Bioinformatic Characterization and Phylogenetic Analysis of Cold-Regulated Genes Across the Genus Eucalyptus

doi:10.21203/rs.3.rs-1558771/v1

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Research Article

Bioinformatic Characterization and Phylogenetic Analysis of Cold-Regulated Genes Across the Genus Eucalyptus

https://doi.org/10.21203/rs.3.rs-1558771/v1

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posted 14 Apr, 2022

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Cold or frost stress is one of the severest abiotic stresses which hinders the distribution, productivity and yield of Eucalyptus worldwide. Almost all aspects of cellular functions are affected under the exposure of cold stress. Being an economically important species, development of cold tolerance in Eucalyptus is very important. Different signalling cascades are known to be activated under cold stress. ICE1-CBF pathway is found to play master regulatory role in cold stress sensing pathways in majority of woody forest plants. In this study, across the genus Eucalyptus, 24 cold-regulated genes (CORs) are identified, divided in 3 gene families namely ICE, CBF and DHN, characterized by the presence of signature motifs and conserved domains in the sequences. Exhaustive location on chromosomes and sequences for these genes are acquired from several databases. These sequences are further analysed with several bioinformatic tools to establish evolutionary relationships among them. Predicted protein sequences from BLASTX are subjected to multiple sequence analysis and percentage similarity matrices are constructed with BLOSUM62. Phylogenetic trees for every gene family are developed using MEGA X using the Maximum Likelihood (ML) method and statistically validated through bootstrapping method. The analysis of these ICE, CBF and DHN genes directed towards cross-talk of different stress response pathways. Cluster of CBF genes are found in Eucalyptus resembling high similarity suggesting a major duplication event during the evolutionary track of this genus. The results of this study will prove to be beneficial in understanding the cold acclimation process and developing genetically improved cold tolerant Eucalyptus.

bioinformatics

cold acclimation

cold-regulated genes

Eucalyptus

freezing tolerance

phylogenetic analysis

Eucalyptus plays a significant role in world’s plantation forestry as a source of pulp for paper and aromatic oil for cosmetic industries. Eucalyptus, belonging to the family Myrtaceae, is the most widely planted forest tree in the world, occupying more than 20 million hectares of land globally (Iglesias and Wilstermann 2009). Eucalyptus is preferred as plantation crop due to its fast-growing habit and high yielding capacity with shorter rotation period than other trees. The Genus Eucalyptus is native to Australia and consists a genetic diversity of more than 700 species along with great intra-specific variation (Turnbull & Booth 2002). Although out of all the species, only 15 species of the genus Eucalyptus are of interest for commercial plantation forestry (Ginwal 2014). Wide adaptability to different agroclimatic zones and inherent tolerance to several biotic and abiotic stresses makes Eucalyptus a preferred species for plantation round the globe.

Eucalypts are known to adapt to various climatic conditions owing to its evolutionary pattern and exposure to wide climatic variations (Teulières et al. 2007). Majority of eucalypt species has shown high degree of tolerance to arid conditions. Eucalyptus shows very high light use efficiency in compared to other forest or plantation crops. Eucalypts can also survive in drained soil where water and nutrient supply is very less. Several species of Eucalyptus are found to be well tolerant to high temperature and drought. E. camaldulensis can tolerate upto 50°C whereas seedlings of E. obliqua are found to be able to survive at a temperature of as high as 80°C (Teulières et al. 2007). However, they are not at all suitable for regions receiving severe winter and frosts. Cold or frost stress is proved to be one of the most severe limiting factors in the expansion of Eucalyptus plantation worldwide. Researchers suggest that majority of eucalypts exposed to heat stress may be able to recover successfully under appropriate conditions, but are more prone to cold shocks and do not recover successfully after the cold stress (Souza et al. 2004). The naked buds and the leaves of eucalypts are the primary organs that is sensitive to frost and subjected to freezing. Although, some species are reported to perform quite well under cold stress. E. gunnii and E. pauciflora, mainly found in Tasmanian subalpine region, probably show the highest cold and frost tolerance (Teulières et al. 2007). The tolerance of these two species is probably the result of acclimation against cold stress. These two species are reported to successfully recover the damage perceived after the exposure to cold stress. However, the tolerance ranges only up to -14°C to -18°C. Beyond the temperature limit, recovery potential falls down drastically. E. grandis and E. globulus are the two most commercially planted species of Eucalyptus around the globe. Unfortunately, both of the species are highly frost sensitive and only been able to withstand the lowest temperature of -6°C to -8°C making them unsuitable for plantation in the provinces with higher latitude and altitude. Even occasional frost or low temperature during winters induces severe cold stress to majority of the eucalypts.

