Towards a comprehensive picture of the genetic landscape of complex traits

Zhong Wang, Yaqun Wang, Ningtao Wang, Jianxin Wang, Zuoheng Wang, C. Eduardo Vallejos, Rongling Wu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The formation of phenotypic traits, such as biomass production, tumor volume and viral abundance, undergoes a complex process in which interactions between genes and developmental stimuli take place at each level of biological organization from cells to organisms. Traditional studies emphasize the impact of genes by directly linking DNA-based markers with static phenotypic values. Functional mapping, derived to detect genes that control developmental processes using growth equations, has proven powerful for addressing questions about the roles of genes in development. By treating phenotypic formation as a cohesive system using differential equations, a different approachçsystemsmappingçdissects the systeminto interconnected elements and thenmap genes that determine a web of interactions among these elements, facilitating our understanding of the genetic machineries for phenotypic development. Here, we argue that genetic mapping can play a more important role in studying the genotype-phenotype relationship by filling the gaps in the biochemical and regulatory process from DNA to end-point phenotype.We describe a new framework, named network mapping, to study the genetic architecture of complex traits by integrating the regulatory networks that cause a high-order phenotype. Network mapping makes use of a system of differential equations to quantify the rule by which transcriptional, proteomic andmetabolomic components interact with each other to organize into a functional whole. The synthesis of functional mapping, systems mapping and network mapping provides a novel avenue to decipher a comprehensive picture of the genetic landscape of complex phenotypes that underlie economically and biomedically important traits.

Original languageEnglish (US)
Article numberbbs049
Pages (from-to)30-42
Number of pages13
JournalBriefings in bioinformatics
Volume15
Issue number1
DOIs
StatePublished - Jan 2014

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology

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