International Research Journal of Biological Sciences ___________________________________ ISSN 2278-3202Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 50 Comparative study of Glycerate Kinase (GK): Bioinformatical ApproachMondal Sunil KantiNeogi Chandra and Choudhury Kuntal Department of Biotechnology, The University of Burdwan, Golapbag, Burdwan, 713104, West Bengal, INDIAAvailable online at: www.isca.in, www.isca.me Received 1st August 2013, revised 12th September 2013, accepted 7th October 2013Abstract There are three classes of Glycerate kinase (GK) which are class I GK, class II GK and class III GK. Class I and class II GKs produce glycerate 2-phosphate whereas class III GK (GLYK) only can produce glycerate 3-phosphate. Phylogenetic analysis on 16S ribosomal RNA sequences reveals the strong evolutionary relationship between cyanobacteria and plants. Phylogeny using GK DNA and amino acid sequences shows that cyanobacteria group is closely related with both bacteria and plants whereas fungi are closely related only with plants. Phylogeny using the amino acid sequence and hierarchical clustering on the basis of the amino acid frequencies of GK shows similar relationship among the taxa. Hierarchical clustering on the basis of GC% of GK encoding gene showing the unusual property like the RSCU value of the codons UUG and AGG are significantly low and CGA is significantly high in GC rich cluster. Correlation coefficient between GC% and the amino acids arginine, tryptophan and serine shows that the plants are different from the other selected species. ENc plot shows that except few GK genes from fungi and gammaproteobacteria all of them are under mutational bias. There is no as such codon usage similarity for the GK encoding gene from different organisms but they have similar degree of expression i.e, CAI (highest in plant) which is significantly low along with the amino acids lysine, phenylalanine, tyrosine, isoleusine and asparagine and serine in GC rich GK encoding gene. Keywords: CAI: Codon Adaptation Index; ENc: Effective number of codon; RSCU: Relative Synonymous Codon Usage. Introduction There are variety of D-glycerate forming pathway which reflect the existence of three classes of glycerate kinases (GK) which are phylogenetically distinct. In bacteria (e.g. E coli) with one reported exceptionthe Class I GKs are thoughtto produce glycerate 3-phosphate (3PGA) in bacterial glucarate and glycolate metabolism3,4. But recently seen that class I GKs in glucarate and glycolate metabolism5 producing only glycerate 2-phosphate (2PGA) not 3PGA. Class II GKs form 2PGA in Archae by sugar degradation via non-phosphorylating branch of Entner–Doudoroff pathway and in animals by serine degradation and fructose metabolism. Functionally defective human GK causes a hereditary disease D-glyceric aciduria. Class III GKs is known as GLYK and only enzyme which form 3PGA and it is one of the essential core enzymes which catalyses the terminal reaction of the photorespiration cycle in plants. Photorespiration also occurs in cyanobacteria like filamentous Nostoc sp. strain PCC 71205 whichare the close relatives of endosymbiontic plastid ancestor10 but surprisingly some unicellular cyanobacteria such as Synechocystis sp. strain PCC 6803 have class I GK's. The enzyme GLYK purified from Saccharomyces cerivisiae11 and some plants12 but recently identified in the genome of Arabidopsis thaliana where GLYK is positioned at the end of the chromosome 1 right arm comprising 11 exons and 1368 bp open reading frame corresponds to a protein of 456 amino acids. The protein also includes chloroplast transit peptide (cTP) of 118 amino acids and ATP/GTP binding site and also identified two highly specific domains GLYK -1domain