ABSTRACT
The evolution of complex body plans in land plants has been paralleled by gene duplication and divergence within nuclear auxin-signaling networks. A deep mechanistic understanding of auxin signaling proteins therefore may allow rational engineering of novel plant architectures. Towards that end, we analyzed natural variation in the auxin receptor F-box family of wild accessions of the reference plant Arabidopsis thaliana and used this information to populate a structure/function map. We employed a synthetic assay to identify natural hypermorphic F-box variants, and then assayed auxin-associated phenotypes in accessions expressing these variants. To more directly measure the impact of the strongest variant in our synthetic assay on auxin sensitivity, we generated transgenic plants expressing this allele. Together, our findings link evolved sequence variation to altered molecular performance and auxin sensitivity. This approach demonstrates the potential for combining synthetic biology approaches with quantitative phenotypes to harness the wealth of available sequence information and guide future engineering efforts of diverse signaling pathways.
INTRODUCTION
Auxin controls many aspects of plant development and environmental adaptation. Natural and synthetic auxins have been used to control plant growth in fields, greenhouses and laboratories for nearly a century. In recent years, the gene families of biosynthetic and metabolic enzymes, transporters and perception machinery that determine the spatial, temporal and developmental specificity of auxin signals have been identified (Enders and Strader 2015). Recent work has just begun to determine how functionally robust the auxin signaling machinery is to mutation (Yu et al. 2013, 2015; Dezfulian et al. 2016), and to measure the propensity for mutations to produce novel plant phenotypes that result in evolutionary innovation (Delker et al. 2010; Rosas et al. 2013). As auxin effects are so wide-ranging, it is not surprising to find that significant variation exists in auxin sensitivity and auxin-induced transcription across A. thaliana accessions (Delker et al. 2010), perhaps contributing to morphological diversity. As such mapping evolutionary trajectories in auxin signaling could facilitate the engineering of numerous plant traits, such as root architecture, shoot branching or leaf venation—all traits associated with crop yield (Mathan et al. 2016).
Auxin is perceived by a coreceptor complex consisting of an F-box protein (TRANSPORT INHIBITOR RESPONSE1/AUXIN SIGNALING F-BOXES, TIR1/AFB; hereafter referred to as AFBs), an auxin molecule and a member of a transcriptional coreceptor/corepressor family (AUXIN/INDOLE-3-ACETIC ACID PROTEINS, Aux/IAAs). The F-box domain of the AFB associates with a Skp/Cullin/F-box (SCF) ubiquitin ligase complex that facilitates ubiquitination of the Aux/IAA proteins, targeting them for degradation (Lavy and Estelle 2016). In low auxin conditions, Aux/IAA proteins interact with and repress a family of transcription factors, the Auxin Response Factors (ARFs) (Guilfoyle and Hagen 2007). Auxin response genes are turned on when local auxin accumulation triggers degradation of Aux/IAAs thereby relieving the repression on ARFs.
A. thaliana has six AFB genes, TIR1 and AFB1-AFB5 (Dharmasiri et al. 2005a). The N-terminal F-box domain is modular and functionally conserved in TIR1 and AFB2, both of which form functional E3 ubiquitin ligase complexes with components in yeast and animals (Nishimura et al. 2009; Zhang et al. 2015). The C-terminal domain of the AFBs is a leucine-rich repeat (LRR). LRR domains offer a highly evolvable scaffold for binding small molecules and proteins and perform diverse functions across all domains of life (Bella et al. 2008). The AFB LRR domain allows auxin sensing by interacting with both auxin and the Aux/IAA transcriptional repressor/co-receptor proteins (Dharmasiri et al. 2005a; Tan et al. 2007; Calderón Villalobos et al. 2012). The identity of the subunits and their affinity for one another governs the rate of Aux/IAA degradation which, in turn, governs transcriptional dynamics, cell fate and morphological change (Dreher et al. 2006; Pierre-Jerome et al. 2014; Guseman et al. 2015; Galli et al. 2015).
Here, we paired an examination of the natural coding sequence variation in the AFB family with quantification of functional variation. We used a synthetic auxin-induced degradation assay in yeast to assess the function of natural variants in isolation from the rest of the auxin response network. Variants with altered function were then evaluated in their native context by quantifying auxin-associated root growth inhibition in accessions containing these polymorphisms. Finally, we directly measured the contribution to auxin sensitivity of the most hypermorphic TIR1 allele by generating transgenic plants expressing this variant under a constitutive promoter. Through this work, we have generated a higher resolution structure/function map of the AFB family and highlighted the challenge of identifying functional divergence in highly buffered signaling pathway components using intact plants.
