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Unleashing meiotic crossovers in crops

Nature Plants volume 4, pages 1010–1016 (2018)Cite this article

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Abstract

Improved plant varieties are important in our attempts to face the challenges of a growing human population and limited planet resources. Plant breeding relies on meiotic crossovers to combine favourable alleles into elite varieties1. However, meiotic crossovers are relatively rare, typically one to three per chromosome2, limiting the efficiency of the breeding process and related activities such as genetic mapping. Several genes that limit meiotic recombination were identified in the model species Arabidopsis thaliana2. Mutation of these genes in Arabidopsis induces a large increase in crossover frequency. However, it remained to be demonstrated whether crossovers could also be increased in crop species hybrids. We explored the effects of mutating the orthologues of FANCM3, RECQ44 or FIGL15 on recombination in three distant crop species, rice (Oryza sativa), pea (Pisum sativum) and tomato (Solanum lycopersicum). We found that the single recq4 mutation increases crossovers about three-fold in these crops, suggesting that manipulating RECQ4 may be a universal tool for increasing recombination in plants. Enhanced recombination could be used with other state-of-the-art technologies such as genomic selection, genome editing or speed breeding6 to enhance the pace and efficiency of plant improvement.

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Fig. 1: RECQ4, FANCM and FIGL1 mutations.
Fig. 2: Genetic maps in fancm and recq4 mutants compared with wild type.
Fig. 3: Average genetic size per chromosome in wild type, fancm and recq4 for Arabidopsis, rice, pea and tomato.
Fig. 4: Distribution of crossovers along the 12 rice chromosomes in Osrecq4l (blue), Osfancm (green) and wild type (grey) plants.

Data availability

The data that support the findings of this study are provided as Supplementary Datasets. Genotyping data and derived recombination frequencies (Figs. 2, 3 and 4) for rice, pea and tomato are given in Supplementary Datasets 2–7, respectively. The protein sequences used for the phylogeny analyses (Supplementary Figs. 1–3) are provided as Supplementary Dataset 1.

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Acknowledgements

We thank J. Burstin, M. Causse, B. Courtois and C. Mézard for fruitful discussions; P. Sourdille and F. Benyahya for sharing wheat sequences before publication; C. Le Signor and M.-C. Le Paslier for offering their expertise and advice; and J.-F. Rami for his help with the SpiderMap software. The pea and tomato work was funded by HyperRec grants from INRA Transfert. The Institute Jean-Pierre Bourgin benefits from the support of the LabEx Saclay Plant Sciences-SPS (ANR-10-LABX-0040-SPS). This work was partly funded by the Investissements d’Avenir, France Génomique (10-INBS-0009) project IRIGIN (International Rice Genome Initiative) and the CGIAR research program on rice (RICE).

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Authors and Affiliations

  1. CIRAD, UMR AGAP, Montpellier, France

    Delphine Mieulet, Gaëtan Droc & Emmanuel Guiderdoni

  2. Université Montpellier, CIRAD, INRA Montpellier SupAgro, Montpellier, France

    Delphine Mieulet, Gaëtan Droc & Emmanuel Guiderdoni

  3. Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, Dijon, France

    Gregoire Aubert, Anthony Klein, Emilie Vieille, Celine Rond-Coissieux & Myriam Sanchez

  4. UMR 1332 BFP, INRA, Université Bordeaux, Villenave d’Ornon, France

    Cecile Bres, Jean-Philippe Mauxion & Christophe Rothan

  5. Institute of Plant Sciences, Paris-Saclay IPS2, CNRS, INRA, Université Paris-Sud, Université Evry, Université Paris-Saclay, Orsay, France

    Marion Dalmais

  6. Institut Jean-Pierre Bourgin, UMR1318 INRA–AgroParisTech, Université Paris-Saclay, Versailles, France

    Raphael Mercier

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Contributions

D.M., G.A., C.B., A.K., G.D., E.V., C.R.C., M.S., M.D. and J.P.M. produced the data. D.M., G.A., C.B., A.K., E.G. and R.M. analysed the data. D.M., G.A., C.B., C.R., E.G. and R.M. conceived and designed the experiments. D.M. and R.M. wrote the paper with inputs from G.A., C.B., C.R. and E.G.

Corresponding author

Correspondence to Raphael Mercier.

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Competing interests

Patents have been deposited by INRA on the use of RECQ4, FIGL1 and FANCM to manipulate meiotic recombination (EP3149027, EP3016506 and EP2755995).

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Supplementary information

Supplementary Information

Supplementary Figures 1–9 and Supplementary Tables 1–3.

Reporting Summary

Dataset 1

Sequences and accession numbers of RECQ4, FIGL1 and FANCM proteins analysed in Supplementary Figures 1–3.

Dataset 2

Genotyping data of rice populations.

Dataset 3

Recombination data in rice.

Dataset 4

Genotyping data of pea populations.

Dataset 5

Recombination data in pea.

Dataset 6

Genotyping data of tomato populations.

Dataset 7

Recombination data in tomato.

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Mieulet, D., Aubert, G., Bres, C. et al. Unleashing meiotic crossovers in crops. Nature Plants 4, 1010–1016 (2018). https://doi.org/10.1038/s41477-018-0311-x

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