The Plant Short-Chain Dehydrogenase (SDR) superfamily: genome-wide inventory and diversification patterns
© Moummou et al.; licensee BioMed Central Ltd. 2012
Received: 23 May 2012
Accepted: 16 November 2012
Published: 20 November 2012
Short-chain dehydrogenases/reductases (SDRs) form one of the largest and oldest NAD(P)(H) dependent oxidoreductase families. Despite a conserved ‘Rossmann-fold’ structure, members of the SDR superfamily exhibit low sequence similarities, which constituted a bottleneck in terms of identification. Recent classification methods, relying on hidden-Markov models (HMMs), improved identification and enabled the construction of a nomenclature. However, functional annotations of plant SDRs remain scarce.
Wide-scale analyses were performed on ten plant genomes. The combination of hidden Markov model (HMM) based analyses and similarity searches led to the construction of an exhaustive inventory of plant SDR. With 68 to 315 members found in each analysed genome, the inventory confirmed the over-representation of SDRs in plants compared to animals, fungi and prokaryotes. The plant SDRs were first classified into three major types — ‘classical’, ‘extended’ and ‘divergent’ — but a minority (10% of the predicted SDRs) could not be classified into these general types (‘unknown’ or ‘atypical’ types). In a second step, we could categorize the vast majority of land plant SDRs into a set of 49 families. Out of these 49 families, 35 appeared early during evolution since they are commonly found through all the Green Lineage. Yet, some SDR families — tropinone reductase-like proteins (SDR65C), ‘ABA2-like’-NAD dehydrogenase (SDR110C), ‘salutaridine/menthone-reductase-like’ proteins (SDR114C), ‘dihydroflavonol 4-reductase’-like proteins (SDR108E) and ‘isoflavone-reductase-like’ (SDR460A) proteins — have undergone significant functional diversification within vascular plants since they diverged from Bryophytes. Interestingly, these diversified families are either involved in the secondary metabolism routes (terpenoids, alkaloids, phenolics) or participate in developmental processes (hormone biosynthesis or catabolism, flower development), in opposition to SDR families involved in primary metabolism which are poorly diversified.
The application of HMMs to plant genomes enabled us to identify 49 families that encompass all Angiosperms (‘higher plants’) SDRs, each family being sufficiently conserved to enable simpler analyses based only on overall sequence similarity. The multiplicity of SDRs in plant kingdom is mainly explained by the diversification of large families involved in different secondary metabolism pathways, suggesting that the chemical diversification that accompanied the emergence of vascular plants acted as a driving force for SDR evolution.
KeywordsShort-chain dehydrogenase/reductase (SDRs) SDR nomenclature initiative Hidden markov model Multigenic family Plant
Short-chain dehydrogenases/reductases (SDRs) constitute one of the largest and oldest protein superfamilies known to date. This ancient family, found in all domains of life (Archea, Eukaryotes, Prokaryotes and viruses), is characterized by large sequence divergences but several common properties: (i) a conserved 3D structure consisting of ‘Rossmann-fold’ β-sheet with α-helices on both sides, (ii) an N-terminal dinucleotide cofactor binding motif, (iii) an active site with a catalytical residue motif YxxxK [1, 2]. With the release of genome sequences of numerous living organisms, the availability of around 300 crystal structures and the identification of many enzymatic functions, much attention has been given to classify the members of the SDR superfamily. A first discrimination was established between five types of SDR: the ‘classical’ type, consisting of approximately 250 amino acids, the ‘extended’ type that has an additional 100-residue domain in the C-terminal region, the ‘intermediate’ type that displays a specific G/AxxGxxG/A cofactor binding motif, the ‘divergent’ type that comprises enoyl-reductases from plant and bacteria and harbours modifications both in the cofactor binding site and active site motifs and the ‘complex’ SDR which are usually part of large multi-domain enzymes, such as mammalian fatty acid synthases or bacterial polyketide synthases [2–4]. Moreover, the discovery of new oxidoreductase structures harbouring the SDR ‘Rossmann-fold’ motif revealed the existence of uncommon types, often referred to as ‘unknown’ or ‘atypical’ types. More recently, the diversity of SDRs, either their amino acid sequences or their functions, led to the development of a second classification effort: the ‘SDR Nomenclature Initiative’ that aims at being more informative regarding SDRs functions and at establishing a sustainable and expandable nomenclature system based on the use of a large set of hidden Markov models (HMM) . Nowadays, 449 families have been listed in this nomenclature .
