Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella

Article

Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella Graphical Abstract

Authors Ushio Fujikura, Runchun Jing, Atsushi Hanada, ..., Shinjiro Yamaguchi, Christian Kappel, Michael Lenhard

Correspondence [email protected]

In Brief Reduced reproductive structures are often associated with the transition from outbreeding to selfing in an organism. Fujikura, Jing et al. address the molecular basis of morphological evolution in the selfing plant Capsella rubella. Evolutionarily derived variations in CYP724A1 increase splicing efficiency and contribute to reduced petal size through higher-than-optimal brassinosteroid levels.

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Variation in the CYP724A1 gene contributes to petal-size reduction in Capsella Two derived SNPs increase the transcript’s splicing efficiency in the selfer This increases CYP724A1 expression and results in higher brassinosteroid levels These higher-than-optimal brassinosteroid levels limit petalcell proliferation

Fujikura et al., 2018, Developmental Cell 44, 1–12 January 22, 2018 ª 2017 Elsevier Inc. https://doi.org/10.1016/j.devcel.2017.11.022

Please cite this article in press as: Fujikura et al., Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella, Developmental Cell (2017), https://doi.org/10.1016/j.devcel.2017.11.022

Developmental Cell

Article Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella Ushio Fujikura,1,4,5 Runchun Jing,1,4,6 Atsushi Hanada,2,7 Yumiko Takebayashi,3 Hitoshi Sakakibara,3 Shinjiro Yamaguchi,2 Christian Kappel,1 and Michael Lenhard1,8,* 1Institute

for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Straße 24–25, House 26, 14476 Potsdam-Golm, Germany School of Life Sciences, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai, Miyagi 980-8577, Japan 3Plant Productivity Systems Research Group, RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro, Tsurumi, Yokohama 230-0045, Japan 4These authors contributed equally 5Present address: Graduate School of Science, Technology and Innovation, Kobe University, Integrated Research Center of Kobe University, Room 306, Chuo-ku, Minatojima Minami-machi 7-1-49, Kobe, Hyogo 650-0047, Japan 6Present address: China Golden Marker (Beijing) Biotech Co. Ltd., Building 1, No. 20 Life Science Park Road, Beijing 102206, P.R. China 7Present address: AB SCIEX, Kitashinagawa 4-7-35, Shinagawa, Tokyo, Japan 8Lead Contact *Correspondence: [email protected] https://doi.org/10.1016/j.devcel.2017.11.022 2Graduate

SUMMARY

Understanding the molecular basis of morphological change remains a central challenge in evolutionary-developmental biology. The transition from outbreeding to selfing is often associated with a dramatic reduction in reproductive structures and functions, such as the loss of attractive pheromones in hermaphroditic Caenorhabditis elegans and a reduced flower size in plants. Here, we demonstrate that variation in the level of the brassinosteroid-biosynthesis enzyme CYP724A1 contributes to the reduced flower size of selfing Capsella rubella compared with its outbreeding ancestor Capsella grandiflora. The primary transcript of the C. rubella allele is spliced more efficiently than that of C. grandiflora, resulting in higher brassinosteroid levels. These restrict organ growth by limiting cell proliferation. More efficient splicing of the C. rubella allele results from two de novo mutations in the selfing lineage. Thus, our results highlight the potentially widespread importance of differential splicing efficiency and higher-than-optimal hormone levels in generating phenotypic variation.

INTRODUCTION The molecular basis of morphological evolution remains poorly understood, in particular for polygenic traits such as organ shape and size. The evolution of the selfing syndrome represents a prominent example of change in the sizes of reproductive structures (Cutter, 2008; Darwin, 1876; Ornduff, 1969; Sicard and Lenhard, 2011). In flowering plants, the transition from outbreeding to reproduction by selfing represents one of the most common evolutionary transitions, believed to have occurred many hundreds of times independently (Barrett, 2010). In cases where the

ancestral outbreeding was mediated by animal vectors, the transition to selfing is often followed by a suite of characteristic changes to flower morphology and function, termed the ‘‘selfing syndrome.’’ This includes a dramatic reduction in flower, particularly petal size, and additional functional changes, such as reduced nectar and scent production, as well as a shift in the ratio of pollen/ovule numbers (Ornduff, 1969; Sas et al., 2016; Sicard and Lenhard, 2011). Having occurred many times independently, the selfing syndrome thus illustrates a case of widespread convergent evolution in plants (Ornduff, 1969; Sicard and Lenhard, 2011). The molecular basis for the loss of self-incompatibility, which is a prerequisite for efficient reproduction by selfing, has been elucidated in a number of cases (Shimizu and Tsuchimatsu, 2015). By contrast, the genetic basis underlying selfing-syndrome traits like reduced flower size is very poorly understood. A number of quantitative trait locus (QTL) studies have identified genomic regions underlying the variation in petal sizes and shapes between selfing and outbreeding species (Sicard and Lenhard, 2011) and a causal gene for shortening of the style in domesticated versus wild tomatoes has been isolated (Chen et al., 2007), as has a single locus leading to reduced petal size in the selfing Capsella rubella versus the outbreeding Capsella grandiflora (Sicard et al., 2016; see below). Mutagenesis studies in model species have identified an increasing number of genes regulating leaf and floral-organ growth in plants (Czesnick and Lenhard, 2015; Gonzalez and Inze, 2015; Hepworth and Lenhard, 2014); also, plant hormones are well-documented important modulators of growth (Wolters and Jurgens, 2009). However, to what extent changes in the activity of these candidate genes and in the synthesis or perception of phytohormones underlie morphological evolution as seen in the selfing syndrome remains unclear. The genus Capsella in the Brassicaceae provides a genetically tractable model to identify the molecular basis of selfing-syndrome evolution. The diploid selfing species C. rubella diverged from its outbreeding ancestor C. grandiflora between 50,000 and 100,000 years ago via a severe population bottleneck (Brandvain et al., 2013; Foxe et al., 2009; Guo et al., 2009; Sicard et al., 2011; Slotte et al., 2013). An independent transition to selfing occurred in a lineage leading to the extant species Capsella

Developmental Cell 44, 1–12, January 22, 2018 ª 2017 Elsevier Inc. 1

Please cite this article in press as: Fujikura et al., Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella, Developmental Cell (2017), https://doi.org/10.1016/j.devcel.2017.11.022

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Figure 1. Phenotypic Effect of the Chromosome 6 Petal-Size QTL (A–D) Petal size (A), petal-cell size (B), shoot dry weight (C), and mature-plant height (D) of NIL and qIL plants segregating for the chromosome 6 petal-size QTL. Values from plants homozygous for the C. grandiflora QTL allele (gg) are shown by gray bars here and throughout; those from plants homozygous for the C. rubella QTL allele (rr) are shown by white bars. The C. grandiflora allele causes a pleiotropic reduction in organ growth. Values are mean ± SD from 40 petals (4 petals/plant) (A and B) and ten plants (C and D). *p < 0.05, significantly different based on Student’s t test. (E–H) Average leaf size (E) and representative leaf outline (F), stamen length (G), and sepal size (H) of qIL plants with the indicated genotypes. Values are mean ± SD from more than ten organs. *p < 0.05, significantly different based on Student’s t test. (I–K) Representative petals and petal cells from the indicated genotypes. Scale bars, are 1 cm (F), 1 mm (I), and 50 mm (J; applies also to K). See also Figure S1.

