Quantitative genetics in the age of omics
Introduction
For most organisms, including plants, variation between individuals of the same species is observed in nature, which can partly be explained by genetic differences [1]. Natural variation among different genotypes (accessions, varieties, etc.) can be classified as qualitative or quantitative. Qualitative traits are characterized by distinct phenotypic classes and are often a result of differences at single genes. Such traits can relatively easily be dissected genetically because of their clear segregation pattern in the progeny of crosses. Quantitative traits, on the contrary, often display a more continuous variation in phenotypes because of a multiplicity of genes involved and a relatively large effect of environmental factors on the expression of the trait. Recombination of genes results in a large number of phenotypic classes, which cannot unambiguously be associated with genotypic classes [2] because various genes can contribute positively or negatively to a quantifiable trait. The complexity of quantitative traits is further enhanced by the presence of epistatic interactions and interactions between genes and the environment [3••].
Quantitative natural variation controls adaptive strategies of organisms to cope with biotic and abiotic influences and its understanding can provide insight into ecological mechanisms and the evolutionary history of plants [4]. Moreover, it is the basis of variation for many agronomic traits [5]. Arabidopsis thaliana has proven to be a very efficient model plant because of a number of biological properties and available genetic resources that make genetic and molecular analyses very efficient [6]. These advantages also make A. thaliana very suitable for the genetic analysis of natural variation [7]. Because of the growing impact of large-scale molecular detection techniques (collectively nicknamed ‘omics’ technologies) in the dissection of complex traits, we aim to present a brief overview of the key technological advances and some of the recent findings in the field with emphasis on A. thaliana.
Section snippets
Genetic analysis of natural variation in quantitative traits
Despite the complexity in genetic regulation of quantitative traits much progress has been made over the past decades in dissecting these traits using molecular markers. The increasing ease by which molecular markers can be generated [8] in combination with the application of sophisticated mapping methods [9•] has led to a strong interest in the use of natural variation for studying quantitative traits [10]. Specific advantages are associated with the study of multiple natural perturbations in
Genetical genomics: variation in genome sequence and expression
In A. thaliana as well as in other species, genome-wide analyses of genomic polymorphisms in a large collection of accessions have revealed extensive sequence variation [1, 14, 15, 16•]. Polymorphisms, when converted to molecular markers, are indispensable for (fine) mapping of quantitative traits in experimental populations. When surveyed in natural populations at high density, polymorphisms will enable high-resolution mapping through linkage disequilibrium [17]. The best marker, however, is
Genetic regulation of complementary omic traits
The impact of variation in gene expression on quantitative traits is now widely acknowledged and the use of high-throughput genomic analyses has become an important tool in genetic analyses of natural variation [31]. An important mechanism in controlling transcriptional activity is through epigenetic modulation of cis-regulatory elements by cytosine methylation. With the recent development of genome-wide detection techniques [32], comprehensive genetic analyses of variation in methylation are
Regulatory network construction
To functionally link the large data sets obtained in ‘omic’ experiments as an order of events that ultimately result in a specific phenotype, network construction provides a useful tool. Biological networks describe relationships between individual components of a biological process [48]. Such components can either be genes, proteins, metabolites, or a combination thereof (Figure 1). Depending on the data source, networks can be constructed in various ways but all aim at resolving the complex
Conclusions
The combination of genetic analyses and large-scale omic analyses in experimental mapping populations has shown to have great potential in unraveling meaningful biological regulatory networks. The dissection of the genetic architecture of quantitative traits will require multiparallel analyses of the different transducers of the biological information flow. The ultimate goal is to link genetic variation to phenotypic variation and the identification of the molecular pathway from
References and recommended reading
Papers of particular interest, published within the annual period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
We apologize to all colleagues whose relevant work we could not cite because of space limitations, and thank Linus van der Plas for critically reading the manuscript. We acknowledge support from the Netherlands Organization for Scientific Research, Program Genomics (050-10-029) and the Centre for Biosystems Genomics (CBSG, Netherlands Genomics Initiative).
References (72)
Genetic architecture of complex traits in plants
Curr Opin Plant Biol
(2007)Mapping and analysis of quantitative trait loci in experimental populations
Nat Rev Genet
(2002)- et al.
Global eQTL mapping reveals the complex genetic architecture of transcript-level variation in Arabidopsis
Genetics
(2007) Update on proteomics in Arabidopsis. Where do we go from here?
Plant Physiol
(2005)- et al.
Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry
Nat Protocol
(2007) - et al.
Network biology: understanding the cell's functional organization
Nat Rev Genet
(2004) - et al.
A functional genomics approach using metabolomics and in silico pathway analysis
Biotechnol Bioeng
(2002) - et al.
Linking metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways
PLoS Genet
(2007) - et al.
The metabolic signature related to high plant growth rate in Arabidopsis thaliana
Proc Natl Acad Sci U S A
(2007) - et al.
The pattern of polymorphism in Arabidopsis thaliana
PLoS Biol
(2005)
Epistasis and balanced polymorphism influencing complex trait variation
Nature
Genetic mechanisms and evolutionary significance of natural variation in Arabidopsis
Nature
Quantitative trait loci and the study of plant domestication
Genetica
Timeline: a fortunate choice: the history of Arabidopsis as a model plant
Nat Rev Genet
Naturally occurring genetic variation in Arabidopsis thaliana
Annu Rev Plant Physiol Plant Mol Biol
Genomics tools for QTL analysis and gene discovery
Curr Opin Plant Biol
Quantitative trait locus mapping in natural populations: progress, caveats and future directions
Mol Ecol
Quantitative trait loci in inbred lines
Improving plant breeding with exotic genetic libraries
Nat Rev Genet
Recombination and linkage disequilibrium in Arabidopsis thaliana
Nat Genet
Large-scale identification and analysis of genome-wide single-nucleotide polymorphisms for mapping in Arabidopsis thaliana
Genome Res
Genome-wide patterns of single-feature polymorphism in Arabidopsis thaliana
Proc Natl Acad Sci U S A
Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana
Science
The extent of linkage disequilibrium in Arabidopsis thaliana
Nat Genet
The impact of genomics on the study of natural variation in Arabidopsis
Plant Physiol
Contribution of transcriptional regulation to natural variations in Arabidopsis
Genome Biol
Genomic survey of gene expression diversity in Arabidopsis thaliana
Genetics
Genetic analysis of variation in gene expression in Arabidopsis thaliana
Genetics
High-density haplotyping with microarray-based expression and single feature polymorphism markers in Arabidopsis
Genome Res
Genetical genomics: the added value from segregation
Trends Genet
Genetic dissection of transcriptional regulation in budding yeast
Science
Genetics of gene expression surveyed in maize, mouse and man
Nature
Genetic regulation of gene expression during shoot development in Arabidopsis
Genetics
Genetic dissection of transcriptional regulation by cDNA-AFLP
Plant J
Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci
Proc Natl Acad Sci U S A
Genetics of global gene expression
Nat Rev Genet
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