found in GLYK and its homologous proteins of plant or non plant. But GLYK- 2 domain is specific for plant and yeast and absent in cyanobacteria. The present study deals with the characterization of the GK based on amino acids frequency, encoding codons RSCU, genes GC%, evolutionary pattern of the genes in prokaryotes (proteobacteria and cyanobacteria) and eukaryotes (fungi and plants). An extensive analysis have been done to reveal the compositional variation and similarity (GC content, amino acid frequency and codon bias) and also to understand the mutational pressure on the GK genes.Material and MethodsCollection of Data: Taxonomic and other related information of 145 organisms were collected (46 proteobacteria spp., 33 cyanobacteria spp., 52 fungi spp. and 11 plant spp.) and their nuclieotide sequence, amino acid sequence, 16S ribosomal RNA sequence and also GK gene and protein sequence collected from KEGG database (www.genome.jp/kegg/) and from NCBI. Evolutionary Analysis: We have generated thousand time boot strapped phylogenetic tree13,14 using ClustalW15-17(www.ebi.ac.uk/tools/msa/clustalw2), PHYLIP version 3.6918,19,20 and Tree view software19 of nucleotide sequence, 16S rRNA sequence and amino acid sequence of GK. Compositional Analysis: The parameters like GC content, amino acid frequencies and RSCU (Relative Synonymous International Research Journal of Biological Sciences ________________________________________________ ISSN 2278-3202 Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 51 Codon Usage) were used for compositional analysis. We have generated GK encoding genes GC1%, GC2%, GC3%, A3%, U3%, Nc22 and gravy score using codonW and inhouse PERL script. The GC1%, GC2%, GC3% of the organisms was collected from Codon Usage Database. We have also calculated amino acid frequency of GK protein, RSCU values of all codons encoding GK protein using in house or home based PERL programme. These provided useful information regarding existence of mutational pressures acting on the genes23. ENc, the expected effective number of codon were calculated from GC3s under H0 (Null hypothesis, i.e., no selection) according to the given equation, where S denotes GC3. Enc=2+S+ {29/[ S2 + (1-S) 2]} (1) RSCU, the relative synonymous codon usage values close to one indicates lack of biasness where as much higher and lower values indicate preference and avoidance of those particular codons, respectively. Using codonW, the correspondence analysis24 has been performed to investigate major trend in RSCU variation among genes and distribute the genes along continuous axes in accordance with these trends also we have calculated gravy score to know about the hydrophobicity / hydrophilicity of the protein. Hierarchical Cluster Analysis: Hierarchical clustering based on gene GC%, amino acid frequencies and RSCU of GK were generated using programme DIANA of the package cluster of R-Statistical software25,26. Expressional Probability: The geometric mean of the weight associated to each codon over the length of the gene sequence (measured in codons) is known as Codon Adaptatation Index (CAI) i.e. the measure of gene’s probable expression. We have calculated it by following Sharp and Li method27 and using inhouse PERL script and MS Excel 2007. Statistical Analysis: We have calculated correlation coefficient and RSQ values between GC content and amino acids frequencies of GK in different groups by using MS excel 2007. Another statistical significance (z) test was performed based on GC1%, GC2%, GC3%, GC%, G3%, C3%, A3%, U3%, CAI and all amino acids of GK protein sequence and GK encoding nucleotide sequence for different situations: i. between high and low GC poor clusters for the same genus, ii. within GC rich