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Acta Agronomica Sinica ›› 2025, Vol. 51 ›› Issue (6): 1501-1513.doi: 10.3724/SP.J.1006.2025.43052

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Effect evaluation and investigation on molecular mechanism of the ZmKL1 favorable allele in regulating maize kernel size

YANG Xiao-Hui1,2(), YAN Xuan-Jun2,3, YANG Wen-Yan2, FU Jun-Jie2, YANG Qin1,*(), XIE Yu-Xin2,*()   

  1. 1College of Agronomy, Northwest A&F University / State Key Laboratory of Crop Stress Resistance and High-Efficiency Production / Key Laboratory of Maize Biology and Genetic Breeding in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, Yangling 712100, Shaanxi, China
    2Institute of Crop Sciences, Chinese Academy of Agricultural Sciences / State Key Laboratory of Crop Gene Resources and Breeding, Beijing 100081, China
    3College of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, Hainan, China
  • Received:2024-11-15 Accepted:2025-03-26 Online:2025-06-12 Published:2025-04-01
  • Contact: *E-mail: xieyuxin@caas.cn;E-mail: qyang@nwafu.edu.cn
  • Supported by:
    the National Natural Science Foundation of China(32101809);the Innovation Program of Chinese Academy of Agricultural Sciences.

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Abstract:

To evaluate the effects of different alleles of the kernel size-related gene ZmKL1 on agronomic traits and to elucidate the molecular mechanisms by which ZmKL1 regulates kernel size in maize, this study constructed near-isogenic lines (NILs) and analyzed their field performance, ear morphology, and kernel traits at two locations. Transcriptome and proteome analyses were conducted to explore the regulatory effects of different alleles on kernel size. The results revealed significant differences in kernel length, kernel width, hundred-kernel weight, plant height, and ear height among the NILs, while no significant differences were observed in flowering time or ear traits. A total of 744 differentially expressed genes (DEGs) and 152 differentially expressed proteins (DEPs) were identified between the two NIL groups. Gene Ontology (GO) analysis indicated that DEGs were enriched in pathways related to protein binding and oxidoreductase activity, while DEPs were primarily associated with transcriptional regulation, gene expression, RNA biosynthesis, and metabolic processes. The expression differences of eight key genes were further validated by quantitative real-time PCR (qRT-PCR). This study not only provides a comprehensive phenotypic assessment of ZmKL1 alleles, demonstrating the potential of the favorable allele for maize yield improvement, but also offers preliminary insights into the molecular mechanisms underlying ZmKL1-mediated kernel size regulation through integrative transcriptomic and proteomic analyses. These findings contribute to the identification of key genes and pathways involved in maize kernel development, laying the foundation for future genetic improvement strategies.

Key words: maize kernel, transcriptome, proteome, allele, near-isogenic line

Fig. 1

Construction of the near-isogenic line population A: allele sequencing diagram; B: flowchart for near-isogenic line construction; C: sequence alignment of ZmKL1 in NILs; D: sequence alignment of ZmKL1 protein in NILs. NIL1 represents the near-isogenic line with the insertion variation (CTCAG); NIL2 represents the near-isogenic line with the deletion variation (-----)."

Table 1

Primers used in the experiment"

