Assembly and annotation of the complex Sedum album genome

We assembled a draft genome of S. album to serve as a foundation resource to understand the genome-wide changes associated with the transition from C3 to drought induced CAM photosynthesis. We estimated the genome size to be 611 Mb based on flow cytometry, which was significantly larger than a previously reported value for S. album (142 Mb)[30]. Karyotype analysis suggests S. album is tetraploid (2n = 4x = 68) with a deduced diploidized genome size of ~305 Mb (S1A Fig). This is consistent with the kmer based genome size estimate, which revealed a heterozygous peak (first) with the full genome at 799 Mb and monoploid (second peak) at 256 Mb (S1B Fig). Because of this complexity, we utilized a PacBio based SMRT sequencing approach to build the draft genome. We generated 4.4 million PacBio reads collectively spanning 33.7 Gb or 55x genome coverage. Raw PacBio reads were error corrected and assembled using the two leading PacBio assemblers: Falcon [31] and Canu [32]. Canu was able to accurately phase the highly similar homeologous regions and produced an assembly of 627 Mb across 15,256 contigs with an N50 of 47kb, designated as the S. album V2 genome. The average nucleotide similarity of homeologous regions is 99.6% based on the Canu assembly, suggesting S. album is either autotetraploid or allotetraploid with two highly similar genomes. Falcon collapsed the homeologous regions into a single haplotype with a total assembly size of 302 Mb across 6,038 contigs and an N50 of 93kb. The Canu and Falcon based contigs were polished to remove residual errors using high-coverage Illumina data with Pilon [33].

The S. album assemblies were annotated using the MAKER-P pipeline [34]. We utilized transcripts assembled from the timecourse RNAseq data (described below), and protein datasets from other angiosperms as evidence for ab initio gene prediction. After filtering transposon derived sequences, the tetraploid and diploidized assemblies contained 93,910 and 44,487 gene models respectively. The two resulting polished assemblies were highly complete with a BUSCO score of 97%. The tetraploid assembly is highly fragmented with lower contiguity, and partial gene models may explain the greater than 2x number of genes compared to the diploid assembly. We identified homeologous genes between the diploid and tetraploid assembly and compared their relative expression. Homeologs within the tetraploid assembly have low sequence divergence and most RNAseq reads map ambiguously to both homeologs, leading to similar transcript quantification for each homeolog in the pair. Comparison of expression between homologous genes in the tetraploid and diploid assemblies revealed a strong correlation across all timepoints collected from well-watered (C3) or drought (CAM) timecourses (C3 r = 0.927, CAM r = 0.901; S2 Fig). Given the similarity in expression and for simplicity of downstream analyses, we proceeded with the diploidized assembly produced from Falcon, and this version is referred to as the S. album V3 genome.

We surveyed synteny and gene level collinearity between S. album and the closely related constitutive CAM plant Kalenchoe fedtschenkoi. Synentic regions between the two genomes were largely collinear, with conserved gene content and order (Fig 1). Roughly 71% of the S. album V3 genome had detectable synteny with K. fedtschenkoi, but this is likely an underestimation given the fragmented nature of both assemblies. Syntenic depth for each S. album region ranged from 1–5 to each region of K. fedtschenkoi, reflecting the two shared whole genome duplications events in the Crassulaceae [13] and polyploidy in S. album (S3 Fig). Collinear regions were larger in K. fedtschenkoi compared to S. album, highlighting the relatively compact nature of the S. album genome (Fig 1). To estimate the divergence time of the S. album subgenomes, we calculated Ks (synonymous substitutions per synonymous site) between homoeologous gene pairs based on synteny with K. fedtschenkoi. We identified a single peak with a median Ks of 0.026, corresponding to an estimated divergence time of ~853,000 years (S4 Fig). This supports a relatively recent polyploid origin of S. album.

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Fig 1. Comparative genomics between the S. album and K. fedtschenkoi genomes.

Microsynteny between syntenic blocks of the S. album (top) and K. fedtschenkoi (bottom) genomes. Syntenic gene pairs are shown by gray connections and genes are colored by orientation with blue and orange representing forward and reverse orientation respectively. The plotted region in Sedum spans 0.06–0.17 Mb on Contig_205 and 2.42–2.83 Mb on Scaffold55 in K. fedtschenkoi.

https://doi.org/10.1371/journal.pgen.1008209.g001

We surveyed patterns of gene family dynamics across the genomes of seven CAM, five C3 and two C4 plants to identify expanded and contracted gene families in S. album. After normalizing for ploidy, we identified 33 gene families that were uniquely contracted in S. album and 41 that are uniquely expanded compared to the other species (S1 Table). Among the contracted gene families in S. album are ABA responsive proteins, sucrose transporter 2, Aluminum activated malate transporter 1, and several flavonoid biosynthesis pathways. Among the expanded gene families in S. album are various transporters, photosynthesis related proteins, and early light induced proteins, among others (S1 Table).

Global transcriptomic co-expression

When S. album is subjected to drought conditions, it switches from robust uptake of CO₂ during the light phase to low rates of nocturnal carbon assimilation [35], which is consistent with weak CAM-cycling induction (Fig 2). We collected parallel diel timecourse data under well-watered (C3) and drought (CAM-cycling) conditions to identify genes, cis-elements and networks associated with the switch from C3 to CAM-cycling. The CAM-cycling timecourse was collected after 14 days of sustained drought when the CAM pathway was induced to conserve water usage (Fig 2A). The well-watered (C3) S. album had mild diel titratable acid and stomatal aperture changes, whereas nocturnal acid accumulation and reduced stomatal aperture were observed under drought (Fig 2B and 2C). Sedum has relatively low rates of carbon assimilation under drought conditions [36], so it is difficult to speculate on stomatal conductance based on aperture alone. However, the stomatal aperture was reduced under drought compared to well-watered samples and with no significant changes in nocturnal stomatal aperture. Together, this suggests that S. album is a drought-inducible CAM-cycling plant, and much of the nocturnal carbon assimilation is likely from recycled respiratory CO₂, as previously reported [37].

