Shape mapping: Genetic mapping meets geometric morphometrics

Wenhao Bo, Zhong Wang, Fang Xu, Guifang Fu, Yihan Sui, Weimiao Wu, Xuli Zhu, Danni Yin, Qin Yan, Rongling Wu

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Knowledge about biological shape has important implications in biology and biomedicine, but the underlying genetic mechanisms for shape variation have not been well studied. Statistical models play a pivotal role in mapping specific quantitative trait loci (QTLs) that contribute to biological shape and its developmental trajectories. We describe and assess a statistical framework for shape gene identification that incorporates shape and image analysis into a mixture-model framework for QTL mapping. Statistical parameters that define genotype-specific differences in biological shape are estimated by implementing statistical and computational algorithms. A state-of-the-art procedure is described to examine the control patterns of specific QTLs on the origin, properties and functions of biological shape. The statistical framework described will help to address many integrative biological and genetic questions and challenges in shape variation faced by the life sciences community.

Original languageEnglish (US)
Article numberbbt008
Pages (from-to)571-581
Number of pages11
JournalBriefings in bioinformatics
Volume15
Issue number4
DOIs
StatePublished - Jul 2014

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology

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    Bo, W., Wang, Z., Xu, F., Fu, G., Sui, Y., Wu, W., Zhu, X., Yin, D., Yan, Q., & Wu, R. (2014). Shape mapping: Genetic mapping meets geometric morphometrics. Briefings in bioinformatics, 15(4), 571-581. [bbt008]. https://doi.org/10.1093/bib/bbt008