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Genome-wide dissection of changes in maize root system architecture during modern breeding

Abstract

Appropriate root system architecture (RSA) can improve maize yields in densely planted fields, but little is known about its genetic basis in maize. Here we performed root phenotyping of 14,301 field-grown plants from an association mapping panel to study the genetic architecture of maize RSA. A genome-wide association study identified 81 high-confidence RSA-associated candidate genes and revealed that 28 (24.3%) of known root-related genes were selected during maize domestication and improvement. We found that modern maize breeding has selected for a steeply angled root system. Favourable alleles related to steep root system angle have continuously accumulated over the course of modern breeding, and our data pinpoint the root-related genes that have been selected in different breeding eras. We confirm that two auxin-related genes, ZmRSA3.1 and ZmRSA3.2, contribute to the regulation of root angle and depth in maize. Our genome-wide identification of RSA-associated genes provides new strategies and genetic resources for breeding maize suitable for high-density planting.

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Fig. 1: Changes in RSA over the course of Chinese maize breeding.
Fig. 2: GWAS identification of candidate genes for variation in maize root traits.
Fig. 3: Profiling of selective sweeps during maize domestication, improvement and modern breeding.
Fig. 4: The role of favourable alleles in the maize breeding process.
Fig. 5: Validation of two candidate genes associated with RSA.
Fig. 6: Genes that have been reported to affect the development of maize roots.

Data availability

Data supporting the findings of this work are available within the paper and its Supplementary Information. The genotype set, population structure and kinship data can be downloaded from the Maizego website (http://www.maizego.org/Resources.html). All root phenotype data for the 380 inbred maize lines are included in Supplementary Table 25. The RNA-sequencing reads used to construct the co-expression network and the root transcriptome sequencing reads were deposited in the NCBI Sequence Read Archive (https://www.ncbi.nlm.nih.gov/) under accession codes PRJNA694491 and PRJNA693427, respectively. Source data are provided with this paper.

Code availability

All scripts for GWAS, co-expression network analysis, selective sweep detection for domestication and improvement, and obtaining aligned sequences of high-priority candidate genes and known root-related genes (https://doi.org/10.5281/zenodo.7112683) are available on Zenodo.

References

  1. Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260–20264 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Duvick, D. N. The contribution of breeding to yield advances in maize (Zea mays L.). Adv. Agron. 86, 83–145 (2005).

    Article  Google Scholar 

  3. Tian, J. et al. Teosinte ligule allele narrows plant architecture and enhances high-density maize yields. Science 365, 658–664 (2019).

    Article  CAS  PubMed  Google Scholar 

  4. Wang, B. et al. Genome-wide selection and genetic improvement during modern maize breeding. Nat. Genet. 52, 565–571 (2020).

    Article  PubMed  Google Scholar 

  5. Hochholdinger, F. Untapping root system architecture for crop improvement. J. Exp. Bot. 67, 4431–4433 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Lynch, J. P. Root phenotypes for improved nutrient capture: an underexploited opportunity for global agriculture. N. Phytol. 223, 548–564 (2019).

    Article  Google Scholar 

  7. Lynch, J. P. Steep, cheap and deep: an ideotype to optimize water and N acquisition by maize root systems. Ann. Bot. 112, 347–357 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Mi, G., Chen, F., Yuan, L. & Zhang, F. Ideotype root system architecture for maize to achieve high yield and resource use efficiency in intensive cropping systems. Adv. Agron. 139, 73–97 (2016).

    Article  Google Scholar 

  9. Thorup-Kristensen, K. et al. Digging deeper for agricultural resources, the value of deep rooting. Trends Plant Sci. 25, 406–417 (2020).

    Article  CAS  PubMed  Google Scholar 

  10. Shao, H. et al. Genotypic difference in the plasticity of root system architecture of field-grown maize in response to plant density. Plant Soil 439, 201–217 (2019).

    Article  CAS  Google Scholar 

  11. Gamuyao, R. et al. The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency. Nature 488, 535–539 (2012).

    Article  CAS  PubMed  Google Scholar 

  12. Uga, Y. et al. Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions. Nat. Genet. 45, 1097–1102 (2013).

    Article  CAS  PubMed  Google Scholar 

  13. Kirschner, G. K. et al. ENHANCED GRAVITROPISM 2 encodes a STERILE ALPHA MOTIF-containing protein that controls root growth angle in barley and wheat. Proc. Natl Acad. Sci. USA 118, e2101526118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Bray, A. L. & Topp, C. N. The quantitative genetic control of root architecture in maize. Plant Cell Physiol. 59, 1919–1930 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Hochholdinger, F., Yu, P. & Marcon, C. Genetic control of root system development in maize. Trends Plant Sci. 23, 79–88 (2018).