引物名称
Primer name		 引物序列
Primer sequence (5'-3')		 引物用途
Primer usage
KL1-genomic-F1 GGTTGTACCACACCTGCCA 分段PCR Segmented PCR
KL1-genomic-R1 GGGGTACACCCAAAGGCT 分段PCR Segmented PCR
KL1-genomic-F2 TAGCTGTGCGTTCAAGTGGT 分段PCR Segmented PCR
KL1-genomic-R2 CGCCGCCAGGATTTGTTG 分段PCR Segmented PCR
Zm00001d000023-F GGCAAATGTCTGATGTGCAGGAGG 实时荧光定量PCR qRT-PCR
Zm00001d000023-R GCCCTTATTGCTCCAGCAAGAGG 实时荧光定量PCR qRT-PCR
Zm00001d010525-F CCTGGTGCAACACCACTAGAGAG 实时荧光定量PCR qRT-PCR
Zm00001d010525-R TTCTGCTCTCCTCGCGCCAAT 实时荧光定量PCR qRT-PCR
Zm00001d010640-F CAAGGCACGAATCCACGCCGA 实时荧光定量PCR qRT-PCR
Zm00001d010640-R GAGGGAAACGAGCCCACAGAGC 实时荧光定量PCR qRT-PCR
Zm00001d013193-F CTTCAGCTCCAGCCGCAGCAT 实时荧光定量PCR qRT-PCR
Zm00001d013193-R CTGCAGCACTCATCGCCTTCG 实时荧光定量PCR qRT-PCR
Zm00001d034160-F GAGCCTCGAGGAGGAGCGCC 实时荧光定量PCR qRT-PCR
Zm00001d034160-R GTCGTCGGCCTTGGCCTCCG 实时荧光定量PCR qRT-PCR
Zm00001d044104-F TGTTCCACACCTCCGCCTTCGT 实时荧光定量PCR qRT-PCR
Zm00001d044104-R CCTCCACACACATGCCAGCAAG 实时荧光定量PCR qRT-PCR
Zm00001d044156-F TGTAGCCATGACGTCGTTCCCC 实时荧光定量PCR qRT-PCR
Zm00001d044156-R CGTGAACTTCTCGAAGTGGCCAAAC 实时荧光定量PCR qRT-PCR
Zm00001d051938-F TGCACATGGACCCCAGCCGGA 实时荧光定量PCR qRT-PCR
Zm00001d051938-R CGCCGTCACCTCCGCCATCAT 实时荧光定量PCR qRT-PCR
ZmActin-F ATGGTCAAGGCCGGTTTCG 实时荧光定量PCR qRT-PCR
ZmActin-R TCAGGATGCCTCTCTTGGCC 实时荧光定量PCR qRT-PCR

Fig. 2

Evaluation of grain phenotypes in natural populations A-C represent the statistical data analysis results for grain length, grain width, and hundred-kernel weight, respectively. *: P < 0.05; ***: P < 0.001; Student’s t-test. Hap1 represents the haplotype with the insertion variation (CTCAG); Hap2 represents the haplotype with the deletion variation (-----)."

Fig. 3

Field phenotype identification of near-isogenic lines (A-E), spike phenotype identification (F-I), and spike phenotype (J) BJ: Beijing; LF: Langfang. *: P < 0.05, ****: P < 0.0001; ns: no significance. Student’s t-test. NIL1 represents the near-isogenic line with the insertion variation (CTCAG); NIL2 represents the near-isogenic line with the deletion variation (-----). Scale bar: 1 cm."

Fig. 4

Phenotypic identification of grain traits in near-isogenic lines A-C represent the measurement charts for grain length, grain width, and hunderd-kernel weight, respectively. D-F are the statistical data analysis results for grain length, grain width, and hunderd-kernel weight. BJ: Beijing; LF: Langfang. ***: P < 0.001, ****: P < 0.0001, Student’s t-test. Scale bar: 1 cm. NIL1 represents the near-isogenic line with the insertion variation (CTCAG); NIL2 represents the near-isogenic line with the deletion variation (-----)."

Fig. 5

Paraffin section images of NIL1 and NIL2 at 10 days (A, B) and 15 days (C, D) after pollination Scale bar: 1 mm."

Fig. 6

Transcriptome analysis of NILs A: volcano plot of differentially expressed genes in NIL1 and NIL2; B: GO analysis plot of differentially expressed genes."

Fig. 7

Proteomic analysis of NILs A: peptide length distribution chart; B: protein molecular weight and isoelectric point distribution chart; C: volcano plot of differentially expressed proteins between NIL1 and NIL2; D: BP enrichment bubble chart of differentially expressed proteins (Top 20)."

