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 journalArticle

3 Citations (Scopus)

Abstract

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
Volume15
Issue number1
DOIs
StatePublished - Jan 1 2014

Fingerprint

Dielectric Spectroscopy
Acoustic impedance
Electric Impedance
Quantitative Trait Loci
Spectroscopy
Ziziphus
Genotype
Likelihood Functions
Maximum likelihood
Networks (circuits)

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology

Cite this

Tong, Chunfa ; Shen, Lianying ; Lv, Yafei ; Wang, Zhong ; Wang, Xiaoling ; Feng, Sisi ; Li, Xin ; Sui, Yihan ; Pang, Xiaoming ; Wu, Rongling. / Structural mapping : How to study the genetic architecture of a phenotypic trait through its formation mechanism. In: Briefings in bioinformatics. 2014 ; Vol. 15, No. 1. pp. 43-53.
@article{158159eb010f406a8bcc0319754882d1,
title = "Structural mapping: How to study the genetic architecture of a phenotypic trait through its formation mechanism",
abstract = "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.",
author = "Chunfa Tong and Lianying Shen and Yafei Lv and Zhong Wang and Xiaoling Wang and Sisi Feng and Xin Li and Yihan Sui and Xiaoming Pang and Rongling Wu",
year = "2014",
month = "1",
day = "1",
doi = "10.1093/bib/bbs067",
language = "English (US)",
volume = "15",
pages = "43--53",
journal = "Briefings in Bioinformatics",
issn = "1467-5463",
publisher = "Oxford University Press",
number = "1",

}

Tong, C, Shen, L, Lv, Y, Wang, Z, Wang, X, Feng, S, Li, X, Sui, Y, Pang, X & Wu, R 2014, 'Structural mapping: How to study the genetic architecture of a phenotypic trait through its formation mechanism', Briefings in bioinformatics, vol. 15, no. 1, bbs067, pp. 43-53. https://doi.org/10.1093/bib/bbs067

Structural mapping : How to study the genetic architecture of a phenotypic trait through its formation mechanism. / Tong, Chunfa; Shen, Lianying; Lv, Yafei; Wang, Zhong; Wang, Xiaoling; Feng, Sisi; Li, Xin; Sui, Yihan; Pang, Xiaoming; Wu, Rongling.

In: Briefings in bioinformatics, Vol. 15, No. 1, bbs067, 01.01.2014, p. 43-53.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Structural mapping

T2 - How to study the genetic architecture of a phenotypic trait through its formation mechanism

AU - Tong, Chunfa

AU - Shen, Lianying

AU - Lv, Yafei

AU - Wang, Zhong

AU - Wang, Xiaoling

AU - Feng, Sisi

AU - Li, Xin

AU - Sui, Yihan

AU - Pang, Xiaoming

AU - Wu, Rongling

PY - 2014/1/1

Y1 - 2014/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84892996890&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84892996890&partnerID=8YFLogxK

U2 - 10.1093/bib/bbs067

DO - 10.1093/bib/bbs067

M3 - Article

C2 - 23104859

AN - SCOPUS:84892996890

VL - 15

SP - 43

EP - 53

JO - Briefings in Bioinformatics

JF - Briefings in Bioinformatics

SN - 1467-5463

IS - 1

M1 - bbs067

ER -