Single-gene resolution of diversity-driven community overyielding

In plant communities, diversity often increases community productivity and functioning, but the specific underlying drivers are difficult to identify. Most ecological theories attribute the positive diversity effects to complementary niches occupied by different species or genotypes. However, the type of niche complementarity often remains unclear, including how complementarity is expressed in terms of trait differences between plants. Here, we use a gene-centred approach to identify differences associated with positive diversity effects in mixtures of natural Arabidopsis thaliana genotypes. Using two orthogonal genetic mapping approaches, we found that between-plant allelic differences at the AtSUC8 locus contribute strongly to mixture overyielding. The corresponding gene encodes a proton-sucrose symporter and is expressed in root tissues. Genetic variation in AtSUC8 affected the biochemical activities of protein variants and resulted in different sensitivities of root growth to changes in substrate pH. We thus speculate that - in the particular case studied here - evolutionary divergence along an edaphic gradient resulted in the niche complementarity between genotypes that now drives overyielding in mixtures. Identifying such genes important for ecosystem functioning may ultimately allow the linking of ecological processes to evolutionary drivers, help to identify the traits underlying positive diversity effects, and facilitate the development of high-performing crop variety mixtures in agriculture.


Summary
In plant communities, diversity often increases community productivity and functioning, but the specific underlying drivers are difficult to identify. Most ecological theories attribute the positive diversity effects to complementary niches occupied by different species or genotypes. However, the type of niche complementarity often remains unclear, including how complementarity is expressed in terms of trait differences between plants. Here, we use a gene-centred approach to identify differences associated with positive diversity effects in mixtures of natural Arabidopsis thaliana genotypes. Using two orthogonal genetic mapping approaches, we found that between-plant allelic differences at the AtSUC8 locus contribute strongly to mixture overyielding. The corresponding gene encodes a proton-sucrose symporter and is expressed in root tissues. Genetic variation in AtSUC8 affected the biochemical activities of protein variants and resulted in different sensitivities of root growth to changes in substrate pH. We thus speculate that -in the particular case studied here -evolutionary divergence along an edaphic gradient resulted in the niche complementarity between genotypes that now drives overyielding in mixtures.
Identifying such genes important for ecosystem functioning may ultimately allow the linking of ecological processes to evolutionary drivers, help to identify the traits underlying positive diversity effects, and facilitate the development of highperforming crop variety mixtures in agriculture.
While plausible, it currently is less clear how the relevant niche dimensions underlying such functional complementarity can be identified, and how complementarity manifests itself in specific trait differences between plants ( Kraft et al., 2015;Crutsinger, 2016;Barry et al., 2019;Plas et al., 2020). An important reason for this knowledge gap is that, rather than quantifying niche space directly, niche complementarity is mostly indirectly implied from observed higher-level phenomena, such as increasing productivity with increasing biodiversity, with little reference to the underlying physiology (Barry et al., 2019;Plas et al., 2020). Furthermore, approaches focusing on traits as surrogates for niches (Roscher et al., 2015) struggle with the problem of co-varying explanatory variables and the difficulty to separate correlation from causation: traits often co-vary because of fundamental evolutionary trade-offs between ecological strategies (Wright et al., 2004;Díaz et al., 2015).
Finally, it also is likely that not a single but many small phenotypic trait differences together determine niche complementarity between plants ( Kraft et al., 2015;Montazeaud et al., 2020). The multivariate nature of phenotypic differences associated with niche complementarity thus makes it difficult to pinpoint specific mechanisms that underly biodiversity-productivity relationships (Cadotte, 2017;Stachowicz, 2004;Crutsinger et al., 2006;Kiaer et al., 2009;Crawford and Whitney, 2010;Reiss and Drinkwater, 2018), although there are exceptions (Bongers et al., 2020). It is reasonable to assume that the mechanisms underlying niche complementarity and overyielding are similar in both cases, although there is clearly a larger potential for niche differences among species than among genotypes of the same species.
