Underwater CAM photosynthesis elucidated by Isoetes genome

Underwater CAM photosynthesis elucidated by Isoetes genome | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Underwater CAM photosynthesis elucidated by Isoetes genome View ORCID Profile David Wickell , Li-Yaung Kuo , Hsiao-Pei Yang , Amra Dhabalia Ashok , Iker Irisarri , Armin Dadras , Sophie de Vries , View ORCID Profile Jan de Vries , Yao-Moan Huang , Zheng Li , View ORCID Profile Michael S. Barker , View ORCID Profile Nolan T. Hartwick , View ORCID Profile Todd P. Michael , View ORCID Profile Fay-Wei Li doi: https://doi.org/10.1101/2021.06.09.447806 David Wickell 1 Plant Biology Section, School of Integrative Plant Science, Cornell University , Ithaca, NY, USA 2 Boyce Thompson Institute , Ithaca, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for David Wickell Li-Yaung Kuo 3 Institute of Molecular & Cellular Biology, National Tsing Hua University , Hsinchu, Taiwan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hsiao-Pei Yang 2 Boyce Thompson Institute , Ithaca, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Amra Dhabalia Ashok 4 Institute for Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen , Goettingen, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Iker Irisarri 4 Institute for Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen , Goettingen, Germany 5 Campus Institute Data Science, University of Goettingen , Goettingen, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Armin Dadras 4 Institute for Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen , Goettingen, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sophie de Vries 4 Institute for Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen , Goettingen, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jan de Vries 4 Institute for Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen , Goettingen, Germany 5 Campus Institute Data Science, University of Goettingen , Goettingen, Germany 6 Goettingen Center for Molecular Biosciences, Department of Applied Bioinformatics, University of Goettingen , Goettingen, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jan de Vries Yao-Moan Huang 7 Taiwan Forestry Research Institute , Taipei, Taiwan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zheng Li 8 Department of Integrative Biology, University of Texas at Austin , Austin, TX, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael S. Barker 9 Department of Ecology and Evolutionary Biology, University of Arizona , Tucson, AZ, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Michael S. Barker Nolan T. Hartwick 10 The Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies , La Jolla, CA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nolan T. Hartwick Todd P. Michael 10 The Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies , La Jolla, CA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Todd P. Michael For correspondence: tmichael{at}salk.edu fl329{at}cornell.edu Fay-Wei Li 1 Plant Biology Section, School of Integrative Plant Science, Cornell University , Ithaca, NY, USA 2 Boyce Thompson Institute , Ithaca, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Fay-Wei Li For correspondence: tmichael{at}salk.edu fl329{at}cornell.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract To conserve water in arid environments, numerous plant lineages have independently evolved Crassulacean Acid Metabolism (CAM). Interestingly, Isoetes , an aquatic lycophyte, can also perform CAM as an adaptation to low CO 2 availability underwater. However, little is known about the evolution of CAM in aquatic plants and the lack of genomic data has hindered comparison between aquatic and terrestrial CAM. Here, we investigated the underwater CAM in Isoetes taiwanensis by generating a high-quality genome assembly and RNA-seq time course. Despite broad similarities between CAM in Isoetes and terrestrial angiosperms, we identified several key differences. Notably, for carboxylation of PEP, Isoetes recruited the lesser-known “bacterial-type” PEPC, along with the “plant-type” exclusively used in other terrestrial CAM and C4 plants. Furthermore, we found that circadian control of key CAM pathway genes has diverged considerably in Isoetes relative to flowering plants. This suggests the existence of more evolutionary paths to CAM than previously recognized. Isoetes , commonly known as quillworts, is the only genus in the lycophyte order Isoetales, containing roughly 250 described species 1 . It is the last remaining member of an ancient lineage with a fossil record that dates back to at least the late Devonian. As such, quillworts are believed to represent the closest living relatives of the giant, tree-like lycopsids such as Sigillaria and Lepidodendron that dominated the terrestrial landscape during the Carboniferous 2 . However, in contrast to its arborescent ancestors, modern Isoetes species are diminutive and mostly aquatic with the vast majority of species growing completely or partially submerged. Underwater, Isoetes can conduct CAM 3 , a carbon concentrating mechanism involving the separation of carbon uptake and fixation in a time of day (TOD) fashion, with carbon being sequestered as malate at night, to be fed into the Calvin cycle during the day. CAM is a common strategy to improve water-use efficiency among xeric-adapted plants, allowing them to keep their stomata closed during the day. However, its prevalence in aquatic species of Isoetes 3 , as well as several aquatic angiosperms 4 , 5 , suggests that it must have some utility unrelated to conserving water. Specifically, it is thought to be an adaptation to low aquatic CO 2 availability in the oligotrophic lakes and seasonal pools where Isoetes species are commonly found 4 , 6 . Though it has been nearly four decades since Keeley first described “CAM-like diurnal acid metabolism” in Isoetes howellii 7 , relatively little is known about the genetic mechanisms controlling CAM in Isoetes or any other aquatic plant. Previous genomic and/or transcriptomic studies that focused on terrestrial CAM have found evidence for regulatory neofunctionalization, enrichment of cis-regulatory elements, and/or reprogramming of gene regulatory networks that underlie the convergent evolution of CAM in Sedum album 8 , Ananas comosus 9 , Kalanchoe fedtschenkoi 10 , several orchids 11 – 13 , and Agavoideae species 14 , 15 . Furthermore, a remarkable case of amino acid sequence