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Dissecting cis-regulatory control of quantitative trait variation in a plant stem cell circuit

Nature Plants volume 7, pages 419–427 (2021)Cite this article

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Abstract

Cis-regulatory mutations underlie important crop domestication and improvement traits1,2. However, limited allelic diversity has hindered functional dissection of the large number of cis-regulatory elements and their potential interactions, thereby precluding a deeper understanding of how cis-regulatory variation impacts traits quantitatively. Here, we engineered over 60 promoter alleles in two tomato fruit size genes3,4 to characterize cis-regulatory sequences and study their functional relationships. We found that targeted mutations in conserved promoter sequences of SlCLV3, a repressor of stem cell proliferation5,6, have a weak impact on fruit locule number. Pairwise combinations of these mutations mildly enhance this phenotype, revealing additive and synergistic relationships between conserved regions and further suggesting even higher-order cis-regulatory interactions within the SlCLV3 promoter. In contrast, SlWUS, a positive regulator of stem cell proliferation repressed by SlCLV3 (refs. 5,6), is more tolerant to promoter perturbations. Our results show that complex interplay among cis-regulatory variants can shape quantitative variation, and suggest that empirical dissections of this hidden complexity can guide promoter engineering to predictably modify crop traits.

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Fig. 1: A large and diverse collection of CRISPR–Cas9-engineered SlCLV3 promoter alleles reveals complex relationships between promoter mutations and fruit locule number variation.
Fig. 2: Mutations in individual conserved sequences of the SlCLV3 promoter result in weak effects on locule number.
Fig. 3: Combining mutations in conserved cis-regulatory regions reveals additive, redundant and synergistic relationships between sequences in the SlCLV3 promoter.
Fig. 4: The promoter of SlWUS is more tolerant to genetic perturbations.

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Data availability

Source data are provided with this paper. All additional datasets are available from the corresponding author upon request.

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Acknowledgements

We thank members of the Lippman laboratory and D. Jackson for discussions and comments on the manuscript; G. Robitaille, J. Kim, A. Krainer and R. Santos for technical support; Z. H. Lemmon for assistance in allele characterization; L. Randall, A. Doyle, P. Keen, K. Swartwood, M. Tjahjadi and J. Van Eck for performing tomato transformations; T. Mulligan, K. Schlecht, A. Krainer, C. Gilbert and S. Qiao for assistance with plant care; and T. Ha for assistance with statistical analyses. This research was supported by the Howard Hughes Medical Institute and grant support from BARD (United States–Israel Binational Agricultural Research and Development Fund, no. IS-5120-18C) to Z.B.L., the Vaadia–BARD Postdoctoral Fellowship (award no. FL-542-16) to A.H. and the National Science Foundation Plant Genome Research Program (grant nos. IOS-1546837 and IOS-1732253) to Z.B.L.

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Author notes

  1. Daniel Rodríguez-Leal

    Present address: Inari Agriculture, Cambridge, MA, USA

Authors and Affiliations

  1. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Xingang Wang, Lyndsey Aguirre, Daniel Rodríguez-Leal, Anat Hendelman, Matthias Benoit & Zachary B. Lippman

  2. School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Lyndsey Aguirre & Zachary B. Lippman

  3. Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Matthias Benoit & Zachary B. Lippman

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Contributions

Z.B.L. conceived the project. X.W., L.A., D.R.-L., A.H. and Z.B.L. designed and planned experiments. X.W., L.A., D.R.-L., A.H., M.B. and Z.B.L. performed experiments and collected data. X.W., L.A., D.R.-L., A.H., M.B. and Z.B.L. analysed data. X.W. and Z.B.L. wrote the manuscript with input from L.A. All authors read, edited and approved the manuscript.

Corresponding author

Correspondence to Zachary B. Lippman.

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Competing interests

Z.B.L. is a consultant for and a member of the Scientific Strategy Board of Inari Agriculture, and he is also a named inventor on a number of patents and patent applications directed to related technology that have been exclusively licensed from CSHL to Inari Agriculture (patent nos. US 2020/0299705 A1, US 2020/0199604 A1, US 2020/0299706 A1 and US 9,732,352 B2).

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Peer review information Nature Plants thanks Qinlong Zhu 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 Additional experiment showing locule number phenotypes from the collection of 30 SlCLV3 promoter alleles.

a, Heat map representations of the slclv3pro alleles and fas. The 2.1 kb promoter region is divided into 20 bp windows. Purple color intensity in each window indicates the ratio of sequence changed relative to WT. Red color indicates inversion. b, Quantification of locule number in a repeated experiment. Box plots show the 25th percentile, median, and 75th percentile of locule numbers for each allele. Number of fruits quantified (n), mean, and standard deviation (sd) are shown.