Here, we focus on the study of complementarity among genotypes of the model plant species Arabidopsis thaliana. A major advantage of this approach is that the diversity of traits and alleles cannot only be manipulated by assembling communities from an existing pool of genotypes but also through crosses (Figure 1). Crosses allow, within the limits of linkage disequilibrium, a redistribution of genetic variation, and therefore trait variation, between genotypes. The assembly of new communities that differ in their genetic composition then allows us to establish causal links between genetic diversity and community-level properties (Wuest and Niklaus, 2018;McGale et al., 2020) (Figure 1). Several recently published papers have expanded the traditional approach that links genetic differences amongst individuals to their phenotypic variation to the genetic study of the properties of ecological communities (Wuest and Niklaus, 2018;Wuest et al., 2019;McGale et al., 2020;Turner et al., 2020;Montazeaud et al., 2022). For example, and in analogy to keystone species that exhibit disproportionately large effects on ecosystems, Barbour and colleagues describe a plant "keystone gene" whose presence determined the stability of an experimental trophic food web containing plants, aphids and their parasitoids (Barbour et al., 2022). Together, these publications demonstrate that genetic effects can cascade across layers of increasing biological complexity, sometimes in unexpected ways. Here, we employed a genetic approach to study how genetic diversity affects plant community overyielding and combined it with ecological and physiological experiments to investigate the specific type of complementarity.

Results
In order to genetically dissect the mechanisms that underly biodiversity effects on productivity, we first needed to identify genotypes that overyield when grown together in mixture, i.e., communities that produce more biomass than the average of  (Figure 1 A). We tested overyielding in communities containing one of ten pairs of Arabidopsis thaliana (L.) Heynh. genotypes. (Supplementary   Figure 1 A). We used these pairs because they are the parents of publicly available recombinant inbred lines, a formidable resource for genetic studies and mapping.
Overyielding estimates in this experiment were all not significantly different from zero. This was not unexpected, because overyielding is calculated as difference between three yield values (of the mixture, and the two monocultures); a high replication of all three communities is therefore required to compensate for the error propagation in this calculation. However, model plant communities that contained the two accessions Slavice-0 (Sav-0) and Umkirch-1 (Uk-1) overyielded consistently across three substrates and across different pot sizes. We replicated this effect in a second experiment with two different pot sizes and two plant densities ( Supplementary Figure 1 B). Across all experimental settings, mixtures of Sav-0 and Uk-1 yielded an average 5.6% more biomass (range: 0-12%) than expected based on monoculture productivities. This effect is relatively large for a pot-based withinspecies experiment. For comparison, the average overyielding in field trials with crop variety mixtures typically ranges from 2 to 4% (Kiaer et al., 2009;Borg et al., 2018;Reiss and Drinkwater, 2018;Kristoffersen et al., 2020). Estimating this deviation is difficult, because it combines three error terms (two monoculture productivity estimates and one mixture productivity estimate). B.
Positive effects on productivity can be found with increasing species or increasing genotype diversity within a community. Past work has put much effort into studying the underlying functional trait differences, but our work is concerned with firstly studying the underlying genetic differences, and then trying to infer functional trait To overcome the challenges in determining overyielding due to low power resulting from error propagation (Figure 1 A), we adopted competition diallels (Figure 2 A) (Griffing, 1956;Harper, 1977;Griffing, 1989;Bossdorf et al., 2004). In these, general and specific combining abilities (GCAs and SCAs, Figure 2 A) can be taken as proxies for additive and non-additive mixing properties of genotypes and genotype combinations. Here, we used a half-diallel containing 18 randomly selected recombinant inbred lines (RIL) derived from a cross between Sav-0 and Uk-1, and the two parental lines. These RILs had been created to allow the map-based cloning of the BREVIS RADIX (BRX) gene, at which natural variation causes strong root architectural differences between Sav-0 and Uk-1 (Mouchel et al., 2004) -differences that may be expected to drive complementarity in genotype mixtures. The 20 chosen genotypes were now grown in all pair-wise combinations. The diallel was replicated four times, at different dates (temporal blocks). We further used two different substrates (sand-rich and peat-rich soils, two blocks each). We determined the average SCA across the four blocks for each of the 210 community compositions (190 genotype mixtures plus 20 monocultures). To adjust for differences in community productivity between substrates, and to obtain a normal distribution of residuals, we scaled the estimated SCAs by division by the average community biomass on the respective substrate. SCA thus was expressed as effect relative to the mean productivity of all communities on the substrate. Next, we tested if variation in SCA among the different communities could be attributed to genetic differences at specific genomic regions. Since the published marker density for the RIL population used here was relatively low, we first constructed high-resolution genotype maps by wholegenome re-sequencing of each line (Methods, Supplementary Figure S 2 A). We then used marker-regression to compare SCAs of communities that were either monoallelic or bi-allelic at a given marker region, i.e., we tested for effects of allelic diversity. We found that specific combining ability was positively associated with genetic differences at a single quantitative trait locus (QTL) on chromosome 2. The high-density marker map allowed us to resolve this QTL to a very small genomic region, spanning approximately 178 kb (Figure 2 B). Mixtures that exhibited allelic diversity in this region exhibited a 2.8% (+/-0.8% s.e.m.) higher SCA than mixtures that contained only one of the two alleles ("mono-allelic" communities, combination at other loci) had a 0.8% higher SCA than genotype monocultures (no allelic differences at any locus). Therefore, a single QTL on chromosome 2 seems to explain a high proportion of overyielding in Sav-0-Uk-1 genotype mixtures.  (Mouchel et al., 2004;Shindo et al., 2008). In our experiment, allelic diversity at the BRX locus was not associated with community overyielding (Figure 2 B, on lower arm of chromosome 1).