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Fig 2. Overview of drought induced CAM-cycling in Sedum album.

(A) Well-watered S. album plants performing C3 (top) and plants performing CAM-cycling after 14 days of drought (bottom). (B) Titratable acid of well-watered (C3) and drought (CAM) treated S. album across the surveyed timecourse. Three replicates were collected per timepoint. Standard error bars are shown. (C) Stomatal aperture in S. album. Stomatal width and length were measured diurnally (ZT06) and nocturnally (ZT22) in C3 and CAM-cycling conditions and divided to calculate aperture (n>10). Standard deviation bars are shown.

https://doi.org/10.1371/journal.pgen.1008209.g002

Parallel sampling of C3 (well-watered) and CAM-cycling (14-day drought) plants were collected every two hours over a 24-hour diel timecourse in triplicate for RNA sequencing and metabolite measurements. Differentially expressed genes between pairwise C3 and CAM-cycling timepoints varied from 702 to 3,245 genes, reflecting massive transcriptional reprogramming (S1 Table). GO enrichment analysis of these differential expressed genes indicated that most of the up-regulated genes under drought and CAM induction were related to abscisic acid responses, oxidative stress, and water deprivation at both day and night. Genes responding to ethylene were mainly enriched at night (S2 Table). Down-regulated differential expressed genes in the CAM samples were enriched with genes involved in cell wall metabolism, organization and biogenesis reflecting the reduced growth under drought conditions. There was also an over-representation of down-regulated genes related to photosynthesis at night (10pm-4am) in drought stressed S. album.

After filtering genes with low expression (total TPM < 5), 29,372 genes were used to construct a differential co-expression network utilizing a weighted correlation network analysis (WGCNA) approach [38]. This approach grouped genes into 32 and 25 co-expression modules for the C3 and CAM-cycling networks respectively. Preservation of modules between the C3 and CAM networks was low (Fig 3A), consistent with massive rewiring of the expression network under drought stress and CAM induction. The core CAM pathway genes (described in more detail below) were found in different modules in the CAM-cycling network, suggesting regulation of CAM and C3 pathways through distinct transcriptional programs and network rewiring.

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Fig 3. Gene co-expression and interaction networks between the well-watered (C3) and drought (CAM-cycling) S. album.

(A) A consensus matrix including the 32 modules for the C3 network and 25 modules for the CAM-cycling network is shown. The number of genes shared between any two modules is shown in the matrix and numbers highlighted in red have significant overlap (Fisher’s exact test), with the percentage of shared genes depicted by a red gradient. Gene interaction networks of C3 (B) and CAM-cycling (C) timecourses are plotted and core CAM pathway genes and their interacting partners are highlighted in yellow.

https://doi.org/10.1371/journal.pgen.1008209.g003

Photosynthesis and stress related pathways were co-regulated in the drought induced CAM-cycling co-expression network. The C3 network module 3 and CAM-cycling network module 7 were enriched in photosynthesis-related GO terms such as photosynthetic electron transport chain (GO:0022900), response to light stimulus (GO:009416), and photosynthesis light harvesting in photosystem I (GO:0009765; S3 and S4 Tables). CAM-cycling network module 7 was also enriched with GO terms related to stress response (GO:0006950) and oxidative stress (GO:0006979) compared to the orthologous module in the C3 network, which had no enrichment. GO terms related to photosystem II assembly and function were over-represented in the C3 network module 3 but not in the corresponding CAM-cycling module 7. This indicates photosystem I and electron transport chain pathways are co-regulated with stress related genes under drought but not photosystem II. This is likely due to drought induced damage on photosystem II and the tightly coordinated regulation of stress responsive and photosynthesis pathways to mitigate photooxidative and drought associated damage. This hypothesis is further supported by the enriched GO terms in CAM-cycling network module 15 and 19, which contain ATP metabolic process, ATP hydrolysis coupled protein transport, and superoxide metabolic processes (S3 and S4 Tables). These GO terms were not enriched in any well-watered, C3 network modules. Reactive oxygen species scavengers accumulate during water deficit to prevent oxidative damage [39], and scavengers such as superoxide dismutase are up-regulated in S. album under drought stress (S5 Fig). The comparison of gene co-expression networks between well-watered (C3) and drought conditions (CAM-cycling) support the tight regulation between photosynthesis and stress responses.

Drought and CAM associated diel regulation and phase changes

In pineapple, core CAM pathway genes have diel expression patterns along with enriched circadian associated cis-elements [27, 28]. Most drought related genes are circadian regulated [40] and proper diurnal expression is associated with growth and resilience under water deficit [41–43]. Therefore, we also estimated the periodicity, phase (peak time of expression) and amplitude differences of each S. album gene under either C3 or CAM-cycling using the JTK_CYCLE program [44]. There were 10,278 (35%) and 11,946 (41%) genes cycling under C3 and CAM-cycling conditions respectively (Table 1). These numbers are similar to those reported for Arabidopsis [21] and other species [24] under diel conditions of 12 light/12 hrs dark (LD) and thermocycles (HC: hot/cold). Surprisingly, only 22% (6,480) genes cycled under both conditions, and of these shared cycling genes, 39% (2,504) had a change in amplitude and 75% (4,579) had a change in phase. In addition, almost 50% of genes displayed a unique pattern of cycling in only one condition. These results corroborate the differential expression and network analysis, which is consistent with a massive time of day rewiring of the transcriptional machinery in S. album under drought and during the switch to CAM-cycling photosynthesis.

