Plant Quantitative Traits


In plants, most of the phenotypic variations are continuously distributed and could be considered as quantitative traits. The complexity of their genetic control is high because the involved genes are numerous, with usually minor effects and very sensitive to environment. The implicated loci are localised by two basic approaches, linkage mapping and association mapping, based on the use of genetic maps and sophisticated statistical analysis. Linkage mapping leads to the identification of small regions of genome but that could contain still several hundred genes. Identification of gene underlying the quantitative trait loci requires positional cloning or direct tests of promising candidates. Association mapping checks directly the relationship between each polymorphism and phenotypic trait variation in wild populations, but physical linkage and population structure are sources of false positives. Finally, validation that an individual gene is responsible for the quantitative trait needs to be performed by using genetic or functional complementation.

Key Concepts:

  • Quantitative traits follow continuous, unbroken quasi‐normal distributions whereas qualitative (mendelian) traits are discreetly distributed.

  • Quantitative traits are controlled by several genes, with small additive, dominant or epistatic effects, and in interaction with the environment.

  • A quantitative trait loci (QTL) is defined as an area of genome associated with an effect on a quantitative trait.

  • The combination of alleles at the many genes involved in a quantitative trait leads to constitute the different phenotypes.

  • QTL mapping relies on statistical linkage analysis among quantitative trait and genetic markers using a population that carries combinations of alleles derived from parental lines.

  • Association mapping looks for association between a genetic marker and phenotype in unrelated individuals by exploiting historical recombination events and genetic diversity.

  • Population structure is the presence of hidden subgroups in wild populations that appear because of relatedness and selection with an unequal distribution of alleles.

  • Physical linkage and population structure are sources of linkage disequilibrium and might influence the genome‐wide association (GWA) mapping by creation of false marker‐trait association.

  • Positional cloning of QTL involves the identification of closely linked recombination events requiring analysis of a large number of segregating progeny with molecular markers covering the critical region.

  • Complete genome sequencing has greatly advanced the use of GWA mapping.

Keywords: natural variation; core‐collection; epistasis; linkage disequilibrium; QTL; GWA

Figure 1.

Natural variation in Arabidopsis thaliana. (a) Seed colour and seed size variation. (b) Inflorescence architecture variation. (c) Leaf shape and rosette size variation.

Figure 2.

(a) Frequency distribution of stem colour in Nicotiana rustica, a qualitative trait evaluated by classification rather than by measurement. (b) Frequency distribution of wheat biomass showing the bell‐shaped or normal distribution typical of quantitative traits.

Figure 3.

Difference between additive, dominant and epistatic gene actions. (a) Additive gene action. Trait values of genotypes depend of alleles A1 and A2 at one locus A. The heterozygous genotype A1A2 has an average phenotypic value of the two homozygous genotypes A1A1 and A2A2. (b) Dominance gene action. The trait value of heterozygous genotype A1A2 deviates from the mean. Dominance effect is equal to this deviation d. (c) Epistatic gene action. Allelic effect at the locus A depends on the alleles at the locus B. If the alleles B1 are fixed at locus B, then the allele A2 has an additive effect at locus A on the trait. If the alleles B2 are fixed at locus B, then the allele A2 has no effect.

Figure 4.

Principle of QTL detection by linkage analysis. (a) Preparation of mapping population. Two parental lines (white P1 and black P2) are used to create a RIL population. Segments derived from parental chromosome are represented by white and black boxes. RIL population is obtained by six generations of single seed descent from the F2 population. As a consequence, the genetic background of RIL is almost completely homozygous. (b) RILs are genotyped with markers covering all chromosomes and scored for trait of interest (deficient – or performing+lines). Statistical combination of genotypes with phenotypes leads to draw the LOD score curve among the chromosome providing an estimation of the QTL presence. When the LOD score exceeds a threshold (blue hashed line), a QTL is localised.

Figure 5.

Principle of association mapping with tomato fruit size. During species history, many recombination events have been appeared to make the current haplotypes from a few ancestral lines. Genotype of present day lines is investigated by using genetic markers (SNP1, SNP2 and SNP3), whereas their phenotypic performance (fruit size) is scored. Correlation between genetic markers and phenotype among collections of diverse germplasm tests association and leads to map locus closed to SNP2 involved in the trait variation with two positive (+) and one negative (−) alleles.



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Further Reading

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Wu R, Ma CX and George Casella G (2007) Statistical Genetics of Quantitative Traits: Linkage, Maps, And QTL. New York: Springer Science.

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Ikram, Sobia, and Chardon, Fabien(Dec 2010) Plant Quantitative Traits. In: eLS. John Wiley & Sons Ltd, Chichester. [doi: 10.1002/9780470015902.a0002021.pub2]