ArticlePloS one2007
A conceptual framework for mapping quantitative trait Loci regulating ontogenetic allometry.
Article in PloS one, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Pleiotropy Structures Plant Height and Seed Weight Scaling in Barley despite Long History of Domestication and Breeding Selection.Plant phenomics (Washington, D.C.) · 2023Article
- Genetic Association Analysis for Relative Growths of Body Compositions and Metabolic Traits to Body Weights in Broilers.Animals : an open access journal from MDPI · 2021Article
- A Bivariate Mapping Model Identifies Major Covariation QTLs for Biomass Allocation Between Leaf and Stem Growth ofFrontiers in genetics · 2021Article
- Article
- A Computational Model for Inferring QTL Control Networks Underlying Developmental Covariation.Frontiers in plant science · 2019Article
- Genome-wide random regression analysis for parent-of-origin effects of body composition allometries in mouse.Scientific reports · 2017Article
- Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection.PloS one · 2015Article
- Systems mapping: how to improve the genetic mapping of complex traits through design principles of biological systems.BMC systems biology · 2011Article
- Article
- A dynamic model for functional mapping of biological rhythms.Journal of biological dynamics · 2011Article
- Functional mapping of genotype-environment interactions for soybean growth by a semiparametric approach.Plant methods · 2010Article
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Authors and funding
7 authors.
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Abstract
Although ontogenetic changes in body shape and its associated allometry has been studied for over a century, essentially nothing is known about their underlying genetic and developmental mechanisms. One of the reasons for this ignorance is the unavailability of a conceptual framework to formulate the experimental design for data collection and statistical models for data analyses. We developed a framework model for unraveling the genetic machinery for ontogenetic changes of allometry. The model incorporates the mathematical aspects of ontogenetic growth and allometry into a maximum likelihood framework for quantitative trait locus (QTL) mapping. As a quantitative platform, the model allows for the testing of a number of biologically meaningful hypotheses to explore the pleiotropic basis of the QTL that regulate ontogeny and allometry. Simulation studies and real data analysis of a live example in soybean have been performed to investigate the statistical behavior of the model and validate its practical utilization. The statistical model proposed will help to study the genetic architecture of complex phenotypes and, therefore, gain better insights into the mechanistic regulation for developmental patterns and processes in organisms.
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