cluster for genus to genus, iii. within GC poor cluster for genus to genus (clusters were obtained through hierarchical clustering on the basis of GC% of the GK encoding gene) and iv. within the population (organism set considered for this study) for genus to genus. Z i = (AVERAGE –AVERAGE )/((STDEV+STDEV)/(Na + N)) (2) Here, i denotes the parameter, a and b denotes the genus and N indicates the sample size. Results and DiscussionPhlogenetic Analysis: Phylogenetic tree (figure - 1A) on the basis of 16s ribosomal RNA sequences showning that the species of the plant group are related closely. Then the plant group clustered with cyanobacteria group more closely than gammaproteobacteria and alphaproteobacteria groups.Phylogenetic tree on the basis of GK amino acid sequence shown in figure - 1B also have two main clusters, in the first one chlorophyta group and streptophyta group are clustered closely and these two groups at first clustered with fungi group and then with cyanobacteria and some organisms of alphaproteobacteria group. Second cluster formed between gammaproteobacteria and other organisms of alphaproteobacteria group denoting their close relation with each other. Phylogenetic tree on the basis of GK encoding DNA sequence shown in figure - 1C have two major clusters, in first cluster some organisms belong to fungi group clustered closely with some organisms of cyanobacteria group then this two clustered with some organisms of gammaproteobacteria group and with some other organisms of cyanobacteria, fungi and streptophyta group. In second cluster some organisms of cyanobacteria group clustered closely with some organisms of gammaproteobacteria group and this two groups clustered at first clustered with alphaproteobacteria group and then with the other organisms gammaproteobacteria and cyanobacteria groups and then this two clusters joined with the major number of organisms of fungi group. Compositional Variability: Hierarchical clustering on the basis of GC%, amino acid frequencies and RSCU values of codons in GK encoding DNA sequence gives the similar variation. The relation obtained through hierarchical clustering on the basis of the amino acid frequencies shows that fungi, chlorophyta and streptophyta are closely clusterd with some organisms of cyanobacterial group. The other organisms of cyanobacterial group are separately clustered with alphaproteobacteria and gammaproteobacteria groups. Statistical significance test (at P0.05) shows (table - 2) that within the GC (60% ± 7%) rich cluster (Cluster IandII in figure - 2A) the parameters like: CAI, K, F, Y, M, I, N and S of the GK encoding gene are significantly low where as the parameters like: R, W, P, G, A, V, Q are significantly high for all genus (with some non significance like CAI, W and Q in FA and V in PG) than the GC (40% ± 7%) poor cluster. In the GC rich cluster, the parameters C, H, T are significantly high in CY and low in PG and within FA, C is high and E is low than the GC poor cluster but D has no significant variation. International Research Journal of Biological Sciences ________________________________________________ ISSN 2278-3202 Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 52 Table–1 List of organisms selected to study GK HC Organisms Full Name PC HC Organisms Full Name PC HC Organisms Full Name PC 1 Chlamydomonas reinhardtii cre_CL 137 Teredinibacter turnerae ttu_ PG 25 Prochlorococcus marinus MIT 9211 pmj_CY 95 Caulobacter sp. K31 cak_PA 33 Synechococcus sp. PCC7002 syp_ CY 17 Nostoc punctiforme PCC 73102 npu_CY 130 Pseudoxanthomonas spadix psd_PG 127 Nitrosococcus watsonii nwa_PG 47 Botryotinia fuckeliana bfu_FA 106 Sphingobium japonicum sjp_PA 41 Aspergillus fumigatus afm_FA 108 Alteromonas sp. SN2 