Selection and Complex Multigene Traits

Esteban R Hasson, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
Juan José Fanara, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
Nicolás Frankel, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina

Published online: May 2013

DOI: 10.1002/9780470015902.a0002295

Abstract

Phenotypic characters that display continuous variation are usually called ‘quantitative traits’ or ‘complex traits’. Alternatively, geneticists refer to them as ‘multigene traits’, because the underlying genetic architecture is assumed to be polygenic. Analyses of the genetic architecture of diverse quantitative traits suggest that the number of loci (quantitative trait loci, QTLs) affecting trait variation can be very different. Moreover, experimental studies report contrasting genetic architectures, where either large‐effect QTLs or small‐effect QTLs explain most of the phenotypic variation. In addition, recent reports highlight the pervasiveness of epistasis. Considerable evidence, obtained with the QST–FST methodology, supports the idea that natural selection plays a key role in the evolution of complex traits. Nevertheless, the identification of a representative number of genes underlying QTLs is necessary to determine the contribution of selection, drift and gene flow for the evolution of complex traits.

Key Concepts:

  • The phenotypic variation in complex traits is usually determined by multiple genes.

  • Understanding the genetic architecture of complex traits begins with the identification and characterisation of quantitative trait loci (QTLs).

  • The search for the genes that harbour naturally segregating variation affecting quantitative traits is commonly performed through linkage QTL mapping.

  • An analysis of the genetic architecture of different characters suggests that the number of QTLs contributing to a trait can be very different.

  • Researchers aim to discover the genes (QTGs) and nucleotides (QTNs) underlying QTL effects.

  • The comparison of the statistics of QST and FST is one of the most popular methods employed to search for the signature of natural selection on quantitative traits.

  • Considerable evidence supports the idea that natural selection is a key player in the evolution of complex traits.

  • The identification of a representative number of QTGs is necessary to determine the contributions of selection, drift and gene flow for the evolution of complex traits.

Keywords: selection; drift; complex traits; genetic architecture; QTL mapping; QST; FST

Figure 1.

Types of phenotypic characters. Some phenotypic characters can be grouped into discrete categories. For example, plumage colour in a population of birds. (a) The size of the bar represents the number of individuals that have that character state in the population. In contrast, other characters (such as height) exhibit continuous variation, and individual values have to be assigned to arbitrary bins in a histogram. (b) These characters usually follow a normal distribution.
Figure 2.

Quantitative trait locus mapping. (a) Two inbred parental lines (P1 and P2) are crossed to produce the F1 generation. Blue/red bars represent a pair of homologous chromosomes. Triangles indicate molecular markers specific for each parental line. F1 individuals can be crossed to P1 and/or P2 to generate a backcross (BC) mapping population or to each other to generate an F2 mapping population. Recombinant inbred lines (RILs) are generated by performing full‐sibling matings for many generations. (b) Identification of QTLs by linkage. Triangles on the x‐axis denote the locations of molecular markers. The likelihood ratio (y‐axis) is the quotient of the likelihood of two contrasting hypotheses: (H1) a QTL is linked to a specific marker and (H0) there is no QTL linked to that specific marker. The horizontal dotted line is the significance threshold for the likelihood ratio based on permutation tests. Genomic regions with markers above this line contain putative QTLs. The most likely location of a QTL is the position on the x‐axis associated with the highest likelihood value. For a detailed explanation of the likelihood ratio test and permutation tests see Lynch and Walsh .
Figure 3.

The workflow of the QST–FST method, illustrated with fly populations. The first step involves the capture of wild flies. The progenies of wild inseminated females are bred in controlled laboratory conditions. Wild caught females are genotyped to obtain measures of genetic differentiation within and between populations (FST) and the lab‐raised progeny is analysed for a particular trait (or set of traits). In this case, wing size is measured to obtain within and between population variances. These values represent within and between population additive genetic variances. QST is calculated with these values. Finally, the evolutionary forces acting on a trait (or suite of traits) may be inferred on the basis of the results of the comparison between QST and FST.
Figure 4.

Experimental studies show that QST is higher than FST for most cases. Data points (black diamonds) are QST–FST values obtained for single traits or averaged across several traits. The red line marks the neutral expectation (QST=FST). Empirical data from Rogell et al. , Chun et al. , Leinonen et al. , Richter‐Boix et al. , Santure et al. and Volis and Zhang were used to construct the graph.
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Related Sub-Topics:

Evolutionary Processes | Quantitative Genetics | Molecular Evolution | Selection and Variation
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Article Title: Selection and Complex Multigene Traits
 
How to Cite close
Hasson, Esteban R, Fanara, Juan José, and Frankel, Nicolás(May 2013) Selection and Complex Multigene Traits. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0002295]