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Phased chromosome-level assembly provides insight into the genome architecture of hexaploid sweetpotato

Nature Plants volume 11, pages 1951–1959 (2025)Cite this article

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Abstract

The hexaploid sweetpotato (Ipomoea batatas [L.] Lam.) is a globally important stable crop that plays a key role in biofortification. Its high resilience and adaptability provide distinct advantages in addressing food security and climate challenges. Here we report a haplotype-resolved chromosome-level genome assembly of an African cultivar, ‘Tanzania’, revealing mosaic genomic origins along haplotype-phased chromosomes. The wild tetraploid I. aequatoriensis, currently found in coastal Ecuador, contributes to a substantial fraction of the sweetpotato genome. Another large proportion of the genome shows a closer genetic relationship to the wild tetraploid I. batatas 4×, distributed in Central America. The sequences contributed by different wild species are not distributed in typical subgenomes but are intertwined along chromosomes, possibly owing to the known non-preferential recombination among sweetpotato haplotypes. This study improves our understanding of sweetpotato origin and genome architecture and provides valuable genomic resources to accelerate sweetpotato breeding.

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Fig. 1: Phased genome assembly of the hexaploid sweetpotato cultivar ‘Tanzania’.
Fig. 2: Architecture of the hexaploid ‘Tanzania’ genome.

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Data availability

Raw genome sequencing reads have been deposited in the National Centre for Biotechnology Information BioProject database under the accession no. PRJNA1138727. The ‘Tanzania’ phased and consensus genome assemblies and annotated genes are also available via Sweetpotato Genomics Resource at http://sweetpotato.uga.edu/.

Code availability

The source code for the haplotype phasing is available via GitHub at https://github.com/wu728/tanzania_genome/blob/main/hapByHiC.py.

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Acknowledgements

We thank S. Williamson from NC State University for her assistance in sample collection, T. Ranney and N. Lynch for assistance in flow cytometry analysis, and B. Yada from National Crops Resources Research Institute, Uganda for providing the ‘Tanzania’ images. This research was supported by grants from the Bill and Melinda Gates Foundation through SweetGAINS (OPP1213329) and RTB Breeding (CGIAR Investment ID1523-BMGF) Projects under a subcontract with the International Potato Centre, Lima, Peru, and USDA National Institute of Food and Agriculture (2022-67013-36269).

Author information

Author notes

  1. Mercy Kitavi

    Present address: Michigan State University, East Lansing, MI, USA

  2. These authors contributed equally: Shan Wu, Honghe Sun, Xuebo Zhao.

Authors and Affiliations

  1. Boyce Thompson Institute, Cornell University, Ithaca, NY, USA

    Shan Wu, Honghe Sun, Xuebo Zhao & Zhangjun Fei

  2. Plant Biology Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA

    Honghe Sun

  3. Center for Applied Genetic Technologies, University of Georgia, Athens, GA, USA

    John P. Hamilton, Mercy Kitavi & C. Robin Buell

  4. Department of Crop and Soil Sciences, University of Georgia, Athens, GA, USA

    John P. Hamilton & C. Robin Buell

  5. Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA

    Marcelo Mollinari & Gabriel De Siqueira Gesteira

  6. Department of Horticultural Science, North Carolina State University, Raleigh, NC, USA

    Marcelo Mollinari, Gabriel De Siqueira Gesteira & G. Craig Yencho

  7. Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai, China

    Mengxiao Yan, Hongxia Wang & Jun Yang

  8. CAS Center for Excellence of Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China

    Hongxia Wang & Jun Yang

  9. Institute of Plant Breeding, Genetics, and Genomics, University of Georgia, Athens, GA, USA

    C. Robin Buell

  10. The Plant Center, University of Georgia, Athens, GA, USA

    C. Robin Buell

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Contributions

Z.F., C.R.B. and G.C.Y. designed and managed the project. S.W. and Z.F. coordinated the genome sequencing. S.W. and H.S. performed the genome assembly and evaluation. J.P.H. and M.K. performed ONT transcriptome sequencing and genome annotation. S.W., H.S., X.Z., M.Y., H.W. and J.Y. contributed to genomic analyses. M.M. and G.D.S.G. constructed the phased genetic map. S.W. wrote the manuscript. Z.F. revised the manuscript. All authors read and approved the manuscript.

Corresponding author

Correspondence to Zhangjun Fei.

