Phenotypic Landscape Inference Reveals Multiple Evolutionary Paths to C4 Photosynthesis

Phenotypic landscape inference reveals multiple evolutionary paths to C4 photosynthesis Ben P. Williams1;∗, Iain G. Johnston2;∗, Sarah Covshoff1, Julian M. Hibberd1 1 Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom 2 Department of Mathematics, Imperial College London, London, United Kingdom ∗ These authors contributed equally to this work. Abstract potential to inform approaches being undertaken to en- gineer C4 photosynthesis to C3 crop species [7]. C photosynthesis has independently evolved from the 4 The C pathway is estimated to have first evolved be- ancestral C pathway in at least 60 plant lineages, but, 4 3 tween 32 and 25 million years ago [8] in response to mul- as with other complex traits, how it evolved is unclear. tiple ecological drivers including decreasing atmospheric Here we show that the polyphyletic appearance of C 4 CO concentration [9]. C species have since radiated photosynthesis is associated with diverse and flexible evo- 2 4 to represent the most productive crops and native veg- lutionary paths that group into four major trajectories. etation on the planet, because modifications to their We conducted a meta-analysis of 18 lineages containing leaves increase the efficiency of photosynthesis in the sub- species that use C ,C , or intermediate C -C forms 3 4 3 4 tropics and tropics [10]. In C plants, photosynthetic effi- of photosynthesis to parameterise a 16-dimensional phe- 4 ciency is improved compared with C species because sig- notypic landscape. We then developed and experimen- 3 nificant alterations to leaf anatomy, cell biology and bio- tally verified a novel Bayesian approach based on a hid- chemistry lead to higher concentrations of CO around den Markov model that predicts how the C phenotype 2 4 the primary carboxylase RuBisCO [11]. The morphology evolved. The alternative evolutionary histories under- of C leaves is typically modified into so-called Kranz lying the appearance of C photosynthesis were deter- 4 4 anatomy that consists of repeating units of vein, bun- mined by ancestral lineage and initial phenotypic alter- dle sheath (BS) and mesophyll (M) cells [11] (Appendix ations unrelated to photosynthesis. We conclude that Fig. 5). Photosynthetic metabolism becomes modified the order of C trait acquisition is flexible and driven by 4 and compartmentalised between the M and BS, with M non-photosynthetic drivers. This flexibility will have fa- cells lacking RuBisCO but instead containing high ac- cilitated the convergent evolution of this complex trait. tivities of the alternate carboxylase PEPC to generate C4 acids. The diffusion of these acids followed by their Introduction decarboxylation in BS cells around RuBisCO increases CO2 supply and therefore photosynthetic efficiency [12]. The convergent evolution of complex traits is surpris- C4 acids are decarboxylated by at least one of three en- ingly common, with examples including camera-like eyes zymes within BS cells; NADP or NAD-dependent malic of cephalopods, vertebrates and cnidarian [1], mimicry enzymes (NADP-ME or NAD-ME respectively), or phos- in invertebrates and vertebrates [2, 3] and the different phoenolpyruvate carboxykinase (PCK) [13]. Specific lin- arXiv:1409.4978v1 [q-bio.PE] 17 Sep 2014 photosynthetic machineries of plants [4]. While the poly- eages of C4 species have typically been classified into one phyletic origin of simple traits [5, 6] is underpinned by of three sub-types, based on the activity of these decar- flexibility in the underlying molecular mechanisms, the boxylases, as well as anatomical and cellular traits that extent to which this applies to complex traits is less clear. consistently correlate with each other [14]. C4 photosynthesis is both highly complex, involving al- The genetic mechanisms underlying the evolution of terations to leaf anatomy, cellular ultrastructure and cell-specific gene expression associated with the separa- photosynthetic metabolism, and also convergent, being tion of photosynthetic metabolism between M and BS found in at least 60 independent lineages of angiosperms cells involve both alterations to cis-elements and trans- [4]. As the emergence of the entire C4 phenotype cannot acting factors [15, 16, 17, 18]. Phylogenetically inde- be comprehensively explored experimentally, C4 photo- pendent lineages of C4 plant have co-opted homologous synthesis is an ideal system for the mathematical mod- mechanisms to generate cell specificity [16] as well as the elling of complex trait evolution as transitions on an altered allosteric regulation of C4 enzymes [19] indicat- underlying phenotype landscape. Furthermore, under- ing that parallel evolution underpins at least part of the standing the evolutionary events that have generated C4 convergent C4 