MATERIALS AND METHODS
Materials, media composition and general growth conditions
PCRs were performed with Phusion (cloning reactions; NEB, Ipswich, MA), GoTaq (diagnostics; Promega, Madison, WI) or GemTaq (genotyping; MGQuest, Lynnwood, WA) with primers from IDT (Coralville, Iowa). Media were standard formulations as described in (Pierre-Jerome et al. 2017). Plants were grown on 0.5x LS media (Caisson Laboratories, Smithfield, UT) containing 0.5% sucrose and 0.7% phytoagar (plantmedia, Dublin, OH). Seeds were obtained from the Arabidopsis Biological Resource Center (Columbus, OH).
Analysis of sequence variation
A reference dataset of the genome locations of the TIR1/AFB family and COI1 was assembled from the TAIR10 database on 28 July 2015. Transcript and coding sequences were identified using the ENSEMBL biomart version of TAIR10. The 1001 genomes Salk dataset (28 June 2010) was obtained from http://1001genomes.org/. Single nucleotide polymorphisms (SNPs) and one base pair deletions with a quality (PHRED) score of 25 and above (i.e. “quality_variant_filtered” files) were used for the following analysis using a custom R scripts unless otherwise specified. SNPs located in genes of interest were isolated and mapped to their respective gene structures using the VariantAnnotation package (Obenchain et al. 2014). Coding variants were identified and assembled for each gene and each accession. Nucleotide diversity, Watterson’s theta and Tajima’s D were calculated using the PopGenome package (Pfeifer et al. 2014).
In identifying polymorphisms, TIR1/AFB genes were split into F-box and LRR domains, with the F-box defined as the N-terminus of the protein to I50 of TIR1 and the corresponding residues of the other genes according to the alignment generated by Tan et al. (Tan et al. 2007). The N-terminal extension of AFB4 and 5 were excluded.
For functional analysis, nonsynonymous polymorphisms in TIR1 and AFB2 were isolated. As domain swap experiments revealed that the F-box regions of TIR1 and AFB2 confer highly similar or identical function in yeast (S4 Fig), we focused our analysis on variants within the LRR domain. Highly represented and potentially functionally divergent nonsynonymous polymorphisms were then identified by creating a dN/dS matrix of all-by-all pairs of accessions for each gene using the kaks function within the seqinr R-package (Charif and Lobry 2007), which implements the method of Nei and Gojobori (Nei and Gojobori 1986). Incalculable and infinite values were excluded from these matrices prior to extraction of outlier pairs and associated nonsynonymous polymorphisms. This set of TIR1 and AFB2 polymorphisms was then cloned into yeast expression vectors and functionally characterized as described below. The remaining polymorphisms were subsequently cloned and characterized (Fig S6 and S7). Annotated code and supplemental data are in S11 Appendix.
Strain construction
Plasmids were designed using j5 (Hillson et al. 2012) and constructed by aquarium (www.aquarium.bio). TIR1 and AFB2 were separately inserted into pGP8G (Havens et al. 2012) downstream of a GPD promoter and followed by 3X-FLAG-6X-HIS tandem affinity purification tag, via Golden Gate cloning (Engler et al. 2009). Mutations were introduced into the parent vectors via two-fragment Gibson assembly (Gibson et al. 2009). The coding sequence of the gene of interest was confirmed by sequencing (Genewiz, South Plainfield, NJ).
Plasmids were digested with PmeI before Lithium PEG (37) transformation into W303-1A ADE2+ yeast (MATa, leu2-3,112 trp1-1 can1-100 ura3-1 his3-11,15 ybp1-1). Correct integration of transformed colonies was confirmed by diagnostic PCR across the 3’ boundary of homologous recombination, relative to the gene of interest. Similarly, pGP4GY-IAA1 and -IAA17 (Havens et al. 2012) were transformed into W814-29B yeast (MATα ade2-1 trp1-1 can1-100 ura3-1 leu2-3,112 his3-11,15). Confirmed transformants were struck to isolation on YPAD plates. AFB strains were individually mated with each Aux/IAA strain using standard methods (Pierre-Jerome et al. 2016).