convergence in phosphoenolpyruvate carboxylase (PEPC), which catalyzes the carboxylation of phosphoenolpyruvate (PEP) to yield oxaloacetate (OAA), has also been reported among terrestrial CAM plants 10 . However, the lack of a high-quality genome assembly has made meaningful comparison of Isoetes or any other aquatic CAM plant to terrestrial CAM species impossible. The only lycophyte genomes available to date are from the genus Selaginella 16 – 18 , leaving a deep, >300-million-year gap in our knowledge of lycophyte genomics and limiting inferences of tracheophyte evolution. Selaginella is the only genus in the Selaginellales, the sister clade to Isoetales. Notably, Selaginella is known for being one of few lineages of vascular plants for which no ancient whole genome duplications (WGDs) have been detected. Conversely, there is evidence from transcriptomic data for as many as two rounds of WGD in Isoetes tegetiformans 19 . As such, a thorough characterization of the history of WGD in Isoetes is vital to future research into the effects and significance of WGD in lycophytes as a whole. With this study we sought to investigate genome evolution as well as the genetic underpinnings of CAM in Isoetes . To that end, we present a high-quality genome assembly for Isoetes taiwanensis . To our knowledge, this is not only the first such assembly for the order Isoetales, but also the first for an aquatic CAM plant. We found evidence for a single ancient WGD event that appears to be shared among multiple species of Isoetes . Additionally, while many CAM pathway genes display similar expression patterns in Isoetes and terrestrial angiosperms, notable differences in gene expression suggest that the evolution of CAM may have followed very different trajectories in these highly divergent groups. Results and Discussion Genome assembly, annotation, and organization Using Illumina short-reads, Nanopore long-reads, and Bionano optical mapping, 90.13% of the diploid (2n = 2x = 22 chromosomes) I. taiwanensis genome was assembled into 204 scaffolds (N50=17.40 Mb), with the remaining 9.87% into 909 unplaced contigs ( Table 1 ). The total assembled genome size (1.66 Gb) is congruent with what was estimated by K-mers (1.65 Gb) and flow cytometry (1.55 Gb) (Supplementary Fig. S1). A circular-mapping plastome was also assembled, from which we identified a high level of RNA-editing (Supplementary Notes, Supplementary Fig. S2). View this table: View inline View popup Table 1. Isoetes taiwanensis genome assembly statistics. A total of 39,461 high confidence genes were annotated based on ab initio prediction, protein homology, and transcript evidence. The genome and proteome BUSCO scores are 94.5% and 91.0% respectively, which are comparable to many other seed-free plant genomes (Supplementary Fig. S3) and indicative of high completeness. Orthofinder 20 analysis of 25 genomes placed 647,535 genes into 40,144 orthogroups. Subsequent analysis of key stomatal and root genes in I. taiwanensis genome supported their homology (at the molecular level) with similar structures in other vascular plants. In addition, examination of lignin biosynthesis genes in I. taiwanensis suggests that evolution of a novel pathway to S-lignin likely predates the divergence of Isoetes and Selaginella . A detailed discussion of these analyses and Orthofinder results can be found in the Supplementary Notes and Supplementary Figures S4-S20. Repetitive sequences accounted for 38% of the genome assembly with transposable elements (TEs) accounting for the majority of those at 37.08% of the assembly length. Long terminal repeat (LTR) retrotransposons were the most abundant (15.72% of total genome assembly) with the Gypsy superfamily accounting for around 68% of LTR coverage (10.7% of total genome assembly; Supplementary Table 1). When repeat density was plotted alongside gene density, the distribution of both was found to be homogeneous throughout the assembly ( Fig. 1 ). This even distribution of genes and repeats is markedly different from what has been reported in most angiosperm genomes 21 where gene density increases near the ends of individual chromosomes, but consistent with several high-quality genomes published from seed-free plants, including Physcomitrium patens 22 , Marchantia polymorpha 23 , and Anthoceros agrestis 24 . The result from I. taiwanensis thus adds to the growing evidence that the genomic organization might be quite different between seed and seed-free plants 25 . Download figure Open in new tab Fig 1: Distribution of genes and repetitive elements in I. taiwanensis . The relatively even distributions differ from angiosperm genomes, but are similar to what have been reported in other seed-free plants. Only scaffolds longer than 10 Mb are plotted. Center: an image of I. taiwanensis . Evidence for WGD in Isoetes taiwanensis Using a combination of methods including synonymous substitutions per site (Ks), phylogenetic, and synteny analyses, we identified a single ancient WGD in I. taiwanensis . This is in contrast to a previous Ks analysis using 1KP transcriptome data, which found evidence for two rounds of WGD, named ISTEα and ISTEβ, in the North American species I. tegetiformans and I. echinospora 26 . These two WGDs have median Ks values of ∼0.5 and ∼1.5 26 (Supplementary Figure S21). Our whole paranome analysis of Ks in I. taiwanensis revealed a single peak at Ks ∼ 1.8 ( Fig. 1a ), suggesting that the earlier of the two duplications (ISTEβ) in I. tegetiformans and I. echinospora is shared by I. taiwanensis while the more recent event (ISTEα) is not. Further analysis of orthologous divergence between I. taiwanensis and I. lacustris indicated that ISTEβ predates the divergence of these two species (Supplementary Figure S22). The ISTEβ event was subsequently confirmed by gene tree-species tree reconciliation using genomic data in the WhALE package 27 . WhALE returned a posterior distribution of gene retention centered on q = ∼0.12. This result compares favorably with a previously documented WGD event in Azolla filiculoides 28 (q = ∼0.08) and is in stark contrast to our negative control, Marchantia polymorpha 23 (q = ∼0) ( Fig. 2b,c ). Download figure Open in new tab Fig. 2: Evidence for WGD in I. taiwanensis . a , Ks plot showing a peak centered on 1.8 corresponding to the ISTEβ event. b , Hypothesized WGD events that were tested (colored rectangles) in our WhALE analysis are shown on a phylogeny. c , I. taiwanensis’ posterior distribution of gene retention rates falls between that of A. filiculoides and P. patens , both are known to have at least one WGD. This provides additional support for the ISTEβ event. Conversely, the gene retention rate is close to zero for M. polymorpha , consistent with its lack of WGD. While self-self syntenic analysis revealed 6,196 genes (15.7%) with a syntenic depth of 1x in 107 clusters (Supplementary Figure S23), we do not believe they resulted from WGD. Our Ks analysis restricted to syntenic gene pairs failed to recover the peak at Ks ∼1.8 and instead consisted of an initial slope toward a much lower Ks value (Supplementary Figure S24). Considering their high degree of similarity and location on separate scaffolds, it is possible that these low Ks gene pairs are the result of relatively recent segmental duplications. The absence of synteny from ISTEβ is unsurprising. The high Ks value implies that ISTEβ is quite ancient; long enough ago for extensive genomic restructuring and fractionation to have taken place. Altogether, of the two hypothesized WGDs in Isoetes , we confirmed the presence of ISTEβ while the younger ISTEα might be either specific to I. tegetiformans and I. echinospora or an artifact stemming from the quality or completeness of the transcriptomes. Similarities to terrestrial CAM plants As a lycophyte, Isoetes represents the oldest extant lineage of vascular plants to exhibit CAM photosynthesis ( Fig 3a ), and may be considered unusual among other CAM plants due to its aquatic lifestyle. Here, we demonstrated that when submerged, titratable acidity in the leaves of I. taiwanensis increased throughout the night, reaching peak acidity in the morning and decreased throughout the daylight hours ( Fig 3b ), consistent with the cycle of carbon sequestration and assimilation seen in dry-adapted CAM plants. To identify the underlying genetic elements, we generated TOD RNA-seq, sampling every 3 hours over a 27-hour period under 12 h light/12 h dark and continuous temperature (LDHH). A multidimensional scaling (MDS) plot of normalized expression data showed that the samples were generally clustered in a clockwise fashion as expected for TOD expression analysis (Supplemental Figure S25). Download figure Open in new tab Fig. 3: Key CAM pathway genes and their expression patterns in I. taiwanensis . a , The CAM pathway with important reactions and their enzymes shown in red. b , Titratable acidity in I. taiwanensis exhibited a clear diel fluctuation. Diel expression patterns for highlighted genes are shown for the day ( c-f ) and night reactions ( g-i ). Average of TPM normalized expression data for I. taiwanensis is plotted in blue with a shaded ribbon representing the standard deviation (left y-axis). Relative expression profiles for homologous, cycling genes in other CAM species are plotted for comparison (right y-axis). All times are displayed in hours after lights-on (Zeitgeber time). We found that some of the CAM pathway genes in I. taiwanensis exhibited TOD expression patterns that largely resemble those found in terrestrial CAM plants ( Fig. 3c-i ). For example, the strong dark expression of PHOSPHOENOLPYRUVATE CARBOXYLASE KINASE ( PPCK ) appears to be conserved in I. taiwanensis as well as in all three terrestrial taxa ( Fig 3i ). Likewise, we found one copy of β-CARBONIC ANHYDRASE ( β-CA ) that cycled similarly with homologs in A. comosus and K. fedtschenkoi ( Fig. 3g )—increasing during the night and peaking in early morning—although this is different from S. album in which no β-CA genes showed a high dark expression. Similar to A. comosus where two copies of MALATE DEHYDROGENASE ( MDH ) were found to cycle in green leaf tissue 9 , we found multiple copies of MDH that appear to cycle in I. taiwanensis with one copy appearing to exhibit similar peak expression to its orthologue in pineapple ( Fig. 3e ). However, neither of the other two MDH genes that cycle in I. taiwanensis exhibit similar expression to their orthologues in terrestrial CAM species (Supplementary Figure S26). During the day, decarboxylation typically occurs by one of two separate pathways ( Fig. 3a ). The first utilizes NAPD-MALIC ENZYME ( NADP-ME ) and PYRUVATE PHOSPHATE DIKINASE ( PPDK ), and appears to be favored by K. fedtschenkoi and S. album 8 , 10 . The second utilizes MDH and PHOSPHOENOLPYRUVATE CARBOXYKINASE ( PEPCK ) and is favored by A. comosus 9 . Based on its TOD expression of multiple copies of MDH and associated expression dynamics, it is possible that I. taiwanensis utilizes the MDH / PEPCK pathway. While all four genes have elevated expression levels during the day, the expression of NADP-ME is inverted compared to K. fedtschenkoi and S. album ( Fig. 3c ), and PPDK exhibits relatively weak cycling overall (R=0.637; Fig. 3d ). Additionally, PEPCK and one copy of MDH have similar TOD expression in I. taiwanensis and A. comosus ( Fig. 3f and 3e , respectively), which may indicate a shared affinity for MDH / PEPCK decarboxylation. Interestingly, the copy of PEPCK that cycles in I. taiwanensis is not orthologous to the copy that cycles in A. comosus , being placed in a different orthogroup by Orthofinder 20 . I. taiwanensis has recruited bacterial-type PEPC While TOD expression of many key CAM pathway genes was broadly similar to that seen in terrestrial CAM plants, one important difference can be found in the PEPC enzyme, which is the entry point of carboxylation in CAM and C4 photosynthesis ( Fig. 3a ). PEPC is present in all photosynthetic organisms as well as many non-photosynthetic bacteria and archaea. It is a vital component of plant metabolism, carboxylating PEP in the presence of HCO 3 - to yield OAA. In plants, the PEPC gene family consists of two clades, the “plant-type” and the “bacterial-type.” The latter was named because of its higher sequence similarity with proteobacteria PEPC than other plant-type PEPC genes 29 . All CAM and C4 plants characterized to date recruited only the plant-type PEPC 30 , with the bacterial-type often being expressed at relatively low levels and/or primarily in non-photosynthetic tissues 31 . Interestingly, in I. taiwanensis we found that both types of PEPC were cycling and that the bacterial-type was expressed at much higher levels than plant-type PEPC ( Fig. 3h ). Copies from both types had similar expression profiles in I. taiwanensis , peaking at dusk and gradually tapering off during the night. While this may