Determining the genetic underpinning of the phenotypic variation of agriculturally relevant traits is a classical question in plant genetics. Genetic mapping approaches, for example QTL mapping and GWAS, are widely applied to dissect the genetic architecture of complex traits in major crops. Due to the advances in large-scale phenotyping systems, multi-omic data measurements and increasing knowledge of cellular interactome, it is time to study these data with advanced techniques to propel gene function discovery. Relevant to these developments is the problem of understanding phenotypic variation under future climate scenarios; as a result, recent studies have focused on phenotypic plasticity and genotype-by-environment interaction analysis. The knowledge of cellular networks and multi-omic data enable a fresh look at the quantitative approach to analyze phenotypic plasticity and genotype-by-environment interaction.
The purpose of this Research Topic is to discuss the current questions and future of analysing complex trait variation to genetic and/or environmental factors in major crops in the context of cellular networks and multi-omic data. This Research Topic aims to encourage researchers to showcase the development of novel network-based approaches and their application in crop studies. From a data-driven aspect, this Research Topic will cover advances in the integration of phenomic, transcriptomic and metabolomic data to understand phenotypic variation in agronomically relevant traits. From a modelling perspective, it aims to highlight how complex traits can be analysed by using network-based modelling or a combination of the classical genetic mapping approaches with embedding of information in cellular networks, such as the gene regulatory network and genome-scale metabolite network. We also welcome perspective and critical views on ideas related to phenotypic variation dissection.
We invite all type of articles concerning the dissection of complex traits in major crops, such as original research of novel approaches in design or modelling, applying integrative approaches in case study and review on the future of gene discovery or phenotypic plasticity analysis. We encourage the submission of articles that cover, but are not limited to, phenotypic data collection, genetic architecture of complex trait (with emphasis on integrative approaches or genotype-by-environment interaction), environmental factor on phenotypes and phenotype predictions, such as:
• Large-scale phenotype quantitation
• Multiomic-based gene discovery study
• Network-assistant gene discovery study
• Genetic basis of phenotypic plasticity
• Genomic/multiomic prediction of phenotypes
Determining the genetic underpinning of the phenotypic variation of agriculturally relevant traits is a classical question in plant genetics. Genetic mapping approaches, for example QTL mapping and GWAS, are widely applied to dissect the genetic architecture of complex traits in major crops. Due to the advances in large-scale phenotyping systems, multi-omic data measurements and increasing knowledge of cellular interactome, it is time to study these data with advanced techniques to propel gene function discovery. Relevant to these developments is the problem of understanding phenotypic variation under future climate scenarios; as a result, recent studies have focused on phenotypic plasticity and genotype-by-environment interaction analysis. The knowledge of cellular networks and multi-omic data enable a fresh look at the quantitative approach to analyze phenotypic plasticity and genotype-by-environment interaction.
The purpose of this Research Topic is to discuss the current questions and future of analysing complex trait variation to genetic and/or environmental factors in major crops in the context of cellular networks and multi-omic data. This Research Topic aims to encourage researchers to showcase the development of novel network-based approaches and their application in crop studies. From a data-driven aspect, this Research Topic will cover advances in the integration of phenomic, transcriptomic and metabolomic data to understand phenotypic variation in agronomically relevant traits. From a modelling perspective, it aims to highlight how complex traits can be analysed by using network-based modelling or a combination of the classical genetic mapping approaches with embedding of information in cellular networks, such as the gene regulatory network and genome-scale metabolite network. We also welcome perspective and critical views on ideas related to phenotypic variation dissection.
We invite all type of articles concerning the dissection of complex traits in major crops, such as original research of novel approaches in design or modelling, applying integrative approaches in case study and review on the future of gene discovery or phenotypic plasticity analysis. We encourage the submission of articles that cover, but are not limited to, phenotypic data collection, genetic architecture of complex trait (with emphasis on integrative approaches or genotype-by-environment interaction), environmental factor on phenotypes and phenotype predictions, such as:
• Large-scale phenotype quantitation
• Multiomic-based gene discovery study
• Network-assistant gene discovery study
• Genetic basis of phenotypic plasticity
• Genomic/multiomic prediction of phenotypes