alt_PG 43 Ashbya gossypii (Eremothecium gossypii) ago_FA 111 Alteromonas macleodii Deep ecotype amc_PG 112 Alteromonas macleodii English Channel 673 amg_PG 105 Sphingobium chlorophenolicum sch_PA 113 Alteromonas macleodii Black Sea 11 amk_PG 109 Alteromonas macleodii ATCC 27126 amac_PG 134 Stenotrophomonas maltophilia K279a sml_PG 126 Nitrosococcus oceani noc_ PG 122 Marinomonas mediterranea mme_PG 135 Stenotrophomonas maltophilia R551-3 smt_PG 38 Phytophthora infestans pif_ EK 91 Zygosaccharomyces rouxii zro_FA 114 Stenotrophomonas maltophilia JV3 buj_PG 119 Marinobacter adhaerens mad_PG 117 Glaciecola sp. 4H-3-7+YE-5 gag_PG 96 Caulobacter crescentus CB15 ccr_PA 55 Cyanidioschyzon merolae cme_FA 53 Coccidioides immitis cim_FA 97 Caulobacter crescentus NA1000 ccs_PA 64 Lachancea thermotolerans lth_ FA 51 Cryptococcus gattii cgi_FA 104 Phenylobacterium zucineum pzu_PA 57 Cryptococcus neoformans JEC21 cne_ FA 128 Pseudoalteromonas atlantica pat_PG 98 Caulobacter segnis cse_PA 44 Aspergillus niger ang_ FA 142 Zea mays (maize) zma_ST 107 Sphingomonas wittichii swi_PA 138 Oryza sativa japonica (Japanese rice) dosa_ST 66 Moniliophthora perniciosa mpr_FA 144 Arabidopsis thaliana (thale cress) ath_ST 56 Cryptococcus neoformans B-3501A cnb_ FA 110 Alteromonas macleodii Balearic Sea AD45 amb_PG 49 Coprinopsis cinerea cci_FA 82 Sordaria macrospora smp_FA 42 Aspergillus flavus afv_FA 46 Aspergillus oryzae aor_FA 87 Ustilago maydis uma_FA 116 Frateuria aurantia fau_PG 67 Myceliophthora thermophila mtm_FA 2 Ostreococcus lucimarinus olu_ CL 121 Methylophaga sp. JAM7 mec_PG 101 Novosphingobium sp. PP1Y npp_PA 141 Sorghum bicolor (sorghum) sbi_ ST 143 Vitis vinifera (wine grape) vvi_ST 14 Gloeobacter violaceus PCC7421 gvi_CY 145 Brachypodium distachyon bdi_ EK 124 Marinomonas posidonica mpc_PG 100 Hyphomonas neptunium hne_PA 71 Nectria haematococca nhe_ FA 58 Coccidioides posadasii cpw_FA 136 Stenotrophomonas maltophilia D457 smz_PG 6 Anabaena sp. PCC7120 ana_ CY 21 Prochlorococcus marinus MIT 9303 pmf_CY 34 Synechococcus sp. RCC307 syr_CY 74 Penicillium chrysogenum pcs_ FA 84 Sclerotinia sclerotiorum ssl_FA 54 Clavispora lusitaniae clu_FA 132 Pseudoxanthomonas suwonensis psu_ PG 77 Phaeosphaeria nodorum pno_FA 12 Cyanothece sp. PCC 8801 cyp_CY 60 Debaryomyces hansenii dha_ FA 27 Prochlorococcus marinus MIT 9313 pmt_CY International Research Journal of Biological Sciences ________________________________________________ ISSN 2278-3202 Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 53 HC Organisms Full Name PC HC Organisms Full Name PC HC Organisms Full Name PC 36 Synechococcus sp. WH7803 syx_CY 89 Vanderwaltozyma polyspora vpo_ FA 73 Paracoccidioides brasiliensis pbl_ FA 35 Synechococcus sp. WH8102 syw_CY 139 Medicago truncatula (barrel medic) mtr_ ST 75 Puccinia graminis pgr_ FA 81 Schizophyllum commune scm_FA 7 Anabaena variabilis ATCC 29413 ava_ CY 39 Arthroderma benhamiae abe_ FA 4 Volvox carteri f. nagariensis vcn_CL 15 Microcystis aeruginosa NIES-843 mar_CY 63 Laccaria bicolor lbc_ FA 92 Asticcacaulis excentricus aex_PA 62 Kluyveromyces lactis kla_ FA 86 Trichophyton verrucosum tve_ FA 3 Ostreococcus tauri ota_CL 140 Glycine max (soybean) gmx_ST 61 Fusarium graminearum fgr_ FA 120 Methylococcus capsulatus mca_PG 16 Anabaena azollae 0708 naz_ CY 79 Pyrenophora teres pte_ FA 29 Synechococcus sp. CC9605 syd_CY 99 Hirschia baltica hba_ PA 85 Tuber melanosporum tml_ FA 65 Magnaporthe oryzae mgr_FA 123 Marinomonas sp. MWYL1 mmw_PG 13 Cyanothece sp. ATCC 51142 cyt_ CY 28 Synechococcus elongatus PCC6301 syc_CY 118 Glaciecola nitratireducens gni_PG 37 Trichodesmium erythraeum IMS101 ter_ CY 31 Synechococcus elongatus PCC7942 syf_CY 131 Pseudoalteromonas sp. SM9913 psm_PG 20 Prochlorococcus marinus NATL1A