seem counterintuitive as PEPC is an important component of the dark reactions, it is consistent with what has previously been found in other terrestrial CAM plants, with the overall expression profile resembling that of S. album 8 . The advantage of recruiting bacterial-type PEPC is unclear. In vivo , both bacterial- and plant-type PEPC can interact with each other to form a hetero-octameric complex that is less sensitive to inhibition by malate 32 . Although the functional and physiological implications await future studies, the unusual involvement of bacterial-type PEPC speaks to the uniqueness of Isoetes ’ underwater CAM. No evidence for convergent evolution of PEPC Plant-type PEPC was recently shown to undergo convergent amino acid substitutions in concert with the evolution of CAM 10 . An aspartic acid (D) residue appears to have been repeatedly selected across multiple origins of CAM such as in K. fedtschenkoi and P. equestris , although notably not in A. comosus 10 . This residue is situated near the active site, and based on in vitro assays, the substitution to aspartic acid significantly increased PEPC activity 10 . However, in I. taiwanensis we did not observe the same substitution in any copies of PEPC ( Fig. 4 ); instead, they have arginine (R) or lysine (H) at this position like PEPC from many non-CAM plants. This lack of sequence convergence between Isoetes and flowering plants could be the result of their substantial phylogenetic distance and highly divergent life histories. Alternatively, it is also likely that the substitution is relevant only in the context of plant-type PEPC, and as I. taiwanensis recruited the bacterial-type PEPC, the aspartic acid residue might not serve the same purpose. Download figure Open in new tab Fig. 4: A lack of PEPC sequence convergence in taiwanensis . Copies with putative convergent amino acid sequence (D at position 3 in alignment) are indicated by thickened connecting lines and green arrows. Copies of bacterial-type and plant-type PEPC shown to cycle in I. taiwanensis are marked with asterisks (*). Branch thickness indicates bootstrap support. A unique circadian regulation in Isoetes Previous analysis of the A. comosus genome found promoter regions of multiple key CAM pathway genes containing known circadian cis-regulatory elements (CREs) including Morning Element (ME: CCACAC), Evening Element (EE: AAATATCT), CCA1-binding site (CBS: AAAAATCT), G-box (CACGTG) and TCP15-binding motif (NGGNCCCAC) 9 . This suggests that expression of CAM genes in pineapple is largely under the control of a handful of known circadian clock elements. The direct involvement of circadian CREs was corroborated by a later study of the facultative CAM plant S. album where shifts in diel expression patterns were tied to a shift in TOD-specific enrichment of CREs: EE and Telobox (TBX: AAACCCT) 8 . In order to examine the role of the circadian clock and light/dark cycles in regulating I. taiwanensis CAM, we used the HAYSTACK pipeline 33 to identify all genes with TOD expression patterns. We predicted 3,241 cycling genes, which is 10% of the expressed genes. While 10% is low compared to land plants that have been tested under this condition (LDHH)— usually at 30-50% genes 8 , 33 , 34 , a recent study found a reduced number of cycling genes in another aquatic plant Wolffia australiana (duckweed/watermeal) 35 . Accordingly, decreased cycling may be a feature of aquatic plants. Core circadian clock genes such as LATE ELONGATED HYPOCOTYL ( LHY ; Fig. 5a ), PSEUDO-RESPONSE REGULATOR 7 ( PRR7 ), LUX ARRHYTHMO ( LUX ), and EARLY FLOWERING 3 ( ELF3 ) (Supplementary Figure S27), cycle with the expected TOD expression seen in their Arabidopsis orthologs 33 . However, ZEITLUPE ( ZTL ) does not appear to cycle in I. taiwanensis , in contrast to orthologues in Arabidopsis and Selaginella 36 . Furthermore, TIMING OF CAB2 1/PSEUDO-RESPONSE REGULATOR 1 ( TOC1/PRR1 ) and GIGANTEA (GI) , which are typically single-copy genes in land plants, have respectively 3 and 5 predicted genes in distinct genomic locations; similarly an increased number of homologs was found in the facultative CAM plant S. album 8 . Closer inspection confirmed all 3 TOC1/PRR1 paralogs are full length, while only 1 of the GI genes ( GIa ) is full length and 1 other ( GIb ) is a true partial/truncated (and expressed) paralog. Surprisingly, all 3 copies of TOC1/PRR1 have dawn-specific expression compared to the dusk-specific expression found in all plants tested to date 37 ( Fig. 5b ). Download figure Open in new tab Fig. 5: Expression of key circadian associated genes is shifted in I. taiwanensis . a , LATE ELONGATED HYPOCOTYL (LHY) ( CCA1 ), b , PSEUDO-RESPONSE REGULATOR 1 ( PRR1 ), and c , GIGANTEA ( GI ) orthologs in Isoetes (blue lines), Selaginella (orange line) and Arabidopsis (red line) over the day. Day (yellow box); Night (black box); Zeitgeber time (ZT) is the number of hours (hrs) after lights-on (0 hrs). In addition, GIa and GIb have antiphasic expression, with the full length GIa having dusk-specific expression, which is consistent with other plants, and GIb having dawn-specific expression ( Fig. 5c ). The duplications and divergent expression patterns of TOC1/PRR1 and GI in I. taiwanensis have important implications on circadian clock evolution. Despite the TOD expression of core circadian clock genes being highly conserved since the common ancestor of green algae and angiosperms, the mechanisms may be simpler in algae 38 and mosses 39 . This is largely due to a lack of key components of the evening-phased loop including PRR1, GI , and ZTL in P. patens and the absence of the same along with morning-phased loop genes ELF3 and ELF4 in algae 36 . While I. taiwanensis possesses all the major clock genes that are found in other vascular plants, lineage specific expansion and phase-shifted gene expression in the evening-phased loop could indicate that circadian control was less conserved during the early evolution of land plants. However, Selaginella exhibits very similar expression of various circadian modules relative to other vascular plants and likewise, possesses a single copy of both GI and PRR1 36 . It is thus possible that the unique TOD architecture in I. taiwanensis represents a more recent adaptation to its aquatic CAM lifestyle. As a comparison, S. album similarly has multiple duplicated clock genes and its transition to CAM is associated with significant shifts in both phase