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A mini foxtail millet with an Arabidopsis-like life cycle as a C4 model system

Nature Plants volume 6, pages 1167–1178 (2020)Cite this article

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Abstract

Foxtail millet (Setaria italica) is an important crop species and an emerging model plant for C4 grasses. However, functional genomics research on foxtail millet is challenging because of its long generation time, relatively large stature and recalcitrance to genetic transformation. Here we report the development of xiaomi, a rapid-cycling mini foxtail millet mutant as a C4 model system. Five to six generations of xiaomi can be grown in a year in growth chambers due to its short life cycle and small plant size, similar to Arabidopsis. A point mutation in the Phytochrome C (PHYC) gene was found to be causal for these characteristics. PHYC encodes a light receptor essential for photoperiodic flowering. A reference-grade xiaomi genome comprising 429.94 Mb of sequence was assembled and a gene-expression atlas from 11 different tissues was developed. These resources, together with an established highly efficient transformation system and a multi-omics database, make xiaomi an ideal model system for functional studies of C4 plants.

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Fig. 1: Phenotypic characterization of xiaomi.
Fig. 2: Molecular characterization of xiaomi.
Fig. 3: Circular plot of the xiaomi genome sequence compared with the Yugu1 genome.
Fig. 4: Expression pattern of the Si9g04830 gene.
Fig. 5: Agrobacterium-mediated transformation of xiaomi.
Fig. 6: Schematic of Agrobacterium-mediated transformation of xiaomi.

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Data availability

The genome assembly, annotation and expression data can be easily accessed at our Multi-omics Database for S. italica (MDSi) (http://sky.sxau.edu.cn/MDSi.htm). The genome assembly and annotation of xiaomi are also available at Genome Warehouse in the Beijing Institute of Genomics Data Center (https://bigd.big.ac.cn/) under accession number GWHAAZD00000000. The raw sequence data have been deposited in the Beijing Institute of Genomics Data Center with the following accession numbers: CRA001973 (Genome sequencing of xiaomi by PacBio), CRA001968 (Hi-C of xiaomi), CRA001972 (isoform sequencing of xiaomi), CRA001967 (Genome resequencing of xiaomi and Jingu21), CRA001953 (RNA-seq of 11 xiaomi tissues), CRA001954 (RNA-seq of the top second leaf of 30-day-old Jingu21), CRA001974 (non-coding RNAs), CRA002603 (genome resequencing of xiaomi-2) and CRA002604 (genome resequencing of 13 transgenic lines). The Yugu1 genome was downloaded from public database Phytozome (https://phytozome.jgi.doe.gov/pz/portal.html). The Zhanggu genome was downloaded from ftp://ftp.genomics.org.cn/pub/Foxtail_millet. Other data can be obtained from the public databases nr (https://ftp.ncbi.nlm.nih.gov/blast/db/FASTA/), KOG (ftp://ftp.ncbi.nih.gov/pub/COG/KOG/), KEGG (https://www.kegg.jp/), TrEMBL (https://www.ebi.ac.uk/uniprot), GO (http://geneontology.org/) and BUSCO embryophyta_odb9 dataset (http://busco.ezlab.org/datasets/embryophyta_odb9.tar.gz). All data and materials are available from the corresponding author upon request. Source data are provided with this paper.

References

  1. Provart, N. J. et al. 50 years of Arabidopsis research: highlights and future directions. N. Phytol. 209, 921–944 (2016).

    Article  CAS  Google Scholar 

  2. Brutnell, T. P., Bennetzen, J. L. & Vogel, J. P. Brachypodium distachyon and Setaria viridis: model genetic systems for the grasses. Annu. Rev. Plant Biol. 66, 465–485 (2015).

    Article  CAS  PubMed  Google Scholar 

  3. Doust, A. N., Kellogg, E. A., Devos, K. M. & Bennetzen, J. L. Foxtail millet: a sequence-driven grass model system. Plant Physiol. 149, 137–141 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Jia, G. et al. A haplotype map of genomic variations and genome-wide association studies of agronomic traits in foxtail millet (Setaria italica). Nat. Genet. 45, 957–961 (2013).