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Table 1. Summary of gene circadian rhythm changes between well-watered (C3) and drought (CAM-cycling) timecourses.

https://doi.org/10.1371/journal.pgen.1008209.t001

To understand the shifts in the S. album circadian clock during C3-CAM conversion, we looked at cycling expression patterns (S5 Table, S6 Fig). First, we found an expansion of core clock genes in S. album compared to Arabidopsis, with large changes in circadian clock associated 1/late elongated hypocotyl (CCA1/LHY, 7 vs. 2), PRRs (10 vs. 4), early flowering 3 (ELF3, 5 vs. 2) and lux arrhythmo (LUX, 7 vs. 5) and additional copies of gigantea (GI) and cryptochrome 1 (CRY1) (S6 and S7 Tables). Many of these expansions were shared with K. fedtschenkoi [13], pineapple[27], and orchid[12], suggesting gene expansion may be linked to the circadian regulation of CAM pathways (S7 Table). While none of the CAM species have a copy of the AtPRR9 ortholog, there were two PRRs only found in S. album and K. fedtschenkoi (S7 Fig). In general, the phase of the cycling of S. album circadian clock gene orthologs matched those of Arabidopsis [21, 24] but they showed a phase shift under drought stress (S6 Table, S6 Fig). While GI, CCA1/LHY and ELF3 maintained the phase of expression between C3 and CAM in S. album, the amplitude of GI and ELF3 decreased under CAM (25–50%) and CCA1/LHY amplitude increased (25%) under CAM. In contrast, most of the PRR1s, PRR5s (but not PRR7/3s) displayed a 1–4 hr phase shift (later) under CAM-cycling conditions, which is consistent with the global 1–4 hr phase shift (S5 Table). By comparing the phase and amplitude changes observed in drought treated S. album with the drought treated C3 plant Brassica rapa and two CAM systems (A. comosus and K. fedtschenkoi) (S6 Table), we were able to untangle the circadian rhythmicity change unique to drought treated S. album. Shared amplitude changes between S. album and B. rapa may represent universal drought responses and those that are unique to S. album represent lineage specific drought responses and changes related to CAM induction. We identified several core clock genes with divergent changes in phase and amplitude. For instance, CRY1 genes were cycling in both conditions of S. album but only under well-watered conditions of B. rapa (S6 Table), suggesting the circadian rhythm of CRY1 was conserved in S. album under drought stress. In addition, flavin-binding, kelch repeat, f box (FKF) displayed cycling pattern in all three CAM plants surveyed but not in the two conditions of B. rapa.

Interestingly, we observed a phase shift where genes with rhythmic expression in well-watered conditions were over-represented at phases 11–17 while genes with rhythmic expression under drought were enriched in later phases (phases 18–23) (Fig 4A). This observed phase changing is not solely caused by drought or CAM photosynthesis but an interaction of both, as drought treated B. rapa and CAM performing A. comosus have different responses (Fig 4A). Therefore, the phase shift of S. album genes under drought is possibly caused by the involvement of both circadian and drought-related cis-element, and expression shift of the circadian clock genes mentioned above. We identified a complete conservation of the time of day overrepresentation of the diel and circadian-related cis-elements, consistent with what we have found in other plant systems[21, 23, 24]. In addition, the time of day overrepresentation of both the evening specific cis-elements, evening elements and TBX, displayed a 1–4 hr phase shift between C3 and CAM-cycling, while the morning specific elements ME and Gbox did not (S8A Fig). Furthermore, there were many more significant evening-specific cis-elements under CAM that were distinct from conserved elements (S8B Fig), including 8 novel drought/CAM-specific cis-elements in S. album that are enriched in specific phases of drought but not well-watered (Fig 4B, S8 Table). These elements were mainly enriched at the later phase, which is consistent with the phase shift of drought-specific cycling genes we observed. While all eight elements were over-represented in drought-specific cycling genes (S9 Table), elements CAM-1 and CAM-7 were also enriched in cycling genes that had higher amplitude in drought condition (Fig 4C). These eight novel cis-elements support our findings that the time of day networks are completely rewired under drought induced CAM photosynthesis, and that is not just a phasing of the C3 networks but instead a new drought and CAM specific network.

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Fig 4. CAM induced phase shift and identification of novel drought cycling cis-elements.

(A) Phase-specific enrichment of cycling genes in well-watered or drought conditions in S. album and B. rapa, and cycling genes in photosynthetic and non-photosynthetic leaf tissue of A. comosus. (B) Enrichment of three novel drought/CAM-specific cis-elements in each phase under well-watered and drought timecoruses of S. album. (C) Enrichment analysis of novel elements in each gene category. A significance line (p-value of 0.05) is plotted as a dashed line.

https://doi.org/10.1371/journal.pgen.1008209.g004

In addition to the novel cis-elements, genes with CAM and drought specific cycling or higher amplitude in CAM were enriched with the stress-mediated ABRE (YACGTGGC) and ABRE-like (BACGTGKM) cis-element in their 2kb upstream promoter sequences (Table 1). CAM specific rhythmic genes were also enriched with the MYB transcription factor binding (MACCWAMC) cis-elements. In contrast, cycling genes with higher amplitude under C3 were enriched with the circadian related evening element [45] and MYC2 transcription factor binding site. To understand the biological functions of genes in each category, we performed a GO enrichment test. Genes with cycling expression in C3 only were mainly enriched with GO terms related DNA replication, translation and protein related metabolic process. Enriched GO terms in genes with CAM specific cycling were mainly related to transcription and gene expression regulation by RNA. Genes that are cycling in both conditions, but with higher amplitude in CAM were over-represented by GO terms involved in stress response including water deprivation (S10 Table).

Identification of core CAM pathway genes through comparative genomics

Genes in the core CAM pathway belong to large gene families shared across plant genomes, and most have functions unrelated to CAM activity. Independent CAM lineages show evidence of convergent amino acid substitutions in core enzymes [13], but independent recruitment of the same orthologs remains untested for most CAM genes. Through comparing diel expression patterns under C3 and CAM induction, we identified S. album genes associated with the core CAM pathway and putative vacuolar transporters involved in metabolite transport. We also compared the annotated S. album CAM genes with their pineapple and K. fedtschenkoi orthologs to identify similarities among the three sequenced CAM plants with diel expression data [13, 27, 28]. Putative CAM pathway genes in S. album had higher expression (PPC, PPCK, NADP⁺-ME, MDH, PPDK) or become oscillating (PPCK, NAD-ME) under drought induced CAM-cycling compared to C3 (Fig 5, Table 2). Core CAM pathway genes were identified in the constitutive CAM plants K. fedtschenkoi and pineapple using a similar approach [13, 27].