Although mentioned by several authors [2, 4], the diversity of SDRs in plants has never been investigated thoroughly. The recent advances in sequencing techniques and the still-increasing speed of genome releases now facilitate an exhaustive review of complex multigenic families. In the case of SDRs, a second challenge for plant scientific community is to unravel the functions of these oxidoreductases. Indeed, in the TAIR10 annotation of Arabidopsis thaliana genome, a large majority of ‘classical’ SDRs (two thirds) are merely annotated as NAD(P)-binding Rossmann-fold superfamily protein oxidoreductase . This lack of information prompted us to adopt an exhaustive approach on plant SDRs. In a previous paper, we reviewed the involvement of different SDRs in primary and secondary metabolism . In the present paper, we combined the use of HMMs and phylogenetic analyses on a set of genomes representative of plant diversity, in order to conduct a global inventory of plant SDRs coherent with the current SDR classification and nomenclature. This inventory was integrated into a functional classification of plant SDRs. Since this genome-wide inventory confirmed the high diversity of plant SDRs, the distribution and evolution of the different SDR families was examined, notably to investigate the link between SDR diversification and the emergence of secondary metabolism in vascular plants.
Reference and size of the analyzed genomes
Number of loci
12X March 2010 release
MSU Rice Genome Annotation (Osa1) Release 6.1
HMM-based analyses of plant genomes
Genomic sets of predicted proteins were challenged with three Pfams HMMs : PF00106, PF01370 and PF01073 using HMMER3. SDR Nomenclature Initiative HMMs were defined and updated as described previously . The five SDR types (‘classical’, ‘extended’, ‘intermediate’, ‘divergent’, and ‘complex’) each has an HMM trained to identify sequences of respective type. The HMMs were created using HMMER3, with manually adjusted alignments of representative sequences as seed. Cutoffs are used to decide if a hit is significant or not: ‘classical’ — 138, ‘extended’ — 108, ‘intermediate’ — 162, ‘divergent’ — 160, and ‘complex’ — 140. In addition to the five types, an ‘unknown’ label is used for sequences with scores lower that these cutoffs but still high enough to safely predict the sequence as an SDR: ‘classical’ — 29, ‘extended’ — 75, and ‘divergent’ — 100. Scores below the cutoffs are considered not positive.
For the PLR/IFR family, an HMM was created and incorporated to the ‘SDR Nomenclature Initiative’ set of family HMMs. The procedure for training the HMM was the same as previously developed with iterative refinement of the model until no new members were found .
Decision rules for SDR inventory
For the gene loci that are associated with several gene models and therefore with different protein predictions, a sole amino acid sequence was selected according two criteria: (1) the maximum HMM score and (2) the maximum alignment score deduced from a BlastP performed on other plant genomes. When the HMM and BlastP analyses led to contradictory predictions, a single protein prediction was manually selected after aligning the different gene models with its closest homologues. To include in the SDR classification the truncated proteins that failed to be recognized by the HMMs, a BlastP sequence search was performed on each genome using as query sequences the complete list of SDRs recognized in the first round of HMM searches. All sequences that displayed a segment of 60 amino acids with more than 50% identity were classified in the same type or family as its closest homologue.
Distance matrices and phylogenetic analyses
Phylogenetic analyses and distance matrices were built using the Mega5 package . Full length amino acid sequences were aligned using the ClustalW algorithm. Distance matrices evaluating the percentage of sequence identity were calculated on the basis of p-distance with the pairwise deletion option. Unless stated differently, phylogenetic trees were built using the Neighbor-Joining method. The percentage of replicate trees in which the associated taxa clustered together was calculated in the bootstrap test (500 replicates). Trees were drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were expressed as the units of the number of amino acid substitutions per site.
Results and discussion
HMM-driven inventory of plant SDR
Initial HMM analyses were performed on ten complete genomes: 4 Eudicots (Arabidopsis thaliana, Populus trichocarpa, Vitis vinifera, Glycine max), 3 Monocots (Zea mays, Oryza sativa and Sorghum bicolor), the lycophyte Selaginella moellendorffii, the moss Physcomitrella patens and the unicellular green alga Chlamydomonas reinhardtii (Table 1). The predicted ‘proteomes’ deduced from the genome annotations were searched against three distinct sets of HMMs: the Pfam HMMs considered to encompass most SDR (PF00106, PF01370, PF01073), HMMs developed in the framework of the SDR nomenclature initiative [5, 21] and a set of HMMs developed to predict the type (‘classical’, ‘extended’, ‘intermediary’, ‘divergent’ and ‘complex’) of SDR (see Methods).
