Medical genetics was revolutionized during the 1980s by the application of genetic mapping to locate the genes responsible for simple Mendelian diseases. Most diseases and traits, however, do not follow simple inheritance patterns. Geneticists have thus begun taking up the even greater challenge of the genetic dissection of complex traits. Four major approaches have been developed: linkage analysis, allele-sharing methods, association studies, and polygenic analysis of experimental crosses. This article synthesizes the current state of the genetic dissection of complex traits—describing the methods, limitations, and recent applications to biological problems.

Genetic Dissection of Complex Traits

Crop domestications are long-term selection experiments that have greatly advanced human civilization. The domestication of cultivated rice (Oryza sativa L.) ranks as one of the most important developments in history. However, its origins and domestication processes are controversial and have long been debated. Here we generate genome sequences from 446 geographically diverse accessions of the wild rice species Oryza rufipogon, the immediate ancestral progenitor of cultivated rice, and from 1,083 cultivated indica and japonica varieties to construct a comprehensive map of rice genome variation. In the search for signatures of selection, we identify 55 selective sweeps that have occurred during domestication. In-depth analyses of the domestication sweeps and genome-wide patterns reveal that Oryza sativa japonica rice was first domesticated from a specific population of O. rufipogon around the middle area of the Pearl River in southern China, and that Oryza sativa indica rice was subsequently developed from crosses between japonica rice and local wild rice as the initial cultivars spread into South East and South Asia. The domestication-associated traits are analysed through high-resolution genetic mapping. This study provides an important resource for rice breeding and an effective genomics approach for crop domestication research.

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A map of rice genome variation reveals the origin of cultivated rice

In this review, recent developments and future prospects of obtaining a better understanding of the regulation of nitrogen use efficiency in the main crop species cultivated in the world are presented. In these crops, an increased knowledge of the regulatory mechanisms controlling plant nitrogen economy is vital for improving nitrogen use efficiency and for reducing excessive input of fertilizers, while maintaining an acceptable yield. Using plants grown under agronomic conditions at low and high nitrogen fertilization regimes, it is now possible to develop whole-plant physiological studies combined with gene, protein, and metabolite profiling to build up a comprehensive picture depicting the different steps of nitrogen uptake, assimilation, and recycling to the final deposition in the seed. A critical overview is provided on how understanding of the physiological and molecular controls of N assimilation under varying environmental conditions in crops has been improved through the use of combined approaches, mainly based on whole-plant physiology, quantitative genetics, and forward and reverse genetics approaches. Current knowledge and prospects for future agronomic development and application for breeding crops adapted to lower fertilizer input are explored, taking into account the world economic and environmental constraints in the next century.

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The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches

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.

The genetics of quantitative traits: challenges and prospects.

■ Abstract Phenotypic variation for quantitative traits results from the segregation of alleles at multiple quantitative trait loci (QTL) with effects that are sensitive to the genetic, sexual, and external environments. Major challenges for biology in the post-genome era are to map the molecular polymorphisms responsible for variation in medically, agriculturally, and evolutionarily important complex traits; and to determine their gene frequencies and their homozygous, heterozygous, epistatic, and pleiotropic effects in multiple environments. The ease with which QTL can be mapped to genomic intervals bounded by molecular markers belies the difficulty in matching the QTL to a genetic locus. The latter requires high-resolution recombination or linkage disequilibrium mapping to nominate putative candidate genes, followed by genetic and/or functional complementation and gene expression analyses. Complete genome sequences and improved technologies for polymorphism detection will greatly advance the genetic dissection of quantitative traits in model organisms, which will open avenues for exploration of homologous QTL in related taxa.

The genetic architecture of quantitative traits

Windows QTL Cartographer 2·5

WINDOWS QTL Cartographer

Understanding and estimating the structure and parameters associated with the genetic architecture of quantitative traits is a major research focus in quantitative genetics. With the availability of a well-saturated genetic map of molecular markers, it is possible to identify a major part of the structure of the genetic architecture of quantitative traits and to estimate the associated parameters. Multiple interval mapping, which was recently proposed for simultaneously mapping multiple quantitative trait loci (QTL), is well suited to the identification and estimation of the genetic architecture parameters, including the number, genomic positions, effects and interactions of significant QTL and their contribution to the genetic variance. With multiple traits and multiple environments involved in a QTL mapping experiment, pleiotropic effects and QTL by environment interactions can also be estimated. We review the method and discuss issues associated with multiple interval mapping, such as likelihood analysis, model selection, stopping rules and parameter estimation. The potential power and advantages of the method for mapping multiple QTL and estimating the genetic architecture are discussed. We also point out potential problems and difficulties in resolving the details of the genetic architecture as well as other areas that require further investigation. One application of the analysis is to improve genome-wide marker-assisted selection, particularly when the information about epistasis is used for selection with mating.

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Estimating the genetic architecture of quantitative traits.

Evolutionary biologists seek to understand the genetic basis for multivariate phenotypic divergence. We constructed an F2 mapping population (N = 539) between two distinct populations of Mimulus guttatus. We measured 20 floral, vegetative, and life-history characters on parents and F1 and F2 hybrids in a common garden experiment. We employed multitrait composite interval mapping to determine the number, effect, and degree of pleiotropy in quantitative trait loci (QTL) affecting divergence in floral, vegetative, and life-history characters. We detected 16 QTL affecting floral traits; 7 affecting vegetative traits; and 5 affecting selected floral, vegetative, and life-history traits. Floral and vegetative traits are clearly polygenic. We detected a few major QTL, with all remaining QTL of small effect. Most detected QTL are pleiotropic, implying that the evolutionary shift between these annual and perennial populations is constrained. We also compared the genetic architecture controlling floral trait divergence both within (our intraspecific study) and between species, on the basis of a previously published analysis of M. guttatus and M. nasutus. Eleven of our 16 floral QTL map to approximately the same location in the interspecific map based on shared, collinear markers, implying that there may be a shared genetic basis for floral divergence within and among species of Mimulus.

https://www.genetics.org/content/genetics/172/3/1829.full.pdf

Pleiotropic Quantitative Trait Loci Contribute to Population Divergence in Traits Associated With Life-History Variation in Mimulus guttatus

Key message
Impacts of population structure on the evaluation of genomic heritability and prediction were investigated and quantified using high-density markers in diverse panels in rice and maize.

Christopher J. Basten

Papers

Windows QTL Cartographer 2·5

WINDOWS QTL Cartographer

Estimating the genetic architecture of quantitative traits.

Pleiotropic Quantitative Trait Loci Contribute to Population Divergence in Traits Associated With Life-History Variation in Mimulus guttatus

The impact of population structure on genomic prediction in stratified populations