    Article  CAS  PubMed  Google Scholar 

  5. Bennetzen, J. L. et al. Reference genome sequence of the model plant Setaria. Nat. Biotechnol. 30, 555–561 (2012).

    Article  CAS  PubMed  Google Scholar 

  6. Brutnell, T. P. et al. Setaria viridis: a model for C4 photosynthesis. Plant Cell 22, 2537–2544 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Acharya, B. R. et al. Optimization of phenotyping assays for the model monocot Setaria viridis. Front. Plant Sci. 8, 2172 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Zhang, G. et al. Genome sequence of foxtail millet (Setaria italica) provides insights into grass evolution and biofuel potential. Nat. Biotechnol. 30, 549 (2012).

    Article  CAS  PubMed  Google Scholar 

  9. Tsai, K. J. et al. Assembling the Setaria italica L. Beauv. genome into nine chromosomes and insights into regions affecting growth and drought tolerance. Sci. Rep. 6, 35076 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Diao, X., Schnable, J., Bennetzen, J. L. & Li, J. Initiation of Setaria as a model plant. Front. Agr. Sci. Eng. 1, 16–20 (2014).

    Article  Google Scholar 

  11. Lata, C., Gupta, S. & Prasad, M. Foxtail millet: a model crop for genetic and genomic studies in bioenergy grasses. Crit. Rev. Biotechnol. 33, 328–343 (2013).

    Article  PubMed  Google Scholar 

  12. Li, P. & Brutnell, T. P. Setaria viridis and Setaria italica, model genetic systems for the Panicoid grasses. J. Exp. Bot. 62, 3031–3037 (2011).

    Article  CAS  PubMed  Google Scholar 

  13. Rockwell, N. C., Su, Y. S. & Lagarias, J. C. Phytochrome structure and signaling mechanisms. Annu. Rev. Plant Biol. 57, 837–858 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Hiei, Y. & Komari, T. Agrobacterium-mediated transformation of rice using immature embryos or calli induced from mature seed. Nat. Protoc. 3, 824–834 (2008).

    Article  CAS  PubMed  Google Scholar 

  15. Sage, R. F. The evolution of C4 photosynthesis. N. Phytol. 161, 341–370 (2004).

    Article  CAS  Google Scholar 

  16. Ermakova, M., Danila, F. R., Furbank, R. T. & von Caemmerer, S. On the road to C4 rice: advances and perspectives. Plant J. 101, 940–950 (2020).

    Article  CAS  PubMed  Google Scholar 

  17. Yang, J. et al. Brassinosteroids modulate meristem fate and differentiation of unique inflorescence morphology in Setaria viridis. Plant Cell 30, 48–66 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. 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 

  19. Saha, P. & Blumwald, E. Spike-dip transformation of Setaria viridis. Plant J. 86, 89–101 (2016).

    Article  CAS  PubMed  Google Scholar 

  20. Huang, P. et al. Population genetics of Setaria viridis, a new model system. Mol. Ecol. 23, 4912–4925 (2014).

    Article  CAS  PubMed  Google Scholar 

  21. Hu, S. et al. Xiaowei, a new rice germplasm for large-scale indoor research. Mol. Plant 11, 1418–1420 (2018).

    Article  CAS  PubMed  Google Scholar 

  22. Meissner, R. et al. A new model system for tomato genetics. Plant J. 12, 1465–1472 (1997).

    Article  CAS  Google Scholar 

  23. Monte, E. et al. Isolation and characterization of phyC mutants in Arabidopsis reveals complex crosstalk between phytochrome signaling pathways. Plant Cell 15, 1962–1980 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Takano, M. et al. Distinct and cooperative functions of phytochromes A, B, and C in the control of deetiolation and flowering in rice. Plant Cell 17, 3311–3325 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Martins, P. K. et al. Setaria viridis floral-dip: a simple and rapid Agrobacterium-mediated transformation method. Biotechnol. Rep. 6, 61–63 (2015).

    Article  Google Scholar 

  26. Liu, Y., Yu, J., Zhao, Q., Zhu, D. & Ao, G. Genetic transformation of millet (Setaria italica) by Agrobacterium-mediated. J. Agric. Biotechnol. 13, 32–37 (2005).