This first analysis led to an exhaustive inventory of plant SDRs presented in supplemental data (Additional file 1: Table S1 and Additional file 2: Table S2). This inventory was divided into a main list (Additional file 1: Table S1), where the HMM scores or the high similarity with known SDRs were sufficient to establish a good prediction, and a complementary list of ambiguous SDR predictions (Additional file 2: Table S2), containing proteins with low HMM scores and absence of structural data (see decision tree in Figure 1 and Methods). Despite its very low HMM scores, we included in the main list a large family that comprises pinoresinol reductase (PLR), isoflavone reductase (IFR), vestitone reductase, phenylcoumaran benzylic ether reductase and eugenol synthase. Indeed, the structures of several members of this family were resolved by crystallography and the data revealed the presence of a SDR-typical Rossmann-fold [22–25]. Subsequently, an HMM was created and incorporated to the ‘SDR Nomenclature Initiative’ set of HMMs. The PLR/IFR family was named SDR460A, where the ‘A’ stands for ‘atypical’.
Distribution of plant SDRs
Distribution of SDRs in different plants
Types of SDR
Sub-classification of plant SDR
Classification of plant SDRs
SDR nomenclature initiative
Average identity (%)
Pisum sativum Tic32 (chloroplast protein import translocon)
β-ketoacyl reductase (fatty acids elongation)
SDRA-IBR1 (indole-3-butyric acid response 1)
ABA2 (xanthoxin oxidase), Tasselseed2, Secoisolariciresinol dehydrogenase, Momilactone A synthase, Isopiperitenol dehydrogenase
Salutaridine reductase, Menthone reductase, Isopiperitenone reductase
Solanum tuberosum TDF511
FAS-II- β-ketoacyl reductase (FabG)
Pterin aldehyde reductase (folate salvage)
Arabidopsis thaliana Forever Young
Enoyl-ACP reductase (ENR)
Cucumis melo ADH2
NYC1/NOL (chlorophyll b reductase)
UDP-D-glucose/UDP-D-galactose 4-epimerase, UDP-arabinose 4-epimerase
UDP-xylose synthase, UDP-glucuronic acid decarboxylase
Dihydroflavonol 4-reductase, Anthocyanidin reductase, Cinnamoyl-CoA reductase, Phenylacetaldehyde reductase, Eutypine reductase
VEIN PATTERNING 1 (VEP1), progesterone 5β-reductase
Chloroplast stem-loop binding protein
3,8-divinyl protochlorophyllide a 8-vinyl reductase
Pinoresinol reductase, Isoflavone reductase, Vestitone reductase, Phenylcoumaran benzylic ether reductase, Eugenol synthase
Farnesol NAD dehydrogenase
On the opposite, 5.5% of plant SDRs (from 4% in Angiosperms to 29% in C. reinhardtii) remained unclassified. The existence of these orphan SDRs lays in the conception of the ‘SDR nomenclature initiative’ HMMs. In order to achieve robust HMMs, the authors considered only families with sufficient number of representative and non-redundant sequences , thus excluding SDR families with too few members. To circumvent this difficulty, we examined the possibility to define new families on the sole basis of amino-acid sequence conservation. Therefore, all the unclassified SDRs from the main inventory (Additional file 1: Table S1) were associated to its closest homologues using BlastP searches and sequence alignments. Interestingly, all the unclassified sequences from Angiosperms clearly matched with at least one Arabidopsis SDR, the e value obtained from a BlastP against Arabidopsis predicted proteome never exceeding 1 e-40. Thus, seven new clusters were defined on the basis of sequence conservation, four being common to all the Viridiplantae genomes while three were found only in land plants (Figure 2 and Table 3). Within these clusters, the average pairwise sequence identities ranged from 48% to 62%. These conservation rates are consistent with the average pairwise identities observed for the families defined by a ‘SDR nomenclature initiative’-HMM, that ranges from 37% to 82% identity (Table 3). All these clusters were represented by a limited number of sequences in each genome, supporting the explanation that the lack of ‘SDR-nomenclature-initiative’-HMMs is simply the consequence of an insufficient set of sequences and that these families might be defined in the future, with the release of new sequences in the UNIPROT database. To complete the plant SDR classification, each new cluster was assigned a representative gene, based on an Arabidopsis thaliana identifier. While all angiosperms SDRs could be categorized in a family, defined either by a specific HMM or by primary structure conservation, 15 sequences from C. reinhardtii, 4 sequences from P. patens and one sequence from S. moellendorffii were too distant to other SDR sequences and remained unclassified.
By extension, the ambiguous SDR sequences were also clustered on the basis of sequence homologies, allowing the definition of nine potential families (Additional file 2: Table S2). Yet, in absence of structural data confirming the existence of typical SDR structures, these sequences were not analysed further.