and amplitude of gene expression 8 . To further investigate the relationship between clock and CAM in I. taiwanensis , we next focused on characterizing the circadian CREs. Canonical circadian CREs are not enriched in Isoetes CAM cycling genes We used ELEMENT 33 to exhaustively search the promoter region of cycling genes for putative CRE motifs. Following de novo identification, putative CREs were compared to known transcription factor binding sites in Arabidopsis to determine to what degree their functions might be conserved between Isoetes and flowering plants. We identified 16 significantly enriched CREs motifs in the 500 bp 5’ promoter region of cycling genes identified by HAYSTACK, and clustered them according to TOD expression (Supplementary Table S3). Half of the motifs shared some degree of sequence similarity to known circadian CREs previously identified in Arabidopsis , including the EE as well as two ‘ACGT’-containing elements (Gbox-like) and two TBX-containing motifs 33 . In the case of TBX, both motifs were associated with peak expression at dusk (at around 12 hrs after lights on; Zeitgeber Time [ZT]) in I. taiwanensis ( Fig. 6a,b ), similar to Arabidopsis under light/dark cycles alone 33 . On the other hand, the EE appear to be associated with peak expression at different TOD. In Arabidopsis , the EE is enriched in genes with peak expression at dusk (ZT = 12), but in I. taiwanensis , this pattern is shifted, with the EE associating with genes that peak in expression around mid-day (ZT= 6) ( Fig. 6c ). Additionally, while the two ‘ACGT’-containing elements were found upstream of genes that exhibited significant cycling behavior, neither was strongly associated with peak expression at a particular TOD. We also found an unidentified CRE (AGAATAAG) strongly associated with peak expression in the morning (ZT = 4)( Fig. 6d ). Download figure Open in new tab Fig. 6: Multiple CREs exhibit time-structured enrichment in I. taiwanensis . a , b , Two telobox (TBX) containing motifs showed similar patterns to one another, both being enriched in genes with peak expression at dusk. c , A motif containing Evening Element (EE) was significantly enriched in genes with peak expression at mid-day. d , A novel motif was significantly enriched at mid-day as well. Day (yellow box); Night (black box); Zeitgeber time (ZT) is the number of hours (hrs) after lights on (0 hrs). We next examined the connection between circadian CREs and CAM genes in I. taiwanensis . Interestingly, with the exception of the RVE1/2 motif, we did not find significant enrichment of any known circadian CREs in CAM cycling genes relative to non-cycling paralogues. While a targeted search of CAM cycling gene promoters did uncover circadian CREs including the CBS, TCP15, TBX, and EE (Supplementary Table S4), none were strongly associated with either light or dark phase CAM gene expression. In addition, both ME and G-box were conspicuously absent from the promoter regions of cycling CAM photosynthetic genes. In sum, TOD-specific enrichment of CREs appears to differ significantly from Arabidopsis . While some CRE sequences themselves are conserved between lycophytes and angiosperms, their interaction with various transcription factors and subsequent regulatory function could be quite different in Isoetes . Importantly, our results stand in contrast to other CAM plants such as S. album 8 and A. comosus 9 where CAM genes appeared to be under the direct control of a handful of strictly conserved circadian CREs. These results either suggest that the circadian clock network that emerged in Isoetes , which included the addition of central components GI and PRR1 , was quite different than that found to be highly conserved in seed plants, or there is significant TOD innovation associated with the evolution of underwater CAM. Additional Isoetes genomes and TOD analysis of underwater CAM plants will be required to narrow these hypotheses. Conclusion The assembly and analyses of the I. taiwanensis genome bridges a substantial gap in our knowledge of vascular plant evolution. We have combined genomic and transcriptomic data to corroborate one of the two hypothesized WGDs in Isoetes relative to its closest extant relative Selaginella , highlighting the contrasting history of WGD in these two lineages. Importantly, comparison of TOD gene expression with genomic sequence data has given us unique insights into the convergent evolution of CAM photosynthesis, not only in a lycophyte, but also in the aquatic environment. As such, our analysis stands as a necessary counterpoint to similar studies previously conducted in terrestrial angiosperms. Shifts in expression of CAM pathway genes and the recruitment of bacterial-type PEPC in I. taiwanensis demonstrate a remarkable degree of plasticity in the convergent evolution of this complex trait throughout vascular plants. Likewise, differences in the enrichment of CREs associated with circadian gene expression suggest that control of CAM, as well as other processes tied to the circadian clock, may have diverged significantly since the common ancestor of Isoetes and flowering plants. We propose that the emergence of underwater CAM may have followed a distinct route in Isoetes , shedding new light on a classic example of convergent evolution of a complex plant trait. Methods Plant sample Isoetes taiwanensis is endemic to a small pond in Northern Taiwan and has been ex situ propagated in Taiwan Forestry Research Institute. This species is expected to have a low genetic diversity due to a very restricted distribution and a small population size. The voucher specimen was deposited at TAIF herbarium. Genome size estimate The genome size of I. taiwanensis was first determined by flow cytometry following the protocols outlined in Kuo et al. 40 and Li et al 28 . The flow cytometric experiments were performed on BD FACSCan system (BD Biosciences, USA), and the Beckman buffer 41 was used with 0.5% (v/v) 2-mercaptoethanol, 40 mg ml -1 PVP-40, and 0.1 mg ml -1 RNaseA added. We used Zea mays (1C = 5.57pg 42 ) as the internal standard. To confirm the flow cytometry-based measurement, a K-mer frequency distribution was generated from Illumina 2×150 bp paired reads (described below) using Jellyfish 43 , which was then input into GenomeScope 44 and an inhouse pipeline to estimate genome size and heterozygosity. Genome sequencing High molecular weight (HMW) DNA was extracted using a modified CTAB