Fig. 8

Joint analysis of transcriptome and proteome A: venn diagram of differentially expressed genes and differentially expressed proteins; B: correlation graph of differentially expressed genes and differentially expressed proteins. DEGs: differentially expressed genes; DAPs: differentially expressed proteins."

Fig. 9

qPCR validation analysis of differentially expressed genes Student’s t-test, **: P < 0.01; ***: P < 0.001; ****: P < 0.0001."

[1] Li X P, Zhou Z J, Ding J Q, Wu Y B, Zhou B, Wang R X, Ma J L, Wang S W, Zhang X C, Xia Z L, et al. Combined linkage and association mapping reveals QTL and candidate genes for plant and ear height in maize. Front Plant Sci, 2016, 7: 833.
doi: 10.3389/fpls.2016.00833 pmid: 27379126
[2] Lu X D, Liu J S, Ren W, Yang Q, Chai Z G, Chen R M, Wang L, Zhao J, Lang Z H, Wang H Y, et al. Gene-indexed mutations in maize. Mol Plant, 2018, 11: 496-504.
doi: S1674-2052(17)30368-4 pmid: 29223623
[3] Liang L, Zhou L, Tang Y P, Li N K, Song T, Shao W, Zhang Z R, Cai P, Feng F, Ma Y F, et al. A sequence-indexed Mutator insertional library for maize functional genomics study. Plant Physiol, 2019, 181: 1404-1414.
doi: 10.1104/pp.19.00894 pmid: 31636104
[4] Dai D W, Ma Z Y, Song R T.Maize kernel development. Mol Breed, 2021, 41: 2.
[5] Cai M J, Li S Z, Sun F, Sun Q, Zhao H L, Ren X M, Zhao Y X, Tan B C, Zhang Z X, Qiu F Z. Emp10 encodes a mitochondrial PPR protein that affects the Cis-splicing of nad2 intron 1 and seed development in maize. Plant J, 2017, 91: 132-144.
[6] Ren X M, Pan Z Y, Zhao H L, Zhao J L, Cai M J, Li J, Zhang Z X, Qiu F Z. EMPTY PERICARP11 serves as a factor for splicing of mitochondrial nad1 intron and is required to ensure proper seed development in maize. J Exp Bot, 2017, 68: 4571-4581.
doi: 10.1093/jxb/erx212 pmid: 28981788
[7] Li X J, Zhang Y F, Hou M M, Sun F, Shen Y, Xiu Z H, Wang X M, Chen Z L, Sun S S M, Small I, et al. Small kernel 1 encodes a pentatricopeptide repeat protein required for mitochondrial nad7 transcript editing and seed development in maize (Zea mays) and rice (Oryza sativa). Plant J, 2014, 79: 797-809.
[8] Xu C H, Song S, Yang Y Z, Lu F, Zhang M D, Sun F, Jia R X, Song R L, Tan B C. DEK46 performs C-to-U editing of a specific site in mitochondrial nad7 introns that is critical for intron splicing and seed development in maize. Plant J, 2020, 103: 1767-1782.
[9] Gao J, Zhang L, Du H N, Dong Y B, Zhen S H, Wang C, Wang Q L, Yang J Y, Zhang P F, Zheng X, et al. An ARF24-ZmArf2 module influences kernel size in different maize haplotypes. J Integr Plant Biol, 2023, 65: 1767-1781.
[10] Qi W W, Zhu J, Wu Q, Wang Q, Li X, Yao D S, Jin Y, Wang G, Wang G F, Song R T. Maize reas1 mutant stimulates ribosome use efficiency and triggers distinct transcriptional and translational responses. Plant Physiol, 2016, 170: 971-988.
doi: 10.1104/pp.15.01722 pmid: 26645456
[11] Wang H Q, Wang K, Du Q G, Wang Y F, Fu Z Y, Guo Z Y, Kang D M, Li W X, Tang J H. Maize Urb2 protein is required for kernel development and vegetative growth by affecting pre-ribosomal RNA processing. New Phytol, 2018, 218: 1233-1246.
