Construction of anti-codon table of the plant kingdom and evolution of tRNA selenocysteine (tRNASec)

Background The tRNAs act as a bridge between the coding mRNA and incoming amino acids during protein translation. The anti-codon of tRNA recognizes the codon of the mRNA and deliver the amino acid into the protein translation chain. However, we did not know about the exact abundance of anti-codons in the genome and whether the frequency of abundance remains same across the plant lineage or not. Results Therefore, we analysed the tRNAnome of 128 plant species and reported an anti-codon table of the plant kingdom. We found that CAU anti-codon of tRNAMet has highest (5.039%) whereas GCG anti-codon of tRNAArg has lowest (0.004%) abundance. However, when we compared the anti-codon frequencies according to the tRNA isotypes, we found tRNALeu (7.808%) has highest abundance followed by tRNASer (7.668%) and tRNAGly (7.523%). Similarly, suppressor tRNA (0.036%) has lowest abundance followed by tRNASec (0.066%) and tRNAHis (2.109). The genome of Ipomoea nil, Papaver somniferum, and Zea mays encoded the highest number of anti-codons (isoacceptor) at 59 each whereas the genome of Ostreococcus tauri was found to encode only 18 isoacceptors. The tRNASec genes undergone losses more frequently than duplication and we found that tRNASec showed anti-codon switch during the course of evolution. Conclusion The anti-codon table of the plant tRNA will enable us to understand the synonymous codon usage of the plant kingdom and can be very helpful to understand which codon is preferred over other during the translation. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-020-07216-3.


Sequence alignment
Multiple sequence alignment of tRNA Sec genes was conducted using multalin software with default parameters. To construct the phylogenetic tree, a multiple sequence alignment of tRNAs and tRNA Sec were conducted using the MUSCLE program in MEGA7 software [55,56]. The resulting alignment was saved in a MEGA le format. The alignment le was subsequently used to construct a phylogenetic tree using MEGA7 software. Prior to the construction of the phylogenetic tree, a model selection was carried out using the following statistical parameters; statistical method, maximum likelihood substitution type, nucleotides, gaps/missing data treatment, complete deletion. Based on the lowest BIC score, a phylogenetic tree of tRNAs and tRNA Sec was constructed. The statistical parameters used to construct the phylogenetic tree were: statistical method (maximum likelihood), test of phylogeny (bootstrap method), no. of bootstrap replicates (1000), substitution type (nucleotides), model/method (Kimura-2-parameter model), rates among sites (gamma distributed), no. of discrete gamma parameters (5), gaps/missing data treatment (partial deletion), site coverage cut-off (95 %), ML Heuristic method (nearest-neighbourinterchange), and branch swap lter (very strong). A separate phylogenetic tree was constructed using all of the tRNA Sec sequences and the same statistical approaches as mentioned above to determine deletion and duplication events. The constructed phylogenetic tree of tRNA Sec genes was exported in a Newick le format. Subsequently, a species tree was constructed using all of the 128 species in the taxonomy browser of NCBI. To determine RNA Sec deletion and duplication events, the phylogenetic tree of tRNA Sec was reconciled with the species tree using Notung software, version 2.9. The reconciled gene and species tree revealed deletion, duplication, and co-divergence events that occurred in tRNA Sec genes. The resultant phylogenetic tree of tRNAs (with tRNA Sec ) and the phylogenetic tree of tRNA Sec were analysed by using Icy Tree to identify recombination events.
Cluster based grouping of the anti-codons Anti-codons were grouped based on their percentage frequency in the tRNAnome. To cluster them, the percent frequency of anti-codons was used against each anti-codon. A classical clustering approach was used to cluster the anti-codons using a paired group UPGMA algorithm and Euclidean similarity index with 1000 bootstrap replicates.

Statistical analysis
The probability plot linear regression analysis of tRNA gene number per genome and frequency of anticodons were statistically analysed and a value of p<0.05 was considered to be signi cant. To investigate anti-codon numbers in different lineages and their statistical signi cance, a t-test was conducted comparing anti-codon number in eudicot vs. monocot, eudicot vs. algae, and monocot vs. algae.
Differences were deemed signi cant at p < 0.05. All of the statistical analyses were conducting using Past3 software.