Fundamental studies of cold stress and tolerance in Eucalyptus involved in physical and biochemical analysis of accumulation of osmolytes in the stressed cells and correlative analysis of differentially cold tolerant genotypes in Eucalyptus (Teulières et al. 2007). These analyses were mainly carried out through studying the differences between cold acclimatised and non-acclimatised plant material after exposing them to cold or frost stress. Breeding techniques like hybridization proved to be more proficient in improvement of tree species, particularly for inducing tolerance against biotic and abiotic stresses. Genomic approaches are being developed for Eucalyptus since the last decade round the globe as an important tool to understand the cold and frost stress damage, tolerance and susceptibility to the stress and identify the candidate genes related to the cold stress mechanism in eucalypts. Global transcriptome analysis is providing a new horizon for in-depth characterisation of cold regulated genes. There have been many significant achievements recently in identifying the candidate genes related to cold and frost stress in eucalypts; but a major problem faced by the researchers is, many of the databases are owned by several private companies which is not openly accessible or available as public consortia (Azar et al. 2012). Limited available literatures reveal that the molecular studies on cold stress responses in the genus Eucalyptus are at very juvenile stage. Thus, there lies very exciting prospects of exploring the molecular mechanism of its unique developmental features. With the help of the mapping data of QTLs regulating cold tolerance, combining with the recent and rapid genomic achievements and exploration of EST collections, it can be predicted that new and more fruitful breeding and improvement programs against cold stress in the genus Eucalyptus will be deployed in very near future. Modern bioinformatics tools can be deployed for exploring the arena of cold stress studies of eucalypts for rapid improvement. In depth characterization for the genes that regulate cold stress and tolerance in eucalypts includes multi-dimensional studies including genomics, proteomics, transcriptomics and also the aid of bioinformatics. Researchers have already identified several genes involved in cold tolerance and acclimation process of eucalypts across the genus. cDNA libraries of several Eucalyptus species have been constructed as a first step for the identification. All these data acquired can be used to create a potential candidate gene pool which may be strongly related to the process of cold tolerance and acclimation in eucalypts.

This study presents a bioinformatic approach to analyze the cold-regulated genes (CORs) across three important eucalypt species i.e., Eucalyptus grandis, Eucalyptus gunnii and Eucalyptus globulus. With the help of available genomic eucalypt databases and several bioinformatic tools, an in-depth characterization of these genes and their translated proteins have been conducted along with predicting several signatory cis-regulating elements on the promoter sequences of these genes. Then phylogenetic analyses have been carried out to understand the evolutionary relationships among these genes across these species of Eucalyptus.

2.1. Exploration of the cold-regulated genes (CORs):

Review of the available literatures revealed that there are three major families of genes those play crucial roles in the cold stress pathways in the eucalypts as well as majority of woody forest tress namely ICE, CBF and DHN. These genes have been found to be overexpressed under cold stress and during cold acclimation process across the genus. The genomic sequence data for the ICE and CBF genes in E. grandis is recovered from EUCANEXT DATABASE (http://bioinfo03.ibi.unicamp.br/eucalyptusdb/) (Nascimento et al. 2017) and Phytozome 12 (https://phytozome.jgi.doe.gov/pz/portal.html) (Goodstein et al. 2012). The genomic sequence data for the CBF genes in E. gunnii and DHN genes in E. globulus have been recovered from NCBI Genbank (https://www.ncbi.nlm.nih.gov/genbank/). The protein coding sequences (CDS) for the genes are deciphered through searching the Open Reading Frames (ORFs) in NCBI ORFFinder (https://www.ncbi.nlm.nih.gov/orffinder/).