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Fig 5. Expression of core CAM pathway genes in the S. album C3 and CAM-cycling timecourses.

The expression in transcripts per million (TPM) is plotted for core CAM genes across the 24-hour timecourse in the C3 (blue) and CAM-cycling (red) conditions.

https://doi.org/10.1371/journal.pgen.1008209.g005

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Table 2. Circadian pattern and amplitude changes of CAM photosynthesis genes between well-watered and drought S. album.

https://doi.org/10.1371/journal.pgen.1008209.t002

Beta carbonic anhydrase (β-CA) converts CO₂ to HCO₃^- in the first step of nocturnal carboxylation in CAM photosynthesis. None of the annotated β-CA genes in S. album had high nocturnal expression under drought induced CAM-cycling compared to C3 (S6 Fig). Low β-CA expression was also observed in the drought inducible CAM plant Talinum triangulare [17] and constitutive CAM species Yucca aloifolia [46]. In contrast, β-CA from pineapple and K. fedtschenkoi had strong nocturnal expression, which may support a higher conversion rate of CO₂ to HCO₃^- (S9 Fig). Nocturnal carbon assimilation in the weak CAM plant S. album likely occurs at a much lower rate than constitutive CAM species. Thus, β-CA may not be essential to provide additional bicarbonate for phosphoenolpyruvate carboxylation in the dark period during CAM-cycling in S. album.

Phosphoenolpyruvate carboxylase (PPC) and Phosphoenolpyruvate carboxylase kinase (PPCK) are the core CAM genes that mediate the fixation of CO₂ at night. Under CAM induction, these genes had up to 73x fold higher expression than C3. PPC (Sal_001109) has high expression during the day while PPCK genes (Sal_021277, Sal_045582, Sal_050851) were expressed mainly nocturnally (Fig 5). PPC transcript expression was slightly shifted compared to pineapple (Aco010025.1) and K. fedtschenkoi (Kaladp0095s0055.1), while PPCK expression pattern was more conserved across the three CAM species (Fig 6A). Although there are multiple copies of PPC in each plant genome, S. album and K. fedtschenkoi recruited the same PPC ortholog for CAM (Fig 6B). Given the unique monocot and eudicot specific duplications of PPC, it is not possible to assess if the same PPC was recruited in monocot and eudicot CAM plants. Based on the conserved diurnal expression of PPC, we surveyed cis-element enrichment across CAM, C4, and C3 orthologs to identify cis-elements related to circadian regulation. The morning element [21] circadian clock motif was present in the PPC promoters from all three CAM plants, as well as the two C4 plants (Fig 6B). In addition, TCP and MYB transcription factor binding sites were also present in the three CAM PPC promoters.

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Fig 6. Conserved transcript expression of core CAM genes and recruitment of PPC during CAM evolution.

(A-C) Transcript expression of PPC, PPCK and MDH genes in S. album, A. comosus and K. fedtschenkoi are plotted. (D) Maximum likelihood phylogenetic tree of PPC orthologs in 10 species. The bootstrap support values are indicated on each node. The PPC copies used by CAM and C4 plants are highlighted in blue and orange, respectively. Clock associated cis-elements located in the 2kb upstream promoter of PPC are denoted in blue (morning element, ME), yellow (TCP transcription factor), and green (MYB transcription factor).

https://doi.org/10.1371/journal.pgen.1008209.g006

Based on expression dynamics between conditions, diurnal decarboxylation in S. album is likely driven by chloroplastic NADP⁺-malic enzyme (NADP⁺-ME, Sal_015733) and pyruvate orthophosphate dikinase (PPDK, Sal_044029; Fig 5). K. fedtschenkoi also utilizes the ME and PPDK pathway but pineapple primarily utilizes the phosphoenolpyruvate carboxykinase pathway (Aco010232.1) for decarboxylation [13, 27]. Nocturnally fixed CO₂ is converted to malate and stored in the vacuole to avoid cytosolic pH fluctuations and prevent feedback inhibition of PPC [10]. While the proton pumps required to establish a gradient in the vacuole are well-characterized [47], the malate transporters remain uncharacterized in CAM plants. The most likely transporters responsible for malate influx and efflux are homologs of the Arabidopsis clade II aluminum activated malate transporter (ALMT 3/4/5/6/9) and tonoplast dicarboxylate transporter respectively [28, 48, 49]. However, under CAM-cycling conditions, no S. album ALMT genes shared a conserved transcript pattern with pineapple and K. fedtschenkoi. The tonoplast dicarboxylate transporter ortholog in S. album had peak expression in the early morning in both C3 and CAM-cycling mode, but the expression drops to almost zero at dusk (ZT12) in CAM-cycling. The sudden expression decrease coincided with the titratable acid accumulation (Fig 1B). This expression pattern was similar in pineapple and K. fedtschenkoi where their expression decreases sharply (>10 fold reduction) before sunset and gradually increases before sunrise (S10 Fig). This supports a potential conserved role of tonoplast dicarboxylate transporter as a malate exporter across CAM plants.

