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A genetic map turns observations of inherited haplotypes into an ordered account of genetic loci along a chromosome. Its distances describe genetic recombination, which makes the map useful for locating a genetic locus relative to known genetic markers. A genetic map measures inheritance separation; separation measured in base pairs describes positions along DNA. Recombination hotspots help explain why equal numbers of base pairs need not give equal genetic map distances. See T. A. Brown, Genomes, 2nd edition (2002), chapter 5: Mapping Genomes.

Write $d$ for the expected value of the number of chromosomal crossovers encountered along one transmitted chromatid between the chosen genetic loci, measured in morgans; $100d$ is the distance in centimorgans. This counts exchanges along that transmitted chromatid, rather than all exchanges in the four-chromatid meiotic bundle. For a short interval with very few multiple exchanges, the recombination fraction satisfies $r\approx d$: about $1\%$ recombinant gametes then corresponds to about one centimorgan.

For a longer interval, hidden even numbers of chromosomal crossovers make that approximation inaccurate. Under the Haldane mapping function, $d=0.2$ morgans gives $r\approx 0.164840$; conversely $r=0.2$ gives $d\approx 0.255413$ morgans, or $25.5413$ centimorgans. Applying the inverse formula to an already specified genetic map distance would confuse a count with a probability.

Genetic map distances add along ordered adjacent intervals because the total exchange count is the sum of its interval counts. For independent random variables describing counts in disjoint intervals of the Haldane mapping function model, the endpoint recombination fraction instead obeysExactly one interval must change parental origin. Thus $r_1=r_2=0.2$ gives $r_{12}=0.32$, although the two genetic map distances add to approximately $0.510826$ morgans. The simple composition formula requires the stated independence; crossover interference can invalidate it.

Genetic recombination rearranges inherited genetic material into new combinations. In the meiosis example considered here, chromosomal crossover exchanges segments between nonsister chromatids of homologous chromosomes. A transmitted chromatid can consequently contain DNA from both parental homologues. This produces new haplotypes without requiring a new mutation at either scored genetic locus. See Meiosis.

For phase-known genotype $AB/ab$, a single chromosomal crossover between the selected genetic loci can yield $Ab$ and $aB$ on the participating chromatids; the other two chromatids can remain $AB$ and $ab$. Thus an exchange in the four-chromatid bundle does not mean every resulting gamete is recombinant. Only a chromosomal crossover encountered along the transmitted chromatid within the selected interval affects its two-locus score.

Follow parental origin along the transmitted chromatid from the first genetic locus to the second. Each exchange switches that origin. An odd number of such chromosomal crossovers changes the endpoint combination; an even number restores parental phase. Two exchanges can therefore leave the scored haplotype as $AB$ even though an internal segment came from the other parental homologous chromosome. Recombinant status is relative to the chosen genetic loci, not a complete record of exchanges along the chromosome.

This integer parity distinction connects the physical process of genetic recombination to the observed recombination fraction. It also explains why a long genetic map interval can accumulate many exchanges while its endpoint recombination fraction approaches $1/2$ in the Haldane mapping function model.

Genetics studies how genes are inherited, how their alleles vary, and how that variation contributes to phenotypes. Its central distinction is between an inherited description, the genotype, and what an organism actually expresses, the phenotype. Following alleles through a pedigree answers a family-level question; following allele frequencies through generations leads to population genetics and evolution.

The beauty of Mendelian segregation is that discrete inherited copies can generate predictable statistical patterns without making every offspring identical. A single genetic locus already connects meiosis, probability and observable variation. The Hardy-Weinberg principle then supplies a population baseline: it separates reshuffling inherited copies from processes such as natural selection that change their frequencies. These simple models are useful precisely because their assumptions can be stated and checked.

A genotype records the inherited alleles carried by an individual at one or more genetic loci. At a two-copy diploid genetic locus with alleles $A,a$, the possible unordered genotypes are $AA,Aa,aa$. The first and last are homozygotes; the middle is a heterozygote. The notation records inherited states, without yet asserting their phenotypes. See NHGRI: genotype.

An unordered $Aa$ combines the two parental orders $Aa$ and $aA$. This small bookkeeping point explains the factor two in Hardy-Weinberg proportions and in an $Aa\times Aa$ cross. If parental origin or arrangement across several genetic loci matters, a phase-known genotype retains extra information about the two haplotypes.

Genotyping determines the alleles carried at chosen genetic loci. A diploid genotype call need not identify its two haplotypes; that additionally requires a phase-known genotype or haplotype estimation.

Consider an explicitly idealized haploid population with two inherited types $A,B$, one allele per individual at the tracked genetic locus, and discrete, nonoverlapping generations. Assume faithful type transmission, no mutation or gene flow, a constant environment, and reproductive contributions independent of type frequency. Let the expected values of offspring surviving to the next census be $m_A,m_B>0$, with relative genotype fitness $w=m_A/m_B$.

For $A$ frequency $p$, expected offspring contributions are proportional to $p{m}_A$ and $(1-p)m_B$. Normalizing gives the deterministic large-population mathematical modelThe denominator is mean relative genotype fitness. For $w=1.2$ and $p_0=0.2$, $p_1=0.24/1.04=3/13\approx 0.23077$. Equivalently, 200 $A$ and 800 $B$ parents with $m_A=1.2,m_B=1$ contribute expected counts 240 and 800. Fractional per-parent expected values are averages, not literal fractional offspring. The ratio of these expectations is a deterministic approximation, not generally the expectation of a random ratio.