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Nature Plants thanks Qinghe Cao, Adam Session 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 Hi-C contact heatmaps for the 90 chromosomes in the ‘Tanzania’ assembly.

The Hi-C contact heatmap was generated using all mapped reads. Each of the 15 homoeologous chromosome groups forms a distinct block.

Extended Data Fig. 2 Haplotype phasing assessment of the ‘Tanzania’ assembly using the phased genetic map.

The density of reference alleles of SNPs within each haplotype across 2-Mb non-overlapping windows throughout the ‘Tanzania’ genome assembly is shown. For each chromosome and haplotype combination used to obtain the SNPs, the majority of reference alleles in these SNPs (98.6%) were phased within a specific haplotype, as indicated by the green boxes.

Extended Data Fig. 3 Large inversions among the six ‘Tanzania’ haplotypes supported by Hi-C contact signals and HiFi read alignments.

The example shown here is the 5.68-Mb inversion on ‘Tanzania’ chromosome 12 F. a, Heatmap of the Hi-C contact signals among the six haplotypes of ‘Tanzania’, supporting the inversion on chromosome 12 F. b, HiFi read alignments using TznChr12F as the reference. Reads spanning the inversion breakpoints at TznChr12F 11.8 Mb and 17.5 Mb, which originated from haplotype TznChr12F, are highlighted by the green boxes. Reads that are split-aligned, which originated from the other five haplotypes, are highlighted by orange boxes.

Extended Data Fig. 4 Dotplot showing the fold change of gene family sizes between the I. trifida NCNSP0306 and phased I. batatas ‘Tanzania’ genome assemblies.

An enlarged view of gene families with sizes smaller than 200 is shown on the right.

Extended Data Fig. 5

Distribution of TIR-NBS-LRR genes across the phased ‘Tanzania’ genome.

Extended Data Fig. 6 Distribution of TIR-NBS-LRR genes across the six haplotypes of ‘Tanzania’ chromosome 7.

Genes within the same syntenic paralogous group are labeled with the same color.

Extended Data Fig. 7 Distribution of sequence identity differences between the two wild tetraploid species and hexaploid sweetpotato.

For each analyzed phased genomic window, the sequence identity difference was calculated as: the mean sequence identity between ten I. aequatoriensis accessions and the hexaploid sweetpotato ‘Tanzania’ minus the mean sequence identity between eight I. batatas 4× accessions and the hexaploid sweetpotato ‘Tanzania’. The two peaks of the identity difference distribution are labeled by the orange and green lines in the top panel. Normal distributions were fitted to the patterns displayed by ‘Tanzania’ genomic windows with higher sequence identity to I. batatas 4× (middle) and those with higher identity to I. aequatoriensis (bottom). The 95% confidence intervals are indicated by the blue dotted lines.

Extended Data Fig. 8 Proportion and length of ‘Tanzania’ genomic sequences inferred to have different origins.

a, Proportion calculated across the entire genome. b, Proportions calculated for each homoeologous chromosome group. c, Lengths of ‘Tanzania’ sequences with different origins across the 90 chromosomes. d, Proportion of ‘Tanzania’ sequences with different origins in each of the 90 chromosomes.

Extended Data Fig. 9 Distribution of sequence identities between ‘Tanzania’ and wild I. aequatoriensis, I. batatas 4×, and I. trifida accessions in ‘Tanzania’ genomic windows with inferred ancestry based on genetic distance and sequence identity.

Genomic windows with consistent and contradictory origin inference between the two methods are shown on the left and in the middle, respectively. Windows whose origin could not be determined based on sequence identity are shown on the right. KNN refers to genomic origin inference based on genetic distance using a k-nearest neighbor algorithm.

Extended Data Fig. 10 IbT-DNA sequences in the hexaploid sweetpotato ‘Tanzania’ genome.

a, Positions of IbT-DNA1 and IbT-DNA2 sequences on the ‘Tanzania’ chromosomes. b, Alignments between the IbT-DNAs and the ‘Tanzania’ genomic regions containing these IbT-DNA insertions.

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Supplementary Tables 1–12.

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Wu, S., Sun, H., Zhao, X. et al. Phased chromosome-level assembly provides insight into the genome architecture of hexaploid sweetpotato. Nat. Plants 11, 1951–1959 (2025). https://doi.org/10.1038/s41477-025-02079-6

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