Results
Genome size is not proportional to the number of tRNA genes A genome-wide analysis of fully-annotated whole genome sequences of 128 species was conducted to identify tRNA genes and to construct an anti-codon table of the plant kingdom (Table 1). The species included in the study varied in the size of their respective genomes (Table 2). A regression analysis was conducted to determine the correlation between genome size and the number of tRNA genes encoded per genome. Results indicated that plant genome size was not correlated (r = 0.5471, y=0.17892x+619. 76) with the number of the tRNA genes per genome ( Figure 1). Ipomoea nil, with a genome size of genome size of 735.23 Mb, possesses 6,475 tRNA genes which was the highest number of tRNA encoding genes identi ed in the species of plants that were analysed. Other species with a high number of tRNA genes in their genome were Cucurbita moschata (4,062), Cucurbita pepo (3,228), Cucurbita maxima (3,036), Papaver somniferum (2,571), Brassica napus (2,180), and Ipomoea triloba (2,180). Among the 128 analysed plant species, 22 (16.92%) species possessed more than one thousand tRNA genes in their genome. In contrast, Ostreococcus tauri and Phaedactylum tricornutum only encoded 41 tRNA genes in their genome, which was the lowest number of tRNA genes in the analysed genomes. Other species encoding lower number of tRNA genes were Raphidocelis subcapitata (43), Monoraphidium neglectum (48), and Bathycoccus prasinus (57). The genome size of O. tauri, P. tricornutum, R. subcapitata, and M. neglectum was 14.76, 27.4, 51.16, and 69.71 Mb, respectively. These genome sizes are relatively smaller than the genome of most of the other plant species that were analysed. CAU (Met) was the most abundant and GCG (Arg) was the least abundant encoded Anti-codons in the Plant Kingdom The occurrence of each of the anti-codons were separately analysed to determine the frequency of anticodons in the genomes of the Plant Kingdom. Results indicated that CAU (Met) was the most abundant (5.033%) anti-codon in the Plant Kingdom, followed by GUC (Asp, 4.274%), GUU (Asn, 4.020%), and GCC (Gly, 3.811%) ( Table 1, Supplementary File 1). In contrast, GCG (Arg) was identi ed as the least abundant (0.004%) anti-codon in the Plant Kingdom, followed by GAG (Leu, 0.009%), CUA (Sup, 0.0111%), and ACU (Ser, 0.019%) ( Table 1, Supplementary File 1). The lowest-abundant anti-codon (GCG) was only present in Ipomea nil, Nicotiana attenuata, Papaver somniferum, and Ziziphus jujuba. When the anti-codon frequency of different tRNA isoacceptor was considered, however, tRNA Leu was found to be the most abundant tRNA isoacceptor (Table 1). Approximately 7.808% of all anti-codons in the Plant Kingdom were found to be encoded by tRNA Leu ( Table 1). The abundance of tRNA Leu , was followed by tRNA Ser (7.668%), tRNA Gly (7.523%), and tRNA Arg (7.284%) ( Table 1). tRNA Leuc , tRNA Ser , and tRNA Arg encode six different isoacceptors which might be the reason for their higher abundance in the plant genomes.
Suppressor tRNA (0.036%) was found to be the least abundant tRNA isoacceptor in the plant genomes, followed by tRNA Sec (0.066%), tRNA His (2.109%), and tRNA Cys (2.547%) ( Table 1) The genome-wide analysis of the Plant Kingdom revealed the diversity in the number of anti-codons present in the genomes of individual species, which ranged from 18-59 (Table 2). Ostreococcus tauri was found to encode only 18 isoacceptors while Micromonas commoda encodes only 26 isoacceptors ( Table 2). Ipomoea nil, Papaver somniferum, and Zea mays encoded the highest number of anti-codons at 59 each. At least 51 (39.53%) species were found to encode 50 or more anti-codons in their genome.
On average, plant genomes encode 48.25 anti-codons per genome. A paired two tailed t-test was conducted to statistically analyse the frequency of anti-codons present in algae, eudicot, and monocot species. The comparison between eudicot and monocot species indicated that the frequency of tRNA anti-codons in these two groups was not signi cantly different (P < 0.05) at 1.2691 < 1.984 (t-test result 1.2691, critical value T 1.984), respectively (Table 3). In contrast, a signi cant difference in tRNA frequency was observed between eudicots and algae (10.3939 > 1.987), and between monocots and algae (6.2914 > 2.037) ( Table 3). Notably, the variance in tRNA frequency in the monocot lineage was much lower than it was in the eudicots and algae.
Only a few species have lost tRNA genes Our analysis revealed that a few species have lost the presence of speci c tRNA genes (tRNA isotype) in their genome. These species include Coccomyxa subellipsoidea (tRNA Tyr (Table 2). These species were found to lost the mentioned gene(s) in their genome. Understanding the loss of tRNA genes and its functional implication in protein translation is very crucial.