To elucidate the potential regulators of CAM-cycling photosynthesis, gene regulatory networks were constructed and compared between the C3 and CAM timecourses and putative activators and suppressors controlling core CAM genes were identified (Table 3; Fig 3B and 3C). Core CAM pathway genes shared few interactors between C3 and CAM-cycling supporting independent networks. PPC expression in the CAM-cycling network was associated with the appearance of 12 putative activators and the disappearance of 2 suppressors. The three copies of phosphoenolpyruvate carboxylase kinase (PPCK) showed similar regulatory patterns. Interestingly, one of the PPCK copies (Sal_021277-RA) interacted with the ABA biosynthesis gene 9-cis-epoxycarotenoid dioxygenase (Sal_006713-RA), an ABA exporter (Sal_009291-RA) and an ABA receptor regulator (Sal_007192-RA) under C3 conditions and this interaction disappeared when S. album switched to CAM-cycling under drought. PPCK phosphorylates PPC at night to reduce the allosteric inhibition of PPC by malate. This phosphorylation process is under circadian control [26] and the changes of interactions of core clock genes with PPCK are evident in our gene interaction networks. Two CCA1/LHY gene copies (Sal_047094-RA and Sal_051928-RA) interacted with PPCK (Sal_021277-RA) under both conditions but two additional CCA1/LHY copies (Sal_050684-RA and Sal_051929) only interacted with PPCK under well-watered condition while CCA1/LHY_C1 (Sal_047093-RA) and PPCK only interacted in drought treated S. album. The only other CAM core gene that had putative gene interactions with core clock gene CCA1/LHY was malic enzyme (ME), where some of these interactions were only observed in the drought network (S11 Table). Malate dehydrogenase (MDH) was potentially controlled by 312 activators and 2 suppressors, including phosphoglycerate mutase (Sal_015714-RA), which is involved in glycolysis and gluconeogenesis. Four additional glycolysis and gluconeogenesis pathway genes (Sal_003892-RA, Sal_043275-RA, Sal_048516-RA, and Sal_050408-RA) were also predicted to be involved in activating ME expression in CAM photosynthesis. In addition, starch synthesis pathway genes including ADP glucose pyrophosphorylase large subunit (Sal_005475-RA and Sal_005955-RA) and starch branching enzyme (Sal_041721-RA) were potential activators for ME and pyruvate orthophosphate dikinase (PPDK) respectively. Our gene regulatory networks demonstrate a direct link between CAM photosynthesis and carbohydrate metabolism (Fig 3B, c) and the drought induction of CAM photosynthesis requires the rewiring of large number of existing genes, similar to patterns observed in pineapple [27].

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Table 3. Summary of gene interactions in the core CAM genes during C3-CAM conversion.

https://doi.org/10.1371/journal.pgen.1008209.t003

Regulation of transitory starch metabolism during the C3-CAM conversion

Nocturnal synthesis of PEP is essential for maintaining high levels of CAM activity. PEP is supplied through the degradation of transitory starch or soluble sugars [50], and mutants deficient in starch degradation have impaired CAM activity [51]. Transitory starch accumulated in S. album throughout the day and was depleted nocturnally in both C3 and CAM, but the total amount of starch synthesized was higher when S. album was operating in CAM-cycling mode (Fig 7). A large proportion of genes in the starch biosynthesis pathway (phosphoglucoseisomerase, starch branching enzymes, granular bound starch synthase and glucan water dikinase) had higher expression in CAM-cycling than C3 (S11A Fig). Starch is mainly synthesized in the stroma from glucose 6-phosphate (G6P) supplied from the Calvin Benson cycle through the conversion of F6P to G6P via glucose-6-phosphate isomerase (PGI). G6P can also be imported from the cytosol through a glucose 6-phosphate/phosphate translocator (GPT). The chloroplastic PGI is tightly regulated by multiple factors in Arabidopsis and this can limit the flux of starch synthesis [52, 53]. When the required flux of starch synthesis exceeds the limit set by PGI (such as the switch to CAM), plants may bypass the rate limiting plastidic PGI pathway by exporting carbon as triose phosphates. Carbon from cytosolic PGI can then be remobilized to the plastid as hexose phosphate using the GPT. Genes involved in this PGI bypass pathway were upregulated in CAM compared to C3 including the triose phosphate/phosphate translocator (Sal_024485-RA) (S11B Fig). Most of the transcripts for genes involved in the branch of the pentose phosphate pathway from glucose 6-phosphate to ribulose 5-phosphate (G6P shunt) in both the plastid and cytosol were down-regulated in the CAM mode (S11C Fig). Together, these data suggest that metabolism in CAM-cycling S. album is shifted to increase starch synthesis while avoiding carbon loss through the G6P shunt, which is consistent with the hypothesis previously proposed by Sharkey and Weise [54].

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Fig 7. Transitory starch associated metabolites across the C3 and CAM-cycling timecourses.

Glucose, sucrose, fructose, fructose 6-phosphate, glucose 6-phosphate, β-maltose and starch were measured on the well-watered (C3, blue) and drought (CAM, red) Sedum album every 2 hours for 24 hours. An average of 3 replicates was plotted for each timepoint and the standard error is shaded.

https://doi.org/10.1371/journal.pgen.1008209.g007

There are plastidic GPTs in plants, however they are not normally expressed in autotrophic tissue. It is hypothesized that this transporter is not expressed to prevent the pool of G6P from reaching the K_m threshold of glucose-6-phosphate dehydrogenase in the chloroplast [54, 55]. A large pool of G6P in the chloroplast could result in a futile cycle and loss of carbon as CO₂ through the G6P shunt [54]. A S. album ortholog to the Arabidopsis GPT2 gene (Sal_018693-RA) had peak daytime expression in both C3 and CAM-cycling but showed drastically increased expression (ranged from 11 to 205-fold higher) in CAM-cycling condition (Fig 8, S12 Table). A similar diurnal expression pattern was observed in the constitutive CAM plants pineapple and K. fedtschenkoi, but not the C3 plant Arabidopsis (Fig 8B). In contrast, the S. album GPT1 ortholog had constitutive expression in both C3 and CAM-cycling, and is likely not associated with CAM activity (S13 Table). Expression dynamics between CAM and C3 indicates that the starch synthesis from G6P in S. album might be regulated at multiple pathways including starch synthesis, plastidic PGI bypass, G6P shunt, as well as triose phosphate and G6P transporters as summarized in Fig 8C.

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Fig 8. Conserved expression of glucose 6-phosphate transporter 2 (GPT2) across CAM plants and regulation of starch metabolism in S. album.