All the sequences of ICE, CBF and DHN genes are subjected to BLASTX in NCBI BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi) in order to get the translated protein sequences of the genes. The translated amino acid sequences are further checked for the conserved domains in their sequences through NCBI Conserved Domain Database (CDD) (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) (Lu et al. 2020). These conserved protein domains are used to identify the similar protein families in model herbaceous plant Arabidopsis thaliana through The Arabidopsis Information Resource (TAIR) (https://www.arabidopsis.org/index.jsp) (Berardini et al. 2015). The genes encoding these protein families in A. thaliana are extracted from TAIR and studied with the ICE, CBF and DHN genes in Eucalyptus for further analysis. A primary prediction for cis-regulatory elements on the promoter sequences of the genes is conducted with the help of the PLACE Database (http://www.dna.affrc.go.jp/PLACE) (Higo et al. 1999).

2.2. Multiple Sequence Alignment and Phylogenetic Analyses:

Multiple sequence alignments (MSA) are performed using the ClustalW 1.83 programme (Thompson, Gibson and Higgins 2003) with the corresponding A. thaliana orthologs in the GeneStudio Pro 2.2 software (Supplementary 1). Pairwise sequence comparisons are done by calculating percentage similarity matrices with BLOSUM62 matrix and constructing consensus sequence logos in the Geneious Prime 2021.1.1 software. For constructing the phylogenetic trees, model with the lowest Bayesian Information Criterion (BIC) Score is used. 500 bootstrap replications have been conducted during the construction of each phylogenetic tree to test the confidence or reliability of the branches of the constructed phylogenetic tree using Mega X 10.2.5 software. Every phylogenetic tree prepared to scrutinize the evolutionary history of the genes was inferred by using the Maximum Likelihood (ML) method (Kishino and Hasegawa 1989)

16 CBF genes from E. grandis, 1 ICE gene from E. grandis, 4 CBF genes from E. gunnii and 3 DHN genes from E. globulus have been mined from the published literatures as major cold-regulated genes (CORs) (Table 1). The ICE, CBF and DHN sequences from the eucalypt species mined from the published literatures were re-confirmed by identifying the known motifs of the proteins translated by the focused genes. Several authors have already predefined these protein motifs. ICE genes are defined as having a basic helix-loop-helix (bHLH) domain containing the ICE-specific sequence KMDRASILGDAIEYLKELL in the coding sequence region (Nakamura et al. 2011). Whereas, CBF genes are identified as those genes encoding proteins with the characteristic conserved signature of PKKP/RAGRxKFxETRHP and DSAWR motifs which surrounds the AP2/ERF DNA binding domains or in many cases a LSWY motif located at the C-terminus (Canella et al. 2010). On the other hand, DHN genes are identified through the presence of a highly conserved lysine-rich domain named the K-segment, generally located at the C-terminal end of the protein (Koag et al. 2009); often along with domains called the Y- and S-segments in the N-terminal part of the protein (Close, 1996). The K-segment is found to have at least one characteristic signature of EKKGIME/DKIKEKLPG (Yang et al. 2012) which can be repeated up to eleven times in the protein sequence translated by the gene (Svensson et al. 2002). These signature motifs were distinguishably found in the consensus sequence logos generated (Fig.1) which validated the conserved domains of the genes found through NCBI Conserved Domain Database (CDD). The conserved domains were also taken into consideration for selecting the Arabidopsis thaliana orthologs from TAIR. For ICE gene in E. grandis, six (6) A. thaliana orthologs (AT3G26744.1, AT2G16910.1, AT1G12860.1, AT1G10120.1, AT1G06170.1, AT1G01260.1); for CBF genes in E. grandis, one (1) A. thaliana ortholog (AT1G06160.1); for CBF genes in E. gunnii, four (4) A. thaliana orthologs (AT5G51990.1, AT4G25490.1, AT4G25480.1, AT4G25470) and for DHN genes in E. globulus, four (4) A. thaliana orthologs (AT5G58260.1, AT5G48950.1, AT1G60550.1, AT1G48320.1) were selected for the analysis. Interestingly, no particular conserved domain was found through NCBI CDD search for the EuglDHN10 gene, although multiple alignment was able to find conserved signature motifs in every identified DHN gene in E. globulus.

