Dew-Budd Kelly, Mathur Ravi, Roy Siddharth, Jarnigan Julie, Moss Andrea, Bombin Andrei, Oza Vishal, Rele Chinmay, Adams Alison, Mendez Sean, Bray Katherine, Davis Dana, Kieffer Matthew, Leonard Leah, Hubickey Joana, Paiva Cheyenne, Izor Nicholas, Nadella Divya, Perkins Lauren Ross, Zeng Xiangpei, Merriam Jordyn, Motsinger-Reif Alison, Reed Laura K
Department of Biological Sciences, University of Alabama; Tuscaloosa, AL.
School of Plant Sciences, University of Arizona; Tucson, AZ.
bioRxiv. 2025 Aug 6:2025.08.04.668530. doi: 10.1101/2025.08.04.668530.
Metabolic Syndrome (MetS) risk, driven by genotype-environment interactions like diet, is rising globally. Due to its genetic and environmental complexity, the genetic architecture and interconnected traits underlying MetS is poorly understood. In , genotype-by-diet interactions significantly influence MetS-like traits. This study used the Synthetic Population Resource to dissect the genetic architecture of both genotypic and genotype-by-diet interaction effects underlying trait variation. The study hypotheses were: 1) Loci responsible for metabolic phenotypic variation should be shared across traits. 2) Genetic loci responsible for plasticity and epistatic interactions for metabolic traits should also be the loci responsible for the main effects. 3) Genes responsible for variation in metabolic traits should share common functions. Using a round-robin crossing scheme and novel analyses, we mapped additive, dominance, and epistatic loci-some diet-specific, others diet-independent. Main-effect and plastic loci were largely distinct, as were epistatic loci from main-effect loci, highlighting that main genetic effects alone will not explain how genetic variants interact with the environment or the genome to influence disease risk. gene-by-diet or gene-by-gene interactions influencing MetS risk. Further, tremendous cryptic genetic variation for metabolic traits is lurking in natural populations. We explored the function of candidate genes from our study empirically and with bioinformatics. While some of the candidate genes might have been expected, most would not have been identified , thus with this study we have identified many new candidate mechanisms contributing to the genetic and genotype-by-diet interaction effects on MetS variance.
由饮食等基因型 - 环境相互作用驱动的代谢综合征(MetS)风险在全球范围内呈上升趋势。由于其遗传和环境复杂性,人们对MetS潜在的遗传结构和相互关联的特征了解甚少。在[具体研究中],基因型与饮食的相互作用显著影响类似MetS的特征。本研究利用合成种群资源剖析性状变异背后的基因型效应以及基因型与饮食相互作用效应的遗传结构。研究假设如下:1)负责代谢表型变异的基因座应在各性状间共享。2)负责代谢性状可塑性和上位性相互作用的基因座也应是负责主要效应的基因座。3)负责代谢性状变异的基因应具有共同功能。通过循环杂交方案和新颖的分析方法,我们定位了加性、显性和上位性基因座——有些是饮食特异性的,有些是饮食非依赖性的。主要效应基因座和可塑性基因座在很大程度上是不同的,上位性基因座与主要效应基因座也是如此,这突出表明仅主要遗传效应无法解释遗传变异如何与环境或基因组相互作用以影响疾病风险。基因与饮食或基因与基因的相互作用影响MetS风险。此外,自然种群中潜藏着大量代谢性状的隐性遗传变异。我们通过实证和生物信息学方法探索了本研究中候选基因的功能。虽然有些候选基因可能在意料之中,但大多数是无法事先确定的,因此通过本研究,我们已经确定了许多新的候选机制,这些机制对MetS变异的遗传效应和基因型与饮食的相互作用效应有贡献。