Auxin-induced degradation assays in yeast
Assays were essentially as described in (Pierre-Jerome et al. 2017) using a BD special order cytometer with a 514 nm laser exciting fluorescence that is cutoff at 525 nm prior to PMT collection (Becton-Dickinson, Franklin Lakes, NJ). Events were annotated, subset to singlet yeast, and normalized to initial levels of fluorescence using the flowTime R package (http://www.github.com/wrightrc/flowTime). Full dataset is available via FlowRepository (http://tinyurl.com/j268y5e). Additional detail in S11 Appendix.
Western blot analyses
Yeast cultures that had been incubated overnight in SC media were diluted to OD600 = 0.6 and incubated until cultures reached OD600 ~ 1. Cells were harvested by centrifugation from four milliliters of culture. Cells were then lysed by vortexing for five minutes at 4°C in the presence of 100 µL of 0.5 mm diameter acid washed glass beads and 200 µL SUMEB buffer (1% SDS, 8 M urea, 10 mM MOPS pH 6.8, 10 mM EDTA, 0.01% bromophenol blue) per 1 OD unit of original culture. Lysates were then incubated at 65°C for ten minutes and cleared by centrifugation prior electrophoresis and blotting (Sambrook and Russell 2001). Mouse anti-FLAG M2 monoclonal primary antibodies (Sigma-Aldrich, St. Louis, MO) were used at a 1:1000 dilution per the manufacturer’s directions.
Root growth inhibition assays
After sterile seeds were stratified on plates oriented vertically at 4°C in the dark for 3 days (or 1 week for wild accessions), they were transferred to long day conditions at 20°C for 4 days. Ten plants each of 4 different genotypes were then transferred in two rows to plates containing either DMSO carrier or 2,4-dichlorophenoxyactic acid (2,4-D) with root tips aligned to a reference mark for each row. Plants were scanned after an additional 3 days of incubation. Plates were regularly rotated during incubation to avoid position effects. Root growth was measured using ImageJ (Rasband 1997) and an Intuos Pro drawing pad (Wacom, Portland, Oregon). Additional detail can be found in S11 Appendix. The experiment in Fig 3A-C was repeated on two different days. The experiments in Fig 3D were repeated on three different days for T2 lines and five different days to T3 lines.
Construction and analysis of transgenic plants
Genes of interest were inserted via Golden Gate cloning (Engler et al. 2009) into pGreenII (Hellens et al. 2000) with a pUBQ10 promoter (Grefen et al. 2010) and 3X-FLAG-6X-HIS tandem affinity purification tag. Plasmids were transformed into Agrobacterium tumefactions GV3101 containing pSOUP (Hellens et al. 2000) via electroporation, and transformants were selected on plates with 50 µg/mL gentamycin and 25 µg/mL kanamycin. Plants were transformed by floral dip (Zhang et al. 2006), and transformants were selected on plates with 30 µg/mL hygromycin at four days post germination after an initial light exposure for seven hours. Root growth inhibition phenotypes were quantified in T2 generation of three independent transformants as described above. Each plant was genotyped for the presence of the hygromycin resistance gene after the growth assay, using the forward primer (GATGTTGGCGACCTCGTATT) and the reverse primer (GTGCTTGACATTGGGGAGTT). Expression levels in T3 lines were measured by quantitative PCR. RNA was isolated from the tissue from young leaves of T3 plants using illustra RNAspin Mini RNA Isolation Kit (GE Healthcare, Little Chalfont, United Kingdom) and reverse transcribed using iScript cDNA synthesis kit (Bio-rad, Hercules, California). Quantitative PCR was performed using iQ SYBR Green supermix (Bio-rad, Hercules, California) and primers for TIR1 (f-CACGGAACAAGAAGACATCCAAAGG, r-TGAGGAAACTAGAGATAAGGGACTGC) or PP2A (f-AACGTGGCCAAAATGATGC, r-AACCGCTTGGTCGACTATCG) in a CFX96 Touch Real-Time PCR detection system (Bio-rad, Hercules, California).
Plasmids, strains and sequence files are available upon request or via Addgene. All code used to perform analysis and visualization is provided in S11 Appendix. All data including raw images are available upon request.