The cis-regulatory elements on the promoter sequences primarily predicts the noncoding DNA sequences in or near the genes containing binding sites for transcription factors required for proper spatiotemporal expression of the genes. Table 2 enumerates the cis-regulatory elements predicted on the promoter sequences of the cold-regulated genes in the genus Eucalyptus through the PLACE Database (http://www.dna.affrc.go.jp/PLACE) (Higo et al. 1999) for better identification and insight to the cold regulatory pathways. For the ICE gene in E. grandis (EgrICE1), signature cis-regulatory elements like MYC recognition sites (CANNTG) and MYB recognition sites (YAACKG, CNGTTR, AACGG) were identified. Several known cis-regulatory elements can be predicted in the promoter sequences (5’ upstream) of the CBF genes in both E. grandis and E. gunnii. Sequences homologous to MYB recognition sites (YAACKG, GGATA, AACCA), MYC recognition sites (CANNTG), ACGT-rich Abscisic acid responsive elements (ABRE) (ACGTGA, ACGTCCC, ACACNNG, TCCACGTCTC) are found in majority of eucalypt CBF genes (El Kayal et al. 2006). Noticeable similarity is inferred on promoter sequences of all the Eucalyptus CBF paralogs, particularly in terms of cis-regulatory elements. A detailed study on the cis-elements in the promoter regions of eucalypt CBF sequences is recently made available by Nguyen et al. (2017) which further validates the findings of this study. Similarly, a number of cis-regulatory elements can be identified in the promoter regions (5’ upstream) of the EuglDHN genes. Several Abscisic acid responsive elements (ABRE) containing ACGT rich regions (GGACACGTGGC, CACGTG, AGTACGTGGC, ACGTGGC) were found EuglDHN1 and EuglDHN2. All of three EuglDHN genes contain Sp1-box (CCG/ACCC) and G-boxes (CACGTT, TGACGTGG, CACGTC/G, ACACGTGT) involved in light responsiveness and photoperiod changes in E. globulus. Other additional regulatory elements like ACE (CTAACGTATT), ARE (TGGTTT), CRT (GGCCGACAT), circadian cycle related element (CAANNNNTC) etc. were identified in EuglDHN2 gene (Fernandez et al. 2012) suggesting that EuglDHN2 gene may be the most responsive and promptly expressed DHN gene in E. globulus during cold stress exposure and cold acclimation process. Translated protein analysis revealed that the ICE gene of E. grandis (EgrICE1) is located on chromosome 7 corresponding to amino acids with a molecular weight of ~60.167 kDa and a calculated isoelectric point of 5.77. 14 CBF genes (EgrCBF1 to EgrCBF14) are clustered on chromosome 1 (~117kb) where no other gene is found. EgrCBF15 is located on chromosome 4 and EgrCBF16 is located on chromosome 5. The CBF genes of E. grandis correspond to amino acids with a mean molecular weight of ~23.521 kDa and a calculated mean isoelectric point of 6.36. The CBF genes in E. gunnii correspond to amino acids with a mean molecular weight of ~23.873 kDa and a calculated mean isoelectric point of 5.88. Whereas, the DHN genes in E. globulus correspond to amino acids with a mean molecular weight of ~20.385 kDa and a calculated mean isoelectric point of 5.83. Although the chromosomal locations for the CBF genes in E. gunnii and DHN genes in E. globulus were not determined due to unavailability of the whole-genome sequencing for these two eucalypt species, the calculated mean molecular weight and mean isoelectric point values are at par with their evolutionary relationships revealed through phylogenetic analyses.

The percentage similarity matrices (Table 3-6) are calculated for each of the gene families with BLOSUM62 matrix by analyzing the amino acid substitution frequencies in clusters of the related protein translated by these gene families. The percentage similarity matrices primarily indicate the evolutionary relationships among the genes. Higher percentage of similarity between two genes corresponds that they are more closely related in terms of evolutionary divergence, which can be make sure of from the phylogenetic trees constructed.

