Structural mapping: How to study the genetic architecture of a phenotypic trait through its formation mechanism

Chunfa Tong, Lianying Shen, Yafei Lv, Zhong Wang, Xiaoling Wang, Sisi Feng, Xin Li, Yihan Sui, Xiaoming Pang, Rongling Wu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Traditional approaches for genetic mapping are to simply associate the genotypes of a quantitative trait locus (QTL) with the phenotypic variation of a complex trait. Amoremechanistic strategy has emerged to dissect the traitphenotype into its structural components andmap specific QTLs that control themechanistic and structural formation of a complex trait.We describe and assess such a strategy, called structuralmapping, by integrating the internal structural basis of trait formationinto aQTLmapping framework.Electrical impedance spectroscopy (EIS) hasbeeninstrumental for describing the structural components of a phenotypic trait and their interactions.By building robustmathematical models on circuit EIS data and embedding these models within a mixture model-based likelihood for QTL mapping, structuralmapping implements the EM algorithm to obtain maximum likelihood estimates of QTL genotype-specific EIS parameters.The uniqueness of structuralmapping is tomake it possible to test a number of hypotheses about the pattern of the genetic control of structural components.We validated structuralmapping by analyzing an EIS data collected forQTLmapping of frost hardiness in a controlled cross of jujube trees.The statistical properties of parameter estimates were examined by simulation studies. Structuralmapping can be a powerful alternative for geneticmapping of complex traits by taking account into the biological and physicalmechanisms underlying their formation.

Original languageEnglish (US)
Article numberbbs067
Pages (from-to)43-53
Number of pages11
JournalBriefings in bioinformatics
Issue number1
StatePublished - Jan 2014

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology


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