RESULTS
We identified polymorphisms across the entire AFB gene family in the 170 A. thaliana accessions of the SALK subset of the 1001 Genomes Project (Schmitz et al. 2013). The AFB gene family is highly conserved relative to other auxin signaling gene families (Delker et al. 2010). We found 1,631 total polymorphisms within coding regions and 175 segregating sites across the whole family (S1 Table and S2 Fig). AFB3 had the highest ratio of per site diversity at nonsynonymous sites relative to synonymous sites. AFB4, critical for response to the synthetic auxin picloram (Prigge et al. 2016), had the highest nonsynonymous diversity (more than 10X that of TIR1) and the only two nonsense polymorphisms identified in this dataset. In contrast, AFB1, which is largely incapable of forming a functional SCF complex (Yu et al. 2015), has similar ratio of nonsynonymous to synonymous diversity as TIR1. Many of the accessions contained nonsynonymous polymorphisms in multiple members of the AFB family (S5 Table). These additional polymorphisms occurred more frequently in TIR1/AFB1 and AFB2/AFB3 sister pairs than expected (permutation analysis, p<0.05, S11 Appendix section “Assessing covariation…”).
None of the identified accessions have nonsynonymous polymorphisms in both TIR1 and AFB2 (S5 Table), an unlikely pattern to occur by chance (permutation analysis, p<0.05, S11 Appendix section “Assessing covariation…”). This may reflect the fact that AFB2 and TIR1 are the major auxin receptors and serve partially redundant functions, a conclusion supported by genetic analysis (Dharmasiri et al. 2005a; Parry et al. 2009). The majority of the nonsynonymous polymorphisms in TIR1 and AFB2 occurred in positions of high diversity across the Col-0 AFB family, and most were located in surface residues of the LRR domain (Fig 1A). The majority of these polymorphisms spanned the exterior helices and loops of the fourth through eighth LRRs, which face the Cullin subunit (Fig 1B and 1C). This region was recently identified as being responsible for SCFTIR1 dimerization (Dezfulian et al. 2016) and is also proximal to the S-nitrosylation site (Terrile et al. 2012). A pair of polymorphisms exists on the surface spanning the final three LRRs and the C-terminal cap (Fig 1D). This region may interact with the KR motif known to strongly affect auxin-induced degradation rates (Dreher et al. 2006; Moss et al. 2015). A final pair of polymorphisms was found on the interior surface of the LRR domain horseshoe (Fig 1E).
Synthetic yeast assays reveal functional variation in TIR1 and AFB2
An auxin-induced degradation assay has been established in yeast using heterologous expression of either TIR1 or AFB2 (Havens et al. 2012). We used this synthetic assay to quantify the function of AFB natural variants in the absence of the potentially confounding effects of feedback from the auxin pathway itself or from modulation by other integrating pathways. Natural variants were engineered into the Col-0 reference sequence with co-occurring polymorphisms cloned individually and in combination. Each AFB was then constitutively co-expressed in yeast with fluorescently labeled Aux/IAA targets. Auxin-induced degradation was measured for two targets, IAA1 and IAA17, as these substrates show distinct patterns of behavior when assayed with Col-0 TIR1 and AFB2. TIR1Col induces degradation of IAA1 and IAA17 at similar rates, while AFB2Col causes IAA17 to degrade much faster than what is observed for IAA1 (Havens et al. 2012). We focused on polymorphisms in the LRR domain that were predicted to be functionally divergent (having any pairwise dN/dS value greater than one), but analysis of the few additional polymorphisms is shown in Figures S6 and S7.
Some natural variants increased function compared to the Col-0 reference, while others decreased or nearly abrogated function (referred to hereafter as hypermorphs, hypomorphs and amorphs, respectively) (Fig 2). Of the TIR1 polymorphisms, T154S was hypermorphic and E239K-S546L was strongly hypomorphic (Fig 2A). E239K alone was nearly amorphic, and adding S546L only slightly restored activity. These polymorphic TIR1 variants are expressed at similar levels to TIR1Col (S8 Fig). Among the AFB2 polymorphisms, T491R was the only clear hypermorph identified (Fig 2B). D176E was slightly hypermorphic, whereas A254V was a moderate hypomorph. In combination, these two polymorphisms were largely additive, giving a response quite similar to AFB2Col. AFB2Q169L was also a moderate hypomorph. Two AFB2 alleles, R396C and R204K, were strong hypomorphs, and T179M was amorphic in our assays. Interestingly, the two most highly represented variants, TIR1T154S (present in 5 accessions) and AFB2R204K (6 accessions), show strong functional divergence from their respective wild-type proteins.
