Phenotypic evaluation and correlation analysis
The kernel traits of the 2CN population and their parents in different environments are listed in Table 1. ‘CN16’ had consistently and significantly higher values for KL than ‘20828’, while ‘20828’ is wider than ‘CN16’ in KW (Table 1, Fig. 1). For the 2CN population, the frequency distribution for kernel traits in all environments and best linear unbiased predictors (BLUP) showed continuous distributions with ranges from 5.33 to 8.07 mm in KL, 2.43 to 4.19 mm in KW and 10.7 to 69.3 g in TKW (Table 1, Fig. 2). The broad-sense heritability of KL, KW and TKW were 0.86, 0.64 and 0.73, respectively (Table 1).
Correlation analysis showed that KL, KW and TKW among different environments were all significant, and the correlation coefficients ranged from 0.38 to 0.92 (P < 0.01, Table S1). Significant correlations with coefficients ranging from 0.48 to 0.83 among all three kernel traits based on the BLUP data were detected as well (P < 0.01, Table S2).
Moreover, the phenotypic correlation analyses between the investigated kernel traits and other agronomic traits showed that all three kernel traits had significantly and negatively correlations with spikelet number per spike and anthesis date (P < 0.01). KW was significantly and positively correlated with plant height (P < 0.01) and significant correlations were also detected between TKW and plant height (P < 0.05, Table S3).
A total of 11 putative QTL associated with kernel traits were detected in the 2CN population (Table 2). They were located on chromosomes 1A (2 QTL), 2B (2 QTL), 2D (3 QTL), 3D, 4A, 6A, and 7A (Table 2, Fig. 3). Of them, six QTL conferring KL were identified individually explaining 2.57-18.05 % of the phenotypic variance. QKL.sicau-2D, as a major locus, was detected in all environments and explained 10.88-18.05 % of the phenotypic variance. The positive allele at QKL.sicau-2D was derived from ‘CN16’ (Table 2). QKL.sicau-6A was detected in two environments. This locus explained 5.16-7.09% of phenotypic variance. The positive allele at this QTL was derived from ‘20828’.
Two QTL conferring KW, QKW.sicau-2D and QKW.sicau-3D were detected and accounted for 5.15-21.49 % of the phenotypic variance. QKW.sicau-2D was a major locus and explained 17.21-21.49 % of the phenotypic variance in three environments and the BLUP dataset. The positive allele at it was derived from ‘CN16’ (Table 2).
Three QTL associated with TKW were detected with 4.01-23.20 % of the phenotypic variance explained. A major QTL, QTKW.sicau-2D, accounting for 10.01-23.20 % of the phenotypic variance, was stably detected in three environments and the BLUP dataset. The positive allele at this QTL was contributed by ‘CN16’ (Table 2).
The remaining 8 QTL including QKL.sicau-1A, QKL.sicau-2B, QKL.sicau-4A, QKL.sicau-6A, QKL.sicau-7A, QTKW.sicau-1A, QTKW.sicau-2B and QKW.sicau-3D explained less than 10% of the phenotypic variance and could only be detected in less than two environments (Table 2).
Interestingly, the three major and stable QTL, QKL.sicau-2D for KL, QKW.sicau-2D for KW, and QTKW.sicau-2D for TKW, were co-located in the same interval between 67.5 and 68.5 cM. QKL.sicau-1A for KL and QTKW.sicau-1A for TKW were co-located in the interval between 167.5 and 172.5 cM. QKL.sicau-2B for KL and QTKW.sicau-2B for TKW were also co-located in the interval between 63.5 and 64.5 cM (Table 2, Fig. 3). These three co-located QTL intervals suggest that there may be a major QTL with pleiotropic effects affecting related traits or a cluster of linked QTL that affect multiple various traits [22, 23].
QTL × environment (QE) interaction analysis showed that a total of 45 QTL were detected (Table S4). Eleven of these QTL were the same as those detected in individual environment QTL mapping. For instance, QKL.sicau-2D, QKW.sicau-2D and QTKW.sicau-2D were all detected, further indicating that they were major and stable. The remaining QTL showed low LOD scores and low phenotypic variance explained in the QE interaction analysis.
Marker development and validation
The co-located interval for the three major QTL, QKL.sicau-2D, QKW.sicau-2D and QTKW.sicau-2D were firstly mapped between AX-111096297 and AX-86171316 (Fig. 4). SNPs in this region detected by the Wheat660K array in the parents of the 2CN population were converted to KASP markers . KASP-AX-94721936 was genetically mapped between AX-111096297 and AX-86171316 (Fig. 4). Finally, QTL re-mapping showed that QKL.sicau-2D, QKW.sicau-2D and QTKW.sicau-2D were all located between AX-111096297 and KASP-AX-94721936 (Fig. 4). In addition, AX-111096297 and KASP-AX-94721936 were used to BLAST against the pseudomolecules of ‘Chinese Spring’ (‘CS’). BLAST results showed that AX-111096297 and KASP-AX-94721936 were located at 32.97Mbp and 33.74Mbp, respectively, in the deletion bin of 2DS5-0.47-1.00 on the short arm of chromosome 2DS (Fig. 4).
The homozygous lines of parental alleles ‘20828’ and ‘CN16’ at each QKL.sicau-2D, QKW.sicau-2D and QTKW.sicau-2D were selected based on the genotyping data of AX-111096297 and KASP-AX-94721936 for the 2CN population. T-test showed that the lines carrying the ‘CN16’ alleles had significantly higher phenotypic values that those carrying the ‘20828’ alleles at all the three QTL in different environments and the BLUP datasets (P<0.05, Fig. 5).
Detection of the effect of 1BL/1RS translocation on kernel traits
No significant difference was detected between lines carrying 1BS and 1RS for KL, KW and TKW (Fig. S1). This result likely indicated that there is no QTL affecting these kernel traits on the 1BS or 1RS chromosome arm.