syndrome. However, while a substantial photosynthesis on many independent occasions has the amount of work has addressed the molecular alterations 1 that generate the biochemical differences between C3 and C4 plants [18] much less is known about the order and flexibility with which phenotypic traits important for C4 photosynthesis are acquired [20]. Clues to this question exist in the form of C3-C4 intermediates, species exhibit- ing characteristics of both C3 or C4 photosynthesis, such as the activity or localisation of C4 cycle enzymes [21], the possession of one or more anatomical or cellular adap- tations associated with C4 photosynthesis [22], or com- binations of both. To address these unknown aspects of C4 evolutionary history, we combined the concept of considering evolutionary paths as stochastic processes on complex adaptive landscapes [23, 24] with the analysis of extant C3-C4 intermediate species to develop a predictive model of how the full C4 phenotype evolved. Results A meta-analysis of photosynthetic phenotypes To parameterise the phenotypic landscape underlying photosynthetic phenotypes, data was consolidated from 43 studies encompassing 18 C3, 18 C4 and 37 C3-C4 intermediate species from 22 genera. These C3-C4 species are from 18 independent lineages likely representing 18 distinct evolutionary origins of C3-C4 intermediacy [4] (Appendix Fig. 6). These studies were used to quantify 16 biochemical, anatomical and cellular characteristics Figure 1: Evolutionary paths to C4 phenotype associated with C4 photosynthesis (Fig. 1). Principal components analysis (PCA) was performed to confirm space modelled from a meta-analysis of C3-C4 phenotypes. Principal component analysis (PCA) on the phenotypic intermediacy of the C3-C4 species (Fig. data for the activity of five C4 cycle enzymes confirms the 1A). This result, the sister-group relationships of C3-C4 intermediacy of C3-C4 species between C3 and C4 phe- species with congeneric C4 clades [4, 25, 26] and the notype spaces (A). Each C4 trait was considered absent prevalence of extant C3-C4 species in genera with the in C3 species and present in C4 species, with previously most recent origins of C4 photosynthesis [8] all support studied C3-C4 intermediate species representing samples the notion that C3-C4 species represent phenotypic states from across the phenotype space (B). With a dataset of through which transitions to C4 photosynthesis could oc- 16 phenotypic traits, a 16-dimensional space was defined. cur. The combined traits of C3-C4 intermediate species therefore represent samples from across the space of phe- (C) shows a 2D representation of 50 pathways across this space. The phenotypes of multiple C3 -C4 species notypes connecting C3 to C4 photosynthesis (Fig. 1B). were used to identify pathways compatible with individ- Within our meta-analysis data, C3-C4 phenotypes were available for 33 eudicot and 4 monocot species. 16 and ual species (e. g. Alternanthera ficoides (red nodes) and 17 of these species have extant congeneric relatives per- Parthenium hysterophorus (blue nodes)), and pathways compatible with the phenotypes of multiple species (pur- forming NADP-ME or NAD-ME sub-type C4 photosyn- ple nodes). thesis respectively. No C3-C4 relatives of PCK sub-type C4 species are known [4]. Our meta-analysis therefore encompassed a variety of taxonomic lineages, as well as representing close relatives of known phenotypic variants performing C4 photosynthesis. We defined each C4 trait as either being absent (0) or present (1). For quantitative traits the Expectation- Maximization (EM) algorithm and hierarchical cluster- ing were used to impartially assign binary scores (Ap- pendix Fig. 7). This generated a 16-bit string for each of the species (Fig. 1), with a presence or absence score for each of the traits included in our meta-analysis. 2 This defined a 16-dimensional phenotype space with 216 control datasets containing intermediate nodes represent- (65,536) nodes corresponding to all possible combina- ing a stepwise evolutionary sequence of events (Fig. 2A) tions of presence (1) and absence (0) scores for each char- and an evolutionary pathway in which four traits are ac- acteristic. quired simultaneously at a time (Fig. 2B). Our approach clearly assigned equal acquisition probabilities to traits whose timing was linked in the underlying dataset, even A novel Bayesian approach for predicting when 50% of the data was occluded (Fig. 2B). These evolutionary trajectories data are consistent with this approach detecting the si- Many existing methods of inference for evolutionary tra- multaneous acquisition of traits in evolution, even though jectories rely on phylogenetic information or assumptions single-trait acquisitions are simulated. about the fitness landscape underlying

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