During construction of the phylogenetic trees, the initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Jones-Taylor-Thornton (JTT) model (Jones, Taylor and Thornton 1992), and then selecting the topology with superior log likelihood value. The number of substitutions per site is calculated as the branch lengths of the phylogenetic trees which infers a great insight to the evolutionary history among the focused genes. The phylogenetic trees are prepared by using the Maximum Likelihood (ML) method which uses a variety of substitution models to correct for multiple changes at the same site during the evolutionary history of the sequences. The model with the lowest Bayesian Information Criterion (BIC) score has been considered to select the best fit substitution model during the constructions of each phylogenetic tree (Table 7). Bootstrapping is conducted with 500 replicates to reduce the sampling errors of the phylogenetic trees and assess the statistical confidence. Three assumptions for the sequences are made during the process, i.e. (i) same path of evolution for every concerned sequence, (ii) the branch lengths or distance measured in the original tree estimates the number of nucleotide substitutions in an unbiased manner, and (iii) the number of the sequences in the analysis are sufficiently large. A null hypothesis is formed for the bootstrap test that the branch length will differ from 0 at least when the Bootstrap Confidence Level (BCL) will be >0.9 (Hillis and Bull, 1993). The BCL shows a very good correlation with the calculated equivalent probability (CP) and branch length of a phylogenetic tree is considered statistically significant when the CP (or BCL in this case) value is high, generally >0.9.

The Phylogenetic analysis for ICE gene from E. grandis and its A. thaliana orthologs ivloved 7 amino acid sequences and there was a total of 812 positions in the final data set. The ICE gene in E. grandis, EgrICE1 is found to be more closely related to AT3G26744.1 and AT1G12860.1 than other A. thaliana orthologs owing to 69.7% and 59.1% similarity to AT3G26744.1 and AT1G12860.1 ortholog respectively (Fig. 2). Previous literatures divided the annotated AP2/ERF member genes in Eucalyptus into four subgroups i.e., DREB, ERF, AP2 and RAV subfamilies (Cao et al., 2014) according to the described similarity of the sequences of AP2/ERF domains in A. thaliana (Mizoi et al., 2012). The ERF subfamily represents the highest share (53.5%) in the whole AP2/ERF family of E. grandis. According to identity, EgrCBF genes can be divided into several subgroups where EgrCBF6-8-10-12 and EgrCBF7-9-11-13-14 show highest level of similarity (>95%) suggesting these CBF sequences are resulted from duplication of one ancestor gene (Fig. 3). Other small clades in the phylogenetic tree constructed represent EgrCBF1-2, Egr3-4-5 and Egr15-16. The phylogenetic analysis also confirmed that CBF genes in E. grandis show a greater conservation compared to the CBF genes in E. gunnii in terms of percentage similarity between different CBF genes. Among the E. grandis CBF genes, EgrCBF15 and EgrCBF16 gene encode the most distant proteins on the AP2-based phylogenetic tree and found to be more related to AtDDFs (AT1G12610, AT1G63030) of DREB subfamily (Cao et al., 2014) suggesting the crosstalk between different stress response pathways. The phylogenetics analysis for CBF genes from E. grandis and its A. thaliana orthologs involved 17 amino acid sequences and there was a total of 326 positions in the final dataset. The CBF genes found in E. gunnii are distinguishably distinct from each other and share less percentage similarity than that of E. grandis. It is found that the EguCBF1c gene is the most phylogenetically distant gene and AT5G51990.1 is the most closely related A. thaliana ortholog to E. gunnii CBF gene family (Fig. 4). The phylogenetics analysis for CBF genes from E. gunnii and its A. thaliana orthologs involved 8 amino acid sequences and there were a total of 244 positions in the final dataset. Interestingly, DHN genes in E. globulus shows very less values in percentage similarity (<40%) among each other, unlike other cold-regulated genes in other eucalypt species and phylogenetic analysis revealed EuglDHN10 is the gene encoding the most distant protein (Fig. 5). EuglDHN10 shares only 26.2% and 29.8% similarity to EuglDHN1 and EuglDHN2 respectively, which verifies the fact that no conserved domain was found for EuglDHN10 gene during NCBI CDD search. The phylogenetic analysis for DHN genes from E. globulus and its A. thaliana orthologs involved involved 7 amino acid sequences and there were a total of 396 positions in the final dataset.