In a last step, plant SDR classification was combined with functional information. Taking advantage of our previous bibliographic research  and of the annotations found for Arabidopsis (TAIR10), we completed the classification by mentioning all the known functions described in the scientific literature in Table 3. Also, to each family, a representative gene was chosen according to three criteria: (1) favour Arabidopsis accessions with respect to the quality of TAIR annotations and its pertinence as a model plant; (2) when possible, opt for genes that have been functionally characterised; otherwise (3), priority was given to the accession that displayed the lowest average distance with other members of its family.
Evolution and diversification of plant SDR as a potential trait of land plant emergence?
The distribution of the different families in the different taxa was further examined to understand the evolution of the plant SDR superfamily. We first addressed the question of potential origins of the different SDR families. Out of the 49 families listed in Table 3, 32 were found both in the alga C. reinhardtii and in the majority of land plants, suggesting that most plant SDRs families emerged prior to land plant radiation that started -460 Myear ago, in the Ordovician period . For three additional families (SDR40C, SDR42E and SDR358U), the absence of a member in C. reinhardtii or even in P. patens predicted proteomes masked the occurrence of these families in other genus of green algae (Volvox, Micromonas, Chlorella and Ostreococcus), suggesting either that some genomic sets are incomplete or that the families are ancestral but the genes might have been lost in some taxa. In addition, 10 families absent in green algae are common to all land plants (Figure 2 and Table 3), indicating that 45 families are shared among land plants (embryophytes). 48 families are common to vascular plants as 3 additional families are specific to S. moellendorffii and Angiosperms. At last, a sole family, SDR115E, is found only in Angiosperms. The origins of some families may be very ancient: SDR1E, 2E, 6E and 7C families are found in all domains of life (Archea, Eukaryote, Prokaryote) while the SDR12C, 17C, 25C, 34C, 35C, 22E and 31E families are common to the majority of Eukaryotes . Besides, several ancestral SDR families are close to Prokaryotic ‘homologues’. For example, the origin of the plastids is illustrated by the presence of chloroplastic SDRs similar to its cyanobacterial homologue. In a recent paper, Kramm et al. listed 39 SDRs in the genome of the cyanobacteria Synechocystis sp. PCC 6803. 20 of these SDRs show clear homologies (>35% identity) with plant SDRs (data not shown). The SDRs clusters present both in cyanobacteria and plant genomes include the very ancient families (SDR1E, 2E, 3E, 6E) and several plastidial proteins involved in primary metabolism, such as sulfolipid biosynthesis protein (SDR52E), protochlorophyllide oxidoreductase (SDR73C), 3,8-divinyl protochlorophyllide a 8-vinyl reductase (SDR98U) or the members of the fatty acid synthase (FasII) complex (SDR152C and SDR87D).
Remarkably, all the five families expanded in vascular plants comprise enzymes involved in secondary metabolism (Table 3): tropinone reductases (SDR65C) are known for their involvement in alkaloids biosynthesis; SDR110C NAD-dehydrogenases oxidize various phenolic or terpeninc compounds, including xanthoxin, a precursor of abscissic acid (ABA); SDR114C menthone and salutaridine reductase, are involved in monterpene and alkaloid metabolism respectively; the large SDR108E family members catalyze the reduction of several phenolic precursors (4-dihydroflavonol, anthocyanidin, cinnamoyl-CoA, phenylacetaldehyde or eutypine) and last, the atypical PLR/IFR family (SDR460A) is also involved in phenolic metabolism. On the opposite, several poorly diversified clusters (SDR52E, 73C, 152C, 87D, 357C) that contain highly conserved sequences participate in primary metabolism such as chlorophyll synthesis or degradation, lipid metabolism or vitamin synthesis.
Identification of functional clusters within SDR families
For multigenic SDR families, the analyses can be conducted further with phylogenetic calculations. To illustrate the importance of this complementary approach, we focused on two large families involved in secondary metabolism: SDR110C (ABA2 xanthoxin dehydrogenase family) and SDR108E (4-DFR) family. For tropinone reductase (SDR65C) and menthone/salutaridine reductase (SDR114C) families, readers are referred respectively to Brock et al. and Ziegler et al. for complete phylogenetic analyses.
