Evaluation of heat tolerance in 98 accessions of perennial ryegrass
A total of seven physiological traits (WUE, Pn, RA, Chl content, RWC, EL, and Fv/Fm) and threephenotypic traits (TQ, LW, and PH) were used to evaluate heat tolerance of 98 perennial ryegrass accessions. Effects of heat stress treatment, genotype, and interaction of these two factors were all significant (p ≤ 0.05) for WUE, Pn, RA, Chl, RWC, Fv/Fm, EL, and TQ. Only genotypic variations were significant for LW and PH (Table 2).
The data for physiological and phenotypic traits of 98 accessions exposed to heat stress or optimum temperature (control) conditions were used to plot a heatmap (Figure 1), in which the hierarchical cluster was clearly grouped into two distinct sub-clusters: accessions under the control condition (sub-cluster ‘a’) and those under the heat stress (sub-cluster ‘b’ as shown in Figure 1). Accordingly, ten traits used to evaluate ryegrass heat tolerance were grouped into four sub-clusters: sub-cluster I included WUE, Pn, and RA, where their values were lower under heat stress than those under control condition; sub-cluster II included Chl content, TQ, RWC, and Fv/Fm, which values were also lower under heat stress; sub-cluster III, including the two morphological traits (PH and LW), did not show consistent alteration under the two growth conditions; and sub-cluster IV, only consisted of one trait (EL), had higher values under heat stress (Figure 1). Therefore, eight traits, excluding LW and PH, were used to evaluate ryegrass heat tolerance in the following analyses.
Ranking of overallheat tolerance for 98 accessionsof perennial ryegrass
The PCA analysis of variations in heat tolerance of 98 accessions based on HSI identified a total of eight principal components (PC 1-8). The sum of the first PCs (PC1 to PC4) explained 88.45% of the total variance, among which the 1st and 2nd PCs were the major ones explaining 52.67% and 20.37% of the variance among 98 ryegrass accessions, respectively (Supplementary Table 1). Based on the PCA result, the following formulas were developed (details of the formula were shown in Supplemental Table 2): PC1 value = 0.897×TQ + 0.766×Fv/Fm + 0.858×Chl content + 0.373×Pn + 0.244×WUE + (−0.691)×EL + 0.891×RWC + 0.785×RA; and PC2 value = (−0.199)×TQ + (−0.311)×Fv/Fm + (−0.055)×Chl content + 0.809×Pn + 0.896×WUE + (−0.043)×EL + (−0.180)×RWC + 0.040×RA; (3) PC3 value = 0.196×TQ + 0.413×Fv/Fm + (−0.119)×Chl content + 0.233×Pn + 0.033×WUE + 0.566×EL + 0.095×RWC + (−0.227)×RA; and PC4 value = 0.031×TQ + (−0.125)×Fv/Fm + 0.219×Chl content + (−0.220)×Pn + 0.130×WUE + 0.431×EL + (−0.166)×RWC + 0.480×RA, and PCA rank value = (52.67%×PC1) + (20.37%×PC2) + (8.25%×PC3) + (7.17%×PC4).
According to PCA results, we clustered 98 ryegrass accessions into two groups：Group-ⅰ consisted of 49 accessions with PCA rank value at the top half of all accessions, while the rest 49 accessions clustered to group-ⅱ (Figure 2). Heat tolerance of 98 accessions were then ranked according to their PCA ranking values based on theHIS of eight parameters (WUE, Pn, RA, Chl content, RWC, and Fv/Fm, EL, and TQ), with accessions 275660, 598892, 277846, 516605, and 598443 ranked as the top five accessions for heat tolerance and 538976, 321681, 317452, 239730, and 303027 ranked as the most heat-sensitive accessions (Table 3). Phenotypes of the top and least five heat tolerant ryegrass accessions were shown in Figure 3, that plants of the top-rated accessions had more green leaves or greener leaves while the most heat-sensitive accessionshad more yellow or less green leaves.