doi: 10.1111/nph.15057 pmid: 29479724
[12] Pang J L, Fu J J, Zong N, Wang J, Song D D, Zhang X, He C, Fang T, Zhang H W, Fan Y L, et al. Kernel size-related genes revealed by an integrated eQTL analysis during early maize kernel development. Plant J, 2019, 98: 19-32.
[13] Chen L, Li Y X, Li C H, Shi Y S, Song Y C, Zhang D F, Wang H Y, Li Y, Wang T Y. The retromer protein ZmVPS29 regulates maize kernel morphology likely through an auxin-dependent process(es). Plant Biotechnol J, 2020, 18: 1004-1014.
doi: 10.1111/pbi.13267 pmid: 31553822
[14] Yang N, Liu J, Gao Q, Gui S T, Chen L, Yang L F, Huang J, Deng T Q, Luo J Y, He L J, et al. Genome assembly of a tropical maize inbred line provides insights into structural variation and crop improvement. Nat Genet, 2019, 51: 1052-1059.
doi: 10.1038/s41588-019-0427-6 pmid: 31152161
[15] Sun Q, Li Y F, Gong D M, Hu A Q, Zhong W S, Zhao H L, Ning Q, Tan Z D, Liang K, Mu L Y, et al. A NAC-EXPANSIN module enhances maize kernel size by controlling nucellus elimination. Nat Commun, 2022, 13: 5708.
doi: 10.1038/s41467-022-33513-4 pmid: 36175574
[16] Zhang Q L, Wu R H, Hong T, Wang D C, Li Q L, Wu J Y, Zhang H, Zhou K, Yang H X, Zhang T, et al. Natural variation in the promoter of qRBG1/OsBZR5 underlies enhanced rice yield. Nat Commun, 2024, 15: 8565.
doi: 10.1038/s41467-024-52928-9 pmid: 39362889
[17] Li Y X, Lu J W, He C, Wu X, Cui Y, Chen L, Zhang J, Xie Y X, An Y X, Liu X Y, et al. Cis-regulatory variation affecting gene expression contributes to the improvement of maize kernel size. Plant J, 2022, 111: 1595-1608.
[18] Fu J J, Cheng Y B, Linghu J J, Yang X H, Kang L, Zhang Z X, Zhang J, He C, Du X M, Peng Z Y, et al. RNA sequencing reveals the complex regulatory network in the maize kernel. Nat Commun, 2013, 4: 2832.
doi: 10.1038/ncomms3832 pmid: 24343161
[19] Lister R, O’Malley R C, Tonti-Filippini J, Gregory B D, Berry C C, Harvey Millar A, Ecker J R.Highly integrated single-base resolution maps of the epigenome in Arabidopsis. Cell, 2008, 133: 523-536.
doi: 10.1016/j.cell.2008.03.029 pmid: 18423832
[20] Stark R, Grzelak M, Hadfield J.RNA sequencing: the teenage years. Nat Rev Genet, 2019, 20: 631-656.
doi: 10.1038/s41576-019-0150-2 pmid: 31341269
[21] Rehman A, Rehman S U, Khatoon A, Qasim M, Itoh T, Iwasaki Y, Wang X, Sunohara Y, Matsumoto H, Komatsu S. Proteomic analysis of the promotive effect of plant-derived smoke on plant growth of chickpea. J Proteomics, 2018, 176: 56-70.
doi: S1874-3919(18)30042-3 pmid: 29391210
[22] Meyer R R, Laine P S. The single-stranded DNA-binding protein of Escherichia coli. Microbiol Rev, 1990, 54: 342-380.
doi: 10.1128/mr.54.4.342-380.1990 pmid: 2087220
[23] Maffeo C, Aksimentiev A. Molecular mechanism of DNA association with single-stranded DNA binding protein. Nucleic Acids Res, 2017, 45: 12125-12139.
[24] Maier D, Farr C L, Poeck B, Alahari A, Vogel M, Fischer S, Kaguni L S, Schneuwly S.Mitochondrial single-stranded DNA- binding protein is required for mitochondrial DNA replication and development in Drosophila melanogaster. Mol Biol Cell, 2001, 12: 821-830.
pmid: 11294889