    Article  CAS  PubMed  Google Scholar 

  16. Zhang, X. M. et al. Genetic variation in ZmTIP1 contributes to root hair elongation and drought tolerance in maize. Plant Biotechnol. J. 18, 1271–1283 (2020).

    Article  CAS  PubMed  Google Scholar 

  17. Schneider, H. M. et al. Root angle in maize influences nitrogen capture and is regulated by calcineurin B-like protein (CBL)-interacting serine/threonine-protein kinase 15 (ZmCIPK15). Plant Cell Environ. 45, 837–853 (2022).

    Article  CAS  PubMed  Google Scholar 

  18. Schneider, H. M. et al. Genetic control of root architectural plasticity in maize. J. Exp. Bot. 71, 3185–3197 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zheng, Z. et al. Shared genetic control of root system architecture between Zea mays and Sorghum bicolor. Plant Physiol. 182, 977–991 (2020).

    Article  CAS  PubMed  Google Scholar 

  20. Chen, Z. et al. Plasticity of root anatomy during domestication of a maize-teosinte derived population. J. Exp. Bot. 73, 139–153 (2022).

    Article  CAS  PubMed  Google Scholar 

  21. Burton, A. L., Brown, K. M. & Lynch, J. P. Phenotypic diversity of root anatomical and architectural traits in Zea species. Crop Sci. 53, 1042–1055 (2013).

    Article  Google Scholar 

  22. Gaudin, A. C. M., McClymont, S. A., Soliman, S. S. M. & Raizada, M. N. The effect of altered dosage of a mutant allele of Teosinte branched 1 (tb1-ref) on the root system of modern maize. BMC Genet. 15, 23 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Perkins, A. C. & Lynch, J. P. Increased seminal root number associated with domestication improves nitrogen and phosphorus acquisition in maize seedlings. Ann. Bot. 128, 453–468 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Wang, H. et al. Natural variation and domestication selection of ZmCKX5 with root morphological traits at the seedling stage in maize. Plants 10, 1 (2021).

    Article  Google Scholar 

  25. Gaudin, A. C. M., McClymont, S. A. & Raizada, M. N. The nitrogen adaptation strategy of the wild teosinte ancestor of modern maize, Zea mays subsp. parviglumis. Crop Sci. 51, 2780–2795 (2011).

    Article  CAS  Google Scholar 

  26. Gao, K., Chen, F., Yuan, L., Zhang, F. & Mi, G. A comprehensive analysis of root morphological changes and nitrogen allocation in maize in response to low nitrogen stress. Plant Cell Environ. 38, 740–750 (2015).

    Article  CAS  PubMed  Google Scholar 

  27. Mano, Y. et al. Variation for root aerenchyma formation in flooded and non-flooded maize and teosinte seedlings. Plant Soil 281, 269–279 (2006).

    Article  CAS  Google Scholar 

  28. Ning, P., Li, S., Li, X. & Li, C. New maize hybrids had larger and deeper post-silking root than old ones. Field Crop Res. 166, 66–71 (2014).

    Article  Google Scholar 

  29. Chen, X. et al. Changes in root size and distribution in relation to nitrogen accumulation during maize breeding in China. Plant Soil 374, 121–130 (2014).

    Article  CAS  Google Scholar 

  30. Mano, Y. & Omori, F. Flooding tolerance in interspecific introgression lines containing chromosome segments from teosinte (Zea nicaraguensis) in maize (Zea mays subsp. mays). Ann. Bot. 112, 1125–1139 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Wang, H., Studer, A. J., Zhao, Q., Meeley, R. & Doebley, J. F. Evidence that the origin of naked kernels during maize domestication was caused by a single amino acid substitution in tga1. Genetics 200, 965–974 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Li, Z. et al. Enhancing auxin accumulation in maize root tips improves root growth and dwarfs plant height. Plant Biotechnol. J. 16, 86–99 (2018).

    Article  CAS  PubMed  Google Scholar 

  33. Zhao, Y. et al. The interaction between rice ERF3 and WOX11 promotes crown root development by regulating gene expression involved in cytokinin signaling. Plant Cell 27, 2469–2483 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Asim, M., Ullah, Z., Oluwaseun, A., Wang, Q. & Liu, H. B. Signalling overlaps between nitrate and auxin in regulation of the root system architecture: insights from the Arabidopsis thaliana. Int. J. Mol. Sci. 21, 2880 (2020).