orientalis before the C. rubella-C. grandiflora divergence (Hurka et al., 2012). The selfing syndrome is already fully established in C. rubella, with a more than 5-fold reduction in petal size compared with C. grandiflora, most of which is due to reduced cell proliferation in C. rubella petals (Sicard et al., 2011). A QTL analysis in a C. grandiflora 3 C. rubella population has indicated that the reduction in petal size is due to changes at more than six different loci (Sicard et al., 2011). Only one of these has been resolved at the molecular level and was found to reflect cis-regulatory variation in the general growth promoter STERILE APETALA that specifically reduces its activity in petal primordia (Sicard et al., 2016). Here, to investigate the molecular basis for selfing-syndrome evolution in Capsella, we identify the causal gene for a majoreffect petal-size QTL. Allelic variation in the gene encoding the brassinosteroid (BR)-biosynthesis enzyme CYP724A1 leads to higher BR levels in plants with the C. rubella allele. These increased amounts of BR inhibit cell proliferation. Increased CYP724A1 activity results from more efficient splicing of the C. rubella-derived allele due to two de novo mutations, highlighting the importance of variation in splicing efficiency and phytohormone levels for morphological evolution in plants. RESULTS The Chromosome-6 QTL Pleiotropically Affects ShootOrgan Growth Previous QTL mapping had localized a major-effect QTL for petal size on Capsella chromosome 6 that explains about 10% of the 2 Developmental Cell 44, 1–12, January 22, 2018

variation between the parental C. rubella and C. grandiflora species (Sicard et al., 2011). A near-isogenic line (NIL) segregating for an approximately 1.3-Mb region around the QTL in an otherwise largely C. rubella homozygous background was generated (see STAR Methods) and used to determine the phenotypic effect of this QTL and its genetic basis in detail. Plants homozygous for the C. grandiflora allele (NILgg) formed 28% larger petals than plants homozygous for the C. rubella allele (NILrr) (Figure 1A). This was due to a difference in cell numbers, as petal-cell sizes were indistinguishable between the two genotypes (Figure 1B). Segregation of the QTL region also affected overall plant height and dry weight, with NILgg plants about 28% taller and 50% heavier than NILrr plants (Figures 1C and 1D). Plants heterozygous for the QTL region showed an intermediate petal size compared with that of the two alternative homozygotes, indicating a semi-dominant action of the C. grandiflora QTL allele (Figure S1A). Thus, the C. grandiflora allele of the QTL pleiotropically increases plant organ growth. To identify the causal gene, we fine-mapped the QTL to a region of 16.7 kb between positions 4,665,216 and 4,681,919 on chromosome 6 (Figure S1B). To confirm our mapping results, we crossed the two closest suitable recombinants to generate a quasi-isogenic line (qIL) segregating for less than 40 kb including this 16.7-kb fragment in an otherwise essentially homozygous background. Again, plants homozygous for the C. grandiflora allele (qILgg) formed 24% larger petals than C. rubella homozygotes (qILrr), due to increased cell numbers (Figures 1A, 1B, and 1I–1K). The quasi-isogenic line also confirmed the pleiotropic

Please cite this article in press as: Fujikura et al., Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella, Developmental Cell (2017), https://doi.org/10.1016/j.devcel.2017.11.022

growth-enhancing effect of the C. grandiflora allele with respect to plant height, dry weight, and leaf size (Figures 1C–1F); by contrast, within the flowers stamen and sepal sizes were not significantly affected (Figures 1G and 1H), potentially reflecting differential sensitivity of the different floral organs to the activity of the causal QTL gene. Thus, this QTL pleiotropically affects the growth of shoot organs. The Chromosome-6 QTL Is due to Allelic Variation in the Transcribed Sequence of the CYP724A1 Locus The 16.7-kb region contains six genes, including a Capsella ortholog of the Arabidopsis thaliana CYP724A1 gene (Figures S1C, S1D, and S2). CYP724A1 encodes a cytochrome P450 enzyme that catalyzes hydroxylation at position C-22 in the synthesis of active BRs (Ohnishi et al., 2006; Sakamoto et al., 2006; Tanabe et al., 2005; Zhang et al., 2012a). To determine whether allelic variation at the CYP724A1 locus underlies the QTL effect, we transformed the genomic sequences of the C. grandiflora and the C. rubella alleles into A. thaliana. The C. grandiflora allele increased petal and leaf size by 17% and 19%, respectively, while the C. rubella allele had no statistically significant effect on leaf and petal size (Figures 2A–2C, S3A, and S3B). Exchanging the promoters and the transcribed sequences in the transformed constructs indicated that the different effects were entirely due to differences in the transcribed sequences, with no functional difference between the promoters (Figures 2A–2C). Thus, allelic differences in the transcribed region of the CYP724A1 locus underlie the petal-size QTL on chromosome 6. Sequence comparison between the two alleles from our mapping population identified three SNPs causing amino acid exchanges (Figure S2). Of these, two are conservative (Leu to Ile) and the third one (Thr to Met) affects an evolutionarily weakly conserved region among functional C-22 hydroxylases from A. thaliana, tomato, and rice (Ohnishi et al., 2006; Sakamoto et al., 2006; Tanabe et al., 2005; Zhang et al., 2012a); they are thus highly unlikely to explain the different allele effects. RTPCR indicated a pronounced difference in the accumulation of spliced versus unspliced transcripts for the two alleles (Figures 3A–3C), both in RNA from young floral buds and from dissected mature petals (Figure S4B). While the C. rubella allele was efficiently spliced, with only a low-level accumulation of unspliced transcript, much of the C. grandiflora transcript was present in the unspliced form (Figure 3C). Sanger sequencing of the major RT-PCR products confirmed that the large product (‘‘unspliced’’ in Figure 3C) contained all seven introns, whereas the smaller product (‘‘spliced mature mRNA’’ in Figure 3C) represents the spliced mature mRNA. qRT-PCR determination of mature, spliced mRNA levels using primers that were spanning exonexon junctions confirmed a higher accumulation of CYP724A1 mRNA from the C. rubella than the C. grandiflora allele (Figures 3A, 3B, and S4A). By contrast, qRT-PCR using a pair of primers of which one was located in an intron to detect unspliced transcript demonstrated higher levels of unspliced transcript from the C. grandiflora allele (Figure 3B). Lastly, qRT-PCR using primers within exon 8 indicated comparable levels of overall, spliced, and unspliced transcript (Figure 3B); together with the absence of any evidence for a functional difference in the promoters between the two alleles (cf. Figures 2A–2C), this equal

signal from both genotypes suggests that the unspliced transcript from the C. grandiflora allele is similarly stable to the fully spliced mRNA. Increased CYP724A1 Expression from the C. rubella Allele Causes Higher-Than-Optimal BR Levels that Inhibit Petal-Cell Proliferation The above observations raised the hypothesis that increased CYP724A1 expression from the C. rubella allele due to more efficient splicing causes the synthesis of more bioactive BRs beyond the optimum level, such that growth is inhibited by the excess BRs in NILrr and qILrr lines. Growth stimulation by low levels, but growth inhibition by high levels of BRs or long BR treatment has been demonstrated in roots and leaves before (Li et al., 2001; Montoya et al., 2002; Mussig et al., 2003; Zhiponova et al., 2013). This hypothesis leads to four testable predictions. First, BR levels should be higher in plants carrying the C. rubella allele than in ones with the C. grandiflora allele. Second, introducing the C. rubella allele into the qILgg background should decrease petal size, whereas—third—downregulating CYP724A1 expression in qILrr plants should increase their petal size. Fourth, exogenous BR treatment should decrease petal size, particularly in qILgg plants. First, levels of bioactive BRs were determined in inflorescences using liquid chromatography-tandem mass spectrometry analysis. Inflorescences of both NILrr and qILrr plants indeed contained higher levels of brassinolide than NILgg and qILgg plants (Figures 4A and 4B). Second, we determined whether the C. rubella CYP724A1 allele could dominantly reduce petal size in a background homozygous for the C. grandiflora allele. Introducing the C. rubella allele of CYP724A1 or a chimeric construct with the C. rubella-transcribed sequence, but the C. grandiflora-derived promoter into qILgg plants decreased their petal size to that of qILrr plants, whereas the transgenes had no effect in a qILrr background (Figures 2D and 2E). By contrast, the C. grandiflora allele had little to no effect in either background (Figure S3C). Third, to determine whether conversely reducing the activity of CYP724A1 in plants carrying the C. rubella allele would increase their petal size, CYP724A1 expression was downregulated in qILrr plants by microRNAinduced gene silencing (MIGS) (Felippes et al., 2012) under the control of the petal-specific APETALA3 (AP3) promoter. qRTPCR on young inflorescences of three independent transformant lines confirmed strong downregulation of CYP724A1 expression (Figure S3D). Petals of these transgenic plants grew larger, reaching the size of those from qILgg plants (Figures 2G and 2H). As seen for allele substitution at the QTL in NIL and qIL plants, the increased petal growth in the MIGS lines was due to higher cell numbers rather than larger cell size (Figure 2I). Of note, the observation that this strong downregulation of CYP724A1 expression in Capsella did not cause any obvious BR-deficiency phenotypes is consistent with the result from A. thaliana cyp724a1 T-DNA insertion mutants that do not show any clear morphological phenotypes and form petals of the same size as those of wild-type plants (Figure S3E). This suggests that CYP724A1 plays a more localized role in modulating BR levels in A. thaliana and possibly Capsella. Fourth, developing flowers of the NIL plants were treated with exogenous BR to test whether this would reduce petal size. Indeed, BR treatment Developmental Cell 44, 1–12, January 22, 2018 3