(A) Maximum likelihood phylogeny of GPT1 and GPT2 among 10 species. (B) Transcript expression of GPT2 in C3 timecourses (Arabidopsis and well-watered S. album), CAM-cycling (drought induced S. album) and constitutive CAM (pineapple and K. fedtschenkoi) is plotted. (C) Schematic diagram representing the regulation of starch synthesis, cytosolic PGI bypass, cytosolic and plastidic G6P shunt in S. album under CAM-cycling photosynthesis. Abbreviations are as follows: GAP: glyceraldehyde 3-phosphate; DHAP: dihydroxyacetone phosphate; F6P: fructose 6-phosphate; G6P: glucose 6-phosphate; FBP: fructose 1,6-bisphosphate; Ru5P: ribulose 5-phosphate; TPT: triose phosphate/phosphate translocator; GPT2: glucose 6-phosphate/phosphate translocator 2.

https://doi.org/10.1371/journal.pgen.1008209.g008

At night, transitory starch is broken down into either maltose and glucose via the hydrolytic degradation pathway, or to G6P via the phosphorolytic degradation pathway [56]. It is thought that starch degradation shifts from hydrolytic to phosphorolytic pathway during the transition from C3 to CAM in ice plant [56, 57]. Chloroplasts isolated from the ice plant under C3 photosynthesis mainly export maltose during starch degradation and switch to G6P export under CAM. We measured the total G6P and maltose contents of S. album across the C3 and CAM diurnal timecourses. C3 performing S. album had a higher abundance of maltose than CAM-cycling plants at night but the G6P content was similar in both C3 and CAM-cycling plants (Fig 7). We also examined the transcript level of genes proposed to be involved in the two starch degradation pathways (hydrolytic and phosphorolytic) [56]. Homologs of Arabidopsis glucan phosphorylase (LSF2), β-amylase 6 and β-amylase 9 were expressed higher in well-watered conditions but glucan phosphorylase (SEX4), β-amylase 2, β-amylase 3, β-amylase 7 and isoamylase 3 were expressed strongly under drought (S11D Fig). Hydrolytic pathway genes were not universally upregulated in either photosynthetic condition. This indicates that either S. album does not switch its starch degradation pathways during the C3-CAM conversion, or the regulation of this shift was not controlled at the transcriptional level.

Plant materials

Sedum album plants were vegetatively propagated via cuttings in growth chambers under 12-hour photoperiod with day/night temperatures of 24°C and 20°C respectively. The light period started at 8am (ZT0) and ended at 8pm (ZT12). To induce CAM activity, plants were subjected to moderate drought by withholding water for 14 days. Well-watered (C3) control plants were watered every 2 days for the duration of the experiment. For the 24-hour diurnal timecourse experiments, leaves from 5 pots of randomly sampled plants were pooled for each replicate and three biological replicates were collected for each timepoint. The well-watered (C3) 6am (ZT22) and drought (CAM) 8am (ZT0) samples had two and one replicates respectively due to loss of samples. Samples were collected every 2 hours over the 24-hour experiment. All tissues were frozen into liquid nitrogen immediately and stored at -80C.

Carbohydrate and titratable acid assays

Carbohydrate and titratable acidity data was collected for each of the samples used in the C3 and CAM timecourse experiment. Carbohydrate and titratable acidity measurements were taken from the same tissue samples used for RNAseq experiment. Frozen leaf tissue (0.1–0.5g) was ground, weighed and transferred into 1.5mL tubes. 500uL of 3.5% perchloric acid was added to the leaf tissue and mixed by vortexing. The resulting supernatant (perchloric acid extract) was neutralized to pH 7.0 using neutralizing buffer (2M KOH, 150mM Hepes, and 10mM KCl). The samples were then frozen to precipitate salts, centrifuged, and the supernatant was transferred to a new 1.5mL tube for carbohydrate assays. Sucrose, glucose, fructose and fructose-6-phosphate, β-maltose, and glucose-6-phosphate were measured. The pellet was resuspended in 1mL of 80% ethanol and mixed by vortexing followed by two rounds of washing. The pellet was air-dried for 30 min, resuspensed in 200mM KOH and incubated at 95°C for 30 min. 1M acetic acid was used to adjust the pH to 5.0 and 5 ul of an enzyme cocktail containing 5 units α-amylase (E-ANAAM Megazyme, Bray, Wicklow, Ireland) and 6.6 units amylogucosidase (E-AMGDF Megazyme) was added to each tube and incubated at room temperature for 24 hours. The resulting supernatant containing glucose was transferred to a new tube for starch content measurement using the glucose assay.

Glucose content was measured using a 96 well plate in a Filter Max F5 plate reader (MDS Analytical Technologies, Sunnyvale CA, USA) at 340 nm with an NADP(H)-linked assay. Wells were filled with 200 μl of 150 mM Hepes buffer pH 7.2 containing 15 mM MgCl₂, 3 mM EDTA, 500 nmol NADP, 500 nmol ATP and 0.4 units glucose-6-phosphate dehydrogenase (G8529 Sigma St. Louis MO, USA). Five μl of sample was added to each well and the reaction was started by adding 0.5 units of hexokinase (H4502 Sigma). Absolute glucose content was determined using an extinction coefficient of 6220 L mol^-1 cm^-1 for NADPH at 340 nm[66]. Sucrose content was assayed as reported above with 20U of invertase (Sigma-aldrich, I4505) and 0.5U of hexokinase. Other carbohydrates (β-maltose, glucose-6-phosphate, glucose, fructose and fructose-6-phosphate) were measured as previously reported by Weise et al. [63, 67]. All enzymes used were purchased from Sigma-Aldrich and 4 unit of maltose phosphorylase was used.

To measure titratable acidity, ~0.3g of fresh ground tissue was mixed with 3mL of 80% ethanol and boiled at 80°C for 60 min. The supernatant was cooled to room temperature and titrated with 0.1N sodium hydroxide until an endpoint pH of 8.3. Titratable acid (in μ Eq per gram of fresh weight) was calculated as volume of 0.1N sodium hydroxide X 0.1 X 1000 / Fresh weight (gram).

