Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data

Zitong Li; Mikko J Sillanpää

doi:10.1016/j.tplants.2015.08.012

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data

Trends Plant Sci. 2015 Dec;20(12):822-833. doi: 10.1016/j.tplants.2015.08.012. Epub 2015 Oct 5.

Authors

Zitong Li¹, Mikko J Sillanpää²

Affiliations

¹ Biocenter Oulu, Oulu, Finland; Department of Mathematical Sciences and Department of Biology, University of Oulu, 90014 Oulu, Finland.
² Biocenter Oulu, Oulu, Finland; Department of Mathematical Sciences and Department of Biology, University of Oulu, 90014 Oulu, Finland. Electronic address: Mikko.Sillanpaa@oulu.fi.

PMID: 26482958
DOI: 10.1016/j.tplants.2015.08.012

Abstract

Advanced platforms have recently become available for automatic and systematic quantification of plant growth and development. These new techniques can efficiently produce multiple measurements of phenotypes over time, and introduce time as an extra dimension to quantitative trait locus (QTL) studies. Functional mapping utilizes a class of statistical models for identifying QTLs associated with the growth characteristics of interest. A major benefit of functional mapping is that it integrates information over multiple timepoints, and therefore could increase the statistical power for QTL detection. We review the current development of computationally efficient functional mapping methods which provide invaluable tools for analyzing large-scale timecourse data that are readily available in our post-genome era.

Keywords: functional mapping; high-throughput phenotyping; multiple-locus method; plant growth and development; quantitative trait loci; timecourse.

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Chromosome Mapping / methods
Genomics / methods*
High-Throughput Screening Assays / methods
Models, Genetic
Phenotype
Plant Development / genetics*
Plants / genetics*
Polymorphism, Single Nucleotide
Quantitative Trait Loci*