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Figure 2. Identification of CYP724A1 as the Causal Gene (A–C) Representative petals (A), petal size (B), and leaf size (C) of transgenic A. thaliana plants expressing the C. grandiflora or C. rubella alleles of CYP724A1 (pCgCYP::CgCYP, pCrCYP::CrCYP) or the corresponding promoter swap constructs pCrCYP::CgCYP and pCgCYP::CrCYP. Schematic drawings of constructs are shown within the bars, with the promoter indicated by the arrow and the transcribed sequence by the box. Sequences derived from the C. grandiflora allele are shown by gray fill and those from the C. rubella allele by white fill. WT denotes non-transgenic wild-type (n > 10); bars with schematic constructs inside represent average value of eight independent transgenic lines per construct, with more than 12 plants per line. The C. grandiflora transcribed sequence increases organ growth irrespective of the promoter used. Values are mean ± SD. *p < 0.05, significantly different based on Student’s t test. (D–F) Representative petals (D) and petal size (E and F) from qILgg and qILrr plants transformed with the C. rubella allele of CYP724A1 (D and E) or with the chimeric pCgCYP724A1::CrCYP724A1 construct (F). Constructs are indicated as in (B) and (C). The C. rubella transcribed sequence reduces petal growth in a qIL_gg background but not in qIL_rr background. Values are mean ± SD from 40 petals (4 petals/plant). *p < 0.05, significantly different based on Student’s t test. (G–I) Representative petals (G), petal size (H), and petal-cell size (I) from qILrr plants with downregulated CYP724A1 expression in petals using the petal-specific APETALA3 (AP3) promoter. Downregulation of CYP724A1 expression increases petal size in a qIL_rr background. See Figure S3D for quantification of CYP724A1 expression. Values are mean ± SD from 40 petals (4 petals/plant) and from more than 400 cells from ten petals in (H) and (I). *p < 0.05, significantly different from non-transgenic qILrr based on Student’s t test. Scale bars, 1 mm (A, D, and G). See also Figures S1–S3.

reduced the petal size of qILgg plants to that of qILrr plants, while the treatment had no significant effect in the qILrr background (Figures 4C and 4E). BR treatment affects qILgg petal-cell number, not cell size (Figures 4D and 4E). Together, these results support our conclusion that higher CYP724A1 expression due 4 Developmental Cell 44, 1–12, January 22, 2018

to more efficient splicing of the C. rubella allele causes overaccumulation of BRs that become inhibitory for petal growth. Transformation of the two CYP724A1 alleles into A. thaliana produced a different result than transformation into Capsella qIL plants (Figures 2A–2F and S3C). Importantly, in both

Please cite this article in press as: Fujikura et al., Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella, Developmental Cell (2017), https://doi.org/10.1016/j.devcel.2017.11.022

backgrounds there was a clear difference between the effects of the C. grandiflora and the C. rubella alleles; however, in A. thaliana the C. grandiflora allele increased petal size and the C. rubella allele had no significant effect, while in Capsella qILgg lines the C. grandiflora allele had no effect and the C. rubella allele decreased petal size. In light of these findings, a possible explanation would be that A. thaliana flowers contain suboptimal levels of BR, such that a small increase due to the C. grandiflora allele leads to larger petals, while a more substantial increase due to the C. rubella allele again becomes inhibitory. By contrast, Capsella qILgg flowers would be at optimal BR levels, such that their petal size could only be decreased by higher BR levels brought about by the C. rubella allele. To test this notion, we treated wild-type A. thaliana and Capsella qILgg plants with increasing concentrations of exogenous BR. As seen above, treatment of qILgg with increasing concentrations of BR reduced their petal size; yet importantly, none of the lower-level treatments was able to increase qILgg petal size further (Figure 4F). By contrast, low-level BR treatment in A. thaliana did increase petal size while higher concentrations led to smaller petals (Figure 4E). Petals of Capsella qILrr plants did not respond significantly to either treatment with BR (Figure S3F). We were not able to directly measure BR levels in petal primordia of the different transgenic lines with increased or decreased CYP724A1 activity and of the plants after exogenous BR treatment to determine by how much these manipulations affect BR levels in petals compared with the differences in endogenous levels measured between the NILrr/qILrr and NILgg/qILgg plants. Nevertheless, given their internal consistency, the above results support the hypotheses that high BR levels inhibit petal growth and that the different effects seen in A. thaliana and Capsella qILgg transformants reflect their different baseline states relative to the BR optimum, with the C. grandiflora CYP724A1 allele causing a small increase in BR levels and the C. rubella allele a more substantial one in both backgrounds. Two Exonic SNPs Underlie Differential Splicing Efficiency of the CYP724A1 Alleles To determine the molecular basis for the differential splicing efficiency of the primary CYP724A1 transcript, we sought to recapitulate the splicing difference by transient expression in Arabidopsis mesophyll protoplast (TEAMP) assays (Yoo et al., 2007). When expressed under the control of the 35S promoter in A. thaliana protoplasts, the C. grandiflora CYP724A1 allele was again inefficiently spliced; by contrast, the C. rubella allele underwent efficient splicing (Figures 3D–3F, S4C, and S4D). Thus, the determinants of the allele-specific splicing efficiency cause the same effect in A. thaliana cells as in the Capsella background. Using a set of chimeric constructs (Figure 3D), the causal polymorphisms could be delimited to within the first two exons and the first intron; as long as this region was from C. grandiflora, splicing was inefficient, affecting both the first intron derived from the C. grandiflora allele (Figure 3E) but also distal C. rubella-derived introns (Figure 3F). This region contains five SNPs between the two alleles, two in exon 1, one in intron 1, and two in exon 2 (Figure S4E). To identify the causal SNPs underlying the differential splicing efficiency, we reciprocally substituted single nucleotides into the other allelic background, either in a minigene consisting of CYP724A1 exon 1-intron

1-exon 2 fused to CFP or in the full-length coding sequence. Testing the splicing efficiency of the resulting constructs expressed in A. thaliana protoplasts under the control of the 35S promoter indicated that SNPs 2 and 4 contributed to the differential splicing efficiency between the alleles (Figures 3G and 3H). Introducing the C. rubella-like nucleotide at these positions into a C. grandiflora background increased the splicing efficiency of intron 1; conversely, substituting the C. grandiflora-like nucleotide in a C. rubella background decreased intron-1 splicing (Figures 3G and 3H). These effects were confirmed in stably transformed A. thaliana cell cultures (Figure 3I). We also assayed the effect of combined exchanges of SNP2 and SNP4 in the minigene context (Figure 3I, right panels). When both C. grandiflora SNPs are introduced into the C. rubella background (‘‘CrCYP w/ CgSNPs’’), only a very low level of spliced transcript is observed, closely mirroring the result of the unmodified C. grandiflora allele (compare right panels of Figures 3G and 3I). Conversely, when introducing C. rubella SNPs into the C. grandiflora background, the double-exchange construct shows a ratio of spliced to unspliced transcript comparable with that of the single-exchange constructs and the unmodified C. rubella allele (Figures 3G and 3I). Thus, it appears that already a single C. rubella-like SNP is sufficient to cause a substantial increase in splicing efficiency in the C. grandiflora allele background, and that the two C. rubella-like SNP alleles do not act in an additive manner. Both SNPs 2 and 4 are located in exons; while SNP2 causes the conservative amino acid exchange of leucine to isoleucine at position 68 in the protein, SNP4 is silent. Thus, two exonic SNPs cause differential splicing efficiency of the C. grandiflora versus C. rubella alleles of CYP724A1. To determine whether these two SNPs are indeed sufficient to explain the different phenotypic effects of the two CYP724A1 alleles in plants, we expressed the genomic coding sequences of different Capsella CYP724A1 versions in A. thaliana under the control of the 35S promoter and measured petal sizes of the transformants (Figure 3K). While expression of the unmodified C. grandiflora allele did not cause a statistically significant change in petal size, expression of the C. rubella allele decreased petal size by approximately 15%. When the SNP2 and SNP4 nucleotides from C. rubella were both introduced into the C. grandiflora allele background, this construct also reduced A. thaliana petal size by a similar amount, confirming that SNP2 and SNP4 are indeed sufficient to convert the activities of the alleles. Introducing only the SNP2 or the SNP4 nucleotides from C. rubella also reduced petal size, with a comparable effect to the double substitution, in accordance with the nonadditive effect of the two SNPs in the above splicing assays. Importantly, the SNP4-exchange construct strongly supports the hypothesis that the allele differences are due to their different splicing efficiencies, as SNP4 does not alter the encoded protein sequence. More Efficient Splicing Represents the Evolutionarily Derived State due to Two De Novo Mutations in C. rubella We next asked whether inefficient splicing of CYP724A1 was seen throughout the ancestral species C. grandiflora, with the more efficient splicing in C. rubella as the derived state; or whether inefficient splicing was limited to the C. grandiflora allele Developmental Cell 44, 1–12, January 22, 2018 5