Stomatal aperture measurements

Epidermal peels from well-watered (C3) and drought stressed (CAM) S. album leaves were prepared according to Wu et al. [68]. Microscope slides were visualized using a Nikon Eclipse Ni-Upright microscope with 40X differential interference contrast objective lens and images were captured with Nikon DS-Fi3 camera. Stomatal width and length was measured using program NIS-Elements and recorded in an Excel file. A minimum of 10 individual stoma from 5 leaves were examined for each time point (ZT06 and ZT22) and condition (C3 and CAM-cycling). A Student’s t-test was performed to test for significant changes in stomatal aperture.

DNA isolation and sequencing

High molecular weight (HMW) genomic DNA was isolated from well-watered S. album leaf tissue for PacBio and Illumina sequencing. HMW gDNA was isolated using a modified nuclei preparation [69] followed by phenol chloroform purification to remove residual contaminants. PacBio libraries size selected for 25kb fragments on the BluePippen system (Sage Science) and purified using AMPure XP beads (Beckman Coulter). The 25kb PacBio libraries were sequenced on a PacBio RSII system with P6C4 chemistry. In total, 4 million PacBio reads were sequenced, collectively spanning 33.7 Gb or 55x genome coverage. Illumina DNAseq libraries were constructed from the same batch of HMW gDNA using the KAPA HyperPrep Kit (Kapa Biosystems) followed by sequencing on an Illumina HiSeq4000 under paired end mode (150 bp). In total, 38 Gb of Illumina data was generated for error correction, representing ~62x coverage.

RNA extraction and RNAseq library construction

RNA was extracted using the Omega Biotek E.Z.N.A. Plant RNA kit according to the manufacturer’s protocol. RNA quality was examined on a 1% agarose gel and RNA concentration was quantified using the Qubit RNA HS assay kit (Invitrogen, USA). 2μg of total RNA was used to construct stranded RNAseq library using the Illumina TruSeq stranded total RNA LT sample prep kit (RS-122-2401 and RS-122-2402). Multiplexed libraries were pooled and sequenced on HiSeq4000 using paired end 150nt mode.

Genome assembly and annotation

Given the complex polyploidy of S. album, several long read assembly algorithms were tested for their ability to resolve and collapse homeologous regions. Raw PacBio reads were error corrected using Falcon (V0.2.2)[31] and Canu (V1.4) [70]. Parameters for Falcon were left as default. The following parameters for Canu were modified: minReadLength = 2000, GenomeSize = 612Mb, minOverlapLength = 1000. The Canu assembly accurately separated the homeologous regions and produced an assembly of 627 Mb across 15,256 contigs with an N50 of 47kb. The Canu assembly graph was visualized in Bandage [71] and most of the nodes (contigs) were highly interconnected. The assembly graph complexity is likely caused by a combination of polyploidy and heterozygosity. This Canu based assembly is referred as tetraploid genome version of S. album and named as Sedum V2 genome. Homeologous regions in the Falcon based assembly were highly collapsed and the total assembly size was 302 Mb with 6,038 contigs and an N50 of 93kb. This assembly is about half of the estimated genome size, and represents a diploidized version of the tetraploid S. album genome. We named this Falcon version as diploid genome version and designated as Sedum album V3 genome. We assessed the completeness of the tetraploid and diploidized assemblies using the benchmarking universal single-copy orthologs (BUSCO; v.2) [72] with the plant specific dataset (embryophyta_odb9). ~97% of the 1,440 plant specific genes were identified in both S. album assemblies, supporting they contained an accurate representation of the gene space.

Contigs from the Falcon and Canu assemblies were polished to remove residual errors with Pilon (V1.22) [33] using 62x coverage of Illumina pared-end 150 bp data. Illumina reads were quality-trimmed using Trimmomatic [73] followed by aligning to the assembly using bowtie2 (V2.3.0)[74] with default parameters. The total alignment rate of Illumina data was 92.3% for the Falcon assembly and 93.1% for Canu, suggesting both were largely complete. Pilon parameters were modified as followed and all others were left as default:—flank 7,—K 49, and—mindepth 15. Pilon was run four times to remove any residual errors.

The S. album diploid and tetraploid assemblies were annotated using the MAKER-P pipeline [34]. A custom library of long terminal repeat [75] retrotransposons was constructed for repeat masking. LTR harvest (genome tools V1.5.8) [76] and LTR Finder (v1.07) [77] were used to predict putative LTRs and this candidate list was refined using LTR retriever (v1.8.0) [78]. Parameters for LTR harvest and LTR finder were assigned based on suggestions from the LTR retriever package. This high quality library was used as input for RepeatMasker (http://www.repeatmasker.org/) [79] with implementation in the MAKER pipeline. RNAseq data from the C3 and CAM-cycling timecourses was used as transcript evidence. Representative transcripts from the RNAseq data were assembled using Trinity [80] with default parameters. Protein sequences from Arabidopsis [81] and the UniprotKB plant databases [82] were used as protein evidence. Ab initio gene prediction was done using SNAP [83] and Augustus (3.0.2) [84] with two rounds of training. Transposable element derived gene models were filtered using a library of representative transposases.

To identify homologs between the diploidized and tetraploid genome assemblies, a reciprocal blast approach was used. First, blastp was run using the tetraploid gene model sequences as query against the diploid gene models with an e-value cutoff of 0.001, maximum target sequence of 1, HSP ≥ 100, protein similarity ≥60%, and match length > 50 amino acids. A reciprocal blastp search was performed with the reversed query and database using the same parameters except without maximum target sequence option. Only gene pairs retained in both blastp results are identified as homologs between the two genome versions.

Expression profiles between the tetraploid and diploid assemblies were compared to assess if the diploid assembly contained a representative gene set for downstream analyses. Expression levels (in TPM) of the RNA-seq samples were quantified using Kallisto v0.43.0[85] with the tetraploid and diploid gene model sets. Expression values from all timepoints collected under C3 or CAM were averaged and plotted for homologous gene pairs in the diploid and tetraploid genome assemblies. Pearson correlation of all homologous gene pairs were calculated to assess the transcript expression similarity between two genomes. Based on the high expression correlation, the diploid version of the assembly and annotation was used for downstream analyses.