Nevertheless, we speculated that the observed overyielding might have been driven by niche complementarity that resulted from adaptive divergence along this edaphic gradient. The identified QTL contained 16 protein-coding putative candidate genes (Supplementary Table S1, putative pseudogenes excluded), including the Arabidopsis thaliana SUCROSE-PROTON-SYMPORTER 8 (AtSUC8), a candidate diversity-effect gene. The gene encodes for a proton symporter that is fueled by the electrochemical gradient across the membrane. AtSUC8 is predominantly expressed in the root columella (Denyer et al., 2019;Graeff et al., 2021), and therefore in cells that are in direct contact with the soil, whose pH might affect its activity. To explore the idea that natural genetic variation at the AtSUC8 locus could drive functional complementarity among Arabidopsis genotypes, we re-analyzed previously published data on competition between Arabidopsis genotypes (Wuest et al., 2019). Single individuals of ten tester genotypes (including Sav-0 and Uk-1) each competed separately with each genotype of a panel of 98 natural accessions, in a factorial design (Figure 3 A and B). For each tester-competitor pair, we determined specific combining abilities (SCAs) as in the present study (Methods and Supplementary   Figure 4 A and B). We then tested for associations of these SCAs with betweengenotype differences at single-nucleotide polymorphisms (SNPs) within the identified QTL on chromosome 2. After adjustment for multiple testing, only one SNP was significantly associated with a positive diversity effect within the QTL (Figure 3C, test for differences between mono-allelic and bi-allelic mixture SCAs by linear contrast t 947 = 4.1; P = 5·10 -5 , Bonferroni-adjusted P = 0.007; standardized effect size = 3.2%). This SNP indeed resides in the AtSUC8 coding region. Although this is not unequivocal proof that the identified SNP is the causal genetic polymorphism (it may instead be in tight linkage disequilibrium with the causal one), our finding provides further evidence that genetic differences in or around the AtSUC8 gene contribute to community overyielding in genotype mixtures. confirmed the presence of several non-synonymous SNPs. Compared with the reference allele, the AtSUC8 coding region of Sav-0 carries three amino acid replacements (one non-conservative) , and the Uk-1 allele carries eleven amino acid polymorphisms (six non-conservative) (Figure 4 A). Among the latter, the K320T and the R472G replacements might be functionally relevant, because they also occur in the C24 accession which we had also used as tester genotype in the association study described above. C24 shares seven amino acid polymorphisms with Uk-1 and shows similar patterns of diversity effects across genotypes (Supplementary Figure   4 C). To determine whether the identified polymorphisms in Uk-1 and Sav-0 affect SUC8 function, we used sucrose uptake in a heterologous system as assay of function.
We expressed the Uk-1 and Sav-0 variants of SUC8 in Xenopus laevis oocytes and measured their sucrose uptake kinetics. Whereas SUC8 Sav-0 conferred efficient sucrose uptake as compared with mock-transformed oocytes, significantly lower import was observed with SUC8 Uk-1 (Figure 4 B). We next tested if such functional protein differences also affect root growth under different pH conditions by growing 80 RILs from the Uk-1×Sav-0 RIL population on two media with pH ~6.8 or ~4.8. For this, we grew seedlings on these media and measured their root length. As expected, root length was reduced (by ≈50%) at low pH and (by ≈60%) in genotypes carrying BRX Uk-1 (Figure 4 C). Relative root length reduction at low pH versus neutral pH did not vary among genotypes carrying different BRX alleles (Figure 4 C). However, the relative root length reduction was significantly smaller when genotypes carried the AtSUC8 Uk-1 instead of the AtSUC8 Sav-0 allele (linear model ANOVA F 1,74 = 5.8; P = 0.02; Figure 4 C). These findings indicate that Uk-1 carries alleles at multiple loci, including BRX and AtSUC8, that change root growth and allocation in response to edaphic conditions, in particular environmental proton concentration. Overall, our results thus suggest that genetic differences associated with community overyielding in genotype mixtures are related to allele-specific differences in protein and root functioning.

