title: HpQTL: a geometric morphometric platform to compute the genetic architecture of heterophylly.
abstract: Heterophylly, i.e. morphological changes in leaves along the axis of an individual plant, is regarded as a strategy used by plants to cope with environmental change. However, little is known of the extent to which heterophylly is controlled by genes and how each underlying gene exerts its effect on heterophyllous variation. We described a geometric morphometric model that can quantify heterophylly in plants and further constructed an R-based computing platform by integrating this model into a genetic mapping and association setting. The platform, named HpQTL, allows specific quantitative trait loci mediating heterophyllous variation to be mapped throughout the genome. The statistical properties of HpQTL were examined and validated via computer simulation. Its biological relevance was demonstrated by results from a real data analysis of heterophylly in a wood plant, mei (Prunus mume). HpQTL provides a powerful tool to analyze heterophylly and its underlying genetic architecture in a quantitative manner. It also contributes a new approach for genome-wide association studies aimed to dissect the programmed regulation of plant development and evolution.
authors.affiliation: Key Laboratory of Ornamental Plants Germplasm Innovation and Molecular Breeding, National Engineering Research Center for Floriculture, Beijing Forestry University, Beijing, China.
authors.forename: Lidan
authors.initials: L
authors.lastname: Sun
authors.affiliation: Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.affiliation: Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
authors.forename: Xuli
authors.initials: X
authors.lastname: Zhu
authors.affiliation: Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
authors.forename: Libo
authors.initials: L
authors.lastname: Jiang
authors.affiliation: Statistical Genetics, Department of Public Health Sciences, Pennsylvania State University, Pennsylvania, USA.
authors.forename: Kirk
authors.initials: K
authors.lastname: Gosik
authors.affiliation: Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
authors.forename: Mengmeng
authors.initials: M
authors.lastname: Sang
authors.affiliation: Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
authors.forename: Fengsuo
authors.initials: F
authors.lastname: Sun
authors.affiliation: Ornamental Genetics, National Engineering Research, Center for Floriculture, Beijing Forestry University Beijing, China.
authors.forename: Tangren
authors.initials: T
authors.lastname: Cheng
authors.affiliation: Ornamental Genetics, National Engineering Research, Center for Floriculture, Beijing Forestry University Beijing, China.
authors.forename: Qixiang
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.|Center for Statistical Genetics, Pennsylvania State University, Pennsylvania, PA, USA.
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D003198:Computer Simulation; D004781:Environmental Exposure; D018515:Plant Leaves / Q000033:anatomy & histology / Q000235:genetics*; D010940:Plant Proteins / Q000235:genetics*; D027861:Prunus / Q000033:anatomy & histology* / Q000235:genetics*; D040641:Quantitative Trait Loci; D012984:Software
chemical_list: D010940:Plant Proteins