The odds multiply particularly simply:Thus $p_{10}\approx 0.60753$: repeated modest advantage can substantially change composition. For $w>1$ and $0<p<1$, $p^{\prime }-p=(w-1)p(1-p)/(1+(w-1)p)>0$. The deterministic boundary $p=0$ remains unchanged: natural selection needs existing variation.

A distinct stochastic extension fixes $N$ offspring and samples their types independently using a binomial distribution: $K\sim \mathrm{Binomial}(N,q)$, where $q=wp/(wp+1-p)$, then $p^{\prime }=K/N$. Its conditional expected value is $q$ and conditional variance is $q(1-q)/N$. With $w=1$, the conditional expected value remains $p$, yet realized frequencies wander through genetic drift. With $w>1$, genetic drift can still lower $p$ or lose $A$ entirely. Over several generations, the deterministic curve need not equal the mean stochastic trajectory, because the recurrence is nonlinear.

A haplotype is the set of alleles on one chromosome across specified genetic loci. Closely linked markers without intervening genetic recombination are transmitted as one haplotype; they are not independent observations of inheritance.

A haplotype frequency is the proportion of chromosome copies carrying specified alleles together across chosen genetic loci. Its marginal distributions give allele frequencies; its departures from products of those frequencies are linkage disequilibrium.

Heterozygosity means that the two allele states at a diploid genetic locus differ; an individual with that property is a heterozygote. Heterozygous parental genotypes provide alternative alleles for a transmission disequilibrium test.

Homologous chromosomes carry corresponding genetic loci, although their alleles may differ. In the diploid $AB/ab$ example, the two homologous chromosomes carry the parental haplotypes $AB$ and $ab$.

Homozygosity means that the two allele states at a diploid genetic locus are the same; an individual with that property is a homozygote. Observed homozygosity does not by itself establish identity by descent.

Independent assortment means that transmission at different genetic loci has conditional independence given the parental genotype. With fair Mendelian segregation, a parent heterozygous at two genetic loci, $AaBb$, produces $AB,Ab,aB,ab$ gametes with probability $1/4$ each. For example,Here $AB$ labels an allele combination; it does not assert that the two genetic loci lie on the same chromosome.

The physical model is stochastic orientation of different homologous chromosome pairs toward the two poles of the spindle apparatus in meiosis I. One pair's orientation does not determine another's. For two pairs, one division can send $A,B$ together and $a,b$ together; another can send $A,b$ together and $a,B$ together. See The Process of Meiosis (§11.1, Metaphase I and Figure 11.5: random orientation of chromosome pairs).

With $k$ distinguishable homologous chromosome pairs, there are $2^k$ choices of parental homologous chromosome origin for a product at a specified pole, each with probability $2^{-k}$ under this model. For $k=3$, enumerate $MMM,MMP,MPM,MPP,PMM,PMP,PPM,PPP$, where M and P mark parental origins. Whole-pole reversal pairs complementary choices, leaving $2^{k-1}$ unordered partitions for $k\ge 1$. For $k=2$ there are four choices for a specified pole but only the two relative orientations drawn. This counts possible products across meioses, not eight different products of one division when $k=3$. Identical alleles at scored genetic loci can also make different parental-origin choices observationally indistinguishable.

Independent assortment of different chromosome pairs does not imply independence of every pair of genes. Nearby genetic loci on the same chromosome can show genetic linkage. Chromosomal crossover can create new haplotypes, but does not automatically erase genetic linkage. See Laws of Inheritance (§12.3, Law of Independent Assortment and Linked Genes Violate the Law of Independent Assortment). In the ordinary fair two-locus model with parental haplotypes $AB/ab$ and recombination fraction $r$,Thus $r=0$ gives only the two parental haplotypes, while $r=1/2$ gives four equal probabilities. A recombination fraction of $1/2$ alone does not establish that the genetic loci lie on different chromosomes.

A motivating experiment appears in Experiments in Plant Hybridization by Gregor Mendel (§9, “The Reproductive Cells of the Hybrids”). In peas, hybrids for round versus wrinkled seeds and yellow versus green seeds were crossed reciprocally with constant wrinkled-green plants. The readout was visible seed shape and color: hybrid seed parents gave 31 round-yellow, 26 round-green, 27 wrinkled-yellow and 26 wrinkled-green; the reciprocal cross gave 24, 25, 22 and 27.

The apparatus was controlled pollination: opening immature flowers, removing stamens with forceps, and applying selected pollen to the stigma. Two-year trials established constant parental characters; greenhouse pots checked interference from insects in outdoor beds. Reciprocal crosses tested both transmission directions. These procedures are described in Experiments in Plant Hybridization by Gregor Mendel (§§2–3).

With complete dominance at both genetic loci, this test cross makes each phenotype report one hybrid gamete combination. The ideal expected values are $110/4=27.5$ and $98/4=24.5$ per class. The observations support four transmitted combinations, approximately equally frequent. They do not directly image chromosome orientation or prove independence for all genes; failed development and seed germination also limit the inference, as §9 notes.