Discussion
Here, we used two complementary genetic strategies, QTL-and association-mapping, to identify the genetic differences between Arabidopsis genotypes that overyield when grown in mixed-genotype communities. We found that a large proportion of the overyielding of mixtures of the Arabidopsis accessions Sav-0 and Uk-1 was due to allelic diversity at a major-effect QTL on chromosome 2. Two aspects of this QTL mapping study are worth noting. First, our QTL mapping resolution was very high  , 2007;Crutsinger, 2016). In our study, we were able to associate diversity at the AtSUC8 locus with community-level overyielding. The respective gene encodes for a proton-sucrose symporter, i.e., a membrane-associated protein that utilizes a proton gradient to transport sucrose across membranes. The gene is expressed predominantly in root tissues that are in direct contact with the soil.
Genetic differences at the AtSUC8 locus affect protein function and were also associated with differences in root growth, in a substrate -pH dependent way. Soil chemistry, composition and texture and resulting effects on plant -plant interactions are major selective forces, but also important drivers of community structure (Tilman et al., 1997;McKane et al., 2002;Kahmen et al., 2006;Jiménez-Alfaro et al., 2018).
Consistent with the idea that the Uk-1 genotype exhibits traits that make it better adapted to grow on acidic soil (Gujas et al., 2012), plants carrying the AtSUC8 Uk-1 allele showed root growth that was less sensitive so substrate acidification. However, and perhaps surprisingly, genetic variation at the BRX locus itself, which had previously been shown to underlie adaptive divergence along this environmental gradient (Mouchel et al., 2004;Gujas et al., 2012), did not drive overyielding in our model communities. Future work should be able to establish possible reasons for these differences between AtSUC8 and BRX, and the specific physiological and morphological effects of the identified genetic variation at the AtSUC8 locus and their consequences for plant fitness under natural conditions. One question that remains open is how specific aspects of SUC8-mediated trait differences account for overyielding in genetically diverse communities. We think that the different responses of root growth to changes in soil acidity associated with the AtSUC8 locus promote the partitioning of the physical soil space between plants.
In other words, these effects may result in different root foraging strategies in a substrate heterogeneous in soil solution pH, resulting in more efficient use of the available biotope space (Dimitrakopoulos and Schmid, 2004;Tylianakis et al., 2008;Jousset et al., 2011). A pH gradient, possibly at a very small scale, would then represent a niche dimension along which niche partitioning promotes community productivity. Obviously, there may be different environmental settings under which other traits, related to other genetic differences, may underly niche partitioning and complementarity among plants. In each case, the trait-based approaches currently applied for the study of ecological phenomena such as overyielding might strongly profit from gene-based approaches, ultimately not only at the within-but also at the between-species level. On the other hand, our work may offer new ways to design more sustainable cropping systems, in which species or genotype diversity can improve both yield and yield stability in the face of biotic and abiotic stress (Finckh et al., 2000;Zhu et al., 2000;Brooker et al., 2015;Litrico and Violle, 2015;Kristoffersen et al., 2020;Wuest et al., 2021). Here, the gene-centered approach may complement currently used trait-centered methods to facilitate the design of highperforming mixtures.