    Article  CAS  PubMed Central  Google Scholar 

  35. Woll, K. et al. Isolation, characterization, and pericycle-specific transcriptome analyses of the novel maize lateral and seminal root initiation mutant rum1. Plant Physiol. 139, 1255–1267 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. von Behrens, I. et al. Rootless with undetectable meristem 1 encodes a monocot-specific AUX/IAA protein that controls embryonic seminal and post-embryonic lateral root initiation in maize. Plant J. 66, 341–353 (2011).

    Article  Google Scholar 

  37. Tang, J. et al. Genetic dissection of plant height by molecular markers using a population of recombinant inbred lines in maize. Euphytica 155, 117–124 (2007).

    Article  CAS  Google Scholar 

  38. Li, H. et al. Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels. Nat. Genet. 45, 43–50 (2013).

    Article  CAS  PubMed  Google Scholar 

  39. Wen, T. J., Hochholdinger, F., Sauer, M., Bruce, W. & Schnable, P. S. The roothairless1 gene of maize encodes a homolog of sec3, which is involved in polar exocytosis. Plant Physiol. 138, 1637–1643 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Huang, P. et al. Sparse panicle1 is required for inflorescence development in Setaria viridis and maize. Nat. Plants 3, 17054 (2017).

    Article  CAS  PubMed  Google Scholar 

  41. Rademacher, E. H. et al. Different auxin response machineries control distinct cell fates in the early plant embryo. Dev. Cell 22, 211–222 (2012).

    Article  CAS  PubMed  Google Scholar 

  42. Rinaldi, M. A., Liu, J., Enders, T. A., Bartel, B. & Strader, L. C. A gain-of-function mutation in IAA16 confers reduced responses to auxin and abscisic acid and impedes plant growth and fertility. Plant Mol. Biol. 79, 359–373 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Huang, J. et al. Formin homology 1 (OsFH1) regulates root-hair elongation in rice (Oryza sativa). Planta 237, 1227–1239 (2013).

    Article  CAS  PubMed  Google Scholar 

  44. Kitomi, Y., Inahashi, H., Takehisa, H., Sato, Y. & Inukai, Y. OsIAA13-mediated auxin signaling is involved in lateral root initiation in rice. Plant Sci. 190, 116–122 (2012).

    Article  CAS  PubMed  Google Scholar 

  45. Chen, H., Patterson, N. & Reich, D. Population differentiation as a test for selective sweeps. Genome Res. 20, 393–402 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Hufford, M. B. et al. Comparative population genomics of maize domestication and improvement. Nat. Genet. 44, 808–811 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Chen, Q. et al. The genetic architecture of the maize progenitor, teosinte, and how it was altered during maize domestication. PLoS Genet. 16, e1008791 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Wang, Y., Deng, D., Bian, Y., Lv, Y. & Xie, Q. Genome-wide analysis of primary auxin-responsive Aux/IAA gene family in maize (Zea mays. L.). Mol. Biol. Rep. 37, 3991–4001 (2010).

    Article  CAS  PubMed  Google Scholar 

  49. Rosero, A. et al. Arabidopsis FH1 formin affects cotyledon pavement cell shape by modulating cytoskeleton dynamics. Plant Cell Physiol. 57, 488–504 (2016).

    Article  CAS  PubMed  Google Scholar 

  50. Shi, J. et al. Ectopic expression of ARGOS8 reveals a role for ethylene in root-lodging resistance in maize. Plant J. 97, 378–390 (2019).

    Article  CAS  PubMed  Google Scholar 

  51. Evans, M. M. & Poethig, R. S. Gibberellins promote vegetative phase change and reproductive maturity in maize. Plant Physiol. 108, 475–487 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Trachsel, S., Kaeppler, S. M., Brown, K. M. & Lynch, J. P. Maize root growth angles become steeper under low N conditions. Field Crop Res 140, 18–31 (2013).

    Article  Google Scholar 

  53. Kell, D. B. Breeding crop plants with deep roots: their role in sustainable carbon, nutrient and water sequestration. Ann. Bot. 108, 407–418 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Hund, A., Reime, R. & Messmer, R. A consensus map of QTLs controlling the root length of maize. Plant Soil 344, 143–158 (2011).

    Article  CAS  Google Scholar 

  55. Schaefer, R. J. et al. Integrating coexpression networks with GWAS to prioritize causal genes in maize. Plant Cell 30, 2922–2942 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. York, L. M., Galindo-Castaneda, T., Schussler, J. R. & Lynch, J. P. Evolution of US maize (Zea mays L.) root architectural and anatomical phenes over the past 100 years corresponds to increased tolerance of nitrogen stress. J. Exp. Bot. 66, 2347–2358 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Chen, F. et al. Breeding for high-yield and nitrogen use efficiency in maize: lessons from comparison between Chinese and US cultivars. Adv. Agron. 166, 251–275 (2021).

