Abstract:
Objective Based on the study of Arabidopsis thaliana plant height traits and the epistatic network models, this research aimed to explore and reveal the processes or patterns of multiple genes interacting with each other in a complex network during plant growth by constructing interactive regulatory networks at different levels.
Method 84 recombinant inbred lines (RILs) of Arabidopsis thaliana were selected for the subsequent experiment, from which a total of 417 495 single nucleotide polymorphisms (SNPs) and plant height growth data across 8 time points were acquired. Through the functional mapping method, correlation analyses were performed on different genotypes and plant height traits previously obtained through sequencing. Afterwards, taking into account the concept of modularization from systems biology and ideas on dimensionality reduction from statistics, a system of ordinary differential equations was further adopted to construct not only a sparse, directed and quantifiable module, but also an epistatic interaction network among the genes. Eventually, database from the Arabidopsis Information Resource (TAIR) was utilized to perform enrichment analyses and functional annotations on candidate genes in various functional modules.
Result The findings obtained herein showed that most functional modules seen from the macroscopic scale in the gene regulatory network not only played a positive regulatory role throughout the growth of Arabidopsis thaliana but also changed corresponding interaction strategy with time. On the other hand, from the microscopic view of the gene regulatory network, AT4G29140, the gene closely associated with structural development of Arabidopsis thaliana, was found to only play an up-regulating role onto other loci and be subjected to only down-regulating effects from ageing-related genes. Moreover, AT4G36910, the gene responsible for maintaining cellular homeostasis, was found to display passive regulatory attitudes and have functional expressions that greatly depend on the regulation from other genes. Last but not least, AT4G22680 was speculated to execute its regulatory functions by regulating RP1 expressions.
Conclusion This study has taken the context of complex network, conducted correlation analysis, and successfully probed into the epistatic mechanism affecting the growth of Arabidopsis thaliana, thereby providing a novel set of method and thought process for analyzing the genetic structures of plants.