RNAseq expression and differential expression analysis

Paired end raw reads were trimmed using Trimmomatic v0.33 [73] to remove adapters and low quality bases. Quality trimmed reads were pseudo-aligned to the S. album gene models to quantify expression using Kallisto v0.43.0[85]. Default parameters were used for Kallisto and 100 bootstraps were run per sample. Transcript expression was quantified in transcripts per million (TPM) and an averaged TPM from the three replicates was used for gene co-expression and single gene analyses. Differential expressed genes of each timepoint between C3 and CAM samples are identified using R program sleuth. Likelihood ratio test and Wald test were used and only genes with q-value < 0.05 and b-value > |1| in both tests were categorized as differentially expressed (DE) gene.

Gene co-expression and gene interaction networks and circadian rhythm analysis

The timecourse RNAseq data was clustered into gene co-expression networks using the R package WGCNA [38]. Prior to network construction, genes were filtered based on TPM and any gene with total TPM < 5 across all samples or 25% of datapoints have zero expression was removed. In total, 29,372 genes were used to construct separate networks for the well-watered (C3) and drought (CAM-cycling) timecourses. Parameters for the C3 network were as follows: power = 7, networkType =“signed", corType = "bicor", maxPOutliers = 0.05, TOMType = "signed", deepSplit = 3, mergeCutHeight = 0.01. For the CAM-cycling network, the following parameters were used: power = 10, networkType = "signed", corType = "bicor", maxPOutliers = 0.05, TOMType = "signed", deepSplit = 3, mergeCutHeight = 0.15.

The JTK_CYCLE program [44] was used to detect rhythmic expression patterns of genes across the two timecourses. JTK_CYCLE was implemented in the R package MetaCycle (v. 1.0.0) [86]. The 29,372 genes used to construct co-expression networks were tested for rhythmicity under the C3 and CAM-cycling conditions. Genes with Bonferroni adjusted p-value < 0.05 were classified as cycling and changes in amplitude were assessed by subtracting the amplitude under C3 from that for CAM-cycling. Gene with amplitude difference less than 3 was categorized as having no changes between the two conditions. The same 29,372 genes used in WGCNA and JTK_CYCLE analysis were used for gene interaction network construction using default setting of program CMIP [87, 88]. The threshold for the C3 and CAM networks was 0.47 and 0.52, respectively. The gene interaction pairs between C3 and CAM networks were compared. Gene interacting pairs that were found in the C3 network but not in the CAM network were classified as “repressor” and gene interactions that were predicted in the CAM network but not in C3 were categorized as “activator”.

For circadian rhythmicity, JTK_CYCLE analysis across the four species (S. album, B. rapa, A. comosus and K. fedtschenkoi) was performed as stated above. The B. rapa well-watered and drought datasets, were downloaded from NCBI GEO GSE90841 and only the second 24 hours of data from the well-watered and drought conditions were used for analysis. For A. comosus, the leaf green tip and white base datasets published in [28] were used and K. fedtschenkoi leaf timecourse dataset were downloaded from the NCBI SRA database (BioSample SAMN07453940-SAMN07453987). An expression matrix table was provided by Dr. Xiaohan Yang (Oak Ridge National Laboratory, USA). These expression datasets were filtered using the same criteria as S. album as stated. For phase enrichment analysis, Bonferroni adjusted p-value of each phase (0–23) was calculated using R program and phases with an adjusted p-value ≤ 0.05 was classified as enriched.

GO enrichment analysis

Gene Ontology (GO) terms of S. album protein sequences were annotated using InterProScan 5 [89]. GO terms for genes without InterProScan annotations were inferred using corresponding GO term from the top BLAST hit to Arabidopsis orthologs. The GO terms from both methods were merged and 33,362 genes had at least one annotated GO term. GO enrichment analysis was performed using the R package TopGO [90] with Fisher’s exact test and Bonferroni adjusted p-values.

Gene family and phylogenetic analyses

OrthoFinder (v1.1.9) [91] was used to identify gene families between sequenced CAM and representative C3 and C4 species. The CAM species Sedum album, Phalaenopsis equestris, Dendrobium catenatum, Dendrobium officinale, Apostasia shenzhenica, Ananas comosus, and Kalanchoe fedtschenkoi, C3 species Brassica rapa, Oryza sativa, Solanum lycopersicum, Populus trichocarpa and Arabidopsis thaliana and C4 species Sorghum bicolor, Setaria italica were used for orthogroup identification. Protein sequences from each species were downloaded from Phytozome V12. Orthofinder was run using default parameters. Only orthologs from the CAM species pineapple and K. fedtschenkoi were included in downstream analyses as timecourse data for orchid (Phalaenopsis equestris) is currently unavailable.

To assess the phylogenetic relationships between orthologs, protein sequences of genes within the same orthogroup identified by OrthoFinder were extracted and aligned with MUSCLE (v.3.8.31)[92] and maximum likelihood phylogenetic trees were built using RAxML (v8.2.10)[93] with bootstraps of 100 and the–m PROTGAMMAJTT flag.

Orthogroups were further analyzed to identify expansions and contractions unique to S. album compared to other CAM as well as C3 and C4 species. The number of genes for each species was normalized by the total number of genes in the genome to account for differences in gene number and ploidy between species, as previously described [94]. Orthogroups were classified as contracted with a ratio of less than 0.2 in S. album compared to other species, and orthogroups with a ratio greater than 3 in S. album compared to other species were classified as expanded.

cis-element analysis

cis-element analysis was carried out as previously described [21]. The S. album promoters (500, 1000, 2000 bp) were parsed using the gene models. Gene lists were generated for each phase as called by JTK_CYCLE with a cycling significance cut-off of 0.05 and for specific conditions: CAM only cycling, C3 only cycling, C3 and CAM cycling with equal expression, C3 and CAM cycling with greater C3 expression, C3 and CAM cycling with greater CAM expression, Overrepresentation of cis-element was calculated for all of 3–8 mers using the ELEMENT program [95] with a p-value cut off of 0.05.