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Repeat-sequence turnover shifts fundamentally in species with large genomes

Nature Plants volume 6, pages 1325–1329 (2020)Cite this article

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Abstract

Given the 2,400-fold range of genome sizes (0.06–148.9 Gbp (gigabase pair)) of seed plants (angiosperms and gymnosperms) with a broadly similar gene content (amounting to approximately 0.03 Gbp), the repeat-sequence content of the genome might be expected to increase with genome size, resulting in the largest genomes consisting almost entirely of repetitive sequences. Here we test this prediction, using the same bioinformatic approach for 101 species to ensure consistency in what constitutes a repeat. We reveal a fundamental change in repeat turnover in genomes above around 10 Gbp, such that species with the largest genomes are only about 55% repetitive. Given that genome size influences many plant traits, habits and life strategies, this fundamental shift in repeat dynamics is likely to affect the evolutionary trajectory of species lineages.

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Fig. 1: Content of repeats present in more than 20 copies in the genomes of 101 seed plant species ranging in size from 0.063–88.55 Gbp and encompassing much of the known range of genome sizes encountered in seed plants.
Fig. 2: Repeat dynamics across the range of plant genome sizes.

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Data availability

The genomic DNA data analysed were already available in the European Nucleotide Archive (ENA) (https://www.ebi.ac.uk/ena/browser/home) or Illumina sequenced during the work described in this article and archived in the ENA (Supplementary Table 3). Details of the ENA accession identifier for each sample are provided in Supplementary Table 3a. Details of the source of the plant material and sequencing platform are given in Supplementary Table 3a. Genome size data were taken from reported estimates given in the Plant DNA C-values Database release 7.1 (https://cvalues.science.kew.org/) or from source publications not yet included in the database; in each case the source reference is provided in Supplementary Table 3a, column S and the species analysed here are listed in Supplementary Table 3b (further information is available in Methods, ‘Flow cytometry and genome size data’).

Code availability

Most of the code used to analyse these data are integral to the published, established software packages as stated above and parameter settings are described as appropriate. New code was generated to filter out all low-quality sequence reads, reads containing adapter sequences and reads with similarity to the plastid and mitochondrial genomes, and this is available in the Git repository https://bitbucket.org/repeatexplorer/re_utilities.

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Acknowledgements

We thank Natural Environment Research Council (NE/G020256/1), the Czech Academy of Sciences (RVO:60077344) and Ramón y Cajal Fellowship (RYC-2017-2274) funded by the Ministerio de Ciencia y Tecnología (Gobierno de España) for support. In addition, the work was supported by the European Regional Development Fund–European Social Fund project ELIXIR-CZ–Capacity Building (no. CZ.02.1.01/0.0/0.0/16_013/0001777) and ELIXIR-CZ research infrastructure project (LM2015047) for the access to computing and storage facilities. We also thank Natural Environment Research Council for funding a studentship to S.D. and the China Scholarship Council for funding W.W. Finally, we thank R.A. Nichols for helpful advice and J. Marquardt for supplying DNA of H. non-scripta.

Author information

Authors and Affiliations

  1. Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic

    Petr Novák, Pavel Neumann, Andrea Koblížková & Jiří Macas

  2. Jodrell Laboratory, Royal Botanic Gardens, Kew, Richmond, UK

    Maïté S. Guignard, Laura J. Kelly, Jaume Pellicer & Ilia J. Leitch

  3. School of Biological and Chemical Sciences, Queen Mary University of London, London, UK

    Maïté S. Guignard, Laura J. Kelly, Steven Dodsworth, Wencai Wang & Andrew R. Leitch