Source data

Extended Data Fig. 2 Additional experiment showing locule number phenotypes from the SlCLV3 promoter alleles with mutations in conserved regions, and expression of SlCLV3 and SlWUS in representative alleles from each targeted region.

a–d, Locule number phenotypes of slclv3pro alleles of R1, R2, R3 and R4, respectively. Box plots in (a–d) show the 25th percentile, median, and 75th percentile of locule numbers for each allele. P values in (a–d) are from two-sided Dunnett’s ‘compare with control’ test (p values less than 0.2 are shown; ns: not significant). e-i, RT-qPCR results showing expression of SlCLV3 and SlWUS in the coding sequence null allele slclv3-10 (e) and in selected slclv3pro R1 (f), R2 (g), R3 (h), and R4 (i) alleles, respectively. Expression is normalized to SlUBIQUITIN and shown as fold-changes compared to WT. Values are means ± s.e. from three biological replicates of pooled meristems. P values smaller than 0.05 from two-tailed, two sample t-tests are shown.

Source data

Extended Data Fig. 3 CRISPR-Cas9 genome editing strategies used to combine mutations from different conserved regions in the SlCLV3 promoter.

a, Schematic depicting the trans-targeting crossing scheme to generate combinations of mutations in two conserved regions (combining mutations in R1 and R4 as an example). Homozygous promoter alleles slclv3pro-R1 and slclv3pro-R4 carrying their respective CRISPR-Cas9 transgenes are crossed, and the inherited transgenes from each parental plant can act in trans in the F1 generation to mutate corresponding wild type R1 and R4 regions in cis, which are inherited from slclv3pro-R4 and slclv3pro-R1 lines, respectively. Alleles carrying mutations in both R1 and R4 were selected by PCR, homozygous plants were identified by sequencing in the F2 generation, phenotyping was performed in the F3 generation. b, Schematic depicting sequential CRISPR-Cas9 mutagenesis of two conversed regions. A homozygous promoter allele (e.g. slclv3pro-R4) lacking the original CRISPR-Cas9 transgene is transformed with a second CRISPR-Cas9 construct targeting a different conserved region. Plants having alleles with combined mutations are selected in the T1 generation, and homozygous plants with combined mutations were selected in the T2 generation and phenotyped in T3 generation. c, Quantification of locule numbers of slclv3pro alleles with combined mutations in R1 and R4 regions. Inherited mutations are denoted with superscript numbers and newly induced mutations are denoted with superscript letters. d, Summary of tests for non-additive effects in combined alleles compared to individual mutations in the R1 and R4 regions. Combined allele R15 + R4d (labeled with *) showed different effects between two replicate experiments. e, Quantification of locule numbers of the large deletion allele that overlaps the R1 and R2 regions. Data in (c) and (e) were collected in an additional experiment (see Methods). P values in (c) and (e) are from two-sided Dunnett’s ‘compare with control’ test (p values less than 0.2 are shown; ns: not significant). Box plots in (c) and (e) show the 25th percentile, median, and 75th percentile of locule numbers for each allele.

Source data

Extended Data Fig. 4 Phenotypes of slwuspro-8 plants and locule number quantification of SlWUS promoter alleles from an additional experiment.

a, Schematic showing the slwuspro-8 allele and an image of an slwuspro-8 plant displaying a stunted bushy plant with an escaped shoot. The slwuspro-8 allele carries a large deletion and a proximal rearrangement that could not be resolved, but the SlWUS coding sequence and proximal promoter region are intact. slwuspro-8 mutants show meristem termination phenotypes like null slwus coding sequence alleles, but can occasionally generate a shoot. b, Quantification of locule number of slwuspro alleles from an additional experiment shown in stacked bar charts and box plots. Box plots show the 25th percentile, median, and 75th percentile of locule numbers for each allele. P values in (b) are from two-sided Dunnett’s ‘compare with control’ test (p values less than 0.2 are shown; ns: not significant).

Source data

Supplementary information

Source data

Source Data Fig. 1

Phenotypic source data.

Source Data Fig. 2

Phenotypic source data.

Source Data Fig. 3

Phenotypic source data.

Source Data Fig. 4

Phenotypic source data.

Source Data Extended Data Fig. 1

Phenotypic source data.

Source Data Extended Data Fig. 2

Phenotypic source data.

Source Data Extended Data Fig. 3

Phenotypic source data.

Source Data Extended Data Fig. 4

Phenotypic source data.

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Wang, X., Aguirre, L., Rodríguez-Leal, D. et al. Dissecting cis-regulatory control of quantitative trait variation in a plant stem cell circuit. Nat. Plants 7, 419–427 (2021). https://doi.org/10.1038/s41477-021-00898-x

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