pme_CY 90 Yarrowia lipolytica yli_ FA 10 Cyanothece sp. PCC 7822 cyj_ CY 26 Prochlorococcus marinus NATL2A pmn_CY 40 Aspergillus clavatus act_ FA 70 Neosartorya fischeri nfi_ FA 18 Prochlorococcus marinus AS9601 pmb_CY 80 Saccharomyces cerevisiae (budding yeast) sce_FA 93 Alpha proteobacterium HIMB59 apc_ PA 94 Alpha proteobacterium HIMB5 apm_PA 68 Neurospora crassa ncr_FA 83 Schizosaccharomyces pombe (fission yeast) spo_ FA 102 Candidatus Pelagibacter sp. IMCC9063 pel_ PA 72 Podospora anserina pan_FA 78 Pichia pastoris ppa_ FA 19 Prochlorococcus marinus MIT 9515 pmc_CY 5 Acaryochloris marina amr_CY 76 Meyerozyma guilliermondii pgu_ FA 22 Prochlorococcus marinus MIT 9301 pmg_CY 88 Uncinocarpus reesii ure_FA 129 Pseudoalteromonas haloplanktis TAC125 pha_ FA 23 Prochlorococcus marinus MIT 9215 pmh_CY 125 Nitrosococcus halophilus nhl_PG 8 Cyanothece sp. PCC 7424 cyc_ CY 24 Prochlorococcus marinus MIT9312 pmi_CY 133 Saccharophagus degradans sde_PG 52 Candida glabrata cgr_ FA 103 Candidatus Pelagibacter ubique pub_PA 11 Cyanothece sp. PCC 7425 cyn_CY 69 Naumovozyma castellii ncs_ FA 48 Candida albicans cal_ FA 45 Aspergillus nidulans ani_ FA 9 Cyanothece sp. PCC 8802 cyh_CY 50 Candida dubliniensis cdu_FA 30 Synechococcus sp. CC9902 sye_CY 115 Colwellia psychrerythraea 34H cps_ FA 59 Candida tropicalis ctp_ FA 32 Synechococcus sp. CC9311 syg_CY *H.C.: Code number used in Hierarchical Clustering; #P.C.: Code used in Phylogeny P.C.: triple letter code from KEGG _ genus (chlorophyta (CL-plant), streptophyta (ST-plant), cyanobacteria (CY), gammaproteobacteria (PG), alphaproteobacteria (PA), fungi (FA). International Research Journal of Biological Sciences ________________________________________________ ISSN 2278-3202 Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 54 Table-2 Score of different genomic and proteomic parameters of the GK encoding gene from CY, FA, PG, PL (plant). Z – score which are greater/less than ±1.96 (at P0.05) are significant and marked as bold. Positive significant values indicating that the parameters are high/greater in GC rich cluster than GC poor cluster for the respective (same) genus in column no. II to IV and the parameters of the first genus are high/greater than the later genus within the corresponding cluster/population in the rest columns V to XV Parameters/ Sample/ Genus Combinations Between high and low cluster GC HIGH CLUSTER GC LOW CLUSTER Population CY FA PG CY FA CY PG FA PG CY FA CY PG FA PG CY FA CY PG FA PG PL CY PL FA I II III IV V VI VII VIII IX X XI XII XIII XIV XV GC1% 13.53 11.38 10.65 1.16 -1.82 -3.12 -3.07 -4.29 -0.67 -2.83 -3.22 -1.21 3.88 2.47 GC2% 14.12 12.99 9.16 0.92 -2.47 -3.75 -2.61 -6.3 -3.78 -2.6 -4.36 -2.74 4.47 3.43 GC3% 13.1 11.6 9.5 0.21 -2.46 -3.09 -3.69 -5.23 -1.58 -3.62 -4.02 -1.5 4.56 2.69 GC 14.25 12.67 10.45 0.98 -2.15 -3.39 -3.31 -5.48 -1.81 -3.01 -3.74 -1.69 4.38 3.02 G3% 10.6 6.93 6.84 0.92 -0.3 -1.16 -3.34 -2.71 0.49 -3.14 -2.4 0.26 3.8 2.17 C3% 12.81 11.13 8.12 -0.96 -3.71 -3.91 -3.03 -5.73 -2.82 -3.54 -5.02 -2.69 4.66 2.46 A3% -11.78 -10.52 -7.58 -3.63 -0.17 2.76 -0.54 2.24 3.29 -0.08 1.57 1.96 -4.11 -5.36 U3% -9.59 -7.95 -8.54 3.91 4.22 2.86 5.95 5.32 -1.1 6.69 5.77 0.74 -4.14 0.19 CAI -2.15 -0.68 -6.61 0.25 2.78 2.67 1.62 -4.17 -5.07 1.56 0.88 -0.31 2.83 3.78 asp(D) -1.02 -1.79 -0.78 0.22 0.39 0.31 -0.32 0.47 0.87 -0.43 1.42 1.95 -0.11 -0.35 glu(E) -1.54 2.11 -0.74 -5.02 -1.28 3.2 -2.29 -0.94 1.42 -5.48 -1.4 3.83 0.9 -4.05 his(H) 1.39 1.59 -2.72 -3.91 -1.51 1.61 -3.71 -6.35 -3.04 -6.22 -5.41 -0.55 2.08 -2.28 lys(K) -12.08 -9.14 -10.81 -9.23 -0.17 7.42 0.21 2.06 3.03 -1.29 1.75 3.91 1.44 1.2 arg(R) 8.98 8.78 9.59 1.51 -2.18 -4.25 -1.07 -0.64 0.38 -1.2 -2.06 -1.45 0.69 -0.22 phe(F) -5.58 -4.37 -7.63 -4.83 -1.17 3.79 -0.07 -0.87 -1.23 -1.38 -0.67 0.62 0.17 -0.88 tyr(Y) -5.97 -4.33 -7.77 -10.93 -2.72 10.5 -6.39 -3.42 3.98 -9.98 -2.99 6.57 8.09 0.65 trp(W) 2.58 0.23 3.01 13.94 7.72 -5.93 10.22 7.24 -4.24 16.87 10.75 -7.11 -9.88 3.94 pro(P) 6.56 6.47 5.49 4.81 1.52 -1.83 2.69 2.11 -0.59 3.21 1.68 -1.02 -2.01 -0.04 cys(C) 5.95 -1.93 -3.95 7.95 5.52 -1.36 -1.35 -3.84 -3.95 2.59 -0.42 -4.16 -0.47 1.79 met(M) -3.22 -5.36 -1.22 1.76 -1.09 -3.1 0.12 -0.38 -0.5 1.72 -0.44 -1.66 2.37 3.76 gly(G) 3.94 3.45 3.79 -0.84 3.13 5.19 -2.35 3.14 6.33 -3.52 3.98 8.77 0.69 -1.55 ala(A) 10.54 8.81 6.89 1.89 -4 -5.9 0.06 -5.19 -5.88 0.05 -5.78 -6.63 2.95 3.56 val(V) 3.53 5.29 -0.73 -7.09 -3.21 3.8 -5.3 -7.33 -2.06 -8.93 -8.5 1.16 6.92 0.91 ile(I) -11.32 -7.77 -5.61 1.05 2.97 3.03 4.05 7.57 3.01 4.28 6.53 3.19 -5.11 -2.1 leu(L) -0.13 -0.69 7.75 12.67 0.99 -9.98 10.97 9.01 0.51 17.9 6.46 -4.83 -13.76 -2.68 gln(Q) 3.76 0.87 2.24 4.84 0.45 -4.21 0.29 -1.34 -2.61 2.9 -1.22 -5.26 -4.03 -3.7 asn(N) -6.28 -8.12 -5.82 -6.73 -1.91 4.44 -0.16 2.58 5.33 -0.65 2.07 4.35 -0.35 -1.36 ser(S) -2.29 -4.46 -8.55 1.01 3.12 3.31 0.91 0.15 -1.24 1.77 2.69 1.63 0.06 1.83 thr(T) 2.22 0.37 -3.34 -3.72 -1.09 1.99 -5.35 -6.15 -2.61 -6.98 -6.05 -0.88 4.25 -2.21 International Research Journal of Biological Sciences ________________________________________________ ISSN 2278-3202 Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 55 Except G3% and D in GC high cluster and D, R, F, M and S in GC low cluster and Dand F in selected organism set for the GK encoding gene the rest calculated parameters were significantly varied from genus to genus. Z-test on the basis of the parameters also showing that GK’s from plant is closer to fungi than cyanobacteria and CAI is highest in plant. Table - 3 depicting that RSCU of the codons within GK having G or C in third position are high in GC rich clusters (IandII in figure - 2B and I in figure - 2C) and low in AT rich clusters (IIIandIV in figure - 2B and IIandIII in figure - 2C) with some exceptions like: the RSCU value of the codons UUG(L) and AGG(R) are significantly low and CGA(R) is significantly high in GC rich cluster. Correlation coefficients of Gene GC% with amino acids frequencies: Figure - 3 showing that within GK the amino acids like aspartate(D) and glutamate(E) are significantly negatively correlated with GC% in chlorophyta and significantly positively correlated in alphaproteobacteria. Arginine(R) and tryptophan(W) are negatively correlated with GC% in chlorophyta, and streptophyta, and positively correlated to GC% in cyanobacteria, fungi, alphaproteobacteria and gammaproteobacteria whereas serine(S) is negatively correlated with GC% in cyanobacteria, fungi, alphaproteobacteria and also in gammaproteobacteria and positively correlated in chlorophyta and streptophyta. Tyrosine(Y) is only positively correlated with GC% in streptophyta among the six groups whereas isoleusine(I) is only positively correlated with GC% in chlorophyta. Cystein(C), valine(V), glutamine(Q) and threonine(T) are the amino acids present in GK have no significant relation with GC% within these six groups. Within GK the other amino acids like proline(P) and leucine(L) significantly positively correlated with GC%. Glycine(G), alanine(A) significantly positively correlated with GC% except streptophyta. Lysine(K), phenylalanine(F) significantly negatively correlated with GC%. Methionine(M) and asparagine(N) significantly negatively correlated with GC% except streptophyta. Expressional Variability: Correspondence Analysis: Figure - 4A showing that there is no as such codon usage similarity for the GK encoding gene from different organisms / genus. Fungi is separated from cyanobacteria and proteobacteria gamma along the first major axis (axis1), thereby