Germplasm
The Sav-0 and Uk-1 seeds were initially obtained from the Arabidopsis Biological Resource Center at Ohio State University. The Sav-0*Uk-1 RIL population was described previously (Mouchel et al., 2004). The lines used for the association analysis are described in detail in (Wuest et al., 2019) Plants and growth conditions Seeds were sown directly on soil and germinated in trays covered with plastic lids under high humidity in a growth chamber at the University of Zurich Irchel Campus (16hrs light, 8 hrs dark; 20°C, 60% humidity). The soil substrates are described below. After approximately two weeks, the trays were moved into a greenhouse chamber, where day-time and night-time temperatures were maintained around 20-25°C and 16-20 °C, respectively. Additional light was provided if required to achieve a photoperiod of 14-16 hours. Seedlings were thinned continuously until a single healthy seedling remained per position. The pots were watered ad libitum, and in case of high herbivory pressure by larvae of the dark-winged fungus gnat the insecticide ActaraG (Syngenta Agro AG) was applied according to the manufacturer's recommendation. The date of harvesting was determined through the occurrence of 5-10 dehiscent siliques on the earliest flowering genotypes in a given block. The aboveground biomass was dried at 65°C for at least three days and then weighed. Einheitserde ED73 soil substrate (pH ~5.8, N 250 mg L -1 ; P 2 O 5 300 mg L -1 ; 75% organic matter content; Gebrüder Patzer GmbH, Sinntal-Jossa, Germany) and in 6*6*5.5 cm or 7*7*8 cm or 9*9*10 cm pot sizes, a 4:1 mixture of quartz sand:ED73 and 7*7*8 cm pots, and Arabidopsis legacy soil, i.e., soil collected from an unrelated previous experiment on which Arabidopsis had grown (originally ED73). Each monoculture or mixture composition in each soil or pot size was grown in each of seven blocks, with the exception of communities on sand-rich and legacy-soil conditions. The legacy and sandy soil conditions were included only in five of the blocks for logistical reasons. Community overyielding in genotypic mixtures containing Sav-0 and Uk-1 was confirmed by growing either i) four plants in medium sized pots (7*7*8 cm); ii) four plants in small pots (5.5*5.5*6 cm) or iii) two plants in small pots, all containing ED73 soil. For each pot/density type, 48 mixtures and 24 of each monoculture were sown, treated and processed as described above.
QTL mapping and association study: The QTL-mapping experiment was designed as a half-diallel containing all pair-wise combinations, and monocultures of, 18 RILs derived from Sav-0 and Uk-1 (Mouchel et al., 2004) and the two parents. The experiment was performed in four sequential blocks; we used a soil consisting of 3 parts ED73 and 1 part quartz sand for the first two blocks. However, because seedling establishment was rather poor on this soil, we changed soil type in blocks three and four to 1 part ED73 and 3 parts sand. Plants were grown and harvested as described above (42-51 days after sowing).
Experimental conditions for the genome-wide association experiment are described in detail elsewhere (Wuest et al., 2019). In short, the association study experimental design consisted of a full factorial competition treatment of growing ten tester The raw data of the association study are available at https://zenodo.org/record/2659735#.YCt0u2Mo8mI).
Genotyping and line re-sequencing For the 18 RIL genotypes used in the QTL-mapping competition diallel, we performed whole-genome resequencing and genotype reconstructions before the genetic analysis. DNA extractions for genome resequencing, library preparation, sequencing and genome reconstruction was performed as previously described (Wuest and Niklaus, 2018), whereby the genome reconstruction approach broadly followed the method described by Xie and colleagues (Xie et al., 2010). Raw reads of resequencing the parental accessions Sav-0 and Uk-1 were downloaded from the NCBI SRA homepage (www.ncbi.nlm.nih.gov/sra, SRX011868 and SRX145024).
To genotype a wider set of RIL lines at the AtSUC8 locus (At2g14670), a Cleaved Amplified Polymorphism (CAPS)-marker assay was developed based on a EcoRVrestriction site in the SUC8 coding sequence that is present in the Sav-allele but missing in the Uk-Allele using PCR primers 5'-GGA GAG TGT TGT TAG CCA CGT C-3'and 5'-ACG ATG TGG TAG CTG TAG ATA GAC-3'. DNA extractions for CAPS-genotyping were performed using the protocol following Edwards and colleagues (Edwards et al., 1991). For four RIL genotypes where the PCR-genotyping yielded ambiguous results, so we inferred it from flanking markers AtMSQTsnp 123: (Chr 2 pos 1798324) and AtMSQTsnp 138 (Chr 2 pos 8370574) (Kim et al., 2007).
We also tried to identify RIL-lines that exhibited heterozygosity at the AtSUC8 locus to isolate heterogeneous inbred families, but failed to find any among the 101 lines screened.
To verify polymorphisms identified in the resequencing, Sanger sequencing of the Note that because of genomic rearrangements, the gene ID for AtSUC8 (AtC24-2G29550) in the C24 accession differs from the other accessions.

