Functional mapping — how to map and study the genetic architecture of dynamic complex traits

Wu, Rongling; Lin, Min

doi:10.1038/nrg1804

Cited by 306 publications

(302 citation statements)

References 74 publications

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“…Conversely, impairment of these buffering factors through pathology may be detectable as an increase in the variance seen in developing structures. Recent advances in statistical methodologies such as functional mapping (Wu & Lin 2006), which are designed to describe the genetic architecture of quantitative traits over development, show promise for disentangling these factors.…”

Section: Discussionmentioning

confidence: 99%

Trajectories of Anatomic Brain Development as a Phenotype

Giedd

Lenroot²,

Shaw³

et al. 2008

Novartis Foundation Symposia

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Many cognitive, emotional and behavioural traits, as well as psychiatric disorders are highly heritable. However, identifying the specific genes and mechanisms by which this heritability manifests has been elusive. One approach to make this problem more tractable has been to attempt to identify and quantify biological markers that are intermediate steps along the gene-to-behaviour path. The field of neuroimaging offers several anatomic and physiologic possibilities to quantify. Stability over time has been proposed as a desired feature for these intermediate phenotypes.However, in this paper we discuss the value of looking at trajectories of anatomic brain development (i.e. morphometric changes over time), as opposed to static measures, as a phenotype. Examples drawn from longitudinal anatomic magnetic resonance imaging studies of typical development, attention deficit/hyperactivity disorder, and childhood-onset schizophrenia are used to demonstrate the utility of trajectories of brain development as a phenotypic bridge between genes and behaviour in health and in illness.

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Section: Discussionmentioning

confidence: 99%

Trajectories of Anatomic Brain Development as a Phenotype

Giedd

Lenroot²,

Shaw³

et al. 2008

Novartis Foundation Symposia

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“…Gene expression analyses may also be used to identify genes in the region that are differentially expressed depending upon magnitude of the behavioral trait. For additional information and issues regarding the search for quantitative genes, several papers are available at every level of complexity (e.g., Belknap et al, 2001;Nadeau and Frankel, 2000;Phillips et al, 2002a;Willis-Owen and Flint, 2007;Wu and Lin, 2006). Table 1 summarizes the existing QTL mapping data for amphetamine-related behavioral and thermal traits.…”

Section: Gene Mappingmentioning

confidence: 99%

Behavioral genetic contributions to the study of addiction-related amphetamine effects

Phillips

Kamens

Wheeler

2008

Neuroscience & Biobehavioral Reviews

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Amphetamines, including methamphetamine, pose a significant cost to society due to significant numbers of amphetamine-abusing individuals who suffer major health-related consequences. In addition, methamphetamine use is associated with heightened rates of violent and property-related crimes. The current paper reviews the existing literature addressing genetic differences in mice that impact behavioral responses thought to be relevant to the abuse of amphetamine and amphetaminelike drugs. Summarized are studies that used inbred strains, selected lines, single gene knockouts and transgenics, and quantitative trait locus (QTL) mapping populations. Acute sensitivity, neuroadaptive responses, rewarding and conditioned effects are among those reviewed. Some gene mapping work has been accomplished, and although no amphetamine-related complex trait genes have been definitively identified, translational work leading from results in the mouse to studies performed in humans is beginning to emerge. The majority of genetic investigations has utilized single-gene knockout mice and has concentrated on dopamine-and glutamate-related genes. Genes that code for cell support and signaling molecules are also well-represented. There is a large behavioral genetic literature on responsiveness to amphetamines, but a considerably smaller literature focused on genes that influence the development and acceleration of amphetamine use, withdrawal, relapse, and behavioral toxicity. Also missing are genetic investigations into the effects of amphetamines on social behaviors. This information might help to identify at-risk individuals and in the future to develop treatments that take advantage of individualized genetic information.

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“…Zhu (1995) presented a genetic model to understand the genetic expression of the development of quantitative traits and dynamic mapping at different stages. In this study, we analyzed seed development and formation in different stages using this genetic model, although a functional mapping approach based on a logistic-mixture model, implemented with the EM algorithm, was developed to provide the estimates of QTL positions, QTL effects, and other model parameters responsible for growth trajectories (Ma et al, 2002;Wu and Lin, 2006). Wang and Wu (2004) extended the use of functional mapping to the LD (linkage disequilibrium)-based identification of host QTL from a natural population, indicating a broad application of this methodology in both natural and cross population.…”

Section: Introductionmentioning

confidence: 99%

QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.)

Teng

Han

et al. 2008

Heredity

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At harvest traits such as seed weight are the sum of development and responses to stresses over the growing season and particularly during the reproductive phase of growth. The aim here was to measure quantitative trait loci (QTL) underlying the seed weight from early development to drying post harvest. One hundred forty-three F 5 derived recombinant inbred lines (RILs) developed from the cross of soybean cultivars 'Charleston' and 'Dongnong 594' were used for the analysis of QTL underlying mean 100-seed weight at six different developmental stages. QTL Â Environment interactions (QE) were analyzed by a mixed genetic mode based on 3 years' data. At an experiment-wise threshold of a ¼ 0.05 and by single-point analysis 94 QTL unaffected by QE underlay the mean seed weight at different developmental stages. Sixty-eight QTL affected by QE that also underlay mean seed weight were identified. From the 162 QTL 42 could be located on 12 linkage groups by composite interval mapping (LOD42.0). The numbers, locations and types of the QTL and the genetic effects were different at each developmental stage. On linkage group C2 the distantly linked QTL swC2-1, swC2-2 and swC2-3 each affected mean seed weight throughout the different developmental stages. The DNA markers linked to the QTL possessed potential for use in marker-assisted selection for soybean seed size. The identification of QTL with genetic main effects and QE interaction effects suggested that such interactions might significantly alter seed weight during seed development.

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Functional mapping — how to map and study the genetic architecture of dynamic complex traits

Cited by 306 publications

References 74 publications

Trajectories of Anatomic Brain Development as a Phenotype

Trajectories of Anatomic Brain Development as a Phenotype

Behavioral genetic contributions to the study of addiction-related amphetamine effects

QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.)

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