Some plant species encode tRNA Sec in their genomes
Several plant species were found to encode tRNA genes for selenocysteine amino acids. More speci cally, 22 (17.187%) species were found to encode a tRNA Sec gene in their genome. These species were Aegilops tauschii, Beta vulgaris, Brassica rapa, Cucumis sativus, Cucurbita maxima, Cucurbita moschata, Cucurbita pepo, Ectocarpus siliculosus, Ipomoea nil, Ipomoea triloba, Lactuca sativa, Momordica charantia, Medicago truncatula, Monoraphidium neglectum, Nicotiana tabacum, Papaver somniferum, Picea glauca, Populus euphratica, Salvia splendens, Tarenaya hassleriana, Triticum urartu, and Zea mays ( Table 2). The length of tRNA Sec encoding genes was ranged from 70 to 90 nucleotides with average length being 72.93 nucleotides per tRNA. A multiple sequence alignment of tRNA Sec genes indicated the presence of a conserved G-x-C nucleotide at the 30 th and 32 nd positions and a conserved U-C-A at 34 th , 35 th , and 36 th positions (Supplementary Figure 1). The pseudo-uridine loop was also found to contain a conserved G-U-U-x 2 -A-x 2 -C nucleotide consensus sequence (Supplementary Figure 1). The tRNA Sec in C. maxima (NW_019272053.1), however, was found to encode a C-U-U nucleotide sequence instead of a G-U-U conserved consensus sequence in its pseudo-uridine loop (Supplementary Figure 1).
Loss of tRNA Sec occurred to a greater extent than duplication A phylogenetic tree was constructed to investigate the evolution of tRNA Sec genes by considering the nucleotide sequences of all the 20 tRNA genes along with tRNA Sec genes. The phylogenetic tree revealed the 28 major tRNA groups ( Figure 3). The tRNA Sec genes were clustered in the middle of the phylogenetic tree and tRNA Sec was found to be present in at least six different clusters ( Figure 3). A few tRNA Sec genes were grouped with tRNA Lys (CUU), tRNA Asn (GUU), tRNA Arg (UCG, CCG), tRNA Gly (UCC), and tRNA Trp (CCA) ( Figure 3). The analysis indicates that tRNA Sec is distributed in different clusters in the phylogenetic tree.
This explains the role of duplication events in the evolution of tRNA Sec genes. Therefore, an analysis was conducted to investigate the deletion/duplication events related to tRNA Sec genes. As a result, we found that tRNA Sec deletion events occurred more frequently than duplication events. A total of 45 duplications, 119 deletions, and 9 co-divergent events were identi ed within 68 tRNA Sec genes found in 22 species  Figure 3) and less than a MYA in the case of the tRNA Sec in P. somniferum. The tRNA Sec in P. somniferum was found to arise from a duplication event. The recent divergence time for the tRNA Sec in P. somniferum indicates that this gene has undergone a recent duplication event.
tRNA Sec underwent a switch in anti-codons during evolution tRNA genes undergo rapid changes during the course of their evolution to meet translational demand.
Therefore, an attempt was made to better understand the role of tRNA Sec genes in plant evolution. It is well known that the tRNA Sec gene is encoded by a UCA anti-codon and that this gene was found in different clusters in the phylogenetic tree of tRNAs. An anti-codon switch occurs more frequently with a nucleotide sequence of a tRNA gene with a different anti-codon than with a gene with a similar anticodon [51]. Therefore, the possibility of anti-codon switch in tRNA Sec gene was examined. tRNA Sec grouped with tRNA Lys (CUU), tRNA Asn (GUU), tRNA Arg (UCG, CCG), tRNA Gly (UCC), and tRNA Trp (CCA). The UCA anti-codon of tRNA Sec was replaced by CUU in tRNA Lys and in tRNA Asn it was replaced by GUU where the 2 nd and 3 rd nucleotide of the anti-codons were constant. In tRNA Arg and tRNA Gly , the UCA anti-codon of tRNA Sec was replaced by UCG and UCC where the 1 st nucleotide of the anti-codons remained constant and the 2 nd and 3 rd anti-codons were variable. For the CCG anti-codon of tRNA Arg and the CCA anti-codon of tRNA Trp , the 1 st nucleotide of U(CA) of tRNA Sec was replaced with a C nucleotide and the 3 rd nucleotide remained variable.