    CAS  Google Scholar 

  27. Liu, Y., Yu, J., Ao, G. & Zhao, Q. Factors influencing Agrobacterium-mediated transformation of foxtail millet (Setaria italica). Chin. J. Biochem. Mol. Biol. 23, 531–536 (2007).

    CAS  Google Scholar 

  28. Allen, G. C., Flores-Vergara, M. A., Krasynanski, S., Kumar, S. & Thompson, W. F. A modified protocol for rapid DNA isolation from plant tissues using cetyltrimethylammonium bromide. Nat. Protoc. 1, 2320–2325 (2006).

    Article  CAS  PubMed  Google Scholar 

  29. Chakraborty, M., Baldwin-Brown, J. G., Long, A. D. & Emerson, J. J. Contiguous and accurate de novo assembly of metazoan genomes with modest long read coverage. Nucleic Acids Res. 44, e147 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 27, 722–736 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Chin, C. S. et al. Phased diploid genome assembly with single-molecule real-time sequencing. Nat. Methods 13, 1050–1054 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Burton, J. N. et al. Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nat. Biotechnol. 31, 1119–1125 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Xu, Z. & Wang, H. LTR_FINDER: an efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acids Res. 35, W265–W268 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Han, Y. & Wessler, S. R. MITE-Hunter: a program for discovering miniature inverted-repeat transposable elements from genomic sequences. Nucleic Acids Res. 38, e199 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Price, A. L., Jones, N. C. & Pevzner, P. A. De novo identification of repeat families in large genomes. Bioinformatics 21 (Suppl. 1), i351–i358 (2005).

    Article  CAS  PubMed  Google Scholar 

  37. Edgar, R. C. & Myers, E. W. PILER: identification and classification of genomic repeats. Bioinformatics 21(Suppl 1), i152–i158 (2005).

    Article  CAS  PubMed  Google Scholar 

  38. Wicker, T. et al. A unified classification system for eukaryotic transposable elements. Nat. Rev. Genet. 8, 973–982 (2007).

    Article  CAS  PubMed  Google Scholar 

  39. Bao, W., Kojima, K. K. & Kohany, O. Repbase Update, a database of repetitive elements in eukaryotic genomes. Mob. DNA 6, 11 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Burge, C. & Karlin, S. Prediction of complete gene structures in human genomic DNA. J. Mol. Biol. 268, 78–94 (1997).

    Article  CAS  PubMed  Google Scholar 

  41. Stanke, M. & Waack, S. Gene prediction with a hidden Markov model and a new intron submodel. Bioinformatics 19(Suppl 2), ii215–ii225 (2003).

    Article  PubMed  Google Scholar 

  42. Majoros, W. H., Pertea, M. & Salzberg, S. L. TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics 20, 2878–2879 (2004).

    Article  CAS  PubMed  Google Scholar 

  43. Blanco, E., Parra, G. & Guigó, R. Using geneid to identify genes. Curr. Protoc. Bioinforma. 18, 4.3.1–4.3.28 (2007).

    Google Scholar 

  44. Korf, I. Gene finding in novel genomes. BMC Bioinf. 5, 59 (2004).

    Article  Google Scholar 

  45. Keilwagen, J. et al. Using intron position conservation for homology-based gene prediction. Nucleic Acids Res. 44, e89 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Haas, B. J. et al. Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res. 31, 5654–5666 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Dimmer, E. C. et al. The UniProt-GO annotation database in 2011. Nucleic Acids Res. 40, D565–D570 (2012).

    Article  CAS  PubMed  Google Scholar 

  48. Conesa, A. et al. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21, 3674–3676 (2005).

    Article  CAS  PubMed  Google Scholar 

  49. Lowe, T. M. & Eddy, S. R. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 25, 955–964 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Griffiths-Jones, S. et al. Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res. 33, D121–D124 (2005).

    Article  CAS  PubMed  Google Scholar 

  51. Simao, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).

    Article  CAS  PubMed  Google Scholar 

  52. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. 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 

  54. Li, B., Ruotti, V., Stewart, R. M., Thomson, J. A. & Dewey, C. N. RNA-seq gene expression estimation with read mapping uncertainty. Bioinformatics 26, 493–500 (2010).

    Article  PubMed  CAS  Google Scholar 

  55. Friedlander, M. R., Mackowiak, S. D., Li, N., Chen, W. & Rajewsky, N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 40, 37–52 (2012).

