterial-type multisubunit RNA polymerase. This is a reported genome inventory, not a calculation from the pictured shape of a mitochondrion. Retention of such bacterial features strengthens the ancestry argument; a living Reclinomonas americana is not itself an ancestral eukaryote. The inspected abstract supplies these observations but not the detailed sequencing protocol or contamination controls, so those details are not attributed to this report here. ^[ref]

A sequence-based investigation obtains nucleotide sequences by DNA sequencing, identifies comparable genes, makes a sequence alignment and uses phylogenetics to infer relationships. The readout is a proposed relationship with support and uncertainty, not a photograph of an ancient encounter. Comparisons of plastid sequences with bacterial sequences support cyanobacterial ancestry, while the exact closest sampled cyanobacterial group has depended on the chosen data and inference. A bacterial affinity in one gene is weaker than coherent evidence across several genes and cellular systems. ^[ref]

For such an analysis, useful checks include distinguishing organelle DNA from bacterial contamination, verifying sequence quality, comparing corresponding rather than unrelated genes, sampling several bacterial groups and testing sensitivity to the sequence alignment and evolutionary mathematical model. These are methodological requirements, not a claim that this article has rerun a particular published analysis. Horizontal gene transfer, gene loss and unequal evolutionary change can make an individual gene's history differ from a whole organism's history. A supported bacterial origin therefore need not identify an extant donor species, an exact date or the original mode of entry. ^[ref]

Evolutionary game theory studies how a population's composition changes when the success of a pure strategy depends on which other pure strategies it encounters. The central feedback is a frequency-dependent payoff: becoming common changes the opponents a strategy meets, which can change whether it does well. In a coordination game, common behaviour can reinforce itself; in the coexistence example below, being rare is an advantage. This makes evolutionary game theory useful for asking which behaviours can persist and which initial compositions lead to different outcomes, without assuming that each participant solves an optimization problem.

In the basic model, a large, well-mixed population has finitely many inherited pure strategies; interactions sample opponents according to their population frequencies. Assume that a strategy's expected payoff determines its per capita net reproductive growth rate, with a common baseline allowed. These are modelling assumptions: reproduction must transmit the strategy, encounters must match the proposed sampling rule, and the conversion from payoff to growth must be justified for an application. The replicator equation below describes the resulting continuous-time frequencies. Taylor and Jonker's ^[ref] explicitly derive this growth model.

For learned behaviour, reproduction can instead be replaced by an assumed copying rule: an individual samples another individual uniformly and copies a better-performing pure strategy at a rate proportional to the positive payoff difference. At frequencies $x_i,x_j$, the net flow from $j$ to $i$ is $x_i{x}_j(f_i-f_j)$, because the two directional positive parts subtract to $f_i-f_j$. Summing over $j$ gives $x_i(f_i-\bar{f})$, the replicator equation. This derivation states a particular mechanism; an arbitrary rule for learning or imitation need not give the same dynamical system.

Three questions must be distinguished. A symmetric Nash equilibrium tests whether an individual can improve its expected payoff against the resident composition. An evolutionarily stable strategy tests whether each distinct rare mutant is outperformed after it is introduced. Dynamical stability tests the response of an actual dynamical system to small changes of composition, and asymptotic stability additionally requires nearby trajectories to converge. For a finite symmetric bimatrix game under the continuous-time replicator equation, every evolutionarily stable strategy is a symmetric Nash equilibrium and a locally asymptotically stable rest point; the converse from asymptotic stability to an evolutionarily stable strategy fails in general. See Ross Cressman and Yi Tao, The replicator equation and other game dynamics (2014), Theorems 1–2 and Example 1. These statements refer to stability on the full probability simplex, including perturbations introducing currently absent pure strategies.