Statistical Analysis
The varied number and frequency of anti-codons led us to understand whether or not a dataset is approximately normally distributed. Therefore, we conducted normal probability plot study of anti-codon numbers ( Figure 6). The normal probability plot correlation coe cient was 0.9632. the correlation coe cient and an approximately straight line indicate that normal distribution was good for the dataset ( Figure 6). Ordinary linear t least square regression model of anti-codon numbers was conducted to nd the best t for a set of data by minimizing the sum of the offsets or residuals of points from the plotted curve and to understand the behaviour of dependent variables (Supplementary Figure 4). The method estimates the relationship by minimizing the sum of the squares in the difference between the observed and predicted values of dependent variable con gured as a straight line. At 95% signi cance and intercept at zero, the slope was found to be 34.621 (Supplementary Figure 4). The statistical result of the ordinary least square regression was; t=10.728, standard error a = 3.227, and p(slope)=6.161E-16. For 95% bootstrap con dence interval (N=1999); correlation r=0.00916, r 2 =8.3917E-05, t=0.072713, p(uncorr)=0.94226, and pemutation p=0.9404. the residual standard error of estimate was 147.

Discussion
tRNA is an adaptor molecule that becomes charged when it binds an amino acid and subsequently donates it to an elongating peptide chain as determined by a codon-anti-codon recognition system. Each tRNA contain a characteristics anti-codon sequence which dictates the translation of a mRNA sequence into a protein. In some cases, the same codon can get decoded by different tRNA species and the same tRNA species can also become decoded by different codons due to wobble interactions (Watson-Crick base pairing) at the rst position of an anti-codon and third position of the codon [26][27][28]. In our analysis of 128 species of the plants, none were found to encode all 64 anti-codons, which suggests that wobble base pairing exists in all plant species. The wobble interaction occurs at the G:U (guanine-uracil) base pairing and modi cations in anti-codons that change the speci city of a codon [57][58][59]. Due to this redundancy, it is not necessary for a plant genome to encode all of existing anti-codons and utilize different tRNAs according to the requirement. The presence of only 29 anti-codons in the genome of Klebsmordium nitens and 31 anti-codons in Bathycoccus prasinos, however, are somewhat very interesting. Species K. nitens and B. prasinos belonged to the phylum algae and the genome sizes of these species are much smaller than the genome sizes found in gymnosperm and angiosperms. The absence of a greater number of anti-codons in these species suggests that the rate of wobble basepairing might be quite high in these species. Mohanta et al., (2020) reported that species of cyanobacteria possessed 32 to 43 anti-codons per genome [20]. Cyanobacterial genomes are smaller than genomes of alae and higher plants [60]. The absence of a greater number of anti-codons in species with smaller genome is directly related to a higher frequency of wobble base-pairing. Ipomea nil (59), Ipomea triloba (58), Papaver somniferum (59), Cucurbita pepo (56), and Zea mays (59) possess a high number of anti-codons and so the occurrence of wobble base pairing may be quite minimal in these species. It will be interesting to determine the factors responsible for the occurrence of high and low frequencies of wobble base-pairing. Zhang et al., (2013) reported that the presence of high concentration of amino acids in the nutrient media led to higher rate of mismatch incorporation of amino acids into the translating protein chain [61]. They also reported that wobble codon position is less stringent in base pair mismatch and base change in 3 rd position explained additional 25% misincorporation either by favourable G mRNA /U tRNA mismatch or wobble position mismatch [61]. The G/U mismatch was predominant during the codon recognition and which is commonly found in the nucleic acid secondary structures as well [62][63][64].
The abundance of the CAU anti-codon that encodes tRNA Met was the greatest among all of the anticodons (Supplementary File 1). Methionine is used to initiate the start of a polypeptide chain, and as a result, almost all proteins require a methionine amino acid. Therefore, the abundance of an anti-codon for tRNA Met was found to be the highest. Additionally, tRNA Met (CAU) was found to have evolved earlier than other tRNAs during the course of evolution [18,19]. If the abundance of isoacceptors is considered, tRNA Leu , which contain six isoacceptors (GGA, AGA, CGA, UGA, ACU, GCU), has the highest abundance (7.808% of the collective plant species). Similarly, tRNA Ser , and tRNA Arg , both with six isoacceptors, have a high percentage of anti-codon abundance. This nding led us to conclude that, the higher the number of isoacceptors for tRNA isotypes, the greater the level of anti-codon sharing in a genome. The study also reveals that plant genomes encode tRNA Leu , tRNA Ser , and tRNA Arg more frequently than other tRNAs. A