Please cite this article in press as: Fujikura et al., Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella, Developmental Cell (2017), https://doi.org/10.1016/j.devcel.2017.11.022

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Figure 3. Differential Splicing Efficiency of Alternative CYP724A1 Alleles (A) CYP724A1 mature mRNA levels quantified by qRT-PCR in inflorescences of the indicated genotypes relative to ACTIN2. Values are mean ± SD from three biological replicates. (B) Overall CYP724A1 transcript levels, spliced levels, and unspliced levels as determined by qRT-PCR in inflorescences of the indicated genotypes relative to ACTIN2. See Figure S4A for details of primer placement for the different forms. Values are mean ± SD from three biological replicates. (C) Differential splicing efficiency of CYP724A1 transcript from the C. rubella (left) and the C. grandiflora (right) alleles in the indicated NILs as determined by RTPCR in inflorescences. Three biological replicates are shown. (legend continued on next page)

6 Developmental Cell 44, 1–12, January 22, 2018

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segregating in our RIL population. RT-PCR analysis of eight unrelated C. grandiflora individuals indicated that all of them accumulated high levels of unspliced CYP724A1 pre-mRNA (Figure 3J), as did eight accessions of the independently derived selfing species C. orientalis (Figures S5A and S5B) (Hurka et al., 2012). This was consistent with sequence analysis of the causal CYP724A1 region, indicating that all tested C. grandiflora samples were homozygous for the C. grandiflora-like SNP alleles at positions 2 and 4, while for the other three SNPs at least one of the tested C. grandiflora samples with inefficient splicing carried a C. rubella-like allele; C. orientalis also shares the C. grandiflora-like allele at SNP4 (Figure S5C), while the sequence surrounding SNP2 is too divergent in pairwise alignments. These findings support the causal role of the SNPs 2 and 4, and indicate that efficient splicing represents the derived state in C. rubella compared with the ancestral inefficient splicing in C. grandiflora. To determine whether the causal SNPs arose by novel mutations in the C. rubella lineage or were derived from standing genetic variation in C. grandiflora, we analyzed CYP724A1 haplotypes from an additional 182 C. grandiflora individuals. SNPs 2 (at position 4,678,409) and 4 (at 4,678,610) were very strongly differentiated between the two species (Figure 5C). While all of the 51 C. rubella accessions analyzed were fixed for the Cr1504-like alleles present in our RIL population, 168 C. grandiflora accessions were homozygous for the C. grandiflora Cg926-like alleles found in this population. The remaining 14 C. grandiflora accessions were heterozygous for SNPs 2 and 4. Using a k-mer enrichment approach, 13 of these accessions show a strong signal for a long CYP724A1 locus-wide C. rubella-like haplotype (Figures 5A and 5B). Given the very short range of linkage disequilibrium in the outbreeding C. grandiflora of a few hundred base pairs (Sicard et al., 2014), such long C. rubella-like haplotypes are very unlikely to have been maintained unrecombined since the divergence of the two lineages about 100,000 years ago; rather, they are likely to have been reintroduced to C. grandiflora by more recent hybridization, such that there have not been enough generations since to erode the C. rubella-like haplotypes by meiotic recombination. An exception is sample Cg152P (arrowhead in Figure 5C), which was not identified as an introgression candidate when probing for the entire CYP724A1 locus; however, Cg152P does contain a C. rubella-like haplotype extending for

several kilobases to the left of the locus. Therefore, we conclude that the more efficiently spliced C. rubella allele most likely arose by two de novo mutations in the selfing lineage after its divergence from C. grandiflora. DISCUSSION To begin to understand the molecular and developmental basis of the selfing syndrome in plants, we have identified the causal gene underlying a major-effect petal-size QTL in Capsella; determined its developmental and physiological effects; analyzed the molecular basis of the allelic variation; and retraced the evolutionary history of the causal mutations. This has led to two unexpected conclusions about the molecular and developmental causes of morphological variation. First, more efficient splicing of the C. rubella CYP724A1 primary transcript has evolved as the derived state from inefficient splicing in the ancestral C. grandiflora allele by two single-nucleotide mutations affecting exonic splicing-regulatory sequences. Second, stronger CYP724A1 expression in C. rubella causes higher-than-optimal levels of BRs that become inhibitory for petal growth. Two Mutations to Exonic Sequences Increase Splicing Efficiency Our analysis of chimeric constructs in TEAMP assays has pinpointed two SNPs, one in exon 1 and the other in exon 2, as causing differences in the splicing efficiency of intron 1, as well as all other introns in CYP724A1 pre-mRNA. The results from transgenic plants confirmed that these two SNPs are indeed causal and sufficient to explain the different biological effects of the C. grandiflora and the C. rubella alleles. The systematic analysis of sequence elements that influence the splicing efficiency of human introns has identified exonic splicing enhancer (ESE) and exonic splicing silencer (ESS) motifs (Lee and Rio, 2015). ESEs tend to be located close to the affected exon-intron boundaries; they are generally purin rich, act by binding SR proteins involved in splicing, and constrain sequence evolution toward exon ends due to purifying selection maintaining ESE function (Caceres and Hurst, 2013). Comparing the sequences surrounding SNPs 2 and 4 with catalogs of human ESE elements identified the motif GATGAT in C. rubella at SNP2 as a candidate

(D) Schematic representation of the constructs used for protoplast transformation and RT-PCR products for CYP724A1 using primers spanning intron 1 (left, ‘‘primer1’’) and intron 6 (right, ‘‘primer2’’). Exons are indicated by boxes, introns by the black line; the 35S promoter and nos terminator sequences are indicated. Sequences derived from the C. grandiflora allele are shown by gray fill in exons and those from the C. rubella allele by white fill in exons. (E and F) RT-PCR performed on RNA from transiently transformed protoplasts to detect splicing defect in intron 1 (E) or intron 6 (F). Protoplasts were transformed with the constructs shown to the left of the gel images in (D). Cr-Cg indicates the construct with the first exons from C. rubella and the later ones from C. grandiflora, and Cg-Cr indicates the complementary combination. PCR products of spliced and unspliced transcripts are indicated on the right. The origin of exon 1-intron 1-exon 2 determines the splicing efficiency not just of intron 1 (E) but also of intron 6 (F). (G and H) Splicing assay of CrCYP724A1 constructs carrying the C. grandiflora allele at the indicated SNP (left) or of CgCYP724A1 constructs carrying the C. rubella allele at the indicated SNP (right). Results from protoplasts expressing truncated CYP724A1 fused to CFP (G) or full-length CYP724A1 (H) are shown. (I) Splicing assay in stably transformed A. thaliana suspension cell cultures. Constructs are as in (G). Right-hand panels show cultures expressing constructs with both SNP2 and SNP4 exchanged as indicated, as well as ACT control to demonstrate the absence of DNA contamination. (J) RT-PCR products for CYP724A1 from eight C. grandiflora accessions from different geographical regions assayed using primers spanning intron 1. Weak lower band (arrowhead) represents the spliced product. (K) Petal sizes of transgenic Arabidopsis plants expressing the indicated Capsella CYP724A1 genomic coding sequences under the control of the 35S promoter. Constructs are shown schematically within bars, with the arrow indicating 35S promoter and the box the transcribed sequence; gray is C. grandiflora-derived sequence, white is C. rubella-derived sequence. ‘‘Control’’ is non-transgenic Columbia-0 wild-type. Values are mean ± SD of 80 petals of 10 plants from 4 to 8 independent transgenic lines per construct and the same for controls. Asterisk indicates significant difference from the control as determined by ANOVA followed by Tukey’s HSD test (*p < 0.05). See also Figures S4 and S5.

Developmental Cell 44, 1–12, January 22, 2018 7

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Figure 4. Effect of Exogenous Brassinosteroid Treatment on Petal Growth (A and B) Quantification of castasterone (CS) and brassinolide (BL) levels in flowers of the alternative NIL (A) and qIL genotypes (B). Values are mean ± SD from three biological replicates. *p < 0.05, significantly different based on Student’s t test. (C) Petal size of qILgg and qILrr plants treated with epi-brassinolide (EBL) (100 nM, twice a day). Values are mean ± SD from 40 petals (4 petals/plant). *p < 0.05, significantly different based on Student’s t test. (D) Petal-cell sizes in qILgg plants after EBL treatment. Values are mean ± SD from more than ten petals. (E) Representative petals (top) and petal cells (bottom) from plants with the indicated genotypes treated with H2O or EBL. Scale bars, 1 mm (top) and 50 mm (bottom). (F and G) Petal sizes of A. thaliana wild-type (F) and Capsella qIL_gg plants (G) treated with the indicated concentrations of epi-brassinolide (EBL) once a day after the start of flowering. Values are mean ± SD from more than 48 petals (4 petals/plant). *p < 0.05, significantly different from mock control based on ANOVA followed by Tukey’s HSD test. See also Figure S3.

