A New Approach To Identify Candidate Target Genes Involved In Complex Traits

Complex traits are often determined by genetic factors, epigenetic factors and environmental factors, and show quantitative variation among different individuals in a population. The quantitative variations in such traits are related to DNA polymorphims such as single nucleotide polymorphisms (SNPs). The relationship between SNPs and complex traits is an active field research. However, the genetic basis of complex traits still remains to be better understood, which could be facilitated by more effective methods of investigation. Our recent data showed a strong correlation between complex traits and SNP numbers or minor allele contents (MAC) of an individual in humans and model organisms, such as the food-lawn leaving rate was correlated with MAC in Recombinant Inbred Advanced Intercross Lines (RIAILs) of C.elegans with HW npr-1genotypes, which indicated that the MAC of an individual may regulate mRNA expression of a specific set of genes that in turn affect complex traits by some way. The food patch-leaving trait of C.elegans is a complex decision making trait regulated by a large number of genetic factors, some of which have been found, such as npr-1, glb-5and tyra-3, while the specific neural and molecular mechanism remained unclear. Objective:To establish a new approach to identify target genes for complex traits.Methods:The decision-making behavior of C.elegans is studied in this research. Screen genes whose mRNA expression levels are correlated with both MAC and leaving rate through SAM in HW npr-1RIAILs, and these genes are thought to be candidate target genes that control this behavior. And then, in order to confirm this method to be effective and feasible, select part of those genes randomly to analyse their function through RNAi.Results:In the gene expression profiles of HW npr-1RIAILs,492gene expressions were correlated with MAC and173gene expressions were correlated with leaving rate, but only about27gene expressions correlated with both leaving rate and MAC. We selected4positive genes (fbxa-103,lnp-1,ZC239.14and F42G2.2) and1negative genes (nspd-7)from those27genes to conduct RNA interference. Relative to controls with vector plasmid alone, the leaving rate of worms with fbxa-103, lnp-1and ZC239.14RNAi were significantly reduced, while that of worms with nspd-7RNAi was significantly increased.Conclusion:The method of double selection for genes whose expression is correlated with both MAC and a specific trait is an effective and feasible way of identifying individual genes involved in a complex trait, which indicates a novel mechanism for MAC to quantitatively affect complex traits, namely by regulating the expression of a small set of target genes, and provide a new train of thought for the study of genetic basis of complex traits.