The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice

Abstract

Maize (Zea mays) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice (Oryza sativa) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1, a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis (Arabidopsis thaliana) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis.

Figure 1.

Measurements of kernel traits and variations of kernel size among 14 parental lines and representative lines in two RIL populations. A, Measurements of KL, KW, and KT illustrated with a B73 kernel. Bar = 1 cm. B, Fourteen parental inbred lines used in this study showed considerable variations of kernel size. The arrows point from paternal lines to maternal lines. C, Kernels of representative lines in YU87-1 × BK (left) and ZHENG58 × SK (right) RIL populations. Bar = 1 cm.

Figure 2.

Overview of the QTLs and significant SNPs for HKW identified with three models. A, The top graph (Manhattan plot) shows likelihood ratio test (LRT) scores from JLM. The red points under the x axis indicate the significant SNPs identified in all three models. The middle graph shows the results of SLM in each of the 10 RIL populations. The colored rectangles indicate the QTL regions in each RIL population, and the color density is proportional to the LOD values. The bottom graph shows the results of GWAS. The blue upward triangles indicate that the minor allele increases HKW relative to the major allele, the green downward triangles indicate the opposite effect, and red dots indicate the candidate SNPs identified by the backward regression model. B, A pleiotropic QTL that was identified for KW, KT, and HKW (R² = 12.4%, 5.13%, and 6.92%, respectively) in the K22 × CI7 population. C, Number of overlapped QTLs or SNPs identified with three methods. Blue numbers are for SLM, red for GWAS, and green for JLM. For example, 102/75/116 means that 102 QTLs identified with the SLM model overlapped with 75 QTLs identified with the JLM model and 116 SNPs from the GWAS model.

Figure 3.

Comparative analysis of QTLs and genes identified from maize mutant studies or based on rice seed size or weight genes. A total of 21 rice genes (18 from this study and GS3, GW2, and GS5 from previous studies; shown in red) and 36 maize genes (shown in blue) reported to be involved in maize kernel development in mutant studies are shown. Points with different color and shape indicate that genes were significantly associated with maize kernel size or weight by different methods. The heat map in the chromosome region indicates the density of QTLs for kernel traits (see scale at bottom right). The window size is 1 Mb.

Figure 4.

ZmINCW1 was significantly associated with maize kernel development. A, ZmINCW1 is located in the QTLs identified in the B73 × BY804 population for kernel size and weight. 12YN, Yunnan province in 2012; 11DHN, Hainan province in 2011. The arrow indicates the position of ZmINCW1. B, SNPs in ZmINCW1 were significantly associated with kernel size and weight in an association panel. C, GWAS of the expression level of ZmINCW1. The red points indicate the SNPs located in ZmINCW1. D, The expression level of ZmINCW1 was significantly positively correlated with HKW in 2011 Yunnan (n = 292, r = 0.16, P = 7.30 × 10⁻³).

Figure 5.

Overexpression of ZmINCW1 rescues the reduced thousand seed weight in the Arabidopsis AtcwINV2 T-DNA mutant. A and B, The T-DNA was inserted into the fourth exon of AtcwINV2, and three primers were used to confirm the insertion (F + R and P + R). C and D, Both the wild type (C) and the T-DNA insertion mutant (D) had normal seeds. Bars = 1 mm. E, The T-DNA insertion mutant had decreased thousand seed weight (TSW) compared with the wild type (WT; n = 20/32, P = 7.34 × 10⁻⁶). F and G, The expression levels of ZmINCW1 in Arabidopsis were confirmed by reverse transcription-PCR (F) and western blot (G). H and I, Both negative (H) and positive (I) transgenic lines had normal seeds. Bars = 1 mm. J, T1 positive transgenic lines had increased thousand seed weight compared with negative transgenic lines (n = 6/26, P = 1.51× 10⁻¹²). The combined result is shown in E. K, There was a significant difference in thousand seed weight between positive lines and negative lines in the T2 generation (n = 6/5, P = 0.03). **, P < 0.01 and *, P < 0.05.