ESE (based on the RESCUE-ESE dataset from Fairbrother et al., 2002 and on the INT2.400 dataset from Caceres and Hurst, 2013), while the corresponding C. grandiflora sequence GATGCT was not found in these datasets. Similarly, the motif GATGAC in C. rubella at SNP4 is a putative ESE according to Caceres and Hurst (2013) (INT2.400 dataset), while the corresponding C. grandiflora sequence GACGAT is not. Thus, despite uncertainties about the transferability of these motifs from humans to plants, these comparisons suggest that the two causal nucleotide exchanges result in the establishment of (more efficient) ESEs close to both exon-intron junctions of intron 1 in C. rubella, ultimately causing its more efficient splicing. As the sequences surrounding intron 1 appear to affect the splicing efficiency of all downstream introns and also those derived from the other allele in chimeric constructs, it is tempting to speculate that inefficient removal of the first intron in the C. grandiflora allele also blocks splicing further downstream. This would explain the observed largely all-or-nothing variation in splicing, whereby transcripts are either fully spliced to the mature mRNA or remain 8 Developmental Cell 44, 1–12, January 22, 2018

unspliced with all introns present, while intermediate products are only found at very low levels. Our population-genetic analysis of CYP724A1 sequence and splicing efficiency in the three Capsella species indicates that the inefficient splicing represents the ancestral state, still found today in C. grandiflora and C. orientalis, and that the more efficient splicing of the C. rubella allele results from two mutations that occurred in the lineage leading to C. rubella, rather than having been captured from standing variation in the ancestral C. grandiflora population. Why might inefficient splicing and intron retention be maintained in C. grandiflora, but have been modified in the derived C. rubella? A trivial explanation would be that inefficient selection in the selfing population has allowed the two underlying mutations to become fixed by drift, without any selective benefit or disadvantage (Wright et al., 2013). Alternatively, it is known that the regulated retention of introns and their removal in response to an endogenous or environmental stimulus controls several developmental transitions in yeast and animals

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(Averbeck et al., 2005; Naro et al., 2017; Ni et al., 2016; Wong et al., 2013), and the extent of intron retention in plants is responsive to environmental stress (Filichkin et al., 2015). Thus, it is an interesting possibility that the inefficient splicing in C. grandiflora may allow for regulation of CYP724A1 activity by stimulus-responsive splicing, while this may have been forsaken in favor of a constitutively higher expression in the geographically more widespread C. rubella. Further studies will be needed to address this possibility and any selective advantage or otherwise of the more efficient splicing in C. rubella, which remains unknown at present. The importance of genetic variation in exonic splicing-regulatory sequences such as ESEs and ESSs for human disease is well established, and about one-quarter of disease-causing mis-sense or non-sense mutations in humans also affects exonic splicing-regulatory sequences (Sterne-Weiler et al., 2011). Prominent examples for disease-causing ESE or ESS mutations occur in the dystrophin gene leading to muscular dystrophy (Disset et al., 2006) and in exon 10 of the microtubule-associated protein tau (MAPT) gene, altering the ratio between two splice variants and causing frontotemporal dementia (D’Souza and Schellenberg, 2000; Iqbal et al., 2016). Beyond these Mendelian diseases, the importance of splicing variation for complex human disease has also recently been recognized (Fraser and Xie, 2009; Garcia-Blanco et al., 2004; Li et al., 2016). Extensive differences in alternative splicing are seen between related Drosophila species, with much of

Samples CgPop CgPop_ig CrDK Cg926 Cr1504

(A) Putative recent C. rubella CYP724A1 introgression in the C. grandiflora population was estimated by counting the presence of C. rubella reference like k-mers of different lengths (in bp) in genome resequencing raw data of a C. grandiflora population (CgPop) and in a species-wide sample of C. rubella (CrDK) around the CYP724A1 locus (transcribed sequence ±1,000 bp). Each line represents an individual. The C. grandiflora population contains 13 samples (shown in red; CgPop_ig) with a signal of recent introgression of the CYP724A1 locus from C. rubella, i.e., a high proportion of long C. rubella reference k-mers. (B) Density distribution of samples with the given presence of C. rubella reference 63-mers. Colors are as in (A). (C) Haplotype clustering and genotype at polymorphisms in the 50 region of CYP724A1 of all the resequenced individuals. Analysis was restricted to all SNPs polymorphic between the two alleles segregating in our RIL population. The red squares indicate C. grandiflora individuals with a signal of more recent introgression from C. rubella (CgPop_ig) as identified in (A) and (B). This dataset includes sequences from all C. grandiflora resequenced individuals (CgPop), from the parental NILgg (Cg926) and NILrr (Cr1504) alleles, and from all publicly available C. rubella genomes (CrDK). Arrowhead indicates individual Cg152P. See also Figure S5.

this variation reflecting cis-regulatory changes, including those in exonic splicing-regulatory sequences (McManus et al., 2014). There are few functional studies linking natural variation in splicing to phenotypes outside of humans. In plants, variable alternative splicing and exon skipping in the P5CS1 gene, encoding an enzyme for proline biosynthesis, due to intronic sequence polymorphisms is associated with variation in drought-induced proline accumulation and potentially adaptation to climate (Kesari et al., 2012); a splice-site mutation in the Brassica rapa FLOWERING LOCUS C gene BrFLC1 found in some cultivated strains is associated with mis-splicing and earlier flowering (Yuan et al., 2009); moreover, different intronic sequence variants in the A. thaliana FLOWERING LOCUS M gene affect the competition between splicing and polyadenylation in the first intron, contributing to natural variation in flowering time (Lutz et al., 2015, 2017). However, none of these previously studied examples from plants involves variation in exonic sequences as potential ESEs as seen here. Also, in contrast to the above examples from plants and to human mutations in exonic splicing-regulatory sequences that modulate the rate of inclusion of individual exons, our Capsella example illustrates an all-or-nothing switch between fully unspliced or spliced forms, adding a further layer to natural splicing-related variation. Thus, our study provides a test case for understanding the molecular basis of splicing-related natural variation and its potentially widespread role in generating phenotypic diversity in plants. Developmental Cell 44, 1–12, January 22, 2018 9

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Higher-Than-Optimal BR Levels in the Evolutionarily Derived State Inhibit Organ Growth Our measurements of BR levels in NIL and qIL plants carrying different alleles of CYP724A1 indicate that the more efficient splicing of the C. rubella allele leads to the accumulation of higher levels of brassinolide and castasterone than in plants with the C. grandiflora allele. At first sight, this appears to contradict findings from RNA sequencing (RNA-seq) of inflorescences of the two species, suggesting reduced BR signaling and thus reduced BR levels in C. rubella. However, this conclusion was based on reduced expression of BR-responsive genes that act during pollen maturation (Slotte et al., 2013), which is explained by the 4-fold reduction in pollen numbers per flower in the selfing species (Sicard et al., 2011). This difference in pollen number was eliminated between our NIL genotypes, allowing us to detect the higher BR levels in plants with the C. rubella CYP724A1 allele. Our combined evidence indicates that these higher BR levels are inhibitory for petal-cell proliferation and growth. First, the C. rubella allele dominantly reduced petal size in an qILgg background. Second, downregulating CYP724A1 expression in qILrr plants conversely increased petal size. Third, exogenous BR treatment reduced petal size in qILgg while it had little effect in qILrr plants. Together, this suggests that plants with the C. rubella allele are positioned beyond the optimum on the BR response curve of shoot-organ growth, while plants with the C. grandiflora allele appear to be located close to the optimum; incidentally, A. thaliana appears to contain suboptimal BR levels for maximum petal growth, as introducing the C. grandiflora allele of CYP724A1 or treatment with low concentrations of exogenous BR could increase its petal size. The role of suboptimal hormone levels in causing natural morphological variation has been demonstrated before—for example, the lower BR levels resulting from naturally occurring mutant alleles of BREVIS RADIX that underlie their short-root phenotype (Mouchel et al., 2006). However, our findings suggest that also the possibility of higher-thanoptimal hormone levels needs to be considered more widely as an explanation for morphological changes in evolutionarydevelopmental research. In conclusion, our study has identified two aspects of broader significance for the study of morphological evolution. First, the CYP724A1 example highlights the importance of variation in exonic splicing-regulatory sequences and the resulting variation in overall splicing efficiency as a cause for phenotypic change. Second, our work underscores the notions that for hormones or other signals whose activity follows an optimum curve both deviations to the lower or to the higher side from the optimum can underlie evolutionary change, and that there can be too much of a good thing underlying natural evolution. STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: d d d

