Brief. Bioinformatics - Towards a comprehensive picture of the genetic landscape of complex traits.

Tópicos

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Resumo

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 approach-systems mapping-dissects the system into interconnected elements and then map 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 and metabolomic 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.

Resumo Limpo

format phenotyp trait biomass product tumor volum viral abund undergo complex process interact gene development stimuli take place level biolog organ cell organ tradit studi emphas impact gene direct link dnabas marker static phenotyp valu function map deriv detect gene control development process use growth equat proven power address question role gene develop treat phenotyp format cohes system use differenti equat differ approachsystem mappingdissect system interconnect element map gene determin web interact among element facilit understand genet machineri phenotyp develop argu genet map can play import role studi genotypephenotyp relationship fill gap biochem regulatori process dna endpoint phenotyp describ new framework name network map studi genet architectur complex trait integr regulatori network caus highord phenotyp network map make use system differenti equat quantifi rule transcript proteom metabolom compon interact organ function whole synthesi function map system map network map provid novel avenu deciph comprehens pictur genet landscap complex phenotyp underli econom biomed import trait

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