Table 1: List of cold-regulated genes (CORs) in the genus Eucalyptus with their Genomic sequence size, CDS sequence size and Peptide sequence size

Sl. No.	Gene Name	Accession Number	Species Name	Genomic sequence size	CDS sequence Size	Peptide sequence size
1	EgrICE1	Eucgr.G01938	E. grandis	3837 bp	1683 bp	560 bp
2	EgrCBF1	Eucgr.A02818	E. grandis	1239 bp	690 bp	229 bp
3	EgrCBF2	Eucgr.A02820	E. grandis	1202 bp	591 bp	196 bp
4	EgrCBF3	Eucgr.A02821	E. grandis	456 bp	456 bp	151 bp
5	EgrCBF4	Eucgr.A02822	E. grandis	1394 bp	678 bp	225 bp
6	EgrCBF5	Eucgr.A02823	E. grandis	617 bp	573 bp	190 bp
7	EgrCBF6	Eucgr.A02824	E. grandis	636 bp	636 bp	212 bp
8	EgrCBF7	Eucgr.A02825	E. grandis	555 bp	555 bp	184 bp
9	EgrCBF8	Eucgr.A02826	E. grandis	636 bp	636 bp	212 bp
10	EgrCBF9	Eucgr.A02827	E. grandis	576 bp	576 bp	191 bp
11	EgrCBF10	Eucgr.A02830	E. grandis	747 bp	663 bp	220 bp
12	EgrCBF11	Eucgr.A02831	E. grandis	585 bp	585 bp	194 bp
13	EgrCBF12	Eucgr.A02832	E. grandis	588 bp	588 bp	195 bp
14	EgrCBF13	Eucgr.A02833	E. grandis	909 bp	522 bp	224 bp
15	EgrCBF14	Eucgr.A02834	E. grandis	978 bp	675 bp	224 bp
16	EgrCBF15	Eucgr.D01925	E. grandis	982 bp	723 bp	240 bp
17	EgrCBF16	Eucgr.E00529	E. grandis	1391 bp	870 bp	289 bp
18	EguCBF1a	DQ241820	E. gunnii	936 bp	663 bp	220 bp
19	EguCBF1b	DQ241821	E. gunnii	893 bp	675 bp	224 bp
20	EguCBF1c	EU794855	E. gunnii	1146 bp	690 bp	229 bp
21	EguCBF1d	EU794856	E. gunnii	1392 bp	591 bp	196 bp
22	EuglDHN1	JN052208	E. globulus	1575 bp	621 bp	205 bp
23	EuglDHN2	JN052209	E. globulus	2130 bp	774 bp	258 bp
24	EuglDHN10	JN052210	E. globulus	730 bp	294 bp	98 bp

Table 2: Mean molecular weight, calculated isoelectric point and predicted cis-regulatory elements on the promoter sequences of the cold-regulated gene families in the genus Eucalyptus

Gene families	Mean molecular weight	Calculated isoelectric point	*Predicted cis-regulatory elements on the promoter sequences*
ICE gene in E. grandis	~60.167 kDa	5.77	MYC recognition sites (CANNTG) MYB recognition sites (YAACKG, CNGTTR, AACGG)
CBF genes in E. grandis	~23.521 kDa	6.36	MYB recognition sites (YAACKG, GGATA, AACCA) MYC recognition sites (CANNTG) Abscisic acid responsive elements (ABRE) (ACGTGA, ACGTCCC, ACACNNG, TCCACGTCTC)
CBF genes in E. gunni	~23.873 kDa	5.88
DHN genes in E. globulus	~20.385 kDa	5.83	Abscisic acid responsive elements (ABRE) (GGACACGTGGC, CACGTG, AGTACGTGGC, ACGTGGC) Sp1-box (CCG/ACCC) G-boxes (CACGTT, TGACGTGG, CACGTC/G, ACACGTGT) ACE (CTAACGTATT) ARE (TGGTTT) CRT (GGCCGACAT) circadian cycle related element (CAANNNNTC)