    Article  Google Scholar 

  58. Xu, C. et al. Cooperative action of the paralogous maize lateral organ boundaries (LOB) domain proteins RTCS and RTCL in shoot-borne root formation. N. Phytol. 207, 1123–1133 (2015).

    Article  CAS  Google Scholar 

  59. Suzuki, M., Sato, Y., Wu, S., Kang, B. H. & McCarty, D. R. Conserved functions of the MATE transporter BIG EMBRYO1 in regulation of lateral organ size and initiation rate. Plant Cell 27, 2288–2300 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Zhang, Y. et al. LATERAL ROOT PRIMORDIA 1 of maize acts as a transcriptional activator in auxin signalling downstream of the Aux/IAA gene rootless with undetectable meristem 1. J. Exp. Bot. 66, 3855–3863 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Taramino, G. et al. The maize (Zea mays L.) RTCS gene encodes a LOB domain protein that is a key regulator of embryonic seminal and post-embryonic shoot-borne root initiation. Plant J. 50, 649–659 (2007).

    Article  CAS  PubMed  Google Scholar 

  62. Zhang, M. et al. Auxin efflux carrier ZmPGP1 mediates root growth inhibition under aluminum stress. Plant Physiol. 177, 819–832 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Benjamins, R. & Scheres, B. Auxin: the looping star in plant development. Annu Rev. Plant Biol. 59, 443–465 (2008).

    Article  CAS  PubMed  Google Scholar 

  64. Ikeda, Y. et al. Local auxin biosynthesis modulates gradient-directed planar polarity in Arabidopsis. Nat. Cell Biol. 11, 731–738 (2009).

    Article  CAS  PubMed  Google Scholar 

  65. Lanza, M. et al. Role of actin cytoskeleton in brassinosteroid signaling and in its integration with the auxin response in plants. Dev. Cell 22, 1275–1285 (2012).

    Article  CAS  PubMed  Google Scholar 

  66. Banno, H. & Chua, N. H. Characterization of the arabidopsis formin-like protein AFH1 and its interacting protein. Plant Cell Physiol. 41, 617–626 (2000).

    Article  CAS  PubMed  Google Scholar 

  67. Martiniere, A., Gayral, P., Hawes, C. & Runions, J. Building bridges: formin1 of Arabidopsis forms a connection between the cell wall and the actin cytoskeleton. Plant J. 66, 354–365 (2011).

    Article  CAS  PubMed  Google Scholar 

  68. Li, G. et al. Rice actin-binding protein RMD is a key link in the auxin–actin regulatory loop that controls cell growth. Proc. Natl Acad. Sci. USA 111, 10377–10382 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Ogura, T. et al. Root system depth in Arabidopsis Is shaped by EXOCYST70A3 via the dynamic modulation of auxin transport. Cell 178, 400–412 (2019).

    Article  CAS  PubMed  Google Scholar 

  70. Yang, P. et al. Light modulates the gravitropic responses through organ-specific PIFs and HY5 regulation of LAZY4 expression in Arabidopsis. Proc. Natl Acad. Sci. USA 117, 18840–18848 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Yang, X. et al. Characterization of a global germplasm collection and its potential utilization for analysis of complex quantitative traits in maize. Mol. Breed. 28, 511–526 (2011).

    Article  Google Scholar 

  72. Trachsel, S., Kaeppler, S. M., Brown, K. M. & Lynch, J. P. Shovelomics: high throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant Soil 341, 75–87 (2010).

    Article  Google Scholar 

  73. Das, A. et al. Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics. Plant Methods 11, 51 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Colombi, T. et al. Next generation shovelomics: set up a tent and REST. Plant Soil 388, 1–20 (2015).

    Article  CAS  Google Scholar 

  75. Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  76. Fu, J. et al. RNA sequencing reveals the complex regulatory network in the maize kernel. Nat. Commun. 4, 2832 (2013).

    Article  PubMed  Google Scholar 

  77. Unterseer, S. et al. A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array. BMC Genomics 15, 823 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  78. Ganal, M. W. et al. A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. PLoS ONE 6, e28334 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Elshire, R. J. et al. A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 6, e19379 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Liu, H. J. et al. MODEM: multi-omics data envelopment and mining in maize. Database 2016, baw117 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Yu, J. et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 38, 203–208 (2006).