  4. Division of Molecular Biology, Department of Biology, University of Zagreb, Zagreb, Croatia

    Jelena Mlinarec

  5. School of Life Sciences, University of Bedfordshire, Luton, UK

    Steven Dodsworth

  6. Institute of Biophysics, Academy of Sciences of the Czech Republic, Brno, Czech Republic

    Aleš Kovařík

  7. Institut Botànic de Barcelona (IBB, CSIC-Ajuntament de Barcelona), Barcelona, Spain

    Jaume Pellicer

  8. Guangzhou University of Chinese Medicine, Guangzhou, China

    Wencai Wang

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Contributions

A.R.L., I.J.L., J. Macas and P. Novák conceived the experiment and designed, implemented and coordinated the project. P. Novák conducted genomic sequence analysis, P. Neumann conducted (retro)transposon protein-coding domains analysis, J.P. and J. Mlinarec provided material and flow cytometry analysis, and M.S.G. provided the statistical analysis. J. Mlinarec, L.J.K., S.D., W.W., A. Kovařík, A. Koblížková and J.P. provided sequence data and experimental advice. All authors were involved in writing the manuscript.

Corresponding authors

Correspondence to Jiří Macas, Ilia J. Leitch or Andrew R. Leitch.

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Extended data

Extended Data Fig. 1 Distribution of genome sizes (GS).

Distribution of genome sizes (GS) in (a) 10,770 angiosperms (out of c. 350,000 known species) (b) 506 gymnosperms (out of c. 1,000 known species).

Extended Data Fig. 2 Genome proportion of the different classes of repeats.

Genome proportion of the different classes of repeats based on copy number fitted against ln-transformed genome size. The grey regression lines show estimated trends for all 101 species fitted with a beta regression (see also Supplementary Table 4). Orange lines show the estimated slope from phylogenetic least squares (PGLS) using a phylogeny with proportional branch lengths (phy P) fitted with an Ornstein–Uhlenbeck process. We also tested a phylogeny with branch lengths transformed to a cladogram (phy C), and results were similar to this PGLS (not shown).

Extended Data Fig. 3 Transposable element analysis of 77 seed plant species.

Analysis of 77 seed plant species (69 angiosperms (1 early-diverging angiosperm, 53 eudicots, 15 monocots) and eight gymnosperms) showing how the proportion of the genome occupied by transposable element-related protein coding domains varies with ln-transformed genome size. The regression lines show the slopes estimated from a beta regression, and from a PGLS with an Ornstein–Uhlenbeck process. The regression line of the graph is similar to that seen for the whole repetitive fraction (see Extended Data Fig. 2a).

Extended Data Fig. 4 Genome proportion of repeats in eudicots, monocots and gymnosperms.

Genome proportion of repeats in four categories (sequences ≤ 20 copies, low (21–500), middle (501–10,000) and high (>10,000) copy sequences fitted against ln-transformed genome size, separately for eudicots, monocots and gymnosperms. See also Supplementary Table 4, which shows significant relationships in these datasets.

Supplementary information

Supplementary Information

Supplementary Tables 1–8 and Figs. 1–4.

Reporting Summary

Supplementary Table Excel file 1

The data and methods used in previously published work to estimate repeat genome proportions (GP) are provided in an Excel spreadsheet (filename: Novak_Supplementary_Table_1 (2 Sept).xlsx).

Supplementary Table Excel file 2

Details of the materials used in sequencing and repeat genome proportions (GP) and genome-size (GS) data: (a) shows the 101 plant species analysed for total repeat GP and the GPs of each of the four repeat categories based on the number of mutual similarity hits. It also shows the GPs of transposable elements (TEs), genome sizes (GS, bp/1 C) of the species analysed and the sources of that data; (b) shows the species in which the GS data were obtained in this work; and (c) lists the technical and biological replicates examined with the sources of the data (filename: Novak_Supplementary_Table_3 (2 Sept).xlsx).

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Novák, P., Guignard, M.S., Neumann, P. et al. Repeat-sequence turnover shifts fundamentally in species with large genomes. Nat. Plants 6, 1325–1329 (2020). https://doi.org/10.1038/s41477-020-00785-x

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