Accessions containing a hypermorphic TIR1 allele are hypersensitive to auxin
We next assessed whether the functional variation observed in the synthetic assays was manifested as phenotypic differences in the respective accessions. As there are many polymorphisms between accessions and previous genome-wide association studies of auxin response have not identified the AFB family (Rosas et al. 2013; Meijón et al. 2014), we did not expect a strong correlation between genotype and phenotype from our analysis. To increase the sensitivity and precision of the test, we measured inhibition of primary root growth in the presence of exogenous auxin and fit a log-logistic dose response model to the data. Similar bioassays have been used extensively to identify and characterize mutants in the AFB gene family (Gray et al. 1999; Dharmasiri et al. 2005a; b; Parry et al. 2009). The effective dose of auxin required to elicit fifty percent of the maximum root growth inhibition (ED50) was the most effective parameter in our model for differentiating among genotypes. Two tir1 mutants in the Col-0 background (a point mutation tir1-1 and a T-DNA insertion tir1-10) were also included in our analysis. Both mutants had significantly higher ED50 values than Col-0, as expected (Fig 3A and C). A loss of function afb2 allele did not significantly affect the root growth response in our assays, although tir1-1 afb2-3 double mutants had a much larger ED50 than the tir1-1 single mutant.
Four out of five accessions carrying TIR1T154S were hypersensitive to auxin, following the pattern predicted by the hypermorphic behavior of that variant in yeast (Fig 3B and C). In three of these accessions, ED50 values were quite close to one another and significantly lower than the ED50 measured for Col-0 or any other accession. However, Mc-0, which contains the strong hypomorph TIR1E239K-S546L, had auxin responses that were only subtly different Col-0. Consistent with the modest phenotype of afb2-3 in our assays, auxin responses of most accessions with AFB2 polymorphisms were essentially similar to those of Col-0 (S11 Appendix, pg. 38-40).
A common TIR1 allele confers auxin hypersensitivity to Col-0
The aberrant auxin responses in yeast and the majority of accessions led us to hypothesize that TIR1T154S is a natural gain-of-function allele with the capacity to impact organ-level auxin responses. To test this, we generated transgenic Col-0 lines expressing TIR1Col or TIR1T154S under a constitutive promoter. Most transgenic lines had relatively similar expression levels, although the Col-0 allele was expressed on average at modestly higher levels than the T154S variant (Fig S9). Expression level and root growth phenotypes were not strongly correlated—the lines with the lowest expression levels showed essentially similar auxin responses as lines with higher transgene expression. In the T3 generation, silencing of the endogenous TIR1 and transgenes was observed in three lines. Two of these lines were from the family with highest transgene expression (Fig S9, TIR1-7).
Overall, plants expressing TIR1T154S had shorter roots than plants expressing TIR1Col even in the absence of auxin treatment, consistent with the expectation that the T154S polymorphism conferred increased sensitivity to endogenous auxin. In the T2 generation, auxin treatments in root inhibition assays confirmed that TIR1T154S had increased auxin sensitivity relative to TIR1Col (Fig 3D) (transgene:treatment effect F = 9.3, p = 0.0001, full statistical analysis shown in S11 Appendix). In the T3 generation, TIR1T154S expressing plants consistently had shorter roots than TIR1Col expressing plants (transgene effect F = 100.4, p < 10−16); however, the difference in sensitivity to exogenous auxin when compared with TIR1Col expressing plants was diminished. This may be because the auxin response is near saturation even in the TIR1Col expressing plants in this generation. The roots of homozygous T3 plants with either transgene were much shorter and had a significantly reduced auxin response when compared with the T2 generation (Fig 3D vs. E, note especially the difference in the y-axis).
Dimerization domain variation affects dominance relations between TIR1 alleles
One of the unexpected findings in our analysis of auxin response across genotypes was a subtle but highly reproducible difference between the two induced alleles of tir1 in the Col-0 background (Fig 3A, C). The point mutation tir1-1 showed a consistently stronger loss of auxin sensitivity than the T-DNA insertion tir1-10, raising the possibility that tir1-1 might be acting as a dominant negative or antimorph rather than as a simple loss-of function. In support of that interpretation, tir1-1 mutants are semi-dominant (Ruegger et al. 1998), and the tir1-1 allele (G147D) and several other mutations in nearby residues negatively affect SCFTIR1 dimerization and activity (Dezfulian et al. 2016).
