Key Points
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Most phenotypic variation in natural populations is attributable to multiple interacting loci, with allelic effects that are sensitive to the exact environmental conditions each individual experiences. The underlying quantitative trait loci (QTLs) can be mapped by linkage to polymorphic marker loci with clear Mendelian segregation such as molecular polymorphisms.
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QTLs can be mapped in families or segregating progeny of crosses between genetically divergent strains (linkage mapping) or in unrelated individuals from the same population (association mapping). In both cases, large numbers of individuals are needed to detect and localize QTLs; the number of individuals and genotypes per individual needed increases as the QTL effect size decreases and the precision of localization increases.
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Positional cloning is the gold standard of identifying genes that correspond to QTLs. Corroborating evidence that a gene causes the variation in the trait of interest includes replication in independent studies, identifying potentially functional DNA polymorphisms between alternative alleles of one of the candidate genes, showing a difference in mRNA expression levels between genotypes, showing that mRNA or protein is expressed in tissues that are thought to be relevant to the trait, and showing that mutations in candidate genes affect the trait or fail to complement QTL alleles.
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Results of QTL mapping efforts in many species over the past 20 years have showed that there are key common features of the genetic architecture of quantitative traits: many loci with small effects are responsible for most quantitative genetic variation, these loci are often unexpected based on prior knowledge of the trait or correspond to computationally predicted genes; the effects of QTL alleles are highly context-dependent and vary depending on genetic background, environment and sex; and pleiotropic QTL effects are widespread.
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Despite 20 years of intensive effort, we have fallen short of our long-term goal of explaining genetic variation for quantitative traits in terms of the underlying genes, the effects of segregating alleles in different genetic backgrounds and in a range of ecologically relevant environments, as well as their effects on other traits, the molecular basis of functional allelic effects and the population frequency of causal variants. The challenge of dissecting quantitative traits into individual genes and their causal molecular polymorphisms will be solved in the near future by applying new sequencing and genotyping technologies to the problem, in combination with new community resources.
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Understanding the biological context in which molecular polymorphisms elicit their effects on trait variation requires knowledge of the effects of the polymorphisms on complex networks of transcriptional, protein, metabolic and other molecular endophenotypes that lead to the organismal phenotype. This is the province of the emerging discipline of systems genetics.
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Systems genetics integrates DNA sequence variation, variation in transcript abundance and other molecular phenotypes, and variation in organismal phenotypes in a linkage or association mapping population and enables us to interpret quantitative genetic variation in terms of biologically meaningful causal networks of correlated transcripts. The association of molecular variation with organismal phenotypes identifies QTLs, the association of molecular variation with gene expression traits identifies expression QTLs and correlations between gene expression and organismal level phenotypes identify quantitative trait transcripts.
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Levels of expression of many transcripts covary between individuals in a mapping population; the correlated transcripts can be grouped statistically into modules, in which each module consists of transcripts with higher correlations to each other than to the rest of the transcriptome. The correlations between transcripts in a module can be visualized graphically as a network with nodes denoting transcripts and edges connecting nodes that are genetically correlated. Causal biological networks can be derived from coexpression transcriptional networks that are also correlated with the phenotype of an organism, using the statistical concept of conditional dependence. The statistical definition of the molecular interactions that govern phenotypic variation through natural genetic perturbations is a testable hypothesis that can be validated and refined by functional studies.
Abstract
A major challenge in current biology is to understand the genetic basis of variation for quantitative traits. We review the principles of quantitative trait locus mapping and summarize insights about the genetic architecture of quantitative traits that have been obtained over the past decades. We are currently in the midst of a genomic revolution, which enables us to incorporate genetic variation in transcript abundance and other intermediate molecular phenotypes into a quantitative trait locus mapping framework. This systems genetics approach enables us to understand the biology inside the 'black box' that lies between genotype and phenotype in terms of causal networks of interacting genes.
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Acknowledgements
This work was supported by National Institutes of Health grants GM45146, GM076083 and AA016560.
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Technologies enabling systems genetics (XLS 681 kb)
Glossary
- Quantitative trait locus
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A region of the genome containing one or more genes that affect variation in a quantitative trait, which is identified by its linkage to polymorphic marker loci.
- Linkage disequilibrium
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(LD). The correlation (non-random association) of alleles at two or more polymorphic loci. Alleles that are in LD co-occur in individuals more often than the random expectation from the product of their allele frequencies in the population.
- Epistasis
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This occurs when the homozygous or heterozygous effects at one locus differ depending on the genotype of the interacting locus.
- Genotype-by-environment interaction
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This occurs when the homozygous and heterozygous effects of a locus change in magnitude or direction in different environments.
- Quantitative trait nucleotide
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A causal molecular variant (allele) that affects variation in a quantitative trait.
- Endophenotype
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An intermediate molecular phenotype associated with an organismal level quantitative trait. Variation in the endophenotype affects variation in the organismal trait.
- Expression quantitative trait locus
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A region of the genome containing one or more genes that affect variation in gene expression, which is identified by linkage to polymorphic marker loci.
- Quantitative trait transcript
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A transcript for which variation in its expression is correlated with variation in an organismal level quantitative trait phenotype.
- Gene ontology
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A widely used classification system of gene functions and other gene attributes that uses a controlled vocabulary.
- KEGG pathway
-
The Kyoto Encyclopedia of Genes and Genomes (KEGG) is a database comprising a collection of graphical pathway maps for metabolism, regulatory processes and other biological processes.
- Bayesian network
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A graph with directed edges that connect nodes. The nodes represent assertions about relationships between the nodes; for example, a node A is related to a node B by an edge that represents that A is a cause of B with a certain probability. Bayesian networks with many interconnected nodes can be constructed.
- Partial correlation analysis
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This quantifies the association between a pair of variables after controlling for the effect of a set of potential confounders.
- Empirical Bayes procedure
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A hierarchical model in which the hyperparameter is not a random variable but is estimated by some other (often classical) means.
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Mackay, T., Stone, E. & Ayroles, J. The genetics of quantitative traits: challenges and prospects. Nat Rev Genet 10, 565–577 (2009). https://doi.org/10.1038/nrg2612
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DOI: https://doi.org/10.1038/nrg2612
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