proteome-wide analysis by Mohanta et al., (2019) reported a higher abundance of Leu amino acids in the proteomes of the Plant Kingdom [65]. This observation directly corroborates that the number and abundance of tRNA Leu genes in genome is directly proportional to the number of Leu amino acids in the proteome. In contrast, a few anti-codons, including GCG, GAG, GGG, GGC, ACU, ACC, UCA (Sec) (group E) of different tRNA isotypes were found to have a low abundance (Figure 2). Yona et al., (2013) reported that multiple copies of rare tRNAs are deleterious to a cell [51]. They also stated that the effective gene copy number of each tRNA anti-codon set can undergo changes during evolution that may be due to the changes in demand-to-supply [51]. A single point mutation in an anti-codon can change one tRNA to another. The lowest encoding anti-codon GCG of tRNA Arg may have undergone a point mutation resulting in tRNA Arg with ACG, CCG, and UCG, which avoids the deleterious effect of the GCG anti-codon. Previous studies have also noted that rare tRNAs may be essential for co-translational folding as low abundance could provide a pause in translation [44,66].
When plants grow in a multitude of environmental conditions, environmental stress can induce the expression of genes needed for stress adaptation, which may affect codon usage by the transcriptome. This leads to a demand for a different pool of tRNAs to support the change in codon usage and avoid a translational imbalance [52,67]. If the altered environmental conditions persist, the tRNAs have to undergo changes in their level of expression to meet and respond to the environmental stress-induced changes in gene expression. If the changes in supply-demand continue, it may lead to changes in the genetic pool of the tRNAs that are bene cial and favoured by selection pressures. These novel translational demands can be maintained by shifting nucleotides in the anti-codons rather than by the duplication of genes. The tRNA pool can evolve to maintain the translational requirement by adjusting the number and/or ratio of tRNA isotypes encoding the same amino acid. An anti-codon switch, however, can also dramatically change the ratios of tRNA isoacceptor within a tRNA pool. This can be done by increasing the copy number of one isoacceptor at the expense of others. The high sequence similarity of different anti-codons (anti-codon switch) can be the result of purifying selection that maintains sequence similarity. Sequence similarity, however, can result from concerted evolution that maintains sequence similarity through frequent recombination among members of the same gene family [68,69]. The presence of a high level of recombination in tRNAs indicates that the evolution of plant tRNAs for anticodon switch and sequence similarity may be due to concerted evolution. A single point mutation in an anti-codon can result in the encoding of a different tRNA family. It would be interesting to understand the evolutionary constraints that lead to the generation of more members while others have fewer members.
It has been previously reported that tRNA Leu encodes a higher number of tRNA genes in the genome, a feature that is directly related to the higher number of tRNA isoacceptors in tRNA Leu [17][18][19][20]. The question remains if purifying selection plays a role in maintaining a low level of certain tRNAs, such as tRNA Sec , tRNA His , tRNA Trp , and tRNA Tyr . It is plausible that this purifying selection might be responsible for maintaining the anti-codons of these tRNAs at non-optimal levels. A previous study reported that increasing the copy number of a low copy tRNA gene family in a cell results in proteotoxic stress due to problems in protein folding [51]. In addressing the need for environmental adaptation, tRNA isotypes provide evolutionary plasticity to changes in translational demand due to their presence as a multimember gene family. A few species have lost tRNA genes for particular tRNA isotypes and anti-codon switch/point mutations of anti-codons may be a factor that contributes to maintaining the function of a genome in the complete absence of a particular gene family.
Selenocysteine (a selenium containing cysteine analog) is co-translationally inserted in a small fraction of proteins (selenoproteins) and is driven by a tRNASec gene. Although Sec is found in all three domains of life, it is not universal. Approximately 20% of the prokaryotic genome contains selenoproteins, while in eukaryotes selenoproteins are reported to be more concentrated in the metazoan lineage [70][71][72][73]. The absence of selenoproteins in fungi and land plants has also been reported previously [74]. and results from a lack of a tRNA Sec gene in their genomes. tRNA Sec is encoded by a UGA anti-codon which also encodes a stop codon. A highly sensitive and e cient method of tRNA identi cation is needed to nd tRNA Sec . The lack of suitable identi cation techniques may be the main reason for stating the absence of tRNA Sec genes in fungal and plant genomes. Using current technology, however, we were able to identify tRNA Sec , as well as tRNASec genes in a few of the genomes of the analysed plant species.