KEY RESOURCES TABLE CONTACT FOR REAGENT AND RESOURCE SHARING EXPERIMENTAL MODEL AND SUBJECT DETAILS

10 Developmental Cell 44, 1–12, January 22, 2018

d

d d

METHOD DETAILS B Plant Phenotyping B BR Measurements B Exogenous BR Treatment B Genetic Mapping B Molecular Cloning and Plant Transformation B Gene Expression and Splicing Analysis B Protoplast Assays and Stable Suspension Culture Cell Transformation B Population Genetic Analysis QUANTIFICATION AND STATISTICAL ANALYSIS DATA AND SOFTWARE AVAILABILITY

SUPPLEMENTAL INFORMATION Supplemental Information includes five figures and one table and can be found with this article online at https://doi.org/10.1016/j.devcel.2017.11.022. ACKNOWLEDGMENTS €ker for plant care; to BarWe are grateful to Christiane Schmidt and Doreen Ma bara Neuffer, Adrien Sicard, and Stephen Wright for providing seeds and sequence information; to Daniel Koenig and Detlef Weigel for making C. rubella genome sequences available prior to publication; to Florian Schroeder for providing the A. thaliana suspension cell culture; to Peggy Lange and Cindy Marona for help with petal-size measurements; and to Laura Golusda and €urle, Adrien Hannes Thonagel for help with splicing assays. We thank Isabel Ba Sicard, and members of the Lenhard group for discussion and comments. This work was funded by an ERC Starting Grant (260455) to M.L. AUTHOR CONTRIBUTIONS U.F. carried out the functional characterization of CYP724A1 in Arabidopsis and Capsella, including phenotyping, expression analysis, production of transgenic plants, and splicing experiments, including TEAMP assay and cell-culture experiments. R.J. performed QTL and fine mapping and established NIL and qIL plants. A.H. and S.Y. measured BR levels in NIL plants, and Y.T. and H.S. measured BR levels in qIL plants. C.K. performed population-genetics analysis. M.L. designed and supervised the project and wrote the manuscript with input from all authors. Received: September 19, 2016 Revised: October 10, 2017 Accepted: November 27, 2017 Published: December 21, 2017 REFERENCES Averbeck, N., Sunder, S., Sample, N., Wise, J.A., and Leatherwood, J. (2005). Negative control contributes to an extensive program of meiotic splicing in fission yeast. Mol. Cell 18, 491–498. Barrett, S.C. (2010). Understanding plant reproductive diversity. Philos. Trans. R. Soc. B Biol. Sci. 365, 99–109. Becker, D., Kemper, E., Schell, J., and Masterson, R. (1992). New plant binary vectors with selectable markers located proximal to the left T-DNA border. Plant Mol. Biol. 20, 1195–1197. Brandvain, Y., Slotte, T., Hazzouri, K.M., Wright, S.I., and Coop, G. (2013). Genomic identification of founding haplotypes reveals the history of the selfing species Capsella rubella. PLoS Genet. 9, e1003754. Caceres, E.F., and Hurst, L.D. (2013). The evolution, impact and properties of exonic splice enhancers. Genome Biol. 14, R143. Chen, K.Y., Cong, B., Wing, R., Vrebalov, J., and Tanksley, S.D. (2007). Changes in regulation of a transcription factor lead to autogamy in cultivated tomatoes. Science 318, 643–645.

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Sas, C., Muller, F., Kappel, C., Kent, T.V., Wright, S.I., Hilker, M., and Lenhard, M. (2016). Repeated inactivation of the first committed enzyme underlies the loss of benzaldehyde emission after the selfing transition in Capsella. Curr. Biol. 26, 3313–3319.

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Sicard, A., and Lenhard, M. (2011). The selfing syndrome: a model for studying the genetic and evolutionary basis of morphological adaptation in plants. Ann. Bot. 107, 1433–1443.

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Yoo, S.D., Cho, Y.H., and Sheen, J. (2007). Arabidopsis mesophyll protoplasts: a versatile cell system for transient gene expression analysis. Nat. Protoc. 2, 1565–1572. Yoshimoto, K., Jikumaru, Y., Kamiya, Y., Kusano, M., Consonni, C., Panstruga, R., Ohsumi, Y., and Shirasu, K. (2009). Autophagy negatively regulates cell death by controlling NPR1-dependent salicylic acid signaling during senescence and the innate immune response in Arabidopsis. Plant Cell 21, 2914–2927. Yuan, Y.X., Wu, J., Sun, R.F., Zhang, X.W., Xu, D.H., Bonnema, G., and Wang, X.W. (2009). A naturally occurring splicing site mutation in the Brassica rapa FLC1 gene is associated with variation in flowering time. J. Exp. Bot. 60, 1299–1308. Zhang, R., Xia, X., Lindsey, K., and da Rocha, P.S. (2012a). Functional complementation of dwf4 mutants of Arabidopsis by overexpression of CYP724A1. J. Plant Physiol. 169, 421–428. Zhang, Y., Werling, U., and Edelmann, W. (2012b). SLiCE: a novel bacterial cell extract-based DNA cloning method. Nucleic Acids Res. 40, e55. Zhiponova, M.K., Vanhoutte, I., Boudolf, V., Betti, C., Dhondt, S., Coppens, F., Mylle, E., Maes, S., Gonzalez-Garcia, M.P., Cano-Delgado, A.I., et al. (2013). Brassinosteroid production and signaling differentially control cell division and expansion in the leaf. New Phytol. 197, 490–502.

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STAR+METHODS KEY RESOURCES TABLE

REAGENT or RESOURCE

SOURCE

IDENTIFIER

ThermoFisher

Cat#18290015

Bacterial and Virus Strains ElectroMAX DH10B Chemicals, Peptides, and Recombinant Proteins Murashige and Skoog basal medium including vitamins

Duchefa

Cat#M0222

Gelrite

Duchefa

Cat#G1101

Gibberellic acid 4+7

Duchefa

Cat#G0938

TRIzol Reagent

Ambion

Cat#15596018

Phusion High Fidelity DNA Polymerase

New England Biolabs

Cat#M0530S

Tween 20

Sigma Aldrich

Cat#P9416-100ML

CloneAmp HiFi PCR Premix

Clontech

Cat#639298

Thermostable b-Agarase

Takara

Cat#317-07123

Cellulase ‘‘Onozuka’’ R-10

YAKULT

N/A

Macerozyme R-10

YAKULT

N/A

Claforan

Duchefa

Cat#C0111

[2H]4 CS

Dr. Hideharu Seto (RIKEN, Wako, Saitama, Japan)

N/A

[2H]4 BL

Dr. Hideharu Seto (RIKEN, Wako, Saitama, Japan)

N/A

chloroform

Wako Pure Chemical Industries, Ltd.

Cat#038-02606

SepPak Silica

Waters

Cat#WAT023595

Methanol

Wako Pure Chemical Industries, Ltd.

Cat#131-01826

ODS column (CAPCELL PAK C18)

Shiseido

Cat#92533

Acetonitrile

Wako Pure Chemical Industries, Ltd.

Cat#019-21691

Epibrassinolide

Sigma Aldrich

Cat#E1641

Critical Commercial Assays SuperScript III First-Strand Synthesis System for RT-PCR

Invitrogen

Cat#18080-051

Q5 Site-Directed Mutagenesis Kit

New England Biolabs

Cat#E0554S

SensiMix SYBR Low-ROX kit

BioLine

Cat#QT625-05

Illumina genome sequencing raw data for 182 individuals from a C.grandiflora population

Josephs et al., 2015

NCBI SRA: PRJNA275635

Illumina genome sequencing raw data for 52 C.rubella accessions

Made available by Daniel Koenig and Detlef Weigel prior to publication

EBI ENA: PRJEB6689

C.rubella reference genome

Slotte et al., 2013

http://www.phytozome.net/ capsella.php

Arabidopsis thaliana (L.) Heynh, Col-0

N/A

N/A

Capsella rubella 1504

Sicard and Lenhard, 2011

N/A

Capsella grandifolia 926

Sicard and Lenhard, 2011

N/A

Capsella near-isogenic lines segregating for QTL6

This paper

N/A

Capsella quasi-isogenic lines segregating for QTL6

This paper

N/A

cyp724a1 Arabidopsis thaliana mutant

Nottingham Arabidopsis Stock Centre (NASC)