    Article  PubMed  CAS  Google Scholar 

  56. Memczak, S. et al. Circular RNAs are a large class of animal RNAs with regulatory potency. Nature 495, 333–338 (2013).

    Article  CAS  PubMed  Google Scholar 

  57. Kurtz, S. et al. Versatile and open software for comparing large genomes. Genome Biol. 5, R12 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Giordano, F., Stammnitz, M. R., Murchison, E. P. & Ning, Z. scanPAV: a pipeline for extracting presence–absence variations in genome pairs. Bioinformatics 34, 3022–3024 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Sun, L. et al. TDNAscan: a software to identify complete and truncated T-DNA insertions. Front. Genet. 10, 685 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Li, W. et al. Gene mapping and functional analysis of the novel leaf color gene SiYGL1 in foxtail millet [Setaria italica (L.) P. Beauv]. Physiol. Plant. 157, 24–37 (2016).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank D. Grierson, Z. Tian, R. Fray and Y. Jiang for their critical reading of the manuscript, and R. Xia for help in developing the xEGP browser. This work was supported by the National Key R&D Program of China (2018YFD1000700, 2018YFD1000704 and 2018YFD1000702), National Natural Science Foundation of China (31600289, 31471502 and 31371693) and Key R&D Projects of Shanxi Province (201703D211008).

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  1. These authors contributed equally: Zhirong Yang, Haoshan Zhang, Xukai Li.

Authors and Affiliations

  1. Institute of Agricultural Bioengineering, Shanxi Agricultural University, Taigu, China

    Zhirong Yang, Xukai Li, Jianhua Gao, Siyu Hou, Bin Zhang, Yuanhuai Han & Xingchun Wang

  2. College of Arts and Sciences, Shanxi Agricultural University, Taigu, China

    Zhirong Yang

  3. Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China

    Haoshan Zhang, Chuanyin Wu & Yi Sui

  4. College of Life Sciences, Shanxi Agricultural University, Taigu, China

    Xukai Li, Huimin Shen, Jianhua Gao & Xingchun Wang

  5. College of Agriculture, Shanxi Agricultural University, Taigu, China

    Siyu Hou, Bin Zhang & Yuanhuai Han

  6. Division of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, UK

    Sean Mayes & Malcolm Bennett

  7. Department of Agronomy, Purdue University, West Lafayette, IN, USA

    Jianxin Ma

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Contributions

X.W., Y.H., Z.Y. and Y.S. designed and coordinated the study. Y.H., J.G., S.H. and B.Z. constructed the Jingu21 EMS-mutagenized library and identified the xiaomi mutant. Z.Y., X.W. and H.S. characterized the xiaomi phenotype, cloned the PHYC gene and analysed the sequence data. H.Z., Y.S. and C.W. established the Agrobacterium-mediated genetic transformation system and wrote the relevant part of the manuscript. X.W., Y.H., X.L., Z.Y., J.M., S.M. and M.B. performed downstream analysis of the sequence data. H.S., J.G., S.H. and B.Z. collected the experimental materials. X.W. and J.M. wrote the manuscript. All authors edited and approved the manuscript.

Corresponding authors

Correspondence to Yi Sui, Yuanhuai Han or Xingchun Wang.

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Peer review information Nature Plants thanks Andrew Doust, Manoj Prasad, Hong Yu 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 Alternative splicing site of the PHYC gene in xiaomi.

a, RNA-Seq reads of Jingu21. xiaomi genome sequences were used as reference genome. The blue vertical line shows the G-T mutation site. b, RNA-seq reads of xiaomi. The wrong splicing site was marked by a red arrow.