We turned to the yeast synthetic system to further investigate this question. By transforming a single copy of each allele into haploid yeast strains of each mating type, we created all pairs of alleles via mating. We also created tir1K159*a mimic of the tir1-10 T-DNA insertion allele. As expected, tir1K159* was an amorph, behaving similarly to an empty expression cassette (S10 Fig). TIR1 dosage had little effect on auxin response in these assays, as TIR1/tir1-10 heterozygotes responded similarly to TIR1 homozygotes (Fig 4A). In contrast, expression of tir1-1 nearly completely abrogated TIR1 activity (Fig 4B), providing strong evidence that tir1-1 is a dominant negative allele. In addition to having a greatly reduced ability to induce Aux/IAA degradation, it is likely that tir1-1 is also outcompeting TIR1 for SCF complex formation and substrate binding as tir1-1 protein accumulated to much higher levels in yeast than TIR1 (Fig 4C).
DISCUSSION
The analysis of intraspecific variation in auxin sensitivity presented here critically extends previous work on the evolution of this pathway by focusing on protein level functional variation. Synthetic assays allowed for direct quantification of differences in the ability of TIR1 and AFB2 variants to facilitate ubiquitin-mediated degradation of their substrates. The creation of a structure/function map of natural variation revealed several areas of the F-box-LRR protein scaffold that can accommodate mutations, while modulating auxin sensitivity. For example, this analysis further underscored the importance of the AFB dimerization domain (Dezfulian et al. 2016) to regulate SCF activity.
The AFB family provides a test case for genome evolution after gene duplication, as there is evidence of both significant novelty and redundancy between family members (Dharmasiri et al. 2005a; Walsh et al. 2006; Parry et al. 2009; Hu et al. 2012). Analysis of intraspecific coding sequence polymorphisms in this study has identified a subset of the tolerated polymorphisms within the AFB family. This natural variation has also revealed potential differences in evolutionary rates across the gene family and redundancies within sister pairs. In the future, quantitative phenotyping and precision genetics will allow us to test related hypotheses and accurately partition the novel and redundant effects of individual AFB genes on developmental phenotypes. Accessions containing highly represented polymorphisms and having phenotypes not predicted by our synthetic functional analysis, should facilitate future examination of evolutionary robustness and plasticity in nuclear auxin signaling and downstream gene networks.
Our analysis demonstrates that functional diversification is occurring within the Arabidopsis TIR1 lineage and clarified the role of induced variants that are commonly used for auxin studies. The integrated biochemical and phenotypic analysis of natural variants refined the map of functionally relevant residues in TIR1 and AFB2. Synthetic analysis of the chemically-induced tir1-1 allele, which is in proximity to many of the natural polymorphisms found in TIR1 and AFB2, has established tir1-1 as a dominant negative allele and highlighted the potential importance of interactions among family members to the auxin response.
The auxin pathway in Arabidopsis, like many critical signaling pathways across eukaryotes, has high levels of redundancy at each node and numerous modes of feedback. Together these factors act as strong buffers masking functional changes in any one component. This effect likely explains the discrepancies between synthetic and plant phenotypes in this study. Similar factors may also contribute to the lack of TIR1/AFB genes identified in genome-wide association studies. Candidate gene approaches incorporating isolated functional assays as demonstrated here can complement genome-wide approaches by removing feedback and other compensatory effects. Future efforts that combine synthetic assays with higher throughput allelic replacement technologies in plants (Čermák et al. 2017) would substantially increase the ability to precisely compare the impact of a given variant in isolation and in a common plant context.
Extending this pipeline for structure/function and genotype/phenotype mapping to additional auxin signaling genes and developmental phenotypes will improve our understanding of how plant form is shaped by this small molecule. This information, along with the general evolvability of the LRR scaffold (Bella et al. 2008), make the AFBs potential candidates for engineering novel traits in crops (Sun et al. 2016).
SUPPORTING INFORMATION CAPTIONS
S1 Table. Sequence variation in the AFB gene family.
S2 Fig. Polymorphisms in the AFB genes of the 170 analyzed accessions. Using a sliding 5-codon window, synonymous (blue dotted) and nonsynonymous (red solid) diversity per site was calculated across each AFB gene for all 170 accessions. A vertical black dotted line separates the F-box and LRR domain of each gene and also identifies the target site of miR393. Only those genes strongly affected by miR393 are labeled. Nonsynonymous polymorphisms functionally characterized in this study are indicated.