Table 3: Percentage similarity matrix for ICE gene from E. grandis and the A. thaliana orthologs

	EgrICE1	AT3G26744.1	AT2G16910.1	AT1G12860.1	AT1G10120.1	AT1G06170.1	AT1G01260.1
EgrICE1	100
AT3G26744.1	69.7	100
AT2G16910.1	40.8	42.5	100
AT1G12860.1	59.1	70.9	41.4	100
AT1G10120.1	36.1	33.8	30.2	33.6	100
AT1G06170.1	37.7	39.7	33.8	36.9	28.5	100
AT1G01260.1	36.4	34.7	35.7	34.9	33	32.6	100

Table 4: Percentage similarity matrix for CBF genes from E. grandis and the A. thaliana orthologs

	EgrCBF1	EgrCBF2	EgrCBF3	EgrCBF4	EgrCBF5	EgrCBF6	EgrCBF7	EgrCBF8	EgrCBF9	EgrCBF10	EgrCBF11	EgrCBF12	EgrCBF13	EgrCBF14	EgrCBF15	EgrCBF16	AT1G06160.1
EgrCBF1	100
EgrCBF2	96.9	100
EgrCBF3	79.1	79.1	100
EgrCBF4	82.1	91.8	81.1	100
EgrCBF5	76	76	66.9	75.8	100
EgrCBF6	88.6	93.1	79.6	83	76.4	100
EgrCBF7	91.9	93	80	96.2	77.2	95.5	100
EgrCBF8	89.1	93.6	80.8	83.5	76.4	98.6	95.5	100
EgrCBF9	92.2	92.7	80.6	95.3	76.8	94.5	97.8	94.5	100
EgrCBF10	88.6	93.4	81.1	84.5	76.3	96.7	95.1	96.7	94.8	100
EgrCBF11	89.3	90.8	79.4	92.8	75.8	91.9	96.2	91.9	97.4	92.3	100
EgrCBF12	91.9	91.8	81.7	90.8	75.8	95.2	93.5	95.7	93.2	96.4	92.3	100
EgrCBF13	84.6	92.9	80.6	88.4	76.3	87.6	98.4	87.6	99.5	88.5	97.4	92.8	100
EgrCBF14	85.1	93.4	81.1	88.8	76.3	88.1	98.9	88.1	99	88.9	96.9	93.3	99.6	100
EgrCBF15	61.4	65	56.1	58.9	52.1	61.3	64.3	60.4	64	59.7	61.8	63.8	59.3	59.7	100
EgrCBF16	54.3	54.9	48.3	53.6	45	50.9	55.9	50.5	57.1	52.6	55.3	55.1	53.3	52.9	57.9	100
AT1G06160.1	41.7	43.1	35.9	40.1	39.9	40.1	43.2	39.7	44.2	38.5	43.6	41.9	40.9	41.3	49	45.5	100

Table 5: Percentage similarity matrix for CBF genes from E. gunnii and the A. thaliana orthologs

	EguCBF1a	EguCBF1b	EguCBF1c	EguCBF1d	AT5G51990.1	AT4G25490.1	AT4G25480.1	AT4G25470.1
EguCBF1a	100
EguCBF1b	88.4	100
EguCBF1c	86.5	83	100
EguCBF1d	91.8	92.3	92.9	100
AT5G51990.1	64.9	61.9	63.5	71.1	100
AT4G25490.1	63.4	64	62.9	70.1	79.1	100
AT4G25480.1	63.8	64.1	64.1	69.6	77.3	92.2	100
AT4G25470.1	63.8	64.6	62.9	69.6	79.6	91.7	91.7	100

Table 6: Percentage similarity matrix for DHN genes from E. globulus and the A. thaliana orthologs