For the highly variable SDR108E family, we included the SDR115E family in the analysis as both family are closely related (see above). As reported for the SDR110C family, several branches can be associated with functions described in the literature : 4-DFR , anthocyanidin reductase (AnR) [34, 35], HC-toxin reductase , phenylacetaldehyde reductase , cinnamoyl-CoA reductase (CCR)  or eutypine reductase  (Figure 3). In contrast to SDR110C, the tree is also informative concerning the evolution of SDRs among land plant since distinct sequences from S. moellendorffii and P. patens are clearly associated with independent clades. These associations are of special interest for certain classes of enzymes such as the CCR catalysing the first irreversible oxidation step leading to monolignol synthesis. Indeed, several enzymes involved in the lignin biosynthesis pathway appeared early in land plant evolution and the moss are believed to accumulate uncondensed monolignols . Thus, the association on the same branch of sequences from P. patens and S. moellendorffii with Angiosperms bona fide CCR suggests that the enzyme anciently acquired its specificity and diverged rapidly from other SDR108E members. Last, as observed for SDR110C, several highly similar genes are clustered in specific chromosomal regions. Hence, with numerous members and a low conservation rate of amino acid sequences, the SDR108E family and its daughter branch SDR115E constitute a good example of a gradual and fast evolution of a multigenic family. Since the majority of the described enzymes reduce phenolic compounds, we may hypothesize that the SDR108E evolution accompanied tightly the complexification of phenolic and phenylpropanoid metabolism during land plant radiation.
Work presented in this paper aimed at providing a full picture of plant SDRs using the current classification, especially the recent SDR nomenclature initiative. The combination of HMM models and similarity searches enabled us to classify most of the plant SDRs into a core of 49 families. Of these 49 families, 42 could be associated to an HMM, while the other 7 families being only defined on the basis of amino acids sequence conservation. Remarkably, all predicted SDRs from Angiosperms or S. Moellendorffii (corresponding to the so-called ‘higher plants’) could be categorized within these families. As all families exhibit a high degree of primary structure conservation, the average amino acid identities ranging from 37% to 87% among plant genomes, all SDRs sequences from Angiosperms can be analysed easily on the sole basis of sequence alignment, using very classical software (Blast, Multialin, ClustalW). For moss P. patens and green alga C. reinhardtii sequences, the predictions are less accurate, 3% and 20% of predicted SDRs remain unclassified. This limitation probably results from the under-representation of bryophyte and chlorophyte sequences compared to Angiosperms. In addition, the development of genome sequencing on more distant taxa (for example charophytes, liverworts or hornworts) should increase the number of UNIPROT sequences with sufficient divergences, thus improving the quality of HMM and allowing, in a mid-term, the definition of HMMs for the orphan SDR families.
Strikingly, the number of families found in Angiosperms (49) does not differ much from the 47 SDR families listed in the human genome . The large proportion of families (35 out of 49) found in all Viridiplantae, from Algae to Angiosperms, is consistent with the view that most SDR sub-branches diverged early during evolution . Plants possess either SDRs common to all Eukaryotes or SDRs of bacterial origin, in particular SDRs deriving from the plastidial endosymbiosis. However, the major difference between plants and other eukaryotes, that explains the high number of SDRs in ‘higher plants’, lies in the existence of large multigenic families. These families expanded much later during evolution, as attested by their under-representation in moss and algae. Because of their involvement in secondary metabolism routes (including hormone biosynthesis), they can be considered as an adaptative character that emerged during land colonization and emergence of the vascular apparatus.
HM participated in sequence alignments, phylogenetic analyses and collection of functional annotations. LB initiated the SDR inventory and participated in sequence alignments. BVDR conceived the study, participated in its design and coordination and drafted the manuscript. YK and BP led the HMM analyses and helped to draft the manuscript. All authors read and approved the final manuscript.
- A. thaliana:
- C. reinhardtii:
- G. max:
Hidden Markov model
- O. sativa:
- P. patens:
- P. trichocarpa:
- S. bicolor:
- S. moellendorffii:
- V. vinifera:
- Z. mays:
Hanane Moummou has received a doctoral fellowship from EGIDE within the frame of a French-Morocco Volubilis project (MA-06-155) and Libert Brice Tonfack from “Service de Coopération et d’Action Culturelle” of the French Embassy (Cameroon). The authors are grateful to Jean-Claude Pech (INP-ENSAT), Mohamed Benichou (CADI AYYAD-Marrakech University) and Emmanuel Youmbi (University of Yaoundé) for the coordination of the exchange programs and their remarks during the manuscript preparation and acknowledge Elie Maza (INP-ENSAT) and Christine Rousseau (INP-ENSAT) for their help in statistical and bioinformatic analyses. Bioinformatic analyses benefited from the Bioinfo-GenoToul facilities and those of Bioinformatics Infrastructure for Life Sciences (BILS).
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