Identifying genes that determine SOC plasticity
To uncover the genetic basis of SOC plasticity, we conducted genome-wide association studies (GWASs) using two reaction norm parameters as phenotypic input, the intercept and the slope, obtained from joint regression analysis based on the environmental mean for SOC across all environments (Fig. S7). When using the intercept as the phenotype, we detected genomic regions containing the PROBABLE METHYLTRANSFERASE PMT6 (PMT6 ) and DIOXYGENASE FOR AUXIN OXIDATION1(DAO1 ) genes, with PMT6 previously reported to influence SOC variation in B. napus (Tang et al., 2021). Using the slope as phenotype, we identified two genomic regions containing genes homologous to Arabidopsis (Arabidopsis thaliana ) MYB DOMAIN PROTEIN 106 (MYB106 ) and DIGALACTOSYL DIACYLGLYCEROL DEFICIENT1 (DGD1 ). MYB106 encodes a MIXTA-like transcription factor involved in cuticle development and lipid transport, while DGD1 encodes a galactosyltransferase-like protein involved in lipid trafficking (Dormann et al., 1999, Oshima et al., 2013).
To uncover the genomic regions that respond to changes in the identified environmental indices (DTR183–192, PR166–195 and UVB144–186), we calculated the slope from a regression between SOC and each index, representing the specific response of each plant to each index. We used the resulting slopes as phenotypes for the GWAS (Figs. 5a, S8). We identified DGD1 for DTR183-192 slopes andMYB106 for UVB144-186 slopes. We also mapped three additional genomic regions associated with PR166-195 slopes. We prioritized the candidate genes within these regions with the Arabidopsis homologs3-HYDROXYACYL-[ACYL-CARRIER-PROTEIN] DEHYDRATASE(HAD ), MYO-INOSITOL-1-PHOSTPATE SYNTHASE3 (MIPS3 ), and PHOSPHATIDYLSERINE DECARBOXYLASE1 (PSD1 ). HAD is a 3-hydroxyacyl-ACP dehydratase involved in fatty acid biosynthesis. MIPS3 catalyzes the rate-limiting step in myo-inositol biosynthesis. PSD1 is a mitochondrion-localized protein involved in phosphatidylethanolamine biosynthesis (Fig. 5a–c). The involvement of these genes in lipid metabolism in Arabidopsis is consistent with their putative role in SOC variation in B. napus .
To delineate potential polymorphisms in the above candidate genes, we aligned their genomic sequences from eight publicly available whole-genome assemblies of B. napus lines (Fig S9; Supplementary Table S16). We discovered structural variations in PMT6 andDGD1 , in the form of transposon insertions in their promoters, defining two haplotypes among these eight B. napus inbred lines.PMT6 in ‘Gangan’, ‘QuintaA’ and ‘Shengli’ contains an insertion of a Mutator retrotransposon; Helitron retrotransposon was inserted in the DGD1 promoter in ‘Shengli’. PMT6 andDGD1 may therefore affect SOC through changes in their expression levels. We also investigated potential coding variants affecting protein function. The most significant amino acid polymorphisms are C106G, H32N and S108C in DAO1, MYB106 and HAD, respectively. These variants provide relevant evidence for follow-up studies of functional polymorphisms.
To understand gene–environment interactions, we examined genetic effect dynamics along the identified environmental indices. We calculated the genetic effects within each environment for the most significant markers within identified candidate genes and used regression analysis to obtain fitted lines representing the genetic effects along the environmental gradient (Fig. 5d–f). This helps interpret the underlying mechanism of plant perceptron interacting with diverse environmental and development cues. Differential sensitivity (DS; magnitude change), conditional neutrality (CN, effect limiting to specific environment), antagonistic pleiotropy (AP; sigh change), and no G×E (no change) (Des Marais et al., 2013) can be viewed as emergent properties in systems. When DGD1interacts with DTR183-192, 57.14% of effect pairs show AP, with 35.71% showing DS and 7.14% indicating no G×E (Fig. 5d). TheMYB106 and UVB144–186 interaction is predominantly AP (42.86%), followed by 25.00% CN, 21.43% DS, and 10.71% no G×E (Fig. 5f). In contrast, the HAD and PR166–195 interaction is primarily CN (39.29%), followed by 32.14% AP, 21.43% DS, and 7.14% no G×E (Fig. 5e). We asked if the two alleles at each SOC plasticity gene showed differences in their expression levels; to this end, we used RNA sequencing data from 289 lines of developing seeds at 20 days after flowering in WH2016 (Tang et al., 2021). Indeed, the two possible alleles differed significantly in their expression, supporting a role in SOC plasticity (Figs. 5g–i, S10).