PoplarV1, Main, Exploration, bibRecord, 000D92

Mapping morphological shape as a high-dimensional functional curve.

Identifieur interne : 000D92 ( Main/Exploration ); précédent : 000D91; suivant : 000D93

Mapping morphological shape as a high-dimensional functional curve.

Auteurs : Guifang Fu ; Mian Huang ; Wenhao Bo ; Han Hao [États-Unis] ; Rongling Wu [États-Unis]

Source :

Briefings in bioinformatics [ 1477-4054 ] ; 2018.

RBID : pubmed:28062411

Descripteurs français

KwdFr :
- Cartographie chromosomique (méthodes), Chromosomes de plante (MeSH), Feuilles de plante (anatomie et histologie), Feuilles de plante (génétique), Gènes de plante (MeSH), Locus de caractère quantitatif (MeSH), Modèles statistiques (MeSH), Phénotype (MeSH), Populus (anatomie et histologie), Populus (génétique), Simulation numérique (MeSH).
MESH :
- anatomie et histologie : Feuilles de plante, Populus.
- génétique : Feuilles de plante, Populus.
- méthodes : Cartographie chromosomique.
- Chromosomes de plante, Gènes de plante, Locus de caractère quantitatif, Modèles statistiques, Phénotype, Simulation numérique.

English descriptors

KwdEn :
- Chromosome Mapping (methods), Chromosomes, Plant (MeSH), Computer Simulation (MeSH), Genes, Plant (MeSH), Models, Statistical (MeSH), Phenotype (MeSH), Plant Leaves (anatomy & histology), Plant Leaves (genetics), Populus (anatomy & histology), Populus (genetics), Quantitative Trait Loci (MeSH).
MESH :
- anatomy & histology : Plant Leaves, Populus.
- genetics : Plant Leaves, Populus.
- methods : Chromosome Mapping.
- Chromosomes, Plant, Computer Simulation, Genes, Plant, Models, Statistical, Phenotype, Quantitative Trait Loci.

Abstract

Detecting how genes regulate biological shape has become a multidisciplinary research interest because of its wide application in many disciplines. Despite its fundamental importance, the challenges of accurately extracting information from an image, statistically modeling the high-dimensional shape and meticulously locating shape quantitative trait loci (QTL) affect the progress of this research. In this article, we propose a novel integrated framework that incorporates shape analysis, statistical curve modeling and genetic mapping to detect significant QTLs regulating variation of biological shape traits. After quantifying morphological shape via a radius centroid contour approach, each shape, as a phenotype, was characterized as a high-dimensional curve, varying as angle θ runs clockwise with the first point starting from angle zero. We then modeled the dynamic trajectories of three mean curves and variation patterns as functions of θ. Our framework led to the detection of a few significant QTLs regulating the variation of leaf shape collected from a natural population of poplar, Populus szechuanica var tibetica. This population, distributed at altitudes 2000-4500 m above sea level, is an evolutionarily important plant species. This is the first work in the quantitative genetic shape mapping area that emphasizes a sense of 'function' instead of decomposing the shape into a few discrete principal components, as the majority of shape studies do.

DOI: 10.1093/bib/bbw111
PubMed: 28062411
PubMed Central: PMC5952977

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Main, to step Corpus: 001490
to stream Main, to step Curation: 001490

Le document en format XML

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<front><div type="abstract" xml:lang="en">Detecting how genes regulate biological shape has become a multidisciplinary research interest because of its wide application in many disciplines. Despite its fundamental importance, the challenges of accurately extracting information from an image, statistically modeling the high-dimensional shape and meticulously locating shape quantitative trait loci (QTL) affect the progress of this research. In this article, we propose a novel integrated framework that incorporates shape analysis, statistical curve modeling and genetic mapping to detect significant QTLs regulating variation of biological shape traits. After quantifying morphological shape via a radius centroid contour approach, each shape, as a phenotype, was characterized as a high-dimensional curve, varying as angle θ runs clockwise with the first point starting from angle zero. We then modeled the dynamic trajectories of three mean curves and variation patterns as functions of θ. Our framework led to the detection of a few significant QTLs regulating the variation of leaf shape collected from a natural population of poplar, Populus szechuanica var tibetica. This population, distributed at altitudes 2000-4500 m above sea level, is an evolutionarily important plant species. This is the first work in the quantitative genetic shape mapping area that emphasizes a sense of 'function' instead of decomposing the shape into a few discrete principal components, as the majority of shape studies do.</div>
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Mapping morphological shape as a high-dimensional functional curve.

Mapping morphological shape as a high-dimensional functional curve.

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