	EuglDHN1	EuglDHN2	EuglDHN10	AT5G58260.1	AT5G48950.1	AT1G60550.1	AT1G48320.1
EuglDHN1	100
EuglDHN2	36.3	100
EuglDHN10	26.2	29.8	100
AT5G58260.1	25.8	29.5	12.7	100
AT5G48950.1	19.6	21.3	9.9	23.7	100
AT1G60550.1	28.1	29.2	19.5	23	35.5	100
AT1G48320.1	24.6	22.8	10.6	24.7	82.8	35.2	100

Table 7: Determination of the best fit substitution model for constructing the phylogenetic trees of the cold-regulated genes in the genus Eucalyptus with regard to A. thaliana orthologs

Phylogenetic tree for gene family	Model	*BIC*	*AIC*	*lnL*
ICE gene in E. grandis	Whelan And Goldman (WAG) + Frequency (F)	16784.71971	16594.761	-8266.090358
CBF genes in E. grandis	Jones-Taylor-Thornton (JTT)	7832.413	7634.786	-3785.099
CBF genes in E. gunnii	Jones-Taylor-Thornton (JTT)	4307.125	4230.922	-2101.339
DHN genes in E. globulus	Whelan And Goldman (WAG)	7577.605	7519.95	-3748.881
BIC - Bayesian Information Criterion value; AIC - Akaike Information Criterion value; lnL - Maximum Likelihood value

Cold or frost stress, being one of the most severe stresses that eucalypt species may be exposed to, rigorous study upon this is of prime importance. High level of heterozygosity of Eucalyptus genome and unavailability of whole genome sequences of a big number of eucalypt species has put a bar to analysis of the genotyping data for improvement purposes. Despite such difficulties, modern transgenic technologies and bioinformatic tools prove to be very powerful tool for deciphering the induced genes and the response pathways for different biotic and abiotic stresses. The analysis on cold-regulated genes (CORs) revealed good evidence of a distinctive pattern of evolution. The probable duplication event took place in the CBF group of genes is strikingly interesting which is considered to be still an ongoing process. It can be hypothesized that the duplication event may play a key role for the adaptive evolution of eucalypts across the globe in several eco-climatic regions. The major CBF cluster in E. grandis (EgrCBF1-14) involved in cold response has shown an accumulation of massive transcript which is a unique characteristic for the genus Eucalyptus and till date not found in any other forest crops. From this study it can be predicted that the ICE, CBF and DHN genes may have undergone transcriptional regulation divergence which opens up a further research possibility on sequence divergence analysis to envisage more functional characterizations of these cold-regulated genes in Eucalyptus.

Backed up by the bioinformatic tools, transgenic eucalypts can be a solution for improved cold tolerance, along with morphological developments for better yield. Recently the U.S. Department of Agriculture (USDA) approved “Arbogen”, a tree biotechnology company to trail on patented genetically modified Eucalyptus, aiming to transfer CBF genes under control of cold responsive novel dehydrin promoters. Unfortunately, such studies are scarce for the eucalypt species and hybrids designated best for plantation in Indian subcontinent. Lack of experimental and field data on cold stress studies hinders the detailed genomic studies upon Indian eucalypt species. As a future prospect, assessment and quantification of cold damage, expression profiling along with construction of detailed cDNA library for genes induced by cold stress exposure and characterization of those genes through molecular and bioinformatic tools can direct us towards identifying the most relevant candidate genes for improving cold or frost stress tolerance in Eucalyptus.

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Acknowledgements: The authors acknowledge the institutional supports provided by Forest Research Institute (FRI) and Indian Council of Forestry Research and Education (ICFRE).

Author contributions: The study is a part of the post-graduate thesis by the author Ayushman Malakar under the guidance of authors Santan Barthwal and Girish Chandra. All authors contributed to the study conception and design. Ayushman Malakar did the literature search, conducted the experiments and wrote the first draft of the manuscript. Santan Barthwal commented on previous versions of the manuscript and corrected the manuscript. Girish Chandra carried out the required statistical validations for the study. All authors read and approved the final manuscript.

Funding: No funding was received for conducting this study.

Competing Interests: The authors have no competing interests to declare that are relevant to the content of this article.

No competing interests reported.

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Bioinformatic Characterization and Phylogenetic Analysis of Cold-Regulated Genes Across the Genus Eucalyptus

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