About this Research Topic
Genotype by environment (GxE) interaction influences many economically relevant traits, and when not accounted for may limit breeding progress. On the other hand, GxE interaction plays an important role in adaptation and resilience. Recently, the impact of climate change on farm animal production has increased interest in exploring GxE interactions. However, besides physical environment, GxE interaction occurs also in the context of other factors relevant to animal production, such as nutrition and microbiome, disease and treatment, production system, and social environment. Understanding and exploitation of GxE interaction is thus of paramount importance for many current challenges faced by farm animal breeding - increasing production efficiency, while ensuring sustainability, food safety, and animal welfare. Therefore, we need more research into methods for measuring of GxE interactions, implementation in breeding programs, and into its biological basis and genetic architecture.
There are many white spots in our knowledge of GxE interaction; for example, we know little how domestication and breeding changed the underlying genetic architecture. Recent advances in sensor and omics technologies facilitate comprehensive characterization of the environment and of the corresponding physiological and (epi)genomic responses and may expedite exploration of GxE interaction. Because gene expression is responsive to the environment, gene expression studies appear particularly suitable to investigate GxE interactions, i.e., which pathways and biofunctions play a key role, while eQTL (expression QTL) studies may reveal the causal loci and variants. Other methods that can be used to explore GxE interactions include investigation of modification and long-term programming of gene expression through epigenetic mechanisms, and pQTL (protein QTL) and mQTL (metabolomic QTL) studies and their dependence on environmental variables. Collection of the multidimensional data requires parallel development in statistical modeling and data analytics.
In this Research Topic we invite manuscripts, including Original Research and Reviews, dealing with all aspects of research on GxE interaction: statistical modeling, big data analytics, GxE interaction studies, QTL and GWAS studies, and also studies employing functional genomic, transcriptomic, epigenomic, proteomic, metabolic and metabolomic, and metagenomic approaches for fine-grained characterization of the physiological responses and investigation of the biological and genetic basis.
There are many white spots in our knowledge of GxE interaction; for example, we know little how domestication and breeding changed the underlying genetic architecture. Recent advances in sensor and omics technologies facilitate comprehensive characterization of the environment and of the corresponding physiological and (epi)genomic responses and may expedite exploration of GxE interaction. Because gene expression is responsive to the environment, gene expression studies appear particularly suitable to investigate GxE interactions, i.e., which pathways and biofunctions play a key role, while eQTL (expression QTL) studies may reveal the causal loci and variants. Other methods that can be used to explore GxE interactions include investigation of modification and long-term programming of gene expression through epigenetic mechanisms, and pQTL (protein QTL) and mQTL (metabolomic QTL) studies and their dependence on environmental variables. Collection of the multidimensional data requires parallel development in statistical modeling and data analytics.
In this Research Topic we invite manuscripts, including Original Research and Reviews, dealing with all aspects of research on GxE interaction: statistical modeling, big data analytics, GxE interaction studies, QTL and GWAS studies, and also studies employing functional genomic, transcriptomic, epigenomic, proteomic, metabolic and metabolomic, and metagenomic approaches for fine-grained characterization of the physiological responses and investigation of the biological and genetic basis.
Keywords: Genotype-by-environment interaction, Big data, Omics, QTL, Resilience
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