method on isolated nuclei. First, leaf tissues were ground in liquid nitrogen, and the powder was resuspended in the Beckman buffer (same as in our flow cytometric experiments). We then used 30µm nylon circular filters (Partec, Germany) to remove tissue debris, and precipitated nuclei with 100g centrifugation under 4°C for 20 minutes. For the downstream CTAB procedures, we followed the protocol outlined in Kuo 45 . HMW DNA was QC’d on an agarose gel for length and quantified on a bioanalyzer. Unsheared HMW DNA was used to make Oxford Nanopore Technologies (ONT) ligation-based libraries (Oxford, UK). Libraries were prepared starting with 1.5ug of DNA and following all other steps in ONT’s SQK-LSK109 protocol. Final libraries were loaded on an ONT flowcell (v9.4.1) and run on the GridION. Bases were called in real-time on the GridION using the flip-flop version of Guppy (v3.1). The resulting fastq files were concatenated and used for downstream genome assembly steps. The same batch of HMW genomic DNA was used to construct Illumina (Illumina, USA) libraries for estimating genome size (above) and correcting residual errors in the ONT assembly. Libraries were constructed using the KAPA HyperPrep Kit (Kapa Biosystems, Switzerland) followed by sequencing on an Illumina NovaSeq6000 with 2×150 bp paired-ends. Genome assembly ONT reads were assembled using minimap2 and miniasm 46 , and the resulting draft assembly was then polished by racon 47 (with nanopore reads) and pilon 48 (with Illumina reads). Because the plants were grown non-axenically under water, the assembly inevitably contained contaminations. We therefore used blobtools 49 to identify non-plant contigs based on a combination of contig read coverage, taxonomic assignment, and GC content. To further scaffold the assembly, we generated a genome map using Bionano with the Direct Label and Stain chemistry and DLE-1 labeling. For this, high molecular weight DNA was extracted using the Bionano Plant DNA Isolation Kit. Hybrid scaffolding, combining the nanopore draft and Bionano map, was done on the Bionano Saphyr computing platform at the McDonnell Genome Institute at Washington University. We then gap-filled the scaffolded genome using two rounds of LR_Gapcloser 50 (3 iterations each and a pilon polishing in between. Finally, to remove redundancy the purge_haplotigs pipeline 51 was used to obtain the v1 assembly. The circular chloroplast genome was assembled from Illumina data using the GetOrganelle 52 toolkit. Repeat annotation We generated a custom I. taiwanensis -specific repeat library using LTR-retriever 53 and RepeatModeler 54 . To identify and remove repeats with homology to plant proteins, we used BLASTx to query each repeat against the uniprot plant protein database (e-value threshold at 1e-10). The resulting library was then input into RepeatMasker 55 to annotate and mask the repetitive elements in the I. taiwanensis genome. Gene annotation We trained two ab initio gene predictors, AUGUSTUS 56 and SNAP 57 , on the repeat-masked genome using a combination of protein and transcript evidence. For the protein evidence, we relied on the annotated proteomes from Selaginella moellendorffii 16 and S. lepidophylla 18 , and for the transcript evidence, we used the RNA-seq data from our time-course experiment and a separate corm sample. To train AUGUSTUS, BRAKER2 58 was used and the transcript evidence was input as an aligned bam file. On the other hand, SNAP was trained under MAKER with 3 Iterations, and in this case, the transcript evidence was supplied as a de novo assembled transcriptome done by Trinity 59 . After AUGUSTUS and SNAP were trained, they were fed into MAKER 60 along with all the evidence to provide a synthesized gene prediction. Gene functional annotation was done using the eggNOG-mapper v2 61 . To filter out spurious gene models, we removed genes that met none of the following criteria: (1) a transcript abundance greater than zero in any sample (as estimated by Stringtie 62 ), (2) has functional annotation from eggNOG, and (3) was assigned into orthogroups in an Orthofinder 20 run (see below). The resulting gene set was used in all subsequent analyses. Homology assessment and gene family analysis Homology was initially assessed with Orthofinder 20 using genomic data from a range of taxa from across the plant tree of life including all CAM plant genomes published to date: Amborella trichopoda 63 , Ananas comosus 9 , Anthoceros agrestis 24 , Arabidopsis thaliana 64 , Azolla filiculoides 28 , Brachypodium distachyon 65 , Ceratophyllum demersum 66 , Isoetes taiwanensis (this study), Kalanchoe fedtschenkoi 10 , Marchantia polymorpha 23 , Medicago truncatula 67 , Nelumbo nucifera 68 , Nymphaea colorata 69 , Phalaenopsis equestris 11 , Physcomitrium patens 22 , Picea abies 70 , Salvinia cucullata 28 , Sedum album 8 , Selaginella moellendorffii 16 , Sphagnum fallax ( Sphagnum fallax v0.5, DOE-JGI, http://phytozome.jgi.doe.gov/ ), Spirodela polyrhiza 71 , Utricularia gibba 72 , Vitus vinifera 73 , and Zostera marina 74 , and one algal genome: Mesotaenium endlicherianum 75 . Following homology assessment, the degree of overlap between gene families was assessed using the UpsetR 76 package in R. RNA editing analysis RNA-seq data was first mapped to combined nuclear and chloroplast genome assemblies using HISAT2 77 . The reads mapping to the chloroplast genome were extracted using samtools 78 . SNPs were called using the mpileup function in bcftools 79 . The resulting vcf files were filtered using bcftools to remove samples with a depth < 20, quality score < 20 and mapping quality bias < 0.05. After filtering, C-to-U and U-to-C edits were identified using an alternate allele frequency threshold of 10%. Finally, RNA editing sites were related to specific genes using the intersect command in bedtools 80 and characterized using a custom python script. Ks analysis Ks divergence was calculated by several different methods. Initially, a whole paranome Ks distribution was generated using the ‘wgd mcl’ tool 81 . Self-synteny was then assessed in i-Adhore and Ks values were calculated and plotted for syntenic pairs only using the ‘wgd syn’ tool 81 . To conduct Ks analysis of related species, RNA-seq data was downloaded from the SRA database for Isoetes yunguiensis, I. sinensis, I. drummondii, I. echinospora, I. lacustris and I. tegetiformans . Transcriptomes were assembled using SOAPdenovo-Trans 82 with a Kmer length of 