S3 Fig. Map of TIR1 and AFB2 polymorphic accessions. The 170 resequenced accessions analyzed in this study were mapped to the latitude and longitude of their reported collection sites. Each accession is shown as a transparent grey diamond, such that locations with many accessions appear darker grey. Accessions containing functionally characterized nonsynonymous polymorphisms in TIR1 or AFB2 are highlighted in pink/purple and cyan/navy respectively, with darker tones representing hypermorphs and lighter tones representing hypomorphs. (A) Many TIR1 or AFB2 polymorphic accessions were collected across Europe. (B) A cluster of AFB2 polymorphic accessions was collected around the Great Lakes region of the United States of America.
S4 Fig. Functional divergence between TIR1 and AFB2 results from sequence divergence in the LRR domains. (A) Schematics of domain swaps between TIR1 and AFB2. Amino acid ranges for each domain are labeled. Line type legend for panel B is to the left of the schematics. (B) Auxin-induced degradation rates are encoded by AFB LRR and not F-box domains. Degradation rates of a fluorescently-labeled IAA17 substrate were measured in yeast expressing wild-type or domain-swapped variants of TIR1 and AFB2 and treated with auxin. Data from two independent experiments is shown. Mock-treated controls are shown in grey. Wild-type TIR1 and TIR1 with an AFB2 F-box domain are indicated in purple, shown as solid and dotted lines respectively. Wild-type AFB2 and AFB2 with a TIR1 F-box domain are indicated in blue, shown as solid and dotted lines respectively.
S5 Table. Accessions containing nonsynonymous variants in TIR1 or AFB2.
S6 Fig. Characterization of additional TIR1 polymorphisms. Nonsynonymous polymorphisms in the Fbox domain of TIR1 and with dN/dS value <1 were synthesized and co-expressed in yeast with fluorescently labeled IAA1 or IAA17. Degradation was assessed using flow cytometry on cultures exposed to different concentrations of the auxin, indole-3-acetic acid (IAA) for one hour. Error bars represent 95% confidence intervals around the median fluorescence calculated from three independent experiments. In many cases, intervals are small enough that they appear as a single line.
S7 Fig. Characterization of additional AFB2 polymorphisms. Nonsynonymous polymorphisms in the F-box domain of AFB2 and or with dN/dS values <1 were synthesized and co-expressed in yeast with fluorescently labeled IAA1 or IAA17. Degradation was assessed using flow cytometry on cultures exposed to different concentrations of the auxin, indole-3-acetic acid (IAA) for one hour. Error bars represent 95% confidence intervals around the median fluorescence calculated from three independent experiments. In many cases, intervals are small enough that they appear as a single line.
S8 Fig. TIR1Col accumulates to similar levels to polymorphic TIR1 variants in yeast. Three replicate lysates of IAA17 and FLAG-tagged TIR1-variant expressing yeast strains were subjected to western blotting. A nonspecific band (*) is included as a loading control.
S9 Fig. TIR1 variant expression in transgenic lines. Triplicate RNA samples were isolated from T3 plants from each independent transformant line and subjected to reverse transcription and quantitative PCR for TIR1 and PP2A as a control. Mean TIR1 expression relative to PP2A normalized to the average expression across all TIR1Col and TIR1T154S lines is shown. Error bars represent SEM.
S10 Fig. tir1-10 is an amorph in synthetic auxin-induced degradation assays. A yeast expression cassette recapitulating the tir1-10 allele (TIR1K159*) was co-expressed with YFP-IAA17 as a homozygous diploid and along with full-length TIR1Col and an empty expression cassette (null). Each yeast strain was treated with various concentrations of auxin for one hour during log-phase growth. YFP-IAA17 fluorescence was measured by flow cytometry. Mean fluorescence +/- SE calculated from four experiments are represented by points and error bars respectively. Some error bars are within the points.
S11 Appendix. Supplemental information. Complete analytical methods, detailed protocols and additional figures for each section of the main text.
ACKNOWLEDGEMENTS
We thank Doug Fowler, Adam Leaché and Eric Klavins for guidance on methods, analysis and interpretation of our findings; members of the Nemhauser, Klavins and Imaizumi Labs for helpful discussions; and Brenda Martinez for technical assistance. This work was supported by the National Institute of Health (R01-GM107084), the National Science Foundation (MCB-1411949) and the Howard Hughes Medical Institute. R.C.W. received fellowship support from the National Science Foundation (DBI-1402222).