depicting the difference in codon usage pattern. ENc plot analysis: The ENc plot analysis (figure - 4B: ENc/Nc ploted against (G+C)) used to search patterns of synonymous codon usage which shows that except some organisms from fungi group like Arthroderma benhamiae, Cryptococcus gattii, Cryptococcus neoformans JEC21, Paracoccidioides brasiliensis, Phaeosphaeria nodorum, Pyrenophora teres, Schizosaccharomyces pombe (fission yeast) and Trichophyton verrucosum and few from gammaproteobacteria group like Alteromonas sp. SN2 and Colwellia psychrerythraea 34H all of them are under mutational bias. Figure- 1A, 1B, 1C Phylogenetic trees based on 1A: 16s ribosomal RNA sequences; 1B: GK amino acid sequences; 1C: GK encoding DNA sequences International Research Journal of Biological Sciences ________________________________________________ ISSN 2278-3202 Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 56 Figure- 2A, 2B, 2C Dendograms based on 2A: total guanine and cytosine percentage in GK gene (GC%); 2B: amino acid frequencies of GK protein (Gene amino acid); 2C: RSCU values of the codons of GK encoding gene International Research Journal of Biological Sciences ________________________________________________ ISSN 2278-3202 Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 57 Figure-3 Correlation and RSQ of amino acids frequencies with total guanine and cytosine percentage in GK encoding gene (GC%) in different genus Figure-4A, 4B 4A: Correspondence analysis of the GK gene from the six groups based on its RSCU values; 4B ENc/Nc vs. GC plot of the GK gene from the six groups CAI and Gravy Score: For these selected genus the CAI is 0.5 and above (as shown in figure - 5A) which predicting the moderate degree of expression of GK encoding gene. In chlorophyta, streptophyta, cyanobacteria, alphaproteobacteria and gammaproteobacteria the gravy score of GK is around -0.3 and for fungi it is -0.45 (as shown in figure - 5B) which indicating that GK from fungi is more hydrophilic (due to negative gravy score) in nature than the GK’s from rest of the selected groups. International Research Journal of Biological Sciences ________________________________________________ ISSN 2278-3202 Vol. 2(12), 50-59, December (2013) Int. Res. J. Biological Sci. International Science Congress Association 58 Figure-5A, 5B Average and standard deviation of 5A: CAI and 5B: Gravy score of the GK encoding gene of the six groups ConclusionThe genomic and proteomic comparative study of GK from different groups of species highlighted few outcomes. First of all, the results show that GK and its encoding DNA sequences from plant species are similar to fungi and then to cyanobacteria in comparison to others. In addition to that the hierarchical clustering on the basis of different genomic and proteomic parameter of GK giving similar variation. The hierarchical clustering on the basis of the amino acid frequencies of GK shows similar relationship among the groups as obtained through phylogenetic study and some unusual property like the RSCU value of the codons UUG(L) and AGG(R) are significantly low and CGA(R) is significantly high in GC rich cluster. The correlation coefficient between GC% and the amino acids arginine, tryptophan and serine shows that the GK’s from plants are different from the other selected species. Enc plot shows that except few GK genes from fungi and gammaproteobacteria all of them are under mutational biasness. There is no as such codon usage similarity for the GK encoding gene from different organisms but they have similar degree of expression (highest in plant) which is low along with some amino acids K, F, Y, I, N and S in GC rich GK encoding gene. 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