    Article  CAS  PubMed  Google Scholar 

  82. Zhang, Z. et al. Mixed linear model approach adapted for genome-wide association studies. Nat. Genet. 42, 355–360 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet 81, 559–575 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Pertea, M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 33, 290–295 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Maere, S., Heymans, K. & Kuiper, M. BiNGO: a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in biological networks. Bioinformatics 21, 3448–3449 (2005).

    Article  CAS  PubMed  Google Scholar 

  88. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Gui, S. et al. ZEAMAP, a comprehensive database adapted to the maize multi-omics era. iScience 23, 101241 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Mikheenko, A., Prjibelski, A., Saveliev, V., Antipov, D. & Gurevich, A. Versatile genome assembly evaluation with QUAST-LG. Bioinformatics 34, i142–i150 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Nakamura, T., Yamada, K. D., Tomii, K. & Katoh, K. Parallelization of MAFFT for large-scale multiple sequence alignments. Bioinformatics 34, 2490–2492 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Ishida, Y., Hiei, Y. & Komari, T. Agrobacterium-mediated transformation of maize. Nat. Protoc. 2, 1614–1621 (2007).

    Article  CAS  PubMed  Google Scholar 

  96. Wang, B. et al. Tryptophan-independent auxin biosynthesis contributes to early embryogenesis in Arabidopsis. Proc. Natl Acad. Sci. USA 112, 4821–4826 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Tan, H. et al. A crucial role of GA-regulated flavonol biosynthesis in root growth of Arabidopsis. Mol. Plant 12, 521–537 (2019).

    Article  CAS  PubMed  Google Scholar 

  98. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This study was financially supported by the National Key Research and Development Program of China (grant nos. 2021YFF1000500 (Q.P.), 2021YFD1200700 (F.C.) and 2016YFD0100700 (L.Y.)), the National Natural Science Foundation of China (grant nos. 31972485 (F.C.) and 31971948 (Q.P.)), the Hainan Natural Science Foundation Innovation Research Team Project (grant no. 321CXTD443 (F.C.)), the Hainan Provincial Science and Technology Plan Sanya Yazhou Bay Science and Technology City Joint Project (grant no. 320LH011 (Q.P.)) and the China Postdoctoral Science Foundation (grant no. 2021M693431 (W.R.)). The transgenic maize seeds were produced by the Center for Crop Functional Genomics and Molecular Breeding of China Agricultural University.

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Contributions

Q.P., L.Y. and F.C. conceived and designed the research. W.R., L.Z., J. Liang, L.W., P.L., Z.L., X.L., Z. Zhang and J. Li performed phenotypic measurements. W.R. and Q.P. performed the data analyses. L.C. performed plasmid construction and genetic transformation. W.R., K.H. and Z. Zhao characterized the transgenic overexpression lines. J.Y. provided the maize inbred lines and genotype set. W.R. and Q.P. wrote the manuscript. F.A., G.M., J.Y., F.Z., F.C., L.Y. and Q.P. revised the manuscript. All authors contributed to the final version of the paper.

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Correspondence to Fanjun Chen, Lixing Yuan or Qingchun Pan.

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Nature Plants thanks Yusaku Uga, Ana Letycia Basso Garcia, Ana Caño-Delgado and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Pearson correlations among eight root traits.

The red lines represent positive correlations, and the green lines represent negative correlations. The line width represents the strength of the correlation. Yellow lines indicate that the correlation coefficient was close to zero.

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Extended Data Fig. 2 Principal component analysis of eight root traits.

The red ellipse indicates the area-related traits; the yellow ellipse indicates the width-related traits; and the green ellipse indicates the angle-related traits.

Extended Data Fig. 3 Cluster analysis of 380 maize inbred lines based on root traits.

(a) Cluster analysis of 380 inbred lines based on ROA, RMEW, and AREA. (b) Representative inbred lines from the three clusters (groups 1–3). (c) Comparison of eight root traits among groups 1–3. (d) Comparison of eight root traits among four subpopulations. (e) Proportion of lines from each of four subgroups in the three cluster groups. The four subgroups (Mixed, SS, NSS, and TST) are based on genetic relationships among the different inbred lines. Mixed, mixed group; SS, stiff stalk group; NSS, non-stiff stalk group; TST, tropical and subtropical group.

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Supplementary Information

Supplementary Note and Figs. 1–19.

Reporting Summary

Supplementary Table 28

Supplementary Tables 1–28.

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Source Data Fig. 1

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Source Data Fig. 2

Statistical source data.

Source Data Fig. 4

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Source Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 1

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Source Data Extended Data Fig. 3

Statistical source data.

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Ren, W., Zhao, L., Liang, J. et al. Genome-wide dissection of changes in maize root system architecture during modern breeding. Nat. Plants (2022). https://doi.org/10.1038/s41477-022-01274-z

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