Dissecting Genetic Networks Underlying Complex Phenotypes In Rice

Molecular biology studies have shown that biological processes of plant and their responses to external cues are controlled by complex gene networks consisting of multiple hierarchical signaling pathways, which presumably include the genetic determinants of complex trait variation. Great progress has been made in genetic dissection of quantitative trait variation during the past two decades, but many studies still reveal only a small fraction of quantitative trait loci (QTLs) with main-effect, and epistasis remains elusive. Unfortunately, these two important areas of study have remained largely independent. We integrate contemporary knowledge of signal transduction pathways with principles of quantitative and population genetics to characterize genetic networks underlying complex traits, which were detected and validated using a series of genetic data and transcriptome data of rice. Following are the results:1. The genetic networks model was founded upon one-way functional dependency of downstream genes on upstream regulators (the principle of hierarchy) and mutual functional dependency among related genes (functional genetic units, FGU). Simulated data suggested that complementary epistasis contributes greatly to quantitative trait variation, and obscures the phenotypic effects of many ’downstream’loci in pathways. The mathematical relationships between the main effects and epistatic effects of genes acting at different levels of signaling pathways were established using the quantitative and population genetic parameters. Both loss of function and "co-adapted" gene complexes formed by multiple alleles with differentiated functions (effects) are predicted to be frequent types of allelic diversity at loci that contribute to the genetic variation of complex traits in populations. Downstream FGUs appear to be more vulnerable to loss of function than their upstream regulators, but this vulnerability is apparently compensated by different FGUs of similar functions. Other predictions from the model may account for puzzling results regarding responses to selection and genotype by environment interaction.2. For validating the predictions associated with random separating population based on the above genetic networks model, meta-analysis of QTLs controlling nine growth and yield traits in IR64/Azucena DH population across11environments by the new genetic networks model revealed three genetic systems:the SD1-mediated,SD1-repressed and SD1-independent pathways that control rice growth, development and productivity. The Green Revolution (GR-I) gene, sd1, actually knocks out the SD1-mediated pathways favored by natural selection and virtually all semidwarf rice cultivars are using the alternative system, SD1-repressed pathways. Thus, GR-I resulted from the overall differences between the two systems. Our results revealed a major risk of exclusive uses of the sdl semidarf lines in the current worldwide rice breeding programs and suggest two general strategies for developing "green super rice" toward higher yield and environmental sustainability in a second Green Revolution.3. For validating the predictions associated with selected population based on the above genetic networks model, four C418BC2F2populations with indica donor parents screened under natural cold conditions at the seedling stage were used to detect the genetic networks underlying CT.177BC2F2:6 progenies were genotyped and reevaluated CT at4℃for7d in the growth chamber and natural low-temperature at the seedling stage as progeny tests. Total30BC2F2individuals verified by progeny testing were used to detect the genome-wide response to CT selection. The putative genetic networks underlying CT improvement under japonica background were dissected according to the genetic networks model. A total of29FGUs involved in41genomic regions associated with CT were identified. The genetic networks consisted of these FGUs associated with CT should be valuable for the improvement of CT in rice breeding programs.4. Genome-wide gene expression profiling is the efficient way to decipher this interesting molecular genetic mechanism of CT enhancement and provide valuable information for the CT improvement in rice breeding. Affymetrix rice genome array was used to analyze the gene expression pattern of two related genotypes with contrasting CT under control and cold conditions at the seedling stage. The transcriptome from shoots of recurrent parent C418and CT IL K354at control condition and5time points (2h,6h,12h,24h, and48h) under4℃cold stress were comparatively analyzed combined with bioinformatics to explore the possible CT enhancement mechanism of K354. Totally3184differentially expressed genes (DEGs) containing195transcription factors were identified under cold stress, approximate half of them were commonly regulated by cold in both genotypes which should be involved in cold responsive pathways including OsDREB1s regulon. The K354-specific cold-induced DEGs were related to stimulus response, cellular cell wall organization, and microtubule-based movement process compared with commonly cold-induced DEGs by GO analysis. Moreover,296constitutive DEGs with significantly different transcription level between C418and K354were detected under both control and cold stress conditions. K354-specific cold-regulated and constitutive DEGs jointly account for the CT improvement of K354. Pathway analysis unraveled up-regulation of starch and sucrose metabolism in both genotypes and presumably weaker defense response to stress in K354than C418under cold stress. The hierarchical relationships among FGUs of putative CT genetic networks detected by Bg300/C418ILs were partially verified based on the candidate genes near or within the donor introgression region. The comparison of the transcriptome between CT IL K354and recurrent parent C418suggested the genotype-dependent CT enhancement mechanism, which can be regarded as the possible way to improve CT of japonica rice using indica germplasm.5. Genetic networks underlying the rice defensive system to two Chinese Xanthomonas oryzae pv. Oryzae (Xoo) races C2and C4mediated by the R gene Xa4or the other unknown R gene were identifed and verified using two sets of reciprocal ILs derived from the same parents, Lemont and Teqing. The complex genetic networks included9FGUs (12loci) and8FGUs (10loci), respectively. Strong epistasis was expcctedly detected between partial pairs of the upstream FGUs and the downstream ones in the genetic network, supporting the principle of hierarchy deduced from the model of genetic networks.