To understand contributions of different traits to heat tolerance in perennial ryegrass, the relationships betweenPCA ranking based on HSIfor overall heat toleranceand each physiological/phenotypic trait was determined using Pearson correlation analysis. As shown in Table 4, the PCA ranking was significantly correlated with all eight traits used in the evaluation (p ≤ 0.05), among which ranking values of PCA and EL had the largest correlation coefficient (r = −0.858). And ranking values of Chl content, RWC, and TQ also showed high correlation coefficients with those of PCA (r = 0.769, 0.764, and 0.744, respectively). Values of Pn and WUE had low correlation coefficients with those of PCA (r = 0.306 and −0.216, respectively), although their correlations were statistically significant as well (p ≤ 0.05) (Table 4).
Transcript levels of chlorophyll-catabolic genes correlated to heat tolerance in perennial ryegrass
Results of Pearson correlation analysis indicated that heat tolerance PCA ranking values and Chl content had the larger correlation coefficient (r = 0.769, Table 4), indicating leaf senescence characterized by Chl loss was mostly associated with overall heat tolerance in perennial ryegrass. To confirm the contribution of Chl catabolism to heat-tolerant accessions of perennial ryegrass, we further analyzed whether there was a correlation between transcription of four Chl catabolic genes (CCGs, including LpNYC1, LpNOL, LpSGR, and LpPPH) and the PCA ranking values of heat tolerance of 98 ryegrass accessions. As shown in Figure 5, relative expression levels of CCGs were significantly higher in heat-sensitive accessions than those in heat-tolerant accessions. The relationship between the relative expression levels of CCGs and PCA ranking values were further analyzed using linear regression analysis and Pearson correlation coefficient analysis. As shown in Figure 6, relative expression levels of LpNYC1, LpNOL, LpSGR, and LpPPHhad strong positive correlations to PCA ranking values with R2=0.943, 0.878, 0.814, and 0.896, respectively.
Classification of 98 accessions of perennial ryegrass based on SSR markers
Genotypic diversity within the selected ryegrass accessions was estimated using 66 pairs of SSR molecular markers. The SSR analysis yielded 864 polymorphic bands in total, with an average of 13 and a range of 3 to 26 bands per pair of primers (Supplementary material 2). The resultant polymorphism information content (PIC) values varied from 0.16 to 0.93, with an average of 0.70; while the gene diversity index (Di) values ranged 0.16 to 0.94, with an average of 0.72 (Supplementary material 2), confirming that the selected accessions represented a diverse genetic pool of perennial ryegrass germplasm. An N-J dendrogram was constructed based on the SSR results, clustering the 98 ryegrass accessions into three groups: Cluster A, B, and C consisting of 14, 10, and 74 ryegrass accessions, respectively (Figure 4).
Values of PCA ranking of heat tolerance and physiological traits were averaged across ryegrass accessions in each phylogenetic cluster (Table 5), and the results showed that averaged PCA ranking values of accessions in cluster C (61.67) were significantly higher than those in clusters A and B (2.65 and 7.89, respectively), suggesting that accessions in clusters A and B were less heat tolerant than those in cluster C. Similar difference was also observed for Chl content, WUE, EL, and RA for genotype ranking of heat tolerance in each phylogenetic cluster (Table 5).
SSR markers associated with physiological traits in heat tolerance
The associations between the 66 SSR markers and the seven physiological traits were further analyzed using a general linear model (GLM) in TASSEL. As shown in Figure 7 and Table 6, a total of 34 associations were identified between the SSR markers and the relative values of Chl content, Fv/Fm, Pn, WUE, EL, and RA at R2>0.05 (p<0.01). We found that two markers M144 and rv0941, located on chromosome 4, were associated with Chl content. The markers Lp165, rv0941, DLF008, B3C10, B3B8, and B5E1, located on chromosomes 3, 4, 5, and 7, were associated with Fv/Fm. The marker rv0985-1, located on chromosome 6, was associated with Pn. Thirteen markers, including PRG, PR10, M4213, 25ca1, LPSSRH01A07, rv0985-1, rv0005, rv1133, LPSSRH02C11, rv0663, B3B7, LpHCA16B2, and PR37, located on chromosomes 1, 3, 4, 6, and 7, were associated with WUE. The markers M844, LPSSRH01A07, B3B7, B1A10, LpSSR100, LP194, rv0757, and LPSSRH02C11, located on chromosomes 1, 3, and 5, were associated with RA. The markers LM15, LPSSRH01H06, rye012, and LpHCA17C6 were associated with EL. No association was identified between SSR markers and TQ or RWC (Figure 7).