A concrete experiment makes the frequency feedback visible. In 2009, Gore, Youk and van Oudenaarden competed two yeast strains: a producer of the enzyme invertase, which enables sucrose hydrolysis, and a mutant lacking the corresponding SUC2 gene. Released sugars can feed neighbours, so avoiding production can be advantageous. They used shaken 5 mL cultures with 5% sucrose at $30{}^{\circ }\mathrm{C}$, diluted daily after 23 hours of growth. Different labelled proteins allowed the two strains to be counted separately by flow cytometry; selective plating periodically checked the counts. The cooperator required externally supplied histidine, so restricting that amino acid imposed an adjustable growth disadvantage. See Snowdrift game dynamics and facultative cheating in yeast, pp. 253 and 255–256, Methods Summary.

Starting with rare producers and, separately, rare nonproducers tested both invasion directions. Under the reported coexistence conditions each rare strain increased; changing histidine or added glucose shifted the eventual composition. Their explanation used nonlinear growth benefits, rather than a fixed pairwise payoff matrix. This motivates testing both rarity regimes before inferring an evolutionarily stable strategy or fitting a replicator equation; it does not identify the illustrative tables below with measured payoffs. See Gore, Youk and van Oudenaarden, Figures 1–3.

An early motivation was understanding why animal contests can involve restraint even when escalation might win an individual encounter. Maynard Smith and Price's ^[ref] introduced the evolutionarily stable strategy in this setting. Taylor and Jonker's ^[ref] then studied explicit continuous and discrete dynamics. Static resistance to invasion and the paths populations follow are related questions, but they require separate definitions.

A segment retained in the mature RNA after RNA splicing, or the corresponding segment of a gene. An exon need not encode a protein: the ribosomal RNA exons in the Tetrahymena ribozyme experiment are an example.

Functional complementation is restoration of a specified function or phenotype by introducing a gene into a deficient recipient. In the yeast cross-species complementation experiment, the restored property is growth without supplied methionine, under the assay conditions. Rescue need not restore every property of the original genotype.

Experimental Reconstruction of Functional Gene Transfer from the Tobacco Plastid Genome to the Nucleus by Sandra Stegemann and Ralph Bock (2006, Results, pp. 2870–2874) separated relocation of DNA from activation of a relocated gene. Engineered tobacco chloroplasts carried an nptII gene with nuclear expression signals beside an aadA gene with plastid expression signals. Selection on kanamycin recovered plants with the segment in the nuclear genome. Crosses then replaced the engineered chloroplasts with ordinary chloroplasts: the nuclear segment remained, but the plants were initially sensitive to spectinomycin and streptomycin. The transferred aadA gene was not yet functional in its new setting.

Leaf pieces were cultured on regeneration medium containing both drugs. Resistant regenerated plants supplied the functional readout. Using both drugs reduced selection of spontaneous plastid mutations conferring resistance mainly to one drug. Reciprocal crosses and selfing distinguished maternal plastid inheritance from nuclear Mendelian segregation; eight of sixteen initial candidates had the latter pattern. ^[ref]

The molecular readout came from RNA hybridization and DNA sequencing. A Northern blot detected aadA messenger RNA in activated lines, with different transcript sizes. Thermal asymmetric interlaced polymerase chain reaction recovered upstream DNA; products present in activated lines but absent in original-line and ordinary-plant controls were sequenced. The mapped rearrangements connected aadA to the upstream nuclear gene promoter. Thus resistance, inheritance, RNA detection and changed nucleotide sequences supported activation of the transferred nuclear gene, rather than resistance alone. ^[ref]

This engineered test demonstrates one route to functional nuclear gene expression after plastid DNA transfer. It does not establish a natural transfer rate, replay ancient endosymbiosis or demonstrate that the resulting protein is imported into a chloroplast. The authors explicitly identify acquisition of targeting information as an additional step not reproduced by this experiment. ^[ref]

A gene is an inherited functional unit of genetic material. In cellular organisms, a gene is a region of DNA whose information produces a functional RNA or contributes to a protein. This connects inheritance to cellular chemistry: a change in a gene can alter the amount or activity of a protein, and thereby a phenotype. See NHGRI: gene.

Alternative inherited versions at a genetic locus are alleles. The distinction matters: two parents can carry the same gene but different alleles, and a genetic locus can have variation outside a gene. Neither the word gene nor a change in DNA alone specifies the resulting phenotype.

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