31. Next, for each Isoetes genome and transcriptome, we used the DupPipe pipeline to construct gene families and estimate the age distribution of gene duplications 83 , 84 . We translated DNA sequences and identified ORFs by comparing the Genewise 85 alignment to the best-hit protein from a collection of proteins from 25 plant genomes from Phytozome 86 . For all DupPipe runs, we used protein-guided DNA alignments to align our nucleic acid sequences while maintaining the ORFs. We estimated Ks divergence using PAML 87 with the F3×4model for each node in the gene family phylogenies. We then used mixture modeling to identify significant peaks consistent with a potential WGD and to estimate their median paralog Ks values. Significant peaks were identified using a likelihood ratio test in the boot.comp function of the package mixtools 88 in R. Estimation of orthologous divergence To place putative WGDs in relation to lineage divergence, we estimated the synonymous divergence of orthologs among pairs of species that may share a WGD based on their phylogenetic position and evidence from the within-species Ks plots. We used the RBH Orthologue pipeline 84 to estimate the mean and median synonymous divergence of orthologs, and compared those with the synonymous divergence of inferred paleopolyploid peaks. We identified orthologs as reciprocal best blast hits in pairs of transcriptomes. Using protein-guided DNA alignments, we estimated the pairwise synonymous divergence for each pair of orthologs using PAML 87 with the F3X4 model. Phylogenetic assessment of ancient whole genome duplication WGD inference was conducted by phylogenomic reconciliation using the WhALE package implemented in Julia 27 . First, prior to WhALE analysis, Orthofinder 20 was used to identify groups of orthologous genes among 7 species representing 3 taxonomic groups (bryophytes, lycophytes, and ferns): Azolla filiculoides 28 , Isoetes taiwanensis (this study), Marchantia polymorpha 23 , Physcomitrium patens 22 , Salvinia cucullata 28 , Selaginella moellendorffii 16 , and Sphagnum fallax ( Sphagnum fallax v0 . 5 , DOE-JGI, http://phytozome.jgi.doe.gov/ ). These species were chosen based on phylogenetic relatedness, availability of a high-quality genome assembly, and previous assessment for the presence or absence of WGD. The resulting orthogroups were filtered using a custom python script to remove the 5% largest orthogroups and those with less than 3 taxa. Additionally, WhALE requires removal of gene families that do not contain at least one gene in both bryophytes and ferns to prevent the inclusion of gene families originating after divergence from the most recent common ancestor. Alignments were generated for the filtered orthogroups in PRANK 89 using the default settings. A posterior distribution of trees was obtained for each gene family in MrBayes 3.2.6 90 using the LG model. Chains were sampled every 10 generations for 100,000 generations with a relative burn-in of 25%. Following the Bayesian analysis, conditional clade distributions (CCDs) were determined from posterior distribution samples using ALEobserve in the ALE software suite 91 . CCD files were subsequently filtered using the ccddata.py and ccdfilter.py scripts provided with the WhALE program. A dated, ultrametric species tree was generated using the ‘ape’ package in R 92 , in which branch lengths were constrained according to 95% highest posterior density of ages, assuming that bryophytes are monophyletic, as reported by Morris et al. 93 . Finally, the filtered CCD files were loaded in Julia along with the associated species phylogeny. A hypothetical WGD node was inferred at 200 million years ago (MYA) along the branch leading to I. taiwanensis , prior to the estimated crown age of extant Isoetes 94 . Modifying the hypothetical age of this WGD node did not affect the outcome. Additional WGD nodes were placed as positive controls along branches leading to Physcomitrium patens and Azolla filiculoides at 40 MYA and 60 MYA, respectively, based on previous studies 22 , 28 . A false WGD event was also placed arbitrarily in Marchantia polymorpha at 160 MYA as a negative control. A WhALE ‘problem’ was constructed using an independent rate prior and MCMC analysis was conducted using the DynamicHMC library in Julia ( https://github.com/tpapp/DynamicHMC.jl ) with a sample size of 1000. Phylogenetic analysis of root, stomata, and CAM pathway genes Following clustering of homologs in Orthofinder, we conducted phylogenetic analysis of several gene families of interest, including those containing SMF, FAMA, TMM, RSL , and PEPC genes, were subsequently identified based on homology using gene annotations from Arabidopsis . Gene trees from Orthofinder were initially used to identify paralogues and remove fragmented genes where appropriate. In the case of PEPC , orthogroups containing “bacterial-type” and “plant-type” PEPC were combined prior to alignment. Next, amino acid sequences were aligned using MUSCLE 95 under default settings and trimmed using TrimAL with the -strict flag. An amino acid substitution model was selected according to the Bayesian Information Criterion (BIC) in ModelFinder 96 prior to phylogenetic reconstruction by maximum likelihood in IQ-TREE v1.6.12 97 with 1000 ultrafast 98 bootstrap replicates. Phylogenetic analysis of genes salient to the phenylpropanoid and lignin biosynthesis pathway The datasets used for phylogenetic analysis were based on de Vries et al. 99 with added I. taiwanensis sequences. In brief, we assembled a dataset of predicted proteins from (A) the genomes of seventeen land plants: Anthoceros agrestis as well as Anthoceros punctatus 24 , Amborella trichopoda 63 , Arabidopsis thaliana 64 , Azolla filiculoides 28 , Brachypodium distachyon 65 , Capsella grandiflora 100 , Gnetum montanum 101 , Isoetes taiwanensis (this study), Marchantia polymorpha 23 , Nicotiana tabacum 102 , Oryza sativa 103 , Physcomitrium patens 22 , Picea abies 70 , Salvinia cucullata 28 , Selaginella moellendorffii 16 , and Theobroma cacao 104 ; (B) the genomes of seven streptophyte algae: Chlorokybus atmophyticus 105 , Chara braunii 106 , Klebsormidium nitens 107 , Mesotaenium endlicherianum 75 , Mesostigma viride 105 , Penium margaritaceum 108 , Spirogloea muscicola 75 —additionally, we included sequences found in the transcriptomes of Spirogyra pratensis 109 , Coleochaete scutata as well as Zygnema circumcarinatum 110 , and Coleochaete orbicularis 111 ; (C) the genomes of eight chlorophytes: Bathycoccus prasinos 112 , Chlamydomonas reinhardtii 113 , Coccomyxa subellipsoidea 114 , Micromonas sp. as well as Micromonas pusilla 115 , Ostreococcus lucimarinus 116 , Ulva mutabilis 117 , Volvox carteri 118 . For phenylalanine ammonia-lyase, additional informative sequences were added based on de Vries et al. 119 . Building on the alignments published in de Vries et al. 99 , homologs of each gene family (detected in the aforementioned species via BLASTp) were (re-)aligned using MAFFT v7.475 120 with a L-INS-I approach; both full and partial sequences from I. taiwanensis were retained. We constructed maximum likelihood phylogenies using IQ-TREE 2.0.6 121 ; 1000 ultrafast 98 bootstrap replicates were computed. To determine the best model for protein evolution, we used ModelFinder 96 and picked the best models based on BIC. Residue information was mapped next to the tree based on structural analyses by Hu et al. 122 , Pan et al. 123 , Louie et al. 124 , Youn et al. 125 and Ferrer et al. 126 . Time course titratable acidity and RNA-seq experiments Leaves of I. taiwanensis were taken from five individuals every 3 hours over a 27-hour period on a 12-hour light/dark cycle and constant temperature. To measure changes in acidity over time, a portion of the leaf tissues was weighed, mixed with 3.5-5ml of ddH20, and titrated with 0.0125M NaOH solution until pH = 7.0. At the same time, we froze the leaf tissues in liquid nitrogen, and extracted RNA using a modified CTAB protocol 127 . RNA quality was examined on a 1% agarose gel and RNA concentration was quantified using the Qubit RNA HS assay kit (Invitrogen, USA). 2ug of total RNA was used to construct stranded RNA-seq libraries 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 an Illumina NovaSeq6000 with 2×150 bp paired-ends. Differential expression analysis RNA-seq reads were mapped to the combined nuclear and chloroplast genome using HISAT2 77 . Stringtie 62 was used to assemble transcripts and estimate transcript abundance. A gene count matrix was produced using the included prepDE.py script. We imported gene count data into the DESEQ2 package in R 128 for read normalization using its median of ratios method as well as identification and removal of outlier samples using multidimensional scaling. A single outlier sample from each of six time points (1hr, 4hrs, 7hrs, 10hrs, 13hrs and 19hrs) was removed from the final dataset. The resulting dataset was used to analyze temporal gene expression patterns in the R package maSigPro 129 . Using maSigPro, genes with significantly differential expression profiles were identified by computing a regression fit for each gene and filtered based on the associated p-value (p<0.001). HAYSTACK global cycling prediction Genes with mean expression across all the time points below 1 TPM were considered “not expressed” and filtered prior to cycling prediction with HAYSTACK ( https://gitlab.com/NolanHartwick/super_cycling ) 33 . HAYSTACK operates by correlating the observed expression levels of each gene with a variety of user specified models that represent archetypal cycling behavior. We used a model file containing sinusoid, spiking traces, and various rough linear interpolations of sinusoids with periods ranging from 20 hours to 28 hours in one-hour increments and phases ranging from 0-23 hours in one-hour increments. Genes that correlated with their best fit model at a threshold of R > 0.8 were classified as cyclers with phase and period defined by the best fit model. This threshold for calling cycling genes is based on previous validated observations 8 , 33 , 34 , 130 . We also validated this threshold by looking at the cycling of known circadian clock genes ( Fig. 5 ). ELEMENT cis-regulatory elements analysis Once cycling genes in I. taiwanensis were identified, we were able to find putative cis-acting elements associated with TOD expression. Promoters, defined as 500 bp upstream of genes, were extracted for each gene and processed by ELEMENT ( https://gitlab.com/salk-tm/snake_pip_element ) 33 , 131 , 132 . Briefly, ELEMENT generates an exhaustive background model of all 3-7 K-mer using all of the promoters in the genome, and then compares the K-mers (3-7 bp) from the promoters for a specified gene list. Promoters for cycling genes were split according to their TOD expression into “phase” gene lists and K-mers that were overrepresented in any of these 24 promoter sets were identified by ELEMENT. By splitting up cycling genes according to their associated phase, we gained the power to identify K-mers associated with TOD-specific cycling behavior at every hour over the day. Our threshold for identifying a K-mer as being associated with cycling was an FDR < 0.05 in at least one of the comparisons. The significant K-mers were clustered according to sequence similarity ( Fig. 6 ). Promoter motif identification Core CAM genes with significantly differential diel expression profiles (as identified in maSigPro) including β-CA, PEPC, PEPCK, ME, MDH , and PPDK were selected for motif enrichment analysis. Enriched motifs were identified relative to a background consisting of non-cycling paralogues of photosynthetic genes using the AME utility 133 . Promoters were searched for known motifs from the Arabidopsis promoter binding motif database 134 with FIMO 135 . Data availability All the raw sequences were deposited in the NCBI Sequence Read Archive under the BioProject PRJNA735564. Genome assembly and annotation are available at https://genomevolution.org/coge/GenomeInfo.pl?gid=61511 . Sequence alignments and tree files can be found at https://github.com/dawickell/Isoetes_CAM . Author contributions D.W., L.-Y.K., T.P.M. and F.-W.L. coordinated the project. Y.-M.H. provided the plant materials. L.-Y.K. carried out the time-course experiment and nucleic acid extraction. T.P.M. and F.-W.L. sequenced and assembled the genome. H.-P.Y. and F.-W.L. annotated the genome. D.W. assembled the plastome and profiled RNA-editing. D.W. circumscribed gene families and examined genes related to stomata and root development. A.D.A., I.I., A.M., S.d.V. and J.d.V. characterized lignin biosynthesis genes. D.W., Z.L. and M.S.B. carried out WGD analysis. D.W. analyzed expressions of CAM pathway genes. N.T.H. and T.P.M. carried out HAYSTACK and ELEMENT analyses. D.W., T.P.M. and F.-W.L. synthesized and wrote the manuscript. 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