SALK_115641

A. thaliana: pCgCYP724A1::CgCYP724A1

This study

N/A

A. thaliana: pCrCYP724A1::CrCYP724A1

This study

N/A

Deposited Data

Experimental Models: Organisms/Strains

(Continued on next page)

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Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

A. thaliana: pCgCYP724A1::CrCYP724A1

This study

N/A

A. thaliana: pCrCYP724A1::CgCYP724A1

This study

N/A

Capsella qILgg: pCgCYP724A1::CgCYP724A1

This study

N/A

Capsella qILrr: pCgCYP724A1::CgCYP724A1

This study

N/A

Capsella qILgg: pCrCYP724A1::CrCYP724A1

This study

N/A

Capsella qILrr: pCrCYP724A1::CrCYP724A1

This study

N/A

Capsella qILgg: pCgCYP724A1::CrCYP724A1

This study

N/A

Capsella qILrr: pCgCYP724A1::CrCYP724A1

This study

N/A

Capsella qILrr: pAP3::MIGS::CgCYP724A1

This study

N/A

A. thaliana: p35S::CgCYP724A1

This study

N/A

A. thaliana: p35S::CrCYP724A1

This study

N/A

A. thaliana: p35S::CgCYP724A1-SNP2ex

This study

N/A

A. thaliana: p35S::CgCYP724A1-SNP4ex

This study

N/A

A. thaliana: p35S::CgCYP724A1-SNP2and4ex

This study

N/A

N/A

N/A

pGreen II 0229

Hellens et al., 2000

N/A

pGreen II 0229 pAP3::MIGS::CgCYP724A1

This study

N/A

ML595 (a modified version of pGPTVBAR)

This study

N/A

ML595 CgCYP724A1

This study

N/A

ML595 CrCYP724A1

This study

N/A

ML595 CrSNP exchange CgCYP724A1

This study

N/A

ML595 CgSNP exchange CrCYP724A1

This study

N/A

pBSII SK(+) 35S::CgCYP

This study

N/A

Oligonucleotides See Table S1 for Oligonucleotides. Recombinant DNA

pBSII SK(+) 35S::CrCYP

This study

N/A

pBar pCgCYP724A1::CgCYP724A1

This study

N/A

pBar pCrCYP724A1::CrCYP724A1

This study

N/A

pBar pCgCYP724A1::CrCYP724A1

This study

N/A

pBar pCrCYP724A1::CgCYP724A1

This study

N/A

ImageJ v.1.8.0

NIH

https://imagej.nih.gov/ij

R

R Foundation for Statistical Computing

https://www.r-project.org

bwa mem

Li, 2013

http://bio-bwa.sourceforge.net/

Samtools

Li et al., 2009

http://www.htslib.org/

Jellyfish

Marcais and Kingsford, 2011

http://www.genome.umd.edu/ jellyfish.html

IGV

Thorvaldsdottir et al., 2013

https://software.broadinstitute. org/software/igv/

Software and Algorithms

CONTACT FOR REAGENT AND RESOURCE SHARING Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Michael Lenhard ([email protected]). EXPERIMENTAL MODEL AND SUBJECT DETAILS The geographical origins of the C. grandiflora and C. rubella accessions used in this study and generation of the RIL population have been described previously (Sicard and Lenhard, 2011; Sicard et al., 2014). Briefly, the RILs were generated by crossing C. rubella accession Cr1504 (from the Canary Islands; as male parent) to C. grandiflora accession Cg926 (from Votonosi, Greece; as female e2 Developmental Cell 44, 1–12.e1–e5, January 22, 2018

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parent). One fertile F1 plant was allowed to self. Two hundred and fifty F2 plants were grown up and propagated for an additional six generations by selfing and single seed descent. A resulting set of 142 F8-RILs was used for the initial QTL mapping (Sicard and Lenhard, 2011). The NIL segregating for the QTL alleles was generated by introgressing the Cg926 allele of the QTL on chromosome 6 into a Cr1504 background by four rounds of backcrossing, followed by selfing, selecting for recombinants and phenotyping of their progenies. This resulted in line O2_7_10, which is homozygous fixed at the flanking markers IF38 (at 4,662,695) and F03 (at 5,967,348) and thus segregates for the intervening roughly 1.3 Mb. The cyp724a1 mutant in A. thaliana used for analysis was the T-DNA insertion line SALK_115641, which was obtained from The Nottingham Arabidopsis Stock Centre. All the plants were grown under long day conditions (16 h light, 8 h dark) at 70% humidity with a light level of 150 mmol m-2 s-1. As default, the temperature cycle was 22 C during the day and 18 C during the night. For Arabidopsis transgenic plant assays, Arabidopsis thaliana (L.) Heynh, Col-0 was used for wild-type. The plants were grown under 16 h day : 8 h night conditions with fluorescent illumination (approximately 48 mmol m2 sec-1) at 22 C. METHOD DETAILS Plant Phenotyping For organ size determination, mature pletals from flowers 10 to 15 on the main inflorescence or the first set of leaves were used. Leaves were fixed in a formalin–acetic acid–alcohol (FAA) solution at 4 C for 12 h, cleared with a chloral hydrate solution for at least 4 h at room temperature, and observed under the microscope. For leaf-size measurements, leaves were attached to white paper and photographed with a digital camera. The petals were digitalized by a table-top scanner at 3600 dpi, after attaching them to a black plastic sheet. For measuring petal cell size, we made replica images of the adaxial petal epidermal cells using the dried-gel method (Horiguchi et al., 2006). To prepare a gel print of petals, pre-warmed 15ml of 2% low-melt agarose containing 0.01% bromophenol blue and 0.05% Triton-X was placed on a glass slide which was pre-warmed on a heat block at 50 C. Petals were immediately placed on it. Then, the glass slide was placed on the bench and the gel was allowed to solidify. After 5 min, petals were carefully peeled off, and the remaining gel cast was left to dry for about 10-20 min. The gel cast was observed without a cover glass under a differential phase contrast microscope. For leaf cell size measurement, more than 20 palisade cells in the subepidermal layer in the center of the leaf blade between the midvein and the leaf margin were analyzed. Organ size and cell size of petals or leaves were determined using Image J ( http://rsb.info.nih.gov/ij/ , NIH, MD, USA). Briefly, photographs of leaves or scans of petals were converted into binary images using appropriate thresholding to ensure the entire organs were segmented from the background. The size of the organs was then automatically measured using the ‘Analyze Particles’ function. To determine cell sizes, the contours of more than 20 cells per leaf or petal were redrawn manually using Photoshop, outlines converted to a binary image and the size was determined using the ‘Analyze Particles’ function in ImageJ. BR Measurements BR measurements were performed by LC-MS/MS (LC; Shimadzu Nexera, MS/MS; AB SCIEX TripleTOF 5600) using [2H] 4 CS and [2H] 4 BL as internal standards. Neutral extracts containing CS and BL were prepared by sequential extraction with hydrophobic, cation-exchange and anion-exchange cartridges essentially as previously described (Yoshimoto et al., 2009). The extract was dried, resuspended in 1 ml of chloroform and loaded onto a normal-phase extraction cartridge (SepPak Silica, Waters). CS and BL were eluted with 2 ml of chloroform:methanol = 9:1 (v/v) after washing with 1 ml of methanol. The eluate was dried and dissolved in 100 ml of 50% methanol and subjected to HPLC equipped with an ODS column (CAPCELL PAK C 18 ). Separation was carried out using a gradient of increasing acetonitrile to water with a flow rate of 1 ml/min. Initial elution was performed with 10% acetonitrile for 10 min, and the acetonitrile concentration was increased to 40% for 1 min. Next, the concentration of acetonitrile was increased to 60% for 20 min. After washes with 90% acetonitrile for 10 min, the initial concentration (10%) of acetonitrile was restored and allowed to equilibrate for 10 min. The eluate was collected at a rate of 1 tube/min. After drying the solvent, the 23rd to 30th fractions were analyzed by LC-MS/MS. Ratios were calculated by comparing the peak areas for endogenous CS and BL to their respective internal standards. Exogenous BR Treatment For exogenous BR treatment, plants were sprayed daily with a solution containing surfactant (Tween 20; 0.5%) and the indicated concentration of epi-brassinolide, starting when the inflorescence was just visible in the base of the rosette. This was continued twice a day for 10 days. Petal sizes and petal-cell sizes were measured from fully opened flowers at positions 10 to 15 on the main inflorescence as described above. Genetic Mapping QTL mapping was performed essentially as described in (Sicard et al., 2015). The PCR-based markers used for fine mapping were retrieved from the whole genome resequencing of Cr1504 and Cg926 (Sicard et al., 2015). The genetic mapping of the gene underlying QTL6 was performed using segregating precursor lines of O2_7_10 (see above). The progenies of these plants (more than 2,000 plants in total) were screened by PCR genotyping for recombination breakpoints between the markers NF42 and NF52. Recombinant individuals were selfed, and from their progenies plants homozygous for the recombinant and for the non-recombinant chromosome were selected (four to ten plants each). Their petal sizes were determined as described above and the mean phenotypes of these Developmental Cell 44, 1–12.e1–e5, January 22, 2018 e3