Conclusion
The repertoire of tRNA has a signi cant impact on the tness of an organism. The frequency (abundance) of anti-codons that explains synonymous codon usage in coding genes, however, has remained unexplored. Anti-codon frequency can be directly attributed to the frequency of synonymous codon usage and an anti-codon table of the Plant Kingdom, along with the percent abundance of each anti-codon, can be very helpful for understanding the relationship between codon and anti-codon frequency in the genome. The 21 st amino acid, selenocysteine, encoded by tRNA Sec has undergone a duplication event along with an anti-codon switch. Understanding the mechanisms involved in the loss of tRNA genes in a few species may be crucial to deciphering the translation mechanism in these species. The frequency of the anti-codons GCG (Arg), GAG (Leu), ACU (Ser), GGG (Pro) were very low in abundance and appear to be the rarest form of anti-codons in the Plant Kingdom. Yona et al., (2013) reported that multiple copies of rare tRNAs are deleterious to a cell [51], which suggests that large copy numbers of CGC, GAG, ACU, and GGG anti-codons may be deleterious to plant cells. Therefore, a very low number of these anti-codons are encoded in the plant genome. A few species have completely lost speci c tRNA isotype genes in their genome. Additionally, a previous also reported the loss of tRNA genes in some plant genomes [75]. All the studied data were taken from publicly available databases and data associated with the manuscript is provided in supplementary le.

Competing of interest
There is no competing of interest to declare   Tables   Table 1 Anti-codon table of the plant kingdom with frequency of anti-codons.  Table 2 Genomic details of plant anti-codons. Phylogenetic tree of tRNASec and other tRNA isotypes. The phylogenetic tree with 21 tRNA isotypes revealed at least 28 major phylogenetic groups where tRNASec (red) was placed with different tRNA isotypes. The phylogenetic tree indicates that tRNA has most likely evolved from multiple common ancestors and has also undergone duplication. The evolutionary history was inferred using the Maximum Likelihood method based on the Kimura 2-parameter model. The tree with the highest log likelihood (-7466.51) is illustrated. The percentage of the branches in which the associated taxa cluster together is shown next to the branches. Initial tree(s) for the heuristic search were automatically obtained applying the Neighbor-Join and BIONJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with a superior log likelihood value. A discrete Gamma distribution was used to model evolutionary rate differences among the sites [5 categories (+G, parameter = 2.6875)]. The tree is drawn to scale, with branch lengths representing the number of substitutions per site. The analysis utilized 702 nucleotide sequences. All positions with less than 95% site coverage were eliminated. Fewer than 5% alignment gaps, missing data, and ambiguous bases were allowed at any position. Evolutionary analyses were conducted in MEGA7 [2].

Figure 4
Recombination events in tRNA isotypes. Results indicated that tRNAs haves undergone dynamic recombination events during the course of evolution. The recombination study was conducted using IcyTree software using a nwk le format obtained from the phylogenetic tree.

Figure 5
Recombination events in tRNASec genes. Results indicate that tRNASec have undergone recombination events within themselves as well during evolution. The recombination study was conducted using IcyTree using the nwk le format of the phylogenetic tree of the tRNASec.

Figure 6
Normal probability plot of anti-codon numbers of the plant kingdom with correlation coe cient 0.9636 suggesting the datasets are normally distributed.

Supplementary Files
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