Extended Data Fig. 2 Phenotypic and molecular characterization of the xiaomi-2 mutant.

a, Forty-day-old plants of Jingu21 (wild type, left) and xiaomi-2 (right) plants grown under natural long-day conditions. b, Heading date of Jingu21 and xiaomi-2 under natural field conditions. The heading date of ≥ 20 plants was measured for each replicate (n = 3 biologically independent replicates, ≥ 102 in total). The bottom and top of boxes represent the first and third quartile, respectively. The middle line is the median and the whiskers represent the maximum and minimum values. Statistical analysis was performed using two-tailed Wilcoxon rank-sum test. c, A mature small-sized xiaomi-2 plant (right) compared to Jingu21 (left), at the 68th day in field. d, Plant height of Jingu21 and xiaomi-2 under natural field conditions. The plant height of ≥ 23 plants was measured for each replicate (n = 3 biologically independent replicates, ≥ 83 in total). e, Molecular charicterization of xiaomi-2. Exons and introns are denoted by filled boxes and lines, respectively. P2F and P2R represent a pair of primers used to amplify the fragments harboring the mutation site from the segregating M3 individuals (Primer sequences are listed in Supplementary Table 3). f, Structure of PHYC and its mutation version deduced according to mutations in xiaomi-2. Scale bars, 10 cm in a and c.

Source data

Extended Data Fig. 3 Sequence alignment of the GAF domain of PHYC in foxtail millet and its homologs.

Alignment was carried out using Clustal W method of the MegAlign software. Red box indicates the conserved residue Leu across all listed species that is substituted with His in xiaomi-2, demonstrating its functional importance for PHYC. Accession numbers for the aligned sequences: Arabidopsis thaliana NP_198433, Brachypodium distachyon XP_003559446, Brassica napus XP_013680236, Ipomoea nil XP_019162785, Oryza sativa AAF66603, Panicum miliaceum, RLN42126, Solanum lycopersicum NP_001307446, Sorghum bicolor XP_002466441, Triticum aestivum AAU06208, Vitis vinifera ACC6096 and Zea mays XP_008665426. PHYC protein in Jingu21 is presented as for Setaria italica (Si9G09200).

Extended Data Fig. 4 Hi-C interaction matrices show the pairwise correlations between ordered scaffolds along the 9 pseudomolecules.

The intensity of the dark color is proportional to the strength of the correlation.

Extended Data Fig. 5 Transgene segregation in T1 transgenic seeds as visualized for GFP expression.

Dry mature seeds from transgenic lines representing single a, two b, or multiple c, T-DNA insertions were scanned with a dissection microscope equipped with UV light. All experiments were performed for eight independent biological repeats, and similar results were obtained. Scale bars, 2 mm.

Extended Data Fig. 6 PCR confirmation of the site-specific T-DNA insertions identified by genome resequencing.

a and b. An Integrative Genomics Viewer (IGV) display of genome sequencing reads from WT (a) or the transgenic line N2 (b) spanning the T-DNA insertion site 22812363 on chromosome 7. The break point caused by the insertion is marked by an arrow. c. PCR confirmation of the insertion site 33288299 on chromosome 6 in line H2. d. PCR confirmation of the insertion site 22812363 on chromosome 7 in line N2. e. PCR confirmation of the insertion site 39094661 on chromosome 5 in line N8. Note: The genomic DNA for sequencing and PCR was prepared from pooling approximate 50 T1 transgenic seedlings, which explains the heterozygous nature of the T-DNA insertion seen in b-e. M, molecular marker; lane 1, no-transformed xiaomi plants; line 2, transgenic xiaomi plants; line 3, water control; F and R are primers for priming genomic regions flanking LB and RB ends of T-DNA, respectively; both the LB1 and LB2 primers are for T-DNA sequence close to the left border (LB). LB1 is 161 bp further apart from the border than LB2 for the vector pCAMBIA1305GFP, resulting in a band of bigger size in the R/LB1 pair in c. Similarly, LB1 and LB2 are distanced by 183 bp for the p8-GFP vector, thus resulting in different band size between F/LB1 and F/LB2 in d and e. All experiments were performed for three repeats, and similar results were obtained. Primers used are listed in Supplementary Table 3.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–7.

Reporting Summary

Supplementary Tables

Supplementary Tables 1–25.

Supplementary Data 1

SNPs and indels between xiaomi and Yugu1.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Unprocessed gel.

Source Data Fig. 5

Unprocessed gels.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 6

Unprocessed gels.

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Yang, Z., Zhang, H., Li, X. et al. A mini foxtail millet with an Arabidopsis-like life cycle as a C4 model system. Nat. Plants 6, 1167–1178 (2020). https://doi.org/10.1038/s41477-020-0747-7

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