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sister groups were compared to determine whether the QTL was still segregating in this progeny or not. Using this strategy the QTL6 region was narrowed down to between the markers s6.4665216 and s6.4681919 (Figure S1A). A full description of all oligonucleotides used in this study and their purpose is given in Table S1, in addition to the Key Resources Table. Molecular Cloning and Plant Transformation For transgenic assay, the pCgCYP724A1::CgCYP724A1 and pCrCYP724A1::CrCYP724A1, pCgCYP724A1::CrCYP724A1 and pCrCYP724A1::CgCYP724A1 constructs were generated by amplifying 5’ upstream region and coding sequence of CYP724A1 from NILgg and NILrr seedling genomic DNA, respectively, using the primers OUF715 and OUF769 for promoter, and OUF714 and OUF700 for coding sequence. The 35S::CgCYP and 35S::CrCYP constructions used for TEAMP assay were generated by amplifying CYP724A1 CDS from NILgg and NILrr genomic DNA, respectively, and transferring the PCR products into the cloning vector pBSII SK(+) with cauliflower mosaic virus 35S promoter and terminator. For stable suspension culture cell transformation, plant transformation binary vector ML595 (a modified version of pGPTVBAR, Becker et al., 1992) with 35S::CgCYP724A1 and 35S::CrCYP724A1 were used. For SNP exchange construction, Q5 Site-Directed Mutagenesis Kit (https://www.neb.com/ products/e0554-q5-site-directed-mutagenesis-kit) from New England Biolabs (NEB) was used. All constructs were generated using standard techniques and SLiCE cloning (Zhang et al., 2012b). Oligonucleotides used are indicated in Table S1 in addition to the Key Resources Table. To generate MIGS knockdown plants, an 420 bp fragment of CYP724A1 fragment was amplified from genomic DNA of Capsella rubella by using primers OUF564 and OUF597 containing the miR173 target site sequence and fused with pAP3 fragment which was amplified from genomic DNA of A. thaliana by using primers OUF802 and OUF803, then transformed into binary vector ML959. A. thaliana and Capsella plants were transformed using ‘floral dip’ with Agrobacterium strain GV3101(pMP90) (Clough and Bent, 1998). Gene Expression and Splicing Analysis RNA isolation and qRT-PCR analysis were performed essentially as described (Fujikura et al., 2014). For RNA isolation, young inflorescences were ground in liquid nitrogen using a ball mill with two stainless-steel balls of 2.0 mm diameter (Retsch MM200 mixer mill, Retsch GmbH, Haan, Germany). Total RNA was extracted with TRIzol reagent (Invitrogen Corp, Carlsbad, CA) according to the manufacturer’s instruction. First-strand cDNA was generated from 1 mg total RNA using oligo(dT)20 primer and SuperScript III kit (Invitrogen Corp, Carlsbad, CA). To detect splicing defect, primers OUF714 and OUF700 were used to amplify full length CYP724A1 transcript. For TEAMP assay, primers OUF714 and OUF597 (1st intron) or RJ468 and RJ469 (for 3’ intron) were used to amplify CYP724A1 fragments covering the 1st intron or the 6th intron, respectively. To determine the accumulation level of different CYP724A1 transcripts by qRT-PCR using SensiMix SYBR Low-ROX kit (Bioline, London, UK) and a Roche LightCycler 480, the following oligonucleotides were used: RJ491 and RJ492 for fully spliced; OUF1071 and OUF1076 for unspliced; and RJ480 and OUF700 for total CYP724A1 transcript. Protoplast Assays and Stable Suspension Culture Cell Transformation Transient expression in A. thaliana mesophyll protoplast (TEAMP) was performed by using fresh leaves from four-week-old A. thaliana Col-0 plants, essentially as described in (Yoo et al., 2007). Young fresh leaves were chopped into stripes in enzyme solution (1% cellulase ’Onozuka’ R10 (Yakult, Tokyo, Japan), 0.25% macerozyme ’Onozuka’ R10 (Yakult), 0.4 M mannitol, 10 mM CaCl2, 20 mM KCl, 0.1% BSA and 20 mM MES, pH 5.7), then incubated at room temperature with gentle shaking (40 rpm). Isolated protoplast were washed and incubated on ice for 30 min with W5 solution (154 mM NaCl, 125 mM CaCl2, 5 mM KCl, 5 mM glucose, and 2 mM MES, pH 5.7). Protoplasts were resuspended with MMg solution (0.4 M mannitol, 15 mM MgCl2, and 4 mM MES, pH 5.7) to adjust their concentration to 2 to 5x105 cells/ml. For protoplast transformation, 20 mg of DNA were added to 0.2 ml of protoplast solution, then the same volume of PEG solution (40% (w/v) PEG (MW 4000; Fluka) with 0.1 M CaCl2 and 0.2 M mannitol) was added. After 5 min of incubation at room temperature, three volumes of W5 solution were slowly added. Protoplasts were washed with W5 solution at least twice and incubated for 16 hr in light condition. A. thaliana suspension cell cultures were kindly provided by Dr. Florian Schroeder. A. thaliana cells were cultured in modified Murashige and Skoog (MS) medium (4.33 g/L of MS salts with B5 vitamin mix, 3% sucrose, 0.5 mg/l NAA, 0.05 mg/l kinetin, adjusted pH7.5 with MES-KOH). The cells were agitated on a rotary shaker at 124 r.p.m. in the light at 23 C. To transform cells, 5 ml aliquots of 3-day-old cell cultures were co-cultivated with A. tumefaciens strain GV3101 in MS medium supplemented with 50 mg/L acetosyringone for 48 h at 124 rpm. in the light at 23 C. Then 5 ml fresh liquid MS medium containing 500 mg/ml claforan was added and cultured for 5 days. Cells were transferred onto a filter paper placed on the modified MS media (MS salts with B5 vitamins, 3% sucrose, 0.5 mg/l 2.4-D, 0.05 mg/l kinetin, 7.5 g agar/l, adjusted pH 7.5 with MES-KOH, 200 mg/ml claforan). After few days of incubation, cells were transferred to the selection MS media (MS salts with B5 vitamins, 3% sucrose, 0.5 mg/l 2.4-D, 0.05 mg/l kinetin, 7.5 g agar/l, adjusted pH7.5 with MES-KOH, 200 mg/ml claforan, 50 mg/l phosphinotricin (Sigma Aldrich, Germany)) and cultured for at least two weeks. Green callus was transferred to modified MS media and used for RNA isolation as described above. Population Genetic Analysis Public sequencing data for the C. grandiflora population were downloaded from NCBI SRA (PRJNA275635; (Josephs et al., 2015)), data for C. rubella accessions from EBI ENA (PRJEB6689; made available prior to publication by Daniel Koenig and Detlef Weigel). C. rubella sample DKCr_180_104.12 (SAMEA2784278) was excluded as it is very different from all other C. rubella. Reads were e4 Developmental Cell 44, 1–12.e1–e5, January 22, 2018

Please cite this article in press as: Fujikura et al., Variation in Splicing Efficiency Underlies Morphological Evolution in Capsella, Developmental Cell (2017), https://doi.org/10.1016/j.devcel.2017.11.022

mapped to the C. rubella reference genome (Slotte et al., 2013) using bwa mem (Li, 2013). Reads mapping to the region of interest were extracted using samtools (Li et al., 2009). Local variant calling was done using samtools. Hierarchical clustering of NIL variants was done using R (www.r-project.org) based on Euclidean distances, C. rubella-like nucleotides being encoded as 0, heterozygous ones as 0.5 and C. grandiflora-like ones as 1. Putatively recent C. rubella introgressions were identified by counting the presence of C. rubella like k-mers of different lengths using Jellyfish (Marcais and Kingsford, 2011). Plots were generated using R. Visual mapping and haplotype inspection were done using IGV (Thorvaldsdottir et al., 2013). QUANTIFICATION AND STATISTICAL ANALYSIS For statistical analysis, Student’s t-test or ANOVA followed by Tukey’s HSD post-hoc test were used to assess significant differences between the samples using the statistical software R (https://www.r-project.org). No randomization was performed. DATA AND SOFTWARE AVAILABILITY Capsella genome re-sequencing data and the software used to analyze it is available from the sources listed in the Key Resources Table.

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