Oocyte uptake assays
Oocyte assays were performed essentially as described (Fastner et al., 2017). Briefly, the SUC8 cDNAs were cloned into pOO2 (Ludewig et al., 2002). cRNA was synthesized using the mmessage mmachine kit (Lifetechnologies Plate assays and root measurements Seeds were surface-sterilized with 70% ethanol, followed by 15 minutes in a solution containing 1% bleach and 0.01% Triton-X100 and three sequential washes, then left for stratification at 4°C overnight. Square MS plates (12 cm) were prepared with 0.8% agarose (instead of agar) and containing 1% sucrose (w/v). The pH was adjusted to 4.5 or 7 using hydrochloric acid or potassium hydroxide and the medium autoclaved.
After autoclaving, the measured media pH was again determined (4.8 and 6.8). Six seeds of each of six different genotypes were sown on a plate pair (identical sowing pattern on pH 4.8 and 6.8) and grown in a climate chamber with long-day conditions (16 hours light at 20°C; 8 hours dark at 16°C) for seven days. Plates were scanned twice, once after 3 days and again after 7 days using an EPSON flatbed scanner (model 2450). The primary root length of seedlings was measured using the Fiji software (Schindelin et al., 2012).

Statistical analyses
In the screen for consistently positive pairwise interactions between genotypes, we fitted a linear model of community biomass as function of genotype composition and substrate type (i.e., substrate composition or volume), including a block term.
Overyielding of a genotype pair on a given substrate was then estimated as linear contrast between the average monoculture productivity and the mixture productivity (i.e., specifying the contrast matrix K=[-0.5, -0.5, 1], equivalent to the term 1m AB -0.5m AA -0.5m BB for the case of a monocultures and mixtures of genotypes A and B), using the glht-function of the multcomp-package (Hothorn et al., 2008).
The mapping experiment was performed on two different substrates (two replicated blocks each), and both mean and variance of community productivities differed across substrates. The blocks with more nutrient-rich substrate also had some pots with missing plants due to seedling mortality, which were removed for the analysis. In order to combine all four blocks for the estimation of specific combining abilities, we therefore first estimated mean community biomass within substrate and calculated specific combining abilities (SCA) within substrates from average total pot biomass values (BM) as BM = Z*u + SCA whereby Z is the design matrix describing genotype composition of a mixture. To make SCAs comparable across substrates, we divided SCA through the mean pot biomass produced on this substrate. The standardized SCA ij value of a genotype composition (containing genotypes G i and G j ) was then estimated by averaging across substrates. SCA outliers were removed if they differed more than two standard deviations from the population mean in their absolute value.
QTL mapping of standardized mixture SCA estimates was then performed by a marker regression approach, where we first fitted a linear model predicting SCA from allelic composition (3 levels, SS, UU, SU), followed by a contrast between allelic monocultures and mixtures (e.g., SCA SU -0.5(SCA UU + SCA SS ), again using the glht function A LOD score (-log10(p-value) of 3 was considered significant, as determined by large-scale simulations (Van Ooijen, 1999)  communities). Such a threshold is also in agreement with our previous work comparing this approach to a standard QTL mapping method and a LOD-cutoff based on re-sampling (Wuest and Niklaus, 2018).

Analysis of association-study competition experiment
The association study represents a factorial design in which each of ten different genotype (testers) was grown in combination with each of 98 different Arabidopsis genotypes, with all monocultures realized too. This design was replicated in two blocks. Pots with missing data (e.g., due to seedling mortality) were removed from the analysis. A genotype's general combining ability was estimated as described above within each block and values were then averaged across blocks.
Pot biomass depended non-linearly on average genotype GCA (Supplementary Figure   4). To determine SCAs, we therefore used a quadratic form of the mean GCA to adjust for this non-linearity. Marker regressions on these SCA values for the SNPs within the QTL interval were performed as described for the QTL mapping approach described above.

Author contributions
SEW conducted and analyzed the screen for overyielding amongst Arabidopsis accessions with support from ME, and the QTL mapping experiment, with support from BS and PAN. CSH provided the genotyped Uk-1 x Sav-0 RIL population. SEW and NP performed the association study with input from UG. SR and CSH performed the sequence analyses of the AtSUC8 gene. LS and UH conducted the oocyte uptake assays. SEW and UG raised funding. SEW together with PAN wrote the first draft of the manuscript. All authors revised and approved the final version of the manuscript.