[25] Ruhanen H, Borrie S, Szabadkai G, Tyynismaa H, Jones A W E, Kang D, Taanman J W, Yasukawa T. Mitochondrial single- stranded DNA binding protein is required for maintenance of mitochondrial DNA and 7S DNA but is not required for mitochondrial nucleoid organisation. Biochim Biophys Acta, 2010, 1803: 931-939.
doi: 10.1016/j.bbamcr.2010.04.008 pmid: 20434493
[26] Radulovic M, Crane E, Crawford M, Godovac-Zimmermann J, Yu V P C C. CKS proteins protect mitochondrial genome integrity by interacting with mitochondrial single-stranded DNA-binding protein. Mol Cell Proteom, 2010, 9: 145-152.
[27] Edmondson A C, Song D Q, Alvarez L A, Wall M K, Almond D, McClellan D A, Maxwell A, Nielsen B L.Characterization of a mitochondrially targeted single-stranded DNA-binding protein in Arabidopsis thaliana. Mol Genet Genomics, 2005, 273: 115-122.
doi: 10.1007/s00438-004-1106-5 pmid: 15744502
[28] Li D Q, Wu X B, Wang H F, Feng X, Yan S J, Wu S Y, Liu J X, Yao X F, Bai A N, Zhao H, et al. Defective mitochondrial function by mutation in THICK ALEURONE 1 encoding a mitochondrion-targeted single-stranded DNA-binding protein leads to increased aleurone cell layers and improved nutrition in rice. Mol Plant, 2021, 14: 1343-1361.
[29] Kozłowski J. Optimal allocation of resources to growth and reproduction: Implications for age and size at maturity. Trends Ecol Evol, 1992, 7: 15-19.
doi: 10.1016/0169-5347(92)90192-E pmid: 21235937
[30] Kumar N V, Varshney U. Contrasting effects of single stranded DNA binding protein on the activity of uracil DNA glycosylase from Escherichia coli towards different DNA substrates. Nucleic Acids Res, 1997, 25: 2336-2343.
pmid: 9171083
[31] Selinski J, König N, Wellmeyer B, Hanke G T, Linke V, Ekkehard Neuhaus H, Scheibe R. The plastid-localized NAD-dependent malate dehydrogenase is crucial for energy homeostasis in developing Arabidopsis thaliana seeds. Mol Plant, 2014, 7: 170-186.
[32] Srivastava R, Li Z X, Russo G, Tang J, Bi R, Muppirala U, Chudalayandi S, Severin A, He M Z, Vaitkevicius S I, et al. Response to persistent ER stress in plants: a multiphasic process that transitions cells from prosurvival activities to cell death. Plant Cell, 2018, 30: 1220-1242.
[33] Yu Y J, Li J, Song B Y, Ma Z, Zhang Y F, Sun H N, Wei X S, Bai Y Y, Lu X G, Zhang P, et al. Polymeric PD-L1 blockade nanoparticles for cancer photothermal-immunotherapy. Biomaterials, 2022, 280: 121312.
[34] Li Y Q, Zhan P L, Pu R M, Xiang W Q, Meng X, Yang S Q, Hu G J, Zhao S, Han J L, Xia C, et al. Transcriptome analysis of potential regulatory genes under chemical doubling in maize haploids. Agronomy, 2024, 14: 624.
[35] Wang Y C, Xu J Y, Ge M, Ning L H, Hu M M, Zhao H. High-resolution profile of transcriptomes reveals a role of alternative splicing for modulating response to nitrogen in maize. BMC Genomics, 2020, 21: 353.
doi: 10.1186/s12864-020-6769-8 pmid: 32393171
[36] Guo S, Arshad A, Yang L, Qin Y S, Mu X H, Mi G H. Comparative transcriptome analysis reveals common and developmental stage-specific genes that respond to low nitrogen in maize leaves. Plants, 2022, 11: 1550.
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